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--- title: Susceptibility and Permissivity of Zebrafish (Danio rerio) Larvae to Cypriniviruses authors: - Cindy Streiff - Bo He - Léa Morvan - Haiyan Zhang - Natacha Delrez - Mickael Fourrier - Isabelle Manfroid - Nicolás M. Suárez - Stéphane Betoulle - Andrew J. Davison - Owen Donohoe - Alain Vanderplasschen journal: Viruses year: 2023 pmcid: PMC10051318 doi: 10.3390/v15030768 license: CC BY 4.0 --- # Susceptibility and Permissivity of Zebrafish (Danio rerio) Larvae to Cypriniviruses ## Abstract The zebrafish (Danio rerio) represents an increasingly important model organism in virology. We evaluated its utility in the study of economically important viruses from the genus Cyprinivirus (anguillid herpesvirus 1, cyprinid herpesvirus 2 and cyprinid herpesvirus 3 (CyHV-3)). This revealed that zebrafish larvae were not susceptible to these viruses after immersion in contaminated water, but that infections could be established using artificial infection models in vitro (zebrafish cell lines) and in vivo (microinjection of larvae). However, infections were transient, with rapid viral clearance associated with apoptosis-like death of infected cells. Transcriptomic analysis of CyHV-3-infected larvae revealed upregulation of interferon-stimulated genes, in particular those encoding nucleic acid sensors, mediators of programmed cell death and related genes. It was notable that uncharacterized non-coding RNA genes and retrotransposons were also among those most upregulated. CRISPR/Cas9 knockout of the zebrafish gene encoding protein kinase R (PKR) and a related gene encoding a protein kinase containing Z-DNA binding domains (PKZ) had no impact on CyHV-3 clearance in larvae. Our study strongly supports the importance of innate immunity-virus interactions in the adaptation of cypriniviruses to their natural hosts. It also highlights the potential of the CyHV-3-zebrafish model, versus the CyHV-3-carp model, for study of these interactions. ## 1. Introduction The zebrafish (Danio rerio) is a member of the family Cyprinidae. It is an extremely useful experimental subject due to its high fecundity and short generation time and is currently one of the most widely used laboratory animal model organisms. Also, its transparent larval stage is highly suited to in vivo imaging, making it particularly well suited to studying host-pathogen interaction, including during viral infection [1]. Furthermore, the availability of a well-annotated zebrafish reference genome [2] and large range of recombinant and mutant zebrafish lines [3] greatly facilitates investigations into gene function in various biological contexts. The zebrafish is known to possess a well-developed immune system, composed of both innate and adaptive immune responses [4,5]. Despite some notable differences and although sites of maturation differ [6], many mammalian immune system cell types have zebrafish counterparts [7,8]. Also, zebrafish orthologs of many (but not all) mammalian pathogen recognition receptors (PRRs), cytokines, adaptor proteins for signal transduction and other important components have been identified [6,9,10], indicating that zebrafish represent a relatively useful model for studying the mechanisms that vertebrates use to detect and respond to pathogen-associated molecular patterns (PAMPs). Although juvenile and adult zebrafish utilize both the innate and the adaptive branches of the immune system, the embryonic and larval stages rely solely on innate immunity, which is detectable and active on the first day of zebrafish embryogenesis, whereas the adaptive system is fully matured by 4–6 weeks post-fertilization [11,12]. During these early life stages, cellular immunity is mediated by myeloid cells only, with macrophages and neutrophils acting as the main effector cells [13,14]. As in mammals, the zebrafish antiviral response is orchestrated by type I pathogen induced interferons (IFNs). These are named IFNϕ1, IFNϕ2, IFNϕ3, and IFNϕ4 [15] (referred to hereafter by the respective gene symbols ifnphi1, ifnphi2, ifnphi3, and ifnphi4) and are structurally similar to mammalian type I (α and β) and type III (λ) IFNs. As in all vertebrates, type I IFNs in zebrafish induce the expression of antiviral genes broadly referred to as interferon stimulated genes (ISGs). However, the IFN response in zebrafish larvae is mediated solely by ifnphi1 and ifnphi3, with ifnphi2 being expressed only in adults and with ifnphi4 having little activity [16,17]. The zebrafish type II IFN family consists of two members, IFNγ1 and IFNγ2 which are also responsible for the induction of ISGs induced by type I IFNs [18]. Taken together, this indicates that the zebrafish represents a relevant and useful model for studying viral pathogenicity, vertebrate host immune response, and viral host-interactions. Strikingly, very few viruses are known to infect zebrafish naturally [19,20,21,22]. Moreover, despite the lower host temperature, several mammalian viruses can infect zebrafish under experimental conditions, with these hosts exhibiting varying degrees of susceptibility and permissivity to infection. This property has also been exploited to study human viruses such as influenza A virus, Chikungunya virus (CHIKV), herpes simplex virus type 1 (HSV-1) and human norovirus [23,24,25,26]. Moreover, infection of zebrafish has been explored in studying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [27,28]. Zebrafish can also be infected with several important fish viruses [29,30,31,32,33,34,35]. One of these, the spring viraemia of carp virus (SVCV), which is a rhabdovirus responsible for a highly contagious disease of the common carp (Cyprinus carpio carpio), has become one of the viruses most frequently used in infection models for studying the antiviral immune response in zebrafish larvae and adults [16,17,35,36,37]. Recent work by Rakus et al. [ 38] demonstrated that cyprinid herpesvirus 3 (CyHV-3) induces an abortive infection after intraperitoneal inoculation of adult zebrafish. CyHV-3 causes mass mortality in common carp and koi carp (Cyprinus carpio koi), resulting in massive economic losses [39]. CyHV-3 is a member of the genus Cyprinivirus in the family Alloherpesviridae, which consists of herpesviruses that infect fish and amphibians. In addition to CyHV-3, the genus Cyprinivirus contains two other economically important viruses: anguillid herpesvirus 1 (AngHV-1) and cyprinid herpesvirus 2 (CyHV-2) [40]. AngHV-1 infects the European eel (Anguilla anguilla), Japanese eel (Anguilla japonica), and American eel (Anguilla rostrata) [41]; CyHV-2 also infects goldfish (Carassius auratus) and the closely related Prussian carp (Carassius gibelio) and crucian carp (Carassius carassius) [42]. Like zebrafish, the natural hosts of CyHV-2 and CyHV-3 are also members of the family Cyprinidae. Cypriniviruses cause diseases only in their natural host species, which suggests the existence of restrictions related to host cell susceptibility (i.e., the ability to support virus entry) and host cell permissivity (i.e., the ability to support viral replication and the transmission of viable viral progeny to new cells, although the former may occur without the latter). Notably, experiments relying on infection of cell lines have demonstrated the ability of cypriniviruses to infect, even if inefficiently, cells originating from non-natural host species. Indeed, both CyHV-2 and CyHV-3 are capable of infecting cell lines derived from species within the family Cyprinidae that are not their natural hosts [39,42], with CyHV-3 already known to infect zebrafish cell lines [38]. Similarly, despite not naturally infecting species outside of the family Anguillidae, it has been demonstrated that AngHV-1 can infect at least one cell line derived from a member of the family Cyprinidae [43]. These data suggest that the ability of cypriniviruses to induce diseases only in their natural host species may be related to complex host-virus interactions downstream of host cell susceptibility. In the present study, we conducted an in-depth evaluation and comparison of AngHV-1, CyHV-2, and CyHV-3 in terms of their ability to infect zebrafish models both in vitro and in vivo. These experiments involved the exploitation of recombinant viruses expressing reporters, timelapse epifluorescence microscopy in vitro, live imaging and transcriptomics in vivo; and finally, the generation of CRISPR/Cas9 mutant hosts to investigate the potential modulation of zebrafish permissivity to infection. Our study strongly supports the importance of the innate immune response alone in clearing viral infection and emphasizes the high degree of adaptation that cypriniviruses have undergone to facilitate successful circulation within their respective natural hosts. It also highlights the potential value of the CyHV-3-zebrafish model versus CyHV-3-carp models to study the fundamental features of virus-host interactions. ## 2.1. Cells and Viruses The zebrafish embryonic fibroblast cells line (ZF4) [44] was kindly provided by Dr K. Rakus (Department of Evolutionary Immunology, Jagiellonian University, Poland) and cultured in advanced Dulbecco’s modified Eagle’s Medium/Ham’s F-12 (Gibco, New York, NY, USA), supplemented with $10\%$ foetal calf serum (FCS), $2\%$ penicillin–streptomycin (Sigma-Aldrich, St. Louis, MO, USA) and $1\%$ L-glutamine (Lonza, Basel, Switzerland). Cells were cultured at 25 °C in a humid atmosphere containing $5\%$ CO2. Eel kidney (EK-1) [45], Ryukin goldfish fin (RyuF-2) [46], and common carp brain (CCB) [47] cell lines were used to produce stocks of AngHV-1, CyHV-2, and CyHV-3, respectively. These cells were cultured as described previously [46,48,49]. Three previously described recombinant viral strains were utilized. The CyHV-3 FL BAC revertant ORF136 Luc strain (referred to as CyHV-3 Luc; GenBank accession KP343683.1) was derived from the CyHV-3 FL BAC plasmid and encodes a firefly (Photinus pyralis) luciferase (Luc2) reporter cassette driven by a human cytomegalovirus (CMV) promoter inserted between ORF136 and ORF137 [50]. The AngHV-1 Luc-copGFP and the CyHV-2 Luc-copGFP recombinant strains both encode the same reporter genes consisting of the Luc2 cassette and a copepod (Pontellina plumata) GFP (copGFP) cassette linked by a T2A sequence, driven by a eukaryotic translation elongation factor 1 alpha (EF-1α) promoter. To generate these recombinants, the dual Luc2/copGFP cassette was inserted in the region between ORF32 and ORF33 in the AngHV-1 UK parental strain genome (GenBank accession MW580855.1) [40] (Delrez et al., unpublished data) and in the intergenic region between ORF64 and ORF66 in CyHV-2 YC-01 parental strain genome (GenBank accession no. MN593216.1) (He et al., unpublished data) using homologous recombination in eucaryotic cells, as described previously [50]. In addition to the three recombinant strains described above, a fourth strain, expressing enhanced (EGFP), referred to as the CyHV-3 EGFP strain, was derived from the CyHV-3 Luc strain and constructed specifically for this study. Details relating to the generation and verification of this strain are provided in Methods S1. ## 2.2.1. Virus Infections ZF4 cells cultured in 24-well plates were mock-infected or infected at 24 hours (h) after seeding. Virus was diluted in 0.5 mL serum-free cell culture medium to provide a multiplicity of infection (MOI) of 3 plaque forming units (PFU)/cell. After incubating for 2 h, 1 mL fresh cell culture medium was added without removing the inoculum, and the cells were incubated at 25 °C with $5\%$ CO2. ## 2.2.2. Timelapse Imaging of Infected Cells At 24 h post infection (hpi), virus-infected ZF4 cells in 24-well plates were placed in an IncuCyte Zoom HD/2CLR microscopy system (Sartorius), which was maintained at 25 °C with $5\%$ CO2. Each well was imaged at 9 different fields of view every 2 h from 1–11 days post infection (dpi). Images were collected in phase contrast and in the green (GFP) channels. Each infection was done in triplicate wells. ## 2.2.3. Image Analysis Data from timelapse imaging of infected cells was analysed using the Fiji plugin TrackMate (v7.7.2) [51] to track fluorescent reporter expression from individual ZF4 cells infected with CyHV-2 or CyHV-3, and by extension, to identify cell infection and cell death events with respect to time. Image sequences containing 123 frames/field of view/well were generated using a series of images acquired from 1 to 11 dpi. Analysis was performed using the default settings with LoG Detector and Simple LAP Tracker. Additional parameters were adjusted empirically in order adequately to detect and monitor fluorescence from infected cells within frames (estimated object diameter: 28.6 pixels; quality threshold: 1). Data were exported in.csv format and imported into GraphPad Prism (v8.0.1) for further analysis and visualization. ## 2.3.1. Zebrafish Larvae Maintenance Wild-type (WT, +/+) AB strain adult zebrafish (Danio rerio) were obtained by natural spawning and maintained at 27 °C, on a $\frac{14}{10}$ h light/dark cycle. They were housed in the GIGA Zebrafish facility in Liège (Belgium) according to animal research guidelines and with the approval of the local ethical commission for animal care and use. Larvae were obtained by pairwise mating of adults in mating cages and maintained in petri dishes with standard embryo medium (E3) and incubated at 25 °C prior to use in experiments. ## 2.3.2. Inoculation of Larvae by Immersion Zebrafish larvae (3 days post-fertilization (dpf)) were placed in 24-well plates containing 1 mL E3 medium and either mock-infected or infected by immersion. For infection, virus suspensions were added to each well and mixed gently (final concentration: 4000 PFU/mL), and plates were incubated at 25 °C. ## 2.3.3. Inoculation of Larvae by Microinjection Borosilicate glass capillaries were loaded with 10 µL of medium containing virus suspensions (1.2 × 106 PFU/mL) and then connected to a FemtoJet microinjector (Eppendorf, Framingham, MA, USA) as described elsewhere [52]. After breaking the capillary tip, the pressure was adjusted to obtain droplets with a diameter of ~0.13 mm. Larvae (3 dpf) were anesthetized in a bath containing tricaine (0.2 mg/mL). The fish were positioned on a petri dish, and the surface of the dish was dried entirely in order to avoid drifting of the larvae during viral injections. In order to visualize the hearts of the larvae, the petri dish was placed under a binocular magnifier (LEICA MZ6) at 4x magnification and illuminated by an external light source (LEICA CLS 50X). The capillary was then manually inserted into the pericardial cavity and three pulses were performed to inject approximately 3 nL of virus suspension (infected fish) or 3 nL of PBS (mock-infected fish). After microinjection, the larvae were transferred into individual wells in a 24-well plate containing 1 mL E3 medium and incubated at 25 °C. ## 2.3.4. Epifluorescence Microscopy The progression of infection with recombinant viruses expressing fluorescent reporters was monitored using epifluorescence microscopy. This facilitated longitudinal observation of the same larvae at multiple timepoints. Prior to observation, larvae were anesthetized in a bath of E3 medium containing tricaine (0.2 mg/mL) and methylcellulose ($2\%$ w/v) in order to avoid drifting of larvae. Imaging of larvae was performed using a Leica DM2000 epifluorescence microscope at 5× and 10× magnification. After imaging, larvae were immediately transferred back to their individual wells and returned to the incubator. After the final observation timepoint, larvae were euthanized using an overdose of tricaine in E3 media (400 mg/L). ## 2.3.5. In Vivo Bioluminescent Imaging An in vivo imaging (IVIS) system (IVIS Spectrum, PerkinElmer) was used to detect bioluminescence in larvae infected with Luc2-expressing recombinant viruses, thus facilitating the monitoring and quantification of viral levels in vivo. At the time of imaging, larvae were anesthetized (as described for epifluorescence microscopy analysis), injected with ~3 nL of D-luciferin (15 mg/mL), and imaged 5 minutes (min) after injection. Images were acquired using the following settings: field of view A, small binning, automatic exposure time with a maximum of 1 min and a subject height of 0.30 cm. Unlike epifluorescence analysis, longitudinal monitoring of individual larvae was not possible due to the harmful effects of repeated D-luciferin injections in the same larvae. Relative bioluminescence intensities were analysed using Living Image software (v4.7.3). Regions of interest (ROIs) were drawn by manually outlining the larval body, and bioluminescence within the ROI was recorded in terms of mean radiance (photons/s/cm2/sr). ## 2.3.6. In Vivo Timelapse Imaging For time-lapse imaging, live larvae infected with CyHV-3 EGFP were imaged using a Zeiss Z1 light sheet microscope according to the protocol described elsewhere [53]. Briefly, larvae were embedded inside FEP tubes containing $0.1\%$ low melting point agarose and tricaine (55 µg/mL) and maintained at 27 °C. Z-stacks encompassing the entire head and heart regions were acquired every 10 min from 2 to 3 dpi and were used to generate a maximum-intensity projection video with ImageJ. ## 2.3.7. Ethics Statement The experiments performed in the present study did not require a bioethical permit as they involved the use of larvae before implementation of feeding. However, all experiments were designed and conducted in accord with the 3R rules and other bioethics standards. ## 2.4.1. Zebrafish Larvae Infection, Sampling and Lysis WT AB zebrafish larvae were inoculated with CyHV-3 EGFP (1.2 × 106 PFU/mL) or mock-infected with PBS via pericardial microinjection. The larvae were placed in 24-well plates with 1 mL E3 medium per well and incubated at 25 °C. Infected and mock-infected larvae were sampled at 1, 2 and 4 dpi (triplicates at each timepoint with 5 larvae pooled per replicate). Prior to sampling, larvae were euthanized using an overdose of buffered tricaine in E3 media (400 mg/L). Each replicate group of euthanized larvae was transferred immediately to 1.5 mL tubes, excess E3 medium was removed, and 700 μL QIAzol lysis reagent (Qiagen, Hilden, Germany) was added. Whole larvae were then completely homogenized in lysis reagent by passing the lysate through a 21 G needle 20 times using a 2 mL syringe. After homogenization, lysates were stored at −80 °C until RNA isolation. ## 2.4.2. RNA Isolation, Library Construction and RNA Sequencing Larvae lysates were thawed and incubated at room temperature for at least 5 min and 140 μL chloroform was added to each sample. Lysates were then vortexed for 15 s, incubated at room temperature for 3 min and centrifuged for 15 min at 12,000× g at 4 °C. After centrifugation, 240 μL of the aqueous layer was removed and 360 μL of $100\%$ ethanol was added with immediate mixing by pipetting. Samples were then added to RNeasy spin columns, and RNA was isolated using an RNeasy Mini Kit (Qiagen, Hilden, Germany) with on-column DNase treatment. RNA was eluted in 100 μL RNase-free water using two 50 μL elution steps, and split into smaller aliquots for storage at −80 °C. For each sample, a single aliquot was used to check the quality of RNA using an Agilent Bioanalyzer, ensuring that RNA integrity (RIN) values were at least 9.5 before proceeding. Samples were used as input for barcoded RNA-Seq library preparation using the TruSeq Stranded mRNA kit (Illumina), and libraries were sequenced using the Illumina NextSeq 500 System. ## 2.4.3. Bioinformatics Analysis Sequence reads were aligned to the zebrafish reference genome GRCz11 (Ref Seq: GCF_000002035.6) in order to generate gene expression data. The data were used to identify differentially expressed genes (DEGs) in infected samples relative to non-infected samples (defined as those with false discovery rate (FDR) adjusted p-values < 0.05). DEGs were analysed further to identify functional relationships, and expression data were analysed to identify gene-sets that were significantly enriched in infected samples relative to non-infected samples. A non-abbreviated summary of the bioinformatic analysis conducted in this study is provided in Methods S2. ## 2.5.1. Generation of Mutant Zebrafish Strains Using CRISPR/Cas9 The mut eif2ak2 (pkr)ulg025, mut pkzulg027, and mut eif2ak2 (pkr) L15-1 knockout (KO) zebrafish lines, hereafter referred to as the PKR-KO, PKZ-KO and PKR-PKZ-KO mutant strains, were generated by CRISPR/Cas9 technology as described previously [54,55,56]. The nls-zCas9-nls mRNA was synthesized by transcription of the plasmid pT3TS-nCas9n (Addgene #46757). First, WT strain AB zebrafish were used to generate the mutant strains PKR-KO and PKZ-KO (Figure 1a). To generate the PKR-KO and the PKR-PKZ-KO mutant strains, CHOPCHOP [57] software was used to design two single-guide RNAs (sgRNA) GAGCACTCACAGTGATGAACCGG and CCACCGTGAACAGGCATCT (PAM motifs are underlined) to target exon 2 of the WT eif2ak2 (or pkr) gene (NCBI/Entrez/GenBank Gene ID: 100001092) and exon 1 of the WT pkz gene (NCBI/Entrez/GenBank Gene ID: 503703), respectively (Figure 1a). sgRNAs were generated by in vitro transcription from oligonucleotide templates using the MEGAscript T7 transcription kit (Ambion) as described previously [58]. The DNA templates were prepared by annealing and filling two oligonucleotides containing the T7 promoter sequence and the target sequences as previously described [56]. One-cell stage zebrafish embryos were injected with approximately 1 nL of a solution containing 50 ng sgRNA and 300 ng nls-zCas9-nls mRNA. The efficiency of mutagenesis was checked by genotyping using heteroduplex migration assays after amplification of targeted genomic sequences. Founder embryos (F0 generation) carrying a germline mutation in eif2ak2 or pkz were raised to adulthood and outcrossed with WT fish to generate heterozygous F1 fish. Fish harbouring frameshift mutations were kept and used to raise F2 homozygous stable knockout lines. Subsequently, PKZ-KO mutant strain zebrafish were then used to generate the double KO PKR-PKZ-KO mutant strain by repeating the process used to generate the PKR-KO mutant strain (Figure 1a). These mutations all resulted in genes producing truncated proteins and were verified by PCR (Figure 1b). ## 2.5.2. Genotyping of Zebrafish Mutant Lines The genotyping of WT, PKR-KO, PKZ-KO, and PKR-PKZ-KO zebrafish was performed by polymerase chain reaction (PCR). In order to extract the DNA, two randomly selected zebrafish larvae (4 dpf) were euthanized per mutant line. Each larva was transferred to an Eppendorf tube containing 25 µL 50 mM NaOH, heated at 95 °C for 25 min, and cooled on ice for 10 min. Finally, 2.5 µL 1M Tris-HCl pH8.0 was added, and cellular debris was pelleted by brief centrifugation for 15 sec. DNA concentration was determined by measuring A260 (NanoDrop 2000, Thermo Scientific, Waltham, NJ, USA), and ~2.5 µL of the resulting lysate was used per standard PCR reaction with gene-specific primers (Table S1). PCR reactions consisted of 1× Thermopol buffer (New England Biolabs, Ipswich, MA, USA), 0.025 U/µL Taq Polymerase (New England Biolabs), 300 nM forward and reverse primers, and 60 nM dNTPs (total volume 25 μL). The cycling conditions were as follows: 95 °C for 2 min, 40 cycles of 45 s at 95 °C, 45 s at 60 °C, 20 s at 72 °C, and ending with 72 °C for 10 min. ## 2.5.3. Quantification of Viral Genome by TaqMan PCR Larvae were euthanized using an overdose of tricaine, transferred into RNAlater (Thermo Fisher, Waltham, NJ, USA) and stored at −20 °C. DNA was extracted from whole larvae with a DNeasy Tissue Kit (Qiagen, Hilden, Germany), and approximately 1 ng genomic DNA was used for each TaqMan PCR reaction. TaqMan qPCR reactions consisted of 1× IQ Supermix (Bio-Rad, Hercules, CA, USA), 200 nM forward and reverse primers, and 400 nM TaqMan probe (total volume of 25 μL). The primers and probes used are provided in Table S1. The PCRs were performed using a CFX96 Touch real-time PCR detection system (Bio-Rad, Hercules, CA, USA) with detection in the FAM channel. The cycling conditions were as follows: 95 °C for 15 min, 40 cycles of 15 s at 94 °C, and 60 s at 60 °C. Each sample was analysed in triplicate. Viral genome copies were normalized to zebrafish genome copies (internal control) by also amplifying zebrafish genomic DNA as described previously [59]. Viral and zebrafish (internal control) PCRs were performed in separate wells, but always on the same plates. Negative template controls and positive controls were included on each plate. Data were exported to Excel using CFX Manager v3.0 software (Bio-Rad, Hercules, CA, USA). Relative levels of viral genome copies were calculated using the 2−△△CT method as described previously [60]. ## 2.6. Statistical Analysis Each dataset was first tested for normality using the Shapiro–Wilk test, which was conducted as a stand-alone test or as part of a two-way ANOVA analysis of residuals implemented in GraphPad Prism (v8.0.1). The omnibus tests used were dependent on the outcome of the Shapiro-Wilk tests. For datasets exhibiting normal distribution, One-way ANOVA, Two-way ANOVA, or Two-way repeated measures (RM) ANOVA were used and implemented in GraphPad Prism. For datasets not exhibiting normal distribution, the Durbin test was used (PMCMR package v4.4 [61]), implemented in R (v4.2.0) [62]. The variables of interest relating to each of these tests and their significance are described in the text. Survival curves were compared using Logrank tests implemented in GraphPad Prism Post-hoc multiple comparisons between groups of interest were made using either the Sidak test (two groups) or the Tukey test (more than two groups) implemented in Graphpad Prism (in conjunction with ANOVA tests), for data exhibiting normal distribution. Multiple comparisons were made using Dunn’s pairwise test (FSA package v0.9.3 [63]) with Benjamini-Hochberg p-value adjustment done using the p.adjust function in R (in conjunction with the Durbin Test), for datasets not exhibiting normal distribution. For the purposes of visual clarity, only significant results from post-hoc multiple comparisons are indicated in each corresponding figure. The results of multiple comparisons tests are represented using the following symbols, * $p \leq 0.05$; $p \leq 0.01$; * $p \leq 0.001$; **** $p \leq 0.0001.$ ## 3.1. ZF4 Cells Express Low Susceptibility and Reduced or Even No Permissivity to Cyprinivirus Infection Leading to Abortive Infection of Cell Monolayers In this experiment we tested the susceptibility and permissivity of the ZF4 cell line to infection with AngHV-1, CyHV-2 and CyHV-3, using recombinant strains expressing green fluorescent proteins as reporters. Cells were monitored from 1 dpi onwards using epifluorescence microscopy. At 1 dpi, infected cells were observed, with much less AngHV-1 infected cells relative to CyHV-2 and CyHV-3. The amount of CyHV-2 and CyHV-3-infected cells increased from 1–4 dpi, while the amount of AngHV-1-infected cells decreased after 2 dpi (Figure 2). Syncytia formation, lysis plaques, or other cytopathic effects (CPE), were not observed in monolayers infected with CyHV-2 or CyHV-3. Together, these data revealed that ZF4 cells expressed some level of susceptibility to the cypriniviruses tested, no permissivity to AngHV-1 infection, and greatly reduced permissivity to CyHV-2 and CyHV-3 infection relative to typical observations in cells derived from their respective natural hosts that are routinely used for culture of these viruses. To further characterise the infection of ZF4 cells by the three cypriniviruses in a more quantitative manner, we utilized timelapse microscopy (Figure 3). ZF4 cells were infected, and the numbers of infected cells present with respect to time were tracked from 1–11 dpi as illustrated in Figure S2. Again, the number of AngHV-1 infected cells were low relative to CyHV-2 and CyHV-3 infections and did not increase over time. Consequently, AngHV-1 was excluded from further quantification analysis in vitro. None of the infections led to the formation of detectible CPE. We observed a steady increase in CyHV-2- and CyHV-3-infected cells from ~24–144 hpi, followed by a rapid clearance of both viruses from ZF4 monolayers (Figure 3). As evident in Figure 2, during the most rapid period of virus propagation within the monolayer (from ~24–144 hpi) the rate of CyHV-2 and CyHV-3 spread was not exponential (Figure 3), indicating poor replication efficiency within infected cells and/or reduced transmission of progeny virus to additional cells. In the CyHV-2-infected monolayers, the peak of infected cells occurred at 146 ± 4 hpi with a mean of 58 ± 7 infected cells observed per well (sum of nine different fields of view in each well, sums from three replicate wells used to derive mean). This peak occurred earlier in CyHV-3-infected monolayers at 124 ± 11 hpi with a mean of 59 ± 13 infected cells at this point. Overall, time postinfection was shown to have a significant effect on the number of CyHV-2 and CyHV-3-infected cells observed (Two-way RM ANOVA, p value < 0.0001), but there was no significant difference between the two viruses in this respect (Two-way RM ANOVA, p value = 0.3164) (Figure 3). However, from ~24–144 hpi, the mean number of infected cells tended to be higher in the CyHV-3-infected monolayer. For example, at 48 hpi there was a mean of 21 ± 6 CyHV-3-infected cells observed per well compared to a mean of 12 ± 3 CyHV-2-infected cells. From ~144–264 hpi, the number of infected cells evolved similarly for both viruses, with infected cell numbers decreasing steadily until the end of the experiment, representing the gradual clearance of infected cells from the monolayer (Figure 3). Notably this clearance was largely characterized by apoptosis-like morphological changes. These two time-ranges, i.e., ~24–144 hpi and ~144–264 hpi, corresponded to periods approximately before and after the peak of infected cells, respectively. Thus, we further scrutinized these two distinct periods separately in order to determine the extent of any differences between CyHV-2 and CyHV-3. After defining the timepoints corresponding to the latest infection peak in each replicate, we examined the two distinct periods of infection, comprised of viral propagation (pre-peak) and clearance (post-peak), by quantifying the appearance (beginning of infection) and disappearance (cell death) of infected cells (Figure 4). This revealed that infected cells appeared at a mean rate of 0.64 ± 0.05 cells per hour for CyHV-2 and 0.78 ± 0.13 cells per hour for CyHV-3 before the peak, with no significant differences between the two viruses in this respect (Two-way ANOVA, p value = 0.1704). It also revealed that a mean of 75 ± $4.16\%$ and 72 ± $8.89\%$ of newly infected CyHV-2 and CyHV-3 cells appeared before the peak of infection, respectively, in what appears to have been several waves of infection (Figure 4). For both viruses, in all replicates, an initial peak of infected cell appearance occurred at ~36 hpi, followed by a period of particularly low appearance of newly infected cells until after ~48 hpi. This may represent the transmission of the first generation of viral progeny to the second generation of infected cells (from ~24–36 hpi), and subsequent progeny to the next generation of infected cells (occurring after ~48 hpi). However, the low numbers of newly infected cells yielded from this transmission provides more evidence to support the possible inefficient replication and/or transmission of CyHV-2 and CyHV-3 between ZF4 cells (as observed in Figure 2). For both CyHV-2 and CyHV-3, a substantial amount of newly infected cells (25–$30\%$) appeared after the peak, even beyond 10 dpi, indicating that transmission of viral progeny was sustained into the later stages of the experiment. We have recently demonstrated that CyHV-3 virions lose infectivity rapidly in cell culture media (>$95\%$ by 24 h) [64], thus excluding the possibility that newly infected cells, particularly beyond 10 dpi, could have originated from the initial inoculum due to delayed viral entry into cells. It is also unlikely that we are observing delayed expression of viral genes, as all fluorescent reporters used in this experiment were driven by highly active constitutive promoters (CMV and EF-1α). Also, we reasoned that because cells expressing fluorescent reporters are actively cleared at increased rates and appear at decreased rates as the experiment continued, the outcome is distinct from that of spurious reporter expression (i.e., without expression of other viral genes, owing to integration of the expression cassette into the host cell genome), which should persist for longer without triggering cell death. Together, these observations indicated the occurrence of at least some viral progeny transmission to non-infected cells after an initial round of viral replication. However, as increase in the numbers of newly infected cells was not exponential, but linear, it indicated that efficient replication and/or transmission of CyHV-2 and CyHV-3 was very rare in ZF4 cells. Nonetheless, it provided evidence that ZF4 cells are transiently permissive to CyHV-2 and CyHV-3 infection. The observation of isolated infected cells without plaque formation indicated the absence of transmission via cell-cell contact. This may indicate a high degree of heterogeneity within ZF4 monolayers regarding susceptibility to these viruses, or very strong or fast innate responses in neighbouring cells. Within at least one permissive cell line, CyHV-3 cell-cell transmission may be greatly enhanced by syncytia formation (in particular with CyHV-3 FL strain derived recombinants, which we recently described [64]). However, we observed a notable lack of syncytia formation among CyHV-3-infected ZF4s, which may also contribute to reduced transmission via cell-cell contact. It is important to note that for all viruses used in this study, the use of a high MOI of 3 (although calculated in the context of permissive cell lines used for viral production), did not result in many initial infected ZF4 cells, indicating a general lack of cyprinivirus susceptibility among ZF4 populations. This may happen for many reasons, for example, a lack of optimum cell surface receptors, resulting in inefficient viral entry. Conversely, entry may occur, but the viral replication may not commence due to a lack of crucial cellular factors. The exact reasons for this remain speculative and are beyond the scope of this present study, but it provides an opportunity for further investigation via single cell sequencing analysis in the future. Notably, cell death before the infection peak was low with 74 ± $0.03\%$ and 74 ± $0.07\%$ of CyHV-2 and CyHV-3-infected cells dying after the peak, respectively. Therefore, the higher transmission, prior to the peak, was not reliant on the release of virions via infected cell lysis/death but rather on the normal mechanism of herpesvirus egress [65,66]. Programmed cell death prior to completion of the viral replication cycle in particular acts as an innate defence mechanism which infected cells can employ to reduce virus replication [67]. Indeed, this is what was observed post infection peak, with an increase in cell death correlating with a reduction in newly infected cells (Figure 4). We propose that relative to cells at the earlier stages of the experiment, both infected and uninfected cells present at later stages would have been subject to cytokine stimulation as part of the innate immune response. Even if such stimulation was transient, these cells (many of which may exhibit limited susceptibility to begin with) may have adopted a stronger antiviral-state at later stages of the experiment. In order to compare the virulence of CyHV-2 and CyHV-3 in ZF4 cells, we returned to the data Figure 3 and monitored all positive cells present at 120 hpi until their death, using this information to generate survival curves (Figure 5). This 120 hpi timepoint was selected, as it represented the earliest peak of infection out of the six that were defined in Figure 4, thus maximizing infected cell sample size while using a common timepoint for all groups. The median survival time for infected cells was 61 ± 3 h and 53 ± 12 for CyHV-2 and CyHV-3-infected groups, respectively. Although CyHV-2-infected cells tended to survive longer, there was no significant difference survival between the two groups (Log-rank Mantel-Cox test, p value = 0.0822). In the majority of cases, death events were morphologically consistent with apoptosis, i.e., cell shrinkage, membrane blebbing leading to the appearance of cell debris resembling apoptotic bodies [68,69,70]) (Figure 6a, top panel). However, the occurrence of apoptosis was not definitively confirmed by staining. We also observed another distinct type of cell death that was not morphologically consistent with apoptosis. In these cases, morphological features mostly included initial cell swelling, followed by cell shrinkage and an absence of cell debris resembling apoptotic bodies prior to disappearance of fluorescent signal (Figure 6a, bottom panel). This is somewhat morphologically consistent with necrosis, where cell-death is associated with membrane rupture and leaking of cytoplasmic contents [68,69,70]. Notably, necrosis can also be initiated in a highly regulated manner known as necroptosis, which acts as a back-up for apoptosis [71,72]. However, it was not possible to differentiate between necrosis and necroptosis based on our morphological observations alone, and as with apoptosis, neither were definitively confirmed via staining. In any case, the apoptosis-like form of cell death was observed to be the dominant form of death among infected cells (Figure 6b). However, there were differences between the two viruses in this respect (Two-way ANOVA, p-value = <0.0001), with the proportion of CyHV-3-infected cells undergoing apoptosis-like cell death being significantly lower (Figure 6b), possibly indicating that CyHV-3 may be more efficient at blocking this apoptosis-like death in ZF4 cells. There was no significant difference between the two viruses in terms of survival times (Two-way ANOVA, p-value = 0.1112). However, among CyHV-3-infected cells, those undergoing non-apoptosis-like death exhibited significantly longer survival times than those undergoing apoptosis-like death (Figure 6c). Previously, a separate study demonstrated that CyHV-3 could indeed infect ZF4 cells, with increasing viral RNA levels observed from 1–4 dpi, and an absence of CPE was also noted [38]. However, the viral dosages used were not directly comparable with this present study, and the possibility of viral clearance after 4 dpi was not investigated. In this present study, we monitored the progression of CyHV-3 infections for much longer (up to 11 dpi). Crucially, through the exploitation of reporter genes, in addition to demonstrating viral gene expression, we were also able to identify and quantify new cell infection events. This revealed continuous CyHV-3 transmission right up until the clearance of infection, albeit with increasingly reduced rates of newly infected cells. While we demonstrated that ZF4s are certainly susceptible to CyHV-3 infection, any initial productive infections leading to transmission of viable progeny were not sustained. Thus, ZF4 cells are transiently permissive to CyHV-3 with inefficient viral replication/transmission unable to overcome the innate immune response among infected and non-infected cells. This may be similar to previous observations with snakehead fish vesiculovirus (SHVV) infections in ZF4 cells where initial increases in virus levels were followed by a decrease, corresponding to ISG upregulation [73]. Unlike CyHV-3, prior to this study, the susceptibility ZF4 cells to AngHV-1 and CyHV-2 had not been investigated. Our results indicate that while ZF4 cells are also susceptible to both AngHV-1 and CyHV-2 infection, they are only permissive to the latter. However, as with CyHV-3, permissiveness to CyHV-2 infection was moderate and transient. These similarities between CyHV-2 and CyHV-3, and their differences to AngHV-1 in this context may reflect the fact that CyHV-2 and CyHV-3 are phylogenetically closer to each other, than each are to AngHV-1 [40,74,75,76]. Furthermore, given their natural host species, it stands to reason that CyHV-2 and CyHV-3 may also be inherently better adapted to growing in ZF4 cells relative to AngHV-1. Despite the lack of sustained permissivity to cypriniviruses, these in vitro experiments with ZF4 cells did provide some indication that the same recombinant viruses may be used to study transient cyprinivirus infection and clearance in zebrafish larvae, which, for many reasons (outlined earlier), may represent a valuable virus-host model. ## 3.2. Zebrafish Larvae Are Susceptible to CyHV-2 and CyHV-3 but Not to AngHV-1 Infection. Inoculation by the Two Cyprinid Herpesviruses Leads to an Abortive Infection We next investigated the susceptibility and permissivity of zebrafish larvae to the same three cypriniviruses. To investigate this, we used WT AB zebrafish larvae at 3 dpf. In the first experiment, larvae were infected with the same recombinants previously used (Figure 2, Figure 3, Figure 4, Figure 5 and Figure 6). Larvae were inoculated by pericardial microinjection with 1.2 × 106 PFU/mL of each recombinant or PBS. In parallel, larvae were also infected by immersion with a final concentration of 4000 PFU/mL of each recombinant or PBS. The susceptibility of larvae to these viruses was assessed using epifluorescence microscopy to detect reporter expression from each recombinant. Independently of the mode of inoculation used or the virus, no morbidity or mortality was observed among larvae. Epifluorescence microscopy indicated no infection in larvae inoculated by immersion. Conversely, viral infection was detected from 1 dpi in larvae inoculated with CyHV-2 and CyHV-3 by microinjection (Figure 7a) with no fluorescence detected in the AngHV-1 inoculated group. Fluorescence intensity in CyHV-2 and CyHV-3-infected larvae increased from 1–2 dpi. However, as per earlier in vitro observations, these infections were transient, with fluorescence intensity (Figure 7a) and the numbers of infected larvae (Figure 7b) decreasing by 4 dpi. While the pattern was similar for both viruses, the CyHV-3 group exhibited greater fluorescence intensity and significantly higher rates of infected larvae (Two-way RM ANOVA p-value = 0.0214). Infection clearance was most pronounced in the CyHV-2-infected group, with a significantly higher proportion of larvae infected at earlier timepoints exhibiting viral clearance by 4 dpi relative to CyHV-3 (Figure 7b). The differences between these three cypriniviruses were investigated further by measuring Luc2 expression from recombinants, representing a more quantitative comparison of viral levels in vivo. This involved the same AngHV-1 and CyHV-2 recombinants used in Figure 7a, with CyHV-3 EGFP replaced with CyHV-3 Luc. Larvae were inoculated or mock-inoculated as per Figure 7a. Again, no mortality was observed in any groups and no infection was detected in the AngHV-1 group. The CyHV-3-infected group exhibited significantly higher viral levels relative to CyHV-2 (Durbin Test, p-value = 0.0008), indicating that CyHV-3 replicates better in this model. Also, for both CyHV-2 and CyVH-3, a reduction in virus levels occurred at 3 dpi, coinciding with a reduction in the numbers of infected fish, indicating the initiation of viral clearance. However, as per Figure 7b, clearance was significantly greater within the CyHV-2-infected group by 4 dpi (Figure 7c). These experiments revealed that zebrafish larvae are not susceptible to any of these viruses via immersion, which may be considered a more natural route. This is similar to previous findings with CyHV-3 in Tübingen zebrafish larvae [38]. Conversely, larvae were susceptible to CyHV-2 and CyHV-3 when inoculated via pericardial microinjection, but not to AngHV-1 via the same route. In line with earlier observations in vitro, CyHV-2 and CyHV-3, which naturally infect members of the family Cyprinidae, are much more fit in this zebrafish model relative to AngHV-1. For CyHV-2 and CyHV-3, a peak of infection was reached at 2 dpi, with viral clearance initiating from 2–3 dpi. Notably, this is the first report of cyprinivirus infection in zebrafish larvae. Our observations are largely consistent with previous description of CyHV-3 infections in adult zebrafish (inoculation by intraperitoneal injection) [38]. There was also a notable lack of mortality in previous studies involving the challenge of zebrafish with other viruses of cyprinid fish [38]. One explanation is that zebrafish may naturally possess robust defences against other viruses that are closely related to CyHV-2 and CyHV-3 which may have circulated in their natural habitat during their evolution. However, few viruses are known to naturally infect zebrafish [1,19], thus it would be useful to determine if any extant uncharacterized members of the family Alloherpesviridae naturally infect zebrafish as a primary host, as it would open up new avenues of investigation with a valuable homologous herpesvirus-host model in zebrafish. It is also possible that this lack of mortality is related to the viral dose or even inoculation site, both of which can impact the severity of viral infections in zebrafish larvae, as exemplified elsewhere [77,78]. Our observations indicated that CyHV-3 exhibits greater fitness in these zebrafish models relative to CyHV-2. Thus, in addition to CyHV-3 being the most studied and the archetype fish alloherpesvirus [39], it also represented a more valuable model to utilize in the further study of alloherpesvirus infections in zebrafish larvae. Thus, CyHV-3 was selected for all further in vivo investigations in this study. ## 3.3. Pericardial Inoculation of Zebrafish Larvae with CyHV-3 Leads to Infection of Resident and Motile Cells around the Inoculation Site Followed by Their Apoptosis-like Death and Viral Clearance Earlier experiments revealed that the levels of CyHV-3 signal increased from 1–2 dpi with clearance commencing from 2–3 dpi (Figure 7a,c). However, it remained unclear if increases in viral signal were merely due to increasing levels of viral gene expression or the numbers of infected cells. We chose to investigate this using light sheet microscopy to capture epifluorescence and brightfield images at regular intervals in live CyHV-3-infected larvae from 2–3 dpi and subsequently generated a timelapse video with this data (Video S1). This timepoint was selected as it overlapped with the highest viral signals and the beginning of the viral clearance process (Figure 7), and because no viable virus from the original inoculum should have persisted to this timepoint [64]. As per Figure 7a, the infection was mainly localized around the heart area, reflecting the inoculation route. In line with earlier observations, a reduction in viral levels commenced between 2.5–3 dpi (Figure 8a and Video S1). Notably, the data revealed a substantial upsurge in apoptosis-like cell death immediately prior to clearance, indicating that programmed cell death may also play a major role in this process in vivo (Figure 8b and Video S1). Although the occurrence of apoptosis in response to CyHV-3 infection in vivo was not confirmed by staining in this present study, our observations are similar to previous studies involving timelapse analysis of CHIKV-infected zebrafish larvae [23]. Throughout the monitoring period, highly motile cells, possibly macrophages or neutrophils, were also observed to be infected. These did not remain localized around the inoculation site. However, they were not observed to establish secondary infection sites elsewhere (Figure 8c and Video S1). Furthermore, some of these motile cells appeared also to undergo apoptosis-like and non-apoptosis-like cell death consistent with necroptosis (Video S1). Unlike earlier in vitro observations, this data did not provide unambiguous evidence of newly infected cells appearing before clearance commenced. Indeed, the induction of a programmed cell death response among infected cells in vivo, thus interrupting the CyHV-3 replication cycle, would lead to a reduction in successful CyHV-3 transmission to new cells. Consequently, CyHV-3 propagation in vivo may be sufficiently restricted to facilitate its clearance via the innate immune response alone. This hypothesis still implies that zebrafish cells are inherently permissive to CyHV-3 replication. However, this would, at the very least, require expression of all essential CyHV-3 protein coding genes in vivo. Thus, we subsequently investigated this and the nature of the innate immune response via transcriptomic analysis of infected larvae. ## 3.4. Transcriptomic Analysis of Infected Zebrafish Indicate Upregulation of ISGs, in Particular Those Involved in Programmed Cell Death, Innate Immune Response and PRR Signalling Pathways In order to further characterise the response to CyHV-3 infection in this zebrafish larvae model in terms of the ISG upregulation, the potential involvement of programmed cell death (as indicated in Figure 8 and Video S1), and to establish the extent of CyHV-3 gene transcription in this model, we conducted transcriptomic analysis of infected zebrafish larvae. CyHV-3-infected and mock-infected larvae were sampled at 1, 2, and 4 dpi for RNA extraction and sequencing. RNA-Seq, yielded ~15–20 million reads per sample with data publicly available under BioProject Accession number PRJNA929940. Gene expression was compared between infected and mock-infected samples at each timepoint to identify DEGs. In line with viral levels observed in earlier experiments, viral RNA levels reached a peak at 2 dpi ($0.34\%$ of total transcriptome), falling considerably by 4 dpi (Table S2). Notably, transcription from all 155 CyHV-3 ORFs was detected by 2 dpi (Figure S3 and Table S3), indicating that indeed, in this model, cells may be permissive to CyHV-3 replication. Host differential gene expression in response to infection also peaked at 2 dpi, with $7.4\%$ of expressed genes classified as DEGs (Table S2 and Figure S4). Prior to this study, it was unknown how zebrafish larvae respond to CyHV-3 challenge in terms of type I IFN gene expression. Consistent with other reports [16], we found that ifnphi2 was not expressed at this developmental stage. The IFN response in zebrafish larvae relies on expression of ifnphi1 and/or ifnphi3 genes [16]. However, we did not observe convincing expression from either gene at any timepoint. Our sampling points range from at 1–4 dpi, which equate to 96–168 hpf, with previous studies indicating that WT AB zebrafish larvae are capable of expressing infphi1 and infphi3 by this developmental stage [16,23]. Notably, these previous studies, involving SVCV and CHIKV challenge, utilized RT-qPCR to detect IFN gene transcription, which may be more sensitive than RNA-Seq in some situations. While CyHV-3 is known to inhibit the IFN-response in vitro [79,80], our observations do not necessarily indicate inhibition of the IFN-response in zebrafish. It is possible that the upregulation of IFN genes occurs very early after infection, returning to basal levels rapidly, prior to the first sampling point. The effects of this rapid and short-lived IFN response should be still observed in the form of subsequent ISG induction. Indeed, in this present study, the list of the 250 most significant DEGs at 2 dpi is dominated by typical ISGs (Table S4). This ISG induction in the absence of IFN detection is similar to previous studies with WT zebrafish larvae infected with nervous necrosis virus (NNV) [78]. In both studies, it is likely that IFN upregulation occurred prior to the earliest sampling point. However, the kinetics of Type I IFN induction in WT AB zebrafish may depend on the nature of the viral challenge (virus, dosage and inoculation site/route). For example, in previous studies in which WT AB larvae were inoculated with HSV-I and CHIKV (72 hpf), ifnphi1 upregulation peaked at 36 hpi [77] and 24hpi [23], respectively, with further differences in sustained upregulation after these timepoints. Furthermore, the expression of infphi1 and ifnphi3 may be model-specific. For example, Tübingen strain zebrafish larvae inoculated with Tilapia Lake Virus (TiLV) (48–60 hpf) were only observed to exhibit significant ifnphi1 upregulation but not insignificant infphi3 upregulation by 48 hpi [81]. It remains unclear if only one or both IFN genes are responsible for this ISG induction (Table S4) in our infection model, and this will be the subject of future studies, involving sampling at earlier timepoints. We also conducted further characterisation of the main types of genes that were differentially expressed in response to CyHV-3 infection in zebrafish larvae. Using STRING, we generated a network (Figure 9) representing the functional relationships between the top 250 most significant DEGs at 2 dpi (Table S4). As expected, functional enrichment analysis of this network revealed that these DEGs were mainly associated with the immune and stress responses (Table S6). Three main clusters formed within this network. The largest cluster (Figure 9a) mainly represented genes involved in viral infection and cytokine responses. These include genes encoding the antiviral GTPase proteins such as mxa, mxb, mxc, and mxe, as well as rsad2 (or vig-1, viperin). This is consistent with previous observations in zebrafish larvae infected with NNV [78], Zebrafish Picornavirus (Zfpv) [19], and CyHV-3-infected adult zebrafish [38]. In terms of the cytokine response, genes encoding IFN regulatory factors irf7 and irf9 were also part of this main cluster. Notably, zebrafish irf3 was also among the top 250 most significant DEGs (Table S4), however as STRING returned no results for this gene, it was not included in the network in Figure 9. In addition, genes encoding other important elements of the IFN response, stat1a, stat1b, stat2, and augmentation and regulation of this response such as isg15 [30] were also featured in this cluster, consistent with zebrafish larvae responses to HHV-1 [77] and NNV [78]. The detection of “non-self” material in cells via PRRs is an important part of the innate immune response. Viral nucleic acids represent major PAMPs during infections, and genes encoding PRRs to detect these PAMPs were among the most significant DEGs in our experimental model. For example, genes encoding important zebrafish RIG-I-like receptor (RLR) orthologs, such as ifih1 (encoding MDA-5 ortholog) [82], and dhx58 (encoding LGP2 ortholog) [83] were centrally located within this large cluster (Figure 9a). An additional gene, rigi, encoding the zebrafish ortholog of RIG-I, the most-studied RLR [84], was also significantly upregulated in response to infection, but not among the top 250 most significant DEGs used to generate this network (274th most significant DEG, Table S5). Genes encoding other important components of the RLR viral RNA sensing apparatus such as trim25 [85,86] were also centrally located in this large cluster (Figure 9a). In addition to RLRs, other genes encoding RNA binding proteins are important actors in the innate immune response such as adar [87], eif2ak2 (encoding PKR ortholog) [88], pkz [88,89,90,91], and ifit10 (human IFIT5 ortholog) [92,93,94] also co-locate within the same large cluster. Interestingly, we noted that two additional genes, helz2a and helz2b, encoding proteins that may act as evolutionarily conserved RNA sensors [95], can be observed at the peripheral regions of this main cluster. Many known vertebrate dsDNA sensing PRRs are absent in teleost fish [95,96]. Of the few known genes encoding dsDNA sensing PRRs in zebrafish, which include ddx41 [77,97], cgasa [98], dhx9 [77], and dhx36 (the latter of which, may act as a conserved RNA and DNA PRR [99]), only cgasa was significantly upregulated, but not featured in the top 250 DEGs (623rd most significant DEG, Table S5). This may indicate that RNA sensing as opposed to DNA sensing PRRs represent an important part of the response to CyHV-3 infection in zebrafish larvae, even though it is a dsDNA virus. This is consistent with growing evidence for the role of RLRs in the detection of dsDNA viruses, such as members of the family Herpesviridae or Adenoviridae [100,101,102,103,104]. Within the largest cluster, in addition to genes being generally involved in antiviral responses, functional enrichment analysis identified a subset of clusters representing genes belonging to IFN signalling and necroptosis gene-sets (Figure 9a). The same functional enrichment analysis indicated that genes in the smaller central cluster were mainly involved in antigen processing and phagosome responses (Figure 9b), with genes in the smaller cluster on the right mainly related to the complement system (Figure 9c). Furthermore, the identification of the potentially most important hub nodes within the network in Figure 9 (based on maximal clique centrality) revealed that nodes representing RNA PRRs ifih1 (MDA5 ortholog) and dhx58 (LGP2 ortholog) were ranked highest, along with rsad2 (or vig-1, viperin ortholog), stat1a, irf7, isg15 and stat1b (Figure S5 and Table S7). Notably, all the top ten ranked hub nodes (twenty in total) represent genes located in the largest cluster (Figure 9a), most of which are described above. Interestingly, in addition to many commonly studied ISGs, we also observed upregulation of genes encoding NACHT-domain and leucine-rich-repeat-containing (NLR) proteins, for example, loc100535428 (Table S4). These represent a protein-class that is now increasingly recognised as representing important elements of the innate immune response in teleost fish [19,105]. We also note the upregulation of many genes encoding uncharacterized products in response to CyHV-3 infection, some of which were >1000–5000-fold upregulated (Table S4). Focusing on those within the top 250 significant DEGs that were >100 fold upregulated, we noted that four of these were not previously described as being upregulated in response to infection or immune stimulation (Table S4). We also noted the upregulation of five non-coding RNA genes in response to CyHV-3 infection, one of which was >3000 fold upregulated (Table S4), representing the 6th most upregulated gene in the dataset. All other uncharacterized genes occurring within the group of top 250 most significant DEGs were further cross-referenced with existing GenBank entry information on predicted protein domains (Table S4). This revealed that three of these genes potentially encode additional NLR proteins, three encode RNA binding domains, and three encode proteins containing retrotransposon derived reverse transcriptase-like (RT-like) domains (Table S4). In the case of the latter, the three genes encoding RT-like domains are all paralogs of each other (KEGG Database) and similarly upregulated (>29–35-fold, Table S4). Further inspection of corresponding entries for these gene products in UniProt and InterPro revealed predicted retrotransposon gag, aspartic proteinase, RT, RNase H, and integrase domains, indicating they may indeed encode retrotransposon polyproteins. The domain organization and motifs are consistent with retrotransposons within the family Belpaoviridae [106] (also referred to as Bel/Pao, Class I retrotransposons based on previous classification systems [107]). It should be noted that the upregulation of retrotransposons and other transposable elements in response to infection has been observed in other organisms [108,109,110], and to the best of our knowledge this is the first description of this in a zebrafish model. Interestingly, upregulation of class I retrotransposons in zebrafish has also been observed in response to genome demethylation, leading to the induction of antiviral responses [111]. In further analysis, we expanded our investigation to all genes included in differential expression analysis at 2 dpi (Table S5), exploring the response to infection at a “gene-set level”. Using GSEA, we identified GO and KEGG pathway gene-sets that were to a significant extent positively or negatively enriched in CyHV-3-infected larvae at 2 dpi (Tables S8 and S9, Figure S6). Cytoscape was used to generate a network of these significantly enriched gene-sets based on the functional relationships between them (Figure 10), providing a greater insight into what biological processes are implicated in the response to CyHV-3 infection in zebrafish larvae, and how they are related. Notably, only one gene-set, “Ribosome” (DRE03010), was found to be significantly negatively enriched, with all other significant gene-set responses involving positive enrichment. During the process of generating the network presented in Figure 10, nodes (i.e., gene-sets) were clustered together based on their similarity coefficient (related to gene-set/functional overlap). This process resulted in the formation of several large clusters, which we numbered. Cluster-1 is the largest of these and exhibits the highest quantity of functional connections with surrounding clusters, and as such, it represents a major aspect of the response to CyHV-3 infection. Within Cluster-1, there are two main sub-clusters. One of these is dominated by gene-sets related to programmed cell death, the other is dominated by PRR signalling, pathogen and inflammatory response gene-sets. Notably, enrichment of the RIG-I-like signalling pathway, the Toll-like receptor signalling pathway, and the Herpes simplex virus 1 gene-sets are consistent with zebrafish larvae response to NNV infection [78]. In Cluster-1, the KEGG Necroptosis pathway (DRE04217) is the most significant positively enriched gene-set, and joint most significantly enriched gene-set overall (Tables S8 and S9). Notably, this pathway gene-set is functionally related to other gene-sets in the apoptosis and PRR/inflammatory/pathogen response sub-clusters (manually isolated from these two sub-clusters in Cluster-1, Figure 10), exhibiting gene overlap with $\frac{15}{19}$ of these gene-sets, with eight of these resulting in similarity coefficients >0.02 and thus displayed in Figure 10. This reflects the substantial crosstalk that exists between programmed cell death and PRR signalling in response to infection [67,112]. The prominence of positively enriched necroptosis and apoptosis related gene-sets in Cluster-1 supports the hypotheses derived from earlier observations in vitro and in vivo (Figure 6 and Figure 8 and Video S1), that apoptosis-like and non-apoptosis-like programmed cell death feature heavily in the zebrafish response to CyHV-3 infection. One of the important genes in the necroptosis pathway is eif2ak2 (or pkr). It was identified as one of the main genes contributing to the enrichment signal for the necroptosis gene-set (Figure S7). It represents an important link between the innate immune response and the initiation of necroptosis [113]. This gene encodes a protein referred to as “interferon-induced, double-stranded RNA-activated protein kinase”, or more commonly, “Protein Kinase R” (referred to as PKR hereafter). PKR functions as both a general cellular stress sensor and PRR. Thus, it plays a diverse role in the innate immune response to viral infections and many fundamental cellular processes including programmed cell death [114]. PKR-mediated programmed cell death is important for the clearance of viral infections [113,115,116]; however, the antiviral roles of PKR are diverse. It also contributes to the antiviral actions of other enriched gene-sets within Cluster-1 (Figure 10). For example, in the “Herpes simplex virus 1” response gene-set (DRE05168), PKR is activated by dsRNA formed during infection, and subsequently phosphorylates eIF2α (its main substrate), resulting in the stalling of mRNA translation [114,115,117] (Figure 11a). However, some mRNA species are less affected by this [118,119,120]. This translational stalling also leads to the formation of stress granules (SGs) [121,122,123], which in some cases are important for detection of viral RNA via PRRs as in the “RIG-I-like receptor signalling pathway” (DRE04622) [124,125]. Furthermore, PKR also facilitates/promotes the NF-κB pathway, indirectly [114,118]. While this induces a pro-inflammatory response which may be useful in terms of counteracting infection, the accompanying pro-survival response (although helpful to some aspects of immune-response [126]), is counter to the pro-apoptotic function of PKR, but may act to only temporarily delay cell death [127]. Notably, expression from the zebrafish nfkb1 gene, which encodes the zebrafish NF-κB ortholog, was not significantly upregulated at 2 dpi in our model (Table S5 and Figure 11b). PKR-mediated apoptosis can occur via the “extrinsic” FADD-caspase-8 mediated pathway [131]. The circumstances under which this occurs are quite diverse. For example, PKR-mediated translational inhibition leads to apoptosis [115,116] via depletion of cFLIP protein [112] which acts as an important inhibitor of caspase-8 (Figure 11b) [132,133]. PKR phosphorylation by PACT (in response to stress) can also lead to translational inhibition leading to caspase-8 dependent apoptosis [134], as can overexpression of PKR [135,136,137]. In addition to IFN stimulation leading to upregulation of PKR, IFN-stimulated PKR-mediated apoptosis can also occur via JAK/TYK-mediated phosphorylation of PKR [129]. Notably, along with eif2ak2 (encoding PKR), many other zebrafish genes encoding orthologs of ISGs involved in IFN-stimulated PKR-dependent apoptosis are also upregulated at 2 dpi in our model (Figure 11b,c). In parallel, PKR may also promote caspase-9 mediated apoptosis via the “intrinsic” apoptosis pathway. However, unlike caspase-8, caspase-9 was not upregulated at 2 dpi in our experiment (Figure 11b), indicating, as with other viral-host models [118,130,131], that caspase-8 mediated apoptosis also plays a more dominant role in response to infection in the CyHV-3-zebrafish larvae model. Many viruses have evolved ways to interfere with apoptosis by disrupting elements of the FADD-caspase-8 pathway [72,114,138,139]. To counteract this, necroptosis may have evolved as a back-up mechanism of programmed cell death [72], which can occur via compromising of the cell membrane though action of MLKL [140] and/or production of reactive oxygen species [141]. This relies on the interaction of RIPK1 and RIPK3 for necrosome formation, a process that is inhibited by the FADD-caspase-8 complex [72,141,142]. Like apoptosis, PKR-mediated necroptosis can occur in response to IFNs, possibly requiring PKR interaction with RIPK1 [113]. While other groups have also observed a physical association between PKR and RIPK1 [143], the exact role that PKR plays in initiating necroptosis in response to IFN stimulation remains unclear [144]. Notably it has been proposed that IFN-stimulated PKR-mediated necroptosis is restricted to the G2M stage of the cell cycle, when FADD is disabled, preventing capase-8 inhibition of necrosome formation [113]. Given that in zebrafish larvae, and to lesser extent, in ZF4 monolayers, we expect widespread, frequent occurrence of mitosis, our models may be particularly predisposed to this type of PKR-mediated necroptosis. Notably, in addition to PKR itself, genes encoding zebrafish orthologs of ISGs involved in PKR-mediated necroptosis are also upregulated at 2 dpi (Figure 11c). The eif2ak2 gene encoding PKR was also among the top 250 most significant DEGs in this study (Table S4) and identified as an important hub gene in functional network in Figure 9, being ranked 3rd overall (Table S7). Given the importance of this ISG in terms of antiviral defence [112,115,145], particularly regarding programmed cell death, we hypothesized that the knock-out (KO) of the eif2ak2 gene may impact CyHV-3 clearance in zebrafish larvae. Unlike other vertebrates, members of the teleost fish families Salmonidae and Cyprinidae also encode an additional PKR-like protein referred to as “protein kinase containing Z-DNA binding domains” (or PKZ) [88,89,91]. PKZ genes may have evolved through duplication of the PKR encoding genes in these teleost fish families, after divergence from tetrapods [88]. Consequently, PKZ exhibits a high degree of sequence similarity to PKR proteins encoded in the same genomes, predominantly to the C-terminal kinase domain, which is responsible for eIF2α phosphorylation by PKR [89,146]. However, unlike PKR, PKZ contains Zalpha (Zα) domains instead of dsRNA binding domains in the N-terminal [146] (Figure 1). These domains are capable of binding to Z-DNA/RNA, which exist in the left-handed double helix conformation as opposed to the more common right-handed conformation of dsDNA/RNA (referred to as A and B-DNA/RNA) [90].These two features indicate that: [1] Like PKR, PKZ acts as an eIF2α kinase and mediates translational stalling, and induction of apoptosis via eIF2α phosphorylation [88,89,147,148], and [2] Like PKR, PKZ acts as a cytosolic PRR, but is activated by a greater diversity of nucleic acids than PKR. PKZ nucleic acid binding, B-to-Z conversion, and PKZ-mediated translational stalling have been best demonstrated using B and Z-DNA [89,149,150,151,152], indicating co-operative antiviral roles for PKZ and PKR. However, given that the Zα domains of PKZ do bind to RNA analogues [153] and that some Zα domains exhibit A-to-Z RNA conversion (as we recently demonstrated [90]), like PKR, PKZ may also detect and be activated by dsRNA. Thus, PKZ may provide at least some degree of back-up for PKR, leading to some redundancy among zebrafish IFN induced eIF2α kinases. Notably, the pkz gene (encoding PKZ) was the 23rd most significantly upregulated gene at 2 dpi in our model, upregulated more than the eif2ak2 gene (encoding PKR, ranked 250th, Table S4), and the pkz expression levels were >3 fold higher. In addition, pkz was ranked 9th in hub gene analysis in Figure 9 (see also Table S7). Given their potentially overlapping functions, in addition to the PKR-KO mutant (lacking eif2ak2), we generated a separate mutant, PKZ-KO (lacking pkz, Figure 1), to investigate the importance of both these multifunctional eIF2α kinases in the clearance of CyHV-3 in zebrafish larvae. ## 3.5. The Absence of PKR and/or PKZ Does Not Impair the Clearance of CyHV-3 Infections in Zebrafish Larvae In vitro and in vivo experiments performed in this study indicated that CyHV-3 infection was rapidly cleared in zebrafish models via programmed cell death. This was supported by the transcriptomic analysis from infected larvae, which also supported a potentially important role for the eIF2α kinases PKR and PKZ in this process. Based on this evidence, we tested the impact of these eIF2α kinases on CyHV-3 clearance using CRISPR/Cas9 generated PKR-KO and PKZ-KO zebrafish mutants (Figure 1). Mutant and WT zebrafish larvae were first infected with CyHV-3 EGFP by microinjection as per earlier experiments. As we hypothesized that the onset of infection clearance may take longer to occur in eIF2α kinase KO mutants, we also extended the monitoring period from 4 dpi (in earlier experiments) to 5 dpi. Epifluorescence microscopy suggested that PKR-KO and PKZ-KO mutants cleared viral infection as efficiently as WT larvae (Figure 12a). There was also no difference between the zebrafish strains in terms of the numbers of infected larvae at each timepoint (Two-way RM ANOVA, p-value = 0.6440), with all groups exhibiting a dramatic decrease in the number of positive fish at 5 dpi (Figure 12b). Next, WT, PKR-KO, and PKZ-KO zebrafish strains were infected with CyHV-3 Luc as before, allowing viral replication to be compared between strains (Figure 12c). This revealed no significant difference in viral signal between the three zebrafish strains (Durbin Test, p-value = 0.6500). Relative differences in signals between the WT and PKR-KO strains were inconsistent over the monitoring period, with no clear trends to indicate a difference between the two strains. In contrast, virus levels in the PKZ-KO strain were consistently higher than both WT and PKR-KO strains from 1–4 dpi, with significant differences at 3 dpi. However, viral levels in PKZ-KO larvae were significantly lower than other strains by 5 dpi (Figure 12c), indicating greater clearance, despite higher viral levels from 1–4 dpi. Cognisant of the possible redundancy in eIF2α kinase function (described earlier), which may have allowed PKZ to compensate for the absence of PKR in the PKR-KO mutant, and vice versa, we generated a third mutant, PKR-PKZ-KO, lacking both pkz and eif2ak2 genes (Figure 1). This strain was included in an additional experiment, like the one presented in Figure 12. ( Figure S8). However, surprisingly, the viral loads observed in the PKR-PKZ-KO mutants were not significantly different from the WT strain. Taken together, the results from these two experiments indicate that 1) PKR and PKZ are not essential for clearance of CyHV-3 infection in zebrafish larvae, and 2) even at this early developmental stage, the zebrafish immune system exhibits sufficient redundancy to enable clearance of CyHV-3 infection in the absence of PKZ and/or PKR. If programmed cell death also features heavily in the response to CyHV-3 infection in these mutant zebrafish strains, as earlier observations in the WT strain suggested (Figure 8, Figure 11 and Video S1), these processes would need to be mediated via other mechanisms. Notably, in addition to IFN-stimulated PKR/PKZ-mediated programmed cell death [112,113,129], these processes can be stimulated by other cytokines such as FAS, TNFα, and TRAIL [154,155,156,157] (the zebrafish orthologs for these proteins are encoded by the faslg, tnfa, and tnfsf10 genes, respectively). Like IFN, these cytokines also operate by binding to their respective cell membrane receptors and downstream interactions between these and various other proteins are required to initiate apoptosis and/or necroptosis. Notably, genes encoding zebrafish orthologs of most of the proteins involved in these processes are also upregulated in response to infection at 2 dpi (Figure 11), indicating some potential redundancy in terms of the programmed cell death response. However, no expression from the faslg and tnfa genes was observed in our model. While we did observe expression for tnfsf10, it was not upregulated in response to infection. Therefore, similar to what we have hypothesized regarding IFN expression kinetics, it is possible that with this model, the upregulation of these three cytokines is also extremely brief, occurring very early after infection with a rapid return to basal levels after. As with IFN, further investigation will be needed to establish the expression kinetics of these cytokines in response to CyHV-3 infection in this host model, and to what extent, if any, they contribute to programmed cell death and clearance of CyHV-3 infection. In both experiments (Figure 12 and Figure S8), the PKZ-KO mutant exhibited a higher viral load than other strains at the earlier stages of infection. The higher levels of CyHV-3 in the absence of PKZ may indicate the importance of host Zα domain-containing PRRs such as PKZ, in restricting CyHV-3 in the early stages of infection. This is consistent with our recent study where we provide strong evidence that the CyHV-3 ORF112 protein, which also contains a Zα domain, acts as an essential antagonist of RNA PRRs during CyHV-3 infection [90]. However, the absence of PKZ still leads to more dramatic viral clearance at 5 dpi relative to PKZ-competent strains (Figure 12c). We hypothesize that higher viral replication, from 1–4 dpi, may have ultimately led to an increased innate immune response, priming a more dramatic clearance at 5 dpi. Even if the absence of PKZ does not prevent viral clearance, the higher levels of viral replication in earlier stages, may lead to increased tissue damage via potential inflammatory response, which may ultimately be harmful to the host. Therefore, having the complete repertoire of PRRs necessary for effective restriction of CyHV-3 replication prior to clearance may still be important. Surprisingly, we do not observe higher viral loads at earlier stages of infection in the PKR-PKZ-KO mutant (also lacking PKZ), which instead exhibited a similar phenotype to WT and PKR-KO strains in response to CyHV-3 (Figure S8). These observations open up several interesting avenues for further investigation, in particular the characterization of the innate immune response in zebrafish mutants lacking these important PRRs and the possible impact of reduced eIF2α phosphorylation on programmed cell death, if any, in response to CyHV-3 infection in this model. ## 4. Conclusions The aim of this present study was to investigate the potential of the zebrafish model to study AngHV-1, CyHV-2, and CyHV-3, which are three economically important viruses in the family Alloherpesviridae. We conclude that while the zebrafish ZF4 cell line is moderately susceptible to these three viruses, it is less susceptible and not permissive to AngHV-1 (Figure 2). ZF4 cells do exhibit transient permissiveness to CyHV-2 and CyHV-3 infection. These cells are more permissive to CyHV-3, but both viruses exhibit inefficient cell to cell viral transmission in this in vitro model (Figure 3 and Figure 4). These viruses are ultimately cleared from ZF4 monolayers, in a process which is preceded by what resembles widespread programmed cell death among infected cell populations (Figure 3, Figure 4 and Figure 6). As zebrafish larvae were not susceptible to these viruses via inoculation by immersion, we conclude that these viruses may not be capable of entering zebrafish larvae through natural routes in vivo (Figure 7). However, zebrafish larvae are susceptible to infections with CyHV-2 and CyHV-3 via microinjection, an artificial inoculation route (Figure 7). Conversely, we conclude that zebrafish larvae are not susceptible to AngHV-1 via both inoculation methods used in this study (Figure 7). This lower susceptibility to AngHV-1 in vitro and in vivo, may reflect the fact that, unlike CyHV-2 and CyHV-3, AngHV-1 does not naturally infect host species from the family Cyprinidae. Even though larvae exhibit greater susceptibility to CyHV-2 and CyHV-3, we conclude that these infections are rapidly cleared (Figure 7 and Figure 12). We also conclude that zebrafish larvae exhibit more susceptibility (and possibly more permissivity) to CyHV-3, given higher viral levels and slower clearance, indicating the superior utility of this virus-host model in future studies. Interestingly, given that strains within each cyprinivirus species clad exhibit natural heterogeneity regarding replication in vitro and/or in vivo (at least with AngHV-1 and CyHV-3 [40,74]), it remains possible that the use of alternative cyprinivirus strains with the same zebrafish models may result in different outcomes, and is something which remains to be explored in the future. As we observed transcription of all 155 known CyHV-3 protein coding genes in infected zebrafish larvae (Figure S3, Table S3), we conclude that zebrafish cells may be permissive to CyHV-3 replication in vivo. However, unlike infections in vitro, we observed no clear evidence of CyHV-3 transmission to new cells prior to clearance in vivo (Figure 8, Video S1). Thus, the extent to which this permissiveness leads to successful CyHV-3 transmission between cells in vivo remains unclear. As per observations in vitro, CyHV-3 clearance in zebrafish larvae is also preceded by apoptosis-like death among infected cells (Figure 8, Video S1). These infections stimulate the upregulation of many ISGs (Figure 9, Tables S4 and S5). The upregulation of genes involved in programmed cell death and nucleic acid sensing PRR pathways represent a core part of this response (Figure 10 and Figure 11). PKR and PKZ are also upregulated in response to infection (Figure 9, Table S4) and may contribute to both programmed cell death and nucleic acid sensing PRR pathways (Figure 10 and Figure 11). However, their absence in mutant zebrafish strains does not impact CyHV-3 clearance (Figure 12). This may be due to sufficient levels of redundancy within the zebrafish innate immune response processes, even at this early developmental stage (Figure 11). Interestingly, CyHV-3 may represent an ideal model to utilize in the study of viral clearance by the innate immune system in this important and widely studied host. This opens many interesting avenues for future investigation to determine what elements of the immune response are essential for this process. As part of this, the generation of new KO mutants, guided by the transcriptomic data generated in this study, may lead to the development of zebrafish strains that are more permissive to these economically important viruses, which may themselves be utilized as valuable research tools in the future. This is the first report of the generation and use of PKR and/or PKZ KO zebrafish mutants (Figure 1 and Figure 12), and they will represent useful subjects for further characterization and the study of other viruses in zebrafish models. Given the importance of PKR, and potentially PKZ, in the innate immune responses and in many more cellular processes, and the widespread use of zebrafish as a model organism, the KO mutants generated in this study will be of interest to many more researchers in the wider field. Thus, sperm corresponding to these mutants will be deposited in the European Zebrafish Resource Centre (EZRC) for ease of distribution elsewhere. Furthermore, we note that many of the most significantly upregulated genes in response to CyHV-3 infection in zebrafish larvae were uncharacterized, and some were previously unreported as being involved in the immune response (Table S4). These include five non-coding transcripts (one of which was >3000-fold upregulated and the 6th most upregulated gene at 2 dpi). We propose to provisionally refer to these five transcripts as “Zebrafish Non-coding Infection Response Element” 1–5 (or ZNIRE 1–5, complete details in Table S4). This observation was particularly intriguing, and we propose that further research into their importance during the immune response will be necessary. We also observed the upregulation of three retrotransposons (all ~30-fold upregulated, Table S4). It is possible that this retrotransposon re-activation/upregulation in response to infection may be beneficial. Their cytoplasmic RNA and/or DNA genome intermediates may potentially act as ligands for PRRs [111], thus enhancing the innate immune response to viral infection and presenting an interesting hypothesis for further study with our model. ## References 1. Levraud J.-P., Palha N., Langevin C., Boudinot P.. 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--- title: Medium Roasting and Brewing Methods Differentially Modulate Global Metabolites, Lipids, Biogenic Amines, Minerals, and Antioxidant Capacity of Hawai‘i-Grown Coffee (Coffea arabica) authors: - Pratibha V. Nerurkar - Jennifer Yokoyama - Kramer Ichimura - Shannon Kutscher - Jamie Wong - Harry C. Bittenbender - Youping Deng journal: Metabolites year: 2023 pmcid: PMC10051321 doi: 10.3390/metabo13030412 license: CC BY 4.0 --- # Medium Roasting and Brewing Methods Differentially Modulate Global Metabolites, Lipids, Biogenic Amines, Minerals, and Antioxidant Capacity of Hawai‘i-Grown Coffee (Coffea arabica) ## Abstract In the United States, besides the US territory Puerto Rico, Hawai‘i is the only state that grows commercial coffee. In Hawai’i, coffee is the second most valuable agricultural commodity. Health benefits associated with moderate coffee consumption, including its antioxidant capacity, have been correlated to its bioactive components. Post-harvest techniques, coffee variety, degree of roasting, and brewing methods significantly impact the metabolites, lipids, minerals, and/or antioxidant capacity of brewed coffees. The goal of our study was to understand the impact of roasting and brewing methods on metabolites, lipids, biogenic amines, minerals, and antioxidant capacity of two Hawai‘i-grown coffee (Coffea arabica) varieties, “Kona Typica” and “Yellow Catuai”. Our results indicated that both roasting and coffee variety significantly modulated several metabolites, lipids, and biogenic amines of the coffee brews. Furthermore, regardless of coffee variety, the antioxidant capacity of roasted coffee brews was higher in cold brews. Similarly, total minerals were higher in “Kona Typica” cold brews followed by “Yellow Catuai” cold brews. Hawai‘i-grown coffees are considered “specialty coffees” since they are grown in unique volcanic soils and tropical microclimates with unique flavors. Our studies indicate that both Hawai‘i-grown coffees contain several health-promoting components. However, future studies are warranted to compare Hawai‘i-grown coffees with other popular brand coffees and their health benefits in vivo. ## 1. Introduction Coffee is one of the most popular drinks worldwide and is a widely consumed beverage. During 2022–2023, global coffee consumption is expected to reach over 168.7 million 60 kg (132 lb.) bags [1], and it is forecasted that the global production will be 172.8 million bags in the 2022–2023 growing season [2]. In the United States, it is estimated that more than 157 million cups of coffee are consumed per day, making the United States the world’s leading coffee consumer [3]. The health benefits of coffee, including its antioxidant properties, are associated with its complex array of bioactive chemicals, the most influential being alkaloids (caffeine and trigonelline), phenolic compounds (chlorogenic acids), and diterpenes (cafestol and kahweol). Epidemiological studies have reported several health benefits of coffee such as reducing the risk of metabolic syndrome (MetS), type 2 diabetes (T2D), cardiovascular disease (CVD), various types of cancer, kidney stones, liver disease, Parkinson’s disease, gout, and neurological disorders [4,5,6,7]. Moderate coffee consumption may also confer protective effects against overall mortality [8,9,10,11,12,13]. However, a few studies indicate that drinking more than four to nine cups of coffee per day may have some detrimental health effects such as increasing plasma cholesterol or triglyceride levels, and decreasing bone density in women [6,14,15,16]. Consuming large amounts of caffeinated coffee can also have negative effects on health such as increased blood pressure, anxiety, or difficulty falling asleep [17]. Abrupt cessation of caffeine consumption may induce withdrawal symptoms such as headache, fatigue, and/or depression. Coffee consumption during pregnancy is associated with adverse birth outcomes and neonatal health including lower infant birth weight [18,19,20,21,22,23,24,25,26,27,28]. Similarly, biogenic amines identified in coffee brews, resulting from amino acid decarboxylation, can be toxic to humans at high concentrations [29]. Inconsistencies observed in the health benefits of coffee may possibly be associated with differences in the chemical compositions of coffee [30,31,32,33,34,35,36]. It has been demonstrated that differences in coffee metabolites and caffeine levels [36,37] are influenced by their geographic origins or environment [38,39,40,41,42,43,44], post-harvest processing [30,33,45,46,47,48], instant versus fresh ground coffees [49,50], degrees of roasting [33,51,52,53], and/or types of brewing methods [31,33,36,49,54,55,56]. Different coffee metabolites not only impart flavors [38,57,58] or aromas [59,60,61,62,63], but also determine therapeutic impact by influencing antioxidant potential [34,64,65,66,67]. Prospective epidemiological studies conducted among populations of Hawai‘i indicate that a moderate level of coffee consumption (one to three cups per day) was associated with a lower risk of T2D, chronic liver diseases, dementia, and Parkinson’s disease [68,69,70,71]. In contrast, drinking more than nine cups of coffee per day was positively associated with increased serum cholesterol among several population-based studies, including Japanese men in Hawai‘i [14,15]. Besides the US territory Puerto Rico, Hawai‘i is the only state in the United States that grows commercial coffee. In Hawai’i, coffee is the second most valuable agriculture commodity after seed crops [72,73]. In 2021, unroasted coffee was valued at USD 102.91 million, and its roasted value was more than USD 148.48 million [74]. In 2022, annual revenue for the US coffee industry was estimated at USD 90.27 billion [75]. Hawai’i-grown coffees account for less than $1\%$ of total global coffee production. However, they are considered specialty coffees since they are grown in unique volcanic soils and tropical microclimates with unique flavors [76]. The main varieties of coffee grown in Hawai‘i are “Kona Typica” and “Yellow Catuai”, which represent two major Coffea arabica botanical varieties of “Typica” and “Bourbon” used worldwide. Metabolomic profiles of coffees brewed by different methods have been reported [33,36]. However, studies on the effect of roasting conditions on coffee metabolites are limited [33]. The antioxidant capacities and mineral contents of several coffee varieties and the impact of roasting conditions have also been reported [64,77,78,79,80,81,82,83]. Green coffee beans (grounds) are generally not brewed for consumption. Only roasted coffee grounds are brewed for consumption worldwide. Roasting generates the flavor of coffee. Green coffee brews would not be considered “coffee” since they do not taste like the “coffee” brewed from roasted grounds. Overall, no studies have addressed the lipidomic profiles of brewed coffee from roasted beans, while only one study evaluated selected biogenic amines in brewed coffee [29]. To date, one study has identified metabolites from spent grounds of Hawai‘ian Kona coffee [84]. However, variability in metabolites, lipids, biogenic amines, mineral contents, or antioxidant capacity of Hawai‘i-grown coffee (Coffea arabica) has yet to be elucidated. The primary objective of our study was to identify the impact of roasting and brewing methods on global metabolites, lipids, and biogenic amines in the two Hawai‘i-grown coffee varieties, “Kona Typica” and “Yellow Catuai”. Drip filter paper, drip filter mesh and French press are the most widely used methods for brewing roasted coffee. For our initial investigation, to evaluate the differences in metabolites, lipids, and biogenic amines among brews of roasted and green coffee beans, we used the above three brewing methods of coffee preparation. However, to understand the effects of different methods of brewing roasted coffee, we also included the cold brewing method, which is gaining popularity worldwide and has been reported to provide more beneficial compounds than other brewing methods [85,86]. The secondary objective of our study was to evaluate the influence of brewing methods on the antioxidant capacity and mineral contents of these two Hawai‘i-grown coffees. Brewing green coffee bean grounds is also not common. Therefore, we analyzed the minerals and the antioxidant capacity of brews prepared only from roasted coffee grounds. ## 2. Materials and Methods Green coffee beans, 50 lbs. each, of “Kona Typica” (purchased from Waialua Coffee and Cacao Estate, Oahu, Honolulu, HI, USA) and “Yellow Catuai” (purchased from Kaua’i Coffee Company, Kaua’i, Kalaheo, HI, USA) were stored at room temperature. “ Kona Typica” is also grown in Kaua’i, and “Yellow Catuai” is grown in Kona and on Oahu. Although metabolite differences are noted based on genetic variety, geographic location can also make a difference [38,39,40,41,42,43,44,46]. For ease of readership and future study reference, we will refer to “Kona Typica” as Waialua and “Yellow Catuai” as Kaua’i coffee. ## 2.1. Green Coffee Grounds Nylon bags filled with green coffee were dunked in liquid nitrogen for three to five seconds in order to freeze the green coffee beans. The frozen, dried green coffee beans were ground using a “Santos burr grinder” (Sao Paulo, Brazil). Grounds were collected in a jar, and larger grounds that did not pass completely through were discarded. Green coffee grounds were brewed using the drip filter paper, drip filter mesh and French press methods described below. ## 2.2. Coffee Roasting Prime-grade green beans were further cleaned by hand to remove any defective green beans and roasted using the electric, programmable rotating drum type “Has Garanti roaster” (Model HSR 1 kg (92.2 lbs.), Turkey), at 230 °C temperature for about 13 min, until coffee reached a medium roast color according to the “Roast Color Classification System” (Agtron 55-65, SCAA, Long Beach, CA, USA), and cooled at room temperature. Coffee beans were ground using the “Santos coffee grinder” (Burr type, Santa Fe Springs, CA, USA) to a size for paper filter brewing. For each type of brewing method, three roasted batches were mixed thoroughly and pooled as one sample. To understand inter-roasting variability, a total of six batches were roasted, providing two pooled samples for preparing the different brews. ## 2.3. Drip Filter Paper (FP) Method Two tablespoons (Tbsp) of coffee grounds with six fluid ounces (fl oz) of room-temperature tap water was brewed in the “Toastmaster” coffee machine (Star International Holdings group of brands, Star manufacturing, Smithville, TN, USA) using the “Total Home #4 Cone Style paper Filter” (CVS Pharmacy, Honolulu, HI, USA). After brewing was completed, the hot plate was turned off, and the coffee was cooled in the pot for 15 min. Cooled coffee brews were aliquoted into 50 mL tubes and stored at −80 °C until lyophilization. ## 2.4. Drip Metallic Filter Mesh (FM) Method Six fl oz of room-temperature tap water with two Tbsp of coffee grounds was brewed in the “Black and Decker Brew ‘N Go” (San Diego, CA, USA) coffee machine, which contains a metallic (steel) mesh filter. After brewing was completed, coffee was cooled in “Brew ‘N Go cup” for 15 min, aliquoted into 50 mL tubes, and stored at −80 °C until lyophilization. ## 2.5. French Press (FrP) Method Six fl oz of boiling water with two Tbsp of coffee grounds was set to steep for 15 min in the “Bodum Brazil 3 cup French Press Coffee Maker 12 oz” (Bodum incorporation, Triengen, Switzerland). The ground coffee beans were pressed with a perforated plunger plate and then cooled for 20 min in the brewing container. The coffee brew was then aliquoted into 50 mL tubes and stored at −80 °C until lyophilization. ## 2.6. Cold Brew (CB) Method A damp, reusable “Toddy Filter” (fabric-like, compostable filter made from tree-free specialized material by Toddy, LLC (Loveland, CO, USA)) was placed in the bottom of the “Toddy Cold Brew System” (Toddy, LLC, Loveland, CO, USA). One fl oz of room-temperature tap water and 4 Tbsp of roasted coffee grounds were added to the system. An additional three fl oz of water was gently added to the mixture and left to sit for 5 min. Another batch of four Tbsp of grounds and three fl oz of water was carefully added. The grounds were lightly pressed down to ensure all grounds were wet. The system was covered with foil and kept to steep for 24 h. After steeping, the coffee was measured and 2 times the amount of water was added to dilute the concentrate. Ten-milliliter aliquots were distributed, frozen, and stored in a −80 °C freezer until lyophilization. Samples were lyophilized in a Martin Christ Alpha 2-4 LD plus (Christ, Osterode am Harz, Germany) for 24 h, pooled, and then stored in a −80 °C freezer until analysis. ## 2.7. Brewed Coffee Omics (Global Metabolites, Lipids, and Biogenic Amines) Roasted coffee grounds were brewed by drip filter paper, drip filter mesh, French press, and cold brew methods. Green coffee bean grounds were brewed by drip filter paper, drip filter mesh, and French press methods. Metabolomics, lipidomics, and analysis of biogenic amines were conducted at the Fiehn Laboratory, NIH West Coast Metabolomics Center. Global metabolites (targeted and untargeted) were analyzed using an automated liner exchange cold injection system gas chromatography time of flight mass spectrometer (ALEX-CIS GCTOF MS) as described previously [87,88,89,90,91]. In brief, 10 mg brewed coffee samples were extracted with 1 mL of 3:3:2 acetonitrile (ACN):isopropanol (IPA):water by vortexing for 10 s and shaking for 6 min at 4 °C. After centrifugation at 14,000 RCF (relative centrifugal force) for 2 min, the supernatant was aliquoted into 475 μL aliquots, dried, and stored until further analysis. Half of the dried sample was derivatized with 10 μL of 40 mg·mL−1 of methoxyamine in pyridine and shaken at 30 °C for 1.5 h. Ninety-one microliters of N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA) + fatty acid methyl esters (FAMEs) was added to each sample and further shaken at 37 °C for 0.5 h to complete derivatization. Then, 0.5 μL derivatized samples were injected on a 7890A gas chromatogram (GC) coupled with a time of flight mass spectrometer (TOF; LECO Corporation, St. Joseph, MI, USA) using a splitless method onto a RESTEK RTX-5SIL MS column with an Intergra-Guard at 275 °C with a helium flow of 1 mL.min−1. The GC oven was set at 50 °C for 1 min and then ramped to 330 °C at the rate of 20 °C.min−1 and held for 5 min. The transfer line was set to 280 °C and the EI ion source was set to 250 °C. The MS parameters collect data from 85 m/z to 500 m/z at an acquisition rate of 17 spectra/s. Lipids were determined using the charged surface hybrid column electrospray method using a quadrupole time of flight mass spectrometer and tandem mass spectrometry (CSH-ESI QTOF MS/MS) as described previously [92,93]. In brief, 10 mg brewed coffee samples were vortexed with LCMS grade methanol (225 μL) and methyl tert-butyl ether (MTBE, 750 μL) and extracted by shaking for 6 min at 4 °C as previously described [90,93]. Samples were then vortexed with LCMS-grade water (188 μL). After centrifugation at 14,000 RCF (relative centrifugal force) for 2 min, the polar and non-polar layers were separated, dried, and stored until further analysis. Free fatty acids (FFAs); mono-, di-, and triglycerides (TGs); cholesteryl ester (CE); phospholipids (PLs); and sphingolipids (SLs) were analyzed by CSH-ESI QTOF MS/MS. Data were collected in both positive electrospray ionization (ESI) and negative ESI mode. Peaks were annotated by comparing MS/MS spectra and accurate masses of the precursor ion to spectra provided in the Fiehn Laboratory’s LipidBlast spectral library [94,95]. To profile biogenic amines, samples were analyzed using the hydrophilic interaction chromatography electrospray method, using a quadrupole time of flight mass spectrometer and tandem mass spectrometry (HILIC-ESI QTOF MS/MS) as described previously [90,93]. Data were collected in both positive and negative ESI modes and processed using MS-DIAL and MS-FLO programs as described [96]. ## 2.8. Mineral and Metal Analysis of Brewed Coffee The brewed coffees were lyophilized and sent to the Agricultural Diagnostic Service Center (ADSC), College of Tropical Agriculture and Human Resources (CTAHR), for analysis. The minerals analyzed included boron (B), calcium (Ca), copper (Cu), iron (Fe), magnesium (Mg), manganese (Mn), molybdenum (Mo), phosphorus (P), potassium (K), sodium (Na), and Zinc (Zn). The metals that were analyzed included arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), lead (Pb), selenium (Se), and vanadium (Va). Three independent brews for each type of coffee and each brewing method were analyzed in triplicate. Minerals and metals were analyzed by the standard EPA 3050B method (https://www.epa.gov/sites/default/files/2015-06/documents/epa-3050b.pdf, accessed on 5 January 2023) with slight modifications. In brief, 0.5 g lyophilized brewed coffee samples were used for analysis. Samples were digested with 3. 5 mL of concentrated nitric acid (15.8 N) for about 10 min at 110 °C. The samples were then mixed with 100 mL of ddH2O, incubated on a shaker, filtered through Whatman 42 filter paper, and analyzed on an Avio 560 Max Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES, Perkin Elmer, Waltham, MA, USA). ## 2.9. Antioxidant Capacity of Brewed Coffee The antioxidant activity of brews prepared from roasted coffee grounds was analyzed using a commercial ORAC Antioxidant Assay Kit, Cat# AOX-2-RB(Zen-Bio, Inc., Research Triangle Park, North Carolina). The ORAC is a kinetic assay that measures fluorescein decay and antioxidant protection over time. It is an assay that is regularly used to measure the total antioxidant capacity of biological fluids, cells, and tissues as well as dietary supplements, therapeutics [97], and food extracts [98]. In this assay, the substrate 2,2′-azobis-2-methyl-propanimidamine dihydrochloride (AAPH) generates a peroxyl radical (ROO-) which is formed upon thermal homolysis at 37 °C. This peroxyl radical oxidizes fluorescein, which thereby produces a non-fluorescent product. The principle of the assay relies on the hydrogen atom transfer (HAT) mechanism of antioxidants to suppress oxidative degradation of the signal and measures the subsequent fluorescent activity vs. reaction time [99]. ORAC measures the inhibition of the peroxyl radical-induced oxidation as carried out by antioxidant compounds in coffee. The fluorescent measurements were expressed relative to the initial reading (excitation/emission at 485 nm/528–538 nm). Three independent brews for each type of coffee and each brewing method were analyzed in triplicate at four different concentrations of 1:100, 1:200, 1:500, and 1:750. Time course reactions of fluorescein decay from AAPH were measured using a 96-well plate reader (Perkin Elmer Wallac 1420 Victor2) and plate reading software (Wallac 1420). Raw data from the ORAC assays were exported from the Wallac 1420 software to Excel and were normalized according to the following equation: AUC = 0.5 + (F1/F0) + (F2/F0) + … + 0.5 (F30/F0), where F0 = initial fluorescence reading at time = 0 min and F1, F2, etc., are the fluorescence readings at different time points. The area under the curve (AUC) values were generated using GraphPad Prism 7.0 for Mac OS X, version 7.0e. The net AUC was determined by subtracting the AUC of the blank from that of the coffee sample. A Trolox standard curve was generated using the net AUC vs. µM Trolox, in accordance with the one site-specific binding model (GraphPad Prism 7, GraphPad Software, CA, USA). Trolox equivalencies were determined by the one-site specific equation (Michaelis–Menten), as determined by the following equation: Y= Bmax * X/(Kd + X), where X is the equivalent Trolox concentration for coffee, Y is the net AUC for each coffee dilution, and Vmax and Kd are values from the Trolox standard curve. The ORAC data are represented as Trolox equivalences (TEs) of coffee. Three independent experiments were performed in replicates of six ($$n = 18$$). ## 2.10. Statistical Data Analysis All coffee metabolites, lipids, and biogenic amines (known and unknown) were analyzed by univariate analysis using the parametric t-test to compare the mean differences of two groups. The one-way analysis of variance (ANOVA) was followed by Holm–Sidak correction for multiple comparisons. The known metabolites were further subjected to multivariate analysis using MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/docs/Publications.xhtml, accessed between 6 September and 20 October 2022) [31]. Data were normalized to sample median, log10 transformed and Pareto scaled. Principal component analysis (PCA) was used to observe clustering trends and exclude outliers. A discriminant model was created by further subjecting the data to partial least squares discriminant analysis (PLS-DA). One thousand permutation tests were performed to check model validity and potential over-fitting of the PLS-DA model and visualized using a validation plot. Known metabolites, lipids, and biogenic amines in each category were used to build the PLS-DA models. After validation of the PLS-DA model, data were further analyzed by orthogonal partial least squares discriminant analysis (OPLS-DA) to identify discriminant metabolites, lipids, and biogenic amines and distinguish between categories at false discovery rate (FDR) < 0.05. Data for mineral and metal contents and ORAC assays are expressed as a mean ± standard deviation of triplicate or quadruplet values. Statistical significance was assessed using GraphPad Prism 7.0. Data were analyzed using either a two-tailed unpaired t-test or one-way ANOVA followed by Tukey’s test. p values < 0.05 were considered to be significant. ## 3. Results A total of 442 metabolites tentatively assigned as global metabolites (139 known and 303 unknown), 1617 metabolites tentatively assigned as positive ESI lipids (80 known and 1537 unknown), 2862 metabolites tentatively assigned as negative ESI lipids (40 known and 2822 unknown), and 1747 metabolites tentatively assigned as biogenic amines (47 known and 1700 unknown) were detected in both coffee varieties. ## 3.1. Differences in Global Metabolites, Lipids, and Biogenic Amines among the Green and Roasted Coffee Varieties of “Kona Typica” (Waialua) and “Yellow Catuai” (Kaua’i) Brews Univariate analysis indicated that 92 metabolites tentatively assigned as global metabolites (36 known and 54 unknown) were significantly different between the green varieties of Kaua’i and Waialua coffee ($p \leq 0.05$, supplement file 1). Similarly, 32 metabolites tentatively assigned as lipids (positive ESI; 4 known and 28 unknown), 103 metabolites tentatively assigned as negative ESI lipids (10 known and 93 unknown), and 132 metabolites tentatively assigned as biogenic amines (9 known and 123 unknown) were significantly different between the green varieties of Kaua’i and Waialua coffee ($p \leq 0.05$, supplement file 1). Kaua’i green coffee brews contained higher amounts of 2-hydroxybutanoic acid (14.64-fold), LPC (18:0; 37.97-fold), chlorogenic acid (18:34-fold), and N6,N6,N6-Trimethyllysine (12.53-fold) as compared to Waialua green coffee brews ($p \leq 0.05$, supplement file 1). Orthogonal projections to latent structures discriminant analysis (OPLS-DA) score plots for green varieties of Kaua’i and Waialua coffee are represented in Figure 1 as determined by multivariate analysis. Brews of the roasted coffees also demonstrated differences in 134 metabolites tentatively assigned as global metabolites (44 known and 89 unknown), 145 metabolites tentatively assigned positive ESI lipids (5 known and 140 unknown), 146 metabolites tentatively assigned as negative ESI lipids (12 known and 134 unknown), and 433 metabolites tentatively assigned as biogenic amines (15 known and 418 unknown) which were significantly different among Kaua’i and Waialua coffees ($p \leq 0.05$, supplement file 2). Among the known compounds, galactinol, pyrogallol, uracil, phosphatidyl choline (PC) (34:1), PC (34:2), PC (36:2), PC (16:0), PE (38:2), PE (36:1), PC (38:2), PC (36:4), PC (36:2), PC (36:1), PC (35:4), PC (34:1), and DL-Indole-3-lactic acid were more than 2-fold higher in roasted Kaua’i coffee brews as compared to the roasted Waialua coffee brews ($p \leq 0.05$, supplement file 2). The OPLS-DA score plots for roasted Kaua’i and Waialua coffee brews are represented in Figure 2. ## 3.2. Influence of Roasting on Metabolites, Lipids, and Biogenic Amines of “Kona Typica” (Waialua) and “Yellow Catuai” (Kaua’i) Coffee Brews As expected, roasting significantly increased caffeine and reduced chlorogenic acid in both coffee varieties (Figure 3A and Figure 3B, respectively). Similar effects of roasting on caffeine and chlorogenic contents of coffee have been reported by others [100]. Roasted Kaua’i coffee contained significantly high amounts of pyrogallol (Figure 3C, $p \leq 0.05$) compared to Waialua coffee. Overall differences in Kaua’i and Waialua coffee varieties as well as the effect of medium roasting conditions are noted in Figure 3D–G which depict hierarchal clustering (heatmaps) of all identified and unidentified metabolites for the green and roasted coffee brews: (C) global metabolites, (D) positive ESI lipid profiles, (E) negative ESI lipid profiles, and (G) biogenic amines. Roasted Kaua’i coffee brews demonstrated significant differences in 102 known and 209 unknown metabolites tentatively assigned as global metabolites, 119 metabolites tentatively assigned as positive ESI mode lipids (5 known and 114 unknown), 678 metabolites tentatively assigned as negative ESI mode lipids (8 known and 670 unknown), and 1132 metabolites tentatively assigned as biogenic amines (38 known and 1094 unknown) as compared to the green Kaua’i coffee brews ($p \leq 0.05$, supplement file 3). Figure 4 compares relative changes in selected metabolites, lipids, and biogenic amines of green and roasted Kaua’i coffee brews (adjusted p value (FDR) < 0.05). Similarly, 312 metabolites tentatively assigned as global metabolites (103 known and 209 unknown), 105 metabolites tentatively assigned as positive ESI mode lipids (5 known and 100 unknown), 697 metabolites tentatively assigned as negative ESI mode lipids (7 known and 690 unknown), and 1129 metabolites tentatively assigned as biogenic amines (38 known and 1091 unknown) were significantly different in roasted Waialua coffee brews as compared to the green Waialua coffee brews ($p \leq 0.05$, supplement file 4). Figure 4 depicts comparative selected box plots of known metabolites (Figure 4A–E), positive ESI lipids (Figure 4F–J), negative ESI lipids (Figure 4K–O), and biogenic amines (Figure 4P–T) as analyzed using MetaboAnalyst 5.0 (supplement file 5). ## 3.3. Influence of Brewing Methods on Metabolites, Lipids, and Biogenic Amines of “Kona Typica” (Waialua) and “Yellow Catuai” (Kaua’i) Coffee Brews A total of six batches were roasted from each coffee variety. Three roasted batches were pooled into one sample, and the procedure was repeated twice to understand inter-roasting variability. Each variety of roasted coffee was brewed twice by four different brewing methods ($$n = 2$$ for each method). Known metabolites, lipids, and biogenic amines for both coffee types were compared for each brewing method by volcano plots using GraphPad Prism 7.0. For example, the cold brew of roasted Kaua’i coffee was compared with the cold brew of roasted Waialua coffee. Unpaired data were analyzed using parametric t-tests. The threshold for p value comparison was set at $p \leq 0.05$ and corrected for multiple comparisons using the Holm–Sidak method. No significant differences were noted among both coffee varieties brewed by the same brewing method. Therefore, data from both coffee varieties were combined for each brewing method ($$n = 4$$) and were analyzed using MetaboAnalyst 5.0. Twenty-two metabolites tentatively assigned as global metabolites (11 known and 11 unknown) were significantly different in the four types of coffee brews as determined by one-way ANOVA followed by Fisher’s least significant difference method (Fisher’s LSD, adjusted p value (FDR) $p \leq 0.05$; supplement file 6). Interestingly, brewing methods significantly affected levels of several lipids. About 891 (49 known and 842 unknown) metabolites tentatively assigned as positive ESI mode lipids and 1447 (12 known and 1435 unknown) metabolites tentatively assigned as negative ESI mode lipids were significantly different in each type of brew ($p \leq 0.05$, supplement file 6). Selected significant metabolites (Figure 5A–D), positive ESI mode lipids (Figure 5E–H), and negative ESI mode lipids (Figure 5I–L) are depicted in Figure 5 below. Among the metabolites tentatively assigned as biogenic amines, only nine unknown amines were significantly different in the four types of brews ($p \leq 0.05$, supplement file 6). ## 3.4. Mineral and Metal Analysis of “Kona Typica” (Waialua) and “Yellow Catuai” (Kaua’i) Coffee Brews Brews of roasted coffee grounds are most widely consumed worldwide as compared to brews of green beans. Hence, the mineral and metal profiles of only the roasted coffee bean brews were analyzed. As indicated in Table 1, the amounts of most minerals in cold brews were significantly higher compared to those brewed by the French press, filter paper, and filter mesh brewing methods (Table 1, $p \leq 0.05$). Although not statistically significant, total minerals were higher in W-CB > K-CB > K-FrP > W-FrP > W-FM > K-FM > W-FP > K-FP (Table 1). An 8 oz cup of cold brew Kaua’i coffee contained $5.19\%$, $13.73\%$, $1.66\%$, $13.79\%$, $1.79\%$, $0.44\%$, $22.85\%$, $0.45\%$, and $3.15\%$ of the RDA for P, K, Ca, Mg, Na, Fe, Mn, Zn, and Cu, respectively. All RDA values were calculated based on recommended values (National Academy of Sciences, 2019). The amounts of minerals in cold brew Kaua’i coffee were in the order of K > Mg > P > Na > Ca > Mn > B > Fe > Zn > Cu. For all other brews of Kaua’i coffee, the order of mineral abundance was K > Mg > Na > P > Ca > Mn > B > Fe > Zn = Cu. In general, except for boron, Kaua’i coffee brewed by filter paper method had the lowest mineral contents, followed by filter mesh < French press < cold brew. Mineral contents in brewed Waialua coffee also showed similar trends to those observed in Kaua’i coffee (Table 1). An 8 oz cup of cold brew Waialua coffee contained $6.03\%$, $17.16\%$, $1.99\%$, $15.29\%$, $1.99\%$, $0.75\%$, $37.05\%$, $0.74\%$, and $11.83\%$ of the RDAs for P, K, Ca, Mg, Na, Fe, Mn, Zn, and Cu, respectively. For Waialua coffee, most of the mineral contents were similar in those brewed by filter paper and filter mesh except for K, while the amounts of minerals in French press coffee were less than those in cold brews. The Food and Nutrition Board has not established an RDA or AI for boron, which also does not have a DV. Total median boron intakes from dietary supplements and foods are about 1.0 to 1.5 mg.day−1 for adults (NIH.gov, accessed on 10 November 2022). ## 3.5. Antioxidant Capacity of “Kona Typica” (Waialua) and “Yellow Catuai” (Kaua’i) Coffee Brews The antioxidant capacity, as measured by ORAC values, was influenced by the methods of brewing rather than the coffee variety. The highest ORAC values were noted for the cold brewing method and were about 2.6- to 2.8-fold higher compared to the filter paper method (Figure 6, $p \leq 0.05$). For both coffee varieties, the antioxidant capacities for different brewing methods were in the order of cold brew > filter mesh > French press > filter paper (Figure 6). Overall, there were no significant differences between the ORAC values for Kaua’i and Waialua coffee brews prepared by the same brewing method (Figure 6, $p \leq 0.05$). ## 4. Discussion To understand the effects of health benefits and/or disease risks of coffee consumption, several studies have identified the metabolite composition of commercially brewed coffees based on the brewing methods, roast levels, coffee varieties, and/or caffeine contents [31,33,36,49,51,52,53,54,55,56]. The goal of our study was to identify differences in metabolites, lipids, and biogenic amines between the two types of Hawai‘i-grown coffees and the effects of roasting and brewing methods. Previous studies have used coffee beans to identify varietal differences in metabolites, while we used coffee brews [41,101]. The metabolomic approach has been previously used to identify specialty coffees and characterize their quality and exotic coffee tastes. For example, higher levels of sucrose and lower levels of γ-aminobutyric acid (GABA), quinic acid, choline, acetic acid, and fatty acids were observed in specialty or high-grade green coffees [102]. Similarly, arachidic acid and stearic acid were identified as markers for the Bourbon genealogical group; myristic and linoleic acids and sucrose, for the exotic genotype coffees; and lauric, palmitoleic, and oleic acids, for the Timor Hybrid group [103]. Metabolomic profiling has been also used to identify differences in Philippine coffee to distinguish between Coffea arabica (Arabica) and Coffea canephora var. Robusta coffees [41], sensory values [104], geographic diversity of Indonesian arabica coffees [105], defective coffee seeds of Brazilian coffee [101], and degrees of coffee adulteration in civet coffee blends [39]; discriminate Arabica and Robusta blends [106,107,108]; compare caffeinated and decaffeinated coffee [37]; and compare fermented coffees [109]. In keeping with published studies, the two Hawai‘i-grown coffee varieties also demonstrate distinct profiles of several metabolites in green beans as well as roasted beans. As previously noted by others [33], roasting significantly reduced chlorogenic acid and increased caffeine in both coffee varieties. Among the several coffee polyphenols, chlorogenic acid is most affected by roasting levels [110]. Compared to Waialua coffee, Kaua’i coffee had higher concentrations of pyrogallol, which is known to inhibit cellular glutathione (GSH) and induce apoptosis (cell death) in human platelets [111]. Lipid content in coffee beans accounts for about 10–$17\%$ of their dry weight, and most of these lipids are triacylglycerols (TAGs) and small quantities of phospholipids (PLs). TAGs contain both saturated and unsaturated fatty acids (FAs), with unsaturated FAs being oleic (18:1(n-9)), linoleic (18:2(n-6)), and linolenic (18:3(n-3)) [112]. Coffee lipids are major contributors to organoleptic properties, quality, and formation and stabilization of coffee foam and emulsion and influence flavor and aroma, specifically in espresso coffees [113,114,115]. Lipids in coffee beans are influenced not only by growing conditions such as altitude, shade, and temperature [115,116,117], but also by genotype [113,116,117,118]. For example, Arabica coffees generally have lipid contents of $15\%$, while Robusta has about $10\%$ lipids [113]. Palmitic (16:0), arachidic (20:0), stearic (18:0), and linolenic (18:3) acid contents are higher and oleic acid (18:1) content is lower in Arabica compared to Robusta [113,119,120]. Considering the fact that lipids play an important role in coffee bean development, coffee brew properties, and the effects of coffee on human health, few studies have focused on lipidomic profiles in coffee beans [112,113,121]). To our knowledge, our study is the first to investigate the effect of coffee varieties, roasting, and brewing on the lipidomic profiles of coffee brews. In our study, palmitic (16:0), stearic (18:0), and oleic (18:1) acids were higher in the Kaua’i compared to Waialua roasted coffee brews. No major differences in these FAs were noted in green coffee beans. Both green and roasted Waialua and Kaua’i coffee brews also differed in a few phospholipids (PC; 34:1, 36:2, 34:2), phosphatidyl ethanolamine (1-PE. 17:$\frac{0}{17}$:0), and several unannotated lipids that warrant further investigation into their identities. Biogenic amines (BAs) in food and beverages are mainly formed due to the decarboxylation or amination of proteins and/or free amino acids via microbial or natural enzyme activity. Putrescine, spermidine, spermine, and serotonin are the most abundant BAs in coffee beans and coffee beverages, while cadaverine and tyramine are present in smaller amounts [122,123]. Processing methods of unripe coffee beans can affect the final levels of some BAs. Histamine, tryptamine, and cadaverine were detected in low-quality and defective coffee beans. The presence of BAs is an indicator of undesired microbial activity and at high concentrations can be toxic to humans [29,124,125]. BA concentrations have been studied to identify coffee origins, e.g., Asia, South America, and Africa [126]. Putrescine is the most abundant amine in both Robusta and Arabica coffee, followed by spermidine, spermine, and serotonin, while cadaverine and tyramine are generally present in smaller amounts [127,128,129,130]. Putrescine is used to discriminate coffee species, while tyramine is considered a chemical marker for Angolan robusta, and low levels of histamine are present in low-quality or immature coffee beans [129,131]. In our study, although brews of green beans or the roasted coffee of both varieties demonstrated differences in several biogenic amines, putrescine, spermidine, spermine, and serotonin, cadaverine and tyramine were not detected. The effect of roasting on BAs is still controversial since some studies report a reduction in BAs while other studies indicate high BA levels after roasting [29,122]. Overall, brewed coffee contains a very low level of BAs compared to green or roasted ground coffee beans [29]. Metabolites, lipids, and BA composition are also affected by methods of brewing coffee, as noted in 76 commercial coffees [36]. Studies have indicated that different brewing methods affect not only the chemical composition but also the aroma [36,63]. Metabolite variations are also influenced by temperature as in hot or cold brews [86], brewing time, or the size of ground solids [45,58]. In contrast to studies by Rothwell et al. [ 36], studies by Kim et al. [ 33] indicated that the composition of bioactive compounds was dependent upon roasting rather than brewing methods. Kim et al. [ 33] demonstrated significantly different levels of resveratrol, eugenol, ferulic acid, and vanillin between hot and cold brews, but only for dark roasted coffee. In our studies, we did not detect resveratrol, eugenol, or vanillin. However, ferulic acid was highest in our coffees brewed by filter mesh (hot brewing method) and French press (cold brewing temperatures) as compared to cold brew and filter paper (hot brew) methods. Differences between our study and that of Kim et al. [ 33] could be attributed to the type of coffee, roasting level, or temperatures of brewing. Similar to Kim et al. ’s study [33], caffeine levels were unaffected by brewing methods in our study. Ferulic acid is known for its antioxidant, anti-inflammatory, and antimicrobial properties [33]. In our study, chlorogenic acid was the lowest in cold-brewed coffee compared to other brewing methods. Caffeine levels were unaffected by brewing methods, which is similar to the result noted by Kim et al. [ 33]. Among several biological properties, the health benefits of coffee are attributed to its antioxidant capacity [43,64,80,81,83,132,133,134,135,136]. A large variation in antioxidant capacity has been observed among commercially brewed coffees [135] as well as variety and origin of coffee [137], degree of roasting [138], type of roast and blend [139], and brewing methods [43,64,81,136,140]. Among the 12 varieties of Arabica and 1 variety of Robusta studied by Priftis et al. [ 132], roasting increased the antioxidant capacity in 1 coffee variety and reduced it in 5 varieties of Arabica and resulted in no difference in the other varieties. On the other hand, slower roasting speeds and dark roasts reduced antioxidant capacity, and lightly roasted coffee had more antioxidants [83,133]. Besides roasting conditions, the preparation of coffee brews with different coffeemakers also influenced their antioxidant capacity. Mocha coffee had the highest antioxidant capacity compared to filter, plunger, and espresso coffees [134]. Another study indicated that cappuccino, a milk-based coffee drink, had the highest antioxidant activity as compared to instant coffee and Turkish coffee [141]. Wolska et al. [ 80] further demonstrated that brewing methods did not affect the antioxidant capacity of Robusta coffee brews, but simple infusion had the highest activity in Arabica brews prepared by French press, espresso maker, overflow espresso, and Turkish coffee. In contrast to the results of Wolska et al. [ 80], antioxidant capacity was unaffected by coffee types in our study but was influenced by brewing methods. Similar to the study by Perez-Martinez et al. [ 134], we also demonstrate that filter coffee had lower antioxidant capacity compared to other brews. Studies have also indicated that besides antioxidant capacity, brewing methods also influence the aroma and mineral contents of coffee [64,142]. To date, one study has demonstrated that among the five brews from a coffee shop in Szczecin, Poland, coffee prepared by espresso machine had the lowest antioxidant capacity, followed by French press < drip = simple infusion coffee < Aeropress [64]. Furthermore, coffees prepared by simple infusion and Aeropress had higher levels of magnesium, manganese, chromium, cobalt, and potassium, while the drip brew had higher silicon levels [64]. Similar to Janda et al. [ 64], our study also indicated that French press coffee had a lower antioxidant capacity. We also observed an effect of brewing methods on the mineral contents of the coffee. Although the results are incomparable between our study and that of Janda et al. [ 64] due to differences in brewing methods, the individual mineral values in French press-brewed coffees are different in the two studies possibly due to the coffee variety or degree of roasting. ## 5. Conclusions Our studies demonstrate that levels of global metabolites, lipids, and biogenic amines were significantly influenced by roasting and differed between the two Hawai‘i-grown coffee varieties: “Kona Typica” and “Yellow Catuai”. Interestingly, the mineral contents and the antioxidant capacity of both these coffee varieties were influenced only by the brewing methods. Total minerals were higher in cold brews compared to other brewing methods. Similarly, regardless of the coffee variety, cold brew coffees had the highest antioxidant capacity, followed by coffees brewed by the French press method. Future studies are warranted to understand and extrapolate the influence of brewing methods on antioxidant capacity in vivo. ## References 1. News L.A.. Global Coffee Production Expected to Recover in 2022/23 with Brazil Crop 2. Halstead T.. Coffee: World Markets and Trade. Worls Production, Markets and Trade Report 3. 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--- title: Applying Reinforcement Learning for Enhanced Cybersecurity against Adversarial Simulation authors: - Sang Ho Oh - Min Ki Jeong - Hyung Chan Kim - Jongyoul Park journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10051329 doi: 10.3390/s23063000 license: CC BY 4.0 --- # Applying Reinforcement Learning for Enhanced Cybersecurity against Adversarial Simulation ## Abstract Cybersecurity is a growing concern in today’s interconnected world. Traditional cybersecurity approaches, such as signature-based detection and rule-based firewalls, are often limited in their ability to effectively respond to evolving and sophisticated cyber threats. Reinforcement learning (RL) has shown great potential in solving complex decision-making problems in various domains, including cybersecurity. However, there are significant challenges to overcome, such as the lack of sufficient training data and the difficulty of modeling complex and dynamic attack scenarios hindering researchers’ ability to address real-world challenges and advance the state of the art in RL cyber applications. In this work, we applied a deep RL (DRL) framework in adversarial cyber-attack simulation to enhance cybersecurity. Our framework uses an agent-based model to continuously learn from and adapt to the dynamic and uncertain environment of network security. The agent decides on the optimal attack actions to take based on the state of the network and the rewards it receives for its decisions. Our experiments on synthetic network security show that the DRL approach outperforms existing methods in terms of learning optimal attack actions. Our framework represents a promising step towards the development of more effective and dynamic cybersecurity solutions. ## 1. Introduction To improve the security of networked systems, red team exercises are commonly used to assess the effectiveness of their defenses by simulating different cyber-attacks. These exercises might include adversary profiles to mimic genuine advanced persistent threats and evaluate the system’s capability to safeguard against various tactics, techniques, and procedures employed by advanced attackers [1]. However, red team exercises can be time-consuming and necessitate specialized human expertise, making them an expensive means of assessing cybersecurity. To improve the efficiency of red teaming, tools such as emulators have emerged to automate these exercises and streamline the attack simulation process [2]. Despite the automation capabilities of these red teaming tools, human experts are still critical in the planning and decision-making stages of the exercises, such as organizing tactics, techniques, and procedures through the different stages of the attack simulation campaign. These tools, such as staging frameworks, enabling scripts, and execution payloads, are designed to support human experts and simplify the red teaming process. Adversarial simulation has become increasingly important as cyber threats continue to evolve and become more sophisticated. Traditional security systems based on predefined rules and signatures are often insufficient to defend against advanced and adaptive threats [3]. Machine learning (ML) models, on the other hand, can provide a more flexible and adaptive solution to cybersecurity by learning from historical data and evolving over time to better detect and respond to new threats [4,5,6]. As interest in using ML for cybersecurity grows, the significance of adversarial cyber-attacks against ML-based applications has become more prevalent. Adversarial simulation for cybersecurity involves the use of ML techniques to model and simulate potential cyber-attacks on a system in order to train ML models to identify and respond to these attacks in real time. This allows organizations to better understand and prepare for potential cyber threats and improve their overall cybersecurity posture. However, traditional ML-based applications have limitations as they are typically trained on historical data and have limited generalizability [7,8,9]. The rapid progress of artificial intelligence (AI) presents the possibility of AI-assisted or self-governing AI red teaming, where AI can use its superior decision-making ability, learned through AI training, to create new attack methods against complex cybersystems that human red team experts may not have considered yet [10]. This leads to our motivation to involve teaching red agents to identify and optimize attack operations in a network using deep reinforcement learning (DRL) algorithms, which is an improved method over the traditional ML model to enhance adversarial cyber-attack simulation to find more robust solutions. Reinforcement learning (RL) is a technique that can help create autonomous agents that can make optimal sequential decisions in complex and uncertain environments. Open-source learning environments, such as OpenAIGym have increased the possibilities of RL research in different application domains [11]. In recent years, the use of reinforcement learning in adversarial simulation in cybersecurity has become more popular [12,13,14,15,16]. With cyber-attacks becoming more sophisticated and the challenge of designing effective defenses against them, researchers have turned to ML techniques such as RL to develop more resilient and adaptable security systems. RL algorithms can learn optimal strategies for defending against attacks, adapting to changing threats, and evolving attack techniques. By repeatedly playing a game of offense and defense, an RL agent can learn to anticipate and defend against various types of attacks, including zero-day exploits [17]. This approach has been shown to be effective in detecting and mitigating cyber-attacks in a variety of settings, including web applications, network intrusion detection, and malware analysis. The RL has the potential to enhance cybersecurity by enabling adaptive and automated defense systems that can learn from experience and respond to changing cyber threats in real time [18]. However, there are still significant challenges that need to be addressed to effectively apply RL in the context of cybersecurity. One of the primary challenges is the lack of training data [5,19]. Adversarial cyber-attack scenarios are often rare and complex, making it difficult to collect sufficient data to train RL models effectively. This can result in models that are underfit, meaning they do not capture the full complexity of the real-world scenarios they are designed to address. Another challenge is the difficulty of modeling complex and dynamic attack scenarios [20,21]. Cyber-attacks can be highly dynamic and adaptive, making it challenging to develop accurate models that can effectively capture the full range of potential attack strategies and tactics. This can lead to models that are overfit, meaning they are too narrowly focused on specific attack scenarios and may not generalize well to new or unexpected attack scenarios. In addition to these challenges, there is also a shortage of open-source cybersecurity-based RL experimentation environments that can help researchers address real-world challenges and improve the state of the art in RL cyber applications [22]. Without access to realistic and scalable experimentation environments, researchers may struggle to develop and test new RL-based approaches to cybersecurity. Despite these challenges, there are efforts underway to address these issues and advance the use of RL in cybersecurity. Elderman et al. focus on cyber-security simulations in networks modeled as a Markov game with incomplete information and stochastic elements [23]. They showed the resulting game that is an adversarial sequential decision-making problem played with two agents, the attacker and the defender. Additionally, Applebaum et al. provide an analysis of autonomous agents trained with RL through a series of experiments examining a range of network scenarios [24]. Additionally, Microsoft released CyberBattleSim, which uses a Python-based OpenAIGym interface to create an initial, abstract simulation-based experimentation research platform for training automated agents using RL [25]. This platform can provide a baseline for researchers to conduct experiments, test different approaches, and develop new models that can be applied to real-world cybersecurity challenges. As technology advances, we can expect to see more RL experimentation environments that can help enhance the state of the art in RL cyber applications. In this research, we aim to demonstrate the effectiveness of applying DRL to adversarial simulation in cybersecurity by performing the red teaming simulation that shows significant learning curves of the agent. We use simulations to model cyber-attacks and evaluate the performance. The results showed that the DRL policy was able to learn and execute effective strategies for successfully infiltrating a simulated cyber environment, highlighting the potential for DRL algorithms to be used for both defensive and offensive purposes in the field of cybersecurity. The research involved the application of DRL to adversarial cyber-attack simulation. The use of DRL in this context allows for the creation of adaptive and automated defense systems that can learn from experience and respond to changing cyber threats in real time. One of the key contributions of this research is the significant results achieved by DRL. By modeling and simulating potential cyber-attacks and their effects on a system, the DRL-based defense systems were able to identify and respond to attacks in real time, enhancing the overall cybersecurity posture of the system. In addition to applying DRL to adversarial cyber-attack simulation, the researchers also experimented with various parameters in DRL, such as values of epsilon and epsilon decay. By varying these parameters and performing several simulations on each parameter value, the researchers were able to identify appropriate values of epsilon and epsilon decay that led to robust convergence. This finding is significant as it allows for the development of more effective and efficient DRL-based defense systems, with parameters that can be fine-tuned to specific cyber threat scenarios. Overall, the research demonstrates the potential of DRL-based approaches to enhance cybersecurity and highlights the importance of parameter tuning in achieving robust convergence and optimal performance of DRL-based defense systems in the context of adversarial cyber-attack simulation. We organize our paper as follows. We cover the materials and methods, which explain the DRL algorithm, deep Q-learning, and simulation settings in Section 2. Section 3 presents the research results, which show the reward obtained by agents for each step. In Section 4, we discuss the results, then present conclusions in Section 5. ## 2. Materials and Methods RL methods are able to discover approximate solutions for Markov decision processes (MDPs) by teaching policies that target the maximization of the expected reward over a specific time horizon [26]. Similar to MDPs, RL makes use of the state, action, and reward components, but instead of exhaustively searching the state space for the optimal policy, an agent interacts with the environment and chooses actions based on its current state and past rewards or penalties. This study employs a simulated virtual environment for the agent to interact with, rather than a real network, resulting in quicker policy learning. Nonetheless, using a simulation necessitates certain simplifications that should be taken into account when implementing the learned policy on a real network. ## 2.1. Environment Settings for Simulation The purpose of the experiment was to verify the applicability of reinforcement learning algorithms for simulating adversarial attacks in cybersecurity. We utilized the CyberBattleSim library to implement the nodes in the virtual environment to simulate attack scenarios, then apply a reinforcement learning algorithm to derive the results. To achieve this, we set our environment as a company with computers to attack, then the following steps were taken:Investigation of vulnerabilities that may exist in virtual company computers. Configuration of nodes based on the findings from the investigation. Creation of a virtual environment to simulate the acquisition of confidential documents hidden within the company’s computers. Implementation of reinforcement learning to determine the effectiveness of the simulated environment. ## 2.2. Deep Q-Learning (DQL) In cases where the transition function or probability distribution of a state variable is known, Q-learning is capable of determining the best course of action. Q-learning is based on the estimation of a value function, which is a set of Q-values. The Q-learning method [27] calculates Q-values for each state–action combination (st,at). Once the final Q-values have been determined, the state of the environment can be used to select the optimal action. At the start of the process, Q-values are initialized to an arbitrary real number. In iteration t, the agent evaluates the reward in each (st,at) combination. The algorithm updates the Q-values iteratively based on the immediate reward rt and the Q-values of the next state–action combination Q(st+1,at+1), as shown in Equation [1]. The discount factor, γ, which has a range of 0 to 1, regulates the effect of future rewards on current rewards. [ 1]Q(st,at)←rt+γmaxat+1{Q(st+1,at+1)} Regardless of the policy being followed, the Q-values are adjusted so that they eventually reach an optimal action-value function Q* [28]. One of the interesting features of Q-learning is that it can produce state–action pairs using various sampling techniques. A common sampling method is the ε-greedy action selection, as shown in Equation [2], where ε is a value in the range (0, 1]. [ 2]at={argmaxa∈AQ(st,a)a ~ A with probability 1−ε,otherwise. The function approximator, such as a deep neural network, can be utilized to estimate the Q-values, instead of using a Q-table [29,30]. The parameter set for the approximator is denoted as θ and the network is represented as Q(s,a;θ). The network is then optimized to estimate the Q-values, as defined in Equation [1] [30,31]. In DQL, there are two networks involved, the Q-network (Q(s,a;θ)) and a target Q-network (Q^(s,a;θ−)) [29,32]. The Q-network is used to determine the optimal action and the target Q-network is used to generate the target value for updating the parameters (θ) of the Q-network. The Q-network is updated at each iteration by minimizing the mean-square error between the target Q-network (Q^(s′,a′;θ−)) and the current Q-network (Q(s,a;θ)) using a loss function, as described in Equation [3]. [ 3]Li(θi)=E[(r+γargmaxa′Q^(s′,a′;θ−)−Q(s,a;θi))2] The exploration and exploitation trade-off must be carefully considered in a DQL as exploration evaluates potential actions while exploitation utilizes previous experience. The DQL also utilizes replay memory, which is a database storing the agent’s experiences [32]. To update the Q-networks, experiences are randomly selected from the replay memory [33]. ## 2.2.1. States In our research, the state is composed of various values such as the node’s name, information, and vulnerability. These values provide the agent with a complete understanding of the current state of the environment. Additionally, there is a reward associated with occupying the node, which serves as a motivation for the agent to take specific actions. The reward can be seen as a reinforcement signal that guides the agent towards optimal behavior. The state, along with the available actions and their corresponding rewards, forms the basis for decision-making in DQL. ## 2.2.2. Actions The attacker has three options for actions: [1] exploiting a vulnerability that is local to the system, [2] exploiting a vulnerability that is remotely accessible, or [3] connecting to another host through lateral movement. The actions require different parameters, such as specifying which vulnerability to use or which user credentials to access. There are also specific requirements that must be met before each action can be taken, such as discovering the target host or having knowledge of the necessary credentials. The consequences of each action can include discovering new hosts, obtaining sensitive information, or gaining control of another host. ## 2.2.3. Rewards The reward is the feedback that the environment provides in response to the agent’s actions, and it plays a crucial role in shaping the interaction between the agent and the environment. This research considers both the cost of the attacker’s actions and the impact of action utilization on the penetration testing process when designing the reward system. The cost of an action and its variation are used to calculate the environmental reward value for the agent’s current action, determining the reward or penalty associated with its use. Specifically, this study provides a positive reward when the attacker successfully acquires the node and a negative reward otherwise. ## 2.3. Simulation Procedure The simulations in the system take place as attacker games, played over a specific network structure. Each game has a set number of turns or iterations, which end either when the attacker has successfully completed their objective or when the maximum number of turns has been reached. During each turn, the attacker takes an action and receives updated information about the environment as well as a reward based on pre-defined values linked to the action taken, the outcome, and the importance of the target host. If the attacker accomplishes their objective, they receive a significant reward and the episode comes to an end. Here is the simulation scenario:The first entry point is allowing remote connection to a conference room PC for a meeting. It is assumed that the administrators have uploaded passwords and credential tokens related to sudo permissions in a GitHub private repository. A GitHub token is found in the bash history of the conference room PC and can be used to access the GitHub private repository. Using the obtained sudo permissions from GitHub, the attacker tries to access files. Using the sudo permissions, the attacker accesses the internet browser’s cookie history and retrieves the administrator’s session ID.The obtained session information is used to access the company PC as an administrator and obtain confidential information in the confidential folder. The terminal condition is that the execution stops if the attacker obtains the confidential information or if the iteration exceeds 500 steps. ## 3. Results In this section, we present the cumulative reward outcomes of our DQL agent in comparison to random search. The results demonstrate that utilizing DRL methods enabled the agent to acquire an efficient attack technique within a short learning period. The findings indicate that the RL policy managed to acquire and execute effective tactics for accomplishing the goal of infiltrating a simulated cyber environment, underscoring the potential of RL algorithms to be utilized for both offensive and defensive purposes in the field of cybersecurity. The graphs presented in this section will show the reward obtained by agents for each step. As the step progresses, the agent will learn in the direction of obtaining a higher reward, and the interesting part to observe here is the difference in reward between DQL and random search as the step progresses. ## 3.1. DQL vs. Random Search Our research aimed to evaluate the performance of two policies, the random policy and the DQL policy. In Figure 1, the results of the experiment are shown in a graph, where the blue line represents the reward obtained using the random policy, and the orange line represents the reward obtained using the DQL policy. The agent’s objective was to reach the terminal condition, a single path, while maximizing the reward within 500 iteration steps. It is clear from the graph that the DQL policy outperforms the random policy, as the orange line gradually increases as step progresses, indicating a continual improvement in the decision-making abilities of the agent. Table 1 provides statistics of the number of iteration steps taken by each method to reach the terminal condition, which signifies convergence to the optimal solution. By analyzing the table, we can assess the speed at which each method meets the convergence condition. On average, DQL takes only 146.14 steps to converge, while random search takes an average of 425.30 steps. Moreover, DQL has demonstrated a minimum of only 24 steps to reach the convergence condition, whereas random search took 238 steps. Therefore, the table highlights the superiority of DQL over random search in terms of convergence speed, which is a critical factor in achieving efficient and effective learning in RL applications. This result demonstrates that the DQL policy is a more effective approach compared to the random policy. The DQL policy’s ability to continually improve its decision-making over time results in a more efficient and effective agent that is able to reach the terminal condition while maximizing the reward. In Figure 1, we demonstrate that the DQL policy outperformed compared to random policy in terms of cumulative reward by reaching the terminal condition. In Figure 2, we experiment with the exploiting (pre-trained) DQL compared with random search. The terminal condition of the experiment was to reach a single path and achieve the highest possible reward within 500 iteration steps. As we can observe in Figure 2, the agent trained with the exploiting DQL policy was able to reach this terminal condition within the allotted steps and achieve a higher reward compared to the random policy. In contrast, the agent using the random policy was not able to satisfy the terminal condition and achieved a lower reward. This supports the conclusion that the agent trained with the DQL policy was able to effectively learn and improve its decision-making capabilities. Additionally, we found that the iteration step comes to an end faster in the exploiting DQL policy compared to the random search policy, as shown in Figure 3. The results of the iteration step in a shorter period of time in the DQL policy indicate that it has the ability to identify and reach the terminal condition more efficiently. The ability to reach the terminal condition faster in the DQL policy is an important factor to consider, as it provides evidence that the training process has effectively improved the policy’s decision-making capabilities. In other words, the policy has learned to make the right decisions more quickly and with greater accuracy, resulting in a faster resolution of the episode. Table 2 presents statistical information on the number of iteration steps taken by each method to reach the terminal condition, indicating convergence to the optimal solution. The results show that exploiting DQL takes an average of only 77.90 steps to converge, which is significantly faster than normal DQL, while random search takes an average of 425.30 steps. Additionally, DQL has demonstrated a minimum of 34 steps to reach the convergence condition, whereas random search took 238 steps. Thus, Table 2 emphasizes the outstanding performance of exploiting DQL over random search in terms of convergence speed. These results highlight the importance of exploring novel techniques, such as exploiting DQL, to enhance the performance of RL algorithms. Furthermore, this ability to reach the terminal condition more efficiently also suggests that the policy is more capable of navigating the environment in a more optimized way, reducing the number of iteration steps required to complete an episode. This not only leads to a faster resolution of the episode but also results in a more efficient use of resources and a reduction in computational costs. In conclusion, the results of the experiment provide valuable insights into the effectiveness of the training process, demonstrating the improvement in decision-making capabilities and efficiency in reaching the terminal condition in the trained policy. These findings highlight the importance of using training methods to improve the performance of an agent in an RL environment. ## 3.2. Comparison of Learning Rates Based on Epsilon In this experiment, we investigated the effect of epsilon in DQL on the learning rate of the agent. By comparing the learning rate for different epsilon values, we were able to observe how the exploration–exploitation trade-off impacted the overall performance of the agent. The results of this comparison provide insights into how the choice of epsilon value can impact the learning process and inform future design decisions. In Figure 4, we compared the results of cumulative rewards by varying the initial value of epsilon. The values used were 0.1, 0.3, and 0.9, which are blue, orange, and green, respectively. The objective of the agent was to reach the terminal condition while maximizing the reward within 500 iteration steps. The comparison of the results based on the epsilon value was conducted to determine the impact on the agent’s learning rate and decision-making abilities. The initial value of epsilon determines the exploration–exploitation trade-off in the reinforcement learning process. A higher initial value of epsilon would result in more exploration and less exploitation, while a lower initial value of epsilon would result in more exploitation and less exploration. The results show that a suitable initial value of epsilon is essential for fast convergence of the agent towards an optimal policy. In Figure 4, the green graph indicates that the agent with a high initial value of epsilon takes longer to converge and shows a lot of fluctuations in its reward trajectory. This can be attributed to the high exploration rate, which leads to inefficient exploitation of the learned policy. On the other hand, the blue and orange graphs show faster convergence and less fluctuation, indicating that the agents with lower initial values of epsilon are better able to exploit the learned policy. Therefore, it can be concluded that selecting an appropriate initial value of epsilon is important for efficient and stable learning of a good policy. A suitable initial value of epsilon ensures that the agent converges quickly and performs optimally, without being too unstable. Table 3 provides statistics on the number of iteration steps taken by each epsilon value and random search method to reach the terminal condition. The results reveal that the epsilon value of 0.1, 0.3, and 0.9 took an average of 123.30, 134.10, and 112.60 steps, respectively, while random search took 473.10 steps. Although DQL outperforms random search, it is crucial to select appropriate epsilon values depending on the training priority in balancing the exploration and exploitation trade-off to achieve optimal performance in RL applications. Higher epsilon values are associated with a high exploration rate, which can result in less exploitation of the learned policy. On the other hand, lower epsilon values indicate faster convergence and less fluctuation, suggesting that the agent can exploit the learned policy effectively. ## 3.3. Cumulative Reward vs. Step with Fixed Epsilon and Variable Epsilon Decay In this section, we aimed to investigate the impact of epsilon decay on the performance of the DQL algorithm. We adjusted the degree of decay, which regulates the rate at which epsilon decreases. The results of this adjustment were recorded and analyzed to determine the optimal decay rate for the DQL algorithm. The impact of the epsilon decay rate on the convergence rate and stability of the learned policy is analyzed in Figure 5. We experimented with epsilon decay of 500, 2000, and 10,000, which are the blue, orange, and green lines in Figure 5, respectively. The results showed that a lower decay rate resulted in a slower convergence rate and a more unstable policy, while a higher epsilon decay rate resulted in a faster convergence rate and a more stable policy. This highlights the importance of carefully choosing the epsilon decay rate to ensure that the DQL algorithm could learn the optimal policy effectively. We investigated the impact of epsilon decay on the rate of epsilon value in Figure 6. Our findings showed that as decay increased, epsilon decreased at a slower rate. This resulted in a model that tended to exhibit greater randomness in its actions even when the episode number was sufficiently high, and the agent had learned enough. This highlights the importance of considering the decay rate when training the agent to ensure it does not exhibit random behavior at the end of the training process. The statistics of the number of iteration steps taken by each epsilon decay to reach the terminal condition shown in Table 4. The epsilon decay of 500, 2000, and 10,000 takes an average of 67.90, 152.70, and 161.90 steps, respectively, while random search takes 472.2 steps. A lower epsilon decay resulted in a suboptimal policy, while a higher epsilon decay resulted in a poorly converged policy. Therefore, it is important to carefully choose the decay rate to ensure that the DQL algorithm is able to learn the optimal policy. ## 4. Discussion The findings from our experiment clearly demonstrate the effectiveness of utilizing DRL methods over random search in the task of infiltrating a simulated cyber environment. As the number of iterations increased, the DQL policy displayed a remarkable improvement in decision-making, which resulted in a higher reward compared to the random policy. This can be observed from Section 3.1, where the DQL policy consistently outperformed the random policy in terms of convergence speed, with an average of 146.14 steps to reach the terminal condition compared to 425.30 steps for random search. The efficiency of the DQL policy in reaching the terminal condition is reflected in the faster resolution of the episode, more efficient use of resources, and reduction in computational costs. Exploiting DQL further improved the performance of the algorithm, with an average of only 77.90 steps to reach the terminal condition. This result highlights the potential of novel techniques, such as exploiting DQL, to enhance the performance of RL algorithms in the field of cybersecurity. We also examined the impact of the initial value of epsilon on the convergence and stability of the learned policy. The epsilon value plays a critical role in balancing the exploration and exploitation trade-off in RL applications. Our results indicate that an epsilon value of 0.1, 0.3, and 0.9 took an average of 123.30, 134.10, and 112.60 steps, respectively, to reach the terminal condition, while random search took 473.10 steps. These results showed that the initial value of epsilon is a critical factor that affects the convergence and stability of the policy. Our results demonstrated that a slower convergence rate led to more fluctuating behavior, while a faster convergence rate led to less fluctuating behavior. Moreover, we also analyzed the impact of the epsilon decay rate on the performance of the DQL algorithm. Our results indicate epsilon decay of 500, 2000, and 10,000 takes an average of 67.90, 152.70, and 161.90 steps, respectively, while random search takes 472.2 steps. A lower epsilon decay resulted in a suboptimal policy, whereas a higher epsilon decay resulted in a poorly converged policy. Therefore, careful selection of the decay rate is crucial to ensure that the DQL algorithm is able to learn the optimal policy. Additionally, the results of our experiments have shown the impact of epsilon decay. When epsilon decay increased, epsilon decreased at a slower rate. This means that the agent has a greater likelihood of selecting random actions, even in the later stages of learning, when it should have learned the best policy. This phenomenon can be seen as the agent continues to select random actions even after enough episodes have passed for it to be considered well trained. One possible explanation for this behavior is that the agent continues to explore its environment even after it has learned a good policy. This can be seen as a benefit, as it allows the agent to refine its policy in response to changes in its environment. However, it can also result in suboptimal performance if the agent becomes too confident in its actions and fails to account for changes in its environment. Our research highlights the significance of considering the decay rate carefully when training reinforcement learning agents. Finding the right balance between exploration and exploitation is crucial for optimal performance, which may vary based on the task and environment. Our results show the superiority of the DQL policy over the random policy in terms of reward and convergence rate, and there is room for further improvement by optimizing the parameters and hyperparameters of the DQL algorithm or exploring alternative reinforcement learning algorithms. ## 5. Conclusions Our research findings provide clear evidence of the superiority of the DQL policy over the random policy in terms of both reward and convergence rate. The DQL policy exhibited a significant improvement in decision-making ability as the number of iterations increased, resulting in a higher reward compared to the random policy. Our analysis of the effect of the initial value of epsilon on the convergence and stability of the learned policy revealed that the initial value of epsilon determines the speed of convergence and stability. Additionally, our results showed that epsilon decay affects the rate of decrease in epsilon, and a higher epsilon decay leads to a slower decrease in epsilon. This can cause the agent to continue making random actions even after it has been well trained. While this exploration can refine the policy, it can also result in suboptimal performance if the agent becomes too confident in its actions. Future studies should explore alternative decay strategies that balance the need for exploration with the need for exploitation. In conclusion, achieving the right balance between exploration and exploitation is crucial for optimal performance and may vary depending on the specific task and environment. There is an opportunity for further optimization of the parameters and hyperparameters of the DQL algorithm, and exploring alternative reinforcement learning algorithms could lead to even more effective policies and provide valuable insights into the field of reinforcement learning. It is important to note that while our findings are promising, the proposed DQL algorithm has limitations and may not be applicable to all scenarios. Future research should investigate the limitations and applicability of the DQL algorithm in different contexts. ## 6. Limitations and Future Works Our limitation of this research is that, since this research focused on the application of the RL algorithm to the cybersecurity field, it was conducted in a simulated environment that did not capture the complexity of real-world cyber-attacks, which may include multiple attackers and defenders, various attack vectors, and dynamic changes in the environment. Furthermore, the impact of varying the network architecture was not investigated in this study, and it is possible that using more complex network architectures could further improve the performance of the algorithm. There is a lot of scope for further exploration in the field of utilizing DRL methods for cybersecurity tasks. One possible direction for future research is to incorporate more complex network architectures such as convolutional neural networks (CNNs) or recurrent neural networks (RNNs) to improve the performance of the DQL algorithm. Additionally, different learning techniques such as actor–critic or policy gradient methods could be explored to determine whether they outperform DQL in this application. Another direction is to examine the performance of the algorithm on real-world cybersecurity datasets and applications. ## References 1. Li L., Fayad R., Taylor A.. Cygil: A Cyber Gym for Training Autonomous Agents over Emulated Network Systems. arXiv (2021.0) 2. Yoo J.D., Park E., Lee G., Ahn M.K., Kim D., Seo S., Kim H.K.. Cyber Attack and Defense Emulation Agents. Appl. Sci. (2020.0) 10. DOI: 10.3390/app10062140 3. Alshamrani A., Myneni S., Chowdhary A., Huang D.. A Survey on Advanced Persistent Threats: Techniques, Solutions, Challenges, and Research Opportunities. IEEE Commun. Surv. 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--- title: Vertical Sleeve Gastrectomy Offers Protection against Disturbed Flow-Induced Atherosclerosis in High-Fat Diet-Fed Mice authors: - Jih-Hua Wei - Wei-Jei Lee - Jing-Lin Luo - Hsin-Lei Huang - Shen-Chih Wang - Ruey-Hsing Chou - Po-Hsun Huang - Shing-Jong Lin journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051344 doi: 10.3390/ijms24065669 license: CC BY 4.0 --- # Vertical Sleeve Gastrectomy Offers Protection against Disturbed Flow-Induced Atherosclerosis in High-Fat Diet-Fed Mice ## Abstract Bariatric surgery reduces body weight, enhances metabolic and diabetic control, and improves outcomes on obesity-related comorbidities. However, the mechanisms mediating this protection against cardiovascular diseases remain unclear. We investigated the effect of sleeve gastrectomy (SG) on vascular protection in response to shear stress-induced atherosclerosis using an overweighted and carotid artery ligation mouse model. Eight-week-old male wild-type mice (C57BL/6J) were fed a high-fat diet (HFD) for two weeks to induce weight gain and dysmetabolism. SG was performed in HFD-fed mice. Two weeks after the SG procedure, partial carotid-artery ligation was performed to promote disturbed flow-induced atherosclerosis. Compared with the control mice, HFD-fed wild-type mice exhibited increased body weight, total cholesterol level, hemoglobin A1c, and enhanced insulin resistance; SG significantly reversed these adverse effects. As expected, HFD-fed mice exhibited greater neointimal hyperplasia and atherosclerotic plaques than the control group, and the SG procedure attenuated HFD-promoted ligation-induced neointimal hyperplasia and arterial elastin fragmentation. Besides, HFD promoted ligation-induced macrophage infiltration, matrix metalloproteinase-9 expression, upregulation of inflammatory cytokines, and increased vascular endothelial growth factor secretion. SG significantly reduced the above-mentioned effects. Moreover, HFD restriction partially reversed the intimal hyperplasia caused by carotid artery ligation; however, this protective effect was significantly lower than that observed in SG-operated mice. Our study demonstrated that HFD deteriorates shear stress-induced atherosclerosis and SG mitigates vascular remodeling, and this protective effect was not comparable in HFD restriction group. These findings provide a rationale for using bariatric surgery to counter atherosclerosis in morbid obesity. ## 1. Introduction With the widespread of the western lifestyle, obesity, and in particular extreme obesity, has become a global problem [1]. Importantly, the prevalence of obesity is dramatically increasing in developed and developing countries in the past decades. Approximately one-third of US residents have a body mass index (BMI) exceeding 30; $5\%$ to $10\%$ have a BMI of more than 40 [2,3,4]. Obesity-induced metabolic syndrome is a potent risk factor for atherosclerotic cardiovascular disease and type 2 diabetes mellitus (T2D) [5]. The long-term results of various non-surgical weight-loss interventions are not satisfactory [6,7]. Obesity needs to be well controlled to reduce the risks of associated co-morbidities [8]. Bariatric surgery can effectively treat obesity and resolve obesity-associated co-morbidities [9,10]. Sleeve gastrectomy (SG), the most commonly performed bariatric surgical remedy for the treatment of morbid obesity worldwide [11], reduces the stomach size by ~$80\%$ after the removal of a large portion of the greater curvature. Bariatric surgery results in an $80\%$ resolution rate for obesity-associated comorbidities such as T2D [10] and lowered cardiovascular risk [12]. Despite the diversity among studies, bariatric surgery is associated with improving subclinical atherosclerosis and endothelial function, which may meaningfully contribute to reducing the CV risk after a successful weight-reduction operation [13]. Bariatric surgical weight loss is associated with favorable vasculature and reduced cardiovascular mortality [14]. Similar to platelets in atherogenesis, coagulation plays a pivotal role in the histopathogenesis of atherosclerosis, plaque formation, and its stability [15]. However, studies on the potential impact of bariatric surgery on vascular remodeling and intimal hyperplasia in response to vascular injury are limited. Previously, we showed the efficacy of metabolic surgery for T2D treatment and the reduction of the risk of cardiovascular diseases by up to $50\%$ for 1 year after surgery [16]. Here, we aimed to investigate the influence of SG on disturbed flow-induced atherosclerosis in a mouse model fed with a high-fat diet (HFD) and underwent partial carotid artery ligation. Furthermore, we sought to identify the beneficial effects of SG, compared to diet restriction, in HFD-fed mice in response to shear stress-induced atherosclerosis. ## 2.1. Effects of SG on Body Weight, Glucose Metabolism, Insulin Resistance, and Cholesterol in HFD-Fed Mice Hyperglycemia and homeostasis model assessment-estimated insulin resistance (HOMA-IR) were significantly induced (p ˂ 0.05) in mice after 2 weeks of HFD consumption (Supplementary Figure S1D–F), however, insulin levels were not altered significantly (Supplementary Figure S1E). After a 2 week-induction of hyperglycemia, the mice were fed HFD throughout the whole study period. HFD-fed mice showed significantly increased body weight, total cholesterol, and fasting glucose levels at the end of the study compared to mice on a chow diet (Figure 1D–I and Supplementary Figure S1). We observed significantly elevated glycated hemoglobin (HBA1c) levels and insulin resistance index as assessed by IPGTT and HOMA-IR after HFD administration (Figure 1E through Figure 1H), indicating that HFD induced obesity-related diabetes and insulin resistance. We then performed the SG and sham operations on HFD-fed mice to investigate the impact of SG on insulin resistance and lipid profiles. HFD-fed mice that underwent SG had significantly reduced body weight, total cholesterol, and fasting glucose levels relative to the HFD-fed sham-operated mice (Figure 1D through Figure 1I and Supplementary Figure S1B,C). Nevertheless, the difference in body weight between mice under restricted HFD and HFD under SG was not significant, which indicated that these metabolic effects were beyond weight reduction. Moreover, SG significantly mitigated insulin resistance as determined by IPGTT, HBA1c, and HOMA-IR in HFD-fed mice. ## 2.2. SG Alleviates HFD-Induced Circulating Inflammatory Cytokines HFD-fed mice exhibited significantly elevated plasma levels of TNF-α, IL-6, MMP-9, and VEGF compared to mice on a normal chow diet before carotid ligation. SG significantly reduced the elevation of cytokines and MMP-9 levels (Figure 2). Furthermore, the plasma levels of TNF-α, IL-6, MMP-9, and VEGF were significantly upregulated after carotid artery ligation in mice on an HFD. Notably, SG significantly mitigated the plasma levels of TNF-α, IL-6, MMP-9, and VEGF. ## 2.3. Effect of SG on Vascular Remodeling after Carotid Artery Ligation As shown in Figure 3, carotid artery ligation induced intimal hyperplasia in mice that were fed a regular chow diet—a phenomenon more prominent in HFD-fed mice. HFD-fed mice that underwent SG before carotid ligation exhibited significantly attenuated intimal hyperplasia, indicating that SG offered protection against restricted blood flow-induced vascular remodeling upon HFD feeding (Figure 3A–C). VVG staining showed that HFD promoted elastic fiber proliferation and arterial fragmentation with loss of elastic lamina integrity in response to carotid ligation compared to mice fed with a regular diet. SG significantly attenuated these adverse effects in HFD-fed mice with carotid ligations (Figure 3D,E). ## 2.4. SG Decreased the Inflammatory Expression of CD68, and TNF-α, MMP-9, and VEGF Protein Expression after Carotid Ligation Carotid artery immunostaining revealed markedly increased macrophage infiltration after HFD feeding (Figure 4A,B). Additionally, SG significantly ameliorated ox-LDL lesion accumulation after carotid ligation in HFD-fed mice (Supplementary Figure S3A,B). MMP-9 activation was increased after HFD feeding especially after carotid ligation-induced vascular injury (Supplementary Figure S3C,D). SG significantly mitigated the MMP-9 activation in HFD-fed mice. Moreover, the protein levels of TNF-α, MMP-9, and VEGF were markedly activated after carotid artery ligation in mice on an HFD, which were ameliorated by SG in HFD-fed mice with carotid ligation (Figure 4C through Figure 4F). ## 2.5. HFD Restriction Had Less Protective Effect on Carotid-Ligated Vascular Remodeling Than SG Surgery Mice on a restrictive HFD ($30\%$ caloric reduction of HFD) showed a similar body weight reduction as SG-operated HFD-fed mice (Supplementary Figure S1B). HFD induced prominent intimal hyperplasia and elastic fiber proliferation with the loss of elastin integrity after carotid ligation, whereas SG and HFD restriction significantly reduced these effects. However, mice with food restrictions exhibited more prominent intimal hyperplasia and elastic fiber proliferation, compared to SG-operated HFD-fed mice (Supplementary Figure S2). Mice on a restricted HFD with carotid ligation had fewer effects on reducing ox-LDL, CD68, and MMP-9 accumulation (Supplementary Figure S4). We observed macrophage infiltration and MMM-9 upregulation compared to SG-operated HFD-fed mice indicated vascular repair enhancement after injury. ## 3. Discussion In this study, we induced weight gain and obesity-associated Mets, including insulin resistance and enhanced local and systemic inflammation, in wild-type mice by administering an HFD. Consistent with previous studies, elevated body weight and high circulating glucose levels were observed in a wild-type mouse after intake of HFD [17]. Insulin levels increased progressively with time, and the mice exhibited insulin resistance and glucose intolerance under intravenous glucose challenge [17]. The fasting glucose, insulin level, and HOMA-IR were all consistently elevated when the assigned HFD continued beyond the eight weeks [17,18]. Moreover, HFD-fed mice exhibited more significant neointimal hyperplasia and atherosclerotic plaques than the control group. The SG procedure significantly attenuated HFD-promoted ligation-induced neointimal hyperplasia and arterial elastin fragmentation. Interestingly, HFD restriction partially reversed the intimal hyperplasia caused by carotid artery ligation, and this protective effect was lower than that observed in SG-operated mice. These findings provide a rationale for using bariatric surgery to counter atherosclerosis in morbid obesity possibly through the reversal of insulin resistance, leading to the amelioration of neointimal hyperplasia. The cytokines IL-6, TNF-α, and leptin play critical roles in the development of obesity, insulin resistance, and chronic inflammation, which culminate into obesity-related metS [19]. Weight loss after laparoscopic SG is associated with a considerable reduction of body weight and adipokine levels tend toward anti-diabetic and anti-inflammatory profiles [20,21]. We showed that HFD and carotid ligation increased TNF-α, IL-6, MMP-9, and VEGF levels in circulation, indicating an induction of systemic inflammation. Plasma levels of TNF-α, IL-6, MMP-9, and VEGF were significantly upregulated after carotid artery ligation in mice on a normal chow diet and HFD. Obesity-associated inflammation plays a causative role in generating insulin resistance [22,23]. A study in type II diabetic rats showed that insulin resistance is associated with balloon injury-related neointimal hyperplasia [24]. In this study, HFD-enhanced TNF-α, ox-LDL, IL-6, and MMP-9 levels, whereas SG markedly downregulated proinflammatory cytokines and reversed insulin resistance, resulting in vascular protection. This study has shown that insulin resistance is linked to intimal hyperplasia and atherosclerosis. Additionally, SG reverses HFD-induced obesity and reduces vascular inflammation. Moreover, this effect was more pronounced than that induced by dietary restriction. Previous studies had demonstrated lower intimal hyperplasia due to wire-induced carotid artery injury in TNF-α-deficient TNF (-/-) mice. However, TNF-α and NF-κB expression was enhanced in wild-type mice subjected to wire carotid artery injury [25]. Rectenwald et al. demonstrated that TNF-α and IL-1 modulate low shear stress–induced neointimal hyperplasia. This study shows that proinflammatory cytokine signaling directly links biomechanical forces on the vessel wall and vascular remodeling [26]. The mechanisms underlying obesity-associated inflammation remain elusive, and the precise triggers may differ between tissues [27]. The innate immune system is activated in obesity; M1-polarized macrophages that display a pro-inflammatory phenotype and secrete cytokines such as TNF-α are increased during obesity [28]. IL-6, which is synthesized and released by macrophages, smooth muscle cells, and endothelial cells, plays a pivotal role in the early stages of atherosclerotic plaque formation. IL-6 can be resident or trapped in arterial walls, playing an important role in the phenotypic determination of plaque macrophages, polarization and shaping of macrophages, and development of vascular intimal hyperplasia and atherosclerosis [29]. Although we did not examine macrophage composition, studies have indicated that M2 macrophages are polarized after SG, which may be relevant to the results of vascular intimal hyperplasia and inflammation [30,31]. Here, we demonstrated the SG improves TNF-α expression, macrophage infiltration, and IL-6 level altered by carotid ligation in HFD-fed mice, eventually resulting in amelioration of intimal hyperplasia. For tissue inflammation analysis, we focused on vascular remodeling after injury. SG downregulated VEGF, which is a crucial mediator for neointimal formation and progression [32]; its expression was induced by HFD feeding. SG and carotid artery ligation are surgical interventions for weight reduction and vascular remodeling after injury, respectively. In line with previous studies, a HFD augmented inflammatory responses toward vascular injury with increased macrophage infiltration, MMP-9 expression, upregulation of inflammatory cytokines, and VEGF secretion [33,34,35,36]. SG after providing an HFD significantly attenuated vascular injury-induced inflammatory responses and consequent vascular remodeling that had a minor degree of neointimal hyperplasia and arterial elastin fragmentation. However, diet restriction ameliorates obesity-associated inflammation and body weight loss [37]. In addition to weight loss, SG provided additional benefits during vascular remodeling after injury compared to HFD restriction by improving ox-LDL and MMP-9 expression and macrophage infiltration. Our results suggest a potential therapeutic rationale for the use of bariatric surgery to treat obesity and associated comorbidities. However, our results indicated that diet-restricted mice exhibited severe neointimal hyperplasia and increased rupture of collagen integrity compared to mice that underwent SG. SG performed before carotid ligation attenuated adverse vascular remodeling in response to shear stress-induced atherosclerosis. Studies indicated that the stress-responsive hypothalamic-pituitary-adrenocortical axis may play a role in the diverse protective effects conferred by SG and diet restriction [38,39]. Here, we demonstrated the protective effects of SG against anti-obesity-associated-inflammation and vascular remodeling under shear stress via histology in comparison to diet restriction. Increased ox-LDL accumulation, macrophage infiltration, IL-6 increasing and MMP-9 activation are associated with unstable plaque rupture and enhanced vascular remodeling in patients with CAD [40,41,42,43]. Hinagata et al. demonstrated that the expression of the ox-LDL receptor LOX-1 in smooth muscle cells is involved in intimal hyperplasia during balloon injury [44]. Our results demonstrated that SG attenuated macrophage infiltration, ox-LDL accumulation, IL-6 increasing and MMP-9 expression, indicating that SG reduced oxidative stress, macrophage bioactivity, and vascular inflammation, and may cause plaque stabilization and decrease cardiovascular events. Gokce et al. demonstrated that bariatric intervention improves vascular outcomes by evaluating flow-mediated dilation and reactive hyperemia in a wide range of individuals with cardiovascular risk [14]. For obesity control, both non-surgical and surgical interventions confer beneficial effects [45,46]. Studies have shown the positive impact of bariatric surgery on albuminuria, endothelial function, and inflammation in patients with obesity and type 2 diabetes [47,48]. Further investigation is needed to elucidate whether these protective effects mitigate obesity-associated cardiovascular risks. Our original study design did not directly incorporate a comparison of the outcomes between SG and diet restriction. However, our results indicated additional beneficial effects of SG in vascular remodeling. Nevertheless, the differences between the underlying protective mechanisms of SG and diet restriction and their clinical impact on cardiovascular risks warrant further investigations. Obesity is associated with prothrombotic status and increased risk of thrombotic events. Bariatric surgery reduces body weight, inflammation, and the activation of extrinsic coagulation pathways. The reduction in protein C (PC), activated PC, soluble thrombomodulin (TM), and soluble E-selectin levels a year after Roux-en-Y gastric bypass surgery suggests a compensatory upregulation of PC during obesity. The reduction in TM and E-selectin suggests improved endothelial function in this cohort of patients [49]. TM deficiency in endothelial cells resulted in increased basal permeability and hyperpermeability when stimulated using thrombin and TNF-α. These results suggest that cell-bound TM maintains a quiescent phenotype in vascular endothelial cells by regulating the expression of procoagulant and proinflammatory molecules [50]. Proinflammatory cytokines may precipitate thrombus formation, activate the endothelial coagulation system, and promote the development of acute coronary syndromes [51]. Unfortunately, this issue was not explored in the current study but will be our main focus in future studies on the link between weight-reduction surgery and intimal hyperplasia-associated atherosclerosis. ## 4.1. Experimental Animals Wild-type (WT) male C57BL/6J mice (total 105 mice; age, 8-week-old; average weight, 16–18 g) were purchased from the National Laboratory Animal Center (NLAC). Mice were housed at the National Yang Ming Chiao Tung University Laboratory Animal Center with a 12–12 h light-dark cycle (light onset at 7:00 A.M). The mice were provided standard rodent chow and water ad libitum. Procedural approval for animal experiments was obtained from the National Yang Ming Chiao Tung University Institutional Animal Care and Use Committee. Our study complied with the “Guide for the Care and Use of Laboratory Animals,” 8th edition, 2011. The animals were subjected to restricted feeding with free access to water on the night before surgery. ## 4.2. Animal Grouping and Diets Mice were randomly assigned to six groups ($$n = 15$$ each group). Group 1 (CSS group) mice were fed chow, and were subjected to sham operations for SG and carotid ligation surgery. Group 2 (CSL) mice were fed chow and underwent carotid ligation alone. Group 3 (HSS) mice were provided HFD and were sham-operated for SG and carotid ligation. Group 4 (HSL) mice were fed HFD and were subjected to sham surgery for SG but received carotid ligation. Group 5 (HGS) mice were fed HFD and underwent SG and sham operation for carotid ligation. Group 6 (HGL) mice were fed HFD and underwent SG and carotid ligation surgeries. The timeline for the procedures, blood sampling, and tissue processing is shown in Figure 1A. Chow diet and HFD were continued throughout the whole study period. We also assessed the effect of diet restriction without sleeve gastrectomy in mice. Mice under strict diet restriction were fed $70\%$ HFD mixed with $30\%$ wheat bran. Chow diet comprised of Picolab Rodent Diet 20 (energy, 4.06 kcal/g; protein, $23.5\%$; fat, $11.3\%$; carbohydrates, $50.3\%$ ($13.5\%$ energy by fat). High fat diet comprised of Teklad diet TD 88137 (energy, 4.55 kcal/g; protein, $17.8\%$; fat, $20.2\%$; carbohydrates, $50.5\%$ ($39.9\%$ energy by fat) Harlan Tackle Co. Body weight of mice was assessed weekly in all experiments. ## 4.3. SG SG was performed using the clip applier technique [52]. Anesthetic and aseptic procedures, antibiotic indication and usage, and post-operative pain control were performed as previously described [53]. Mice underwent fasting ~6 h before surgery. The hair over the upper abdomen was removed and a 1–1.5 cm upper midline incision was made. SG was performed using a magnifying dissecting microscope (MICROTEK SZ5T-ST®, Telescopes, Taipei, Taiwan) and magnifier as needed to prevent unpredictable blood loss with eventual micro suture closure. After the stomach was externalized, the gastric fundus from the surrounding tissue and other internal organs were dissected. As the fundus and pylorus of the stomach were stretched gently and laterally with micro-forceps, the midline was identified as in Figure 1B; the Ligaclip Applier (Ethicon Inc., Somerville, NJ, USA) was carefully applied to the $80\%$ medial side of the stomach inferiorly from the gastroesophageal junction and superiorly from the lower pole. Approximately $80\%$ of the stomach was clamped and excluded; the stomach’s entire lateral sleeve was created. The stomach’s excluded sleeve was removed, sterilized, and the clipped line was over-sewn with a 6-0 nonabsorbable monofilament suture to ensure no leakage. The stomach was returned to the original site in the abdominal cavity; the abdomen was closed by running a 5-0 nonabsorbable monofilament discontinuous suture to the fascia and abdominal wall layers separately. For the SG sham procedure, the mice received the same laparotomy, externalizing of the stomach using a wet warm saline gauze coverage for 5 min. The stomach was returned to the abdominal cavity; the abdominal wall was closed as described previously. ## 4.4. Partial Ligation of the Left Carotid Artery To establish a model of disturbed flow-induced vascular remodeling in vivo, we partially ligated the left carotid arteries (LCAs) in mice as described previously [54,55,56,57]. The hair over the upper chest and neck was removed. Povidone-iodine solution was used to follow aseptic procedures and a 4–6 mm midline vertical incision was made. The soft tissue was dissected laterally, and the left common carotid artery was identified using the above-mentioned magnifying dissecting microscope. The external carotid artery, internal carotid artery, occipital artery, and superior thyroid artery were carefully dissected from the carotid bulb. The external carotid artery above the superior thyroid artery was tied off using a 6-0 silk suture. The internal carotid artery was similarly tied off contemporaneously. The skin was approximated and closed using a 5-0 monofilament nonabsorbable suture. For the sham partial carotid ligation, the skin and fascia over the upper chest wall was opened; the LCA and associated tissues were identified as described above. The tissue was returned to the original sites and the skin and fascia were closed. ## 4.5. Morphometric Analysis Four weeks after carotid artery ligation, the mice were euthanized using an intraperitoneal 250 mg/kg avertin injection. The left ventricle was cannulated, perfused with phosphate-buffered saline (PBS), and fixed with $4\%$ paraformaldehyde (PFA) (Sigma-Aldrich, St. Louis, MO, USA). The left and right carotid arteries were collected and incubated in $4\%$ PFA for 8 h. After cryopreservation in $30\%$ sucrose/PBS at 4 °C, the arteries were embedded in the Tissue-Tek optimal cutting temperature compound and frozen. Cross-sections of 5 µm thickness were obtained ~1 mm proximal to the bifurcation of the common carotid artery and stained with hematoxylin and eosin (H&E). Four regions (the lumen, intima, media, and total vascular area) of the H&E-stained cross-sections were examined using ImageJ software (National Institutes of Health). The areas surrounding the luminal surface, internal elastic lamina, and external elastic lamina were measured. The intimal area was determined by subtracting the luminal area from the area defined by the internal elastic lamina. The medial area was calculated by subtracting the area defined by the internal elastic lamina from the external elastic lamina. ## 4.6. Elastic Fragmentation Measurement Frozen carotid artery sections were harvested and stained with Verhoeff-van Gieson (VVG; Sigma-Aldrich) stain to distinguish the elastic fibers. The sections were hydrated and stained in Verhoeff’s solution for 10 min. Next, the sections were incubated in $2\%$ ferric chloride for 2 min and treated with $5\%$ sodium thiosulfate for 1 min. The sections were counterstained in VVG for 5 min and dehydrated. Fragmentation was defined as the presence of noticeable cracks in the continuous elastin fiber. Images were acquired using the Olympus BX63 microscope (Olympus, Center Valley, PA, USA); the number of elastin fragments was estimated in representative VVG images for each mouse carotid artery. ## 4.7. Postoperative Care The mice were placed on a warm pad after the operation or sham procedure; an oxygen flow of 2 L/min was given until the mice were fully awake. Post-operative mice were under surveillance in an isolated chamber as they regained mobility and resumed walking around the cage. A single dose of meloxicam (0.1 mg/kg) was administered intraperitoneally for pain relief after surgery and once daily as required for 3 days. An intraperitoneal injection of cefazolin (25 mg/kg) was administered for 1 day after the operation. The mice were kept in an independent incubator at 30 °C for 5 days. One mouse was housed per cage to prevent injury. The mice were free-fed a high-fat gel diet ($10\%$ lard, $10\%$ liquid sugar, $57\%$ water) for 3 days after surgery and were subsequently reintroduced to the previous diet. The mouse body weight was measured weekly throughout the study period. Blood samples and tissue specimens were harvested as scheduled. There was no major bleeding or other significant life-threatening side effect noted during the experimental surgeries. The mortality rate was less than $5\%$ at the early stage of the study. In our hands, the success rate of partial carotid ligation surgery and sleeve gastrectomy was $100\%$ and higher than $90\%$, respectively. ## 4.8. Intraperitoneal Glucose Tolerance Test (IPGTT) After overnight fasting of mice (for at least 10 h), a baseline blood sample was taken (0 min) before the intraperitoneal glucose injection (1 mg/g of body weight). The blood glucose levels were measured at 5, 15, 30, 60, and 120 min after glucose challenge using ACCU-CHEK glucometers (Roche, Basel, Switzerland) and test strips. All blood samples were obtained from the tail vein of freely moving mice using topical cream anesthesia to cause less pain and panic [58,59]. ## 4.9. Histology and Immunohistochemistry The 2–3 mm long common carotid arterial tissues were obtained 1 mm near the carotid bifurcation and were fixed for pathologic evaluation using a $4\%$ PFA solution. Cross-sections of 5 µm were obtained 1 mm proximal to the bifurcation and were stained with H&E and VVG for elastin. Duplicate frozen sections were used for immunohistochemical staining. Briefly, sections were incubated with primary antibodies against oxidized low-density lipoprotein (ox-LDL, 1:500, TA336722, OriGene Technologies, Rockville, MD, USA), CD68 (1:10, NB100-683, Novus-Biologicals, Littleton, CO, USA), and MMP-9 (1:500, SAB5200294, Sigma-Aldrich). The sections were incubated with a biotinylated secondary antibody. An avidin-biotin complex kit (Cell and Tissue Staining Kit, R&D System, Minneapolis, MN 55413, USA) was used for detection. ## 4.10. Measurement of Inflammatory Cytokines Blood samples were collected from each mouse and centrifuged at 3000× g for 10 min at 4 °C. The plasma was transferred to separate tubes without disturbing the blood clots and stored at −80 °C. Plasma samples were analyzed using mouse ELISA kits (R&D System, Minneapolis, MN, USA) for vascular endothelial growth factor (VEGF), pro-matrix metalloproteinase 9 (MMP-9), IL-6, and tumor necrosis factor-α (TNF-α) as per the manufacturer’s instructions. ## 4.11. Western Blotting The carotid arteries were harvested and homogenized in radioimmunoprecipitation assay (RIPA) buffer (R0278; Sigma-Aldrich). After centrifugation at 4 °C, the supernatants were collected. Protein concentration was determined using a Bio-Rad Protein Assay Kit (#5000006; Bio-Rad Laboratories, Hercules, CA, USA). Briefly, 20 µL of 2× SDS sample buffer was added to each sample and heated for 10 min. The samples were loaded onto a $12\%$ Tris-HCl gel (Bio-Rad Laboratories, Hercules, CA, USA) and run at a constant voltage (80 V). Proteins were then transferred to a polyvinylidene fluoride membrane (Bio-Rad Laboratories) for blotting using a constant 350 mA current. Blocking was performed for 1 h with $5\%$ bovine serum albumin (BSA) in phosphate-buffered saline with $0.2\%$ Tween-20 (PBS-T). Membranes were incubated overnight at 4°C with mouse antibody against MMP-9 (1:500, sab5200294, Sigma-Aldrich), mouse monoclonal anti-β-Actin antibody (1:20,000), goat anti-mouse VEGF (1:500, V1253, R&D System), and mouse monoclonal TNF-α antibody (1:2000, T0938, Sigma-Aldrich). After incubation, the blots were washed with PBS-T and were incubated with horseradish peroxidase-conjugated mouse anti-rabbit and mouse antibodies (Dako, Glostrup, Denmark) (1:1000, in PBS-T) at room temperature for 1 h. The enhanced chemiluminescence system (ECL Western Blotting Detection Reagents, Millipore Corporation, USA) and Luminescence/Fluorescence Imaging System (LAS4000, Fujifilm) were used for detection. ## 4.12. Statistical Analysis Data are expressed as mean ± standard deviation. Multiple groups comparisons were performed using one-way analysis of variance followed by Scheffe’s and Tukey multiple-comparison post hoc test. Paired-t tests were used to analyze the statistical significance of the effects of treatments. Two-way analysis of variance was also performed with one treatment parameter being normal chow diet, HFD, HFD with SG and carotid ligation surgery/no surgery. A p-value < 0.05 in the two-way ANOVA tests were considered statistically significant. p-values for the trend and one-way ANOVA were estimated for diet intake and serial changes of glucose in IPGTT. Analyses were conducted using SPSS software (version 22; SPSS, Chicago, IL, USA). p-values < 0.05 were considered statistically significant. ## 5. Conclusions Our findings demonstrated that HFD deteriorates shear stress-induced atherosclerosis and SG significantly attenuated vascular remodeling (graphical abstract). 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--- title: Kaempferol, a Phytoprogestin, Induces a Subset of Progesterone-Regulated Genes in the Uterus authors: - Tova M. Bergsten - Kailiang Li - Daniel D. Lantvit - Brian T. Murphy - Joanna E. Burdette journal: Nutrients year: 2023 pmcid: PMC10051346 doi: 10.3390/nu15061407 license: CC BY 4.0 --- # Kaempferol, a Phytoprogestin, Induces a Subset of Progesterone-Regulated Genes in the Uterus ## Abstract Progesterone functions as a steroid hormone involved in female reproductive physiology. While some reproductive disorders manifest with symptoms that can be treated by progesterone or synthetic progestins, recent data suggest that women also seek botanical supplements to alleviate these symptoms. However, botanical supplements are not regulated by the U.S. Food and Drug Administration and therefore it is important to characterize and quantify the inherent active compounds and biological targets of supplements within cellular and animal systems. In this study, we analyzed the effect of two natural products, the flavonoids, apigenin and kaempferol, to determine their relationship to progesterone treatment in vivo. According to immunohistochemical analysis of uterine tissue, kaempferol and apigenin have some progestogenic activity, but do not act in exactly the same manner as progesterone. More specifically, kaempferol treatment did not induce HAND2, did not change proliferation, and induced ZBTB16 expression. Additionally, while apigenin treatment did not appear to dramatically affect transcripts, kaempferol treatment altered some transcripts ($44\%$) in a similar manner to progesterone treatment but had some unique effects as well. Kaempferol regulated primarily unfolded protein response, androgen response, and interferon-related transcripts in a similar manner to progesterone. However, the effects of progesterone were more significant in regulating thousands of transcripts making kaempferol a selective modifier of signaling in the mouse uterus. In summary, the phytoprogestins, apigenin and kaempferol, have progestogenic activity in vivo but also act uniquely. ## 1. Introduction Progesterone is a steroid hormone that plays numerous roles in normal human physiology, particularly in the female reproductive system. Progesterone carries out most of these functions by binding to the nuclear progesterone receptors (PRA and PRB) and acting as a transcription factor to regulate downstream target genes [1]. Perhaps most prominently studied are the roles of progesterone in female reproductive tissues including the breasts, ovaries, and uterus [2]. In particular, progesterone is well-known for its ability to counteract estrogen-induced epithelial proliferation in the endometrium [3]. As such, progesterone is prescribed to counteract unwanted symptoms such as premenopausal abnormal bleeding or excessive uterine proliferation in conditions such as endometriosis [4]. These prescriptions are typically for synthetic progestins that bind the progesterone receptor, since progesterone itself is not orally bioavailable unless formulated as micronized progesterone. However, recent data suggest that women have been increasingly turning to botanical supplements to alleviate these and other symptoms, including those from premenstrual syndrome, menopause, and infertility [5,6]. In 2020, consumer spending on herbal supplements increased by over $17\%$ from 2019, reaching over USD 11 billion dollars nationwide [7]. Unfortunately, while these supplements may provide women with alternative treatment strategies, they are often not regulated by the U.S. Food and Drug Administration and therefore have not undergone rigorous testing to identify active compounds, effective doses, inherent toxicity, or drug–supplement interactions. Hence, it is important to characterize and quantify active compounds in botanical supplements, and also their biological targets within cellular and animal systems. Several studies have identified that botanical supplements contain compounds that are capable of binding human steroid receptors and activating their downstream effects. Traditionally, these compounds have included phytoestrogens, which can bind the estrogen receptor, but have more recently been shown to include phytoprogestins as well, which can bind the progesterone receptor [8,9]. Two such compounds, the flavonoids apigenin and kaempferol, are found in a variety of fruits, vegetables, and botanicals [10,11]. In vitro, kaempferol demonstrates antioxidant and anti-inflammatory properties as well as anti-proliferative properties in ovarian cancer cells, which is noteworthy as progestins also have an immunosuppressive and anti-inflammatory action [12,13,14]. We previously reported that apigenin and kaempferol were orally bioavailable in an ovariectomized rat model and had progestin-like effects on uterine tissue when administered by oral gavage [15,16]. However, progesterone was unable to be utilized as a control treatment in these studies as it is not orally bioavailable. Therefore, the need to directly compare the effects of apigenin and kaempferol to progesterone remained. To accomplish this, we employed a mouse model where treatments would be provided via intraperitoneal injections allowing for the inclusion of progesterone alongside apigenin and kaempferol, and the subsequent identification and analysis of genome-wide target genes. ## 2.1. Animal Study and Chemicals This study utilized ovariectomized 6–8-week-old CD1 mice (Envigo, Indiannapolis, IN, USA). Animals were housed in a temperature- and light (12L:12D)-controlled environment. Water and food were provided ad libitum. Mice were fed with AIN-76A diet (Envigo CA.170481), devoid of phytoestrogens. All animals were treated in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. Mice were ovariectomized by the supplier and treatment began no sooner than two weeks after surgery to ensure sufficient time to minimize endogenous hormone effects. Progesterone (≥$99\%$ purity, Sigma-Aldrich, St Louis, MO, USA, P0130) was used at 1 mg/kg. Kaempferol (≥$98\%$ purity, Cayman Chemical, Ann Arbor, MI, USA, 11852) and apigenin (≥$98\%$ purity, Cayman Chemical 10010275) were each used at 5.625 mg/kg. These doses were utilized to maintain consistency with our previous studies which utilized 5.625 mg/kg of either compound [15,16]. Five mice were randomly assigned into each treatment group and received once a day intraperitoneal injection of either drug dissolved in $10\%$ DMSO for 7 days. At day 7, mice were weighed and euthanized via humane means (asphyxiation via CO2 and cervical dislocation) prior to the collection and weight of their uterine tissue. One uterine horn was snap-frozen in liquid nitrogen and stored at −80 °C for RNA extraction. The second uterine horn was fixed in 10 mL of $10\%$ buffered formalin for 24 h, transferred into $70\%$ EtOH, and processed for histology using a Shandon 1000 processor (Thermo, Waltham, MA, USA). Processed tissue was then embedded with paraffin into 5 mm thick blocks and sectioned into 5 µm sections with a microtome. This study was approved by the UIC Institutional Animal Care and Use Committee (protocol number 18-205). ## 2.2. Immunohistochemical Staining IHC was performed for proliferating cell nuclear antigen (PCNA), zinc finger and BTB domain-containing 16 (ZBTB16), heart and neural crest derivates-expressed protein 2 (HAND2), and FK506 binding protein 5 (FKBP5) on uterine samples as previously described [17]. The tissue sections were incubated with the following primary antibodies overnight at 4 °C: PCNA (1:200, 13,110 Cell Signaling, Danvers, MA, USA), HAND2 (1:200, ab200040 Abcam, Cambridge, UK), FKBP5 (1:200, 14155-1 Protein Tech, Rosemont, IL, USA), and ZBTB16 (1:200, PA5-112862 Invitrogen, Waltham, MA, USA). RRIDs for these antibodies are as follows: PCNA (AB_2636979), HAND2 (AB_2923502), FKBP5 (AB_2231625), and ZBTB16 (AB_2867596). Subsequently, slides were incubated with anti-goat biotinylated secondary antibody (Vectastain ABC kit; Vector Laboratories, Inc., Burlingame, CA, USA) at 1:200 dilution in PBST for 60 min at room temperature. Slides were imaged using a Nikon E600 Eclipse microscope with a CMOS C-Mount microscope camera. PCNA expression was counted for each stained cell in either glandular or luminal epithelium. The number of stained cells was graphed using GraphPad and a one-way ANOVA was used to determine significance (* $p \leq 0.05$). Expression of ZBTB16, FKBP5, and HAND2 in treatment-blinded representative images was determined on a scale of 0 to +3 by distinct viewers. These results were graphed using GraphPad and a one-way ANOVA was used to determine significance (* $p \leq 0.05$). ## 2.3. RNA Isolation and RNA Sequencing Profiling Uteri of mice treated with $10\%$ DMSO, 1 mg/kg progesterone, or 5.625 mg/kg kaempferol or apigenin for 7 days in the first animal study were subjected to RNA isolation and RNA sequencing. RNA sequencing of uterine tissue was profiled ($$n = 4$$ per treatment group). Total RNA was extracted from uterine tissues of mice using the Qiagen RNeasy mini kit (Qiagen, Hilden, Germany, #74104) according to the manufacturer’s instructions. The concentration of mRNA was determined by a Nanodrop. RNA libraries (three technical replicates/treatment) were created. The Genomics Core Facility at Northwestern University performed RNA quality determination, mRNA enrichment, library construction, sequencing, and transcriptome statistical analysis. Samples with RINs of 7 or greater were prepared with TruSeq mRNA-Seq Library Prep (Illumina, San Diego, CA, USA) with 1 μg of RNA and 12 cycles of PCR amplification. The libraries were barcoded, pooled, and sequenced on the HiSeq Sequencing 50 followed by statistical analysis. ## 2.4. Statistical and Bioinformatics Analysis For RNAseq data, gene set enrichment of differentially expressed genes was performed using GSEA. Gene sets with an FDR adjusted p-value of <0.05 were considered significant. ## 3.1. Kaempferol and Apigenin Have Progestogenic Activity In Vivo In this study, CD-1 mice ($$n = 5$$/group) were injected intraperitoneally (IP) with $10\%$ DMSO, 1 mg/kg progesterone (P4), 5.625 mg/kg kaempferol, or 5.625 mg/kg apigenin once a day for 7 days. To evaluate the progestin-like effects of each treatment, mouse uteri were collected and subjected to immunohistochemistry (IHC) to determine the protein levels of progesterone-receptor-regulated genes such as HAND2, ZBTB16, FKBP5, and PCNA. Heart and neural crest derivates-expressed protein 2 (HAND2) is known to regulate a specific function in uterine epithelium and is upregulated by P4 in ovariectomized mice [18,19]. Specifically, HAND2 expression in the stromal cells of the uterus is required for secretion of hedgehog signaling factors that then block estrogen-induced proliferation in uterine epithelial cells through paracrine signaling. Compared to the control (Figure 1A), progesterone-treated mice expressed significantly increased HAND2 protein in the stromal cell compartment (Figure 1B,E). While HAND2 expression in kaempferol-treated mouse uteri was more similar to DMSO-treated tissue than progesterone-treated tissue (Figure 1C,E), apigenin treatment seemed to have no effect on HAND2 expression (Figure 1D,E). This result in mice differs from our previous work in which compounds were given orally to rats and both apigenin and kaempferol increased HAND2 expression in uterine tissues [15,16]. Zinc finger and BTB domain-containing 16 (ZBTB16) is also induced by P4 and known to play a role in stromal cell decidualization [20]. In this study, progesterone (Figure 2B) and kaempferol (Figure 2C) treatments seemed to slightly increase ZBTB16 expression when compared with DSMO (Figure 2A), although these changes were not statistically significant (Figure 2E). However, apigenin (Figure 2D) significantly increased ZBTB16 protein levels as compared to DMSO as seen in IHC (Figure 2A,E). FK506 binding protein 5 (FKBP5) is involved in the assembly of the glucocorticoid receptor complex and functions as an inhibitor of its assembly until it disassociates from the complex [21]. However, the fkbp5 gene is inducible by glucocorticoids, as well as progesterone and androgenic hormones [22,23,24,25,26,27,28]. While FKBP5 expression was seemingly increased by progesterone (Figure 3B) treatment, only kaempferol (Figure 3C) and apigenin treatments (Figure 3D) induced significantly increased ZBTB16 expression when compared with control (Figure 3A,E). Additionally, we investigated the effects of these compounds on uterine epithelial proliferation. It is well established that progesterone inhibits estrogen-induced uterine epithelial proliferation through the progesterone receptor [3]. Importantly, the mice in this study were ovariectomized thereby reducing endogenous hormone production. In this model, progesterone-treated mouse uteri displayed a decreased expression of proliferating cell nuclear antigen (PCNA) (Figure 4B), an epithelial proliferation marker, when compared with the DMSO-treated mouse uteri (Figure 4A,E). While kaempferol and apigenin did not appear to significantly decrease PCNA expression in the epithelium, there was seemingly less expression in the stroma than in the control-treated tissue (Figure 4C–G). In a previous study, although apigenin increased expression of Ki67, another proliferation marker, it increased expression to a lesser degree than the phytoestrogen genistein and was able to block the genistein-induced Ki67 increase in combination treatment [15]. Kaempferol had a similar profile in another study, increasing Ki67 expression when compared with control but also counteracting the estrogenic proliferation induced by genistein [16]. These data underscore the role of progesterone receptor-mediated signaling in the presence and absence of estrogen receptor activation and indicate that both apigenin and kaempferol block genistein-induced signaling but do not reduce basal levels of uterine epithelial proliferation. ## 3.2. Kaempferol and Progesterone Effects on mRNA Transcripts To investigate and compare the transcriptomic profiles of tissues collected from mice injected with progesterone, kaempferol, and apigenin, we extracted mRNA from the uteri of these mice ($$n = 4$$/group) and performed next generation RNA sequencing (a full list of altered transcripts is available in Table S1). Apigenin did not appear to regulate more than a handful of transcripts, suggesting poor bioavailability when given intraperitoneally. As such, the majority of our analysis focused on the effects of progesterone and kaempferol treatments. Progesterone treatment altered significantly more transcripts than were found to be altered in kaempferol-treated tissues. Progesterone upregulated 2472 transcripts while kaempferol upregulated only 34 transcripts; 10 transcripts were upregulated by both treatments (Figure 5A, Table 1). Progesterone downregulated 2366 transcripts while kaempferol downregulated only 67 transcripts; 34 transcripts were downregulated by both treatments (Figure 5B, Table 2). Roughly half ($44\%$) of all the transcripts regulated by kaempferol were also regulated by progesterone treatment. A total of $29\%$ of the upregulated transcripts and $51\%$ of the downregulated transcripts were altered by both kaempferol and progesterone treatments. Lefty1 was the most upregulated transcript (2.61-fold), while Cemip was the most downregulated transcript (−1.43-fold) in kaempferol-treated tissues. RNAseq data were then subjected to GSEA analysis to identify significantly altered gene sets [29,30]. Similarly altered pathways were found for both progesterone and kaempferol treatments including unfolded protein response (UPR), androgen response (AR), and interferon alpha response (IAR) (Figure 5C). The normalized enrichment score (NES) values for the UPR and AR pathways were positive for both progesterone- and kaempferol-treated tissues, implying that the majority of altered genes in these pathways were upregulated in the tissues of both treatments. According to GSEA, the transcripts in the UPR pathway, such as ATF3, are typically upregulated in a cellular stress response related to the endoplasmic reticulum (ER). In the corpus luteum, UPR signaling pathway activation has been shown to help maintain progesterone expression during luteal phase progression [31]. Further, ER stress-induced apoptosis mediated by CHOP and the caspase cascade, parts of the UPR pathways, has been shown to be involved in the regression of the corpus luteum [31,32]. These data suggest that UPR pathways play a role in the regulation of the corpus luteum and progesterone production. In prostate cancer cells, progesterone treatment induced several UPR pathway proteins [33]. Additionally, both in vitro treatment with progesterone and uterine tissue analyzed during the secretory phase of the uterine cycle, which is characterized by high levels of progesterone, showed increased CHOP expression and apoptosis in endometrial cells [34]. These data suggest that progesterone is both capable of regulating and being regulated by the UPR pathway. Unsurprisingly, progesterone treatment upregulated transcripts defining of the androgen response since progesterone signaling is canonically deeply intertwined with androgen signaling. Progestins are known to bind similar DNA response elements as androgens and have been known to act as partial androgen receptor agonists, which is often the suggested rationale for why progestins can cause seemingly androgen-induced side-effects [35,36]. The similar pattern of gene alteration in these pathways seen in both kaempferol- and progesterone-treated tissues is indicative of kaempferol acting as a progestin. In contrast, the NES value for the IAR pathway was negative for both treatments. This suggests that the majority of altered genes in the IAR pathway, such as RSAD2, were downregulated in both sets of tissues, or that both progesterone and kaempferol treatment attenuate the transcription of genes canonically upregulated in response to alpha interferon proteins meant to handle a viral infection. ## 4. Discussion Synthetic progestins are widely sought as treatments for many unwanted symptoms originating in female reproductive tracts. While these molecules have current practical applications in women’s health, the natural compounds that function to modify PR signaling in botanical dietary supplements remain less well studied. As such, the need to understand the contents of these supplements and their numerous effects is ever growing. For this reason, we undertook an in vivo study to determine the effects of two previously identified phytoprogestins, apigenin and kaempferol, and their similarity to progesterone treatment. According to our immunohistochemistry results, kaempferol and apigenin have some progestogenic activity, but do not act in exactly the same manner. For instance, while progesterone treatment upregulated the known progesterone target gene HAND2, neither kaempferol nor apigenin upregulated HAND2 expression to the same extent. However, both kaempferol and apigenin increased ZBTB16 and FKBP5 expression, other progesterone inducible genes, as did progesterone. Interestingly, FKBP5 is one of the main drivers of the androgen response pathway in GSEA that was upregulated by progesterone in our RNAseq data. While kaempferol treatment did not significantly upregulate FKBP5 expression according to RNAseq, this may be due to a single replicate of RNA as the IHC suggests kaempferol does increase FKBP5 expression at the protein level. Both kaempferol- and apigenin-treated tissues stained for PCNA demonstrated higher expression of PCNA in the luminal epithelium than in those of tissues treated with progesterone. This aligns with previous data suggesting that while kaempferol is not able to suppress PCNA expression alone, it is able to decrease proliferation when given in combination with an estrogenic compound such as genistein [16]. These data suggest that both kaempferol and apigenin have some progestogenic activity. However, there remains more to learn about the extent of their activity in vivo, particularly comparing mouse and rat uteri. RNAseq data determined that progesterone treatment altered many more transcripts than kaempferol treatment. However, while kaempferol treatment did alter some transcripts in a similar manner to progesterone treatment, kaempferol treatment also had some unique effects. A few of the transcripts upregulated only by kaempferol treatment, including LEFTY1 and MMP3, are known to be altered during menstruation. For instance, MMP3 has been shown to increase in ovarian granulosa cells exposed to P4 treatment, suggesting that its upregulation in our data could be evidence of kaempferol’s progestogenic action [37]. Our study also showed an upregulation of LEFTY1 transcripts due to kaempferol treatment. Interestingly, LEFTY1 is expressed all throughout the estrus cycle but has been shown to induce MMP3 upregulation, which may suggest a relationship between these transcripts and their regulation by progesterone [38,39]. Several transcripts upregulated by both progesterone and kaempferol treatments are known to play a role in successful implantation of a conceptus into appropriately decidualized endometrium, a process regulated by PR signaling. In a human model of implantation, ATF3 was shown to promote adhesion of spheroids to endometrial cells and has been shown to be decreased in the endometria of patients experiencing recurrent implantation failure [40]. Additionally, knockdown of ATF3 in a human endometrial model impaired decidualization, suggesting a rationale for the recurrent implantation failure seen in patients with insufficient amounts of ATF3 [41]. ATF3 is also a hallmark gene in the UPR pathway that was identified as having several transcripts significantly upregulated by both kaempferol and progesterone treatments. Similarly, SFRP4 has been shown to be highly expressed in decidualizing endometrium [42]. SFRP4 has also been identified as significantly downregulated in uterine lavage samples of infertile women, and this downregulation may affect the proper endometrial development necessary for successful implantation [43]. Lrp2 expression, which was upregulated by kaempferol 2.61-fold over progesterone in the RNAseq data, is known to be upregulated by progesterone treatment and reach its peak at the implantation window in mice endometria [44]. These data suggest that kaempferol treatment may have progestogenic properties in that it similarly upregulates many transcripts involved in appropriate endometrial preparations for successful implantation. In contrast, MRAP2, upregulated by kaempferol and progesterone treatments, has been identified as downregulated in human pre-receptive and receptive endometria and upregulated in the endometria of infertile patients [45,46]. These data suggest that both progesterone and kaempferol may not have completely isolated pro-implantation affects. Future studies could focus on kaempferol treatment and its regulation of decidualization and implantation. Interestingly, many more transcripts were downregulated by kaempferol treatment than were upregulated. This is congruent with the literature demonstrating that when steroid hormones, such as estrogen, bind to nuclear receptors, the majority of altered transcripts are repressed rather than activated [47,48]. Many of the transcripts downregulated by kaempferol are involved in fertility or the implantation process of pregnancy. For example, knockout of 4930447C04Rik or Six6ox1, which was only downregulated by kaempferol, in female mice results in oocyte insufficiency causing infertility [49]. In mice with knockout of Asb4−/−, here downregulated by both progesterone and kaempferol treatments, there were many placental development issues resulting in decreased fertility [50]. Similarly, Nr5a2, downregulated by kaempferol only, is required for healthy placental formation and the promotion of decidualization in both mouse and human models [51,52]. While these data suggest that kaempferol treatment may repress the expression of genes required for successful pregnancies, we saw that kaempferol treatment activates expression of transcripts necessary for healthy pregnancies as well. Therefore, more research is needed to fully understand the relationship between kaempferol treatment and implantation events. Other transcripts that were downregulated by kaempferol treatment are shown in the previous literature to be related to cancer. These genes are of interest due to the association in the literature between progesterone-only contraceptive use and reduced risk of ovarian and endometrial cancer. CEMIP, downregulated by both kaempferol and progesterone treatments, is upregulated in the tumor tissues of patients with epithelial ovarian cancer [53]. Knockdown of CEMIP is also shown to decrease oncogenic properties, including proliferation, invasion, and migration, in a human ovarian cancer cell line [53]. Additionally, OGDHL is upregulated in epithelial ovarian cancer tumor samples compared with controls but downregulated by both kaempferol and progesterone treatments [54]. Similarly, both kaempferol and progesterone treatment downregulated RSAD2 which is both upregulated and associated with poorer progression in patients with endometrial adenocarcinoma [55]. RSAD2 is also a hallmark gene of the IAR pathway, transcripts of which were significantly downregulated by both progesterone and kaempferol treatment. These results suggest that kaempferol treatment may decrease expression of transcripts involved in these specific cancer types. However, OSR2 expression, decreased only by kaempferol treatment, is commonly downregulated in endometrial cancer suggesting that some transcripts associated with risk have varied expression patterns as a result of kaempferol treatment [56]. Another trend our RNAseq data identified was that several genes downregulated by kaempferol treatment are related to polycystic ovary syndrome (PCOS) according to the literature. PCOS is characterized by the formation of many cysts on the ovaries, which also produce an abnormally high level of androgens and low circulating levels of progesterone due to reduced ovulation. Expression of SLC5A3, decreased by kaempferol treatment, was also found to be decreased in the endometrial tissue from women with PCOS [57]. Further, this decreased expression contributed to the development of insulin-resistance commonly seen in PCOS patients. Similarly, decreased expression of Procr, which was also decreased by both progesterone and kaempferol treatment, led to disrupted ovarian follicle development and a PCOS phenotype in mice [58]. CXCL14 transcripts, decreased by both progesterone and kaempferol treatment, have been shown to be decreased in human luteinized granulosa cells from women with PCOS [59]. Additionally, a lack of CXCL14 in these cells likely contributes to their decreased ability to produce progesterone as treatment with increasing doses of CXCL14 consistently increased progesterone production [59]. Pdgfd expression was also decreased by kaempferol treatment. In women with PCOS, both follicular fluid and serum were found to contain decreased amounts of PDGFD protein when compared with samples from control patients [60,61]. Further, PDGFD levels were found to be decreased in a rat model of PCOS [62]. These data suggest that kaempferol treatment may be inducing a similar gene expression as those seen in PCOS models, as supported by one of the significant GSEA pathways being related to androgen signaling. However, kaempferol and progesterone treatment both decreased C3 transcript expression, which is shown to be upregulated along with other complementary pathway factors in patients with PCOS and is thought to contribute to the inflammatory aspect of the disease [63,64]. This suggests that the effects of kaempferol treatment on PCOS pathways and regulated transcripts may not be entirely consistent and require more investigation. In summary, these data suggest that both apigenin and kaempferol have progestogenic activity in vivo in a murine model. For instance, immunohistochemical analysis shows that both apigenin and kaempferol increase ZBTB16 and FKBP5 expression in the uterus similarly to progesterone. 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--- title: 'Periodontal Disease in Young Adults as a Risk Factor for Subclinical Atherosclerosis: A Clinical, Biochemical and Immunological Study' authors: - Smiljka Cicmil - Ana Cicmil - Verica Pavlic - Jelena Krunić - Dragana Sladoje Puhalo - Dejan Bokonjić - Miodrag Čolić journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051366 doi: 10.3390/jcm12062197 license: CC BY 4.0 --- # Periodontal Disease in Young Adults as a Risk Factor for Subclinical Atherosclerosis: A Clinical, Biochemical and Immunological Study ## Abstract Although a strong relationship between periodontal disease (PD) and atherosclerosis was shown in adults, little data are published in younger PD patients. Therefore, this study aimed to investigate and correlate clinical parameters of PD, pro- and immunoregulatory cytokines in gingival crevicular fluid (GCF) and serum, biochemical and hematological parameters associated with atherosclerosis risk, and carotid intima-media thickness (IMT) in our younger study participants ($$n = 78$$) (mean age 35.92 ± 3.36 years) who were divided into two equal groups: subjects with and without PD. PD patients had higher values of IMT, hs-CRP, triglycerides, total cholesterol, and LDL; most proinflammatory and Th1/Th17-associated cytokines in GCF; and IL-8, IL-12, IL-18, and IL-17A in serum compared to subjects without PD. These cytokines in GCF positively correlated with most clinical periodontal parameters. Clinical periodontal parameters, TNF-α and IL-8 in GCF and IL-17A, hs-CRP, and LDL in serum, had more significant predictive roles in developing subclinical atherosclerosis (IMT ≥ 0.75 mm) in comparison with other cytokines, fibrinogen, and other lipid status parameters. Hs-CRP correlated better with the proinflammatory cytokines than the parameters of lipid status. Except for serum IL-17A, there was no significant association of clinical and immunological PD parameters with lipid status. Overall, these results suggest that dyslipidemia and PD status seem to be independent risk factors for subclinical atherosclerosis in our younger PD population. ## 1. Introduction Periodontal disease (PD) is a chronic inflammatory disease that occurs in the surrounding tissues of the teeth [1]. PD is caused by the influence of periopathogens from oral biofilm and is characterized by complex pathogen–host interactions [1,2]. PD affects up to $90\%$ of the worldwide population and is ranked the sixth most prevalent disease in humans [1]. Numerous recent studies support the hypothesis that PD influences systemic health [2]. However, recent results indicated a low level of awareness, where about $50\%$ of individuals did not know about this association [3]. Atherosclerosis is a chronic progressive narrowing of arteries that may lead to their occlusion due to lipid deposition and atheroma formation in the arterial wall [4]. It underlies coronary heart disease ($80\%$) and myocardial and cerebral infarctions, mostly due to atheroma rupture, therefore having big socio-economic importance [1,2,4]. Apart from abnormalities in lipid status (hypercholesterolemia and hypertriglyceridemia), chronic inflammation is recognized as an important etiopathogenetic factor in the development of atherosclerosis [1,2,4,5]. In this context, several inflammatory markers, such as high-sensitivity C-reactive protein (hs-CRP) and fibrinogen blood levels, as well as the number of leukocytes, are recognized as predictable risk factors of atherosclerosis and other cardiovascular diseases [6,7,8,9]. The link between periodontal disease and atherosclerosis was first introduced in 1963 when a $25\%$ higher risk of atherosclerotic plaque formation in patients with periodontitis was demonstrated [6,7]. Since then, there is growing evidence regarding the contribution of chronic periodontal inflammation to the risk of atherosclerosis [5,6,7,8,9]. Although the exact mechanisms of this association are most probably very complex, there are at least two accepted models: microbial invasion and infection of atheromas, or inflammatory/immunological mechanisms [6]. The first model suggests that periopathogens from periodontal pockets can enter systemic circulation and lodge in most distant tissues, including atheromatous plaque. This finding is supported by the knowledge that bacteremias may occur following oral interventions and/or even by brushing the teeth and that such dental procedures can even cause infective endocarditis [10]. The second model implies an indirect effect of numerous inflammatory mediators, which enter systemic circulation from affected periodontal tissues or are triggered in distant tissues by their influence. These inflammatory mediators include C-reactive protein (CRP), matrix metalloproteinases, fibrinogen, and numerous hemostatic factors and cytokines, which further accelerate atheroma formation and progression through oxidative stress and lipid oxidation or inflammatory dysfunction [6]. Cytokines play the most important role in the pathogenesis of PD through a complex network where the balance between proinflammatory and anti-inflammatory cytokines leads to the progression and restriction of periodontal inflammation and tissue destruction [11,12]. Among cytokines produced during PD, some are known to have a proatherogenic effect, such as interleukin (IL)-1β, IL-6, IL-8, IL12, IL-17A, IL-18, tumor necrosis factor (TNF)-α, and interferon (INF)-γ. In contrast, IL-5, IL-10, IL-13, IL-19, IL-27, IL-33, IL-37, and transforming growth factor (TGF)-β may have antiatherogenic potential [13]. The proatherogenic effect of cytokines may be partly due to their interference with lipid metabolism, manifested as an increase in levels of triglycerides, total cholesterol, and its low-density lipoprotein (LDL) fraction [14,15,16]. However, the specific role of individual cytokines within this complex cytokine network activated in PD is not known. In this context, good mutual correlations studies between clinical parameters of PD, pro- and anti-inflammatory (immunoregulatory) cytokines in gingival crevicular fluid (GCF) and systemic circulation, and known biochemical and hematological parameters associated with inflammation and the intima-media thickness (IMT) of carotid arteries, as a parameter of atherosclerosis, could be helpful. Therefore, this was the primary goal of our study on younger adults, a population with subclinical parameters of atherosclerosis that has not been extensively studied. We hypothesized that clinical periodontal indices, the cytokine profile in GCF and serum of PD patients, and serum inflammatory parameters (CRP and fibrinogen) are independent risk factors for subclinical atherosclerosis compared with lipid profiles. ## 2.1. Study Participants In this case-control study, 78 participants from the region of Foča, R. Srpska, Bosnia and Herzegovina, were recruited. Of the participants, 31 were male, 47 were female, and the mean age was 35.92 ± 3.36 years, and the participants were divided into two equal groups: group I-subjects with chronic PD ($$n = 39$$) and group II-subjects with healthy periodontal status ($$n = 39$$). The subjects were between 28 and 40 years and were categorized as younger adults according to previous publications in this field [17,18]. This was the main inclusion criterion. The subjects in both groups were recruited during two periods, September 2018–September 2020 and January 2022–August 2022, and were randomly selected within the same age range. Smoking status and educational attainment were ascertained. The clinical part of the study was performed at the Department of Dental Pathology, Faculty of Medicine Foca, University of East Sarajevo, Bosnia and Herzegovina, whereas biochemical and immunological parameters were measured at the Department of Biochemistry and the Center for Biomedical Sciences in the same faculty. The study followed the STROBE guidelines for reporting observational studies [19]. Patients with PD and control subjects were fully informed about the study and signed written informed consent. The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Medicine Foča, University of East Sarajevo, Bosnia and Herzegovina (protocol code 01-$\frac{8}{29}$, date of approval 8 June 2015). Exclusion criteria were pregnancy; the presence of systemic diseases or isolated cardiovascular, lung, kidney, and liver disease; use of medication within the past 6 months (antibiotic or anti-inflammatory drugs and/or immunomodulators); obesity (class II and III); diabetes; malignant disease; and periodontal treatment within the past 6 months. General clinical examination included general health status (based on an interview and clinical measurements of anthropometric data (weight, height, and body mass index/BMI) and blood pressure, which were performed before the evaluation of the periodontal status. Height and body mass were measured in centimeters and kilograms, respectively. BMI was calculated by the ratio of body mass and height squared and expressed as kg/m2 during data processing. The average systolic and diastolic blood pressures (SBP and DBP, mmHg) were calculated from two separate readings of the same designated arm and recorded. ## 2.2. Clinical Examination for Periodontal Disease and Subgingival Sampling The periodontal evaluation was performed by two experienced calibrated periodontists (S.C. and A.C.) in the Department of Dental Pathology, Faculty of Medicine Foca, who were blinded to the biochemical and immunological parameters. The calibration exercise between the two examiners was performed previously on 20 patients who did not participate in this study. The calibration involved all five periodontal indices: plaque index (PI), gingival index (GI), bleeding on probing (BOP), clinical attachment level (CAL), and periodontal pocket depth (PPD). The kappa coefficients for intra- and inter-examiner agreement, and intra-class correlation, were between 0.88 and 0.95 depending on the investigated periodontal index (highest for PI and GI and lowest for PPD). PD was diagnosed based on standard clinical features of chronic inflammatory changes in the marginal gingiva, the presence of periodontal pockets, and loss of clinical attachment, and in some cases radiographically based on evidence of bone loss. Periodontal clinical examination was performed on the teeth numbered 16, 21, 24, 36, 41, and 44 as described by Ramfjord, 1953 [20]. The buccal, lingual, and interproximal surfaces (6 sites per tooth) of these teeth were evaluated separately, including PI according to Silness and Löe [21], GI according to Löe and Silness [22], BOP [23], CAL, and PPD. PPD was measured by using William’s periodontal probe. Measurements of CAL were made in millimeters and were rounded to the nearest whole millimeter. The periodontal diagnosis was in accordance with the criteria proposed by the 1999 classification for periodontal diseases [24]. The PD group consisted of subjects with at least 4 periodontal pockets, CAL > 1 mm and PPD > 3 mm, present in at least three sites in two different quadrants. The control group was subjects without periodontitis who had health periodontium or mild gingivitis (a mean BOP below $15\%$ and no sites with PD > 3 mm and CAL > 1 mm) [25]. The GCF samples were collected using the paper point technique (Periopaper, Pro Flow Inc., Amityville, NY, USA) from the bottom of three periodontal pockets of PD patients or in the gingival sulcus of the control group subjects. The samples were collected in the same session as the periodontal exams. Each sample site was isolated with cotton rolls, gently scalled supragingivaly, and air-dried. A sterile paper point was inserted into the apical extent of each selected pocket/sulcus (0.5–2 mm in depth), kept for 30 s, and transferred immediately to a sterile Eppendorf tube with 100 µL saline. The tubes were shacked for 20 min, then paper points were removed, and the samples were kept at −80 °C until further analysis. This method, based on the quantification of variables in GCF fluid as a function of time (30 s), was accepted in the periodontal literature when there was no possibility of quantifying the exact volume of GCF [26]. No additional measurement of GCF/saline volume was obtained. ## 2.3. Analysis of Biochemical and Hematological Parameters After overnight fasting, blood samples were collected into Eppendorf tubes for the following hematological and biochemical analyses: high-sensitivity C-reactive protein (hs-CRP), fibrinogen, leukocytes’ count, and lipid profile parameters such as triglycerides, total cholesterol, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol. Plasma was obtained after centrifugation at 3000 for 15 min and stored at −80 °C until analysis. The number of leukocytes was determined using a Sysmex KX-21 N apparatus, while the fibrinogen concentration was determined by using a Stago STA-r® 4 Hemostasis Analyzer (Diagnostica Stago Inc., Parsippany, NJ, USA). Lipids and hs-CRP levels were determined using standard spectrophotometric analysis (Architect Plus ci4100, Abbott Diagnostics, Chicago, IL, USA). ## 2.4. Immunological Analysis The immunological analysis consisted of the determination of proinflammatory cytokine levels (IL-1β, IL-6, IL-12, IL-17A, IL-18, IL-23, IL-33, TNF-α, INF-α, and INF-γ), chemokines IL-8 and monocyte chemoattractant protein-1 (MCP-1), and immunoregulatory cytokines IL-10 and TGF-β in GCF and serum. After thawing, both sera and GCF were centrifuged at 5800× g to remove small clots, plaque, and cellular elements. The levels of all cytokines, except for TGF-β, were determined by multiplex bead analysis using a flow cytometer (Attune, ThermoFisher Scientific, New Castle, DE, USA) and commercial immunoassay kit (LEGENDplex™ Human Inflammation Panel, BioLegend, San Diego, CA, USA) according to the manufacturer’s recommended protocol. TGF-β was analyzed by the enzyme-linked immunosorbent assay (ELISA) (DuoSet ELISA kit, R&D Systems Inc, Minneapolis, MN, USA). All samples were analyzed in duplicates, and mean values were used. Variations between duplicates were less than $12\%$. The analyses from each of the two study periods were performed simultaneously and under identical experimental conditions. The results were expressed as the mean concentration of cytokines in serum (pg/mL) or pg/30 s (GCF). ## 2.5. IMT Measurement of Carotid Arteries IMT measurements of the left (L) and right (R) common carotid arteries were performed at the Department of Radiology, University Hospital Foča, Bosnia and Herzegovina, applying a standardized protocol (Touboul et al., 2000) according to the guidelines of the Mannheim IMT Consensus using a LOGIQ pro 6 (GE Medical Systems Ultrasound, Bedford, UK) ultrasound scanner with a 9 MHz linear transducer. The experienced examiner was blinded with respect to periodontal status. Longitudinal electrocardiography (ECG)-triggered images of the arteries were obtained proximally to the bifurcation at 1 cm point, with the patient in the supine position, the head straight, and the neck extended. For each subject, the average of three determinations of each side was measured and the mean value was calculated. ## 2.6. Statistical Analysis To describe the distribution of data, the mean and standard deviation for quantitative variables and absolute and relative frequencies for categorical variables were used. After testing the assumption of normality with the Kolmogorov–Smirnoff test, group differences were tested with either the t-test for independent groups or the Mann–Whitney test for quantitative variables, while the chi-square test was used for categorical variables. Associations between the quantitative variables were estimated by calculating Spearman’s rank correlation coefficients. p values less than 0.05 were considered statistically significant. To evaluate the accuracy and predictive values of immunological parameters in serum and GCF to detect PD, and the accuracy of biochemical, clinical periodontological, and immunological parameters in detecting subclinical atherosclerosis, receiver operating characteristic (ROC) curves and areas under the curve (AUC) were calculated. In a ROC curve, the true positive rate (sensitivity) is plotted as a function of the false positive rate (100-specificity) for different cut-off points. Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold [27]. Cut-off values were calculated as the Index of Union, as described [28]. According to the suggested method [29], AUC was classified as follows: less accurate (0.5 < AUC < 0.7), moderately accurate (0.7 < AUC < 0.9), highly accurate (0.9 < AUC < 1), and perfect tests (AUC = 1). Probability levels of <0.05 were considered significant. The cut-off value for subclinical atherosclerosis was mean left/right carotid IMT ≥ 0.75, as determined in a recent study on moderate PD [30]. All analyses were performed within the statistical software SPSS 22.0 for Windows (released 2013; IBM Corp, Armonk, NY, USA). ## 3.1. The Demographic Characteristics of Study Participants The main demographic characteristics of study participants are presented in Table 1. The mean age of the total study participants was 35.92 ± 3.36 years (range of 28–40 years). The PD and control groups were age-matched, and the differences between them were not statistically significant. Females dominated in comparison to males, but the female/male ratio did not significantly differ between groups. The mean BMI was 24.27 ± 2.53 kg/m2 without a significant difference between groups. The level of education (high school versus university degree) was similar in the whole group of subjects. However, the proportion of persons with a university education was higher in the control group ($p \leq 0.05$). About three-quarters of our participants were non-smokers, and they were equally distributed between PD and control groups. ## 3.2. Comparison of Periodontal, Biochemical, and Clinical Parameters Associated with Atherosclerosis in Subjects with and without PD The first aim of this study was to compare periodontal, biochemical, and clinical parameters associated with atherosclerosis in subjects with and without PD. As expected (Table 2), clinical periodontal parameters (PI, GI, BOP, PPD, and CAL) were significantly higher ($p \leq 0.0001$) in subjects with PD when compared to subjects with healthy periodontium. The patients with PD had statistically significantly higher values of hs-CRP ($p \leq 0.0001$) and parameters of lipid profile such as triglycerides ($p \leq 0.01$), total cholesterol ($p \leq 0.05$), LDL cholesterol ($p \leq 0.01$), and fibrinogen ($p \leq 0.05$) levels. No significant differences were observed between groups regarding the values of HDL cholesterol and the number of leukocytes. The clinical parameters of atherosclerosis included IMT of the left (IMT-L) and right (IMT-R) carotid arteries and values of systolic (SBP) and diastolic (DBP) blood pressure. Although mean values of SBP and DBP were within the normal range in both groups, both parameters were higher in patients with PD ($p \leq 0.05$). IMT measurements showed no significant differences between IMT-L and IMT-R, but both parameters were significantly higher in the PD group ($p \leq 0.0001$). ## 3.3. Comparison of Cytokine Levels in Serum and GCF in Subjects with and without PD Many proinflammatory and anti-inflammatory (immunoregulatory) cytokines were determined in the serum and GCF of the study participants, as described in Section 2. The results are presented in Figure 1 and Figure 2. The levels of all proinflammatory cytokines were higher in GCF than in serum. Among them, the levels of IL-1β, MCP-1, and TNF-α, in GCF were statistically significantly higher in subjects with PD ($p \leq 0.001$ and $p \leq 0.0001$, respectively) compared to the control group. The levels of IL-8 and IL-18 in the PD group were higher both in serum ($p \leq 0.001$ and $p \leq 0.05$, respectively) and GCF ($p \leq 0.0001$ and $p \leq 0.001$, respectively) than in the periodontally healthy subjects. No significant differences were obtained between the groups in serum and GCF levels of IL-6 and IFN-α (Figure 1). A number of T-cell-producing cytokines and their inducers/enhancers were analyzed (Figure 2). The level of IFN-γ in GCF, but not in the serum, of PD subjects was higher than in the control group ($p \leq 0.05$). However, the concentrations of IL-12 (an IFN-γ-inducing cytokine) were higher in serum but not in GCF ($p \leq 0.05$). The levels of IL-17A in both the serum and GCF of the PD group were higher ($p \leq 0.05$ and $p \leq 0.01$, respectively). In contrast, the level of IL-23 (an IL-17-enhancing cytokine) was higher only in the GCF of the PD group ($p \leq 0.05$). No significant differences were found between the groups in the levels of Th2 cytokines (IL-4 and IL-33) and Treg cytokines (IL-10 and TGF-β) in both serum and GCF. A statistically significant positive correlation between serum and GCF concentrations of IFN-γ and IL-17A was found ($r = 0.35$; $p \leq 0.05$). Other correlations were not statistically significant (data not shown). To further investigate the possible predictive value of cytokines in sera and GCF for PD, we performed an ROC curve analysis (Figure 3). Evaluation of areas under the curves (AUC) showed that the levels of IL-8, TNF-α, IL-1β, IL-17, IL-18, and MCP-1 in GCF were of moderate accuracy in predicting PD (AUC values between 0.7 and 0.9). In serum, IL-8 showed moderate accuracy, whereas IL-17, IL-18, and IL-12 were of low accuracy (AUC values lower than 0.7) in predicting PD. Of them, IL-8 in GCF had the highest sensitivity (84.82) and specificity (76.92) (Table 3). ## 3.4. Correlation between Clinical Periodontal Parameters and Cytokine Levels Numerous cytokines are involved in the pathogenesis of PD, but their association with the extent of PD, determined by periodontal indices, especially in younger adults, is not well elucidated. Therefore, this was the next aim of this study. The results are presented in Table 4. The strongest association (correlation between cytokine levels in GCF and periodontal parameters) was seen with IL-8, MCP-1, and IL-23 (four periodontal indices), followed by TNF-α, IL-18, and IL-17A (three periodontal indices). IL-1β correlated with BOP and PPD, whereas IL-12 and IL-33 correlated with GI and BOP. IL-6 correlated with PPD. No statistically significant correlations were obtained between GCF levels of IFN-α, IFN-γ, IL-10, IL-4, and TGF-β. Serum levels of TNF-α correlated with four periodontal indices followed by IL-18, which correlated with three indices. IL-4 and TGF-β correlated with GI and BOP, negatively and positively, respectively. Serum levels of IFN-α correlated with PI, whereas IL-12 correlated with PPD. The correlation between either serum or GCF cytokine levels or periodontal indices in the control group was of much lesser importance (Table 4). When ROC and AUC analysis was performed to check the predictive values of serum and GCF cytokines with PPD (> or <3 mm), similar results were obtained as those presented for PD versus the control group (Supplementary Figure S1 and Supplementary Table S1). ## 3.5. Association of Periodontal, Biochemical, and Immunological Parameters with Atherosclerosis Parameters One of the main aims of this study was to determine how periodontal, biochemical, and immunological parameters correlate with atherosclerosis parameters. We used IMT as an atherosclerosis parameter because both SBP and DBP were within the normal range. The cut-off values for IMT were set up at 0.75 mm (mean left/right carotid measurements according to the applied methodology). ROC, AUC, sensitivity, and specificity were determined and analyzed (Figure 4 and Table 5). Evaluation of AUC showed that all PD indices had the same (0.85) or slightly lower values for PPD (0.83) in predicting subclinical atherosclerosis (moderate accuracy). The sensitivity was the same ($84\%$), but GI and BOP had the highest sensitivity (77.36). AUC for hs-CRP was 0.82, the specificity was $82\%$, and the sensitivity was $77.16\%$. The parameters of lipid status (total cholesterol, LDL, cholesterol, and triglycerides) showed the lowest accuracy (graded as moderate) in predicting subclinical atherosclerosis (range 0.76–0.80) of all tested parameters, with similar sensitivity and specificity (68–$80\%$ and 74–$75\%$, respectively). When the predictive values of cytokines in GCF and serum for the development of subclinical atherosclerosis were evaluated by ROC and AUC (Figure 5 and Table 6), very interesting and unexpected results were obtained. Regarding GCF cytokine values, TNF-α, IL-18, and IL-23 showed moderate accuracy (AUC: 0.76, 0.72, and 0.70, respectively) with a sensitivity of $76\%$, $68\%$, and $64\%$, respectively, and specificity of $64.15\%$, $73.58\%$, and $69.81\%$, respectively. IL-12, IFN-γ, IL-4, and TGF-β in GCF showed much lower but statistically significant accuracy (AUC: 0.66–0.69; sensitivity: 64–$69\%$; and specificity: 56.6–$71.7\%$). The prediction values of other cytokines were not statistically significant (data not shown). Of all cytokines in serum, only IL-17 and IL-23 had some prediction values in the development of subclinical atherosclerosis, categorized as moderate accuracy (AUC: 0.76 and 0.72; sensitivity: $75\%$ and $70\%$; and specificity: $69.23\%$ and $73.07\%$, respectively). ## 3.6. Correlation of Periodontal Parameters with hs-CRP, Fibrinogen, and Lipid Status Previous results showed a statistically significant association between IMT and clinical periodontal parameters and most biochemical parameters involved in the pathogenesis of atherosclerosis. Therefore, our next aim was to check how clinical periodontal parameters correlate with the hs-CRP and lipid profile of our subjects. The results, which are presented in Table 7, show that in PD subjects, only triglycerides and HDL cholesterol correlated with PPD and CAL ($p \leq 0.05$). In contrast, in control subjects, triglycerides correlated with GI ($p \leq 0.05$). Other correlations were not statistically significant. ## 3.7. Correlation of Cytokine Profile with hs-CRP, Lipid Status, and Fibrinogen In PD patients, hs-CRP correlated with several proinflammatory cytokines (IL-6, MCP-1, IL-8, IL-12, and IL-18) in GCF and IL-17A in serum ($p \leq 0.05$ or 0.01). LDL cholesterol correlated with MCP-1, IL-8, IL-18, and IL-17A ($p \leq 0.05$ or 0.01), whereas triglycerides correlated with IL-12, IL-8, and IL-18 in GCF ($p \leq 0.05$). Total cholesterol correlated with IL-18 in GCF ($p \leq 0.05$). In control subjects, IL-17A in GCF correlated with hs-CRP, whereas IL-4 and IL-33 correlated with fibrinogen and total cholesterol, respectively ($p \leq 0.05$) (Table 8). ## 4.1. Association of Cytokines with PD and Subclinical Atherosclerosis The hypothesis about the association between PD and atherosclerosis has been confirmed in many publications, and in this context, several review papers summarized hundreds of published results [4,31,32,33]. However, the studies of subclinical atherosclerosis in young adults and the mechanisms involved in these processes are limited. The main focus of our study was to check the profile of cytokines in GCF as parameters of the intensity of the inflammatory/immune response during PD, its association with the serum profile of these cytokines, and their relationship with IMT. We showed that the levels of all proinflammatory cytokines were higher in GCF than in serum. Among them, PD was characterized by higher levels of IL-1β, TNF-α, and MCP-1 in GCF, whereas the levels of IL-8 and IL-18 in the PD group were higher both in serum and GCF compared to the periodontally healthy group. The levels of cytokines associated with Th1 cells (IL-12 and IFN-γ) and Th17 cytokines (IL-23 and IL-17A) were higher in GCF, serum, or both compartments in PD subjects compared to non-PD subjects, whereas the differences between Th2 (IL-4 and IL-33) and Treg (IL-10 and TGF-β) cytokines were not significant. An altered cytokine/chemokine profile has been detected in serum, GSF, or saliva in periodontitis patients, and in this context, our results are generally similar to many other published results, which are summarized in three recent reviews [34,35,36]. Some differences depend on the study populations, cytokine gene polymorphism, the severity of PD, disease confounding factors, methods and fluid samples used for the analysis of these biomolecules, and many other factors. Locally produced proinflammatory immune mediators in PD lesions, such as IL-1β, IL-6, TNF-α, IL-8, and MCP-1, are the earliest-produced cytokines. Their activation can be partly dependent on reactive oxygen species (ROS), whose production was triggered during PD [37]. IL-1β and TNF-α have only a proinflammatory role, whereas IL-6 may have both pro- and anti-inflammatory effects [38]. IL-8, also known as CXCL8 chemokine, and MCP-1 (CCL2 chemokine) stimulate the migration of granulocytes and monocytes, respectively, into inflamed tissue [39,40]. All studies published up to now [31,32,33,34,35,36,37,38,39,40,41,42,43] showed an increased expression of these cytokines and chemokines in PD, which are responsible for the induction or exacerbation of periodontal inflammation, including the stimulation of bone resorption through activation of receptor activator of nuclear factor kappa-β ligand (RANKL) production. Some of them, such as IL-1β and IL-6, in saliva could be candidates for early diagnosis of periodontitis [36]. These cytokines can be dumped into systemic circulation, and subsequently, they may exert different effects on distant organs. Andrukhov et al., 2011 showed an increased level of TNF-α in the serum of patients with chronic periodontitis, and this finding is associated with an abundant presence of certain periodontal pathogens in the dental plaque [44]. Similar results were published for IL-1β [45,46] and IL-6 [47], especially in patients with aggressive periodontitis. Of these cytokines/chemokines, only IL-8 was increased in the serum of PD patients in our study, and this chemokine both in GCF and serum had the highest predictive values in discriminating subjects with and without PD. Moderate predictive values for PD development were shown for IL-1β, TNF-α, and MCP-1 in GCF, and all four biomolecules positively correlated with at least two (maximum four) periodontal indices. TNF-α and IL-8 in GCF showed moderate accuracy in predicting subclinical atherosclerosis, whereas IL-1β in GCF had low accuracy. The link between these proinflammatory mediators and atherosclerosis has been demonstrated in many publications, and the main mechanism is connected with increased oxidative stress [48]. In this context, gingipain from P. gingivalis has been shown to stimulate NLRP3 inflammasome and the subsequent production of IL-1β in gingival and aortic tissue [49]. TNF-α, from macrophages, activated by P. gingivalis induced endothelial–mesenchymal transitions of the endothelial cells [50]. IL-8 activates endothelial cells by increasing adhesion molecules to allow the infiltration of various immune cells into the vascular wall and stimulates chronic vascular inflammation. In addition, MCP-1 can stimulate the thrombosis, proliferation, and migration of vascular smooth muscle cells; angiogenesis; and oxidative stress [39]. Moreover, it has been shown that MCP-1 levels in human atherosclerotic lesions are associated with plaque vulnerability [40]. According to our study, it seems that MCP-1 is of lesser importance for the development of subclinical atherosclerosis. Th1 cells produce IFN-γ, a potent cytokine involved in the activation of macrophage proinflammatory functions and activation of cytotoxic T cells. Their differentiation is dependent on IL-12, produced by activated dendritic cells and macrophages, and IFN-γ, produced by NK cells [51]. The production of IFN-γ is additionally stimulated by IL-18, a cytokine of the IL-1 family with proinflammatory functions [52]. The role of IFN-γ in the pathogenesis of PD is still controversial. Studies on experimental animals mainly show the anti-inflammatory properties of this cytokine, whereas some opposite results were published in clinical studies [53]. Our results support the concept that IFN-γ has a proinflammatory role in PD because its levels in GCF were increased. The same results were presented in a meta-analysis [54]. However, neither serum nor GCF levels of IFN-γ correlated with periodontal indices. In addition, this cytokine had no predictive role in developing subclinical atherosclerosis. This was in contrast to serum levels of IL-12, which correlated with PPD. However, we did not find increased levels of IL-12 in PD, similarly as has already been published [54], although IL-12 in GCF showed some degree of accuracy in the development of atherosclerosis. We did not show an increased serum level of IFN-γ in our PD patients in contrast to another study [50]. In line with our results, Chen et al. 2016 [55] showed an increased proportion of IFN-γ + cells in the circulation of patients with chronic periodontitis compared to healthy controls, simultaneously with an increased expression of IFN-γ in tissue biopsies at both protein and mRNA levels. In addition, the authors showed a positive correlation between the proportion of circulating Th1 cells and PPD. A much better association was seen with IL-18 in our study because its levels in GCF and serum were higher in PD patients, and in addition, positive correlations with three periodontal indices were found. Both serum and GCF levels of IL-18 had predictive values for the development of PD. In addition, GCF levels of IL-18 had a predictive value for the development of subclinical atherosclerosis, a finding that was not previously published. Several studies reported the role of IFN-γ and IL-18 in the pathogenesis of atherosclerosis [56,57,58], and our findings related to the association of GCF concentrations of IFN-γ, IL-12, and IL-18 with IMT support the proposed concept that an increased Th1 response caused by PD could be a risk factor for atherosclerosis even in its early stage. The role of Th2 cells in PD still remains controversial. In humans, numerous studies have supported the hypothesis that Th2 cells are associated with progressive lesions [59,60]. In contrast, several studies provided evidence that the upregulation of Th1 and downregulation of Th2 responses are involved in periodontal tissue destruction [61,62,63]. Our study did not support the hypothesis that Th2 cells, as judged by unchanged levels of IL-4 in GCF, play a destructive role in PD. The unchanged levels of IL-33 are in line with this presumption. IL-33 is dominantly associated with Th2 cells, but this alarmin plays different pro- and anti-inflammatory functions. Experiments with IL-33-receptor-deficient mice showed that IL-33 exacerbates periodontal disease through the induction of RANKL [64]. However, some data demonstrated that IL-33 levels in GCF were significantly lower in patients with chronic periodontitis than in patients with gingivitis and patients without periodontal disease [65]. The suppressive role of IL-33 in bone resorption via RANKL inhibition and OPG induction in human PD was also supposed in one study [66]. The possible anti-inflammatory role of Th2 cells in PD is additionally based on the negative correlation of IL-4 in GCF with GI and BOP. In addition, IL-4 has been shown to have a certain degree of association with IMT. A positive correlation between IL-33 in GCF and GI and BOP indicates that this cytokine may have a proinflammatory role in PD. The Th17 subset is important for immunity against extracellular bacteria and fungi and also for the pathogenesis of autoimmunity and cancer. Overproduced cytokines of Th17 cells, especially IL-17A, IL-17F, IL-21, and IL-22, play a role in osteodestructive diseases such as rheumatoid arthritis (RA) and PD. IL-1β, IL-6, and TGF-β are important for Th17 differentiation, whereas IL-23 is important for the expansion of differentiated Th17 cells [63]. Osteodestructive effects of IL-17A are mediated by RANKL, either directly or indirectly by stimulating TNF-α, IL-1β, and IL-6, which further promote RANKL expression. Th17 cells themselves also express RANKL and thus participate directly in osteoclastogenesis [67]. Novel data suggest that IL-17 is disease-promoting in the early stages and protective in the late stages of experimental periodontitis [68]. In our study, IL-17A showed the most prominent changes of all investigated Th cytokines. Namely, we showed an increase in both serum and GCF concentrations of IL-17 and positive correlations of this cytokine in GCF with BOP, PPD, and CAL. IL-23 was increased only in GCF, and its concentration correlated with four periodontal indices. The association of the IL-17/IL-23 axis with atherosclerosis was confirmed by the positive correlations of both cytokines with IMT, and according to ROC and AUC analyses, both cytokines had predictive values for the development of subclinical atherosclerosis. The proatherogenic role of IL-17 is confirmed by many experimental studies in mice and humans including those showing the accumulation of IL-17+ cells in the atherosclerotic vascular wall [69]. In addition, oxidized LDL promoted IL-6 production, which then induced Th17 cell differentiation [70]. In contrast, there are some opposite results suggesting a role for IL-17 in promoting fibrous plaque stability [71]. However, when acted together with IFN-γ, both cytokines promoted plaque instability [57]. One study showed that mRNA levels of IL-23 and IL-23R were significantly increased in carotid plaques in comparison with nonatherosclerotic arteries, and this finding correlated with increased plasma levels of IL-23 and increased IL-23-dependent production of IL-17 by mononuclear cells of patients with atherosclerosis [72]. Our findings support the concept of the significance of the IL-17/IL-23 axis in the pathogenesis of atherosclerosis, at least in its early stage, bearing in mind the mean age of our study participants and mean carotid IMT. TGF-β and IL-10 are the main Treg cytokines that downregulate inflammation and immune responses. Although their role in the immunopathogenesis of PD has not been directly investigated, their role has been postulated due to the presence of Foxp3+ T cells in periodontal tissue and increased levels of these cytokines after periodontal treatment [33]. In addition, IL-10 has been shown to dampen an IL-17-mediated periodontitis-associated inflammatory network by acting on the cells of innate immunity [73]. TGF-β is involved in the development of Treg cells and plays a role in healing during PD [74]. Furthermore, a decrease in TGF-β1 in sera was shown with the progression of experimental periodontitis [75]. We did not find any difference in serum or GCF levels of both IL-10 and TGF-β, nor were their levels associated with IMT, indicating that, at least in our study on patients with moderate PD and subclinical atherosclerosis, these immunoregulatory cytokines do not play a significant role. ## 4.2. Association of Dyslipidemia and CRP with PD Status and Atherosclerosis Dyslipidemia, characterized by elevated total and LDL cholesterol, triglycerides, and lipoprotein (a), as well as decreased levels of HDL, is a major risk for atherosclerosis and cardiovascular diseases due to the chronic accumulation of lipid-rich plaque in arteries [76]. Atherosclerosis is accompanied by local inflammation in the vascular wall due to endothelial and vascular smooth muscle cell dysfunction. Both the innate and adaptive immune response is involved in the initiation and progression of atherosclerosis [77]. On the other hand, dyslipidemia modulates the immune response by activating immune cells and the secretion of proinflammatory mediators and cytokines [78]. Chronic PD is characterized by systemic inflammation, as judged by increased levels of CRP, fibrinogen, and other mediators [79], and our results are in accordance with similar results published in young adults of the same age [17]. However, we found that hs-CRP, but not fibrinogen, had a predictive role in atherosclerosis. The role of CRP as a predictive marker of atherosclerosis through its association with IMT has already been well documented [80,81,82]. However, it is interesting that in our study, the IL-6/IMT association was not statistically significant. This finding contradicts the knowledge that IL-6 is the main inducer of CRP synthesis [48]. The discrepancy can be explained by the fact that our study was performed on a relatively younger population in which an increase of IMT in the PD group was modest (lesser than 1 mm). IL-6 may also exert anti-inflammatory properties. In addition, both IL-1β and TNF-α may act synergistically with IL-6 to stimulate CRP synthesis [48]. Dyslipidemia together with a proinflammatory status characterized by increased levels of CRP, fibrinogen, cytokines, and other biomolecules is mutually connected with PD through bidirectional interactions as suggested by numerous cross-sectional and longitudinal prospective clinical studies [83]. Based on these findings and a well-documented association of PD with atherosclerosis [32,84], our study aimed to see how clinical parameters of PD and cytokines correlate with the lipid status in our study group. Our results showed that all five periodontal indices had a better predictive role in developing subclinical atherosclerosis than hs-CRP and lipids. We expected that most periodontal indices correlated positively with total cholesterol, LDL, and triglycerides and negatively with HDL because such a relationship has been already published in the literature for adults. Based on 19 publications, Nepomuceno et al., in a meta-analysis, demonstrated that PD is significantly associated with a reduction in HDL and an elevation in LDL and triglyceride concentrations [85]. Yeun et al. showed in a study of 809 patients with PD, aged >50 years, that HDL alleviated PD, while LDL exacerbated PD. In contrast, total cholesterol and triglycerides were not connected with PD [86]. However, we found that only triglycerides and LDL correlated with PPD and CAL, whereas LDL, triglycerides, and total cholesterol had a predictive role in atherosclerosis. The association between cytokines produced during chronic PD and dyslipidemia seems to be an important pathway in the pathophysiology of atherosclerosis [87], but this mechanism is not systematically investigated. It was hypothesized that proinflammatory cytokines from GCF or systemic circulation, such as TNF-α, IL-1β, and IL-6, induce hyperlipidemia due to enhanced hepatic lipogenesis, increased synthesis of triglycerides, and reduced clearance of both triglycerides and LDL. These changes could be due to reduced lipoprotein lipase activity or increased adipose tissue lipolysis [77]. However, in our study, none of these cytokines in the serum of PD patients were associated with dyslipidemia, suggesting that other factors released from inflamed periodontal tissue could influence lipid status. Of these hypothetic factors, bacterial lipopolysaccharides, matrix metalloproteinases, stress, altered neuroendocrine axis, smoking, and genetic or gender predispositions could be relevant [77]. The only significant positive correlation in our study was found between serum IL-17A and LDL. Similar results were published in another study [75]. A cross-talk between IL-17A and lipids was shown in a study, where hyperlipidemia induced IL-17A production and the subsequent activation of human aortic endothelial cells [88]. The postulated mechanisms of these interactions are numerous. It has been shown that IL-17A increases lipolysis and alters adipogenesis. Adipose tissue from obese human subjects promotes IL-17A release from CD4+ T cells. In addition, human pre-adipocytes stimulated with IL-17A upregulate different genes associated with fibrosis, inflammation, and the synthesis of matrix metalloproteinases [89]. An association of LDL, triglycerides, and total cholesterol with some proinflammatory cytokines in GCF (MCP-1, IL-12, IL-8, or IL-18) could be explained by an indirect effect. Namely, it was suggested that systemic exposure to P. gingivalis in PD patients can be a trigger for hyperlipidemia [90]. ## 4.3. Limitation of the Study Our study has many limitations. At first, the number of subjects included in the study was relatively small. We obtained better results of correlations when the whole group of subjects was analyzed ($$n = 78$$) (data not shown), most probably because a large number of subjects increases the statistical significance and because some subjects without PD had signs of mild gingivitis. In such circumstances, some parameters overlapped between the groups. These facts can explain some correlations that were obtained in the control group. Only IMT was used as a parameter of subclinical atherosclerosis, and biologically implausible IMT values may be due to natural variation between and within individuals or from routine measurement errors. There are other parameters of subclinical atherosclerosis, such as abdominal or neck interference [91]. However, they were not applied because obese patients (grades II and III) were excluded from our study. This was the reason BMI was not included in the analysis. In our study, the participants were not adequately sex-matched due to the predominance of females. In addition, we did not separate smokers from non-smokers because that procedure would further reduce the number of subjects per group. The quantification of GCF could increase the validity of cytokine values. However, the obtained results are a good introduction to more extensive studies. ## 5. Conclusions As extensively discussed, many experimental and clinical studies provided evidence that PD is associated with atherosclerosis, and in this context, PD-induced inflammation is recognized as a dominant etiopathogenetic mechanism. In our study, a number of proinflammatory, Th1, and Th17 cytokines were elevated in GCF fluid, serum, or both compartments in PD patients. There was a significant association of clinical periodontal parameters, proinflammatory cytokines, hs-CRP, and LDL with carotid ITM as a measure of subclinical atherosclerosis. 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--- title: Metabolic and Transcriptomic Changes in the Mouse Brain in Response to Short-Term High-Fat Metabolic Stress authors: - Ji-Kwang Kim - Sehoon Hong - Jina Park - Seyun Kim journal: Metabolites year: 2023 pmcid: PMC10051449 doi: 10.3390/metabo13030407 license: CC BY 4.0 --- # Metabolic and Transcriptomic Changes in the Mouse Brain in Response to Short-Term High-Fat Metabolic Stress ## Abstract The chronic consumption of diets rich in saturated fats leads to obesity and associated metabolic disorders including diabetes and atherosclerosis. Intake of a high-fat diet (HFD) is also recognized to dysregulate neural functions such as cognition, mood, and behavior. However, the effects of short-term high-fat diets on the brain are elusive. Here, we investigated molecular changes in the mouse brain following an acute HFD for 10 days by employing RNA sequencing and metabolomics profiling. Aberrant expressions of 92 genes were detected in the brain tissues of acute HFD-exposed mice. The differentially expressed genes were enriched for various pathways and processes such as superoxide metabolism. In our global metabolomic profiling, a total of 59 metabolites were significantly altered by the acute HFD. Metabolic pathways upregulated from HFD-exposed brain tissues relative to control samples included oxidative stress, oxidized polyunsaturated fatty acids, amino acid metabolism (e.g., branched-chain amino acid catabolism, and lysine metabolism), and the gut microbiome. Acute HFD also elevated levels of N-acetylated amino acids, urea cycle metabolites, and uracil metabolites, further suggesting complex changes in nitrogen metabolism. The observed molecular events in the present study provide a valuable resource that can help us better understand how acute HFD stress impacts brain homeostasis. ## 1. Introduction Increasing rates of obesity and related metabolic disorders in recent decades have become a serious public health concern [1,2]. Obesity is a chronic disease that is closely linked to major comorbidities such as type two diabetes, hypertension, and certain types of cancer [3]. Although obesity is considered a multifactorial disorder with genetic dispositions and environmental components (e.g., a sedentary lifestyle), it is ultimately caused by an energy imbalance when calorie intake exceeds energy expenditure, which has been largely attributed to the consumption of diets rich in fat and sugars [4]. Particularly, the prolonged consumption of a high-fat diet (HFD), which increases food and caloric intake per meal, has been demonstrated to induce weight gain and increase adiposity in both human and animal models [5,6]. HFDs are characterized by a high content of saturated fatty acids such as palmitate and stearate. The physiological impacts of prolonged HFD exposure and diet-induced obesity (DIO) are known to dysregulate the autonomic and metabolic functions related to energy homeostasis throughout the development of obesity, insulin resistance, and ectopic fat accumulation such as hepatic steatosis [5,6]. The effects of HFDs in the brain have emerged as key routes that lead to nutrient oversupply, resulting in the deterioration of metabolic homeostasis. Multiple studies have revealed that long-term HFD consumption leads to neuroinflammation and leptin resistance in the hypothalamus, which governs the food intake response [7,8]. Mechanistically, HFD-mediated endoplasmic reticulum stress appears to trigger apoptosis in hypothalamic neurons [9,10]. Furthermore, clinical and preclinical studies have consistently demonstrated that diets high in saturated fats can impair higher-order brain functions including cognition and psychiatric control [11]. Even short-term HFD intake has been associated with impaired attention and visual memory in human studies [12,13]. Notably, recent evidence has demonstrated that obese people are more prone to developing neurological pathologies such as stroke, depression, and neurodegenerative diseases. Therefore, chronic HFD consumption is considered a risk factor for cognitive impairment, brain aging, and even dementia [14,15,16,17]. Many previous studies have systemically assessed how HFDs impact the genome-wide molecular landscape in peripheral metabolic organs [18,19,20,21]. However, only a few investigations to date have analyzed the impact of a chronic HFD on the brain [22,23]. Given that cells and tissues undergo complex indirect molecular changes over time in response to chronic metabolic stress, characterizing the effects of acute and short-term HFD exposure at the molecular level is particularly critical. Here, we employed a multiomics approach in mice to identify core differentially expressed molecules and pathways underlying acute HFD metabolic stress. After 10 days of HFD feeding, RNA-seq and LC-MS/MS analyses were respectively conducted to detect differences in the gene expression and metabolite profiles of the whole brain of HFD-exposed and control mice. Intriguingly, we detected alterations in metabolites and transcriptional reprogramming, thus providing insights into the genetic and metabolic changes linked to the central responses to acute HFD stress. ## 2.1. Animals C57BL/6J male mice were used for the experiments (8–10 weeks old; KRIBB, Daejeon, Republic of Korea). Mice were housed under specific pathogen-free conditions on a 12 h light–dark schedule, and their food and water were provided ad libitum. Animal protocols were performed in accordance with guidelines approved by the Korea Advanced Institute of Science and Technology Animal Care and Use Committee. Mice were fed a normal chow diet (NCD) or high-fat diet (HFD, 60 kcal% fat) for 10 days. After removing the olfactory bulbs and cerebellum, the whole forebrain was separated into two hemispheres. Each hemisphere was subject to RNA-seq and metabolomics analysis. ## 2.2. Total RNA Extraction and RNA-Sequencing Total RNA was purified using Trizol reagent (Invitrogen, Waltham, MA, USA). RNA quality was evaluated with Agilent 2100 bioanalyzer using the RNA 6000 Nano Chip (Agilent Technologies, Amstelveen, The Netherlands). RNA was quantified using ND-2000 Spectrophotometer (Thermo Inc., Wilmington, DE, USA). RNA libraries were prepared using QuantSeq 3′ mRNA-Seq Library Prep Kit (Lexogen, Inc., Vienna, Austria) according to the manufacturer’s instructions. Five hundred ng of prepared total RNA were hybridized with an oligo-dT primer containing an Illumina-compatible sequence at its 5′ end, followed by reverse transcription. Second strand synthesis was initiated by random primers with an Illumina-compatible linker sequence at the 5′ end. The double-stranded library was purified using magnetic beads. After the library was amplified to add the complete adapter sequences required for cluster generation, it was purified from the PCR components. High-throughput sequencing was performed as single-end 75 bp sequencing using NextSeq 550 (Illumina, Inc., Madison, WI, USA). QuantSeq 3′ mRNA-Seq reads were aligned using Bowtie2 [24]. Bowtie2 indexes were generated from genome assembly sequences or representative transcript sequences for alignment to the genome and transcriptome. Sequenced reads were trimmed for adaptor sequence, then mapped to mm10 (UCSC) whole genome using Bowtie2. The alignment file was used to assemble transcripts, estimate their abundances and detect differential gene expression. Based on counts from unique and multiple alignments using coverage in Bedtools [25], differentially expressed genes were determined. The RC (read count) data were processed based on the quantile normalization method using EdgeR within R (https://www.R-project.org (accessed on 25 August 2022)) using Bioconductor [26]. Gene classification was based on searches done by DAVID (http://david.abcc.ncifcrf.gov (accessed on 2 September 2022)) and Medline databases (http://www.ncbi.nlm.nih.gov (accessed on 2 September 2022)). Data mining and graphic visualization were performed using ExDEGA (Ebiogen Inc., Seongdong-gu Seoul, Republic of Korea). Sequence data were uploaded in the NCBI GEO (accession number GSE226771). ## 2.3. Global Metabolite Profiling and Data Analysis Samples were prepared, as previously described at Metabolon, Inc. (Morrisville, NC, USA) [27,28]. Briefly, the MicroLab STAR® system (Hamilton Company, Reno, NV, USA). A recovery standard was added prior to the first step in the extraction process for QC purposes. Proteins were precipitated using methanol for 2 min (Glen Mills GenoGrinder 2000). Extracts were subject to different analyses including UPLC-MS/MS with positive ion mode electrospray ionization, UPLC-MS/MS with negative ion mode electrospray ionization, UPLC-MS/MS polar platform (negative ionization), and GC-MS. Controls were analyzed in parallel with the experimental samples and a pooled matrix sample. Metabolomic analyses were performed by Metabolon, Inc. using ultrahigh-performance UHPLC/MS/MS, as previously described [29]. The LC/MS part was based on a Waters ACQUITY UPLC and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer with 35,000 mass resolution. Extracts were dried and reconstituted in acidic or basic LC-compatible solvents, each of which contained 8 or more injection standards. Sample extracts were analyzed using positive and negative ion conditions using separate columns (Waters UPLC BEH C18-2.1 × 100 mm, 1.7 µm). For elution, water and methanol with $0.1\%$ formic acid or 6.5mM ammonium bicarbonate were used. Samples were also analyzed via negative ionization using a HILIC column (Waters UPLC BEH Amide 2.1 × 150 mm, 1.7 µm) under a gradient consisting of water and acetonitrile with 10 mM ammonium formate. The MS analysis alternated between MS and data dependent MS2 scans using dynamic exclusion, and the scan range was from 80–1000 m/z. For GC-MS, samples were dried under vacuum for a minimum of 18 h prior to derivatization. Derivatized samples were separated on a $5\%$ diphenyl/$95\%$ dimethyl polysiloxane fused silica column (20 m × 0.18 mm ID; 0.18 mm film thickness) with helium as a carrier gas and a temperature ramp from 60 to 340 °C in a 17.5 min period. Samples were analyzed on a Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer using electron impact ionization. The scan range was from 50–750 m/z. Raw data were extracted, peak-identified, and QC processed using Metabolon’s hardware and software. These systems are built on a web-service platform utilizing Microsoft’s. NET technologies, which run on high-performance application servers and fiber-channel storage arrays in clusters to provide active failover and load balancing. Compounds were identified by comparison to library entries of purified standards or recurrent unknown entities Biochemical identifications are based on three criteria: retention index within a narrow RI window of the proposed identification, accurate mass match to the library +/−0.005 amu, and the MS/MS forward and reverse scores between the experimental data and authentic standards. The MS/MS scores are based on a comparison of the ions present in the experimental spectrum to the ions present in the library spectrum. While there may be similarities between these molecules based on one of these factors, the use of all three data points can be utilized to distinguish and differentiate biochemicals. More than 3300 commercially available purified standard compounds have been acquired and registered into LIMS for distribution to both the LC-MS and GC-MS platforms for the determination of their analytical characteristics. A variety of curation procedures were carried out to ensure that a high-quality data set was made available for statistical analysis and data interpretation. The QC and curation processes were designed to ensure accurate and consistent identification of true chemical entities and to remove those representing system artifacts, misassignments, and background noise. Peaks were quantified using the area under-the-curve. For studies spanning multiple days, a data normalization step was performed to correct variation resulting from instrument interday tuning differences. Essentially, each compound was corrected in run-day blocks by registering the medians to equal one (1.00) and normalizing each data point proportionately. Statistical calculations were made by performing Welch’s two-sample t-test and a Wilcoxon test. ## 3.1. Transcriptome Analysis of the Brain after Short-Term HFD Feeding Adult male mice were fed an HFD for 10 days. To gain a deeper understanding of the molecular pathways affected by short-term HFD stress in the brain, RNA-Seq analyses were conducted using forebrain tissues. A total of 92 differentially expressed genes (DEGs) (36 upregulated and 56 downregulated) were identified between the control and HFD-exposed animals based on a fold change (FC) threshold of ≥1.5 for upregulation and ≤−1.5 for downregulation were represented with volcano plat (Figure 1A) and heatmap (Figure 1B). All gene expression data are summarized in Supplementary Table S1. Gene ontology (GO) enrichment analysis was conducted to clarify the biological pathways and functions in the mouse brain affected by HFD (Figure 2A). Several modestly but significantly enriched GO categories were identified in the brains of “the HFD-treated mice, including “phosphorylation”, “positive regulation of ERK1 and ERK2 cascade” and “intracellular signal transduction”, suggesting changes in the neural signaling events (Figure 2B). Moreover, KEGG pathway analysis elucidated multiple significantly enriched infection-related pathways (e.g., “African trypanosomiasis”, “human T-cell leukemia virus 1 infection”, “malaria”, “herpes simplex virus 1 infection”), in addition to the “cellular senescence” and “sphingolipid” signaling pathways (Supplementary Figure S1A,B). ## 3.2. Unique Alterations in a Broad Range of Metabolites in the Mouse Brain Exposed to Acute HFD Stress To identify HFD-induced metabolic changes, we next performed a global untargeted metabolomics analysis. To identify the differences in the metabolic profiles of the normal chow diet (NCD) and HFD groups, the sample distribution patterns were visualized using a principal components analysis (PCA) score plot. As shown in Figure 3A, our PCA analyses revealed significant heterogeneity and overlap among the NCD and HFD groups. Despite the low degree of separation, Welch’s two-sample t-tests revealed 59 statistically significant metabolites (p ≤ 0.05) out of 407 identified in total after 10 days of HFD feeding (Figure 3B). These results demonstrated that the brain metabolome was moderately affected when the mice were fed with the HFD. Random forest (RF) analysis was then conducted to identify the most important metabolites and exclude associations by chance (Figure 3C). Using the primary groupings of the HFD and control samples, the RF analysis had a predictive accuracy of $92\%$. The main metabolites that were dysregulated in the HFD brain tissue samples compared to the NCD (control) samples were involved in oxidative stress, amino acid metabolism (e.g., branched-chain amino acid catabolism, lysine metabolism), and microbiome metabolism. ## 3.3. HFD Treatment Increases Oxidative Stress Compared to the control group, the HFD group exhibited significant differences in 2-hydroxybutyrate (AHB) and ophthalmate (Figure 4). These metabolites are derived from α-ketobutyrate, a metabolite that can be formed via cystathionine in the transsulfuration pathway or from threonine. AHB is synthesized when α-ketobutyrate is reduced by lactate dehydrogenase (LDH) or α-hydroxybutyrate dehydrogenase (alpha-HBDH) [30]. Notably, AHB has also been identified as an early marker for insulin resistance and altered glucose tolerance [31,32]. Changes in AHB levels may thus be linked to alterations in glucose sensitivity in HFD-fed mice [33]. Ophthalmate, on the other hand, is a compositional derivative of glutathione that is formed when the cysteine residue of glutathione is replaced with a 2-aminobutyrate residue [34,35,36]. A 2-aminobutyrate can be derived enzymatically from α-ketobutyrate. The levels of AHB and ophthalmate typically increase in response to increased oxidative stress within cells. The metabolic changes described herein are therefore consistent with increases in oxidative stress. ## 3.4. Elevated Levels of Oxidized Polyunsaturated Fatty Acids Polyunsaturated fatty acids (PUFAs) ingested from the diet or produced from phospholipase A-mediated hydrolysis are peroxidized enzymatically by lipoxygenases or nonenzymatically through reactive oxygen radicals [37,38]. These bioactive oxidized PUFAs have been linked to a wide variety of pathological conditions such as cardiovascular disease, diabetes, inflammation, obesity, and cancer [39,40,41,42,43]. The brain tissues of the HFD-fed mice displayed elevated levels of 13-hydroxyoctadecadienoic acid (13-HODE), 9-hydroxyoctadecadienoic acid (9-HODE), and 12-hydroxyeicosatetraenoic acid (12-HETE) (Figure 5), suggesting increased oxidative stress and inflammation. ## 3.5. Changes in Branched Amino Acid (BCAA) Metabolism The HFD and control NCD groups exhibited clear differences in BCAA metabolism. As shown in Figure 6, the HFD group presented higher levels of isoleucine and valine. Additionally, the HFD group accumulated higher levels of several BCAA catabolites, including alpha-hydroxyisovalerate, beta-hydroxyisovalerate, 2-methylbutrylcarnitine, tiglyl carnitine, isobutyrylcarnitine, and 3-hydroxyisobutyrlcarnitine. Alpha-hydroxyisovalerate is a 2-hydroxycarboxylic acid formed from 4-methyl-2-oxopentanoic acid (i.e., a keto acid derived from leucine). On the other hand, 2-methylbutryl-carnitine, tiglyl carnitine, isobutyrylcarnitine, and 3-hydroxy-isobutyrlcarnitine are carnitine derivatives of fatty acid coenzyme A (CoA), which are formed in the downstream steps of BCAA catabolism. Collectively, these changes are consistent with alterations in the rates of BCAA utilization and/or uptake in the HFD-fed mice, suggesting alterations in energy metabolism and neurotransmitter synthesis [44]. ## 3.6. Changes in Lysine Metabolism Lysine degradation in humans occurs through two distinct but convergent pathways: the saccharopine pathway and the pipecolate pathway. The saccharopine pathway is the main catabolic pathway through which lysine catabolism occurs. However, the pipecolate pathway is dominant in the brain [45]. Higher levels of lysine and several lysine-derived catabolites (pipecolate, 2-aminoadipate, and glutarate) were detected in the HFD group (Figure 7). In turn, these changes were consistent with alterations in the rates of lysine uptake and/or catabolism. It should be noted that 2-aminoadipate is a marker of oxidative stress [46]. The 2-Aminoadipate can also antagonize neuroexcitatory activity modulated by the N-methyl-D-aspartate (NMDA) receptor [47]. Moreover, lower levels of 5-aminovalerate were observed in the HFD group, and 5-Aminovalerate can be generated either endogenously or through bacterial activity. Lower levels of this metabolite may thus reflect alterations in gut microbiome metabolism, as discussed below [48]. The HFD-fed group displayed elevated levels of all three branched-chain amino acids (BCAAs), including leucine, isoleucine, and valine (Figure 6). The changes in these amino acids reflect either increased protein breakdown within brain cells (e.g., neurons, glia) or increased uptake of amino acids into the brain from the bloodstream. Among other amino acid metabolites, significant increases in the lysine catabolite 5-aminovalerate were also found in the brain tissues of the HFD-fed mice, indicating alterations in the utilization, catabolism, and/or uptake of lysine. ## 3.7. N-Acetylamino Acids N-acetyl amino acids are synthesized either via specific N-acetyltransferases or throughout the degradation of N-acetylated proteins by specific hydrolases. N-terminal acetylation of proteins is known to protect and stabilize proteins [49,50]. In this study, the HFD group displayed elevated levels of several N-acetylated amino acids including N-acetylthreonine, N-acetylasparagine, N-acetylglutamine, N-acetylhistidine, and N-acetylleucine (Figure 8). These changes suggest that the HFD treatment induces amino acid imbalances such as increased protein breakdown. ## 3.8. Alterations in Arginine Metabolism, Urea Cycle Metabolites, and Uracil Metabolites The HFD group exhibited lower arginine levels, which were accompanied by elevated urea levels (Figure 9A), suggesting increased arginase activity that hydrolyzes arginine into urea and ornithine. In addition to these changes, the HFD group also displayed elevated levels of homocitrulline, a metabolite formed from lysine and carbamoyl phosphate via the activity of ornithine-transcarbamylase (OTC). Homocitrulline is a metabolic precursor of homoarginine, an arginine analog that can inhibit arginase. It was unclear whether homocitrulline accumulated due to changes in lysine metabolism (described above) or alterations in arginase activity. N-delta-acetylornithine was also present at lower levels in the HFD group. This metabolite can be derived from both ornithine and glutamate. The HFD brain samples also exhibited elevated levels of 5,6-dihydrouracil and 3-ureidopropionate, both of which are metabolites involved in uracil catabolism (Figure 9B). These changes were consistent with alterations in the rate of uracil degradation and may be related to changes in the urea cycle, as both involve changes in nitrogen balance. ## 3.9. Gut Microbiome Metabolites The brains of the HFD-fed mice exhibited alterations in the levels of ippurate and several aromatic amino acid catabolites of microbial origin such as p-cresol sulfate, phenol sulfate, indolepropionate, and 3-indoxyl sulfate (Figure 10). Hippurate is synthesized in the liver from glycine and benzoic acid [51]. The p-cresol sulfate and phenol sulfate are generated from the microbial breakdown of tyrosine, whereas indolepropionate and 3-indoxyl sulfate are formed via the microbial breakdown of tryptophan. Therefore, the observed alterations in the levels of these metabolites in the brain could reflect differences in the rates at which these catabolites are produced or, alternatively, differences in the rates of brain uptake. ## 3.10. Integration Analysis of Transcriptomic and Metabolomic Data Multiomic profiling is a comprehensive approach that provides more indepth insights into the molecular mechanisms of biological phenomena compared to transcriptomic, proteomic, or metabolomic analyses alone [52]. Therefore, MetaboAnalyst 5.0 was used in this study to conduct joint pathway analysis of transcriptomic and metabolomic data. Notably, the dysregulated pathways at both the metabolomic and mRNA expression levels in acute HFD-exposed brain were involved in aminoacyl-tRNA biosynthesis, arginine biosynthesis, valine–leucine–isoleucine biosynthesis, and nitrogen metabolism, among other processes. Figure 11 shows the altered pathways, including the metabolic pathways of interest. Four metabolic pathways (i.e., aminoacyl-tRNA biosynthesis, arginine biosynthesis, valine–leucine–isoleucine biosynthesis, and nitrogen metabolism) had p-values < 0.05 and impact coefficients > 0.2, indicating that these pathways were regulated due to HFD treatment. ## 4. Discussion High-fat diets are known to contribute to central energy homeostasis and neural functions by dysregulating synaptic plasticity, exacerbating neuroinflammation, and suppressing long-term potentiation. Although many studies have demonstrated that chronic HFD treatment induces gene expression changes in the brain, the impact of short-term HFD on the brain had remained largely unexplored. Therefore, this study sought to define the major molecular changes in the brain induced by acute HFD treatment at the transcriptome and metabolite level in an unbiased manner. According to our RNA-Seq results, the expression of 92 mRNAs changed significantly in the mouse brain in response to acute HFD exposure, of which 36 mRNAs were upregulated and 56 were downregulated. GO enrichment analysis of the differentially expressed mRNAs revealed the dysregulation of the “phosphorylation”, “positive regulation of ERK1 and ERK2 cascade”, and “intracellular signal transduction” pathways, among others. A recent transcriptomic study conducted by Yoon et al. demonstrated that chronic (i.e., eight weeks) HFD treatment altered the expression of synaptotagmin genes and NMDA receptor subunits in mice [22]. In our 10 day study, the HFD-treated mice did not exhibit perturbations in the aforementioned target genes. Instead, we observed aberrant upregulation of serotonin receptor 2A and synaptopodin-2, which is known to control dendritic spine plasticity in the hippocampus [53]. Moreover, we observed a notable downregulation of several key signaling factors involved in neural communication such as phospholipase C 1 beta, opioid receptor delta 1, and cyclin-dependent kinase 2 (Cdk2). Acute HFD treatment also markedly affected the expression of genes responsible for brain development and morphogenesis (e.g., Foxb1, Foxa2, ASPM, RFX4) [54,55,56,57], further confirming the link between acute HFD treatment and neuronal signaling defects. Surprisingly, acute HFD treatment had no effect on metabolic endocrine factors or enzymes associated with energy metabolism. Instead, we observed changes in the expression of metabolic enzymes such as aldehyde dehydrogenase (ALDH3b2), which is involved in the metabolism of a toxic aldehydic metabolite of dopamine in the brain [58], suggesting possible changes in catecholamine networks. Our findings also demonstrated the downregulation of GTP cyclohydrolase 1 (GCH1), a known Parkinson’s disease (PD) risk gene. Specifically, GCH1 mediates the rate-limiting step for the production of tetrahydrobiopterin (BH4), an essential cofactor required for the synthesis of monoaminergic neurotransmitters such as serotonin and dopamine [59]. GCH1 deficiency was recently shown to activate the innate immune response in the brain [60]. Furthermore, genes involved in immunity and infection [e.g., chemokine ligand 19 (ccl19), dedicator of cytokinesis 8 (DOCK8), and intercellular adhesion molecule-1 (ICAM-1)] [61,62] were also significantly dysregulated. Taken together, these transcriptomic changes in the brain in response to acute HFD feeding provide key insights into the molecular mechanisms underlying HFD-induced neural dysfunction, which can lead to impairments in cognition, mood control, and central nervous system (CNS) immunity. Consistent with the results of our RNA-seq analyses, acute HFD treatment did not alter the levels of metabolites related to energy and glucose metabolism. Instead, our metabolomic data revealed marked HFD-induced changes in metabolites related to oxidative stress, amino acid metabolism (e.g., BCAA catabolism and lysine metabolism), nitrogen metabolism (e.g., urea cycle and uracil metabolism), and the gut microbiome. In a previous study, nuclear magnetic resonance (NMR)-based metabolomics analyses revealed significant changes in alanine, creatine/phosphocreatine, taurine, and myo-inositol levels after eight weeks of chronic HFD feeding [63]. In another study, long-term HFD treatment modulated the levels of membrane phospholipids and diacylglycerol in the brain [64]. Although both acute and chronic HFD treatment increased the levels of metabolites associated with oxidative stress, acute HFD treatment appeared to have a more pronounced effect on amino acid metabolism and nitrogen metabolism in the brain during the early stages of the feeding experiment. The major changes in BCAA and lysine metabolism observed after HFD treatment suggested that HFD could significantly affect neural control. Glutamate, which is synthesized via BCAA transamination, is an excitatory neurotransmitter and substrate for the production of the major inhibitory neurotransmitter gamma-aminobutyric acid (GABA). Current understandings of the role of BCAAs in the brain are consistent with the association of glutamatergic and/or GABAergic systems in the etiology of neurological disorders. Fluctuations in BCAA levels significantly influence CNS function, particularly the balance between excitation and inhibition. BCAA metabolism contributes to the synthesis of new glutamate when this amino acid becomes depleted in the neurons in response to oxidative stress, and, therefore, this process plays a crucial role in brain function homeostasis. Decreases in the levels of the BCAAs are typically observed in psychiatric patients with major depressive disorder, immune-related major depression, and bipolar disorder [65,66,67]. BCAA levels are also elevated in the hippocampus after antidepressant treatment [68]. Furthermore, 5-aminovaleric acid, which is endogenously synthesized or derived from the metabolism of lysine by gut microbiota, is also known to act as a methylene homolog of GABA and functions as a weak GABA agonist [69]. Recently, 5-aminovaleric acid was also identified in the plasma and brain tissues of Alzheimer’s disease patients [70]. The elevated levels of N-acetyl amino acids (e.g., N-acetylthreonine, N-acetylasparagine, N-acetylglutamine, N-acetylhistidine, and N-acetylleucine) in response to acute HFD also drew our attention. N-terminal-acetylation reactions mainly occur through N-acetyltransferase enzymes (NATs) [49,50]. N-acetylated amino acids such as N-acetylhistidine can be also produced by N-acylpeptide hydrolases which can degrade target proteins. In addition to the NAT enzymes and protein-based acetylation, Free amino acids can be acetylated. For example, N-acetylhistidine can be biosynthesized from L-histidine and acetyl-CoA by the enzyme histidine N-acetyltransferase. Many N-acetylamino acids are classified as uremic toxins when they are found in high abundance in the serum or plasma [71]. Uremic toxins are a diverse group of endogenously produced metabolites that can cause kidney damage and neurological deficits if not properly cleared or eliminated by the kidneys. In addition to precisely defining the molecular pathways through which HFD feeding leads to increased N-acetylamino acids, their effects on neural functions should also be further investigated. A nearly fivefold increase in the levels of p-cresol sulfate (PCS), which is produced by gut microbiota from tyrosine degradation, was among the most striking changes induced by acute HFD treatment. PCS and 3-indoxyl sulfate are classified as uremic toxins that may contribute to CNS toxicity [72]. Moreover, growing evidence has demonstrated that PCS triggers cell death and dysfunction by inducing oxidative stress and inflammation, impairing mitochondrial dynamics, and suggesting pathogenic roles of PCS in CNS diseases [72,73]. Elevated levels of PCS have been detected in the urine and feces of autistic patients [74,75,76]. In rodents, PCS administration induced autism-like behavioral changes [77,78,79]. Additionally, acute HFD lowered indole proprionate (IPA), another microbiota-derived metabolite of tryptophan. As a strong free radical scavenger, IPA is known to play a neuroprotective role in lowering inflammation, lipid oxidation, and free radical formations [80]. 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--- title: Angiographic Features and Clinical Outcomes of Balloon Uncrossable Lesions during Chronic Total Occlusion Percutaneous Coronary Intervention authors: - Judit Karacsonyi - Spyridon Kostantinis - Bahadir Simsek - Athanasios Rempakos - Salman S. Allana - Khaldoon Alaswad - Oleg Krestyaninov - Jaikirshan Khatri - Paul Poommipanit - Farouc A. Jaffer - James Choi - Mitul Patel - Sevket Gorgulu - Michalis Koutouzis - Ioannis Tsiafoutis - Abdul M. Sheikh - Ahmed ElGuindy - Basem Elbarouni - Taral Patel - Brian Jefferson - Jason R. Wollmuth - Robert Yeh - Dimitrios Karmpaliotis - Ajay J. Kirtane - Margaret B. McEntegart - Amirali Masoumi - Rhian Davies - Bavana V. Rangan - Olga C. Mastrodemos - Darshan Doshi - Yader Sandoval - Mir B. Basir - Michael S. Megaly - Imre Ungi - Nidal Abi Rafeh - Omer Goktekin - Emmanouil S. Brilakis journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10051461 doi: 10.3390/jpm13030515 license: CC BY 4.0 --- # Angiographic Features and Clinical Outcomes of Balloon Uncrossable Lesions during Chronic Total Occlusion Percutaneous Coronary Intervention ## Abstract Background: Balloon uncrossable lesions are defined as lesions that cannot be crossed with a balloon after successful guidewire crossing. Methods: We analyzed the association between balloon uncrossable lesions and procedural outcomes of 8671 chronic total occlusions (CTOs) percutaneous coronary interventions (PCIs) performed between 2012 and 2022 at 41 centers. Results: The prevalence of balloon uncrossable lesions was $9.2\%$. The mean patient age was 64.2 ± 10 years and $80\%$ were men. Patients with balloon uncrossable lesions were older (67.3 ± 9 vs. 63.9 ± 10, $p \leq 0.001$) and more likely to have prior coronary artery bypass graft surgery ($40\%$ vs. $25\%$, $p \leq 0.001$) and diabetes mellitus ($50\%$ vs. $42\%$, $p \leq 0.001$) compared with patients who had balloon crossable lesions. In-stent restenosis ($23\%$ vs. $16\%$. $p \leq 0.001$), moderate/severe calcification ($68\%$ vs. $40\%$, $p \leq 0.001$), and moderate/severe proximal vessel tortuosity ($36\%$ vs. $25\%$, $p \leq 0.001$) were more common in balloon uncrossable lesions. Procedure time (132 [90, 197] vs. 109 [71, 160] min, $p \leq 0.001$) was longer and the air kerma radiation dose (2.55 (1.41, 4.23) vs. 1.97 (1.10, 3.40) min, $p \leq 0.001$) was higher in balloon uncrossable lesions, while these lesions displayed lower technical ($91\%$ vs. $99\%$, $p \leq 0.001$) and procedural ($88\%$ vs. $96\%$, $p \leq 0.001$) success rates and higher major adverse cardiac event (MACE) rates ($3.14\%$ vs. $1.49\%$, $p \leq 0.001$). Several techniques were required for balloon uncrossable lesions. Conclusion: In a contemporary, multicenter registry, $9.2\%$ of the successfully crossed CTOs were initially balloon uncrossable. Balloon uncrossable lesions exhibited lower technical and procedural success rates and a higher risk of complications compared with balloon crossable lesions. ## 1. Introduction Balloon uncrossable lesions are defined as lesions that cannot be crossed with a balloon after successful guidewire crossing and confirmation of the guidewire position in the true lumen [1,2,3]. In a prior publication from the PROGRESS-CTO registry, the prevalence of balloon uncrossable lesions was $9\%$. These challenging lesions often required the use of multiple complex treatment modalities and were associated with lower technical and procedural success rates [2]. Several treatment strategies are available for treating balloon uncrossable lesions and can be broadly categorized into (a) plaque modification techniques, and (b) techniques that increase guide catheter support. An algorithmic approach to balloon uncrossable lesions usually starts with the use of small, low-profile balloons, followed by techniques that increase guide catheter support, and various plaque modification strategies, such as the use of microcatheters, atherectomy, laser, and extraplaque lesion modification [3]. We examined the contemporary clinical outcomes of balloon uncrossable CTO PCI. ## 2.1. Study Population We analyzed the baseline clinical and angiographic characteristics and procedural outcomes of 8671 CTO PCIs with successful guidewire crossing performed between 2012 and 2022, at 41 centers. Data collection was recorded in a dedicated online database (PROGRESS-CTO: Prospective Global Registry for the Study of Chronic Total Occlusion Intervention; Clinicaltrials.gov identifier: NCT02061436) [2,4,5,6,7]. Study data were collected and managed using REDCap (Research Electronic Data Capture) electronic data capture tools hosted at the Minneapolis Heart Institute Foundation [8,9]. The study was approved by the institutional review board of each site. ## 2.2. Definitions Coronary CTOs were defined as coronary lesions with Thrombolysis in Myocardial Infarction (TIMI), grade 0 flow of at least 3 months duration. Estimation of the duration of occlusion was clinical, based on the first onset of angina, prior history of myocardial infarction (MI) in the target vessel territory, or comparison with a prior angiogram. Calcification was assessed by angiography as mild (spots), moderate (involving ≤ $50\%$ of the reference lesion diameter), or severe (involving > $50\%$ of the reference lesion diameter). Moderate proximal vessel tortuosity was defined as the presence of at least 2 bends > 70° or 1 bend > 90°, and severe tortuosity as 2 bends > 90° or 1 bend > 120° in the CTO vessel. A retrograde procedure was an attempt to cross the lesion through a collateral vessel or bypass graft supplying the target vessel distal to the lesion; otherwise, the intervention was classified as an antegrade-only procedure. Antegrade dissection/re-entry was defined as antegrade PCI during which a guidewire was intentionally introduced into the subintimal space proximal to the lesion, or re-entry into the distal true lumen was attempted after intentional or inadvertent subintimal guidewire crossing [4]. ## 2.3. Outcomes Technical success was defined as successful CTO revascularization with the achievement of <$30\%$ residual diameter stenosis within the treated segment and restoration of TIMI grade 3 antegrade flow. Procedural success was defined as the achievement of technical success without any in-hospital major adverse cardiac event (MACE), which was defined as any of the following events prior to hospital discharge: death, MI, recurrent symptoms requiring urgent repeat target-vessel revascularization (TVR) with PCI, or coronary artery bypass graft (CABG) surgery, tamponade requiring either pericardiocentesis or surgery, and stroke. MI was defined using the Third Universal Definition of Myocardial Infarction (type 4a MI) [4,6,7,10]. The Japanese CTO (J-CTO) score was calculated as described by Morino et al. [ 11], the PROGRESS-CTO score was as described by Christopoulos et al. [ 12], and the PROGRESS-CTO MACE score was as described by Simsek et al. [ 13]. ## 2.4. Statistics Categorical variables were expressed as percentages and compared using Pearson’s Chi-square test. Continuous variables were presented as mean ± standard deviation or median (interquartile range (IQR)), unless otherwise specified, and were compared using the student’s t-test for normally distributed variables and the Kruskal–Wallis test for non-parametric variables, as appropriate. The variables associated with technical success and periprocedural MACE were examined using univariable logistic regression; thereafter, logistic multivariable regression was performed, and the variables with p values over 0.1 were removed from the model. All other statistical analyses were performed using JMP, version 13.0 (SAS Institute). A two-sided p-value of < 0.05 was considered statistically significant [4,5,6]. ## 3. Results Among cases with successful guidewire crossing the prevalence of balloon uncrossable lesions was $9.2\%$. The mean patient age was 64.2 ± 10 years, $80\%$ were men, $43\%$ had diabetes mellitus, approximately half had a prior MI ($45\%$), and approximately one-third had prior artery coronary bypass surgery ($27\%$). Table 1 represents the baseline clinical characteristics of the study patients classified according to the presence of balloon uncrossable lesions. Patients with balloon uncrossable lesions were older (67.3 ± 9 vs. 63.9 ± 10, $p \leq 0.001$), more likely to have had prior coronary artery bypass graft surgery ($40\%$ vs. $25\%$, $p \leq 0.001$), diabetes mellitus ($50\%$ vs. $42\%$, $p \leq 0.001$), and peripheral arterial disease ($17\%$ vs. $13\%$, $$p \leq 0.004$$) compared with patients who had balloon crossable lesions (Table 1). The right coronary artery ($52\%$) was the most common target vessel, followed by the left anterior descending coronary artery ($27\%$), and the left circumflex ($19\%$). Overall, the most common successful crossing strategy was antegrade wire escalation ($66\%$), followed by the retrograde approach ($20\%$), and antegrade dissection and re-entry ($14\%$). The mean J-CTO score was 2.27 ± 1.26, the mean PROGRESS-CTO score was 1.13 ± 0.98, and the mean PROGRESS-CTO MACE score was 2.46 ± 1.63. Moderate or severe calcification was present in $42\%$ and in-stent restenosis in $16\%$ of the cases. The baseline angiographic and procedural characteristics of the target lesions, classified according to whether they were uncrossable or not, are demonstrated in Table 1. Moderate or severe calcification ($68\%$ vs. $40\%$, $p \leq 0.001$) and proximal vessel tortuosity ($36\%$ vs. $25\%$, $p \leq 0.001$) were more common in balloon uncrossable lesions, which were also more complex with higher mean J-CTO (2.58 ± 1.19 vs. 2.23 ± 1.28, $p \leq 0.001$), PROGRESS-CTO (1.30 ± 1.02 vs. 1.11 ± 0.97, $p \leq 0.001$), and PROGRESS MACE (2.66 ± 1.54 vs. 2.44 ± 1.64, $p \leq 0.001$) scores compared with PCI of balloon crossable CTOs. Procedural outcomes and techniques are shown in Table 2, the Graphical Abstract, and Figure 1. In cases where successful guidewire crossing was achieved, the overall technical and procedural success rates were $98\%$ and $96\%$, respectively, and the incidence of in-hospital MACE was $1.64\%$. Balloon uncrossable lesions had lower technical ($91\%$ vs. $99\%$, $p \leq 0.001$) and procedural ($88\%$ vs. $96\%$, $p \leq 0.001$) success and higher incidence of major adverse cardiac events ($3.14\%$ vs. $1.49\%$, $p \leq 0.001$). Procedure time (132 [90, 197] vs. 109 [71, 160] min, $p \leq 0.001$) was longer and the air kerma radiation dose (2.55 (1.41, 4.23) vs. 1.97 (1.10, 3.40) min, $p \leq 0.001$) and contrast volume (210 [150, 300] vs. 200 [145, 280] mL, $$p \leq 0.001$$, Figure 1) were higher in balloon uncrossable lesions. Several techniques were used in balloon uncrossable lesions, such as guide catheter extensions in 267 cases ($34\%$), grenadoplasty in 198 cases ($25\%$), rotational atherectomy in 179 cases ($23\%$), and laser in 140 cases ($18\%$, Figure 2). Rotational atherectomy combined with laser atherectomy was used in 31 cases ($4\%$), while rotational atherectomy, together with orbital atherectomy, was used in 3 cases ($0.4\%$). Intravascular lithotripsy was used in 5 cases ($0.6\%$). On multivariable analyses moderate/severe calcification, longer occlusion length, and balloon uncrossable lesions were associated with lower technical success, while bigger vessel diameter and the presence of interventional collaterals were associated with higher technical success (Figure 3A). Balloon uncrossable lesions were also associated with higher MACE on multivariable analyses along with the presence of interventional collaterals, cerebrovascular disease, and moderate/severe calcification (Figure 3B). ## 4. Discussion The key findings of our study are that: (a) in a contemporary multicenter registry, $9.2\%$ of CTOs that were successfully crossed with a wire were balloon uncrossable; (b) balloon uncrossable lesions had lower technical and procedural success and higher risk of complications compared with balloon crossable lesions; and (c) balloon uncrossable lesions often required use of advanced plaque modification and increased support techniques. In a prior publication from the PROGRESS-CTO registry, the prevalence of balloon uncrossable lesions following successful guidewire crossing was $9.0\%$ [2], whereas the prevalence of balloon uncrossable or balloon undilatable lesions was $15.5\%$ [4], and the prevalence of balloon undilatable lesions was $8.5\%$ [14]. The prevalence was similar in the present study ($9.2\%$). In this study, balloon uncrossable lesions were more complex, with a higher prevalence of moderate or severe calcification, proximal vessel tortuosity, and higher J-CTO and PROGRESS-CTO scores. The high prevalence of balloon uncrossable CTOs also could be explained by new guidewires enabling antegrade intraplaque crossing, which could contribute to more difficulties with microcatheter, and balloon crossing compared with extraplaque crossing. In our study perforation rates were higher in the balloon uncrossable group compared with the balloon crossable group ($6.04\%$ vs. $3.42\%$, $p \leq 0.001$). Moreover, pericardiocentesis was also more common in the balloon uncrossable group ($1.76\%$ vs. $0.69\%$, $$p \leq 0.001$$). In a prior study from the PROGRESS-CTO registry, the pericardiocentesis rates were numerically higher but not statistically different, which could be due to smaller sample size ($1.6\%$ vs. $0.6\%$, $$p \leq 0.388$$) [2]. In a study examining GuideLiner use in balloon uncrossable CTO PCI, only one distal wire perforation occurred in 28 CTO PCI cases, which was treated conservatively without any hemodynamic compromise and no pericardial effusion on echocardiography [15]. A prior study examining rotational atherectomy in balloon uncrossable CTOs did not report any perforations associated with rotational atherectomy [16], neither did the study by Fernandez et al. with balloon uncrossable CTOs and laser atherectomy [17], although these studies had modest sample sizes. The cause of the increased rates of perforations in balloon uncrossable lesions could be explained by higher angiographic complexity (higher J-CTO and PROGRESS-CTO scores, calcification, and proximal vessel tortuosity), as well as need for more complex treatment modalities, which are associated with a higher risk of complications. Several strategies are available to deal with balloon uncrossable lesions and in general, can be categorized into (a) plaque modification techniques, and (b) techniques that increase guide catheter support [18]. Attempted crossing with low-profile balloons (e.g., 1–1.5 mm diameter), grenadoplasty/balloon assisted microdissection (BAM) [19], and improved guide support with a guide extension [15] or anchor balloon are usually tried first [3]. Other options include rotational [16], orbital or laser atherectomy [18,20], and extraplaque techniques to modify the uncrossable lesion through the extraplaque balloon crush technique or by tracking around the uncrossable plaque, through the less resistant extraplaque space and re-entering the lumen distally [21,22]. Combinations of the various plaque modification techniques can be used if required, such as laser-assisted orbital or rotational atherectomy [18]. The combined use of rotational atherectomy and excimer LaSER is called the “RASER” technique and consists of the upfront use of laser atherectomy followed by rotational atherectomy in heavily calcified lesions after the failure of Rotawire delivery [3,23]. An advantage of laser atherectomy is that it can be performed over any standard 0.014-inch guidewire (although it should be performed with caution over polymer-jacketed guidewires due to the risk of “melting” the polymer). After successful crossing, further modification can be performed with balloons (non-compliant, high-pressure, scoring, cutting), atherectomy devices, or intravascular lithotripsy [18,24]. Image guidance with intravascular ultrasound is valuable after dilatation of initially balloon-uncrossable lesions. An algorithmic approach to balloon uncrossable lesions usually starts with the use of low-profile balloons, followed by improved guide catheter support, the use of microcatheters, wire cutting or puncture techniques, atherectomy, laser, and extraplaque techniques. Sequential and simultaneous application of these techniques can result in the successful treatment of balloon uncrossable lesions [3,25,26]. There is limited data on the techniques that are the most successful in treating balloon uncrossable lesions. In our study orbital atherectomy, rotational atherectomy, and laser were associated with the highest technical success (Figure 2). In a single-center study of 290 lesions from 288 cases, with uncrossable lesions treated with rotational or orbital atherectomy, intravascular ultrasound analyses showed that the lesions were not always severely calcified (CTOs were excluded). The interaction of lesion morphology (continuous long and large arcs of calcium) and vessel geometry (bend in the vessel or ostial lesion location) affected lesion crossability [27]. In a prior study from the PROGRESS-CTO registry, which examined the use of atherectomy during chronic total CTO PCI, atherectomy was used in 51 cases ($1.4\%$) as a bailout strategy for “balloon uncrossable” or/and “balloon undilatable” lesions. The cases with “balloon uncrossable” and “balloon undilatable” lesions, where atherectomy was used, had higher technical success rates ($92\%$ vs. $79\%$, $$p \leq 0.032$$) and procedural ($90\%$ vs. $79\%$, $$p \leq 0.046$$) success rates compared with similar lesions not treated with atherectomy. MACE rates were similar ($7\%$ vs. $4\%$, $$p \leq 0.422$$) [28]. The BLIMP study randomized 126 patients with an uncrossable lesion to treatment with the Blimp balloon (Interventional Medical Device Solutions—IMDS, Roden, Netherlands) or low-profile balloon, and found no difference in the first attempt to cross ($48\%$ vs. $45\%$, respectively; $$p \leq 0.761$$). After placement of a guide extension, the overall successful lesion crossing was $80\%$ in the BLIMP group compared to $76\%$ in the low-profile balloon group ($$p \leq 0.327$$) [29]. In a retrospective study by Ye et al., the efficacy and safety of the BAM technique were assessed in 24 balloon uncrossable CTOs with the Sapphire® II 1.0 mm balloon (OrbusNeich, Hong Kong, China). The technical success rate was $75\%$ ($\frac{18}{24}$) for the lesions successfully treated with BAM, with a total technical success rate of $92\%$ ($\frac{22}{24}$; when BAM failed, 2 patients were successfully treated with laser and 2 with rotational atherectomy) [30]. Fernandez et al. assessed the use of laser atherectomy in 58 cases of balloon failure in a single center study in the United Kingdom, 16 of whom had balloon uncrossable CTOs, with a procedural success of $87.5\%$ and $2\%$ incidence of complications (in 2 cases laser was combined with rotational atherectomy). In the same cohort, the laser alone was applied successfully in two balloon undilatable CTO cases but with one Ellis class I perforation [4,17]. The Laser Veterans Affairs (LAVA) study, examining laser use in the veteran population at three US centers undergoing PCI, found balloon uncrossable lesions to be the most common indication for laser ($43.8\%$) associated with $87.8\%$ technical, and $83.7\%$ procedural success rates [4,24]. The LEONARDO (Early outcome of high energy Laser (Excimer) facilitated coronary angioplasty ON hARD and complex calcified and balloOn-resistant coronary lesions) study examined 80 patients with 100 lesions in 4 Italian centers treated with laser atherectomy and described a $93.7\%$ success rate without any complications (perforation, major side branch occlusion, spasm, no-reflow phenomenon, dissection, and acute vessel closure) [4,31]. Another technique for treating balloon and microcatheter uncrossable CTOs is the Carlino and guide-extension Carlino technique, which uses hydraulic disruption by contrast injection via either the microcatheter or guide catheter extension wedged against the uncrossable proximal cap or occlusive segment [32], as well as intentional subintimal dissection and reentry to “go around” the recalcitrant lesion. After the wire entered the extraplaque space, it can re-enter into the distal true lumen with different re-entry techniques, the calcific lesion can be “crushed” with a balloon over the extraplaque wire [22], or distal to the CTO to anchor the true lumen guidewire and allow balloon crossing (“subintimal distal anchor technique”) [3,33]. ## 5. Study Limitations Limitations of our study are that the data is observational, there was no clinical event adjudication or core laboratory analyses, and all procedures were performed at high-volume, experienced CTO PCI centers, limiting the generalizability of our findings to centers with more limited experience. ## 6. Conclusions In a contemporary multicenter registry, $9.2\%$ of successful wires across CTOs were balloon uncrossable. Balloon uncrossable lesions had lower technical and procedural success and higher complication rates compared to balloon crossable lesions and often required the use of advanced plaque modification and support techniques. ## References 1. Patel S.M., Pokala N.R., Menon R.V., Kotsia A.P., Raja V., Christopoulos G., Michael T.T., Rangan B.V., Sherbet D., Patel V.G.. Prevalence and treatment of "balloon-uncrossable" coronary chronic total occlusions. J. Invasive. Cardiol. (2015) 27 78-84. PMID: 25661758 2. 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--- title: 'Effects of Age, Metabolic and Socioeconomic Factors on Cardiovascular Risk among Saudi Women: A Subgroup Analysis from the Heart Health Promotion Study' authors: - Hayfaa Wahabi - Samia Esmaeil - Rasmieh Zeidan - Amel Fayed journal: Medicina year: 2023 pmcid: PMC10051484 doi: 10.3390/medicina59030623 license: CC BY 4.0 --- # Effects of Age, Metabolic and Socioeconomic Factors on Cardiovascular Risk among Saudi Women: A Subgroup Analysis from the Heart Health Promotion Study ## Abstract Background: Cardiovascular disease (CVD) remains the leading cause of death in women. Along with the effect of age on the risk of CVD, the reproductive profile of women can influence cardiac health among women. Objectives: The objective of this study is to investigate the influence of age and reproductive stages on the development and progression of cardiovascular disease risks in Saudi women. Methods: For this study, we included 1907 Saudi women from the Heart Health Promotion Study. The study cohort was divided into five age groups (less than 40 years, 40–45 years, 46–50 years, 51–55 years, and ≥56 years). The cohort stratification was meant to correspond to the social and hormonal changes in women’s life, including reproductive, perimenopausal, menopausal, and postmenopausal age groups. The groups were compared with respect to the prevalence of metabolic, socioeconomic, and cardiac risks, and the age group of less than 40 years was considered as the reference group. The World Health Organization stepwise approach to chronic disease risk factor Surveillance-Instrument v2.1 was used in this study to collect the anthropometric and biochemical measurements and the Framingham Coronary Heart Risk Score was used to calculate the cardiovascular risk (CVR). Logistic regression analysis was conducted to assess the independent effect of age on CVD risks after adjustment of sociodemographic factors. Results: Metabolic and CVR increased progressively with the increase in age. There was a sharp increase in obesity, hypertension, diabetes, and metabolic syndrome, from the age group <40 years to 41–45 years and then again between the age groups of 46–50 and ≥56 years. A similar noticeable increase in metabolic risk factors (high cholesterol, high triglyceride, high Low-Density Lipoprotein) was observed between the age group <40 years and 41–45 years, but with a steady increase with the increase in age between the other age groups. The high and intermediate Framingham Coronary Heart Risk Scores showed a progressive increase in prevalence with the increase in age, where the proportion doubled from $9.4\%$ at the age group 46–50 years, to $22\%$ at the age group 51–55 years. It doubled again at the age group ≥56 years to $53\%$—these sharp inflections in the risk of CVD correspond to the women’s reproductive lives. Conclusions: In Saudi women, CVR increases with the increase of age. The influence of pregnancy and menopause is apparent in the prevalence of increased risks for cardiovascular and metabolic diseases. ## 1. Introduction Globally, $35\%$ of death in women is due to cardiovascular disease (CVD), with an estimated 8.9 million deaths in 2019 [1]. The Middle East, including Saudi Arabia, is among the regions with the highest mortality in women from CVD with 486 deaths per 100,000, which is considerably high compared to other high-income countries such as Australia and North America with a reported <130 deaths per 100,000 [2]. Ischemic heart disease is leading cause of death in women from CVD worldwide including in Saudi Arabia, with stroke coming in second place. The main risk factor for CVD in women in the Middle East and North Africa is hypertension, which imposes higher risk of myocardial infarction in women than in men, followed by dyslipidemia with total cholesterol showing considerable increase following the menopause [2,3,4]. Other equally important and interrelated risk factor for CVD in women are high body mass index (BMI), sedentary lifestyle and diabetes. It is documented that older women lead more sedentary lifestyles than older men [5]. Physical inactivity is associated with obesity, diabetes, and hypertension. Observation showed that a similar increase in both genders in BMI is associated with a greater increase in systolic blood pressure in women than in men [6]. Furthermore, the risk of CVD attributed to obesity is $20\%$ more in women compared to the risk in men of the same age group [7]. Most of the studies which investigated CVD and risk factors in women in Saudi Arabia were either small cross-sectional studies targeting young college students [8,9,10], mostly investigating one risk factor for CVD [11,12], or studies which included both men and women but did not include analysis to investigate the influence of age, or the hormonal changes of pregnancy and the menopause on the CVD risk factors [13,14,15,16]. The objective of this study is to investigate the influence of age on the development and progression of CVD and cardiovascular risk (CVR) in women which will define the target age group for intervention to reduce mortality and morbidity for CVD among women in Saudi Arabia. ## 2.1. Consent and Ethics The study followed the standards of the Helsinki Declaration after receiving approval from King Saud University’s Institutional Review Board (IRB) (reference number 13–3721). We invited 5200 individuals to participate in the study and 4500 participants agreed to be enrolled (response rate of $87\%$). All participants signed informed consent forms. ## 2.2. Study Setting The original cohort included 4500 participants recruited from employee clinics in King Saud University Hospital that serve the employees and their families. The data collection extended for a period of 9 months (from 8 July 2013 to 30 April 2014) and the first report was published in 2016. ## 2.3. Study Population and Sampling Technique For this study we included only 1907 Saudi women from the total cohort. We excluded pregnant women from the study. Considering prevalence of obesity as of $25\%$ ± $5\%$ ($p \leq 0.01$), a power of >0.9 was calculated using STATA/IC14.2. The study cohort was divided into five age groups (less than 40 years, 40–45 years, 46–50 years, 51–55 years and ≥56 years). The stratification of the cohort was meant to approximately correspond to the social and hormonal changes in women’s life including reproductive, perimenopausal, menopausal and postmenopausal age groups. The groups were compared with respect to the prevalence of the metabolic and the socioeconomic CVD and CVR. ## 2.4. Data Collection and Physical Measurements The sociodemographic data (age, marital status, occupation, and educational attainment), data about tobacco use, physical activity, healthy diet, and anthropometric and biochemical measurements were collected using the World Health Organization (WHO) stepwise approach to chronic disease risk factor Surveillance-Instrument v2.1 [17]. All participants were required to fast for at least 12 h before giving blood samples. Glycosylated hemoglobin (HbA1c), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TG) were measured. ## 2.5. Study Variables Obesity: Weight and height were measured for all participants. Weight was measured to the nearest 10 g, while height was measured to the nearest 0.1 cm. ⮚The Body Mass Index (BMI): was calculated using the formula BMI = weight (kg)/height (m2). Based on the BMI, the study population was divided into five groups: underweight, normal weight, overweight, obese and morbidly obese, (<18.5; 18.5–24.9; 25–29.9; 30–34.9; ≥35 kg/m2), respectively [18].⮚Central Obesity: The waist circumference (WC) was measured in centimeters to the nearest 0.1 cm, using a flexible non-stretchable plastic tape, in a standing relaxed position, during expiration, at the midline between the lower costal margins and the iliac crest parallel to the floor. A WC of 88 cm was used for diagnosis of central obesity among women, which are cut-off values reported to be applicable to Arab ethnicities [19].Current smokers: were classified as individuals who had smoked at least one cigarette per day for the previous six months, one cigar or water pipe weekly for the last six months, or one waterpipe tobacco smoke/shisha session each month for the prior three months [20].Physical inactivity: participants were deemed physically inactive if they did not meet any of the following WHO standards: 150 min of moderate activity each week, or 60 min of vigorous activity [21].Low fruit and vegetable intake: According to the WHO, any subject who had less than five servings (400 gm) of fruit and/or vegetables per day was considered as having inadequate intake [22].Hypertension: Both systolic and diastolic pressures were measured, at two readings, set five minutes apart; the average of the two readings was used. Hypertension was defined as being previously diagnosed as hypertensive and currently using any anti-hypertensive medications or having high blood pressure readings according to Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7) [23].Diabetes mellitus was defined as per WHO and American Diabetes Association criteria, or by subject reporting of being previously diagnosed as diabetic and using anti-diabetes medication [24].Cardiovascular risk (CVR) scores were calculated for all participants using Framingham Coronary Heart Risk Score (FRS) which is one of the most extensively used cardiovascular risk calculators in clinical practice. It was used to calculate the 10-year risk of coronary heart disease where the cohort was sub-divided according to their scores into three categories: low risk score (<$10\%$), intermediate (10–$20\%$), and high (>$20\%$) [25].Metabolic Syndrome (MetS): If participants satisfied at least three of the five criteria listed in the Third Report of the National Cholesterol Education Program (NCEP) Adult Treatment Panel III) (NCEP-ATPIII) criteria, they were considered to have metabolic syndrome [26].Dyslipidemia: dyslipidemia was considered according to definitions adopted by the National Cholesterol Education Program (NCEP) criteria for dyslipidemia (elevated cholesterol, elevated TG, high HDL-C level and low LDL-C) [26]. ## 2.6. Statistical Analysis Continuous variables, interval and ratio variables were reported as means with standard deviations. Categorical variables were presented as frequencies with equivalent percentages, and Pearson’s chi-square test was used for comparison of different proportions. Logistic regression analysis was conducted to assess the independent effect of age on CVR after adjustment of sociodemographic factors (education, occupation, and marital status) and considered the younger age group (<40 years) as the reference group. When assessing the CVR using the FRS, we aggregated the intermediate and high-risk groups as one category to convert the FRS into binary variable. Predictive probability (PP) of outcomes according to different age groups was plotted with its $95\%$ confidence intervals (CI). Statistical analyses of the data were done using SPSS V.26.0 statistical package (IBM SPSS) and STATA version 16. ## 3. Results A total of 1907 women were included in this study. The socioeconomic characteristics with impact on cardiovascular risks are shown in Table 1. While $46.5\%$ of the age group <40 years were single, only $4.6\%$ of the age group 40–$45\%$ were in this category. The range of the prevalence of unhealthy dietary habits (84–$92\%$), and physical inactivity (83–$93\%$) was high across all age groups, despite the significant difference in prevalence of employment between the <40 years old and the older groups (Table 1). However, the prevalence of tobacco smoking was low across all age groups (Table 1). Cardiometabolic risks increased progressively with the increase in the age of the cohort (Table 2 and Figure 1). In addition, the analysis showed a marked increase in HTN, DM, and MetS, between the age group <40 years and 41–45 years and between the age groups of 46–50 and ≥56 years (Table 1). Similar noticeable increase in overweight/obesity, and dyslipidemias was observed between the age group <40 years and 41–45 years, but with steady increase with the increase in age between the other age groups (Table 2). The intermediate and high FRS showed a progressive increase in prevalence with the increase in age. There are two points of sharp increase in the proportion of women with intermediate and high scores, where the proportion doubled from $9.4\%$ at the age group 46–50 years, to $22\%$ at the age group 51–55 years, and it doubled again at the age group ≥56 years to $53\%$ (Table 2 and Figure 1). Predicted probability of high and intermediate CVR as measured by FRS was derived from the regression models after adjustment of socioeconomic factors. There was an escalating trend of the probabilities of CVR across the age groups that reached above $50\%$ ($95\%$ C.I. = 47–$59\%$) among women aged 56 years (Figure 2). ## 4. Discussion The results of this study showed that there was a progressive increase in the risks and probability of developing CVD with the increase of age in Saudi women, and that there was a high proportion of women in this cohort who have unhealthy food habits and who had led a sedentary lifestyle. Furthermore, the prevalence of risk factors showed a sharp and progressive increase after the age of 40–45 years with noticeable association of transition from single to married social status and with the completion of reproductive stage of the women’s life. Similar to our results, previous reports confirmed that ageing is one of the main and independent risk factors for CVD both in males and females [27]. This observation is mainly due to the changes at the cellular level of the heart and the vasculature with increased accumulation of collagen and depletion of elastin [27]. These changes lead to deterioration in the function and morphology of the heart and the vascular system; including high systolic blood pressure, widening of the pulse pressure together with atrial dilatation and ventricular hypertrophy [28] due to stiffness of the aorta and generalized endothelial dysfunction and central arterial stiffness of the vascular system. The clinical manifestations of the deteriorating function of the cardiovascular system include; hypertension, atrial fibrillation [29], heart failure [30], stroke and ischemic heart disease [31]. Often women develop non-coronary obstructive heart diseases. One example is Takotsubo Syndrome that seems to afflict the female sex almost exclusively [32]. The pivotal effect of aging as risk factor for CVD is clearly shown in Figure 1 and Figure 2, which showed a steady increment of prevalence of CVR scores with age and substantial increase in the probability of developing CVD with the increase in age. This observation may be explained by the known effects of advanced age equally on the other risk factors including hypertension, as shown above, glucose metabolism, and obesity. Recent studies provided evidence on the dysregulation of glucose metabolism in elder men and women with defective insulin secretion, high fasting blood glucose, delayed postprandial glucose clearance and increased liver production of glucose compared to young individuals [33]. Although old women have slightly different defects of glucose regulation compared to old men, both genders are at increased risk of developing diabetes as they get older [33]. Obesity, especially visceral, is a proven risk factor for insulin resistance, diabetes, dyslipidemia and CVD [34]. In this study the prevalence of obesity, as indicated by BMI, is very high, but it plateaus after the age of 45 years as shown in Figure 1, unlike the prevalence of central obesity which showed an incremental course with the advancing age of the women; hence, it corresponds to the increased prevalence of the risk of CVD. Previous studies confirmed our findings that as women get older, they are more borne to develop visceral obesity, which is more detrimental as a risk factor for CVD than total body fat [35,36,37]. Such change in the distribution of body fat is mediated by estrogen deficiency during the perimenopause and menopause stage of the woman’s reproductive life [38,39]. Visceral obesity is the main source of the high levels of LDL-C, free fatty acids, and insulin resistance observed with the advance of the individual’s age [40], which has been confirmed by the findings of this study (Table 2). Other events in women reproductive life have been linked to cardiometabolic risks for CVD including gestational diabetes, prepregnancy obesity, postpartum weight retention and preeclampsia [41,42,43,44]. Almost all of these conditions are quite prevalent among Saudi women during pregnancy and the postpartum period, as proven by the largest study conducted in Riyadh city which included more than 14,000 women and their neonates [45], which may indicate that Saudi women are at greater risk of developing CVD compared to women in other high income countries. In this study there is a noticeable increment in all CVD risk factors after the age of 40 years (Figure 1 and Figure 2 and Table 2). This age group corresponds to a social status of married women who have completed their families and approaching the perimenopausal period of their reproductive life, which indicate not only the effect of age on CVR, but the detrimental effect of postpartum weight retention, events during pregnancy such pre-eclampsia, gestational diabetes, and estrogen deficiency. We are aware of the limitations of this study including the lack of data and analysis of the influence of reproductive life events on the risk of developing cardiovascular disease including the number of pregnancies and the occurrence of events such as gestational diabetes and pre-eclampsia. However, the completion of all records in this large size cohort revealed robust evidence for other important variables. We should also refer to the use of FRS instead of using SCORE2 & SCORE2-OP [46], as we were not able to define studies conducted among Saudis that used this score for CVR assessment; however, we are planning to re-analyze our database and compare the results of these scores with FRS in future reports. ## 5. Conclusions In Saudi women, CVR increases with the increase of age. The influence of pregnancy and menopause are apparent in the prevalence of increased risks for cardiovascular and metabolic diseases. ## References 1. Roth G.. Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2017 (GBD 2017) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2018. Lancet (2018) 392 1736-1788. DOI: 10.1016/S0140-6736(18)32203-7 2. Vogel B., Acevedo M., Appelman Y., Merz C.N.B., Chieffo A., Figtree G.A., Guerrero M., Kunadian V., Lam C.S., Maas A.H.. 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--- title: 'Association of Obstructive Sleep Apnea and Atrial Fibrillation in Acute Ischemic Stroke: A Cross-Sectional Study' authors: - Valerio Brunetti - Elisa Testani - Anna Losurdo - Catello Vollono - Aldobrando Broccolini - Riccardo Di Iorio - Giovanni Frisullo - Fabio Pilato - Paolo Profice - Jessica Marotta - Eleonora Rollo - Irene Scala - Paolo Calabresi - Giacomo Della Marca journal: Journal of Personalized Medicine year: 2023 pmcid: PMC10051494 doi: 10.3390/jpm13030527 license: CC BY 4.0 --- # Association of Obstructive Sleep Apnea and Atrial Fibrillation in Acute Ischemic Stroke: A Cross-Sectional Study ## Abstract Background: There is a growing body of evidence suggesting a link between obstructive sleep apnea (OSA) and atrial fibrillation (AF). The primary objective of this study is to evaluate the association between OSA and AF in acute ischemic stroke. The secondary objective is to describe the clinical features of patients with acute ischemic stroke and concomitant OSA. Methods: We enrolled consecutive patients with acute ischemic stroke. All patients underwent full-night cardiorespiratory polygraphy. To determine if there is an association between AF and OSA, we compared the observed frequency of this association with the expected frequency from a random co-occurrence of the two conditions. Subsequently, patients with and without OSA were compared. Results: A total of 174 patients were enrolled (mean age 67.3 ± 11.6 years; 95 males). OSA and AF were present in 89 and 55 patients, respectively. The association OSA + AF was observed in $\frac{33}{174}$ cases, which was not statistically different compared to the expected co-occurrence of the two conditions. Patients with OSA showed a higher neck circumference and body mass index, a higher prevalence of hypertension and dysphagia, and a higher number of central apneas/hypoapneas. In the multivariate analysis, dysphagia and hypertension were independent predictors of OSA. A positive correlation was observed between OSA severity, BMI, and neck circumference. The number of central apneas/hypoapneas was positively correlated with stroke severity. Conclusions: Our data suggest that OSA and AF are highly prevalent but not associated in acute stroke. Our findings support the hypothesis that OSA acts as an independent risk factor for stroke. ## 1. Introduction Obstructive sleep apnea (OSA) and atrial fibrillation (AF) are both highly prevalent in acute ischemic stroke (AIS). There is a significant overlap between OSA and AF, suggesting a possible pathogenic link between these two conditions [1]. Growing evidence suggests that OSA plays a causal role in the initiation and maintenance of AF [2]. OSA can promote arrhythmogenesis through several mechanisms. First, the hemodynamic changes induced by repetitive forced inspiration against the collapsed airway lead to increased cardiac load, which, in turn, leads to atrial remodeling, promoting arrhythmia [3]. Furthermore, repetitive apneas/hypopneas, and the consequent intermittent hypoxemia, induce a metabolic derangement that causes oxidative stress and, consequently, a chronic inflammation condition that increases the susceptibility to develop AF [4]. Finally, OSA results in autonomic imbalance with increased tone and surges of sympathetic activation, providing a favorable substrate for the development of cardiac arrythmias, in particular AF [5]. AF is the most common cause of cardioembolic stroke, representing approximately 15–$30\%$ of all ischemic strokes [6]. Recent data indicate that OSA is associated with increased risk of cardioembolic stroke [7], suggesting a role of OSA in determining AIS through AF. Based on these findings, we hypothesized that these conditions are closely associated in AIS. Few studies have investigated the association between AF and OSA in AIS, with inconsistent results [7,8,9,10]. Therefore, the primary endpoint of the current study was to evaluate the association between OSA and AF in AIS, comparing the observed frequency of this association with the expected frequency. The secondary endpoint was to describe the clinical features of patients with AIS and concomitant OSA. ## 2.1. Patients and Data Source This is a cross-sectional study with prospective enrollment, conducted at the stroke unit of the Gemelli Hospital in Rome. The inclusion criteria were age ≥18 years and diagnosis of ischemic stroke with NIHSS ≥1 confirmed with neuroimaging (brain MRI or CT). Exclusion criteria were patients with an unstable clinical condition and a pre-existing diagnosis of sleep disorder, including OSA. The following data were collected: age, sex, body mass index (BMI), neck circumference, obstructive apnea–hypopnea index (O-AHI), central apnea–hypopnea index (C-AHI), oxygen desaturation index (ODI), AF (from medical history or newly diagnosed), hypertension, diabetes, dyslipidemia, reperfusion therapy (intravenous thrombolysis or endovascular thrombectomy), wake-up stroke, the Oxfordshire Community Stroke Project (OCSP) classification based on clinical symptoms, the etiology of stroke according the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification, National Institutes of Health Stroke Scale (NIHSS) at admission, dysphagia, pneumonia, and death. All patients underwent a polygraphic sleep study within 7 days of AIS onset, in an in-hospital setting. The following parameters were recorded: airflow (measured by nasal cannula), thoracic and abdominal effort, snore, and peripheral oxygen saturation. OSA was diagnosed when the obstructive apnea–hypopnea index (O-AHI) was ≥10 events per hour. The choice of this cut-off was based on the meta-analysis of Johnson and Johnson [11], since most of the studies that have assessed the prevalence of OSA in patients with acute stroke in a hospital setting have used an AHI cut-off of ≥10 events/hour. Respiratory events were scored according to the criteria of the American Academy of Sleep Medicine [12]. Sleep apnea was scored when there was a drop of ≥$90\%$ of the peak of airflow signal for more than 10 s. Sleep hypopnea was scored if there was a reduction of ≥$30\%$ of the airflow for more than 10 s in association with a drop of hemoglobin saturation of ≥$3\%$. Central apneas and hypopneas were not included in the calculation of O-AHI but were considered separate events and included in the count of the central apnea–hypopnea index (C-AHI). Continuous multiparametric monitoring (electrocardiogram, hemoglobin saturation, respiratory rate, blood pressure) was performed in all patients for at least 24 h. The continuous electrocardiographic monitoring performed in our stroke unit involves automatic rhythm analysis to detect atrial fibrillation through dedicated software. The diagnosis is subsequently confirmed by a 12-lead electrocardiogram, evaluated by a cardiologist. Furthermore, all patients were also subjected to a 24-h ECG Holter recording, which was evaluated by a cardiologist. This study was conducted in accordance with the amended Declaration of Helsinki. Local institutional review boards approved the study (protocol number: ID-5137), and written informed consent was obtained from all patients or caregivers. ## 2.2. Statistical Analysis First, we calculated sample size of the study population. According to the data extrapolated from the literature, we considered an expected prevalence of AF and OSA in the AIS population in an in-hospital setting of $20\%$ [13] and $64\%$ [11], respectively. Therefore, the expected random association of the two conditions is $12\%$. Based on these assumptions, the minimum number of patients to enroll to have a confidence level of $95\%$ and a margin of error of $5\%$ was 162. To determine if there is an association between AF and OSA in AIS, we compared the expected prevalence of each condition with that observed in the sample. Then, we compared the observed frequency of the association OSA + AF with that expected from a random co-occurrence of the two conditions, by means of Pearson’s χ2. Subsequently, we divided the study population into two subgroups based on the diagnosis of OSA (OSA+ vs. OSA− groups) and compared the two subgroups for clinical and demographic variables. Continuous and categorical variables were summarized using means and standard deviations, and counts and percentages, respectively. Continuous variables were tested using the nonparametric Mann–Whitney U test, while categorical variables were tested using Pearson’s χ2. The level of significance was set at $p \leq 0.05.$ Next, to adjust for potential confounding effects of well-known risk factors for OSA and stroke, variables compared in the univariate analysis were evaluated using backward stepwise binary logistic regression analysis. The dependent variable for the binary logistic regression model was the diagnosis of OSA (OSA+ vs. OSA−), and the predictors were the variables with $p \leq 0.25$ in the univariate analysis, along with variables considered to be clinically relevant. The goodness of fit for the logistic regression model was evaluated using the Hosmer–Lemeshow test. Odds ratios, p values, and $95\%$ confidence intervals are reported. Finally, we correlated the AHI with the continues variables collected (age, BMI, neck circumference, and NIHSS) and estimated correlation coefficients using Spearman’s rho. Statistical analysis was performed by means of the Statistical Package for Social Science (SPSS®) software, version 20. ## 3. Results A total of 174 patients were consecutively enrolled (mean age 67.3 ± 11.6 years; 95 males). Demographic and clinical features of the study group are reported in Table 1. OSA and AF were present in 89 ($51.2\%$) and 55 ($31.6\%$) patients, respectively. Therefore, the expected number of patients that should present both conditions, if randomly distributed, was 28 ($16.1\%$). The association of OSA + AF was observed in $\frac{33}{174}$ cases ($19.0\%$), which was not statistically different from the expected co-occurrence of the two conditions (χ2 = 0.500; $$p \leq 0.481$$). Subsequently, we compared OSA+ ($\frac{89}{174}$) and OSA− ($\frac{85}{174}$) groups. Regarding anthropometric measurements, BMI (OSA+: 28.4 ± 6.6 vs. OSA−: 25.9 ± 4.7; $$p \leq 0.001$$) and neck circumference (OSA+: 42.3 ± 4.3 vs. OSA−: 39.4 ± 4.4 cm; $p \leq 0.001$) were significantly higher in the OSA+ population. The prevalence of hypertension (OSA+: $\frac{76}{89}$ vs. OSA−: $\frac{50}{85}$; $p \leq 0.001$) and dysphagia (OSA+: $\frac{63}{89}$ vs. OSA−: $\frac{29}{85}$; $p \leq 0.001$) was significantly higher in OSA+; the prevalence of diabetes was higher in the OSA+ group, showing a trend toward statistical significance (OSA+: $\frac{33}{89}$ vs. OSA−: $\frac{20}{85}$; $$p \leq 0.052$$). The prevalence of AF was higher, but not statistically different, in the OSA+ group (OSA+: $\frac{33}{89}$ vs. OSA−: $\frac{22}{85}$; $$p \leq 0.112$$). We observed a significantly higher value of C-AHI in the OSA+ group (OSA+: 5.6 ± 3.2 vs. OSA−: 3.2 ± 6.1 events/hour; $$p \leq 0.028$$). No other significant differences were observed between the two subgroups; in particular, the prevalence of OSA did not statistically differ according to the stroke subtypes ($$p \leq 0.483$$), as shown in Figure 1. Detailed results of the univariate comparison between OSA+ and OSA− patients are reported in Table 2. In the multivariate binary logistic regression, hypertension (odds ratio = 5.19; $95\%$ confidence interval = 1.58–16.85; $$p \leq 0.006$$) and dysphagia (odds ratio = 7.08; $95\%$ confidence interval = 2.23–22.35; $p \leq 0.001$) were independent predictors of OSA after adjustment for possible confounders. The model of multivariate analysis showed a good fit according to the Hosmer–Lemeshow test ($$p \leq 0.507$$). Detailed results of multivariate analysis are reported in Table 3. Finally, we observed a significant positive correlation between OSA severity, measured by O-AHI, and BMI (Spearman’s rho = 0.289; $p \leq 0.001$) and neck circumference (Spearman’s rho = 0.329; $p \leq 0.001$), and stroke severity, measured by NIHSS, and CSA severity, measured by C-AHI (Spearman’s rho = 0.191; $p \leq 0.013$). No significant correlations were observed between O-AHI and stroke severity and age. Significant correlations are reported in Figure 2. ## 4. Discussion The current study confirms that OSA and AF are both highly prevalent in AIS. Nevertheless, the frequency of their association is not different from what is expected by the random occurrence of the two conditions. The prevalence of AF in our sample was $31.6\%$, which is higher than in previous studies investigating the prevalence of AF in AIS. This finding is in line with recent evidence indicating that the prevalence of AF in AIS has been constantly increasing in recent years [14]. These data could be the result of an increased probability of diagnosing AF in the stroke unit due to the prolonged and continuous ECG monitoring. The prevalence of OSA (defined as AHI ≥10 events/h) in our cohort was $51.2\%$, which is similar to previous studies investigating the prevalence of OSA in AIS [11,15]. The lack of association between OSA and AF in our population suggests that OSA contributes independently to AIS, and that there is no causative relationship between the two conditions in determining stroke. However, it is worth noticing that the OSA+ group presented a non-statistically significant higher prevalence of AF. From this point of view, larger studies with a considerably higher number of patients may demonstrate a causative link between AF and OSA in causing stroke. Notably, we excluded central apneas and hypopneas from the count of O-AHI. We excluded central events because of the well-documented relatively high prevalence of central apneas in both AF and acute stroke [16,17]. Additionally, central apneas recognize a different pathogenic mechanism compared to obstructive apneas [18]. The exclusion of central events in the count of O-AHI could have led to a lower prevalence of OSA in our population regarding patients who presented concomitant heart diseases and AF. To date, the association of AF and OSA in AIS has been poorly studied, with conflicting findings. Masukhani et al. [ 19] retrospectively evaluated a population with OSA, reporting a higher prevalence of ischemic stroke in those who presented concomitant AF and proposing an additional role of OSA in the interplay between AF and AIS. However, the study design did not allow for the demonstration of a causative relationship between OSA and AF in determining stroke. Recently, Dalmar et al. [ 20] observed an increased prevalence of stroke and AF in obese patients with concomitant OSA compared to obese patients without OSA; however, in the stroke group only $20\%$ of patients with stroke and OSA had documented AF, suggesting that the stroke risk is mediated by other factors. Lipford et al. [ 7] reported an increased prevalence of cardioembolic stroke in an OSA population; however, the relationship between OSA and cardioembolic stroke was still significant after adjusting for known AF, indicating that AF does not entirely justify the association between OSA and stroke. In contrast to what was reported by Lipford et al. [ 7], we did not observe a significantly higher prevalence of OSA according to the stroke subtypes. However, in our cohort, the prevalence of OSA appears to be particularly high in lacunar strokes, suggesting that OSA plays a determining role in the cerebral small vessel disease [21]. Conversely, Bassetti et al. [ 22] found an increased prevalence of OSA in strokes due to a large artery disease rather than in cardioembolic stroke, proposing a role of OSA in the atherogenic process. In the Sleep Heart Health Study [23], a strict association between stroke and OSA was still observed after excluding from the analysis patients who presented AF. Munoz et al. [ 10] found that OSA represented an independent risk factor for AIS in a large elderly population, also after adjusting for others known risk factors, including AF. In addition, OSA has been identified as an independent risk of stroke in patients with AF [24,25], and, particularly, the severity of OSA-related hypoxia has been found to be associated with an increased risk of cardioembolic stroke, stratified by CHA2DS2-VASc [26]. Recent evidence suggests that a thrombogenic atrial substrate can lead to atrial thromboembolism even in the absence of AF [27]. OSA has been linked to several alterations, such as endothelial dysfunction, atrial fibrosis and dilatation, and mechanical dysfunction in the left atrial appendage, all of which have been associated with atrial thrombosis regardless of the presence of AF [27]. Furthermore, it is important to consider that AIS is a condition characterized by autonomic imbalance [28] and an altered respiratory pattern [29]. Therefore, both OSA and AF could be not only determinants but also consequences of AIS [30]. In fact, autonomic imbalance is a frequent complication of AIS, particularly in lesions involving the insula [31]. Animal models have proven a direct role of the autonomic output imbalance in inducing persistent and paroxysmal arrhythmias [32]. Similarly, an altered regulation of the autonomic nervous system has been observed in humans prior to the onset of paroxysmal AF, and interventions aimed at reducing autonomic innervation of the heart result in better control of atrial arrhythmias [33]. Dysautonomia can have a partial or complete recovery after stroke, with autonomic unbalance potentially being transient [34] or persisting for several months [35]. From this perspective, AF could be a transient manifestation of AIS. Similarly, it is possible that OSA is, at least in part, a reversible manifestation of AIS resulting from an altered respiratory pattern, pharyngeal muscular dysfunction, and prolonged immobilization [18,30,36]. In this view, AIS may exacerbate or precipitate pre-existing sleep-disordered breathing [18]. Current evidence suggests that OSA may be a pre-existing condition aggravated by stroke, while CSA may appear de novo as a symptom of the acute phase. Longitudinal studies evaluating the evolution of sleep apnea after acute stroke have revealed only a slightly lower prevalence of OSA in the chronic phase, and amelioration of CSA [15,22,37,38,39]. Regarding the secondary aim of our study, we observed that patients with AIS and concomitant OSA constitute a subgroup of stroke patients with a higher prevalence of other risk factors for cerebrovascular disease. Specifically, our study showed that OSA patients were more likely to have hypertension and diabetes, indicating a close relationship between these conditions, which promote each other in a detrimental way. As expected, the OSA population presented higher BMI and neck circumference, which are well-established risk factors for OSA. Furthermore, the severity of OSA was directly correlated with higher BMI and neck circumference [40]. Another interesting data point, although not confirmed in the multivariate analysis, was the higher number of central apneas in stroke patients with concomitant OSA. This observation suggests that AIS may result in a unique sleep-related breathing disorder characterized by the simultaneous presence of central and obstructive components [41]. Various mechanisms contribute to sleep-disordered breathing in AIS, including compromised upper airways patency (as a result of the weakness or incoordination of the pharyngeal, intercostal, and diaphragmatic muscles) and reduced arousal response. Additionally, the involvement of the respiratory centers located in the brainstem, caused either by the direct localization of the ischemic lesion or by diffuse cerebral injury resulting from the ischemic stroke, can lead to the development of central apneas. Finally, we observed a high prevalence of dysphagia in our cohort of stroke patients with OSA. Dysphagia is the commonest clinical manifestation of the involvement of pharyngeal muscles in AIS. Our previous study demonstrated a close association between OSA and dysphagia in AIS, suggesting that pharyngeal muscle palsy represents a common pathogenic link between these two conditions in AIS [42]. In this view, OSA+ patients are at higher risk to develop complications related to dysphagia, in particular aspiration pneumonia. Interestingly, dysphagia is often reversible within a few weeks after stroke, due to gradual recovery of pharyngeal muscle function [43,44]. Therefore, the sleep-disordered breathing observed in AIS may improve simultaneously with the recovery of dysphagia [16,22,45]. Our study has several limitations. First, the observation was limited to patients with acute ischemic stroke, which may not reflect the entire population affected by AF and/or OSA outside of the acute stroke phase. Additionally, the AHI cut-off value for diagnosing OSA in acute stroke is not well established. Our choice to use a cut-off of 10 events/h comes from data available in the literature, although a different cut-off could lead to different prevalence. Furthermore, the diagnosis of AF was based on the analysis of previous clinical recordings or was detected during hospitalization, potentially missing patients with paroxysmal atrial fibrillation. Although we found a nonsignificant higher prevalence of AF in our sample of patients with OSA, larger studies are needed to investigate the potential pathological link between OSA and AF in promoting ischemic stroke. Finally, our study’s cross-sectional design limits the availability of follow-up data, and thus we cannot draw any meaningful conclusions regarding the effect of OSA treatment on AF or stroke outcomes. ## 5. 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--- title: Effects of Gold Nanoparticles Functionalized with Cornus mas L. Fruit Extract on the Aorta Wall in Rats with a High-Fat Diet and Experimental-Induced Diabetes Mellitus—An Imaging Study authors: - Remus Moldovan - Daniela-Rodica Mitrea - Adrian Florea - Luminiţa David - Laura Elena Mureşan - Irina Camelia Chiş - Şoimița Mihaela Suciu - Bianca Elena Moldovan - Manuela Lenghel - Liviu Bogdan Chiriac - Irina Ielciu - Daniela Hanganu - Timea Bab - Simona Clichici journal: Nanomaterials year: 2023 pmcid: PMC10051497 doi: 10.3390/nano13061101 license: CC BY 4.0 --- # Effects of Gold Nanoparticles Functionalized with Cornus mas L. Fruit Extract on the Aorta Wall in Rats with a High-Fat Diet and Experimental-Induced Diabetes Mellitus—An Imaging Study ## Abstract Diabetes mellitus and high-fat diets trigger the mechanisms that alter the walls of blood vessels. Gold nanoparticles, as new pharmaceutical drug delivery systems, may be used in the treatment of different diseases. In our study, the aorta was investigated via imaging after the oral administration of gold nanoparticles functionalized with bioactive compounds derived from Cornus mas fruit extract (AuNPsCM) in rats with a high-fat diet and diabetes mellitus. Sprague Dawley female rats that received a high-fat diet (HFD) for 8 months were injected with streptozotocin to develop diabetes mellitus (DM). The rats were randomly allocated into five groups and were treated, for one additional month with HFD, with carboxymethylcellulose (CMC), insulin, pioglitazone, AuNPsCM solution or with Cornus mas L. extract solution. The aorta imaging investigation consisted of echography, magnetic resonance imaging and transmission electron microscopy (TEM). Compared to the rats that received only CMC, the oral administration of AuNPsCM produced significant increases in aorta volume and significant decreases in blood flow velocity, with ultrastructural disorganization of the aorta wall. The oral administration of AuNPsCM altered the aorta wall with effects on the blood flow. ## 1. Introduction The obesity–diabetes mellitus–hypertension triad represents a well-known pathological interconnection that still requires studies of the involved factors, intricate mechanisms and possible treatments. Data in the literature present a high-fat diet (HFD) as the promoter of heart, kidney and liver impairments, diabetes mellitus (DM) or atherosclerosis development, among other tissue alterations [1]. Diabetes mellitus type 2 evolves through different mechanisms (oxidative stress produced by chronic hyperglycemia, insulin resistance, polygenic defects, environmental trigger factors, etc.) [ 2] and requires specific treatment approaches. Numerous researchers studied the effects of different natural extracts (Aloe vera, Zingiber officinale, Tabernaemontana divaricata, etc.) on the pathophysiological mechanisms of DM, showing beneficial effects on hyperglycemia [3,4,5] and on diabetes-related cardiovascular impairments [6]. New pharmaceutical drug delivery systems, including nanoparticles of different structures, dimensions, chemical and electrical properties, were developed to improve the treatment of diseases [7]. Gold nanoparticles (AuNPs) are considered biocompatible and stable delivery systems [8], but several studies have presented the noxious potential of AuNPs functionalized with different natural extracts on the liver [9], DNA [10] or with conflicted results in the cardiovascular system [11]. Our study evaluated rats with chronic HFDs and DM, treated with Cornus mas L. extract (CM) or gold nanoparticles functionalized with Cornus mas (AuNPsCM) to evaluate modifications in the aorta wall using imaging techniques. The present study is part of a larger project that started with the idea that gold nanoparticles could improve the delivery of the Cornus mas L. extract in the vessel wall, to prevent or even to solubilize the atherosclerotic plaques that occur with a prolonged, high-fat diet with or without experimental-induced diabetes mellitus. ## 2.1. Fruit Extract Preparation and Characterization All chemicals used to obtain fruit extract and synthesize the gold nanoparticles were purchased from Merck (Darmstadt, Germany). The Cornelian cherries (bought from the Central Market of Cluj-Napoca in August 2021 and kept frozen until use) were crushed and mixed with food-grade acetone (in a 1:5 ratio). After stirring for 1 h at ambient temperature, the mixture was vacuum-filtrated, and the acetone was totally removed using low-pressure distillation. The biological activity of the resulting concentrated fruit extract was determined and used to synthesize the gold nanoparticles. The Cornelian cherry extract was characterized in terms of total phenolic content, determined using the Folin–Ciocalteu assay [12] with minor modifications [13]. Thus, to a mixture of Folin-Ciocalteu reagent (100 µL) and Cornelian cherry fruit extract (10 µL), Na2CO3 (80 µL) were added. After 2 h of storage in a dark at room temperature, the absorbance of the solution was recorded at 765 nm. Using a calibration curve (solutions in the range of 0.025–0.15 mg/mL, R2 = 0.9986), the total phenolic content of the fruit extract was expressed as milligrams of gallic acid equivalents (GAE)/mL extract [12,14,15]. ## 2.2. High-Performance Liquid Chromatography (HPLC) The LC/MS analysis was performed on a Shimadzu Nexera I LC/MS—8045 (Kyoto, Japan) HPLC system equipped with a quaternary pump and autosampler, respectively, an ESI probe and quadrupole rod mass spectrometer. The separation was carried out on a Luna C18 reversed-phase column (150 mm × 4.6 mm × 3 mm, 100 Å) from Phenomenex (Torrance, CA, USA). The column was maintained at 40 °C during the analysis. The mobile phase was represented using a gradient made from methanol (Merck, Darmstadt, Germany) and ultra purified water prepared with a Simplicity Ultra Pure Water Purification System (Merck Millipore, Billerica, MA, USA). Formic acid (Merck, Darmstadt, Germany) was used as an organic modifier. The methanol and the formic acid were of LC/MS grade. A flow rate of 0.5 mL/minute was used. The total time of an analysis was 35 min. The detection was performed on a quadrupole rod mass spectrometer operated with electrospray ionization (ESI), both in negative and positive multiple reaction monitoring (MRM) ion mode. The interface temperature was set at 300 ºC. Nitrogen was used at 35 psi for vaporization and as drying gas, respectively, at 10 L/min. The capillary potential was set at +3000 V. The identification was performed using comparison of retention times, MS spectra and its transitions between the separated compounds and standards. The identification and quantification were conducted based on the main transition from the MS spectra of each compound. For quantification purposes, the calibration curves were determined. The injected volume for each standard at each concentration was 1 µL [14,15]. All compounds used were purchased from Phytolab, Vestenbergsgreuth, Germany. ## 2.3. Gold Nanoparticles Synthesis, Characterization and Tissue Determinations Gold nanoparticles were obtained using tetrachloroauric acid as the source of gold ions and the Cornelian cherry fruit extract as the source of reducing and capping bioactive compounds. Thus, the alkalinized fruit extract (brought at pH = 7.5 using a 0.1 M solution of NaOH) was slowly added to a boiling 1 mM solution of HAuCl4 (in a 1:4 ratio) and the resulted mixture was stirred at room temperature. After 30 min, the change of the color from faint pink to red–purple confirmed the formation of colloidal gold. The colloidal solution was subjected to centrifugation at 14,000 rpm for 30 min and the resulting AuNPs were washed twice with bidistilled water and air-dried. UV-Vis spectroscopy (using a Perkin-Lambda 25 double beam spectrometer, band width 1 nm, minimum spectral resolution 0.5 nm, wavelength accuracy ±0.1 nm) and transmission electron microscopy (using a Hitachi Automatic H-7650 microscope) was used to characterize the obtained gold nanoparticles. ImageJ software was used for automatic particle counting and size determination, 100 nanoparticles were considered. The zeta potential of the gold nanoparticles was determined through microelectrophoresis using a DLS instrument with a He–Ne laser (633 nm) and an avalanche photodiode detector. The level of the gold nanoparticles in the aorta wall was determined with ICP–OES (inductively coupled plasma–optical emission spectrometry) using a Perkin Elmer OPTIMA 2100 DV spectrometer, following the method that was described in our previous article [16]. ## 2.4. Animals Sprague Dawley adult female rats were used to investigate the effects of gold nanoparticles functionalized with Cornus mas L. extract (AuNPsCM) as treatment after prolonged high-fat diet and experimental-induced diabetes mellitus. The animals (35 rats), 3 months old with body weight of 300 ± 10 g, were brought from Cantacuzino National Medico-Military Institute for Research and Development, Bucharest, Romania. The rats were hosted in cages in standard environmental conditions (temperature 21 ± 2 °C, relative humidity $55\%$ ± 5) and were nourished exclusively with standardized rich lipid food. After 9 months of high-fat diet (HFD), the rats increased their body weight at 600 ± 10 g. The access to filtered tap water was ad libitum, like the access to the same type of feed that was administered by gavage every day. The study had the approval of the Ethics Committee of the Iuliu Hatieganu University of Medicine and Pharmacy (no. $\frac{158}{11.03.2019}$) according to the Directive $\frac{86}{609}$/EEC. ## 2.5. High-Fat Diet (HFD) The lipid-rich diet used for animal feeding was purchased from the Cantacuzino National Medico-Military Institute for Research and Development, Bucharest, Romania. The high-fat food was administered by gavage, bringing an additional $45\%$ level of energy. The composition of the diet was described in our preliminary study [16]. ## 2.6. Diabetes Mellitus Induced by Streptozotocin Administration During the last 3 days of the 8th month of the experiment, diabetes mellitus was induced in all rats in the following manner: streptozotocin was injected intraperitoneally, 30 mg/kg, 2 times, 72 h apart. ## 2.7. Experimental Design In the study, 35 rats were randomly allocated into 5 groups ($$n = 7$$) with high-fat diet (HFD) for the entire duration of the experiment. At the beginning and at the end of the experiment, the rats were weighed. After 33 weeks of HFD, diabetes mellitus was induced in all rats and the treatment was introduced at 3 days after the streptozotocin administration when all rats had glycemia above 250 mg/dL. The diabetic rats were treated daily, between 8 a.m. and 9 a.m., for one month (the 9th month of the experiment with HFD) as follows: CMC group: 0.6 mL/day of $1\%$ carboxymethylcellulose solution, through gavage; Insulin group: 0.1 mg/kg of insulin, subcutaneous injection; Pioglitazone group: 0.6 mL/day of pioglitazone solution, 10 mg/kg, through gavage; AuNPsCM group: 0.6 mL/day of gold nanoparticles functionalized with Cornus mas L. extract (260 μg AuNPs/kg/day), through gavage; CM group: 0.6 mL/day of Cornus mas L. extract solution (30 mg/kg/day of polyphenols), through gavage. During the last day of the experiment, ultrasound and MRI scans were performed. Ketamine $10\%$ (5 mg/100 gbw) and xylazine hydroxychloride $2\%$ (100 mg/100 gbw) were used to induce deep anaesthesia in rats and descending thoracic aortas were collected for transmission electron microscopy investigation. ## 2.8. Ultrasound (US) Evaluation A 2D Doppler transthoracic echocardiogram was performed to determine the blood flow speed and the aorta caliber, using a Sonotouch Tablet System (Ultrasonix Medical Corporation, Richmond, BC, Canada). The animals were sedated throughout the whole procedure. The system included a MS250 transducer that used a frequency of 24 MHz with harmonics and 16 MHz with Doppler. The transducer was placed on a system with linear positioning, which allowed it to pan across the scanning area. The Doppler incidence angle was 51° with a maximal individual correction of 60°, conducted for each rat. ## 2.9. IntraGate Flash CINE The aortas of all rats were scanned. Before scanning, the animals were anesthetized through intramuscular administration of 100 mg/kg ketamine and 50 mg/kg xylazine at a 2:1 ratio. After complete anaesthesia was confirmed, the rats were placed in a ventral decubitus position on the MRI bed and connected to an external ECG device to monitor and synchronize the IntraGate FLASH. This method provided two core advantages: both a short preparation and examination time. Moreover, it enabled the acquirement of high-resolution images, which in turn, allowed for accurate volumetric measurements and a low error rate in determining aortic functionality. The MRI model utilized for scanning was BrukerBioSpec $\frac{70}{16}$ USR, operated at 7 Tesla, with a dedicated IntraGate FLASH protocol, used to acquire structural images at the T2 relaxation time. It was equipped with a superconductive magnet, which functioned at a temperature of 4.2 Kelvin, with an active diameter of 160 mm, while the gradient unit (BGS 9 HP) offered 90 mm for the radiofrequency (RF) coils used to investigate the experimental animals. The dual resonance frequency was configured for investigations conducted at the 300 MHz mark for hydrogen protons, and, respectively, a varying frequency for the X channel. The protocol for the rat aorta geometry study followed a 2D IntraGateTripilot design with a visual field of 6 cm, a section width of 1 mm and an inter-section distance of 2 mm, obtained through a repeating time interval of 200 ms and an ECO time of 3 ms. The tripilot images with a sagittal section were investigated to confirm that the acquired sections included the area of interest, as depicted in Figure 1. For aorta reconstruction, an IntraGateFlash CINE scanning technique was used—a fast acquiring protocol, with a field of view of 4.20–5.60 cm, axially oriented in a specific way that eased reconstruction, with a section width of 0.8–1 mm and an inter-slice length of 0.4–1.5 mm and a matrix of 256 × 256, which assured a resolution power between 0.0128 and 0.0129 cm/pixel. These adjustments, coupled with a repetition time of 453–511 ms and 45–69 slices, led to a maximal acquirement time of 5 min and 36 s. The measurements were performed on the descending aorta, 10 mm of its superior part, after the aortic arch. The images obtained for 3D reconstruction were run through the specialized software AMIRA. After reconstruction, the descending aorta was selected, and the surrounding areas were removed (Figure 2). Following reconstruction, the software automatically calculated the volume of interest according to a table. ## 2.10. Transmission Electron Microscopy (TEM) For the TEM investigation, the aorta samples were prepared using the method described in our previous article [16]. The aorta sections of 60–80 nm were examined with a JEOL JEM 100CX II transmission electron microscope (JEOL, Tokyo, Japan) and the images were taken with a MegaView G3 camera (EMSIS, Münster, Germany). ## 2.11. Statistical Processing GraphPad Prism version 5.03 for Windows, GraphPad Software (San Diego, CA, USA) was used to evaluate the modification significance of the measured parameters with a one-way ANOVA followed with the Tukey post-test. The threshold significance level was considered at $p \leq 0.05.$ ## 3.1. Characterization of Cornus mas L. xtract The results obtained for the identification and quantification of the polyphenolic compounds from the tested extract are presented in Table 1, together with their retention times and main MS transitions. ## 3.2. Characterization of Gold Nanoparticles Functionalized with Cornus mas L. Phytocompounds The distribution of gold nanoparticles on the aorta wall was investigated with a finding of 0.038 ± 0.003 mg/g. The synthesized nanoparticles were stable. After 13 zeta runs, the synthesized nanoparticles presented a zeta potential of −33.7 ± 3.03 mV. The Folin–Ciocalteu method, applied to determine the total phenolic content of the fruit extract, resulted in a value of 0.7437 ± 0.071 mg GAE/mL of fruit extract. UV-Vis spectroscopy was used to confirm the formation of the gold nanoparticles through the reduction in gold ions by the bioactive compounds from the Cornelian cherry extract. The UV-Vis spectrum of the Cornelian cherry fruit extract (Figure 3) exhibited a maximum at 507 nm, which is the specific λmax for anthocyanin compounds. In the spectrum of the colloidal gold solution, a maximum at 527 nm could be observed, which is the characteristic value for the surface plasmon resonance of metallic gold [17,18]. The shape and size of the obtained gold nanoparticles were investigated using transmission electron microscopy. Figure 4 shows a TEM image of the investigated AuNPs, which proved that they were spherical and had a mean diameter of 19 nm ± 1.5 nm. ## 3.3.1. Ultrasound Aorta Examination The effects of the administered treatment on the aorta were investigated in the rats with prolonged HFD and experimental-induced DM. The diameter of the rats’ descending aorta was significantly increased in the Insulin ($p \leq 0.05$), Pioglitazone ($p \leq 0.001$) and AuNPsCM ($p \leq 0.01$) groups, compared to the CMC group (Figure 5 and Figure 7A). The blood flow velocity in the descending aorta was correlated with the aorta diameter modifications; significant decreases were recorded in the Pioglitazone ($p \leq 0.001$) and AuNPsCM ($p \leq 0.05$) groups, compared to the negative control group. When compared to the positive control Pioglitazone group, the CM group showed significant increases ($p \leq 0.01$) in the blood flow velocity (Figure 6 and Figure 7C). ## 3.3.2. IntraGateFlash CINE Scanning Investigation MRI was used to determine aorta volume. Compared to the CMC group, all of the treated groups presented significant increases in the volume of the aorta: the Insulin, Pioglitazone and AuNPsCM groups ($p \leq 0.001$); the CM group ($p \leq 0.01$). In comparison with insulin administration, significant increases ($p \leq 0.001$) in the volume of the descending aorta was recorded in the groups that received pioglitazone or gold nanoparticles functionalized with Cornus mas L. extract, while the treatment with the simple solution of the natural extract significantly ($p \leq 0.001$) decreased the volume in the descending aorta. The CM group had the smallest increase in descending aorta volume, and, in comparison with the AuNPSCM group, the MRI investigation recorded significant decreases ($p \leq 0.001$) (Figure 7B). ## 3.3.3. TEM Investigation In the CMC group, the TEM examination of the aorta samples revealed a normal thickness of intima that was heterogeneous and with fine ultrastructural alterations (Figure 8A,B). The endothelial cells contained numerous and large vacuoles, both around the nucleus and in their extensions (Figure 8A), some of them prominent into the lumen (Figure 8A,B). Rare endothelial cells were partially detached from the subendothelial connective layer, and their numerous transcytosis vesicles indicated intense metabolic activity (Figure 8B). The subendothelial connective layer also had normal thickness but was heterogeneous (Figure 8A) or rarefied (Figure 8B), in many places being visible macrophages that participated int the formation of atherosclerotic plaques. In media, the smooth muscle cells displayed characteristic ultrastructure with many vesicles of endocytosis (Figure 8C,D) and some large cytoplasmic vacuoles (Figure 8D); the extracellular matrix was homogeneous (Figure 8C,D). All elastic laminae were homogeneous, with normal aspect (Figure 8A–D). In the aorta of the rats in the Insulin group, the intima showed a thinned and mostly continuous endothelium (Figure 9A–D). The endothelial cells contained many transcytosis vesicles and rare large vacuoles (Figure 9C). In some regions, the endothelial cells were removed from the subendothelial connective layer, and the remaining gaps were filled with aggregated blood platelets forming thin clots (Figure 9D). The subendothelial connective layer had variable thicknesses and heterogeneous structure (Figure 9A–D), with infiltrated macrophages (Figure 9A) and vacuoles (Figure 9C). In media, the smooth muscle cells displayed normal ultrastructure, with the exception of some cytoplasmic vacuolations, most likely enlarged mitochondria (Figure 9A,B), and the extracellular matrix was heterogeneous with rarefied areas. The elastic laminae had a normal, homogeneous aspect (Figure 9A–D). In the Pioglitazone group, the intima was of a different thickness in the different studied regions, in some cases due to the different sizes of the subendothelial connective layer (Figure 10A) or due to the endothelial cells prominent into the lumen, with numerous macrophages (of atherosclerotic plaques) in the subendothelial connective layer, respectively (Figure 10B). In the cytoplasm of the endothelial cells, many vesicles of transcytosis were noted, as well as rare large vacuoles (Figure 10A,B). The endothelial cells also contained many Weibel–Palade bodies (Figure 10A,B). The media presented smooth muscle cells with characteristic aspect, but with extensive cytoplasmic vacuolation, and the matrix among the cells was heterogeneous with rarefied areas (Figure 10C,D). All elastic laminae were homogeneous (Figure 10A–D). In the AuNPsCM group, the intima was severely reduced in thickness, mainly due to the presence of a very thin, uniform subendothelial connective layer (Figure 11A,B). The endothelial cells had a normal ultrastructure (with many vesicles of transcytosis and Weibel–Palade bodies), and sometimes were prominent into the lumen (Figure 11A,B). All of these features suggested a previous denudation of the inner lamina. The media showed smooth muscle cells with normal aspect, connected by a homogeneous extracellular matrix (Figure 11C,D). All elastic laminae were homogeneous (Figure 11A–D). In the aortas from the CM group, the intima was well represented: the endothelial cells had normal aspect and ultrastructure while the subendothelial connective layer was thick but heterogeneous, showing rarefied regions and regions consisting of compact packed, dense fibers (Figure 12A,B). The media contained smooth muscle cells with characteristic aspect, and the extracellular matrix was homogeneous (Figure 12C,D). All elastic laminae were homogeneous (Figure 12A–D). ## 4. Discussion The present study investigated the modifications in the aorta wall structure and functionality in rats with 9 months of a high-fat diet, the last month with experimental-induced diabetes mellitus and treatment. To evaluate the effects of gold nanoparticles functionalized with Cornus mas L. extract, insulin and pioglitazone were used as positive controls and CMC as a negative control. The effect of Cornus mas L. simple extract administration on this pathological condition (diabetes mellitus) was also studied. The imaging examination of the descending aorta in a length of 1 cm, right after the aortic arch, showed significant modifications among the groups. Insulin administration produces vasodilation [19] through its direct action on the endothelial cells that release nitric oxide [20]. Insulin also has anti-atherosclerotic effects [21] that are blocked in DM by the release of the protein kinase C isoforms, β and δ, in several tissues but also in the aorta and heart [22]. In the present study, similar to these previous researches, significant aorta vasodilation with significant increases in aorta volume was observed in diabetic rats that received insulin as a treatment, but with non-significant decreases in blood flow velocity. The TEM investigation identified ultrastructural modifications in the intima (thin endothelium with vacuolized endothelial cells, few of these cells were removed and replaced by small clots; heterogenous subendothelial connective layer with macrophages and vacuoles) and in media (several smooth muscle cells with vacuoles, probably the enlarged mitochondria). Compared to the aorta in rats with DM and prolonged HFD treated with CMC that presented the modifications specific for this pathological condition in the intima (endothelial cells with vacuoles, only a few partially detached; heterogenous subendothelial connective layer with macrophages) and in media (smooth muscle cells with endocytic vesicles and large vacuoles), the aorta of the rats treated with insulin presented much altered ultrastructure. Our findings are concordant with the data presented by Kaur et al. in their review that identified hyperglycemia as a trigger for endothelial dysfunction, platelet activation and adhesion to the wounded vessel wall area [23]. The variable thickness of the aorta subendothelial connective layer, found in our rats with insulin treatment, may explain the aorta stiffness presented by Dec-Gilowska et al. in their study of patients with diabetes mellitus type 2; stiffness that was much higher in patients that received insulin [24]. The accumulation of macrophages in the intima of the aorta found in our TEM investigation may be, as Quinn showed in her study, the consequence of hyperglycemia that stimulates the low density lipoprotein (LDL) glycation, process that makes them miss the connection with LDL receptors, leading to the cholesteryl esters synthesis, a mechanism that attracts the macrophages to uptake these lipid molecules and to develop the foam cells [2]. The presence of foam cells in the aorta wall of our rats could be also the result of the prolonged HFD that transformed the smooth muscle cells of the aorta into macrophage-like cells for lipids storage, as Gui et al. presented in their review [25]. The well-developed mitochondria observed in the smooth muscle cells might be the effect of insulin administration, a result that is in concordance with those mentioned by Karwi et al. in their study performed on isolated mouse hearts, using insulin to analyze glucose oxidation [26]. Pioglitazone administration had similar effects to the insulin treatment. The ultrasound examination of the rats’ aorta treated with this antidiabetic medication that proved to also have antioxidant and anti-inflammatory effects [11,27], had the most significant vasodilation with the lowest significant blood flow velocity, compared to the rats in the negative control group. These modifications were confirmed with the MRI investigation that recorded the highest descending aorta volume (Figure 7). These findings were concordant with the study performed on persons with impaired glucose regulation by Yu et al., which showed the increase in nitric oxide levels after the administration of pioglitazone at a dose of 15 mg/day for 12 weeks [28]. The vasodilation may be also explained by the opening effect of pioglitazone on the smooth muscle KV (voltage-dependent K+) and/or KIR (inward rectifier K+) channels that was reported by Nomura et al. in their study on the isolated rat aorta [29]. The TEM investigation on the aorta wall of the Pioglitazone group showed similar effects as were recorded in the Insulin group, no clots inside the endothelial layer but Weibel–Palade bodies inside the endothelial cells, the sign of DM modifications of these cells toward a secretory phenotype that leads to atheroma development, as Toma et al. mentioned in their review [30]. Gold nanoparticles functionalized with Cornus mas L. extract (AuNPsCM) altered the aorta wall in a specific manner: it stimulated the endothelial layer to produce Weibel–Palade bodies and thinned the subendothelial connective layer. The presence of Weibel–Palade bodies in high amounts in the endothelial cells was correlated with the initial phase of DM, before the onset of the vascular alterations [31]. The fact that the endothelial layer was not affected by the AuNPsCM treatment might be explained by the small dimensions of these delivery systems (19 nm) that permitted their passage toward the subendothelial layer. The denudation of the inner lamina and the subendothelial connective layer alteration that were observed in the aorta of the diabetic rats with HFD treated with AuNPsCM were also noticed in our preliminary study, performed on rats with only HFD [16], suggesting that these nanoparticles were involved in the ultrastructural modifications of these areas. Compared to the CMC (negative control) group, the ultrasound examination showed a significant increase in the descending aorta diameter, a significant decrease in blood flow velocity, and the MRI investigation presented a significant increase in this aorta segment volume, results that correlate with TEM findings: the thinning of the aorta wall might be the cause of the diameter increase. The administration of Cornus mas L. extract as a simple solution improved the aorta wall ultrastructural aspect in rats with DM and prolonged HFD, compared to the negative and positive control groups, while the imaging investigations showed similar results to the negative control. The beneficial effects of natural extract might be explained by its chemical compounds that we identified through HPLC determination: flavonoids (naringenin, kaempferol, rutoside and their derivatives) that have been previously presented in the literature as part of this natural compound [32,33,34]; phenolic acids (caffeic and chlorogenic acids) mentioned by Bayram and Ozturkcan [35]; but also chrysin, hyperoside and luteolin. Several studies presented caffeic acid as an antioxidant [36], anti-inflammatory [37] and even a smooth muscle relaxing compound, as Siva et al. showed in their study performed in organ bath using the rat thoracic aorta [38]. The other phenolic acid identified in Cornus mas L. extract, chlorogenic acid, was found in our previous studies as an efficient antioxidant and anti-inflammatory element, in a dose-dependent manner [39,40], Wu et al. described this natural compound as anti-atherosclerotic [41], Hada et al. as a potent inhibitor of aorta senescence in their study performed on mice with saline or angiotensin II administration [42], and many other studies indicated the beneficial effects of this acid. Among the Cornus mas flavonoids identified in our study, naringenin was presented by Fallahi et al. in their experiment performed on diabetic rats as a factor that might improve the endothelial function of the aorta [43], kaempferol was described by Xiao et al. in their study realized in apolipoprotein E-deficient mice as an inhibitor of the aorta oxidative stress and atherosclerotic lesion [44] while Ren et al. in their review, exposed this flavonoid properties in DM alleviation [45]. In their study performed on mice with HFD and streptozotocin-induced DM, Lee et al. found that rutin (rutoside) could improve the activity of the β-cell function [46]. Chrysin, the flavonoid found in our HPLC determination, has anti-atherosclerotic effects through lipid peroxidation inhibition, as Farkhondeh et al. presented in their review [47]; produces vasodilation, an effect related by Tew at al. in their experiment performed on rat aorta ring [48], and like luteolin (another identified flavonoid in Cornus mas L. extract), may restore the vascular response [49]. Luteolin has protective effects on β-cells, providing protection against the noxious mechanisms that occur in DM and may improve endothelial dysfunction, as Queiroz et al. revealed in their experiment using the administration of this natural compound in rats (10 mg/kg/day for 2 months) [50]. Luteolin decreases the oxidative stress protecting the aorta function, as Qian et al. showed in their study on aorta rings of male Sprague Dawley rats [51] and may have antioxidant, anti-inflammatory and antidiabetic effects [52]. In our experiment, we also identified hyperoside as a Cornus mas constituent, a chemical that improves endothelial dysfunction and protects the myocardial cells in diabetes mellitus, properties that were presented by Xu et al. in their review [53]. All of these beneficial effects of the elements identified in Cornus mas L. extract may explain our result: the preservation of the aorta wall function and structure, in experimental-induced DM in rats with chronic HFD. The present study focused on the modifications that might occur in the wall of the descending aorta in rats with prolonged HFD and experimental-induced DM when insulin, pioglitazone or Cornus mas L. extract in two forms (simple or nanoparticulate solutions) were administered as a daily treatment for one month. The results showed the beneficial effects of Cornus mas L. simple solution on the intima of the diabetic aorta wall with a normal aspect of endothelial cells, and the injury produced by the AuNPsCM treatment on the subendothelial connective layer. The aim of our larger project was to evaluate the effects of gold nanoparticles suspended in citrate buffer (AuNPs) (Sigma Aldrich, Germany) or functionalized with Cornus mas L. extract (AuNPsCM) on the aorta wall in healthy rats [54], rats with prolonged HFD [16] and also rats with chronic HFD and experimental-induced DM ([11] and the current study). 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--- title: 'Effects of Radiofrequency Diathermy Plus Therapeutic Exercises on Pain and Functionality of Patients with Patellofemoral Pain Syndrome: A Randomized Controlled Trial' authors: - Manuel Albornoz-Cabello - Alfonso Javier Ibáñez-Vera - Cristo Jesús Barrios-Quinta - Inmaculada Carmen Lara-Palomo - María de los Ángeles Cardero-Durán - Luis Espejo-Antúnez journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051503 doi: 10.3390/jcm12062348 license: CC BY 4.0 --- # Effects of Radiofrequency Diathermy Plus Therapeutic Exercises on Pain and Functionality of Patients with Patellofemoral Pain Syndrome: A Randomized Controlled Trial ## Abstract Although consensus has been reached about the use of therapeutic exercise in patellofemoral pain syndrome, several techniques used worldwide such as radiofrequency diathermy could be useful as complementary therapy. The objective of this randomized controlled trial was to compare the effects of adding radiofrequency diathermy to therapeutic exercises in patients with patellofemoral pain syndrome. Fifty-six participants were randomly assigned either to radiofrequency diathermy plus therapeutic exercises group ($$n = 29$$) or therapeutic exercises group ($$n = 27$$). Both groups received the same therapeutic exercises, and the diathermy group additionally received monopolar dielectric diathermy for three weeks (5–3–2 weekly sessions). Data related to intensity of pain, probability of neuropathic pain, functionality, and range of movement of the knee were measured at baseline and three weeks after the intervention. Comparing pre-treatment and values obtained at the third week, significant improvements were found in intensity of pain, neuropathic pain, functionality, and range of motion in both groups ($p \leq 0.05$). The diathermy plus exercises group had significantly better intensity of pain than the control group at the end of the three weeks ($p \leq 0.01$). The addition of diathermy by emission of radiofrequency to the therapeutic knee exercise protocol is more effective than a therapeutic exercise protocol alone in the relief of intensity of pain in patients with patellofemoral pain in the immediate post-treatment follow-up compared with baseline scores. ## 1. Introduction Patellofemoral pain syndrome is a very common musculoskeletal dysfunction, characterized by pain in the anterior surface of the knee that often tends to chronicity [1]. Although it affects all population groups, a higher incidence has been observed in adolescents and young adults [2]. Pain while walking upstairs and downstairs, squatting, running, or sitting for a long time is referred to by most patients with patellofemoral pain syndrome [1,3]. Even though it has traditionally been associated with cartilage damage, knee osteoarthritis and elevated body mass index, researchers have shown no relation with these aspects [4,5]. According to some authors, the compression forces implicated in these activities could explain these symptoms [6]; however, some other authors’ views differ, pointing to unknown causes for patellofemoral pain [7]. A wide variety of pathologies can present similar signs and symptoms as patellofemoral pain syndrome, and for this reason, the term is used to describe any pain in the anterior surface of the knee [8]. Patellofemoral pain syndrome could precede patellofemoral osteoarthritis, a condition that may require surgical treatment and total knee replacement [9,10]. Non-surgery-based treatments are frequent, outshining physiotherapy as the most common approach [3,11]. The physiotherapy treatments include quadriceps strengthening to improve the active stability of the patella in the femoral trochlea, strengthening of the hip muscles, manual therapy, taping for patellar realignment, stretching, and therapeutic exercises [3,11,12,13,14,15,16]. Even though these treatments seem to produce benefits in patellofemoral pain syndrome, there is no evidence that one treatment modality is better than another intervention for any subgroup of patients [11,14]. Only therapeutic exercises have consistent evidence to support their recommendation [11,15,16]. Clinical guidelines also advise against the use of physical agents, including in this sense ultrasound, cryotherapy, sonophoresis, electrical stimulation, and laser [11]. However, no studies about the use of radiofrequency diathermy based on capacitive-dielectric energy transmission were considered due to the lack of them. Monopolar dielectric diathermy by emission of radiofrequency (MDR) is an endogenous thermotherapy, which consists in the emission of high frequency electromagnetic signals via an isolated electrode that transfers energy to soft tissues containing electrolytes: muscles, vascular, or lymphatic tissues [17]. This modality has a documented capacity to increase the local temperature of a tissue in order to stimulate its metabolism and reduce pain by a control gate mechanism [18,19]. Furthermore, some radiofrequency-based diathermy techniques have demonstrated to have more effects on intramuscular blood flow, tissue metabolism, pain and inflammation, muscle spasms, cell activity, and elasticity [17,18,19,20], than other physical agents, such as pulsed shortwave therapy [19]. Although other diathermy methods have documented its capacity to reduce pain in patients with numerous degenerative and inflammatory orthopedic problems, such as in low back pain or in shoulder impingement syndrome [21,22], evidence about the use of monopolar dielectric diathermy in knee pain is scarce [23,24,25]. Considering therapeutic knee and hip exercises as the most consistent approach for treating patellofemoral pain syndrome [3,11], and the hypothesis that this technique could promote pain and functional recovery, the purpose of this study was to compare the effectiveness of adding MDR to a therapeutic exercise protocol versus a therapeutic exercise protocol in the intensity of pain, probability of neuropathic pain, functionality, and range of movement of patients with patellofemoral pain syndrome. ## 2.1. Study Design A prospective single-blind randomized controlled clinical trial was conducted, in which the researcher in charge of collecting the data from patients remained blind to the treatment applied to each participant. The trial was properly registered at ClinicalTrials.gov identifier NCT04538508. The investigation protocol was designed following the Helsinki Declaration and the Good Clinical Practice guidelines, according to CONSORT Standards and considering all the clinical regulations for research in humans. In this regard, all participants were appropriately informed about the study and their rights before signing the informed consent form accepting to participate. The research protocol was approved by the Ethics Committee of Virgen de la Macarena Hospital, Seville (CEI 1696-N-17). ## 2.2. Participants A total of 120 participants were initially recruited for the study, who were between 18 and 65 years of age, diagnosed with patellofemoral pain syndrome, and who were not currently undergoing any type of treatment. To be eligible, patients had to meet the following inclusion criteria: [1] patients between 18 and 65 years of age; [2] referred pain in the anterior surface of the knee of 30 mm or over in the Visual Analogue Scale (VAS) during the previous three months; [3] without radiological findings compatible with osteoarthritis; [4] without sensitivity to patellar tendon or iliotibial band palpation; [5] scoring below 45 in the psychological apprehension scale (PPAS) [25]; [6] not having previously received radiofrequency diathermy treatment. The PPAS is a validated tool, reliable, and easy to use in evaluating the apprehension of the participants to receive electrical stimulation therapy [25]. The exclusion criteria included were [1] any contraindication for the use of diathermy by the emission of radiofrequency (tumours, use of implanted electronic devices as pacemakers, thrombophlebitis or deep venous thrombosis, pregnancy, active process of tuberculosis, fever, infected wounds, osteomyelitis, and rheumatoid arthritis) [17,26,27,28]; [2] having received a corticoid or hyaluronic acid injections treatment; [3] having reduced cognition or communication abilities; [4] or being currently involved in a medical-legal dispute. The use of basic analgesic drugs was allowed in order to avoid introducing significant changes in their treatment, but it was recorded to control possible changes that could influence in the final results. Sample size calculation was based on the detection of [1] an improvement of $15\%$ in self-perceived pain intensity [29]; [2] a difference of >9 points in Lower Extremity Functionality Score at inter-group comparison after the treatment [30]; and >10 points in the Kujala Score. Considering a one-tail hypothesis, an alpha value of 0.05, a desired power of $95\%$, and a medium effect size (r2 = 0.25), and a $10\%$ drop-out at follow-up, the desired sample size was calculated to be 30 participants per group (G* Power, version 3.1.9.2, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany). ## 2.3. Outcomes Measures All 60 participants provided demographic and clinical information, and also completed a number of self-report measures and underwent a physical examination, performed by an assessor blinded to the treatment allocation of the patients. Outcome measures were assessed before the first treatment session (baseline data), and immediately after treatment (at the third week) (Figure 1). Demographic measurements of weight, body mass index, metabolic age, and fat mass were performed with a Body Composition Analyser DC 430MA (III) device Japanese Technology (Tanita Europe B.V., Amsterdam, The Netherlands) [31]. The Visual Analogue Scale (VAS) was used to assess the patients’ current level of pain and the highest and lowest level of pain experienced in the preceding 24 h. A score of 00 would mean “no pain” and 10 “extreme and insufferable pain” [32]. The minimal clinically important differences (MCID) for VAS were determined as a variation of 15–$20\%$ [33] or a reduction of 2 in VAS after the intervention [34]. The Douleur Neuropathique-4 items (DN4) questionnaire, consisting of 10 items [34,35], was used to identify patients who had a high probability of having a neuropathic pain component. The scores of the individual items are added to obtain a maximum total score of 10, with a cut-off point ≥4. The patient-reported measures of lower limb functional status were the Kujala Function Score and lower extremity functionality score. The Kujala Function Score is a 13-item self-administered questionnaire that regards symptomatology in people with patellofemoral pain syndrome, with a variable ordinal response format. The total scores range from 0 to 100 [36]. This tool presents a Cronbach’s alpha of 0.8 and test-retest Intraclass Correlation Coefficient (ICC) of 0.99 for its Spanish version [37]. Lastly, the lower extremity functionality score is a questionnaire which contains 20 questions to evaluate the function of the lower limb in patients who present local disorders [38]. The maximum possible score was 80 points, which indicated very high function, while 0 points indicated very low function. This questionnaire presents a high internal consistency (Cronbach’s alpha of 0.989) and an excellent test-retest reliability (ICC = 0.998, $95\%$) for the Spanish-speakers version [39]. The passive range of motion (ROM) in flexion and extension was measured with a conventional two-leg goniometer (angular measurement), which has shown high intratester reliability (ICC = 0.996, range 0.953–0.955 for both flexion and extension) and intertester (ICC range 0.959–0.970 for flexion and 0.85–0.898 for extension) [39]. ## 2.4. Interventions After the initial evaluation, 60 participants (considering a 1:1) with patellofemoral pain syndrome were randomly assigned to receive either MDR plus therapeutic knee exercise (experimental group) or therapeutic knee exercise alone (control group). Concealed allocation was performed using an external website (http://www.randomization.com; accessed on 6 September 2020) before the start of data collection by a researcher not involved in the recruitment or treatment of patients. One researcher distributed the randomized allocation of participants using opaque envelopes, with the participants being unaware of their selection. Another blinded researcher collected outcome measurements at baseline and immediately after the last treatment. All participants received three weeks of the intervention. Diathermy treatment was performed across three weeks, consisting of ten treatment sessions in total (the first week comprised five sessions, the second week three sessions, and the third week two sessions), while therapeutic exercises for the knee were performed daily. Each session of therapeutic exercises lasted 20 min, and, in the case of the MDR group, another 12 min of diathermy were added before the exercise protocol. Both groups were treated by a physical therapist with more than 20 years of experience in the interventions. The details of the interventions are provided below. ## 2.4.1. MDR plus Therapeutic Exercise In the MDR plus therapeutic exercise group, the participants received the same exercise protocol than the therapeutic exercise group, but prior to the exercise protocol. The participants received 12 min of monopolar dielectric diathermy by emission of radiofrequency with an ABD Modular® device (Biotronic®, Granada, Spain), in pulsed emissions of 640 kHz and 30 V in dynamic application, with a continuous rotation and translational movement on the anterior surface of the knee (Figure 2). Five milliliters of almond oil were used to improve gliding along the twelve-minute application of MDR [17,25]. The use of almond oil as transfer substance was due to the fact that a dielectric transmission device was used instead of a resistive-capacitive one; this allows the energy to be focused on depth, minimizing heating tissues on the surface [17]. ## 2.4.2. Therapeutic Exercise All participants were instructed to perform the exercise protocol for knee stability, according to the recommendations of Van Der Heijden [16]. Participants performed the therapeutic exercises over three weeks, under the supervision of a physiotherapist. The protocol included the following:Squats for concentric strengthening of quadriceps: standing with the affected knee in the maximum degree of flexion that the subject was able to achieve, the knee was slowly straightened to its full extension. Series: 3. Repetitions: 20.Squats for eccentric strengthening of quadriceps: standing with the affected knee, which was slowly flexed to the maximum degree of flexion that the subject was able to achieve. Series: 3. Repetitions: 20.Side step: consisted in lowering the good leg over the side edge of the step without touching the ground. Series: 3. Repetitions: 20Bridge exercise for hamstrings: the patient lied supine on a mat, with the knees bent, the soles of the feet well supported, and the heels at a distance of half a foot from the gluteus. From this position, the patient had to raise the pelvis towards the ceiling. Series: 3. Repetitions: 20 s.Clam exercise for gluteus medius: the patient lied on their side with the knees bent and keeping the feet together. Then, the patient had to raise the knee of the top leg, opening the legs up so that the legs made the shape of a clam. Series: 3. Repetitions: 20 s.Soleus Stretch Standing: standing with the affected leg back, both knees bent, keeping the heels on the floor, turned slightly out, leaning the body towards the wall until the stretch was felt in the lower calf. Series: 3. Repetitions: 1 min. Gastrocnemius Stretch Standing: same as the previous stretch but with the affected knee extended. Series: 3. Repetitions: 1 min. The exercises were performed during approximately 20 min according to the patients’ possibilities, not exceeding 3 of pain in VAS and including one minute of rest among each series. Those patients who reported a pain sensation of 3 or greater reduced the number of repetitions and increased the rest time, thus reducing the level of resistance requested. The progression was performed according to the patient’s sensations. ## 2.5. Statistical Analysis An assessor blinded to the treatment allocation conducted the statistical analysis using SPSS statistical software, version 27.0. Data were reported as mean (standard deviation) and confidence intervals (IC $95\%$). Firstly, the normal distribution of variables was verified by the Kolgomorov–Smirnov test, after a descriptive analysis. Levene test was used to assess the homogeneity of variances. Linearity was assessed by bivariate dispersion graphics of residual values observed from the expected values. Baseline demographic and clinical variables were examined between both groups, with independent Student’s t-test for continuous data and χ2 tests of independence for categorical data. Separate 2 × 2 mixed model ANOVA with time (baseline and post- treatment) as the within-subjects factor, and group (MDR plus therapeutic exercise or therapeutic exercise) was used to determine the effects of the treatment. Effect size was tested using Cohen’s d. An effect size <0.2 reflects a negligible difference, between ≥0.2 and ≤0.5 a small difference, between ≥0.5 and ≤0.8 a moderate difference, and ≥0.8 a large difference. Eta squared (η2) was also used to calculate the effect size (small, 0.01 ≤ η2 < 0.06; medium, 0.06 ≤ η2 < 0.14; and large, η2 > 0.14). A p-value less than 0.05 was considered to indicate a statistically significant difference. ## 3. Results Four general practitioners (blinded to group allocations and assessment) from a primary care health center of the Andalusian Health Service (Seville, Spain) recruited 120 participants between August and September 2020. After referral by a general practitioner, patients were interviewed face to face by another blinded researcher to check that they met the inclusion and exclusion criteria. A total of 60 participants with patellofemoral pain syndrome met the inclusion criteria and were recruited for the clinical trial (Figure 1). After the inclusion phase, four subjects withdrew from the study because they missed almost one session of treatment and 56 participants were thus included in the study, 27 men and 29 women [mean age: 43.18 (5.7) years]. They were randomly assigned either to MDR plus therapeutic exercise group ($$n = 29$$) or to therapeutic exercise group ($$n = 27$$). Out of the knees treated, 29 were right ($52\%$) while the remaining 27 were left ($48\%$). The mean (SD) for demographic characteristics and differences between groups at baseline are shown in Table 1 ($p \leq 0.05$ for all). Within group analysis showed a significant improvement from baseline values for all subscales in the MDR plus therapeutic exercise group (change score: VAS = 4.8, DN4 = 4.1, Kujala Score = 19.2, Lower Extremity Functionality Score = 22.4, flexion = 15.7°; $p \leq 0.001$); only the range of movement in extension obtained a $$p \leq 0.031$$ (change score extension = 1.0). Although the therapeutic exercise group also experienced changes in all subscales, except for extension ($$p \leq 0.161$$), these differences were smaller than in the MDR plus exercise group (change score: VAS = 0.9, DN4 = 1.8, Kujala Score = 19.7, Lower Extremity Functionality Score = 14.2, flexion = 8.8°; $p \leq 0.002$). Table 2 includes baseline and post-treatment outcomes, as well as the between-groups mean differences and effect size. An ANOVA test showed statistically significant differences between groups with respect to intensity of pain (F1,54 = 37.79, $$p \leq 0.000$$, η2 = 0.41), and probability of neuropathic pain (F1,54 = 4.23, $$p \leq 0.045$$, η2 = 0.07). Although no significant differences between groups were found for disability and range of movement, the results showed greater improvement in Lower Extremity Functionality Score in the MDR plus therapeutic exercise group (change score: 22.4) than in the therapeutic exercise group (change score: 14.2) at post-treatment follow-up. No significant differences between groups were found for Kujala Score (F1,54 = 1.4, $$p \leq 0.242$$, η2 = 0.025), Lower Extremity Functionality Score (F1,54 = 0.18, $$p \leq 0.67$$, η2 = 0.003), and range of movement (Flexion: F1,54 = 3.44, $$p \leq 0.069$$, η2 = 0.06; Extension F1, 54 = 0.01, $$p \leq 0.91$$, η2 = 0.000). ## 4. Discussion The main finding of the present study is that the addition of MDR to therapeutic exercise produces a greater improvement in intensity of pain and probability of neuropathic pain than only supervised exercises in patients with patellofemoral pain in the immediate post-treatment follow-up compared with baseline scores. Moreover, the addition of MDR reduces disability to a greater degree than only exercise at short term. These findings are clinically very relevant as exercises have shown good results for improving function, but moderate for short-term pain reduction [12]. Through the data of this study, useful evidence to support the use of diathermy by radiofrequency in addition to therapeutic exercises for the knee has been obtained. Benefits of exercises have been observed related to functionality in patellofemoral pain syndrome [14,16]. These improvements related to movement had been explained by the effects of exercise on central nervous system neuroplasticity, which enhances the subject’s capacity to respond to new demands with functional adaptations [40]. For this reason, despite the lack of consensus about exercise in patellofemoral pain syndrome, the existing evidence is consistent enough to be the most recommended approach. Considering this, our hypothesis was based on the point that MDR plus therapeutic exercise for the knee could make a difference on pain and recovery time reduction. According to the results of this study, pain decreased in 48 in VAS ($p \leq 0.001$) when diathermy by radiofrequency was added to therapeutic exercises. This result agrees with those referred by previous studies such as the one of Kumaran and Watson [23] in knee osteoarthritis, who obtained 40 pain improvements in VAS, and the one of Albornoz et al. [ 24] in patellofemoral pain syndrome, where the diathermy group obtained a difference of 53 with respect to the control group. Summarizing, it must be outstood that the addition of MDR to therapeutic exercises obtained greater reductions in pain than therapeutic exercises alone. However, it must be considered that most of the studies about exercise for patellofemoral pain syndrome lasted for months [11], so the three-week intervention used in this study according to the local public health system could have reduced the potential benefits of exercise in this condition. In addition, and given that the patients in the diathermy group could not be blinded, a positive expectation of success in pain treatment or a placebo effect could have been created. This could be the reason for the differences between the groups. However, some authors have determined that each medical treatment takes place in the context of individual expectations and previous experiences [41,42]. Among the inclusion criteria, we determined that the participants had to have never received radiofrequency diathermy in order to minimize bias; although, it would be advisable to investigate its possible effects in future studies. Regarding function, no significant differences were observed between the MDR plus therapeutic exercise group versus the therapeutic exercise alone group, both obtaining significant improvements at post-treatment follow-up. However, adding MDR to the exercises seems to produce greater improvements in function than performing therapeutic exercises alone (differences between groups: Kujala Score 4.4; Lower Extremity Functionality Score: 5.3). We believe that these differences can be explained by the relation between pain intensity and kinesiophobia [43]. Previous studies have demonstrated that the presence of fear of movement may influence treatment outcome. Studies show that in people with chronic musculoskeletal pain, fear of physical exercise or movement is due to the common assumption of increased pain or injury, and this has been associated with increased pain intensity and disability [44,45,46,47]. There is no doubt that physical exercise has been an important component in the treatment of pain in both groups [48]; although, the diathermy group could have had better results in terms of pain and thus better function. However, this study has not evaluated the pain–kinesiophobia–function relationship in patients with patellofemoral pain syndrome. Another explanation for not having observed this more clearly could be that participants do not have enough time in the three weeks of intervention to assess subjective improvements in their daily function, as most of the studies use a larger period of intervention of four, six, or eight weeks [16,20]. Due to the fact that range of motion is not as subjective as Kujala or Lower Extremity Functionality Score, it is understandable that more clear improvements were assessed in this outcome. Regarding range of motion in flexion, statistically significant improvements were observed in patients of the diathermy group compared with those in the therapeutic exercise group. This could be explained in different ways; on the one hand, it is known that patients suffering from greater pain usually show higher levels of fear to movement, so the pain relief may have improved the range of motion [49]. While, on the other hand, the results of the study are consistent with those of Szabo et al. [ 50], who stated that the recovery protocol of combining therapeutic physical exercises with endogenous thermotherapy processes has beneficial results in recovering flexion and reducing pain. Furthermore, Ribeiro et al. [ 51] demonstrated that diathermy therapy is a good complementary method in the treatment of musculoskeletal disorders, which should be incorporated into the rehabilitation program or used in isolation, with both short- and long-term effects. For all the above, it could be recommended to always use exercise as the first approach for patellofemoral pain syndrome since its effects are more than demonstrated in all the outcome measures. Adding MDR could also be useful, effective, and safe to obtain higher pain reductions and reduce the time of recovery, as it has been shown in various musculoskeletal medical disorders such as sports-type injuries, in low back pain, and in urology [21,52,53,54]. Due to its thermotherapy implications, the diathermy therapy encourages the therapeutic procedures of wounded tissues without unwanted elevation of skin temperature [20]. However, more studies combining both therapies in patellofemoral pain syndrome are needed to confirm that a reduction in the healing process occurs. The main weakness of this study is related to the lack of a placebo group of MDR. The difficulty to solve this lies in the impossibility of producing a thermal sensation similar to diathermy without heating or promoting metabolism of the tissue. Although the use of non-emission devices is accepted, participants’ distrust could easily increase with these devices due to the lack of sensation and therefore they may suspect the sham. Another limitation is the lack of a long-term follow-up, which was not viable owing to the different places of residence of most of participants and the pandemic situation. Future research should evaluate the long-term results and implement longer treatment programs. In addition, physiological responses such as vascularity, deep muscle temperature, motor unit recruitment, etc., should be assessed. On the other hand, it should also be assessed whether the results are satisfactory enough for the application of treatment to be profitable at the clinical level. In terms of clinical relevance, this randomized clinical trial has shown significant short-term improvements in pain intensity, probability of neuropathic pain, and range of motion in flexion in patients with patellofemoral pain with a three-week MDR adjunct to exercise therapeutics. The study highlights the potential benefits of radiofrequency emission monopolar dielectric diathermy in the treatment of patellofemoral pain syndrome and provides baseline data for future research in other musculoskeletal disorders. ## 5. Conclusions The addition of MDR to therapeutic knee exercises is more effective than only therapeutic exercises at reducing intensity of pain, probability of having neuropathic pain, and range of motion in flexion in patients with patellofemoral pain syndrome. 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--- title: Kinin B1 and B2 Receptors Contribute to Cisplatin-Induced Painful Peripheral Neuropathy in Male Mice authors: - Gabriela Becker - Maria Fernanda Pessano Fialho - Indiara Brusco - Sara Marchesan Oliveira journal: Pharmaceutics year: 2023 pmcid: PMC10051506 doi: 10.3390/pharmaceutics15030852 license: CC BY 4.0 --- # Kinin B1 and B2 Receptors Contribute to Cisplatin-Induced Painful Peripheral Neuropathy in Male Mice ## Abstract Cisplatin is the preferential chemotherapeutic drug for highly prevalent solid tumours. However, its clinical efficacy is frequently limited due to neurotoxic effects such as peripheral neuropathy. Chemotherapy-induced peripheral neuropathy is a dose-dependent adverse condition that negatively impacts quality of life, and it may determine dosage limitations or even cancer treatment cessation. Thus, it is urgently necessary to identify pathophysiological mechanisms underlying these painful symptoms. As kinins and their B1 and B2 receptors contribute to the development of chronic painful conditions, including those induced by chemotherapy, the contribution of these receptors to cisplatin-induced peripheral neuropathy was evaluated via pharmacological antagonism and genetic manipulation in male Swiss mice. Cisplatin causes painful symptoms and impaired working and spatial memory. Kinin B1 (DALBK) and B2 (Icatibant) receptor antagonists attenuated some painful parameters. Local administration of kinin B1 and B2 receptor agonists (in sub-nociceptive doses) intensified the cisplatin-induced mechanical nociception attenuated by DALBK and Icatibant, respectively. In addition, antisense oligonucleotides to kinin B1 and B2 receptors reduced cisplatin-induced mechanical allodynia. Thus, kinin B1 and B2 receptors appear to be potential targets for the treatment of cisplatin-induced painful symptoms and may improve patients’ adherence to treatment and their quality of life. ## 1. Introduction Cancer incidence is increasing yearly, with an expected expansion rate of approximately $50\%$ by 2040 [1]. Concomitantly, remarkable improvements in the survival rates of cancer patients have been observed due to advances in early detection and available treatments [2,3,4]. With the increasing number of cancer survivors, more attention must be given to the potential risk of developing severe adverse effects associated with therapy, such as chemotherapy-induced peripheral neuropathy (CIPN) [3,5,6]. CIPN is the most frequent and potentially permanent neurological complication of cancer treatment [5,7,8]. Platinum-based chemotherapeutics, such as cisplatin, are associated with a high incidence of CIPN and may affect up to $85\%$ of treated patients [5,7,8,9,10,11]. Cisplatin treats highly prevalent tumours such as those of bladder, ovarian, testicular, lung, and head and neck cancers, as well as sarcomas [12]. However, cisplatin accumulation in the dorsal root ganglia neurons causes neuronal dysfunction and apoptosis, often resulting in irreversible changes in the peripheral nervous system, leading to peripheral neuropathy [7,9,13]. The incidence and severity of cisplatin-induced peripheral neuropathy are dose-dependent, and the symptoms appear during or after treatment [6,7,8]. Consequently, this condition can lead to dose reduction and treatment discontinuation, affecting overall patient survival [6,8,9,14]. Clinically, CIPN sensory symptoms are predominant in patients and can persist for months after completion of chemotherapy [7,8,14,15]. They usually develop first in the feet and hands; however, prolonged treatment may aggravate the signs and symptoms and extend to more proximal limb areas [6,8,9,16]. Patient symptoms manifest as spontaneous or evoked abnormal sensations such as paraesthesia, dysesthesias, numbness, and tingling. In addition, neuropathic-like painful sensations are frequently reported, such as mechanical or thermal allodynia or hyperalgesia, burning pain, and shooting or electric shock-like pain [6,8,16]. An essential aspect of platinum-based CIPN is the “coasting” phenomenon, whereby the signs and symptoms may worsen months after the discontinuation of chemotherapy [9,12,16]. Currently, there are no preventive strategies to attenuate this painful condition, and treatment is limited and commonly ineffective in many patients [14,15]. Although various pharmacologic agents have been evaluated for the treatment of CIPN, only duloxetine has been moderately recommended by the American Society of Clinical Oncology [14,15]. Given the limited treatment options for CIPN, it is necessary to identify efficacious and well-tolerated novel pharmacological strategies for CIPN symptoms without affecting cancer treatment regimens. In this sense, kinin B1 and B2 receptors activated by kinins have attracted attention due to their involvement in nociceptive processes and different painful conditions [17,18,19,20,21,22,23]. Bradykinin (Bk) and kallidin target the B2 receptor, while the B1 receptor has a higher affinity for the active metabolites of kinins, namely des-Arg9-Bk (DABk) and des-Arg10-kallidin. Nociceptive neurons express kinin B1 and B2 receptors [21,24,25,26], which, when activated, cause painful nociceptive responses in humans and experimental animals [20,27,28,29]. Kinin B1 and B2 receptors mediate the acute and chronic pain induced by various pain models [17,18,20,21,22,23,30], including chemotherapy drugs such as paclitaxel and vincristine [27,31,32,33]. Furthermore, kinin B1 and B2 receptors are involved in cisplatin-induced nephrotoxicity since the pharmacological blockade and knockout animals of kinin receptors attenuate acute kidney injury [34,35]. Due to the significant implications for cancer survivors, it is important to gain an understanding of the principal pathophysiological mechanisms involved in chemotherapy-induced painful symptoms to aid in the search for potential therapies to prevent or minimize these pain symptoms. In this respect, using a model of cisplatin-induced painful neuropathy in mice, we evaluated the involvement of the kinin B1 and B2 receptors in the pain symptoms induced by cisplatin. ## 2.1. Drugs and Reagents Cisplatin (cis-diamminedichloridoplatinum II, C-Platin®; Blau, SP, Brazil), bradykinin (Bk; kinin B2 receptor agonist), Icatibant (peptide kinin B2 receptor antagonist), des-Arg9-bradykinin (DABk; kinin B1 receptor agonist), and des-Arg9-[Leu8]-bradykinin (DALBK; peptide kinin B1 receptor antagonist) were purchased from Sigma Chemical Company (St. Louis, MO, USA). FR173657 (non-peptide kinin B2 receptor antagonist) and SSR240612 (non-peptide kinin B1 receptor antagonist) were obtained from Sanofi-Aventis (Berlin, Germany). Antisense oligonucleotides targeting the kinin B1 receptor (5′-AGG TTC CTG TGG ATG GCG TCCC-3′), kinin B2 receptor (5′-AGA ATT CTG TTC ACT GTT TCT TCC CTG-3′), and nonsense oligonucleotides (5′-GGT GGA T TTG AGG ATT TCG GC-3′) were acquired from GenOne Biotechnologies (Rio de Janeiro, Brazil). Cisplatin and antagonists were prepared in a saline solution ($0.9\%$). Phosphate-buffered saline (PBS; 10 mM) was used to dilute reagents administered via the intraplantar route (kinin B1 and B2 receptor agonists). The control groups (vehicles) received the vehicles where the treatments were solubilized. All the intraperitoneal treatments were administered in mice in a volume of 10 mL/kg, while intraplantar injections were administered in a volume of 20 µL. ## 2.2. Animals The experiments were conducted using adult male Swiss mice (25–30 g; 4–5 weeks of age) produced and provided by the Federal University of Santa Maria. The animals were maintained in a temperature-controlled room (22 ± 1 °C) under a 12 h light/12 h dark cycle with free access to food and water. Experimental protocols were performed with the approval of the Institutional Animal Care and Use Committee of the Federal University of Santa Maria (approval processes #$\frac{7152261119}{2020}$ and #$\frac{6380261021}{2022}$). Experimental protocols were conducted according to the guidelines for investigation of experimental pain in conscious animals [36,37], the Animal Research: Reporting in vivo Experiments ARRIVE guidelines [38], and national and international legislation (guidelines of the Brazilian Council of Animal Experimentation Control (CONCEA) and the U.S. Public Health Service’s Policy on Humane Care and Use of Laboratory Animals (PHS policy)). The number of animals and the intensities of noxious stimuli used were the minimum necessary to demonstrate the consistent effects of the treatments. Behavioural experiments were conducted in a quiet, temperature-controlled room (20 °C to 22 °C) between 9 a.m. and 5 p.m. and were performed by investigators blinded to the treatment conditions. The group size for each experiment was based on studies with protocols similar to ours [27,39,40], which were confirmed by power calculations (GPower version 3.1.9.7). ## 2.3. Cisplatin-Induced Peripheral Neuropathy Model To establish the cisplatin-induced peripheral neuropathy model, the mice were treated with intraperitoneal (i.p.) injections of cisplatin at a dose of 2.3 mg/kg administered every 48 h for 10 days (days 0, 2, 4, 6, 8, and 10), totalling 6 doses of cisplatin [41,42]. The control group received the vehicle (10 mL/kg, i.p.; saline solution [$0.9\%$]), employing the same administration schedule. Mannitol (125 mg/kg, intraperitoneal) was administered 1 h before cisplatin to avoid renal toxicity [43]. After the first cisplatin or vehicle injection, the animals were subjected to behavioural assessments. The experimental design is represented in Figure 1A. ## 2.4. Study Design for Behavioural Assessment Mechanical paw withdrawal threshold (PWT) and cold sensitivity were evaluated before the cisplatin administration protocol (baseline, B1). Next, the mice received vehicle (control group; 10 mL/kg, i.p.) or cisplatin (2.3 mg/kg, i.p.). The PWT was continuously assessed 24 h after each cisplatin or vehicle administration up to 30 days after the first administration [following the protocol described below (2.6.1 Mechanical allodynia* assessment)]. Cold sensitivity was evaluated on days 5, 11, 18, and 25 after the first cisplatin or vehicle administration [following the protocol described below (2.6.2 Cold sensitivity)]. The locomotor activity of the animals was evaluated in an open field on the 11th and 30th days after the first administration of cisplatin or vehicle [following the protocol described below (2.7.2 Locomotor Activity)]. Spontaneous pain was assessed by the voluntary wheel activity and nesting behaviour [following the protocols described below (2.6.3 Voluntary wheel activity and 2.6.4 Nesting behaviour test)]. Anxiety and depressive-like behaviours, as well as cognitive function, were assessed by thigmotaxis behaviour and a forced swimming test, as well as a novel object/place recognition test, respectively [following the protocols described below (2.6.5 Thigmotaxis behaviour, 2.6.6 Forced swimming test, and 2.6.7 Novel object place recognition test)]. ## 2.5. Study Design for the Assessment of Kinin B1 and B2 Receptor Involvement in Cisplatin-Induced Painful Behaviours A therapeutic and preventive protocol using kinin B1 and B2 receptor antagonists was performed to evaluate their contribution to the mechanical and cold painful hypersensitivity induced by cisplatin. Agonists and antisense oligonucleotides for the kinin B1 and B2 receptors were also used. ## 2.5.1. Therapeutic Protocol The therapeutic protocol was designed to evaluate the effect of kinin B1 and B2 receptor antagonists in mice with mechanical and cold allodynia previously established by cisplatin. The mechanical PWT and cold sensitivity of animals were measured before the cisplatin (2.3 mg/kg, i.p.) administrations (baseline values; B1) and 24 h after the last injection (11th day) (baseline values; B2). Next, the mice received a single intraperitoneal (i.p.) administration of the peptide kinin B1 or B2 receptor antagonist, i.e., DALBK (150 nmol/kg, i.p.) or Icatibant (100 nmol/kg, i.p.), respectively. The mechanical PWT and cold sensitivity were evaluated at different time points following the treatments (from 0.5 h up to 4 h). The mechanical PWT and cold sensitivity were also evaluated after treatments (from 0.5 to 24 h) with non-peptide kinin B1 (SSR240612, 150 nmol/kg, i.p.) or B2 (FR173657; 100 nmol/kg, i.p.) receptor antagonists. The experimental design is represented in Figure 3A. ## 2.5.2. Preventive Protocol The preventive protocol was delineated to evaluate the capacity of the kinin B1 and B2 receptor antagonists to prevent the development of cisplatin-induced mechanical allodynia and cold sensitivity. Mechanical PWT and cold sensitivity were measured before cisplatin and treatments (baseline values; B1). After baseline measurements, the mice were treated concomitantly every 48 h for 10 days with cisplatin (2.3 mg/kg, i.p.) + vehicle (10 mL/kg, i.p.), cisplatin (2.3 mg/kg, i.p.) + kinin B1 receptor antagonist (DALBK, 150 nmol/kg, i.p.), or cisplatin (2.3 mg/kg, i.p.) + kinin B2 receptor antagonist (Icatibant, 100 nmol/kg, i.p.). Mechanical PWT and cold sensitivity were assessed 24 h after each administration up to 14 days after the first cisplatin administration. The experimental design is represented in Figure 4A. ## 2.5.3. Effects of Sub-Nociceptive Doses of Kinin B1 and B2 Receptor Agonists on Mechanical Allodynia in Mice with Cisplatin-Induced Peripheral Neuropathy We examined whether low doses of kinin B1 and B2 receptor agonists could enhance the mechanical nociception of cisplatin-treated mice. The animals were previously treated with cisplatin (2.3 mg/kg, i.p.) or vehicle (10 mL/kg, i.p.). Twenty-four hours after the last cisplatin administration (11th day), the animals received an intraplantar (i.pl.) injection of DABk (3 nmol/paw, kinin B1 receptor agonist) or Bk (1 nmol/paw, kinin B2 receptor agonist), all in sub-nociceptive doses, or their vehicles (20 µL PBS/paw, i.pl.), and the mechanical PWT was evaluated again from 0.5 up to 3 h and from 0.5 up to 2 h after the agonist injections, respectively. The experimental design is represented in Figure 5A. To confirm the involvement of kinin B1 and B2 receptors in mechanical allodynia, the mice were treated with DALBK (150 nmol/kg, i.p.) or Icatibant (100 nmol/kg, i.p.) 24 h after the last cisplatin dose (11th day). After 0.5 h, the same animals were treated with sub-nociceptive doses of the respective kinin B1 and B2 receptor agonists—DABk or Bk—by the intraplantar route. Next, the PWT was assessed until treatments with the antagonists showed an effect. The experimental design is represented in Figure 6A. ## 2.5.4. Effects of Antisense Oligonucleotides for Kinin B1 and B2 Receptors on Cisplatin-Induced Mechanical and Cold Sensitivity in Mice To confirm the contribution of kinin B1 and B2 receptors to cisplatin-induced painful behaviours, mice were treated with intrathecal injections of an antisense oligonucleotide for kinin B1 and B2 receptors or their control. First, baseline (B1) mechanical PWT and cold sensitivity were measured. Then, the animals were treated with 6 doses of cisplatin (2.3 mg/kg, i.p.). Twenty-four h after the last cisplatin administration (11th day), mechanical and cold sensitivity were evaluated again (baseline values; B2). Next, the animals were treated intrathecally (5 μL; between L5 and L6) twice a day ($\frac{12}{12}$ h) for three consecutive days with antisense oligonucleotides targeting the kinin B1 receptor (antisense B1; 5 μg/site) and the kinin B2 receptor (antisense B2; 5 μg/site) or the control oligonucleotide (nonsense, 5 μL/site) [18]. On the fourth day, the animals received one last administration of antisense or nonsense oligonucleotides 1 h before evaluating mechanical PWT and cold sensitivity. The experimental design is represented in Figure 7A. ## 2.6.1. Mechanical Allodynia Assessment Mechanical allodynia was assessed using flexible nylon filaments (von Frey) of increasing stiffness (0.02–10 g) by the up-and-down method [44,45]. The mechanical PWT response, expressed in grams (g), was calculated from the resulting scores using von Frey filaments, according to previous studies [23,27,45]. Mechanical allodynia was considered a decrease in the PWT compared with the baseline values (B1) before cisplatin administration. ## 2.6.2. Cold Sensitivity Cold sensitivity was assessed with the acetone drop method as previously described [23,46]. The mice were placed on a wire mesh floor, and a drop of acetone (20 µL) was applied three times on the plantar surface of the right hind paw. The behavioural response was analysed for 30 s and recorded in scores. The scores were: 0 = no response; 1 = quick withdrawal, flick, or stamp the paw; 2 = prolonged withdrawal or repeated paw flicking; and 3 = repeated paw flicking with licking directed at the ventral side of the paw. The sum of the three scores was used for data analysis. Cold sensitivity was considered an increase in the scores compared with the baseline values before cisplatin administration. ## 2.6.3. Voluntary Wheel Activity The running activity is a simple, observer-independent objective measure and provides a measure of spontaneous activity in a known environment, potentially reflecting whether the activity is painful [47]. The voluntary wheel activity was assessed in polycarbonate cages with free access to stainless steel activity wheels (Wheel activity EP 172—Insight, Ribeirão Preto, SP, Brazil). The wheel could be turned in either direction. The wheels were connected to a digit counter that automatically recorded the number of turns. First, mice were habituated in individual activity cages for three sessions over at least three days. The distance travelled by each animal on the wheel during each 1 h evaluation session was obtained by multiplying the number of turns by the wheel diameter (30 cm). The mice that refused to run on the wheels during the baseline measurement (travelled a distance <150 m) were excluded from further evaluation [47]. ## 2.6.4. Nesting Behaviour Test Nesting is an innate behaviour in mice that may be sensitive to pain conditions [48]. Mice were habituated to the nesting cage for 48 h before testing. As nesting material, one 5 × 5 cm2 nestlet consisting of pressed virgin cotton was cut into six roughly equal pieces (~1.7 × 2.5 cm2). The nest pieces were evenly placed in the four corners and the middle of each long side of the cage (49 × 34 × 16 cm2), and the cage space was divided into six equal zones for nesting assessment. The nesting quality score ranged from 0.5 to 6 points and was measured as follows: 0.5 points were assigned to the mouse if it cleared one zone, and 0.5 points were assigned if the mouse shredded the nestlet. The nesting score ranged from 0.5 to 6 points. The nesting behaviour was scored after 120 min of exposure to the initial nesting material [48,49]. A decrease in the nesting score indicates pain-depressed nesting behaviour, suggesting one useful spontaneous nociception behaviour. ## 2.6.5. Thigmotaxis Behaviour Thigmotaxis behaviour was evaluated using an open field (40 cm × 30 cm × 18 cm) with a delimited inner zone (12 × 12 cm). Each mouse was transferred to the apparatus and observed for 15 min [46,50]. The number of entries into the inner zone and the total immobility time were analysed by ANY-maze Software (7.0 version, Stoelting Co., Wood Dale, IL, USA). Thigmotaxis behaviour corresponds to a decreased exploration of the inner zone of the open field and indicates anxiety-like behaviour [50]. ## 2.6.6. Forced Swimming Test Forced swimming is a commonly used assay to study depressive-like behaviour in rodents [51]. The forced swimming test was performed using a cylinder (20 cm diameter and 45 cm height) filled with water (23–25 °C) at a height of 30 cm. Mice were placed in the water, and the time for which the mice remained immobile was quantified in seconds over a period of 2–6 min using a chronometer [46,50]. Immobility was defined as the absence of all movements except those required to maintain the head above water. ## 2.6.7. Novel Object/Place Recognition Test To assess cognitive function, we subjected mice to a novel object/place recognition test (NOPRT). NOPRT measures the spatial and working memory of mice using the innate preference of mice for novelty [52,53] and was performed as previously described [52,54]. One day after administration of the last dose of cisplatin, mice were habituated to the test arena (40 cm × 30 cm × 18 cm), with two identical objects placed on the same side of the arena for 5 min (training phase), after which the mouse was returned to its home cage. Thirty minutes later, the mice were transferred back to the arena, which now contained one familiar object placed at the same location as in training and one novel object placed on the opposite end of the arena (testing phase), and they were allowed to explore for another 5 min. Sniffing, climbing, and touching the objects were regarded as exploration behaviour. The exploration time of the familiar and novel object was scored manually. The discrimination index was determined as [time with the novel object − time with the familiar object]/total exploration time of both objects. ## 2.7.1. Physical and Behavioural Changes Physical (body weight verified through a scale and hair appearance) and behavioural (irritability, salivation, and tremors) changes were visually evaluated before and throughout the experimental period (during and after cisplatin administration) by the experimenter. ## 2.7.2. Locomotor Activity We assessed the effect of cisplatin on the locomotor activity of animals one day after the last cisplatin (2.3 mg/kg, i.p.) or vehicle (control group; 10 mL/kg, i.p.) administration (11th day). The spontaneous locomotor activity was recorded for 15 min in an open-field apparatus (40 cm × 30 cm × 18 cm), and the results of the total distance travelled were obtained by automated analysis ANY-maze™ software (7.0 version, Stoelting Co., Wood Dale, IL, US). The spontaneous locomotor activity was also evaluated on the 30th day after the first cisplatin or vehicle administration by an open-field test [55]. The open-field apparatus consists of a glass box (28 × 18 × 12 cm) divided into nine squares. On the 30th day after the first cisplatin or vehicle administration, each mouse was placed in the apparatus, and the number of squares crossed with all paws and rearing was counted in a 5 min session. The forced locomotor activity was evaluated using the rotarod test. Before the first cisplatin or vehicle dose, all the animals were trained in the rotarod (3.7 cm in diameter, 8 rpm) until they could remain in the apparatus for 60 s without falling. On the 30th day after the first cisplatin (2.3 mg/kg, i.p.) or vehicle (control group; 10 mL/kg, i.p.) dose, the number of falls from the apparatus was recorded for up to 240 s [55]. ## 2.7.3. Biochemical Analysis The mice received the cisplatin (2.3 mg/kg, i.p.) or vehicle (10 mL/kg, i.p.) administrations. On the 30th day after the first cisplatin dose, they were deeply anaesthetized, and blood was collected by heart puncture. The obtained serum was used for a biochemical assay to assess serum urea nitrogen and serum creatinine levels, as well as the activities of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) enzymes. ## 2.8. Statistical Analysis Statistical analyses were performed using Graph Pad Prism 8.0 software (Graph Pad, San Diego, CA, USA). Results were expressed as the mean ± standard error of the mean (SEM). The significance of differences between groups was evaluated with a Student’s t-test and one-way or two-way analysis of variance (ANOVA) followed by Bonferroni’s post hoc test. To meet the parametric assumptions, the data on the mechanical threshold were log-transformed before analyses. The nesting test scores are reported as medians followed by their 25th and 75th percentiles (interquartile range). The percentages of maximum effect were calculated for the maximal developed responses compared to baseline values or the control group. p-values less than 0.05 ($p \leq 0.05$) were considered statistically significant. ## 3.1. Cisplatin Induces Prolonged Painful Peripheral Neuropathy in Mice First, we explored whether the treatment regimen used to induce the peripheral neuropathy model (Figure 1A) causes mechanical allodynia and cold sensitivity. Cisplatin reduced the mechanical PWT of mice from the third cisplatin dose (5th day) until 30 days after the first cisplatin administration, indicating the development of mechanical allodynia (Figure 1B). A PWT reduction of 72 ± $7\%$ was observed on the 11th day after the first cisplatin administration. Mice treated with cisplatin also developed cold sensitivity after the final dose of cisplatin (11th day) compared to the vehicle group (Figure 1C), which remained until the 18th day. Thus, the 11th day after the first cisplatin administration was chosen for subsequent experiments. Measurements of spontaneous pain were performed one day after the last cisplatin dose. Cisplatin partially decreased the distance travelled in the voluntary activity in the wheel test (Figure 2A) and reduced nesting behaviour compared to the vehicle group (Figure 2B). Mice treated with cisplatin showed a decreased preference for the novel object when compared to vehicle-treated mice, indicating impairment in cognitive function (Figure 2C). No differences were observed in the total time the animals interacted with objects, indicating that the decreased discrimination index of cisplatin-treated mice was not due to reduced interest (Figure 2D). Moreover, cisplatin did not cause anxiety and depressive-like behaviour, as evaluated by the number of entries to the inner zone and total immobility time in the open-field apparatus, and it did not increase the immobility time in the forced swimming test (Table S1). Furthermore, cisplatin neither changed the body weight (Table S2) nor caused behavioural alterations (e.g., irritability, salivation, or tremors) compared with the vehicle group. Cisplatin treatment also did not affect the locomotor function of mice, as demonstrated by the total distance travelled (m) in the open-field apparatus on the 11th day (Table S2). In addition, cisplatin treatment affected neither the mice’s spontaneous locomotor function evaluated on the 30th day, as demonstrated by crossing and rearing numbers (Table S2), nor the forced locomotor activity, as shown by the mice’s number of falls in the rotarod test (Table S2). The treatment with cisplatin that induced peripheral neuropathy did not cause changes in the urea and creatinine levels or ALT and AST enzyme activities (Table S3). ## 3.2. Kinin B1 and B2 Receptors Contribute to Mechanical Allodynia in Cisplatin-Induced Peripheral Neuropathy in Mice First, utilizing a therapeutic protocol, we evaluated whether pharmacological blockade using the kinin B1 and B2 receptor antagonists reduces the cisplatin-induced mechanical allodynia (Figure 3A). The peptide antagonists for kinin B1 (DALBK, 150 nmol/kg, i.p.) and B2 (Icatibant, 100 nmol/kg, i.p.) receptors reduced cisplatin-induced mechanical allodynia from 0.5 up to 2 h after their administration (Figure 3B), with reductions of 52 ± $7\%$ and 57 ± $5\%$ at 2 h after treatments, respectively. Similar effects were observed for non-peptide kinin B1 and B2 receptor antagonists. Non-peptide antagonists for kinin B1 (SSR240612, 150 nmol/kg, i.p.) and B2 (FR173657, 100 nmol/kg, i.p.) receptors decreased the cisplatin-induced mechanical allodynia from 0.5 up to 4 h (reduction of 31 ± $8\%$ at 0.5 h) and from 0.5 up to 6 h (reduction of 34 ± $9\%$ at 2 h) after their treatments (Figure 3C), respectively. Peptide and non-peptide antagonists for kinin B1 or B2 receptors failed to reduce cisplatin-induced cold sensitivity. Next, we assessed the effect of peptide antagonists for kinin B1 and B2 receptors in preventing the mechanical allodynia development induced by cisplatin (Figure 4A). DALBK (150 nmol/kg, i.p.) effectively prevented mechanical allodynia development when administered concomitantly with cisplatin until the 12th day, with prevention of 55 ± $21\%$ on the 5th day after the first treatment. Similarly, Icatibant (100 nmol/kg, i.p.) also prevented mechanical allodynia development when administered concomitantly with cisplatin until the 11th day after the first treatment, with prevention of 43 ± $16\%$ on the 5th day (Figure 4B). Peptide kinin B1 or B2 receptor antagonists did not prevent cisplatin-induced cold sensitivity. ## 3.3. Kinin B1 and B2 Receptor Agonists Enhanced Cisplatin-Induced Mechanical Nociception, Which Was Reversed by B1 and B2 Receptor Antagonists First, we evaluated whether low doses of kinin B1 and B2 receptor agonists could enhance cisplatin-induced nociceptive behaviour (Figure 5A). Intraplantar (i.pl.) DABk (3 nmol/paw; a sub-nociceptive dose of kinin B1 receptor agonist) enhanced cisplatin-induced mechanical nociception 2 h after its administration when compared to the cisplatin plus vehicle group (Figure 5B). Likewise, i.pl. Bk (1 nmol/paw; a sub-nociceptive dose of kinin B2 receptor agonist) enhanced cisplatin-induced mechanical nociception 1 h after its administration when compared to the cisplatin plus vehicle group (Figure 5C). As expected, sub-nociceptive doses of the Bk and DABk agonists did not alter the mechanical sensitivity in animals previously treated with vehicle (Figure 5B,C). Since low doses of kinin B1 and B2 receptor agonists intensified the cisplatin-induced mechanical nociception, we evaluated whether kinin receptor antagonists prevented this behaviour (Figure 6A). The kinin B1 receptor antagonist DALBK (150 nmol/kg, i.p., 0.5 h prior agonist injection) prevented the enhancement of mechanical nociception, with an effect of 31 ± 4 % 2 h after its administration (Figure 6B). Icatibant (100 nmol/kg, i.p., 0.5 h prior to agonist injection), a kinin B2 receptor antagonist, markedly prevented the enhancement of mechanical nociception, with an effect of 75 ± $11\%$ at 1 h after its administration (Figure 6C). ## 3.4. Antisense Oligonucleotides for Kinin B1 or B2 Receptors Attenuated the Cisplatin-Induced Mechanical Allodynia To reinforce the involvement of kinin B1 and B2 receptors in cisplatin-induced mechanical allodynia, we silenced the gene expression of the kinin B1 or B2 receptor using antisense oligonucleotides (Figure 7A). Antisense oligonucleotides for kinin B1 and B2 receptors attenuated cisplatin-induced mechanical allodynia, with inhibition of 57 ± $8\%$ and 33 ± $7\%$, respectively (Figure 7B). On the other hand, control oligonucleotide injection (nonsense) did not affect the cisplatin-induced mechanical allodynia. Antisense oligonucleotides did not attenuate cisplatin-induced cold sensitivity. ## 4. Discussion Peripheral neuropathy is one of the most common adverse effects of platinum-based chemotherapy drugs such as cisplatin. CIPN considerably impacts cancer treatment strategies, leading to a dose reduction or treatment discontinuation and negatively affecting the patients’ quality of life [9,11,56]. The increasing number of cancer survivors and the lack of treatment to prevent or manage CIPN emphasizes the urgent need to unveil the pathophysiological mechanisms of CIPN to develop effective therapeutic strategies. This study provided the first evidence of the involvement of the kinin B1 and B2 receptors in cisplatin-induced painful peripheral neuropathy using pharmacological and genetic tools. Therefore, kinin receptors seem crucial to mediating mechanical nociception in cisplatin-induced peripheral neuropathy, suggesting that these receptors may also be critical in a clinical setting. Moreover, we demonstrated that kinin B1 and B2 receptor antagonists have therapeutic potential to relieve cisplatin-associated pain symptoms. Clinically, cisplatin dose is a determinant for peripheral neuropathy development [11,12,57,58]. CIPN commonly manifests as an increased perception of innocuous (allodynia) or noxious (hyperalgesia) stimuli, which are hallmark symptoms of neuropathic pain [6,8,56]. In the present study, cisplatin treatment resulted in prominent and persistent mechanical allodynia lasting at least 30 days. This result agrees with previous data demonstrating the development of mechanical allodynia after the third cisplatin dose in a different strain of mice [41,42,59]. Changes in peripheral sensory sensations concerning cold stimuli are commonly associated with neuronal toxicity caused by antineoplastic agents such as platinum-based agents [11,12,56]. Here, we observed that six doses of cisplatin increased cold sensitivity. Although our results are consistent with previous studies [60,61,62], the changes in thermal hypersensitivity (cold and heat) caused by cisplatin are controversial [56] and seem to be more associated with oxaliplatin use—another platinum-based agent. Since literature data demonstrate no differences in the onset or severity of CIPN between male and female mice, we evaluated the cisplatin effects only on male but not female mice [56,63,64,65]. In this study, we demonstrated that cisplatin treatment induced spontaneous pain-like behaviours. The reduction in the spontaneous wheel-running activity and nesting performance reflects depressed pain behaviours typical during painful conditions in rodents [47,48,66]. Reductions in these behaviours were previously described for different pain models [47,49,67]. Nonetheless, these are the first data showing the effects of cisplatin on nest building and wheel running, indicating spontaneous pain development, that is, pain in the absence of a stimulus. In addition to painful symptoms observed in CIPN, after undergoing cancer chemotherapy, patients also present a high risk of cognitive impairment—another neurotoxic condition of chemotherapy agents [53,68,69]. Chemotherapy-induced cognitive impairment, commonly known as chemobrain, consists of damage in several cognitive domains, including impairment in working memory, attention, processing speed, concentration, and executive function [54,68]. Cognitive dysfunction is also related to cisplatin treatment, as it crosses the blood–brain barrier in low concentrations [52,70]. In the present study, repeated cisplatin treatment caused a decreased preference for the novel object, indicating impaired working memory and spatial recognition [54]. These results corroborate previous data showing that cisplatin induces cognitive impairment [52,53,54]. Pain and humour disorders, such as depression, may develop secondarily to each other or may coexist. In general, depression may cause increased pain perception by patients who may be more likely to develop chronic pain [71]. Cancer patients undergoing chemotherapy treatment present symptoms of depression and anxiety, in addition to neuropathic pain symptoms [72,73]. In our study, cisplatin caused neuropathic pain symptoms but not depressive- and anxiety-like behaviours since it altered neither the mice’s immobility time in the forced swimming test nor thigmotaxis behaviour, unlike in other studies [74,75,76]. These discrepancies between the results may be due to the different administration schedules, doses of cisplatin, or differences between the animal strains tested [74,75,76]. Thus, it is important to better elucidate such conditions underlying chemotherapeutic treatment, as well as cognitive impairment and mood disorders, in experimental models, since they can influence or be influenced by chronic pain states [71,77]. The cisplatin dose used in this study promoted nociceptive responses without causing damage to the general health of the mice. On the other hand, higher doses of cisplatin result in weight loss accentuated after the second cisplatin administration [78]. Furthermore, cisplatin did not cause motor impairments, as evaluated by spontaneous and forced locomotor activity. The pathological mechanisms underlying CIPN development have been widely debated [9,11,64,65]. Potential targets that might be involved in cisplatin-induced painful peripheral neuropathy pathophysiology are the kinin B1 and B2 receptors, which are involved in various painful conditions, including those induced by other chemotherapy drugs [27,31,32,33,39]. Kinins (bradykinin and kallidin), as well as their active metabolites (des-Arg9-Bk and des-Arg10-kallidin), are endogenous peptides that mediate inflammatory and painful processes via the kinin B1 and B2 receptors, respectively [79,80]. In the present study, pharmacological antagonism and gene silencing using antisense oligonucleotides for the kinin receptors attenuated cisplatin-induced mechanical allodynia. These findings indicate that cisplatin can promote the painful symptom characteristic of CIPN in male mice in a kinin B1 and B2 receptor-dependent manner. Since no study has shown discrepant kinin receptor effects on painful conditions in male and female experimental animals, we evaluated the antinociceptive effect of kinin B1 and B2 receptor antagonists only in male mice. The systemic administration of peptide kinin B1 and B2 antagonists decreased mechanical allodynia in the therapeutic and preventive protocol. It is worth mentioning that nociceptive tests in the preventive protocol were carried out 24 h post administration of the antagonists, indicating a lasting effect of the peptide kinin B1 and B2 antagonists once efficacy was reached. In the therapeutic protocol, non-peptide kinin B1 and B2 receptor antagonists SSR240612 e FR173657 exerted a more prolonged antiallodynic effect than the peptide antagonists. Similarly, antinociceptive effects more prolonged from non-peptide antagonists than peptide antagonists were evidenced in a fibromyalgia model and paclitaxel-induced pain syndrome [23,27]. Notwithstanding the longer-lasting effect observed for non-peptide antagonists, the inhibition percentage of mechanical allodynia was similar to that caused by peptide antagonists. Therefore, their effects were not evaluated in the preventive protocol. The ability of kinin antagonists to attenuate cisplatin-induced mechanical allodynia can be explained by the constitutive expression of kinin B1 and B2 receptors in structures important for nociceptive transmission, such as nociceptive neurons, the dorsal root ganglion, and spinal cord [25,26,28,81]. Still, immune cells, such as monocytes, neutrophils, and microglia, also express kinin receptors [80,82]. In this sense, microglia activation on the spinal cord was previously demonstrated in the cisplatin-induced peripheral neuropathy model [83]. Therefore, our results agree with previous studies that have linked kinin receptors to the pathogenesis of different acute and chronic pain models, highlighting the role of these receptors in pain hypersensitivity following mechanical stimulus [18,19,21,22,23,84]. In particular, kinin receptors also contribute to mechanical hypersensitivity induced by chemotherapeutic agents such as paclitaxel and vincristine [27,31,33]. To contribute to our hypothesis that kinin B1 and B2 receptors mediate cisplatin-induced painful symptoms, mice previously treated with cisplatin received sub-nociceptive doses of kinin B1 and B2 receptor agonists. Local exposure to agonists of kinin receptors (at doses that generally do not cause nociception) is associated with more prolonged and intensified nociceptive behaviours [18,23]. Kinin B1 and B2 receptor agonists—DABK and Bk, respectively—enhanced cisplatin-induced mechanical nociception. Similarly, chronic pain studies have reported hypersensitivity to sub-nociceptive doses of kinin B1 and B2 agonists [18,23]. The respective antagonist reduced this increased nociceptive response, providing additional evidence of the involvement of kinin B1 and B2 receptors in cisplatin-induced pain hypersensitivity. The intrathecal administration of antisense oligonucleotides targeting kinin B1 and B2 receptors decreased cisplatin-induced mechanical allodynia. Our results are consistent with previous studies showing that genetic deletion of kinin receptors effectively reduces pain responses in different experimental models [18,85]. As mentioned before, in addition to their expression at the peripheral level, the kinin B1 and B2 receptors also are found or upregulated in the spinal cord, astrocytes, and microglia in the central nervous system, contributing to chronic pain states such as neuropathic pain [82,86,87]. This explains the ability of intrathecal antisense oligonucleotides targeting kinin B1 and B2 receptors to attenuate cisplatin-induced mechanical allodynia. Although kinin receptor antagonists and antisense oligonucleotides reduced cisplatin-induced mechanical allodynia, in our study, they did not reduce cold hypersensitivity. These results are in agreement with a study by Gonçalves et al. [ 2021], which disregards the involvement of kinin receptors in cold hypersensitivity. Unlike our findings, kinin receptor antagonists attenuated the cold sensitivity in a spinal nerve ligation and fibromyalgia model [22,23]. However, considering that TRPA1 is a harmful cold sensor and that the activation of B1 and B2 receptors causes sensitization of TRP channels, including TRPA1 [25,39,88,89,90,91,92], kinin receptors may be indirectly involved in cold hypersensitivity. Therefore, it is essential to better elucidate the mechanisms of cold allodynia in the cisplatin-induced neuropathy model and define the role of kinin receptors in this condition. In addition to neurotoxicity, cisplatin is also associated with nephrotoxic effects [6,8]. In this regard, cisplatin did not alter the urea and creatinine levels of animals in a previous study [93]. Interestingly, both kinin B1 and B2 receptors seem to be involved in cisplatin-induced nephrotoxicity once the deletion and blockage of kinin B1 and B2 receptors have been shown to protect against cisplatin-induced acute kidney injury [34,35]. Furthermore, Estrela et al. [ 2017] showed that the deletion and blockage of the kinin B1 receptor prevented the downregulation of organic transporters in kidney cisplatin-induced toxicity, increasing the cisplatin efflux and consequently protecting against cisplatin nephrotoxicity [94]. Thus, using kinin receptor antagonists to relieve painful symptoms could also help to protect against cisplatin-induced renal toxicity. Kinin antagonists might also present additional beneficial effects, such as avoiding cancer cell proliferation since kinin antagonists alone or in association with chemotherapeutics, including cisplatin, inhibit the growth of ovarian and lung tumour cells [95,96,97]. In general, an ideal therapeutic strategy should act synergistically, aiding in antitumour action and protecting against neurotoxic and nephrotoxic effects. Thus, our study and previous studies support the potential of kinin antagonists in these conditions induced by cisplatin and a possible synergistic effect on antitumour activity. Our findings show that the mechanisms mediated by kinin B1 and B2 receptors contribute to cisplatin-induced peripheral neuropathy symptoms, especially in mechanical nociception, indicating that kinin B1 and B2 receptors are potential pharmacological targets to relieve the pain symptoms associated with cisplatin. Furthermore, considering the safety and tolerability of the kinin B2 receptor antagonist, Icatibant, which has already been approved for treatment of hereditary angioedema [98], our data suggest a possible clinical repositioning of Icatibant for patients with cancer undergoing chemotherapy with cisplatin. 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--- title: Cornus officinalis Seed Extract Inhibits AIM2-Inflammasome Activation and Attenuates Imiquimod-Induced Psoriasis-like Skin Inflammation authors: - Se-Bin Lee - Ju-Hui Kang - Eun-Jung Sim - Ye-Rin Jung - Jeong-Hyeon Kim - Prima F. Hillman - Sang-Jip Nam - Tae-Bong Kang journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051512 doi: 10.3390/ijms24065653 license: CC BY 4.0 --- # Cornus officinalis Seed Extract Inhibits AIM2-Inflammasome Activation and Attenuates Imiquimod-Induced Psoriasis-like Skin Inflammation ## Abstract The AIM2 inflammasome is an innate immune system component that defends against cytosolic bacteria and DNA viruses, but its aberrant activation can lead to the progression of various inflammatory diseases, including psoriasis. However, there have been few reports of specific inhibitors of AIM2 inflammasome activation. In this study, we aimed to investigate the inhibitory activity of ethanolic extracts of seeds of Cornus officinalis (CO), a herb and food plant used in traditional medicine, on AIM2-inflammasome activation. We found that CO inhibited the release of IL-1β induced by dsDNA in both BMDMs and HaCaT cells, but that it showed no effect on the release of IL-1β induced by NLRP3 inflammasome triggers, such as nigericin and silica, or the NLRC4 inflammasome trigger flagellin. Furthermore, we demonstrated that CO inhibited the cleavage of caspase-1, an inflammasome activation marker, and an upstream event, the translocation and speck formation of ASC. In addition, further experiments and mechanistic investigations revealed that CO can inhibit AIM2 speck formation induced by dsDNA in AIM2-overexpressing HEK293T cells. To verify the correlation in vivo, we investigated the efficacy of CO in an imiquimod (IMQ)-induced psoriasis model, which has reported associations with the AIM2 inflammasome. We found that topical application of CO alleviated psoriasis-like symptoms, such as erythema, scaling, and epidermal thickening, in a dose-dependent manner. Moreover, CO also significantly decreased IMQ-induced expression of AIM2 inflammasome components, including AIM2, ASC, and caspase-1, and led to the elevation of serum IL-17A. In conclusion, our results suggest that CO may be a valuable candidate for the discovery of AIM2 inhibitors and the regulation of AIM2-related diseases. ## 1. Introduction Inflammasomes are multiprotein complexes in cytosol that defend against various pathogens [1]. The complexes are composed of sensors that detect pathogens, an inflammatory enzyme called capase-1, and, in some cases, an adaptor molecule called ASC [2,3]. Several sensors have been identified, including members of the pyrin domain-containing NLR family (NLRP1 and NLRP3), absent in melanoma 2 (AIM2), the NLR family apoptosis inhibitory protein (NAIP)/NLR family, and caspase activation and recruitment domain (CARD) containing 4 (NLRC4), which have been widely studied [4]. When triggers from pathogens bind to these sensors, protein complexes are formed, which activate caspase-1 through autocleavage [5,6]. The activated caspase-1 cleaves pro-inflammatory cytokines, such as pro-IL-1β and pro-IL-18, converting them into their bioactive forms, which induce inflammation [7]. However, inflammasome activation can occur in the absence of infection, leading to unnecessary and prolonged inflammatory responses that may contribute to the progression of various inflammatory diseases [8,9]. Therefore, there have been many efforts to identify compounds that can regulate inflammasome activation from various sources, such as chemical libraries and medicinal plants, and these efforts have been particularly focused on NLRP3 inhibitors, which are known to have significant associations with several metabolic diseases, such as gout, diabetes, and cardiovascular disease [10,11,12]. AIM2 is a cytosolic sensor that activates inflammasomes upon recognizing dsDNA derived from viruses and bacteria [13,14,15,16]. However, it also responds to dsDNA from damaged self-cells and tissues, leading to unnecessary inflammatory responses that contribute to the progression of diseases, such as psoriasis, cancer, and atherosclerosis [17,18,19,20,21,22]. Therefore, this study investigated the inhibitory effects of plant extracts that have been used in traditional medicine on AIM2 inflammasomes and identified that the extract of Cornus officinalis seed has an inhibitory effect on AIM2 inflammasomes. Cornus officinalis is a flowering plant species of the dogwood family that is used in traditional medicine and as a food source in East Asia [23]. Previous studies have reported various biological activities of Cornus officinalis, such as anti-inflammatory, antioxidant, and neuroprotective effects, but its potential as an inflammasome inhibitor has not yet been explored [24,25,26,27,28]. We examined the inhibitory effects of Cornus officinalis seed extracts on AIM2 inflammasomes and its mechanisms of action within cells, as well as its in vivo efficacy in an imiquimod-induced psoriasis model. ## 2.1. Identification of Compounds of CO in LC-MS Fingerprinting The presence of seven compounds in CO were determined from the interpretation of LC-MS and NMR spectroscopic data. Sarracenin, plicosepalin A, loganin, (−)-epicatechin-3-O-gallate, and oenothein C were identified from the comparison of the mass data of five compounds with previously reported ones (Figure S1) [29,30]. Meanwhile, HPLC-UV-guided isolation of CO yielded a compound, and the chemical structure was identified as ellagic acid by comparing NMR, MS, and UV spectral data (Figures S2–S4). In addition, methyl gallate was identified from the comparison of retention time and mass data with the standard (Figure S5). However, the major peaks (A and B) shown in the LC-MS were not able to be identified because they easily decomposed during the isolation (Figure 1). ## 2.2. CO Inhibits the Release of IL-1β and Cell Death of Macrophages Induced by Intracellular Poly(dA:dT) A screening study of 110 plant extracts, which are traditionally known to show anti-inflammatory activities, found that the seed extract of Cornus officinalis (CO) has an inhibitory effect on AIM2-inflammasome activation. Therefore, follow-up studies were carried out to verify its activity. The non-cytotoxic concentration of CO was determined through MTT and LDH assays performed on mouse bone-marrow-derived macrophages (BMDMs). The results show that CO is not toxic up to 10 μg/mL (Figure 2A,B); thus, this concentration was used for subsequent experiments. Since the release of cleaved IL-1β into culture supernatants and pyroptotic cell death are hallmarks of inflammasome activation [31], we assessed whether CO could inhibit IL-1β release and cell death of BMDMs stimulated with various stimuli. The results showed that CO inhibited the release of IL-1β and cell death in a dose-dependent manner in response to poly(dA:dT) stimulation but that it had a mild inhibitory effect on ATP-induced IL-1β release and cell death (Figure 2C,D). However, CO had no effect on inflammasome activation triggered by nigericin, silica, LPS transfection, or flagellin (Figure 2E–H). These results indicate that CO preferentially inhibits AIM2 inflammasome activation triggered by poly(dA:dT) and that there was a mild or lack of effect on inflammasome activation of other types of inflammasome, such as NLRP3 and NLRC4 stimuli. ## 2.3. CO Suppresses the Release of Cleaved IL-1β through the Inhibition of Caspase-1 Activation The transcriptional upregulation of inflammasome components and the activation of pro-caspase-1 are considered upstream signals that lead to the maturation of pro-IL-1β in the inflammasome activation pathway [32]. To investigate the effect of CO on the expression of inflammasome components and on caspase-1 activation, we examined their levels in LPS-primed mouse bone-marrow-derived macrophages (BMDMs) upon stimulation with poly(dA:dT), nigericin, or flagellin in the presence or absence of CO. Western blotting was used to analyze the expression of AIM2, NLRP3, and NLRC4 inflammasome components. The results show that CO had no effect on the expression of these components (Figure 3A,B). Nevertheless, CO treatment significantly decreased the activation of capase-1 and the cleavage of its substrates, pro-IL-1β and gasdermin-D (GSDMD), in poly(dA:dT)-treated BMDMs (Figure 3A). These findings suggest that inhibitory effects of CO on AIM2 inflammasome activation are not due to changes in the transcript-expression levels of inflammasome components but, rather, the inhibition of caspase-1 activation. ## 2.4. CO Inhibits AIM2 Inflammasome Activation via the Suppression of ASC Speck Formation To elucidate the mechanism by which CO inhibits AIM2 inflammasome activation, we examined the response of key steps in the AIM2 inflammasome signaling pathway. The adaptor protein ASC plays a critical role in inflammasome activation by physically linking sensors and caspase-1 [33]. Upon activation, ASC translocates into a Triton X-100 insoluble fraction, where it undergoes oligomerization and forms a multiprotein complex known as ASC speck [16,34,35]. Therefore, we investigated whether CO could inhibit these ASC changes in LPS-primed mouse bone-marrow-derived macrophages (BMDMs) treated with poly(dA:dT) in the presence or absence of CO. The results show that CO inhibited ASC translocation in a dose-dependent manner (Figure 4A). Furthermore, CO suppressed the ASC oligomerization and speck formation induced by poly(dA:dT) (Figure 4B–D). These findings suggest that CO inhibits AIM2 inflammasome activation by targeting the upstream events of ASC translocation and oligomerization, which subsequently results in the inhibition of caspase-1 activation. ## 2.5. CO Inhibits AIM2 Speck Formation The binding of AIM2 with dsDNA induces AIM2 oligomerization and speck formation, which is crucial for AIM2 inflammasome complex formation [33,36]. To investigate the effect of CO on AIM2 speck formation, AIM2-overexpressing HEK293T cells were treated with poly(dA:dT) to induce AIM2 speck formation in the presence or absence of CO. The cells were then analyzed by immunocytochemistry, and the results showed that CO significantly decreased poly(dA:dT)-induced AIM2 speck formation (Figure 5A,B). These data suggest that CO inhibits AIM2 inflammasome activation through the inhibition of AIM2 speck formation. ## 2.6. CO Inhibits AIM2-Mediated IL-1β Release from HaCaT Cells and Attenuates IMQ-Induced Psoriasis-Like Skin Pathology To determine whether CO also affects inflammasome activation in other cell types beyond BMDMs, its activity was tested in human keratinocyte cells (HaCaTs), which are known to express AIM2 and release IL-1β upon stimulation with double-stranded DNA (dsDNA) [37]. To ensure that it did not impact cell viability (Figure 6A), a concentration of less than 10 μg/mL of CO was applied in the subsequent experiments with HaCaT cells. HaCaT cells were first treated with IFN-γ and TNF-α, then stimulated with poly(dA:dT) transfection to induce AIM2 inflammasome activation [37,38]. In accordance with the results observed in BMDMs, CO also inhibited the poly(dA:dT)-induced secretion of IL-1β in HaCaT cells (Figure 6B). Prior studies showed that excessive cytosolic DNA can trigger AIM2 inflammasome activation in keratinocytes in psoriatic lesions and contribute to the progression of psoriasis [21,38]. Therefore, to investigate whether CO treatment could reduce psoriatic-like skin inflammation, mice were pre-treated with CO or a vehicle and then exposed to Aldara cream containing $5\%$ imiquimod for 8 consecutive days to induce psoriasis (Figure 6C) [39]. Mice treated with the vehicle showed typical signs of skin inflammation, including erythema, scaling, and thickening of the back skin and ears (Figure 6D–G). However, CO treatment reduced the severity of the skin lesions in a dose-dependent manner and also reduced body weight loss and ear swelling caused by the Aldara cream (Figure 6D–F). The psoriasis area and severity index (PASI) scores showed that CO significantly reduced the erythema, scaling, and thickness (Figure 6G). Finally, the histological analysis showed that CO treatment also reduced parakeratosis, hyperpigmentation, and hair follicle destruction caused by the Aldara cream (Figure 6H). Together, these results indicate that CO has a protective effect against imiquimod-induced psoriasis. ## 2.7. CO Reduces the Levels of IL-17A and AIM2 Inflammasome Components in IMQ-Induced Skin Lesions During IMQ-induced skin inflammation, the expression of AIM2 inflammasome components, such as AIM2, ASC, and pro-caspase-1, in skin lesions is upregulated [21,40], and serum levels of IL-17A, a cytokine which has been implicated in the pathogenesis of psoriasis, are increased [41,42,43,44,45]. In order to gain further insight into how CO ameliorates IMQ-induced skin inflammation, we examined the impact of CO on the expression of AIM2 inflammasome components in skin lesions and of serum IL-17A in the mice treated with IMQ. The data revealed that IMQ treatment caused an increase in IL-17A levels, which were significantly diminished by CO treatment (Figure 7A). Moreover, as expected, we observed increased AIM2, ASC, and caspase-1 in IMQ- induced skin lesions, and CO treatment attenuated this increase in expression (Figure 7B). These findings suggest that the reduction in skin inflammation by CO treatment may be due, at least in part, to the inhibition of IL-17A cytokine release and the suppression of AIM2 inflammasome activation. ## 3. Discussion Inflammasomes are part of the innate immune system and are responsible for sensing danger signals from pathogens in damaged cells, which is essential for protecting the host from environmental threats [31]. However, dysregulated inflammasome activation has been implicated in the pathogenesis of various inflammatory diseases [46]. Therefore, many efforts have been made to explore inhibitors of inflammasome activation from various sources, including medicinal plants that have been traditionally used for their anti-inflammatory properties [47,48,49]. This study provides evidence for the inhibitory activity of CO, an ethanolic extract of Cornus officinalis seed, on AIM2-inflammasome activation and its potential therapeutic effect on psoriatic-like skin inflammation induced by IMQ, to which the AIM2 inflammasome is known to contribute [38,40]. The AIM2 inflammasome is responsible for sensing cytosolic dsDNA derived from both pathogens and damaged cells [15,50], and its activation participates not only in host protection but also in some inflammatory diseases, such as psoriasis, chronic kidney injury, and atherosclerosis [18,21,51]. To explore the underlying mechanisms that mediated the inhibitory effect of CO on AIM2-inflammasome activation, we investigated the impact of CO treatment on the series of steps required for inflammasome activation. Caspase-1 is a key enzyme that cleaves to the proinflammatory cytokines IL-1β and IL-18 in their active form, which contribute to triggering an inflammatory response [6]. Caspase-1 activation occurs within the inflammasome complex, where ASC speck is crucial for recruiting and activating caspase-1 [2,3,5]. Therefore, most inflammasome inhibitors show inhibitory activity towards ASC speck formation and subsequent caspase-1 activation [52,53]. The treatment of CO also exhibited the inhibition of both ASC speck formation and caspase-1 cleavage, indicating that its ability to inhibit the release of IL-1β from cells is attributable to the inhibition of inflammasome complex formation. Furthermore, CO also inhibited the formation of dsDNA-induced AIM2 speck in AIM2-overexpressing HEK293T cells, which is an essential step in the activation of the AIM2 inflammasome [33]. This observation is crucial in explaining why CO specifically inhibits the AIM2 inflammasome activation, since ASC speck formation and caspase-1 cleavage are also commonly observed in other inflammasome activation occurrences, such as NLRP1, NLRP3, and NLRC4 [4,6]. Some studies suggest that the AIM2 inflammasome activation is contributed to by the progression of psoriasis by the release of pro-inflammatory cytokines [38,40]. Psoriasis is a form of chronic, immune-mediated inflammatory dermatosis that affects approximately 2–$4\%$ of the population worldwide [54]. Despite the various therapies available, such as psoralen, steroids, ultraviolet (PUVA) photochemotherapy, immunosuppressants, and biological therapies, most treatments have various side effects and require long-term administration [55,56,57,58,59,60]. Therefore, the discovery of new substances that can treat psoriasis is an area of great interest. To explore the in vivo relevance of the inhibitory effect of CO on AIM2 inflammasome activation in cells, we investigated the effect of CO on skin inflammation in an imiquimod-induced psoriasis mouse model. In this study, psoriasis-like skin inflammation was induced by repeated topical application of Aldara cream containing $5\%$ imiquimod [39], and treated mice exhibited typical psoriasis phenotypes, such as red colored plaques (erythema), silvery white dry scales, thickened skin, ear swelling, and bodyweight loss [61]. However, these psoriasis-like symptoms were alleviated by the topical application of CO. Histological analysis revealed that, as expected, CO ameliorates histological changes associated with imiquimod-induced psoriasis, such as parakeratosis, hyperpigmentation, and hair follicle destruction, which demonstrates its protective effect on imiquimod-induced psoriasis-like skin inflammation. Furthermore, we found that CO application significantly reduced the expression levels of AIM2 inflammasome components, including AIM2, ASC, and caspase-1, in skin lesions, as well as serum IL-17A levels in IMQ-treated mice. In previous studies, AIM2 has been shown to be upregulated in psoriatic skin lesions [21,40], and the blocking activation of the AIM2 inflammasome reduces inflammation and improves symptoms in animal models of psoriasis [62], suggesting that it may play a role in the chronic inflammation associated with the disease. Serum levels of IL-17A are increased, which increases are implicated in the pathogenesis of psoriasis [41,42,43,44,45]. The exact mechanism by which CO alleviates IMQ-induced skin inflammation is currently unknown, and the identification of active compounds with therapeutic efficacy and further research will be required in order to fully understand it. However, at least in part, the decrease in AIM2 inflammasome activation and IL-17A levels in serum may contribute to this effect. Altogether, these results indicate that CO holds potential not only as a therapeutic material for the treatment of psoriasis and other diseases associated with the AIM2 inflammasome and cellular damage, but also as a source for further exploration of the effective active compound. ## 4.1. Reagents The following reagents and materials were purchased for the study: LPS (L2630), from Pierce Chemical (Rockford, IL, USA); nigericin (tlrl-nig), nano-SiO2 (tlrl-sol), poly(deoxyadenylic-deoxythymidylic) acid (poly(dA:dT), tlrl-patn), Pam3CSK4 (tlrl-pm2s-1), lipofectamine 2000 [11668019], YVAD-CMK (Inh-yvad), and a mouse IL-1 beta ELISA kit [88-7013-88], from Invivogen (San Diego, CA, USA); a human IL-1 beta ELISA kit (DY201), from R&D systems (Minneapolis, MN, USA); flagellin (AG-40B-0095), from Adipogen International (San Diego, CA, USA); ATP (A7699), thiazolyl blue tetrazolium bromide (M5655), DMSO (D2660), KCl (P5405), and glycine (G7126), from Sigma-Aldrich (St. Louis, MO, USA); disuccinimidyl suberate (DSS, #21555) and a BCA assay kit (#23225), from Thermo Fisher Scientific (Walthan, MA, USA); RIPA lysis buffer (#89900), from iNtRON (Seoul, Republic of Korea); protease inhibitor (P3100-005), from GenDEPOT (Katy, TX, USA); RPMI1640 [11875119], DMEM [11995073], Opti-MEM [31985088], fetal bovine serum [16000-044], antibiotic-antimitotic [15240062], and trypsin/EDTA [15400-054], from Gibco (Grand Island, NY, USA); TNF-alpha (315-01A) and human interferon gamma [300-02], from PeproTech (Rocky Hil, NJ, USA); antibodies against ASC (AL177) and caspase-1 (p20) (AG-20B-0042), from Adipogen International (San Diego, CA, USA); antibodies against mouse IL-1 beta/IL-1F2 (AF401-NA) and NLRP3 (Cryo2), from R&D systems (Minneapolis, MN, USA); antibodies against β-actin (sc-1616), from Santa Cruz Biotechnology (Santa Cruz, CA, USA); antibodies against AIM2 (63660S) and GAPDH (sc-365062), from Cell Signaling Technology (Beverly, MA, USA); antibodies against FLAG (F1804), from Sigma-Aldrich (St. Louise, MO, USA); an LDH assay kit (DG-LDH1000) and a Western blot chemiluminescence reagent kit (EZ-Western Lumi Pico Kit, DG-WP250), from DoGenBio (Seoul, Republic of Korea); Nitrocellulose membranes (HATE00010), from Millipore Corporation (Bedford, MA, USA); and an ELISA MAX™ Deluxe Set Mouse IL-17A kit [432504], from BioLegend (San Diego, CA, USA). ## 4.2. Animals Male BALB/c and C57BL/6 mice, six weeks old, were obtained from Orient Bio Co. (Seoul, Republic of Korea). The mice were housed in groups of five in a controlled environment (22 ± 2 °C, 55 ± $5\%$ humidity, 12-hour light/dark cycle) with unlimited access to food and water. The experiments were conducted in accordance with the guidelines set by the Konkuk University Animal Care Committee and were reviewed and approved by the Ethics Committee of Konkuk University (approval number: KU22192). ## 4.3. Plant Materials For the screening, crude extracts were obtained from the plant extract bank at the Republic of Korea Research Institute of Bioscience and Biotechnology (KRIBB) (Daejeon, Republic of Korea). The powder was then dissolved in dimethyl sulfoxide (DMSO) and diluted with cell culture media immediately before use. The final concentration of DMSO in the cell culture media was maintained below $0.1\%$. The preparation of samples for follow-up studies was as follows. The seeds of Cornus officinalis were ground and extracted with $100\%$ ethanol at room temperature for 48 h and filtered through a filter paper (Whatman ND, No. 41, Grade 5). After evaporation, the extracts were dissolved in distilled water and lyophilized. ## 4.4. General Experimental The 1H NMR spectrum was recorded at 300 MHz in DMSO-d6 on Varian Inova spectrometers. The 13C NMR spectrum was obtained at 100 MHz in DMSO-d6 using an Agilent NMR spectrometer. Low-resolution LC-MS data were acquired using an Agilent Technologies 1260 quadrupole LC/MS system, equipped with a diode array detector (DAD) and a Phenomenex Luna C18 [2] 100 Å, 50 mm × 4.6 mm, 5 μm, at a flow rate of 1.0 mL/min, at the National Research Facilities and Equipment Center (NanoBioEnergy Materials Center) at Ewha Womans University. The fractions were purified by reversed-phase high-performance liquid chromatography (HPLC) (Phenomenex Luna C18 [2], 100 Å, 250 nm × 10 mm, 5 μm). ## 4.5. LC-MS Fingerprinting Analysis and Isolation of Compound The dried powder of 10 mg CO was added to a 1.5 mL Eppendorf tube. Subsequently, 1 mL of water was added and mixed. The sample was filtered through a 0.2 μm filter and injected into an LC-MS system for analysis. A binary gradient elution system composed of $1\%$ trifluoroacetic acid in water and acetonitrile was employed. The LC-MS data were acquired using the following gradient: 0–10.0 min, $13\%$ acetonitrile; 10.0–40.0 min, 13–$15\%$ acetonitrile; 40.1–45.0 min, $100\%$ acetonitrile; 45.1–48.0 min, $5\%$ acetonitrile. The following chromatogram and content assays for CO were performed using the above liquid-phase conditions. The CO (2 g) was subjected to open column chromatography purification in an RP C18 flash column by step gradient elution of methanol/H2O from $20\%$ to $100\%$ of methanol, subsequently, to afford 8 fractions (SSU-F1 ~ SSU-F8). Fraction SSU-F3 (22.5 mg) (H2O: MeOH = 50:50) was purified by reversed-phase HPLC (Phenomenex Luna C-18 [2], 250 × 100 mm, 2.0 mL/min, 5 μm, 100 Å, UV = 254 nm) using an isocratic solvent system with $17\%$ acetonitrile in water to yield ellagic acid (1 mg) as white powder. Its molecular formula was deduced based on the LC-MS data and 1H NMR data. Ellagic acid: white powder; 1H NMR (300 MHz, in DMSO-d6) δH 7.46 (2H, s); 13C NMR (100 MHz, in DMSO-d6) δC 159.1, 148.1, 139.5, 136.4, 112.3, 110.3, 107.7; LR-ESI-MS m/z 303.07 [M + H]+. ## 4.6. Cell Culture HEK293T, HaCaT, and L929 cells were cultivated in DMEM medium supplemented with L-glutamine, $10\%$ FBS, and 100 U/mL antibiotic–antimitotic. For L929 conditioned medium (LCM), 1.3 × 106 cells were cultured for 7 days in a T175 cell culture flask, and the culture supernatants were filtered through 0.22 μm and kept at −80 °C until needed. Bone marrow cells were prepared from femurs, and red blood cells were removed by incubation with RBC lysis buffer (150 mM NH4Cl, 10 mM KHCO3, 120 μM monosodium EDTA, pH 7.3). The bone marrow cells were suspended in complete medium (RPMI 1640 supplemented with $10\%$ FBS, $1\%$ penicillin/streptomycin, 50 μM 2-mercaptoethanol, 1 mM sodium pyruvate, MEM-NEAA, $30\%$ LCM medium). The cells were cultured in a 150 cm2 dish at a density of 5 × 106 cells/20 mL, and at days 3 and 6 the medium was replaced with fresh medium. At day 7, the macrophages were detached and seeded for further experiments. ## 4.7. Cytotoxicity Assay Cells were seeded in 96-well plates and cultured overnight. Then, the cells were incubated with the indicated concentrations of CO for 24 h. For the MTT assay, the culture medium was discarded and replaced with MTT solution (500 μg/mL) in culture medium, followed by 2 h incubation at 37 °C. Then, DMSO was added to solubilize the formazan, and absorbance (OD) was measured at 550 nm using a Multiskan GO Microplate spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The viability was calculated by relative comparison with control cells. The cell viability was calculated as % = (OD of each sample/OD of non-treated control) × 100. ## 4.8. Inflammasome Activation in BMDMs The BMDMs were pre-treated with either LPS (100 ng/mL) or Pam3CSK4 (300 ng/mL) for 3 h. After priming, the medium was replaced with Opti-MEM, and the cells were incubated with or without various samples before stimulation with various inducers: ATP (5 mM) or nigericin (10 μM) for 1 h, silica (150 μg/mL) for 3 h, transfection with poly(dA:dT) (1 μg/mL) for 2 h, and flagellin (1 μg/mL) or LPS (50 μg/mL) for 3 h using lipofectamine 2000. ## 4.9. Immunoblot Analysis The amounts of protein in cell lysates were determined using a BCA assay kit; cell lysates and cell supernatants were boiled for 5 min with sample buffer. Equivalent amounts of samples from cell lysates and cell supernatants were separated by SDS-PAGE and transferred onto nitrocellulose membranes. Blocked membranes were incubated with primary antibodies overnight, and the membranes were incubated with horseradish peroxidase (HRP)-conjugated antibody for 1 h at room temperature. After incubation with secondary antibodies, the membranes were developed for visualization using an Enhanced chemiluminescence (ECL) detection kit by Image Analyzer (Bio-Rad, Hercules, CA, USA, Clarity Western ECL substrate, #1705061). ## 4.10. Enzyme-Linked Immunosorbent Assay (ELISA) Cell supernatants were collected for measuring IL-1β levels using an ELISA kit according to the manufacturer’s instructions. Mouse sera were collected for measuring IL-17A levels using an ELISA kit, according to the manufacturer’s instructions. The absorbance (OD) was measured at 450 nm using a Multiskan GO Microplate spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). ## 4.11. Lactate Dehydrogenase (LDH) Assay Cell death was determined by measuring LDH release into culture supernatants using an EZ-LDH kit (DoGen Bio, Seoul, Republic of Korea), according to the manufacturer’s instructions. The absorbance (OD) was measured at 450 nm using a Multiskan GO Microplate spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The LDH release was calculated as % = (OD of each sample/OD of lysis control) × 100. ## 4.12. Separation of Cell Lysates into Soluble and Insoluble Fractions of Triton X-100 Cells were lysed with TTNE lysis buffer ($1\%$ Triton X-100, 150 mM NaCl, 50 mM Tris, and 2 mM EDTA and containing a protease inhibitor cocktail) on ice for 20 min and centrifuged at 13,000 rpm for 15 min. The supernatants (soluble fractions) and pellets (insoluble fractions) were extracted using $1\%$ SDS lysis buffer (20 mM Tris (pH 7.5), 150 mM NaCl, $1\%$ SDS). ## 4.13. ASC Oligomerization Assay For the ASC oligomerization assay, cells were lysed in TTNE buffer ($1\%$ Triton X-100, 50 mM Tris-HCl, pH 7.4, 150 mM NaCl, 2 mM EDTA, and complete protease and phosphatase inhibitor cocktail) on ice for 20 min. The cell lysates were centrifuged at 6000 rpm at 4 °C for 15 min. Pellets were washed with and resuspended in PBS and cross-linked using 2 mM disuccinimidyl suberate (DSS) at room temperature for 30 min, and were then denatured in 20 mM Tris-HCl (pH 7.4) for 15 min at room temperature. The cross-linked pellets were centrifuged at 13,000 rpm for 15 min and dissolved in SDS sample buffer. ## 4.14. Immunofluorescence Staining for ASC Specks BMDMs seeded on four-well chamber slides were primed and pre-treated for 30 min with or without inhibitors before transfection with poly(dA:dT) (1 μg/mL) for 2 h. The slides were transferred to $4\%$ paraformaldehyde for 20 min on ice and permeabilized with $100\%$ acetone for 10 min at −20 °C. The dried slides were rehydrated with PBS and blocked with $10\%$ horse serum for 1 h. The cells were stained with anti-ASC antibodies (AL177, Adipogen, San Diego, CA, USA) and Cy3-conjugated anti-rabbit antibodies. Nuclei were stained with DAPI, and fluorescence microscopy (AX10, Zeiss, Oberkochen, Germany) images were obtained. ## 4.15. Immunofluorescence Staining of AIM2 Specks HEK293T cells cultured on poly-L-Lysine-coated cover glass were transfected with pCMV2-FLAG-mAIM2 plasmids (Addgene_51450) using lipofectamine 2000 for 24 h. Moreover, the cells were pre-treated with CO (10 μg/mL) for 30 min, followed by transfection with poly(dA:dT) (1 μg/mL) for 4 h. The slides were transferred to $4\%$ paraformaldehyde for 20 min on ice and permeabilized with $100\%$ acetone for 10 min at −20 °C. Then, the dried slides were rehydrated with PBS and blocked with $10\%$ horse serum for 1 h. The cells were stained with anti-FLAG antibodies (F1804, Sigma-Aldrich) and Cy3-conjugated anti-rabbit antibodies. Nuclei were stained with DAPI, and fluorescence microscopy (AX10, Zeiss, Oberkochen, Germany) images were obtained. ## 4.16. Inflammasome Activation in HaCaTs The HaCaTs were pre-treated with IFN-γ (100 ng/mL) and TNF-α (10 U/mL) for 24 h. The primed cells were incubated with or without CO or YVAD for 30 min and stimulated with poly(dA:dT) (1 μg/mL) for 24 h. ## 4.17. IMQ-Induced Mouse Psoriasis Psoriasis-like dermatitis was induced in mice by topical administration of Aldara cream (50 mg/day) on a 2 cm × 3 cm area of the back and 10 mg/day on the right ear for 8 consecutive days. CO mixed in Vaseline cream was topically applied 4 h before the Aldara cream application. The study animals were divided into four experimental groups: group 1: control group ($$n = 4$$), mice received Vaseline cream without Aldara cream application; group 2: vehicle group ($$n = 4$$), mice received Vaseline cream with Aldara cream application; group 3: CO 5 mg/kg ($$n = 4$$), mice received CO (5 mg/kg) in Vaseline cream with Aldara cream application; group 4: CO 10 mg/kg ($$n = 4$$), mice received CO (10 mg/kg) in Vaseline cream with Aldara cream application. The animals were monitored for the severity of their skin conditions over 8 consecutive days according to the Psoriasis Area and Severity Index (PASI) with a score range of 0–4 (0, none; 1, mild; 2, moderate; 3, severe; 4, very severe) for erythema and scaling. In addition, the thickness of skinfolds on the back and ear were also measured using a caliper (accuracy: ±0.02 mm; Mitsutomo, Tokyo, Japan). On the eighth day, the animals were sacrificed, their back skins were excised, and the biopsies of lesional skin were fixed in formalin and embedded in paraffin. The paraffin-embedded biopsies were sectioned and stained with hematoxylin and eosin (H&E) for a histological analysis. ## 4.18. Statistical Analysis Data are expressed as means ± standard errors of the means (SEMs) or as the standard deviations (SDs) of at least three independent experiments, each performed in triplicate. 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--- title: CT Characteristics of the Thymus in Adult Dogs with Non-Thymic Neoplasia Compared to Young Dogs authors: - Alessia Cordella - Jimmy H. Saunders - Emmelie Stock journal: Veterinary Sciences year: 2023 pmcid: PMC10051521 doi: 10.3390/vetsci10030192 license: CC BY 4.0 --- # CT Characteristics of the Thymus in Adult Dogs with Non-Thymic Neoplasia Compared to Young Dogs ## Abstract ### Simple Summary The thymus is a lymphatic organ located in the cranial mediastinum. Both in humans and dogs, the thymus is largely changing with age, becoming smaller with time and also undergoing replacement of the active tissue with fat. Computed tomography is the imaging modality of election for the visualization and characterization of the thymus in human patients, and the characteristics of this organ with regard to the age of the patients are well described. On the contrary, in dogs, detailed description of the computed tomographic appearance of the thymus in adult and young patients is so far lacking. The results of this study show the different appearance of the thymus in two populations: adult dogs with diagnosed neoplasia and young dogs. ### Abstract The thymus is a lymphatic mediastinal organ that is largely subject to changes with age. In human patients, the CT characteristics of the thymus in children and adults is well described. Furthermore, it is known in human medicine that stress can lead to a reduction in the size of the thymus, followed by a phase of hyperplasia (called the ‘rebound effect’). The visualization of thymic tissue in the cranial mediastinum of adult dogs with neoplasia is possible and could be related to a similar effect. In this study, we aimed to describe the CT characteristics of the thymus in adult dogs with neoplasia and to compare the aspect of the thymus in these dogs to juvenile dogs with a presumed normal thymus. A total of 11 adult dogs with neoplasia and 20 juvenile dogs were included. Several CT features of the thymus were evaluated, including the size, shape, and pre- and post-contrast attenuation values. The overall appearance was lobulated in all of the adult dogs and homogeneous in all of the juvenile dogs; it was left-sided in all of the adult dogs, while it was located in the midline in a few of the juvenile dogs (right-sided only in one). The thymus was less attenuating in adult dogs, in some cases with negative minimum pre-contrast attenuation values. In some dogs with neoplasia, the thymus can be detected at CT examination despite their age. ## 1. Introduction The thymus is mainly a lymphoid structure located in the cranial mediastinum, with a role in T-lymphocyte maturation [1,2]. The size of the thymus in dogs differs with age; it is relatively large at birth, and it continues to grow reaching its maximum size around 4–6 months of age [2]. Then, the thymus progressively involutes, with it being no longer visible at about 1 year of age in most cases, and the lymphoid tissue is progressively replaced by fatty tissue [1,2,3]. Its visualization with different imaging modalities is therefore conditioned by the age of the patient [3,4]. Computed tomography is widely used nowadays to assess mediastinal structures in dogs, and the CT characteristics of different types of mediastinal masses have been previously described [5,6,7]. In humans, the CT characteristics of a normal thymus have been described both in children and adult patients. A normal thymus in children appears as a variably attenuating cranial mediastinal structure, with smooth lateral contours, without a tendency to produce displacement or deformity of the surrounding structures [8]. Thymic CT attenuation correlates inversely with age, likely representing the increase in the amount of fat [9]. In addition, the volume of the thymus decreases progressively with age in humans, with no solid tissue component left in the majority of patients older than 50 years old, where the involuted thymus is difficult to differentiate from the mediastinal fat even in CT [10,11]. Thymic hyperplasia has been reported in humans after recovery from stress, associated with thyroid diseases, and after chemotherapy [12,13,14,15]. This phenomenon is known as ‘rebound thymic hyperplasia’ and the mechanism is thymic depletion due to high plasma glucocorticoid concentrations, followed by a rebound effect when cortisol levels drop [16,17]. Little information is currently available in the veterinary literature regarding the normal CT appearance of the thymus in young and adult dogs and about thymic hyperplasia in this species [16]. The authors incidentally noticed the presence of a well-visible thymus in the cranial mediastinum of dogs that had undergone CT examination. The aim of this retrospective study was therefore to describe the CT characteristics of the thymus in this population of adult dogs and to compare them with those of a population of young dogs. ## 2. Materials and Methods This single-center descriptive study consisted in the retrospective description of cases in which the thymus was noticed in adult dogs at the time of CT examination. Dogs who underwent CT examination at Ghent University in the period between August 2020 and August 2022, in which the thymus was visible, were considered for inclusion. Dogs were included if they had a thoracic/whole body CT scan consisting of at least one pre-contrast scan and one post-contrast scan available for review, and if they had the confirmation of primary disease (thoracic or other than thoracic). Data regarding the age, sex, breed, and body weight of these dogs were collected, together with the final diagnosis of the primary disease. Exclusion criteria were incomplete patient data, incomplete or suboptimal CT studies, and a lack of definitive diagnosis. Young dogs (less than 9 months old), who underwent CT examination of the thorax for different clinical purposes in the same period of time, were also included for comparison. All CT images were retrieved from the Picture Archiving and Communication System (PACS) and analyzed using freestanding workstations (OsiriX v5.8.5 64-bit, Geneva, Switzerland) by a third-year European College of Veterinary Imaging resident (A.C.). Different features of the thymus were subjectively evaluated: [1] the shape (triangular, elongated, bilobed, or flattened,); [2] the overall appearance (lobulated or homogeneous); [3] the lateralization in the mediastinum (left-sided, midline, or right-sided); the grade and type of enhancement (mild/moderate/severe and homogeneous/heterogeneous). Quantitative findings, such as the dimensions (length, width, and height) and the pre- and post-contrast mean, minimum, and maximum attenuation values (measured in Hounsfield Units—HU) of the thymus were also assessed. In particular, to assess the attenuation values, a round region of interest (ROI) was placed (approximately) in the center of the structure in the pre-contrast images and copied (to have the exact same location and dimensions of the ROI) in the post-contrast images. When more than one post-contrast phase were available, the delayed phase was used for the measurements. ## CT Scanning Techniques Computed tomographic data were obtained with a 320-row MDCT unit (Aquilion One, Toshiba Medical Systems, Otawara, Japan). The technical parameters for all of the patients were as follows: helical modality, 120 kVp, 200 mAs, image matrix 512 × 512, 0.5 mm slice thickness. All of the dogs (except two in the young dog’s group) were scanned in sternal recumbency on the CT table, with the head first, front limbs cranially extended, and hindlimbs caudally extended. For all studies, a pre-contrast series of the whole body was acquired, followed by one post-contrast series acquired from 1 to 3 min after injection of iodinated contrast agent (iohexol 370 mgI/mL, 2 mLI/kg dosage followed by a saline flush) via the cephalic vein with a dual-barrel injector system. Some studies consisted of more post-contrast phases (either dual-phase or ECG-gated cardiac protocol), but the scans evaluated for all dogs included were pre-contrast and delayed post-contrast phases. ## 3.1. Animals In the period of inclusion, 73 dogs who has undergone a thoracic CT received (or presented with) a definitive diagnosis of neoplasia (based on cytology, histology, or post-mortem). Of these, the thymus was clearly visible in the cranial mediastinum in 11 dogs ($15\%$). The median age of the 11 dogs included was 9 (2–12) years, and the median body weight was 22.7 (7.2–82.3) kg. The majority of the included dogs were males ($\frac{8}{11}$—$73\%$), of which 4 were neutered, and the remaining $\frac{3}{11}$ ($27\%$) were females; all three were neutered. Eleven different breeds were represented (one dog each): a Cavalier King Charles Spaniel, a White Swiss Shepherd, a Staffordshire Bull Terrier, a Shih-Tzu, a Jack Russell Terrier, a Mastino Napoletano, a Pug, a Chow Chow, an American Staffordshire Terrier, a Border Collie, and a crossbreed dog. All of the dogs included in this group (adult dogs) were diagnosed with neoplasia, and in particular, one dog had a meningioma at the level of T5, one had an anal sac adenocarcinoma, one had a mast cell tumor in the neck, one had a mammary gland carcinoma, one had soft tissue sarcoma in the cervical region, one had a nasal carcinoma, one had muscular hemangiosarcoma, one had Leydig cell tumor of the testicle, one had rib chondrosarcoma, and two had synovial cell sarcomas (one in the stifle and one in the tarsus). In the same period, 20 young dogs (less than 9 months old) underwent CT examination of the thorax. The median age of this group of dogs was 4 (2–9) months, and the median body weight was 13.5 (1.5–47) kg. Eleven out of the twenty dogs were males ($55\%$), and the remaining $\frac{9}{20}$ ($45\%$) were females, all intact. Different breeds were represented: two Border Collies, two Chihuahuas, two English Bulldogs, two Golden Retrievers, one Bullmastiff, one Australian Cattle Dog, one Coton de Tulear, one Great Dane, one Bernese Mountain Dog, one Flatcoated Retriever, one French Bulldog, one Labrador Retriever, one Malinois, one Newfoundlander, one Thai Ridgeback, and one Dachshund. Seven of these dogs underwent CT examination for cardiac congenital anomalies (six with pulmonic stenosis and one with a ventricular septal defect), four for thoracic disease (two with pneumonia, one with pyothorax, and one with megaesophagus), four for orthopedic or neurological disease (one with a spinal cyst, one with meningitis/arthritis, one with hip and elbow dysplasia, and one with a dermoid sinus), three for trauma, one for abdominal disease (enteritis), and one presented with situs inversus. ## 3.2. CT Appearance of the Thymus in Adult and Juvenile Dogs CT features of the thymus in the adult dogs and in the juvenile dogs groups are summarized in Table 1. In both groups, most of the dogs presented with a triangular thymus (Figure 1); in the adult group, some dogs had an elongated thymus, and in the juvenile group, some dogs had a flattened thymus (Figure 2). The overall appearance was lobulated in all of the adult dogs and homogeneous in all of the juvenile dogs (Figure 1 and Figure 3). The thymus was left-sided in all of the adult dogs, while it was located in the midline in a few juvenile dogs; one presented a thymus on the right side due to situs inversus (Figure 4). The maximum dimension of the thymus in the adult dogs group was always the length, while in some juvenile dogs, the maximum diameter was the width (Figure 2). The dimensions of the thymus were variable between different patients, with several breeds included and large differences in body weight between the dogs. For this reason, a ratio between the maximum diameter of the thymus (measured in cm) and the body weight (measured in kg) was calculated for each dog. The median ratio in the adult dogs group was 0.2 (minimum: 0.06; maximum: 0.4), while in juvenile dogs, it was 0.4 (minimum: 0.1; maximum: 1.4). The dogs with the higher ratio (>1) were in the juvenile group and they presented with spinal a cyst and enteritis and were 6 and 7 months old, respectively. The dogs with the lower ratio (<0.1) were in the adult group and they presented with muscular hemangiosarcoma (one dog) and synovial cell sarcoma (two dogs) and were 2, 6, and 8 years old, respectively. The thymus was less attenuating in adult dogs compared to young dogs, with a median of the mean pre- and post-contrast attenuation values lower in adult dogs compared to juvenile dogs (Table 1). In $\frac{5}{11}$ ($45\%$) adult dogs, the minimum pre-contrast attenuation values were negative values (from −22 to −2 HU), due to the presence of multiple, hypoattenuating, thick septi within the thymic parenchyma (Figure 5). ## 4. Discussion The CT characteristics of the thymus in young and adult dogs have been described in this study. In young dogs, the thymus showed different shapes, with the majority presenting with a triangular appearance and some with flattened ones. In humans, a normal thymus can show some degree of individual variation, but some features are considered characteristic of a normal gland, including smooth lateral contours, convex lateral borders in very young patients, and straight or concave lateral borders with increasing age [8]. The sharp angular contour to the lateral margin of the thymus is similar to the described “sail sign” in thoracic radiography [8]. This radiographic feature has also been described in thoracic radiographs of young dogs [3,4], and the majority of young dogs in our population showed a similar shape in the dorsal reconstructions. The parenchyma of the thymus in our population of young dogs was homogeneous in all cases and with variable soft tissue attenuation values, which were higher in the post-contrast series. These characteristics were similar to those described in human medicine, where the thymus can show high variability in its attenuation in preadolescent and adolescent patients, especially in the pre-contrast series [8]. According to the results of this study, the thymus was less attenuating in adult dogs compared to young dogs, both in the pre- and post-contrast series. This finding is in accordance with the human literature, in which CT attenuation of the thymus is inversely correlated with age [9,10,17]. In particular, the decrease in attenuation is due to the known fatty degeneration that occurs in the thymus [8,9,17,18]. The increased amount of fat in the thymus of adult dogs compared to the younger population is also visible in our population, where almost half of the adult dogs show negative pre-contrast attenuation values, typical for fat tissue. In humans, other factors have been found to influence the attenuation of the thymus in adult patients, such as sex, cigarette smoking, and obesity [18,19]. The thymus in women shows less fat content than in men, most likely due to delayed thymic involution in women [18]. In our population there was a disproportion in the included adult dogs, with three-quarters of them being males; therefore, a comparison between sex was not attempted, and further studies are necessary to test this hypothesis in the canine species. Similarly, body condition score has not been evaluated as a factor in our study, but interestingly, upon retrospective revision, no patients with severely increased body condition scores were included in our population. The shape of the thymus in our population of adult dogs was variable, with the majority of the included dogs showing a triangular or elongated thymus, and only one with a bilobed thymus. In human patients, the thymus may appear as two separate lobes or as an arrowhead (triangle) formed by the confluence of the right and left lobes [17]. Furthermore, it has been suggested that in adult human patients (older than 40 years old), the presence of an ovoid or spherical soft tissue thymic appearance usually represents a neoplasm [10]. Several CT features of thymic neoplasia have been described in dogs. Thymomas have been described as large, space-occupying masses arising from the cranial mediastinum, frequently heterogeneous or with a cystic appearance, mainly left-sided but being more centrally located with increasing size [6]. Vascular invasions have been reported, especially in larger masses [6]. Cranial mediastinal lymphomas have been described as more homogeneous masses compared to thymic epithelial neoplasms, more likely to envelop the cranial vena cava [7]. The CT characteristics of thymic neoplasia reported in these previous studies, such as large masses, heterogeneous, enveloping or invading the adjacent vasculature [6,7], were significantly different from the findings of the current study, in which the thymus was in fact considered non-neoplastic. The CT appearance of thymic hyperplasia in humans can be variable, but some features, such as bipyramidal morphology and the presence of gross intercalated fat (also described as ‘marbling’), are considered pathognomonic [20]. This appearance of ‘marbling’, with the presence of several hypoattenuating septations throughout the thymic parenchyma, was present in all of the adult dogs included in the current study, suggesting that these dogs may have presented with thymic hyperplasia at the time of CT examination. A histopathological, post-mortem study showed that thymic cysts are associated with several pathologic conditions in dogs, including neoplasia [21]. While the young and healthy dogs’ histology revealed a high proportion of lymphocytes, in adult chronically diseased cases, the cystic component was predominant [21]. The differences in histological components could reflect the different appearance of the thymus at CT examination in our two populations of dogs. The cystic component was not evident in CT in any of the cases included, but it is possible that some thymic cysts may have been missed, as it is known from human medicine that thymic cysts can have high attenuation values and resemble solid tissue on CT [20]. Despite the fact that a small thymic remnant can be detected in some dogs at any age [2], it has been reported that, in adult dogs, the thymus should have undergone the involution processes, and it is in most cases no longer visible at about 1 year of age [1,3]. The thymus was well visible in the adult dogs included in the current study. The characteristics, as already mentioned, were more suggestive of hyperplasia and not of a neoplastic process (neither a thymic epithelial tumor nor lymphoma). Rebound thymic hyperplasia has been rarely described in veterinary patients, with the CT features proposed being thymic enlargement but with a normal shape [18]. In humans, the thymus can atrophy during illness, and excessive regrowth may occur in the recovery phase, with subsequent thymic enlargement, called rebound thymic hyperplasia [17]. Similar thymic enlargement has been described in patients after remission of Cushing’s syndrome, where the thymic atrophy is due to high levels of glucocorticoids in plasma, followed by rebound hyperplasia when these levels drop [16]. Following this mechanism, in dogs with neoplasia, as with the adult population described in this study, the thymus should be atrophied and therefore either barely or not visible at CT examination. Thymic hyperplasia was considered more likely than a neoplastic infiltration in our study population, but the mechanism is likely different from the one described in human medicine. We can hypothesize that at the time of presentation, these dogs were already chronically ill, and therefore, they could have passed the phase of thymic atrophy and could have already started the ’rebound’ phase. Unfortunately, given the lack of CT examination prior to the description of these findings, this hypothesis is only one of the possible explanations. This study has some additional limitations. First, no histological confirmation was available for the thymus for the included dogs; therefore, we could only hypothesize that the thymus visualized in our group of young dogs was normal and possibly hypertrophic in the adult dogs. The inclusion of patients with different diseases in the group of young dogs could have altered the results, with the possible inclusion of some dogs with thymic hyperplasia in this group. Other limitations included the low number of cases and the retrospective nature of the study. For these reasons, further studies are needed in order to confirm our findings and to understand the potential mechanisms of thymic hyperplasia and/or rebound in dogs, which seemed to partially differ from what has been described in human medicine. ## 5. Conclusions The thymus can also be identified at CT examination in adult dogs, in the case of our study, dogs affected by different types of neoplasia. Some CT characteristics of the thymus are different between young dogs (with different diseases) and adult dogs with neoplasia. The appearance of the thymic parenchyma is lobulated in adult dogs and homogeneous in juvenile dogs. 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--- title: New Senolysis Approach via Antibody–Drug Conjugate Targeting of the Senescent Cell Marker Apolipoprotein D for Skin Rejuvenation authors: - Kento Takaya - Toru Asou - Kazuo Kishi journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051536 doi: 10.3390/ijms24065857 license: CC BY 4.0 --- # New Senolysis Approach via Antibody–Drug Conjugate Targeting of the Senescent Cell Marker Apolipoprotein D for Skin Rejuvenation ## Abstract Senescent cells accumulate in aging skin, causing age-related changes and a decline in functional efficiency. Therefore, senolysis, a treatment that specifically removes senescent cells and rejuvenates the skin, should be explored. We targeted apolipoprotein D (ApoD), a previously identified marker expressed on senescent dermal fibroblasts, and investigated a novel senolysis approach using a monoclonal antibody against this antigen and a secondary antibody conjugated with the cytotoxic drug pyrrolobenzodiazepine. Observations using fluorescently labeled antibodies revealed that ApoD functions as a surface marker of senescent cells and that the antibody is taken up and internalized only by such cells. The concurrent administration of the antibody with the PBD-conjugated secondary antibody specifically eliminated only senescent cells without harming young cells. The antibody–drug conjugate treatment of aging mice combined with the administration of antibodies reduced the number of senescent cells in the dermis of mice and improved the senescent skin phenotype. These results provide a proof-of-principle evaluation of a novel approach to specifically eliminate senescent cells using antibody–drug conjugates against senescent cell marker proteins. This approach is a potential candidate for clinical applications to treat pathological skin aging and related diseases via the removal of senescent cells. ## 1. Introduction The accumulation of senescent cells in tissues causes a number of age-related medical conditions [1]. In recent years, pharmacological research aimed at eliminating senescent cells or senolysis has attracted attention towards combatting such problems. A number of clinical trials are currently underway to investigate innovative pharmacological treatment methods. For example, the therapeutic potential of senescent cell removal has been demonstrated in mouse models of diverse diseases and disorders, including pulmonary fibrosis [2,3], atherosclerosis [4,5], diabetes [6,7], and neurodegeneration [8,9]. In the skin, the senescent phenotype is attributed to senescent cells accumulated in the epidermal and dermal cells and subcutaneous adipose tissue depots, and the development of new senolytic agents is expected [10]. One approach for senescent cell elimination focuses on the fact that senescent cells differ significantly from proliferating cells in the pattern of expressed proteins, including those on the cell surface, which can serve as markers and therapeutic targets. This strategy of using senescent cell-specific markers to target senescent cells is similar to that used to selectively eliminate cancer cells [11]. Senolysis-mimicking anti-cancer therapies targeting specific markers of senescent cells, such as antibody-dependent cellular cytotoxicity [12] and T-cell therapy [13], have been reported. In a previous study, we found that ApoD is specifically expressed in senescent fibroblasts in the dermis [14]. Here, we aimed to develop a senolysis method by combining the targeting of this marker with the existing idea of anti-cancer therapies. Recently, one of the therapeutic approaches used to target only specific cells is the use of antibody–drug conjugates (ADCs). The therapeutic concept of ADCs is to selectively target tumor cells with small-molecule cytotoxic drugs to maximize cell-killing efficacy and minimize toxicity [15]. ADCs typically consist of antibodies that chemically target proteins on the surface of the target cells. The antibodies bind to the target protein and are generally internalized by the cell. Cytotoxic agents are released into endosomal or lysosomal compartments, and by diffusion or transport, these cytotoxic agents can exert cell-killing effects. Currently, specific ADCs have been developed and are FDA-approved for the treatment of breast cancer, lymphoma, multiple myeloma, and gastric cancer [16,17]. We aimed to analyze whether the specific elimination of senescent fibroblasts occurs when a secondary antibody conjugated with pyrrolobenzodiazepine (PBD), a candidate ADC that inhibits DNA synthesis, is administered using a monoclonal antibody against ApoD, a senescent fibroblast specific marker. This approach could potentially aid in the development of a new method of senolysis. ## 2.1. ApoD Antibodies Are Specifically Internalized within Aging Dermal Fibroblasts To determine whether ApoD monoclonal antibodies are specifically internalized within aging dermal fibroblasts, fluorescently labeled ApoD antibodies were administered to cells, as well as fluorescently labeled non-specific IgG and fluorescent dye as controls. Cells induced to senescence by replicative senescence and ionizing radiation showed an increase in SA-β-gal-positive cells (Figure 1A) and a significant decrease in BrdU uptake, indicating reduced mitotic activity (Figure 1B). In addition, the membrane protein marker CAV1 was found to be expressed at similar levels in all cell models, while ApoD was found to be significantly more highly expressed in the cell membrane of the senescent cell model compared to younger cells (Figure 1C). When fluorescently labeled antibodies were administered to these cells, fluorescence was observed in the cytoplasm only when the senescent cells were treated with fluorescently labeled ApoD antibodies. This did not occur with the usage of fluorescent dye alone or of a non-specific antibody. Furthermore, no internalization of antibody sites was observed when young cells were treated with ApoD antibodies. The results indicate that the ApoD antibody is specifically taken up and internalized by senescent cells (Figure 1D). ## 2.2. Combination of ApoD Antibody and a Secondary Antibody Conjugated with PBD Specifically Eliminates Human Skin Fibroblasts Since the ApoD antibody was found to be specifically taken up and internalized by senescent cells, we investigated whether cell-specific killing occurred when a secondary antibody conjugated with cytotoxic PBD was administered with the ApoD antibody. As controls, we administered PBS (control), a primary antibody only, and a PBD-conjugated secondary antibody only. In young cells, there was no difference in cell viability with either intervention. However, in the two senescent cell models, the combination of primary and secondary antibodies significantly reduced viability (Figure 2A). To optimize the concentration, we administered multiple concentrations of the PBD-conjugated secondary antibody and found a significant difference in survival between young and senescent cells at 100 µM, which is the concentration used in the assay (Figure 2B). Thus, it was shown that senescent fibroblasts are specifically killed by ADC with the ApoD antibody and the PBD conjugated secondary antibody. Furthermore, when the relationship between the time after the start of the antibody treatment and cell viability was investigated, the viability of senescent cells decreased significantly after 72 h, and the extent of the decrease was the same after 96 h; hence, the treatment time was determined to be 72 h (Figure 2C). In addition, the concentrations of inflammatory cytokines, such as IL6 and IL8, as well as MMP3 and MMP9 proteins involved in dermal senescence, in the medium were reduced after these treatments, indicating that the senescent cell secretory phenotype (SASP) was suppressed (Figure 2D). ## 2.3. Combination of ApoD Antibody and Secondary Antibody Conjugated with PBD Rejuvenates Skin of Aging Mice To determine the effect of treatment using a combination of a anti-ApoD primary antibody and a PBD-binding secondary antibody on the skin of animals, young and old mice were administered a single dose of vehicle and the primary and secondary antibody combination intravenously, respectively. The results showed no histological changes in the skin of the young mice, but a significant increase in the thickness of the subcutaneous fat of the old mice was observed. The thickness of collagen fibers in the dermis was also increased by the ADC treatment (Figure 3A). The number of senescent cells (p16ink4a-positive cells) in the dermis was also significantly reduced (Figure 3B). No apparent adverse events, such as death or the appearance of skin ulcers in the mice, were observed during the observation. ## 3. Discussion Our results show that a monoclonal antibody against ApoD, a marker of aging dermal fibroblasts, was specifically taken up and internalized into the cytoplasm. Furthermore, when a complex of a secondary antibody was conjugated to this monoclonal antibody and a cytotoxic PBD was administered in combination, senescent cell-specific elimination was observed. Senescent cells have been reported to secrete a variety of cytokines (SASP) that affect the microenvironment of the tissue and disrupt its structure and function through a paracrine effect [18,19]. Additionally, treatment with ADCs inhibited the secretion of inflammatory cytokines associated with skin aging, and MMP secretion was inhibited. In an in vivo study, the administration of ADCs in combination with antibodies to aging mice reduced the number of senescent cells in the dermis and thickened collagen fibers without significant adverse events. In addition, the thickness of subcutaneous fat was significantly increased. The decreased collagen fiber thickness and subcutaneous fat thickness was consistent with the aging phenotype, and treatment resulted in improvements in these phenotypes [10]. Overall, our findings support the idea that treatment with a combination of anti-ApoD antibodies and PBD-conjugated secondary antibodies may play a partial role as a novel mechanism of senolysis in aging skin. Previous studies have indicated that ApoD expression may be induced by stress conditions, such as oxidative and inflammatory stress or UV treatment [20]. The nuclear factor PARP-1 (Poly ADP-ribose polymerase-1), which is upregulated in growth-arrested cells under special circumstances that induce senescence, such as oxidative stress, induces ApoD expression [21,22]. Thus, it is consistent that DNA damage caused by replication or ionizing radiation induces ApoD expression, and serves as an internalizing marker of senescence, as shown in the present study. The main cellular source of ApoD-inducing reactive oxygen species (ROS) is the mitochondria, and in a vicious cycle, ROS damage mitochondrial enzymes and mitochondrial DNA, and more ROS are produced due to defects in oxidative phosphorylation reactions [23]. Dysfunction of this intracellular pathway can lead to aging-related diseases, and an approach for ApoD induced by ROS may exert an anti-aging therapeutic effect by interfering with mitochondrial biosynthesis-related pathways [24]. Treatments that selectively destroy senescent cells include ABT263 [25] and ABT737 [26], which inhibit the anti-apoptotic protein Bcl family, as well as dasatinib and quercetin [27] as senolytic drugs that have been reported, but these have been associated with serious side effects. Therefore, attention is needed in finding markers with high specificity for tumor cells in the treatment of melanoma and other cancers to reduce side effects [28]. There is a need for senolysis as a highly specific therapy to kill senescent cells; antibody-dependent cell-mediated cellular cytotoxicity targeting DPP4 [12], antibody–drug conjugates targeting B2M [29], and CAR T therapy targeting the urokinase plasminogen activator receptor (uPAR) [13] were discovered using antigens with high specificity for senescent cells. ADCs are based on the recognition by antibodies of extracellular epitopes, which are then internalized, and the drug attached to them is released by the cleavage of linker molecules in lysosomes [30]. Our experiments showed that combination treatment with ApoD monoclonal antibody and PBD-conjugated secondary antibody selectively induced senescent cell death and decreased the expression of senescence-associated SASP without significantly affecting the survival of control proliferating cells. Furthermore, ApoD-negative young cells did not respond to ADC, and isotype control antibodies had no effect on senescent cell survival. This indicates that drug delivery indeed occurs via the specific binding of the antibody to ApoD and does not affect the cells themselves. This information suggests that ADCs can be generated for different targets and can be made specific to cell types or tissues to more selectively eliminate replication or stress-induced senescence, depending on clinical needs. The ApoD-targeted ADC therapy used herein may be a solid alternative to existing methods as it specifically eliminates senescent cells without affecting younger cells and improves the phenotype of aging skin without apparent side effects. These proof-of-principle data indicate that ADCs can be effectively used to eliminate senescent cells. However, our study has several limitations, and further experiments are needed to fully understand the relevant mechanisms. Our data strongly suggest that the specific removal of cells can be achieved by the internalization of ADCs. The effects of linker cleavage and the involvement of alternative pathways need to be explored in the future. In addition, no conclusions can be drawn on the aging of other types of cells in the skin, such as keratinocytes and macrophages, the fibroblasts of other tissues, or on side effects. In the present study, no apparent adverse events were observed after in vivo administration to mice. However, the major adverse effects of PBD in patients include vascular leak syndrome, elevated liver enzymes, myelosuppression, gastrointestinal effects (nausea, vomiting, diarrhea, and mucositis/stomatitis), metabolic effects (hyponatremia, hypophosphatemia, etc.), musculoskeletal effects (muscle weakness and myalgia), neuropathy, pain, dyspnea, fatigue, and renal impairment (hyperuricemia and proteinuria) [27]. Therefore, patients will need to be carefully monitored for the appearance of these symptoms with prolonged administration or changes in dosage. However, if necessary, cytotoxic stimuli that require the presence of multiple targets on the cell surface can be designed, which would greatly reduce potential toxic side effects, increase specificity, and increase the feasibility of the approach [31,32]. Our results indicate that specific antibodies may be an efficient system for introducing toxic drugs into human-aged dermal fibroblast cells, following the success of similar approaches in cancer therapy. Further studies are needed to determine the best targets, as well as the safety and efficacy of the therapy, but these data are a potential contribution to the development of new skin rejuvenation therapies. ## 4.1. Cell Culture Normal human dermal fibroblasts (NHDF) were obtained from Takara Bio (Shiga, Japan). NHDFs were grown in a low-glucose Dulbecco’s modified Eagle medium (Wako Pure Chemical Industries, Osaka, Japan) supplemented with $1\%$ penicillin/streptomycin (Thermo Fisher Scientific, Waltham, MA, USA) and $10\%$ fetal bovine serum (Thermo Fisher Scientific). Replicative senescence was defined as a cell population doubling level greater than 50 and no proliferation for more than 2 weeks. Ionizing radiation-induced senescence was induced in the same manner as previously reported [14]. Cells were irradiated with 10 Gy of X-rays by AB-160 X-Ray Irradiation System (AcroBio, Tokyo, Japan) and analyzed 10 days later. Control (young; proliferating) cells were mock-irradiated by removal from the incubator, transport to the irradiator, and maintenance outside the irradiator for the same period as the irradiated cells. Intracellular SA-β-gal activity was assessed by staining cells using Senescence β-Galactosidase Staining Kit from Cell Signaling (Danvers, MA, USA). ## 4.2. Evaluation of Proliferative Capacity by Measuring BrdU Uptake BrdU uptake was assessed using Frontier BrdU Cell Proliferation Assay (Exalpha Biologicals Inc, Shirley, MA, USA) according to the manufacturer’s protocol. SpectraMax i3x (Molecular Devices, San Jose, CA, USA) was used for analysis at $\frac{450}{550}$ nm. ## 4.3. Membrane Protein Quantification (Western Blotting) To extract membrane proteins from cells, cell lysates were prepared according to the manufacturer’s protocol using the Mem-PER™ plus membrane protein extraction kit (Thermo Fisher Scientific, Waltham, MA, USA) and processed. Each sample (40 μg) was electrophoresed on $10\%$ polyacrylamide gels (Mini-PROTEAN TGX precast gels; Bio-Rad Laboratories, Inc.) and transferred to polyvinylidene chloride membranes (Millipore, Bedford, MA, USA). After blocking with $3\%$ nonfat milk for 1 h at 25 °C, the membranes were incubated overnight at 4 °C with primary antibodies against apolipoprotein D/APOD (1:100, 347-MSM4-P1; ThermoFisher Scientific), CAV1 (1:1200, sc-53564; Santa Cruz Biotechnology, Santa Cruz, CA, USA) and GAPDH (1:2000; Santa Cruz Biotechnology) in a blocking solution. The next day, the samples were incubated with goat anti-mouse IgG H & L (Horseradish peroxidase) (ab205719; abcam, Cambridge, UK) at 1:1000 dilution for 2 h at 37 °C. After washing, immunoreactive protein bands were visualized using an electrochemiluminescence detection kit (Pierce Biotechnology, Rockford, IL, USA). Images of the bands were acquired using a chemiluminescence imager (ImageQuant LAS4000mini; GE Healthcare, Chicago, IL, USA). Image analysis was performed using ImageJ (ver. 1.53p, National Institutes of Health, Bethesda, MD, USA). Each experiment was repeated three times. ## 4.4. Fluorescence-Labeled ApoD Monoclonal Antibody Uptake Assay To confirm the endocytosis of mouse anti-human apolipoprotein D/APOD monoclonal antibody (ThermoFisher Scientific) into the cells, Alexa Fluor™ 488 Antibody Labeling Kit (ThermoFisher Scientific) was used to fluorescently label the antibody according to the manufacturer’s protocol. As a control, an anti-human IgG antibody (ab200699, abcam) was prepared with a similarly labeled antibody and Alexa Fluor 488 dye (ThermoFisher Scientific). Aged or normal human skin fibroblasts were plated in 96-well plates (5 × 103 cells per well, $$n = 4$$) and maintained in 100 μL of a medium. After 24 h, fluorescently labeled the anti-ApoD antibody (final concentration: 10 µM), anti-human IgG (final concentration; 10 µM), and fluorescent dye (final concentration: 10 µM) were added to respective wells. After 24 h, the cells were collected, labeled with CellMask™ Deep Red Plasma Membrane Stain (ThermoFisher Scientific), and observed with the confocal laser scanning microscope FLUO-VIEW FV3000 (Olympus, Co., Ltd. Tokyo, Japan). ## 4.5. Antibody–Drug Conjugate Assay Aged or normal human skin fibroblasts were plated in 96-well plates (5 × 103 cells/well, $$n = 4$$) and maintained in 100 μL of a serum-free medium; after 24 h, the anti-ApoD antibody (final concentration: 10 μM) or PBS (control) was added, and the cells were incubated for another 24 h. Anti-mouse IgG (Fc Specific) or PBD-conjugated IgGs with a cleavable linker (Moradec LLC, San Diego, CA, USA) was added at 100 μM, and the cells were incubated for another 72 h. In addition, PBD-conjugated IgG was administered at the concentrations of 0, 1, 5, 10, 50, 100, and 200 μM to optimize the concentration of secondary ADCs. To optimize the reaction time, viability was measured at 4, 12, 24, 48, 72, and 96 h after the administration of PBD-conjugated IgG. Cell viability was analyzed using CellTiter-Glo® 2.0 Cell Viability Assay (Promega, Madison, WI, USA) according to the manufacturer’s protocol. Relative viability was normalized against the PBS control, and quantification experiments were performed in triplicate. ## 4.6. ELISA After the preparation of the young and senescent cell model as described above and treatment with ADC and controls, the culture media were collected and subjected to ELISA [Human IL-6 Quantikine ELISA Kit (D6050), Human IL-8 Quantikine ELISA Kit (D 8000C), Human MMP-9 Quantikine ELISA Kit (DMP900) (R & D Systems, Inc., Minneapolis, MS, USA), and Human MMP3 ELISA Kit (ab100607, abcam)] for quantifying IL-6, IL-8, MMP9, and MMP3 concentration. ## 4.7. In Vivo Efficacy Study Male Bl6 mice (Sankyo Laboratories, Inc., Tokyo, Japan), at 9 weeks old (young) or 80 weeks old (old), were intravenously treated with the vehicle alone or with anti-ApoD antibody and PBD-conjugated IgG with a cleavable linker (Moradec LLC, San Diego, CA, USA), each at a concentration of 0.3 mg/kg and 3 mg/kg in a single dose. Each group contained five mice. The mice were kept with free access to food and water; after 1 month, the mice were euthanized, and tissue samples were collected. The frozen specimens were sliced into 7 µm thick sections, mounted on glass slides, and fixed in acetone for 10 min at room temperature. To block nonspecific binding sites, the slides were incubated with $3\%$ goat serum in PBS for 30 min at room temperature. The slides were then incubated overnight at 4 °C with the primary antibody p16 (ab108349, abcam, 1:200). 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--- title: High-Intensity Training Represses FXYD5 and Glycosylates Na,K-ATPase in Type II Muscle Fibres, Which Are Linked with Improved Muscle K+ Handling and Performance authors: - Morten Hostrup - Anders Krogh Lemminger - Laura Bachmann Thomsen - Amanda Schaufuss - Tobias Langballe Alsøe - Gustav Krogh Bergen - Annika Birring Bell - Jens Bangsbo - Martin Thomassen journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051537 doi: 10.3390/ijms24065587 license: CC BY 4.0 --- # High-Intensity Training Represses FXYD5 and Glycosylates Na,K-ATPase in Type II Muscle Fibres, Which Are Linked with Improved Muscle K+ Handling and Performance ## Abstract Na+/K+ ATPase (NKA) comprises several subunits to provide isozyme heterogeneity in a tissue-specific manner. An abundance of NKA α, β, and FXYD1 subunits is well-described in human skeletal muscle, but not much is known about FXYD5 (dysadherin), a regulator of NKA and β1 subunit glycosylation, especially with regard to fibre-type specificity and influence of sex and exercise training. Here, we investigated muscle fibre-type specific adaptations in FXYD5 and glycosylated NKAβ1 to high-intensity interval training (HIIT), as well as sex differences in FXYD5 abundance. In nine young males (23.8 ± 2.5 years of age) (mean ± SD), 3 weekly sessions of HIIT for 6 weeks enhanced muscle endurance (220 ± 102 vs. 119 ± 99 s, $p \leq 0.01$) and lowered leg K+ release during intense knee-extensor exercise (0.5 ± 0.8 vs. 1.0 ± 0.8 mmol·min–1, $p \leq 0.01$) while also increasing cumulated leg K+ reuptake 0–3 min into recovery (2.1 ± 1.5 vs. 0.3 ± 0.9 mmol, $p \leq 0.01$). In type IIa muscle fibres, HIIT lowered FXYD5 abundance ($p \leq 0.01$) and increased the relative distribution of glycosylated NKAβ1 ($p \leq 0.05$). FXYD5 abundance in type IIa muscle fibres correlated inversely with the maximal oxygen consumption (r = –0.53, $p \leq 0.05$). NKAα2 and β1 subunit abundances did not change with HIIT. In muscle fibres from 30 trained males and females, we observed no sex ($$p \leq 0.87$$) or fibre type differences ($$p \leq 0.44$$) in FXYD5 abundance. Thus, HIIT downregulates FXYD5 and increases the distribution of glycosylated NKAβ1 in type IIa muscle fibres, which is likely independent of a change in the number of NKA complexes. These adaptations may contribute to counter exercise-related K+ shifts and enhance muscle performance during intense exercise. ## 1. Introduction Na+/K+ ATPase (NKA) plays a vital role in muscle biology because it regulates the excitability of muscle fibres and counters the run-down of ion gradients for Na+ and K+ during muscle contractions [1,2,3]. It comprises an α and β subunit with several isoforms to form multiple isozyme complexes in a tissue-specific manner [4,5,6]. In skeletal muscle, NKA complexes reside mainly with a catalytic α subunit (α1-4) and a structural glycosylated β subunit (β1-3) [3,7,8,9]. Proteins belonging to the FXYD family anchor and regulate NKA, of which FXYD1, also known as phospholemman, is the most well described and prevalent in skeletal muscle [10,11,12,13]. However, several other members of the FXYD family exist, possibly adding further isozyme heterogeneity and specificity between muscle fibres [3,14]. FXYD5 is a dysadherin-related single-pass type I membrane glycoprotein that regulates NKA. While mainly expressed in epithelial tissues and markedly upregulated in carcinomas [15,16], FXYD5 is also expressed in skeletal muscle [15,16,17,18]. However, not much is known about FXYD5 in human skeletal muscle. Persons with spinal cord injuries express muscle FXYD5 at >10-fold higher levels than healthy comparators [18], which implies that muscle activation regulates FXYD5 expression. Thus, it is likely that FYXD5 expression in skeletal muscle is exercise-responsive, similar to the FXYD1 auxiliary protein [19,20]. Human skeletal muscle tissue is heterogeneous. It consists of muscle fibres with different functional and metabolic characteristics [21], which typically are classified as slow- or fast-twitch, depending on their expression of myosin heavy chain (MHC) isoforms. Given that muscle tissue also comprises other cell types, including endothelial, inflammatory, and neural cells, as well as connective tissue, emphasises the need for a refined single muscle fibre analysis to provide a homogenous and cleaner portrayal of muscle fibre characteristics [12,21]. NKA subunits, including FXYD1, demonstrate some muscle fibre-type specificity, are influenced by sex, and exhibit remarkable adaptability to exercise training and inactivity [3,22,23,24,25]. The putative role of FXYD5 in the regulation of NKA and, hence, K+ shifts during muscle contractions is unknown in humans. Boon et al. [ 2012] speculated that FXYD5 upregulation in spinal cord injury patients could be a compensatory mechanism to facilitate NKA activity, as these patients had low NKA expression. However, in cell models, FXYD5 decreases the degree of glycosylation of NKAβ1 and destabilises the NKA complex [15,16,26]. Therefore, it is possible that exercise training leads to a greater distribution of glycosylated NKAβ1 in skeletal muscle. This calls for an in-depth investigation of the muscle fibre type-specific responsiveness of FXYD5 to a period of exercise training and its putative role in glycosylated NKAβ1 and K+ regulation of contracting muscles during exercise in humans. Thus, we examined muscle fibre type-specific adaptations in FXYD5 and glycosylated NKAβ1 in response to a period of high-intensity interval training (HIIT) in young males. Since spinal cord injury markedly increases muscle FXYD5 content, we hypothesised that HIIT would lower muscle FXYD5 abundance and consequently increase the relative distribution of glycosylated NKAβ1. Furthermore, we investigated the effect of HIIT on the abundance of NKAα2 and β1, in addition to functional measures of K+ regulation and performance during isolated muscle exercises. Last, we examined sex and muscle fibre-type differences in FXYD5 abundance. ## 2.1. HIIT Counters Exercise-Related K+ Shifts and Enhances Muscle Performance Nine habitually active young males performed a 6-week HIIT intervention comprising 3 weekly sessions of 1-min all-out intervals on indoor spinning bikes interspersed by 2-min active recovery repeated 5 times during the first week and progressively increasing to 10. Subjects were 23.8 ± 2.5 years (mean ± SD), had a VO2max of 47 ± 7 mL⋅min–1⋅kg–1, and a BMI of 23.3 ± 1.4 kg⋅m–2. The 6-week period with HIIT lowered ($$p \leq 0.023$$) femoral venous plasma K+ concentrations during knee extensor exercise at high intensity but not significantly at low and moderate intensity (Figure 1A). Femoral venous plasma K+ concentrations reached similar levels at task failure from high-intensity incremental exercise before and after HIIT, but task failure incurred much later after HIIT (220 ± 102 vs. 119 ± 99 s, $p \leq 0.0001$) (Figure 1A). In the immediate recovery from exercise 0–3 min after task failure, femoral venous plasma K+ concentrations declined ($$p \leq 0.006$$) more after HIIT than before (Figure 1A). Femoral arterial plasma K+ concentrations did not change with HIIT (Figure 1B). Leg K+ release rate was lower during exercise at high intensity after HIIT than before (0.5 ± 0.8 vs. 1.0 ± 0.8 mmol·min–1, $$p \leq 0.008$$) (Figure 1C), while cumulated leg K+ reuptake 0–3 min into recovery was greater after HIIT than before (2.1 ± 1.5 vs. 0.3 ± 0.9 mmol, $$p \leq 0.007$$) (Figure 1C). ## 2.2. HIIT Downregulates Muscle FXYD5 Independent of Changes in NKA Isoforms A total of 630 single muscle fibres from nine males who completed the HIIT intervention revealed some inter-subject variability that partially violated normality (for type IIa fibres after HIIT) (Figure 2A). Mixed model analysis on log-transformed FXYD5 abundance values showed an effect of HIIT, which was driven by a reduction of FXYD5 abundance in type IIa muscle fibres ($$p \leq 0.009$$) but not in type I fibres (Figure 2B). Pearson correlation coefficient analysis showed that the muscle log-FXYD5 abundance correlated with maximal oxygen consumption (VO2max) (r = –0.532, $$p \leq 0.023$$) in type II fibres only (Figure 2C). NKAα2 and β1 subunit abundance did not change significantly with HIIT in either fibre type (Figure 2D,E). ## 2.3. HIIT Increases Muscle NKAβ1 Glycosylation The degree of NKAβ1 glycosylation was not different between type I and type IIa muscle fibres (1.45 ± 0.22 vs. 1.46 ± 0.18, $$p \leq 0.946$$). HIIT raised the NKAβ1 glycosylation ratio in type IIa muscle fibres from 1.12 ± 0.11 before to 1.80 ± 0.30 after HIIT ($$p \leq 0.037$$) but not in type I muscle fibres ($$p \leq 0.206$$) (Figure 3B). For type IIa muscle fibres, Spearman’s rho revealed a significant negative correlation between FXYD5 abundance and NKAβ1 glycosylation ratio (r = −0.577, $$p \leq 0.012$$), whereas no such relation was apparent in type I fibres (r = −0.188, $$p \leq 0.485$$). ## 2.4. Fibre Type-Specific FXYD5 Abundance and Influence of Sex To determine sex- and fibre type-specific differences in FXYD5 abundance, we dissected and pooled around 1050 single fibres of biobank vastus lateralis biopsies obtained from 30 trained males and females ($$n = 15$$ from each sex) matched for age (21–35 years). The analysis revealed some inter-subject variability and skewness for FXYD5 abundance in both type I and IIa fibres that violated normality (Figure 4A). Thus, we used log-transformed FXYD5 data for subsequent comparative statistical analyses. Mixed model analysis showed no sex differences in FXYD5 abundance between trained males and females ($$p \leq 0.872$$). Furthermore, the analysis revealed no apparent fibre type differences, though the abundance was numerically, but non-significantly, higher in type IIa fibres than type I fibres in males ($$p \leq 0.181$$) (Figure 4B). ## 3. Discussion The key findings of this study were that HIIT downregulated FXYD5 and increased the relative distribution of glycosylated NKAβ1 in type IIa muscle fibres of young males. These adaptations occurred independent of changes in NKAα2 and NKAβ1 abundance and were associated with improved K+ regulation and muscle performance during intense knee extensor exercise. Thus, our findings highlight FXYD5 as a potential player in the complex regulation of NKA and K+ shifts during muscle contractions. The finding that HIIT downregulated FXYD5 agreed with our working hypothesis. While this effect only was evident in type IIa muscle fibres, the finding extends to the opposite phenomenon observed in patients with spinal cord injury, in which FXYD5 abundance in mixed muscle homogenates is markedly upregulated [18]. This implies that muscle activity and innervation regulate FXYD5 expression in human muscle fibres. However, electrical pulse stimulation of human cultured myotubes for 48 h, as a model of chronic muscle activity, upregulated FXYD5 abundance, while innervation did not affect its abundance [17]. Discrepancies between the in situ and in vitro findings may reflect that other factors also regulate FXYD5 in muscle fibres, including the metabolic and hormonal milieu. HIIT induces pronounced muscle metabolic disturbances and hormonal fluctuations [27,28,29,30] that are difficult to replicate in cells [31]. Several circulating hormones have also been shown to affect the expression of NKA. For example, adrenal hormones cortisol (glucocorticoids), aldosterone, and epinephrine (and adrenergic compounds) have all been shown to regulate NKA expression in skeletal muscle [1,32,33,34]. The downregulation of FXYD5 with HIIT occurred despite no concomitant changes in NKAα2 and β1 abundance, which indicates that the repression of FXYD5 arose independently of a change in the number of NKA complexes. This is similar to FXYD1, which can exhibit a fibre type-specific responsiveness to exercise training independent of changes in NKAα and β subunits [35]. The lack of change in NKAα2 and β1 abundance, irrespective of fibre type, was nevertheless surprising, as HIIT generally upregulates NKA isoforms [22,36,37,38,39]. However, not all HIIT studies found an effect on NKAα2 and β1 abundance [40,41,42], and studies have demonstrated substantial fibre type specificity in the responsiveness of NKA isoforms to exercise training [24,43,44]. This emphasises the importance of performing fibre type-specific analyses when determining NKA subunits and FXYD adaptability to exercise training, as demonstrated in this and other studies [3,45]. The implications of a lower abundance of FXYD5 with HIIT likely means that membrane-bound NKA complexes will be under less FXYD5-mediated deglycosylation of NKAβ1 [15,16,26]. We observed that HIIT not only increased the relative distribution of glycosylated NKAβ1 in type IIa muscle fibres but also that the degree of glycosylated NKAβ1 correlated inversely with FXYD5 abundance. Given that a greater distribution of glycosylated NKAβ1 may stabilise NKA complexes [15,16,26], such an adaptation could be of importance during intense muscle activity, where metabolic perturbations and redox disturbances compromise NKA function [3]. Indicative of improved NKA function, we observed that HIIT enhanced leg muscle performance and countered exercise-related K+ shifts, as reflected by a lower leg K+ release and femoral venous K+ accumulation during intense exercise and greater leg K+ reuptake during recovery. Furthermore, FXYD5 abundance in type IIa muscle fibres correlated inversely with VO2max. This collectively implies that FXYD5 contributes to the complex regulation of NKA and may have a role in K+ regulation in skeletal muscle during exercise and, hence, influence ionic disturbances and fatigue development. Similar to that of FXYD1 [12], we observed no apparent differences between the fibre types in FXYD5 abundance. However, human muscle fibre-type differences in NKA isoforms have been shown with some inconsistency. β2 subunit expression, in particular, appears fibre type-specific, with a higher abundance in type II muscle fibres than in type I of young and aged individuals [23,24,35], whereas this does not seems to be the case for the β1 subunit [12,23]. For NKAα2, its abundance was greater in type II muscle fibres than in type I fibres of recreationally active males in some [12,35], but not all, studies [23,24]. Thus, muscle fibre-type differences appear isoform-specific in humans and are not apparently evident for the auxiliary members of the FXYD family. We also observed no sex differences in FXYD5 abundance for either muscle fibre type. Murphy et al. [ 2007] observed a higher muscle mRNA expression of the NKAα3 and β3 subunits for recreationally active males than females but not for either the total NKA content or maximally stimulated activity. A putative role of sex hormones, testosterone, and oestrogen in the regulation of NKA abundance has been shown in rat soleus muscle [46] and cardiomyocytes [47], respectively. Furthermore, the oestrogen receptor has been implicated in the regulation of dysadherin in multiple large-scale studies on cancer progression [48]. Hence, it is likely that sex hormones play some part in the expression of NKA isoforms in human skeletal muscle but not clearly for FXYD5—at least not in young, trained individuals. The beneficial health and performance-related effects of exercise are indisputable [49,50]. The bulk of these effects lie in the exceptional exercise-responsiveness of skeletal muscle [21,51,52]. While it is well known that NKA isoforms and FXYD1 are among the most exercise-adaptive proteins and contribute to enhancing muscle fatigue resilience and performance [3], the present study extends previous studies on the regulation of NKA [3,22] by demonstrating that FXYD5 may also be a part of the complex exercise-related regulation of NKA. A limitation of our longitudinal training study was the small sample size. However, almost all the males undergoing the training intervention had a variable repression of FXYD5 abundance in type IIa fibres (eight out of nine). Furthermore, the three subjects who had a particularly large reduction in FXYD5 abundance with training had a concomitantly large increase in the relative distribution of glycosylated NKAβ1. In summary, our findings demonstrate that FXYD5 exhibits muscle fibre type-specific adaptability to HIIT performed at the near-maximal intensity in young males. While FXYD5 abundance in type I muscle fibres was unrelated to the fitness level and did not respond to HIIT, its abundance in type IIa muscle fibres was associated with fitness level and declined in response to 6 weeks of HIIT. The downregulation of FXYD5 in type IIa muscle fibres was associated with a greater relative distribution of glycosylated NKAβ1 after HIIT. These adaptations were likely independent of a change in the number of NKA complexes, as NKAα2 and β1 abundance did not change with HIIT and was associated with an enhanced muscle endurance and lower muscle K+ release and accumulation of femoral venous K+ during intense exercise. Collectively, this highlights FXYD5 as a possible exercise-responsive regulator of the degree of NKAβ1 glycosylation that contributes to the complex regulation of NKA in skeletal muscle and, hence, K+ shifts during muscle contractions in humans. ## 4.1. Subjects Nine habitually active, but otherwise untrained, young males participated in this longitudinal training intervention study comprising 6 weeks of HIIT. Before inclusion, subjects received oral and written information about the contents and risks of the study, and each subject gave oral and written informed consent. Inclusion criteria were healthy males, aged 18–40 years, maximal oxygen consumption (VO2max) 45–55 mL⋅min–1⋅kg–1, and BMI 19–26 kg⋅m–2. Exclusion criteria were abnormal electrocardiogram, chronic disease, ongoing medical treatment, and smoking. The study was approved by the Committee on Health Research Ethics of the Capital region (H-17004045) and conducted in accordance with the Declaration of Helsinki [2013]. The study was registered at clinicaltrials.gov (NCT03317704). ## 4.2. Assessment of Eligibility and Familiarisation For the assessment of eligibility, subjects underwent a medical examination consisting of a health questionnaire about previous events and medicine use, as well as a heart and lung auscultation, followed by an electrocardiogram. Then, subjects completed an incremental test to exhaustion on a bike ergometer (Monark LC7TT, Monark Exercise, Vansbro, Sweden) to determine VO2max and exercise capacity. Following a short break, subjects were familiarised with one-legged knee extensor exercise and were instructed in contracting the quadriceps while relaxing the thigh during knee flexion and maintaining a cadence of 60 RPM. At least two days after the screening, subjects returned to the laboratory for a familiarisation visit, where subjects performed a one-legged knee extensor incremental test to task failure for determination of incremental peak power output of the leg (Wmax). The protocol started at 12 W and increased by 6 W⋅min–1 until task failure, which was defined as an inability to maintain a cadence of 60 RPM for 10 s or a drop-in cadence below 55 RPM, despite strong verbal encouragement. Wmax was calculated from task failure in a time-dependent manner, considering the amount of time spent on the last increment. Leg Wmax of the subjects was 61 ± 14 W. ## 4.3. Pre- and Post-Training Intervention Trials Before and after the 6-week training intervention comprising HIIT 3 times weekly, subjects underwent an experimental trial. Subjects met at the laboratory in the morning after an overnight fast and rested in a supine position for 10 min. Hereafter, subjects received a standardised meal with 500 mL water and rested for two hours. During this period, we inserted catheters (20 gauge, Teleflex, Wayne, PA, USA) into the femoral artery and vein, under local anaesthesia (5 mL Xylocaine®, 20 mg⋅mL–1 lidocaine without adrenaline, AstraZeneca, London, UK) below the inguinal ligament and advanced the catheters proximally with ultrasound guidance (Vivid E9, GE, Healthcare, Waukesha, WI, USA). During the last 15 min of the resting period, we sampled a muscle biopsy at the belly of the vastus lateralis using a Bergström needle with suction [53]. Before biopsy sampling, we applied local anaesthesia (2 mL Xylocaine®). The sampled muscle specimen was quickly washed in ice-cold saline, dried, frozen in liquid nitrogen, and stored at –80 °C until analysis. After the resting period, subjects performed one-legged knee extensor exercise at 60 RPM for 4 min at low intensity ($20\%$ leg Wmax), 4 min at moderate intensity ($40\%$ leg Wmax), and 4 min at high intensity ($90\%$ leg Wmax), followed by increments of 6 W⋅min–1 until task failure as defined above. We collected femoral arterial and venous blood before and during the last minute of each workload until task failure, as well as 1, 2, and 3 min into recovery. Venous blood was sampled ≈6 s after arterial blood to account for the mean transit time of arterial blood through the capillary bed [54]. A trained technician measured the femoral arterial blood flow at the blood sampling time points using ultrasound Doppler (Vivid E9, GE, Healthcare, Waukesha, WI, USA). The post-intervention experimental trial was conducted 3–4 days after the final training session. Subjects were told to refrain from exercise 48 h before the experimental days and caffeine and alcohol 24 h before the experimental days. In addition, subjects recorded their food and fluid intake 24 h before the pre-intervention experimental trial, which was replicated the day before the post-intervention experimental trial. ## Training Intervention During the 6-week training intervention, subjects performed 3 weekly sessions of HIIT on indoor spinning bikes. Training sessions consisted of a 10-min warm-up with two 5-s sprints, followed by 1-min all-out intervals interspersed by 2-min active recovery repeated 5 times during the first week and progressively increasing to 10 intervals during the final week. This type of HIIT effectively augments the capacity for ion transport in skeletal muscle and enhances the ability to counter exercise-related K+ shifts [3,22]. The training sessions were supervised by instructors who provided verbal encouragement during each interval. All subjects had $100\%$ training compliance. ## 4.4.1. Maximal Oxygen Consumption during Incremental Bike Ergometer Exercise The VO2max-test protocol consisted of a 4-min period at 100 W followed by increments in the workload of 25 W⋅min–1 until exhaustion on a bike ergometer. During the test, pulmonary gas exchange was measured breath-by-breath using an online gas analyser (Oxycon Pro, CareFusion, Hoechberg, Germany). VO2max was determined as the highest value reached over a 30-s period. At least two of the following criteria had to be met before the test was approved: a plateau in oxygen uptake despite an increase in workload, a respiratory exchange ratio of above 1.15, or inability to maintain a cadence above 80 RPM for 5 s, despite strong verbal encouragement. ## 4.4.2. Femoral Arterial and Venous Blood Samples and Blood Flow Femoral arterial and venous blood samples were drawn in heparinised syringes and immediately analysed with a blood gas analyser (ABL800 FLEX, Radiometer, Copenhagen, Denmark) for plasma K+ concentration, haemoglobin, and haematocrit. Femoral arterial blood flow was measured using Doppler ultrasonography (Vivid E9) with a linear probe operating at an image frequency of 8.0 MHz and a Doppler frequency of 3.1 MHz, as previously described [55]. Blood flow was measured over a 15-s period before and after each blood sampling, with the average of these blood flows being used for data analysis. ## 4.4.3. Leg Plasma K+ Shifts The net plasma K+ exchange (release or uptake) of the leg was calculated as previously described [56,57], accounting for net transcapillary water exchange (Jv) into or out of the vein:Exchangeion=Fp−Jv·ionv−Fp·iona where ionv and iona are the venous and arterial ion concentrations, respectively. Femoral arterial plasma flow (Fp) was calculated as:Fp=F·1−Hcta100 where F is the femoral arterial blood flow, and Hcta is the arterial haematocrit. Jv was calculated as:Jv=F·HbaHbv·100−Hctv100−Hcta−1 where Hba and Hbv are the arterial and venous haemoglobin concentrations, respectively, and Hctv is the venous haematocrit. ## 4.4.4. Human Muscle Single Fibre Dissection We used a microscope and fine forceps (Fine Science Tools GmbH, Heidelberg, Germany) to dissect sections of single human muscle fibres from freeze-dried biopsy samples as described previously [21,32]. Around 35 single fibre pieces 1–2 mm in length were collected from each muscle sample and placed in the bottom of a 0.5 mL tube and spun at 2000× g using a table centrifuge (Kinetic Energy 26 Joules Galaxy Mini Centrifuge, VWR, Søborg, Denmark) before each single fibre piece was dissolved in 10 µL of 3 × sample buffer (6 × Laemmli buffer: 7 mL 0.5 M Tris base, 3 mL glycerol, 0.93 g DTT, 1 g SDS, and 1.2 mg bromophenol blue diluted 1:1 with 0.5 M Tris base) and vortexed thoroughly. After another short table centrifugation step, the fibre type was determined by dot blotting, as described below. ## 4.4.5. Fibre Typing Using Dot Blotting We determined muscle fibre types using dot blotting, as previously described [58]. We activated PVDF membranes in $96\%$ ethanol for 15–30 s and then equilibrated them for 5 min in transfer buffer ($0.58\%$ Tris base, $0.29\%$ glycine, $0.015\%$ SDS, and $20\%$ ethanol). The wet membranes were then placed on a stack of filter papers, where two wet pieces soaked in transfer buffer were on top of three dry pieces. We next aliquoted 1 µL, corresponding to $\frac{1}{10}$ of the dissected fibre segment, and spotted it on two separate membranes. Samples obtained from the same biopsy were spotted on the same two membranes. After complete absorption of the samples, we moved the membranes to a filter paper to dry for ≈5 min. The dried membranes were reactivated in $96\%$ ethanol for 15–30 s and equilibrated in transfer buffer for 5 min. After three quick washes in Tris-based saline with $0.1\%$ Tween-20 (TBST), we blocked the membranes with $2\%$ skimmed milk in TBST for 5 min at room temperature on a rocking table. We then rinsed the membranes with TBST before incubation of the two identical membranes with either an MHCI (A4.840) or MHCIIa (A4.74) antibody (diluted 1:200 in $3\%$ BSA in TBST, Developmental Studies Hybridoma Bank, University of Iowa, USA) for 2 h gently rocking at room temperature. After incubation in the primary antibody, we washed the membranes in TBST before a 1-h incubation with an HRP-conjugated goat anti-mouse secondary antibody (1:5000 in $2\%$ skimmed milk TBST, P-0447 Dako, Glostrup, Denmark) at room temperature on a rocking table. Membranes were then washed three times in TBST and exposed to an enhanced chemiluminescence (ECL) reagent (Immobilon Forte Western HRP substrate, Merck Millipore, Darmstadt, Germany) and imaged (ChemiDoc MP Imaging System, Bio-Rad, Hercules, CA, USA). We determined each sample to be a type I or type IIa fibre based on signal intensities. Only fibre segments with a clear signal concomitant and no signal in the opposite staining were included in further analyses (Figure 5A). Hence, hybrid fibre segments (signals in both stainings) and potential type IIx fibres (no signal in both stainings) were not used for further analyses. We then pooled all type I and type IIa fibres for each subject and time point. ## 4.4.6. Immunoblotting and SDS Page We performed immunoblotting on muscle fibre pools, as previously described [59]. We loaded an equal amount of the pooled type I and type IIa fibres from the same subject on the same gel (4–$15\%$ TGX Stain-FreeTM, Bio-Rad), together with two protein markers (Precision plus all blue, Bio-Rad) and three human skeletal muscle standard samples, obtained as a pool of samples. After SDS-page gel electrophoresis, proteins were transferred semi-dry to a PVDF membrane. The total protein amount loaded in each lane was determined as the stain-free signal by 5 min of UV light incubation of the gels before a digital picture was obtained (ChemiDoc MP Imaging System, Bio-Rad, Hercules, CA, USA). The same part of the gels (5–50 kDa for FXYD5 analyses) was placed on one membrane. The empty parts on the membrane were blocked with either $2\%$ skimmed milk or $3\%$ BSA in TBST before overnight incubation with a primary antibody. The following antibodies were used with the migration of the quantified signal noted: NKAα2: 100 kDa, 07-647 (Merck Millipore, Darmstadt, Germany); NKAβ1: 40–50 kDa, MA3-930 (Affinity Bioreagents, Golden, CO, USA); and FXYD5: 19–40 kDa, HPA010817 (Merck Sigma-Aldrich, Darmstadt, Germany) (see validation below). The membrane was washed in TBST, incubated for 1 h in HRP-conjugated secondary antibody (goat anti-mouse: P-0447 DAKO, Glostrup, Denmark and goat anti-rabbit: 4010-05 (Southern Biotech, Birmingham AL, USA) at room temperature and washed 3 × 15 min in TBST before the bands were visualised with an ECL reaction and signals recorded with a digital camera (Bio-Rad, Hercules, CA, USA). Densitometry quantification of the immunoblotting band intensities was done using Image Lab version 4.0 (Bio-Rad, Hercules, CA, USA) and determined as the total band intensity adjusted for the background intensity. A three-point standard curve on each gel was used to confirm that the loaded amount of samples was capable of determining differences between samples by the signal intensity being on the linear and steep part of the standard curve. Either the average of the triplicate human standard sample signal loaded across each gel or the average of all pooled single fibre samples was used for the normalisation of all samples on the gel to allow for semi-quantitative comparisons across gels and subjects. ## 4.4.7. FXYD5 Antibody Validation and Specificity We tested the specificity of two anti-FXYD5 antibodies (HPA010817, Merck Sigma-Aldrich and sc-166782, Santa Cruz Biotechnology, Dallas, TX, USA). Both antibodies showed multiple signals from 19 to 40 kDa in human skeletal muscle homogenates and FXYD5 overexpression (OE) cell lysates compared to the control (C) (LY408093, OriGene Technologies, Rockville, MD, USA), indicating that the abs recognise FXYD5 (Figure 5B,C). Afterwards, we tested the effect of the amount of protein loaded. With a low amount of protein loaded onto the gels, equivalent to a single muscle fibre, only the 40-kDa band was present. However, bands below 40 kDa were present when 3 pooled fibres were loaded, indicating that it is possible to detect FXYD5 in both single fibres (single band at ~40 kDa) and homogenates (multiple bands), while the amount of protein is important to visualise all bands (Figure 5D). According to the UniProt database, human FXYD5 is a 178 amino acid and 19 kDa protein (canonical sequence) with potential isoforms. However, given that FXYD5 is subjected to post-translational O-glycosylation [60,61] and due to “abnormal electrophoretic mobility” [16], it migrates with varying weights, as shown in mice (24–55 kDa) [16,60,61], Xenopus oocytes (24 kDa) [16], MIA PaCa-2 and Panc-1 cells (30–45 kDa) [62], A549 human lung cancer cells (32–55 kDa) [63], and the present study (19–40 kDa). Since FXYD5 migrated around 40 kDa in our human muscle samples, we tested if the antibodies bound to actin. The stain-free signal indicated that the total amount of protein was similar between OE and C and that actin (~42 kDa) was not highly expressed in these samples (Figure 5E). Incubation with an anti-actin antibody (A2066, Merck Sigma-Aldrich, Darmstadt, Germany) revealed no presence of actin in FXYD5 overexpression cell lysates (OE), while it showed expected strong signals in the human skeletal muscle samples (Figure 5F). Thus, the stronger positive signals with two different commercial antibodies (19–40 kDa) in FXYD5 overexpression cell lysates than in the control samples (Figure 5B,C) are not due to binding to actin. From these ab tests, we concluded that both abs bound specifically to FXYD5 proteins in human skeletal muscle samples and used the HPA010817 antibody (Merck Sigma-Aldrich, Darmstadt, Germany) to determine the FXYD5 abundance in human skeletal muscle. ## 4.4.8. NKAβ1 Glycosylation NKAβ1 is glycosylated at three N-linked glycosylation sites, and because of this, it migrates with a double band between 40 and 50 kDa in human skeletal muscle (Figure 3A). We confirmed that NKAβ1 glycosylation caused the two-band signal in human muscle samples using a deglycosylation kit (P0753, Lambda Protein Phosphatase, New England BioLabs, Ipswich, MA, USA). We added either 1 unit of N-glycosidase per 40 µg protein or a control buffer without N-glycosidase to a human skeletal muscle lysate and incubated the lysate at 37 °C for 60 min. Total deglycosylated NKAβ1 migrated at 35 kDa, whereas the control samples and the original human muscle sample migrated at 40–50 kDa (Figure 3A). Thus, to determine the relative distribution of glycosylated NKAβ1 in the single fibre pools before and after HIIT, we calculated the ratio between the most and least glycosylated NKAβ1 subunits (upper and lower bands between 40 and 50 kDa, respectively, Figure 3B). ## 4.4.9. 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--- title: 'Factors Associated with COVID-19 Death in a High-Altitude Peruvian Setting during the First 14 Months of the Pandemic: A Retrospective Multicenter Cohort Study in Hospitalized Patients' authors: - Fátima Concha-Velasco - Ana G. Moncada-Arias - María K. Antich - Carolina J. Delgado-Flores - Cesar Ramírez-Escobar - Marina Ochoa-Linares - Lucio Velásquez-Cuentas - Homero Dueñas de la Cruz - Steev Loyola journal: Tropical Medicine and Infectious Disease year: 2023 pmcid: PMC10051565 doi: 10.3390/tropicalmed8030133 license: CC BY 4.0 --- # Factors Associated with COVID-19 Death in a High-Altitude Peruvian Setting during the First 14 Months of the Pandemic: A Retrospective Multicenter Cohort Study in Hospitalized Patients ## Abstract Risk factors for COVID-19 death in high-altitude populations have been scarcely described. This study aimed to describe risk factors for COVID-19 death in three referral hospitals located at 3399 m in Cusco, Peru, during the first 14 months of the pandemic. A retrospective multicenter cohort study was conducted. A random sample of ~$50\%$ ($\frac{1225}{2674}$) of adult hospitalized patients who died between 1 March 2020 and 30 June 2021 was identified. Of those, 977 individuals met the definition of death by COVID-19. Demographic characteristics, intensive care unit (ICU) admission, invasive respiratory support (IRS), disease severity, comorbidities, and clinical manifestation at hospital admission were assessed as risk factors using Cox proportional-hazard models. In multivariable models adjusted by age, sex, and pandemic periods, critical disease (vs. moderate) was associated with a greater risk of death (aHR: 1.27; $95\%$CI: 1.14–1.142), whereas ICU admission (aHR: 0.39; $95\%$CI: 0.27–0.56), IRS (aHR: 0.37; $95\%$CI: 0.26–0.54), the ratio of oxygen saturation (ROX) index ≥ 5.3 (aHR: 0.87; $95\%$CI: 0.80–0.94), and the ratio of SatO2/FiO2 ≥ 122.6 (aHR: 0.96; $95\%$CI: 0.93–0.98) were associated with a lower risk of death. The risk factors described here may be useful in assisting decision making and resource allocation. ## 1. Introduction Peru has the highest mortality worldwide [1]. Although Peru promptly implemented several non-pharmaceutical interventions at individual and population levels, such as physical distancing, use of masks, mandatory lockdowns, restrictions on gatherings, travel-related restrictions, and closure of non-essential services and workplaces, the SARS-CoV-2 spread rapidly throughout the country and the disease burden overwhelmed the health system [2]. The precarious organization of the Peruvian health system, healthcare disparities, shortage of medical oxygen, and the scarcity of Intensive Care Units (ICUs) and specialized healthcare personnel were factors that contributed to high mortality rates, particularly during the second wave of the COVID-19 pandemic [3,4,5]. A large proportion of deaths is expected in a hospital setting, since most of the attended patients are comorbid and have severe or critical diseases, thus requiring highly specialized care [6]. In this scenario, multiple biological and non-biological factors associated with death have been described; male, older age, comorbidities (such as hypertension and diabetes), hypoxemia, inflammation, availability, need for mechanical ventilation, and ICU admission [7,8,9]. Numerous investigations have evaluated factors associated with COVID-19 death in hospitalized patients; most of them have been conducted over a short period, and only a few of them have been conducted in Peru [10,11,12,13,14,15]. Of the studies carried out in Peru, one included information from three healthcare centers [12] and another described factors associated with ICU admission among hospitalized patients in a high-altitude setting [10]. Peru has been greatly affected by the pandemic. This situation resulted in an overwhelmed and fragmented health system that contributed to high and heterogeneous mortality rates between Peruvian cities and regions. The scarce characterization of death-related factors creates a knowledge gap and limits targeted efforts and decision making, as well as the implementation of population-specific interventions. The characterization of factors associated with COVID-19 death in a high-altitude Peruvian setting could contribute to the understanding of the COVID-19 mortality rate and address a knowledge gap. Here, we describe risk factors for COVID-19 death in three high-altitude health centers in Cusco, Peru, during the first 14 months of the pandemic. ## 2.1. Study Design and Sites A retrospective multicenter cohort study was conducted in adult (≥18 years old) hospitalized patients in three tertiary referral hospitals in the region of Cusco, Peru. Hospital Regional del Cusco (HRDC), Hospital Nacional Adolfo Guevara Velasco—EsSalud (HNAGV), and Hospital Antonio Lorena (HAL) are high-altitude healthcare facilities located in the capital of the Cusco region (13°31′30″ S 71°58′20″ W), at an altitude of 3399 m in the Peruvian Andes. These hospitals care for approximately 1.2 million people who live in the region and people who are referred from nearby localities [16]. Given the level of complexity and geographical location, the three hospitals were designated for the care of all suspected and confirmed COVID-19 cases in Cusco. According to the Regional Health Administration (GERESA) of Cusco, a total of 77,843 COVID-19 cases and 1321 deaths related to COVID-19 were recorded in 2020, resulting in a mortality rate of 9.7 per 10,000 inhabitants and a case fatality rate (CFR) of $1.7\%$. By 2021, a total of 79,654 cases and 2991 deaths were recorded, resulting in a mortality rate of 22.0 per 10,000 inhabitants and a CFR of $3.8\%$ [17]. The research and its secondary data analysis were approved by the Institutional Review Board of the Universidad Continental (019-2022-VI-UC) and by GERESA of Cusco. Hospitals also approved the study protocol and its procedures. ## 2.2. COVID-19 Death Definition A COVID-19 death was defined as the death of a subject who met laboratory and/or imaging criteria. The laboratory criterion was composed of two components: (i) a positive reverse transcription-polymerase chain reaction (RT-PCR) and/or COVID-19 antigen test result using a nasopharyngeal swab, and/or (ii) the detection of IgM, IgM/IgG, or IgG by a serological COVID-19 rapid test using blood or serum/plasma. The subject had to meet at least one component of the laboratory criteria within 21 days before or after the hospital admission. This time frame was used because most life-threatening pulmonary complications occur in that period [18,19]. The imaging criterion was also composed of two components, and the subject had to meet at least one of them; (i) a score of at least 4 on the last computed tomography (CT) scan of the lungs according to the COVID-19 reporting and data system (CO-RADS) classification [20,21], and (ii) pulmonary infiltrate compatible with the “typical appearance” of COVID-19 pneumonia on the last CT scan [21]. ## 2.3. Data Sources and Collection Medical records of all deaths, including those caused by or related to COVID-19, are systematically and routinely recorded in the National Death Registry Information System (SINADEF; https://bit.ly/3hjRbOA; accessed on 1 July 2021) within the first 24 h, as required by Peruvian regulations. A retrospective search was conducted on 1 July 2021 in the SINADEF database listing U07.1 and/or U07.2 (International Classification of Diseases (ICD), 10 revision), and/or with any term related to COVID-19, including “COVID”, “SARS”, and/or “pneumonia”. Terms were included as part of the selection criteria since COVID-19 deaths may not have been correctly recorded using ICD-10 codes, but may have included contributing conditions that can later be used to correctly classify the record [22,23]. The search was restricted to hospitalized adult subjects with residence in Cusco who died between 1 March 2020 and 30 June 2021 in any of the three hospitals. The search resulted in 2674 death records, of which 1225 ($45.8\%$) were selected by a simple sampling method using random numbers generated in Epidat v4.1. To assess a potential selection bias associated with sampling, epidemiological curves (Figure 1) were constructed and compared using the dates of death registered in all records ($$n = 2674$$) and the selected records ($$n = 1225$$). As the pattern of deaths was comparable, it is reasonable to assume that there was a low risk of systematic bias introduced by sampling. Then, selected records were cross-referenced with individual medical records at each hospital by research-trained personnel for full data extraction (Figure 2). Using the definition of COVID-19 death described above, a total of 993 subjects who met the laboratory and/or imaging criteria were identified (Figure 2). However, sixteen records were excluded because subjects arrived dead at the hospital and therefore were not hospitalized ($$n = 15$$), or because records had incomplete data ($$n = 1$$). In Table 1, information on the 977 subjects is summarized according to the COVID-19 definition of death used in this study. Epidemiological, demographic, and clinical data were extracted from medical records by research-trained physicians and nurses using a standardized form. All entries were de-identified to preserve patient confidentiality, and then the quality control was assessed by two research-trained physicians. In case of discrepancies, a third research-trained physician adjudicated the difference. ## 2.4. Outcome The outcome of interest was time to death among hospitalized COVID-19 cases. The start and end of the follow-up time were defined by the patient’s admission to the hospital (time 0) and death, respectively. ## 2.5. Covariates Demographic and clinical variables were collected at the hospital admission from patients’ medical records and then evaluated as predictors of death. Age (years), sex, and comorbidities, including cardiovascular disease (includes hypertension), diabetes, chronic lung disease, chronic neurological and neuromuscular disease, liver disease, cancer, and immunodeficiency (includes HIV/AIDS), were collected. COVID-19 disease severity (moderate, severe, or critically severe) was defined as described elsewhere [24], and registered symptoms such as respiratory distress, malaise, cough, fever (axillary temperature ≥ 37.3 °C) or chills, headache, chest pain, sore throat, muscle pain/aches, irritability or confusion, nasal congestion, arthralgia, nausea or vomiting, diarrhea, and abdominal pain were also collected. Data such as respiratory rate (breaths per minute), heart rate (beats per minute), the respiratory rate–oxygenation (ROX) index [25], the oxygen saturation to fraction of inspired oxygen ratio (SatO2/FiO2) [26], ICU admission, invasive mechanical ventilation, time elapsed from symptom onset to hospitalization, and time from hospitalization to death were also collected. ## 2.6. Statistical Analysis Categorical variables were described as n (%), and continuous variables as median and interquartile ranges (IQR). Three continuous variables were categorized as follows: age, <60 and ≥60 years; ROX index, <5.3, ≥5.3 to <13.5, and ≥13.5; and SatO2/FiO2, <122.6, ≥122.6 to <286.8, and ≥286.8 [27]. To account for potential changes in the epidemiology of COVID-19 deaths during the study period, we defined five time periods as follows: period I (1 March to 31 July 2020), period II (1 August to 31 October 2020), period III (1 November 2020, to 31 January 2021), period IV (1 February to 30 April 2021), and period V (1 May to 30 June 2021). These periods captured the temporal changes in the incidence of COVID-19 in the Cusco region [17]. Specifically, according to local health authorities, periods II and IV corresponded to the first and second waves of the COVID-19 pandemic, respectively [17]. The Fisher’s exact and Kruskal–Wallis with ties tests were used to assess differences between patient characteristics, comorbidities, symptoms, signs, ICU admission, invasive mechanical ventilation, and times from symptom onset to hospitalization and from hospitalization to death across defined periods. Cox proportional-hazard models were used to explore risk factors associated with COVID-19 death, and the Kaplan–Meier estimator was also used to assess differences in the outcome by ICU admission, invasive respiratory support, and disease severity. The multivariable-adjusted models included age and sex as confounders as described elsewhere [28], and in all models, the intra-group correlation of each hospital was specified. In addition, time-stratified and time-adjusted models were constructed to assess the robustness of the estimates. No other variables were included in the multivariable analysis to avoid overfitting. Crude and adjusted hazard ratios (HR) and their $95\%$ confidence intervals ($95\%$CI) were computed in Stata v17 (StataCorp. 2021. Stata Statistical Software: Release 17. College Station, TX, USA: StataCorp LLC). All tests were two-sided, and p-values < 0.05 were considered significant. ## 3. Results A total of 977 death records from the same number of subjects who died from COVID-19 between May 2020 and June 2021 were analyzed. According to periods, 166 ($16.9\%$) deaths were registered in period I, 329 ($33.7\%$) in II, 68 ($7.0\%$) in III, 299 ($30.6\%$) in IV, and 115 ($11.8\%$) in V. ## 3.1. Characteristics of the Study Population The average age of the subjects who died from COVID-19 was 66.3 years (standard deviation: 12.9), and the proportion ≥60 years was $70.6\%$ (Table 2). Throughout the study period, those aged ≥60 years, males, those not admitted to ICU, those not receiving invasive ventilatory support, and those hospitalized for severe illness were the largest groups (Table 2). The median time from symptom onset to hospitalization was 7 days (IQR: 5–10) and did not vary according to the periods ($$p \leq 0.298$$). The median time from symptom onset to death was 4 days (IQR: 2–9) and varied by periods ($p \leq 0.001$). Specifically, the median time for period I was 6 days (IQR: 3–11), 4 days (IQR: 2–9) for II, 5 days for III (IQR: 2–14), and IV (IQR: 2–9), and 3 days (IQR: 2–7) for V. The most frequent comorbidities were cardiovascular disease ($31.0\%$) and diabetes ($20.7\%$), and the frequency of comorbidities was comparable across all periods (Table 3). Regarding symptoms, respiratory distress ($89.5\%$), malaise ($74.5\%$), cough ($74.4\%$), and fever or chills ($55.5\%$) were the most frequent. Interestingly, the clinical presentation varied significantly between periods (Table 3). However, four symptoms had no significant variation throughout periods: respiratory distress, cough, chest pain, and diarrhea (Table 3). The proportion of subjects with ROX index < 5.3 and SatO2/FiO2 < 122.6 was $35.6\%$ and $34.1\%$ (Table 3), respectively. The signs at hospital admission varied significantly between periods (Table 3). ## 3.2. Factors Associated with COVID-19 Death In the bivariate analysis, a significantly greater risk of death was observed in those aged ≥60 years, and in periods II, IV, and V (vs. period I) (Table 4). In contrast, a significantly reduced risk of death was observed in males, in those admitted to the ICU, in those who received invasive respiratory support (vs. no), and in those with ROX index ≥ 5.3 (Table 4). The survival curves for hospitalized subjects by ICU admission, invasive respiratory support, and disease severity are shown in Figure 3. Specifically, those admitted to ICU and those who received invasive respiratory support exhibited a better probability of survival. The time-dependent probability of survival was comparable across all disease severity groups (Figure 3). In multivariable models adjusted by age, sex, and periods, those with critical illness and those with cough or irritability/confusion had a significantly higher risk of death (Table 4), whereas those admitted to ICU, those who received invasive respiratory support, those with liver disease, those with ROX index ≥ 5.3 or SatO2/FiO2 ≥ 122.6, and those with chest pain, sore throat, or muscle pain/aches had a significantly lower risk of death (Table 4). In the stratified multivariate models, having been admitted to the ICU and having received invasive ventilation was consistently associated with a significantly lower risk of death in nearly all time periods (Table 5). Regarding disease severity, there was an overall trend toward a higher risk of death for those with severe or critical diseases throughout all periods, except for period V. For this last period, the risk of death was lower, although it was not significant (Table 5). Furthermore, a ROX index ≥ 5.3 and SatO2/FiO2 ≥ 122.6 were both associated with a lower risk of death for almost all the evaluated periods. ## 4. Discussion The evaluation of factors associated with death from COVID-19 is still of vital importance. Risk factor studies have found that age >60 years and oxygen saturation below $90\%$ were associated with a higher risk of death [12,13,29,30,31]. In high-altitude settings, two Peruvian studies have suggested that saturation <$80\%$, age between 40 and 60 years, comorbidities, and non-admission to ICU are factors associated with a greater risk of death [10,11]. Similarly, two Colombian studies conducted in a high complexity facility located at an altitude of 2640 m reported that older age and low SatO2/FiO2 ratio at admission were predictors of death [32,33]. Additionally, an Ecuadorian study suggested that in high-altitude settings, cases admitted to the ICU have better survival and disease progression [34]. In this multicenter cohort study conducted in three referral hospitals located in a high altitude setting and during the first 14 months of the pandemic, several variables such as demographic characteristics, ICU admission, invasive respiratory support, disease severity, comorbidities, and symptoms and signs at hospital admission were evaluated as risk factors in hospitalized patients. After controlling for sex, age, and periods, critical illness was associated with a higher risk of death, while ICU admission, invasive respiratory support, ROX index ≥ 5.3, and SatO2/FiO2 ratio ≥ 122 were associated with a lower risk of death. Overall, our results are similar to those that have been reported previously [10,11,32,33,34], and robust even in the stratified analyses performed in this study. Early mechanical ventilation is associated with a reduced release of proinflammatory cytokines (such as IL-6, IL-8, and TNFα) that cause alveolar damage [35,36,37]. The availability of beds in critical care units plays a crucial role in patient care and early response [8,38]. In multiple regions of Peru, the hospital response capacity was substantially expanded and improved by increasing the number of ventilators and the number of available ICU beds; however, the increase was not sufficient, given the weak and fragmented nature of the healthcare system [2]. Our findings suggest that invasive respiratory support and ICU admission were both associated with a reduced risk of death from COVID-19 and improved survival probability. Despite not having formally assessed the response capacity of the hospitals studied across the time period, it is reasonable to hypothesize that greater availability of ventilators and ICU beds would have contributed to reducing deaths and improving the survival of hospitalized patients. As such, greater availability and better redistribution of resources could lead to a reduction in in-hospital mortality [8,38]. Physiological adaptations and genetic characteristics of individuals who live at high altitudes have been described as factors associated with lower mortality, higher probability of hospital discharge, and higher survival [34,39,40,41,42,43]. Notably, the most widely described factors that could account for the lower mortality rates in high-altitude populations are as follows: the hypobaric hypoxia in response to long-term exposure to high altitude and the resulting improved lung capacity, the reduced expression of the angiotensin-converting enzyme, and the higher levels of inflammatory cytokines (such as IL-6 y TNFα), hemoglobin, and erythropoietin [39,40,44,45]. It has also been reported that, compared to individuals residing in low-altitude areas, COVID-19 cases residing in high-altitude areas may present with low levels of fibrinogen and platelets, and disturbed electrolyte levels [46]. On the other hand, high-altitude environmental characteristics such as high ultraviolet radiation and low barometric pressure could play a role in virus survival and virus transmission, respectively [44,47]. However, it has also been suggested that infections, case-fatality rate, risk of death, and/or disease progression may not necessarily be associated with altitude, physiological adaptations, or both [48,49,50,51]. It is plausible to consider that the physiological adaptations, characteristics, and environmental exposures that have been outlined above influence the risks described here; however, their effect could not be estimated in the present study, given the absence of a comparison group. Future studies are needed to validate our findings through comparison with populations living in areas of varying altitudes. The low oxygen saturation within the first 24 h of hospital admission predicts COVID-19 severity and death [52]. The utility of the oxygen saturation assessment could be affected by the oxygen–hemoglobin dissociation curve [53]; thus, the use of complementary parameters such as the ROX index and the SatO2/FiO2 ratio could be required [27]. The PaO2/FiO2 is the gold standard for the diagnosis of respiratory failure and ARDS [54]; however, this is an invasive method that is not always available in healthcare facilities. The ROX index and SatO2/FiO2 ratio are non-invasive clinical parameters that are easy to implement in emergency rooms. In this study, ROX ≥ 5.3 or SatO2/FiO2 ≥ 122 at hospital admission were associated with a lower risk of death. According to our findings, these cut-off values could be useful to discriminate cases with higher or lower risk of death. Future studies are needed to validate these findings. The admission of patients with severe or critical illnesses demands highly specialized care. Based on our findings, patients with severe disease were the most frequently admitted to the hospital, followed by those with a critical illness. While the survival probability of those with severe or critical illnesses was comparable, the overall risk of death was only significantly higher in those with critical illnesses. This greater risk was only significant at the beginning of the first peak (period I) and the second peak (period IV) of the COVID-19 pandemic in Cusco. The inconsistency of this finding across all periods could be related to the lack of statistical power, in particular for periods III and IV, as well as to the low preparedness and collapse of the healthcare system in specific periods with a high number of COVID-19 cases. However, despite the significance, the risk of death was particularly greater for patients with critical illnesses. The risk of death for hospitalized patients with or without diabetes or chronic lung disease was comparable. These findings differ from those reported elsewhere, where it is suggested that these conditions have an impact on mortality [15,55,56,57]. However, the lack of association observed here could be explained by the “diabetes/obesity paradox” and by the physiological readjustment during the critical stage of the disease [58]. Furthermore, we observed that patients with liver disease had a lower risk of death. However, this finding also differs from what has been previously reported [59,60]. It is important to note that several studies have shown contradictory results regarding the association of various comorbidities with COVID-19 death [15,29,61]. Overall, the lack of association between comorbidities evaluated here and COVID-19 death, as well as the observed association between liver disease and death, should be interpreted with caution given that the low number of individuals with comorbidities such as chronic lung or neurological disease, liver disease, cancer, and immunodeficiency could undermine the statistical power to detect differences, and the comorbidities may not have been correctly recorded or diagnosed. Hence, the associations between comorbidities and death described here could be biased. Further studies are needed to determine whether comorbidities, particularly in high-altitude settings, have a major impact on the risk of death from COVID-19. This study has multiple limitations. First, this study is subject to limitations that are inherent to a retrospective study with secondary data analysis. Second, the analyzed data were collected at hospital admission; therefore, disease progression and post-admission events were not considered in the analyses. Third, the type of patient and their management could have been different at each healthcare institution. Although the multicenter design and the intra-group correlation control in all models can be considered strengths, it is still plausible to assume that results are affected by uncontrolled institutional characteristics and/or policies. Fourth, the hospital response capacity (such as the increase in ventilators and ICU beds) and the local dynamics of SARS-CoV-2 variants were not considered in the analysis. It is reasonable to expect that the risk of death would be lower in settings with higher availability of medical resources and that the risk would be greater in settings with the circulation of highly virulent variants that cause greater lung injury. The time-stratified analyses were performed under the assumption that unstudied or unknown conditions affect the estimates. Despite not having observed major differences in the estimates, further studies are needed to understand the effect of these conditions on the risk and survival of hospitalized patients. Finally, the diagnostic performance and the variable availability and supply of laboratory and imaging tests affect the definition of death used in this study. In Peru, RT-PCR was used as a diagnostic test during the first months of the pandemic. Later, RT-PCR was largely replaced by serology tests. RT-PCR and antigen tests have comparable diagnostic utility, whereas the diagnostic use of serology has been widely discussed in acute disease [62,63,64]. Furthermore, the use of CT scans in the diagnosis of COVID-19 is not perfect, and the identification of infiltrate could vary between observers [65,66,67]. Despite the use of a composite definition for COVID-19 death, the use of this definition did not overcome the bias inherent to each test used to construct the definition [68,69]. ## 5. Conclusions In summary, in this multicenter study in a high-altitude Peruvian setting during the first 14 months of the COVID-19 pandemic, we observed that ICU admission, invasive respiratory support, and ROX ≥ 5.3 or SatO2/FiO2 ≥ 122 at hospital admission were associated with a lower risk of death. In contrast, critical illness was associated with a higher risk of death. 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--- title: 'Degassing a Decellularized Scaffold Enhances Wound Healing and Reduces Fibrosis during Tracheal Defect Reconstruction: A Preliminary Animal Study' authors: - Nguyen-Kieu Viet-Nhi - Yen-Chun Chen - Luong Huu Dang - How Tseng - Shih-Han Hung journal: Journal of Functional Biomaterials year: 2023 pmcid: PMC10051568 doi: 10.3390/jfb14030147 license: CC BY 4.0 --- # Degassing a Decellularized Scaffold Enhances Wound Healing and Reduces Fibrosis during Tracheal Defect Reconstruction: A Preliminary Animal Study ## Abstract Few efforts have been made regarding the optimization of porcine small intestinal submucosa (SIS) to improve its biocompatibility. This study aims to evaluate the effect of SIS degassing on the promotion of cell attachment and wound healing. The degassed SIS was evaluated in vitro and in vivo, compared with the nondegassed SIS control. In the cell sheet reattachment model, the reattached cell sheet coverage was significantly higher in the degassed SIS group than in the nondegassed group. Cell sheet viability was also significantly higher in the SIS group than in the control group. In vivo studies showed that the tracheal defect repaired by the degassed SIS patch showed enhanced healing and reductions in fibrosis and luminal stenosis compared to the nondegassed SIS control group, with the thickness of the transplanted grafts in the degassed SIS group significantly lower than those in the control group (346.82 ± 28.02 µm vs. 771.29 ± 20.41 µm, $p \leq 0.05$). Degassing the SIS mesh significantly promoted cell sheet attachment and wound healing by reducing luminal fibrosis and stenosis compared to the nondegassed control SIS. The results suggest that the degassing processing might be a simple and effective way to improve the biocompatibility of SIS. ## 1. Introduction The use of decellularized tissue during surgical procedures in humans for repair and reconstruction has been made possible by using an SIS mesh derived from the porcine small intestinal submucosa (SIS) [1,2,3,4]. SIS mesh is composed primarily of extracellular matrix (ECM) without cellular contents and thus can be widely used for soft tissue repair in many surgeries [5]. However, there have been few explorations on the optimal use of SIS mesh to increase its biocompatibility. Ever since 1998, when SIS was cleared by the FDA for its first clinical applications in wound repair [6], ECM-based porcine SIS has exhibited good biocompatibility and low immunogenicity when reconstructing various types of tissues, including those involving urological diseases such as hypospadias [2] and urinary bladder reconstruction after cystectomy [7]; gynecological illnesses such as cervicovaginal reconstruction [4] and pelvic organ prolapse [8]; and chronic poor healing wounds such as diabetic foot ulcers [9] and stage III or IV pressure ulcers [10]. Moreover, SIS has been used for focal tissue repair in the eardrum [1] and heart valves [11] and for bone augmentation in animal studies [12]. However, the outcomes remain uncertain in several fields in which SIS is used [8,11]. For instance, one retrospective study using SIS in the repair of pelvic organ prolapse revealed the relatively high complication rates ($56\%$) after the operations, leading to the suggestion of little benefit of SIS graft in prolapse surgery [8]. Another study in the pediatric congenital aortic valve repair found a shorter time interval to reintervention and significantly higher odds ratio of the occurrence of moderate aortic regurgitation or stenosis when using SIS compared to the use of autologous pericardium [11]. While SIS holds the potential to promote constructive remodeling at site-appropriate functional tissue [13], whether this material needs to be pretreated or surface-modified before site-specific implantation to increase clinical efficacy warrants more investigation. In tissue engineering, a degassing process is usually adopted to remove cellular contents from an ECM-based scaffold or the air bubbles inside a porous material. Two studies reported that decellularization of porcine tracheal scaffolds using a combined vacuum–enzyme/detergent protocol significantly decreased the fabrication time to 9 days compared to 3–8 weeks without vacuum assistance [14,15]. Another study pointed out the benefit of applying vacuum pressure to increase the penetration of collagen into a poly-L-lactic acid (PLA) scaffold, in which the resultant PLA–collagen composite scaffold showed improved water adsorption and degradation [16]. Currently, degassing processes, or vacuum-assisted methods, are often used to shorten the preparation time and eliminate residual cellular contents in tissue engineering [17,18,19]. Luo et al. showed that the efficiency of decellularization in heart valves treated under vacuum was enhanced, and the elasticity and tensile strength after the decellularization process remained uncompromised [17]. Furthermore, another study demonstrated that the preparation of decellularized tracheal scaffolds with vacuum assistance and optimal DNase I concentration could achieve good effects of decellularization within only two days [19]. In comparison to other previously reported methods of surface modification in SIS such as functional group bonding, protein adsorption, mineral coating, or topography and formatting modifications [20], the relatively simple and practicable degassing process might hold potential in increasing the efficiency of SIS in tracheal luminal wound healing. The study by Negishi et al. [ 16] presented a method to overcome the difficulty of incorporating the heat-sensitive natural polymer collagen into a PLA scaffold by using a vacuum pressure impregnation method. This encouraged us to consider whether the process of degassing would enhance cellular adhesion and proliferation and therefore enhance the biocompatibility and clinical effectiveness of SIS. This study aims to evaluate the efficacy of degassed SIS on the promotion of cell attachment and wound healing and the reduction of fibrosis in an in vitro cell sheet reattachment model and an in vivo tracheal patch defect repair model. ## 2. Materials and Methods The study flow diagram is shown in Figure 1A. In brief, degassed SIS was subjected to an in vitro cell attachment ability test with an NIH-3T3 cell sheet. Following the in vitro evaluation, degassed SIS was evaluated for its ability to facilitate wound healing and reduce fibrosis in a rabbit trachea patch repair model. ## 2.1.1. SIS Mesh Preparation DynaMatrix Plus produced by Cook Biotech Incorporated (1425 Innovation Place, West Lafayette, IN 47906, USA) was used in this study. DynaMatrix Plus is specifically designed to serve as a bioactive soft tissue regeneration product for augmentation procedures. The qualified pig’s small intestinal submucosa (SIS) was harvested and fabricated into an extracellular membrane. The natural composition of matrix molecules such as collagen (types I, III, and IV), glycosaminoglycans (hyaluronic acid, chondroitin sulfates A and B, heparin, and heparan sulfate), proteoglycans, growth factors (FGF-2, TGF-β), and fibronectin were retained in the SIS derivation process. After purchase, the sterilized SIS scaffolds were cut into smaller pieces (10 mm × 10 mm) and divided into two groups and treated with or without degassing. ## 2.1.2. Degassing of the SIS Scaffold A custom-designed vacuum system with a covering cup, medical pump, flexible tubes, and cell culture dishes was used in the degassing process in this study (Figure 1B). First, all devices were sterilized with $75\%$ alcohol and UV irradiation for 15 min. Six pieces of SIS material were placed into a 100 mm culture dish (diameter 100 mm, surface area 56.7 cm2). Then, 2 mL of fresh DMEM (Gibco, Life Technologies Corporation, 3175 Staley Rd., Grand Island, NY 14072, USA) containing $10\%$ fetal bovine serum (EDM Millipore Corp., 290 Concord Rd, Billerica, MA 01821-3405, USA) and $1\%$ penicillin-streptomycin (Gibco, USA) were added to the 100 mm culture dishes. Next, the cup (diameter 45 mm, surface area 15.9 cm2) was placed on the 100 mm culture dish, and the contour of the cup was pressed down slightly to the surface of the 100 mm culture dish. A specific DOW CORNING high vacuum grease (DOW CORNING Corporation, Midland, MI 48686-0994, USA) was used between the contour of the cup and the surface of the 100 mm culture dish. A sterilized flexible tube was used to connect the valve of cup to a standard medical portable suction machine (SPARMAX, Taipei 110, Taiwan) located outside of the hood. The input operating vacuum was set to 650 mm Hg, and the output airflow was set to 20 LPM (liters per min) over 20 min. ## 2.2.1. Preparation of the Cell Culture Inserts According to our previous publication, we used porous polyethylene terephthalate (PET) membranes for chemical surface modification [21,22]. Solutions one and two were prepared by dissolving 0.125 M hyaluronic acid (Kewpie, Japan) in 0.25 M boric acid buffer and EDC/NHS/cystamine (ACROS Organics, Belgium) in 0.25 M boric acid buffer. The final solution (three) was prepared by pouring solution one into solution two for two hours of reaction. Then, a 6-well culture insert with a porous PET membrane (pore size: 430 nm, pore density: 5.63 × 106/cm2, thickness: 12.5 μm) (ANT Technology, Taiwan) was preactivated with low-pressure plasma (PDC-002-HP, Harrick Plasma, USA) at 500 mTorr for 45 min under a carbon dioxide atmosphere. After immersing the PET culture insert in 0.25 M EDC/NHS in 0.25 M boric acid buffer at pH 6.0 and 4 °C for 2 h, the insert was mixed with an equal volume of solution. Continuous shaking was then performed for 4 h. The culture inserts containing HA-modified porous HA-PET with a disulfide bond were gently washed with water and kept dry overnight. Finally, the inserts were sterilized with ethylene oxide gas for future use in culture. ## 2.2.2. Cell Sheet Culture In our previous attempts (unpublished data), we found that nasal epithelial primary cell cultures differ significantly from other cell lines in their ability to attach. Therefore, in our current study, instead of a direct cell seeding model, a cell sheet detachment and reattachment model was used to reveal the effectiveness of degassing the SIS surface as in living healing conditions; the tissue and the SIS interact through surface-to-surface contact. The surface reattachment ability might more accurately reveal the effectiveness of degassing the SIS in promoting tissue healing instead of seeding individual cells on the SIS surface. The NIH/3T3 cell line was chosen based on its rapidly growing property and is relatively stable in creating a condition similar to the cell sheet for reattachment comparison purposes. The NIH/3T3 (mouse) fibroblast cells were purchased from the Bioresource Collection and Research Center, Hsinchu, Taiwan (BCRC no. 60008) and used in this study. A monolayer of the cells was cultured in a 60 mm culture dish (AlphaPlus, Taiwan) in fresh 3T3 medium containing DMEM (Gibco, USA), $10\%$ fetal bovine serum (EDM Millipore Corp., MA 01821-3405, USA), and $1\%$ penicillin-streptomycin (Gibco, USA). The medium was replaced every 3 days, and the cells were maintained in an incubator at 37 °C with $5\%$ CO2. When the density reached approximately $80\%$ confluence, the 3T3 cells were detached with $0.25\%$ trypsin–EDTA (Gibco, USA). Then, the obtained cells were seeded on the cell culture inserts (surface area 3.5 cm2/insert) at a density of 5 × 105 cells/insert in fresh 3T3 medium. After 10 days of culture, the 3T3 cell sheets were harvested from the inserts by adding 5 mL of reducing agent solution, a mixture of 0.279 g of L-cysteine in 0.5 mL of 1 N NaOH and 29.5 mL of PBS. ## 2.2.3. NIH/3T3 Cell Sheet Reattachment to the Scaffold The degassed scaffolds were placed into a new 6-well culture plate. Then, medical tweezers were used to move the harvested cell sheets to the 6-well culture plate. Initially, a few volumes of medium were added to the 6-well culture plate. The 3T3 cell sheets reattached to scaffolds were incubated in the incubator (+37 °C, $5\%$ CO2) for one hour, and then more medium was gently added for two weeks of further culture. The nondegassed scaffolds, as the control group, underwent a similar procedure. ## 2.3.1. Reattached Cell Sheet Surface Analysis After the incubation period, the old medium was removed, and the reattached 3T3 cell sheets were washed twice from the SIS surface. The cell sheet scaffolds underwent the shaking test and the rinsing test. First, the cell sheet scaffolds were shaken by a shaking machine for 10 min at 100 rpm. Then, they were held by medical tweezers, inclined 45 degrees to the surface of the culture plate, and rinsed under PBS solution flow five times. After rinsing, the cell sheet scaffolds were placed into another 6-well plate culture. ## 2.3.2. Reattached Cell Sheet MTT Assay First, 200 μL of MTT reagent (MedChemExpress Co., Ltd., 1 Deer Park Dr, Suite Q, Monmouth Junction, NJ 08852, USA) (final concentration of 0.5 mg/mL) was added to each well containing the reattached SIS cell sheet material, and the plate was placed in an incubator (+37 °C, $5\%$ CO2). After four hours, the MTT solution was removed. Purple crystals were observed on the surface of the SIS material. A standard light was used to take photos of the attached SIS cell sheet. Then, the attachment areas were analyzed by the image processing software ImageJ (version 1.43u) developed by the National Institutes of Health (USA). The color threshold was set to accurately capture the purple area of the MTT-stained attached cell sheet without picking up any signals in the control group (group without the cell sheet). Next, 200 μL of DMSO solution was added to each well. After that, the plates were incubated in the incubator for 10 min (+37 °C, $5\%$ CO2). It was verified that the purple formazan crystals had been completely solubilized, and the absorbance of each sample was measured spectrophotometrically at 570 nm by a Tecan Spark™ 10 M multimode microplate ELISA reader. ## 2.3.3. H&E Staining For histological analysis, the reattached cell sheet samples were fixed in a $10\%$ neutral buffered formalin solution in PBS (pH 7.4) at room temperature for 20 min, washed with PBS 3 times, dehydrated in graded alcohol, embedded in paraffin (Merck, Darmstadt, Germany), and sectioned at 5 µm. Adjacent sections were stained with hematoxylin and eosin (H&E) (Sigma, USA) and observed under a microscope (OLYMPUS BX53, Japan). ## 2.4.1. Ethics Statement and Animal Use The following animal handling procedure was reviewed and approved by the Institutional Animal Care and Use Committee of Taipei Medical University (approval no. LAC-2020-0173). Ten 9-month-old male New Zealand white rabbits (supplied by BioLASCO Taiwan Co., Ltd., Taipei City, Taiwan) with body weights between 3 kg and 3.5 kg were included in this study. The rabbits were housed individually under standard conditions (22–24 °C, exposed to cycles consisting of 12 h of light and 12 h of dark, and allowed free access to food and water). Six hours before anesthesia, the rabbits were provided a light meal, but water was provided ad libitum. Prior to surgery, the rabbits were weighed and then intramuscularly injected with 0.1 mL/kg Zoletil, which contains 50 mg/mL tiletamine and 50 mg/mL zolazepam (Zoletil® 100; Virbac, Carros, France) and 0.4 mL/kg xylazine (®Rompun 20 mg/mL; Bayer HealthCare, LLC, Animal Health Division, Shawnee Mission, KS 66201, USA) to induce short-term anesthesia. Rabbits were intubated and constantly monitored during the course of anesthesia for level of consciousness and any signs of discomfort. Removal of the intubation tube was attempted when the animal regained consciousness and began rejecting the tracheal tube. All reasonable actions were taken to minimize suffering throughout the operation. Rabbits were euthanized at either the end of the experiments or when a humane endpoint was reached, whichever came first. Humane endpoints for all experiments were defined as $20\%$ acute weight loss or clinical signs consistent with severe dyspnea, altered mentation, or anorexia. ## 2.4.2. Patch Model After assessing the capacity of the degassed SIS mesh to promote cell adhesion and proliferation, we then applied the degassed SIS mesh to reconstruct tracheal defects. The patch defect model was constructed in 10 rabbits that were able to adequately before the investigation. After the trachea was accessible, the ventral portion, which had a semicylindrical shape and measured approximately 0.7 cm × 0.7 cm, was excised. On five rabbits, a degassed SIS mesh patch of the same size as the wound was sutured in place using a nonabsorbable surgical suture (Prolene® 6-0; ETHICON, LLC., San Lorenzo, Puerto Rico 00754-0982, USA) to reconstruct the defect. The muscle was closed with two sutures (Vicryl® 4-0; ETHICON, USA), followed by S.C. skin closure (Nylon® 4-0; ETHICON, USA) Five other rabbits underwent the same procedure, but the original SIS mesh was sutured in place of the defect as the control group. ## 2.4.3. Histological Analysis After administering Zoletil (Zoletil® 100; Virbac, Carros, France) intramuscularly to induce general anesthesia, euthanasia was carried out using carbon dioxide gas. After that, the transplanted section was promptly removed together with the host tracheal structures for gross and histological analyses. The explanted specimens were dissected to remove all surrounding tissues to expose the cartilage tube structure. Subsequently, the samples were fixed for 24 h in a $10\%$ neutral buffered formalin solution in PBS (pH 7.4) at room temperature, rinsed with distilled water, dehydrated in graded alcohol, and embedded in paraffin. Paraffin blocks were cut into 4 μm sections and stained with a hematoxylin-eosin staining solution (Sigma-Aldrich, MI, USA). Using a light microscope (Axioskop; Carl Zeiss, Oberkochen, Germany) at 100× magnification, microscopic quantification was performed by one researcher blinded to the experimental groups. The thickness of the tracheal wall at the implanted defect was measured. ## 2.5. Statistical Analysis ImageJ software (National Institute of Health, New York, NY, USA) was used to measure the thickness of each implanted graft. Statistical analyses were carried out using Prism version 5 (GraphPad Software, CA, USA). Differences in the thicknesses of the mucosal layers of the grafted patches with and without cell sheet application were assessed by unpaired Student’s t test. A p value < 0.05 was considered significant and noted as $p \leq 0.05$ (), $p \leq 0.001$ (), and $p \leq 0.0001$ (). ## 3.1. In Vitro Evaluation of the Ability of the Degassed SIS Mesh Cell Sheet to Attach Upon analysis of the MTT-stained reattached cell sheet images, the percentage of the area of the reattached cell sheets in the degassed group was 34.57 ± $11.8\%$, which was significantly higher than the 16.72 ± $3.8\%$ in the nontreated group ($p \leq 0.05$) (Figure 2). The degassed group had more live reattached cell sheets than the untreated group. The absorbance values of the samples were calculated and analyzed using the independent t test. The optical density (OD) detected by the ELISA reader in the degassed group was 0.363 ± 0.116, which was significantly higher than the 0.228 ± 0.072 of the nontreated group (* $p \leq 0.001$) (Figure 3). The HE-stained specimens showed that the fabricated scaffolds consisting of cell sheets that had reattached during vacuum treatment could adhere to the surface of the SIS since no voids were observed between the two layers (Figure 4). ## 3.2. In Vivo Evaluation of the Degassed SIS Mesh in a Trachea Patch Repair Model No animals died during the surgical procedure. The surviving rabbits did not exhibit any clinical symptoms of respiratory difficulty, and euthanasia was performed in time. As the implanted site is deep in the tracheal lumen, we found it difficult to observe the progress of the thickness of the implanted scaffold continuously. Instead, the thickness of the implanted graft of the two groups at the time of two months postoperation was compared. At two months postoperation, histological assessment showed that the areas that were transplanted with the graft in both experimental groups had an intact epithelium. However, the tracheal defect repaired by the degassed SIS patch showed enhanced healing and reductions in fibrosis and luminal stenosis compared to the nondegassed control group. In the control group, we observed dense fibrosis, high neovascularization in the subepithelial layer, and a large amount of fibrosis formation at the contact site where the SIS mesh had been implanted (Figure 5). Conversely, the degassed SIS patch showed better incorporation into the transplanted site, with less lymphocyte infiltration and less fibrosis formation. As a result, there was a significant reduction in the thickness of the degassed SIS transplanted graft compared with the nondegassed SIS graft (346.82 ± 28.02 µm vs. 771.29 ± 20.41 µm, respectively; $p \leq 0.05$) (Figure 6). The results from the transplanted graft study showed that the issues of fibrosis and stenosis improved dramatically in the experimental group. Consequently, degassing treatment appeared to enhance the incorporation of the SIS mesh into the host tissue. ## 4. Discussion In this study, we demonstrated that degassing SIS promotes cell sheet attachment in vitro. In a rabbit trachea patch repair model, the trachea defect repaired with the degassed SIS patch showed enhanced healing and reductions in fibrosis and luminal stenosis compared to the nondegassed control group. Our current study demonstrated the importance and benefits of degassing SIS, which has not been addressed in the literature previously. SIS has been applied for more than two decades, as Clark et al. reported the use of intestine submucosa to repair the abdominal walls of dogs [6]. A later study confirmed that these bioscaffold materials functioned well to repair large ventral abdominal wall defects, and there was no evidence of local infection or other local detrimental pathology to any of the graft materials at any time point [23]. The short-term and long-term results from human studies were also satisfactory, even when used in contaminated or potentially contaminated surgical fields [24]. However, studies have also demonstrated that in some cases, especially in critically ill patients, the SIS mesh must be removed due to infection or reoperation [25]. In Clark’s study, the SIS bioscaffold showed more polymorphonuclear leukocytes in the SIS group at the 1-week time point than those in the other, non-SIS scaffold material groups, which raises concern for more significant foreign body reactions [6]. SIS has also been used for tracheal reconstruction in some studies. Gubbels et al. showed that SIS could be completely mucosalized, integrate into the surrounding tissues, produce minimal granulation, and support cartilage neoplasia using a vascularized perichondrial flap [26]. Bergonse et al. self-treated the submucosa of the small intestines of pigs for SIS implantation into rabbit tracheal defects with dimensions of 6mm × 8 mm (48 mm2) [27]. As described by the authors, after treatment, the acellular SIS was composed of collagen, elastin, glycoproteins, glycosaminoglycans, proteoglycans, and matricellular proteins, which is similar to the composition of the SIS graft we used in this experiment. The authors indicated that SIS facilitated neovascularization, epithelial remodeling, and immature chondrogenesis. However, the SIS alone could not ameliorate tracheal stenosis [27]. A promising way to increase the biocompatibility of SIS for various applications is to incorporate stem cells. Du et al. [ 2012] used monolayered mesenchymal stem cells (MSCs) combined with SIS to maintain airway patency, and the results were promising [28]. Nevertheless, the isolating and cultivating MSCs from adipose tissue to obtain the correctly differentiated cell has not always been sustainable and has not produced the desired results due to the decreased telomerase activity at higher cell passages. Even more importantly, long-term culture might lead to an increase in the probability of malignant transformation [29]. Alternatively, SIS can be modified to enhance cell attachment, and with increased cell attachment and migration, better healing and fibrosis reduction effects can be expected. Additionally, the SIS might be preattached to a respiratory epithelium cell sheet layer from the airway that can be easily harvested and cultured, such as a patient’s nose. Our previous study demonstrated the feasibility of fabricating an intact and transplantable cell sheet cultured from autologous rabbit nasal epithelial cells [21]. These nasal epithelial cell sheets appear to be functional and fully transplantable, which might serve as an ideal component in the abovementioned SIS scaffold applications to limit stenosis and preserve tracheal patency after transplantation. To achieve the improved outcome mentioned above, the cytocompatibility of the SIS materials must be enhanced. Coating the surface with biocompatible substances such as collagen or hyaluronic acid is a commonly used protocol [30]. Surface modification with plasma can also be utilized to show significant improvement [31,32,33]. Nevertheless, none of these methods practically solves the problem that all of the current clinically available SISs are supplied in a dried form for storage at room temperature for a reasonable period of time. Inevitably, the prepared SIS is composed of dry ECM fibers with interlaced small air pockets that are initially filled with tissue fluid before being manufactured. Limited studies have addressed the impact of these SIS air pockets on wound healing. The degassing process, which is frequently used to eliminate microbubbles in meshes for many applications, is seldom addressed [34]. In a study by McKenna et al. on the fabrication of a dermal tissue engineering scaffold, degassing the scaffold (PLGA + E.C. solution) was found to be essential and the degassing process produced a morphology that was more consistent, increasing the suitability of the scaffold to support the growth of keratinocytes as well as promote skin tissue regeneration [35]. In contrast, in their study, the degassing process was emphasized to take place during the mesh manufacturing phase; we focused on applying the degassing process after manufacture. Using degassing protocols in a postproduction phase would allow physicians to further enhance the treatment effectiveness of a stock commercial product, which is essentially more clinically favorable. Whether degassing is performed during the pre- or postproduction phase, these studies demonstrated the importance of degassing and removing the dead space in the bioscaffold to increase the bioavailability of the material. In our in vitro shaking/rinsing test, we observed better adhesion of the cell sheet on the SIS surface in the treated group. It should be noted that in our study, instead of using a direct cell seeding model, a cell sheet detachment and reattachment model was used to reveal the effectiveness of degassing the SIS surface. With direct seeding, the viability of the cells on the SIS varies significantly according to different cell types (unpublished data). We realized that under these conditions, we would actually be testing the survivability of the individual cells seeded on the SIS surface instead of testing the ability of the SIS surface to attach to the tissue. Therefore, the in vitro cell sheet reattachment model was chosen to more closely mimic physiological conditions, as SIS is typically placed in contact with living tissues in the clinic. The benefits of degassing are also demonstrated in our in vivo study. Unlike in our previous study, where a nasal epithelial cell sheet was used as the scaffold lining in a tracheal patch defect model, in this study, pure SIS was used to repair the defect without any epithelial lining [21]. This allowed us to directly evaluate the effect of SIS degassing on tracheal defect reconstruction. Without the cell coverage provided by the inner lining, the tracheal wall defect was expected to undergo a primary healing process, in which the ability of the cells to attach and migrate would be directly reflected by the degree of healing, stenosis, and fibrosis. As expected, the animal defects repaired with the degassed SIS showed decreased degrees of stenosis and fibrosis at the healing site, implying that the degassing process effectively increased the primary healing ability. Nevertheless, the extent of fibrosis remained significant. Although the experimental animals will not experience mortality in this trachea wall patch defect model, if a segmental replacement or even transplantation is desired, the extent of stenosis/fibrosis reduced by the degassing process might not be sufficient to produce a favorable clinical outcome. Thus, utilizing the epithelial lining might be necessary for segmental replacements to prevent fatal stenosis [36]. Under these circumstances, efficient attachment of the cell sheet lining to the reconstruction scaffold will be necessary. As it has already been made commercially available and approved for use in humans, SIS might be one of the most readily available scaffolds in clinical practice. If the SIS can be preattached to the epithelial lining sheet, this hybrid scaffold–cell sheet might serve as an ideal transplant material for tissue repair, as SIS delivers mechanical strength for handling during surgery and the functional epithelial cell sheet lining provides functional coverage of the defect surface. To achieve this notion, protocols intended to minimize the time needed for cell sheet adhesion as well as maximize the ratio of cell sheet adhesion onto the surface of the SIS scaffold are necessary. Using continuous negative pressure to remove the gas inside the scaffold and pulling the culture medium to fill the tiny pores on the surface of the SIS material entirely may help each part of the cell sheet have optimal exposure to nutrients, and the cell sheet may attach more quickly and firmly to the scaffold. While the use of tissue-engineered hybrid “scaffolded” cell sheets might still take some time to be achieved, the effect of degassing revealed in this study can actually be used in clinical practice at the current stage. As degassing can be performed easily through negative pressure treatment, it is not difficult to perform in the operating room by simply applying the surgical suction system to an air-sealed chamber. It is possible to optimize the surface of SIS materials by degassing and simply incorporating peripheral blood to enhance biocompatibility in vivo. In 2019, Sofu et al. used a chitosan-glycerol phosphate/blood implant (BST-CarGel®) mixed with peripheral blood that resulted in clinical and radiographic outcomes similar to those of a hyaluronic-acid-based cell-free scaffold for the treatment of focal osteochondral lesions of the knee joint [37]. Here, we recommend that physicians use a simple protocol by applying surgical suction in connection with a sterilized cup. The SIS can be placed in a sterilized dish and mixed with the blood gathered during the surgical procedure, and then the dish can be placed in a sterilized bag or chamber and connected to the surgical suction system, which would easily degas the SIS and allow the peripheral blood to fill the air pockets within it. We observed dramatic SIS softening after 15–30 min of degassing treatment. Microscopically, the red blood cells were observed to be interlaced with the SIS interfiber spaces after degassing (Figure 7A). Then, when the blood was poured on the SIS surface, the red blood cells aggregated on only the SIS surface and did not penetrate the SIS matrix even after immersion for more than 30 min (Figure 7B). This study has several limitations. First, a patch tracheal defect repair model was used, and a relatively small defect that was below the fatal threshold was created and repaired. Thus, this study did not fully mimic the clinical conditions of tracheal implantation. Although degassing might have some positive impacts on partial tracheal repair, degassing would be of less clinical value if this protocol cannot be applied in circumferential segmental repair or transplantation. Our next step will be to test the degassing protocol in a whole tracheal segmental transplantation model to evaluate the true effectiveness of this degassing procedure. Additional evaluations of respiratory dynamics should also be considered. Second, while the removal of the air pockets in the SIS seems to be the critical feature of this study, it is difficult to observe cell-to-surface contact behavior consecutively in real time, as the SIS is a nontransparent material with a specific thickness, making it difficult to observe by light microscopy. A noncytotoxic alternative to scanning electron microscopy must be used to more clearly demonstrate that the air pockets become obstacles to the living cells when the cells are trying to attach, migrate, and proliferate. Third, the pressure and pretreatment time needed to remove a substantial number of air bubbles inside the SIS material to facilitate the adhesion and proliferation of the respiratory epithelial cell sheets were not precisely determined. The degassing time of approximately 30 min in our current protocol seemed to be acceptable to maintain a functional cell sheet, but optimization is worth further investigation. Last, the potential of developing a wound infection after degassing the SIS should always be kept in mind, because after removing the air bubbles from the materials, the bioavailable spaces created can be used by microorganisms. Thus, whether this degassing process causes a higher tendency to develop subsequent infection needs to be further explored, mainly since SIS is intended to be used in contaminated surgical fields. In our study, we have observed no signs of inflammation or infection under H&E staining. However, an additional check of inflammatory markers such as the cytokines might help identify the concerns mentioned above. Despite these limitations, we believe that the degassing process, which helps to remove air bubbles from inside a porous material, plays a pivotal role in increasing cell-material adhesion and biocompatibility and thus might be a vital component for the clinical applications of SIS. SIS was approved by the FDA a long time ago, which makes it easy to purchase and to apply in humans. Most importantly, the degassing process can be easily performed in almost all operation rooms as long as a suction device is available. Surgeons might consider immersing the SIS in clean body fluid or saline under negative pressure for a short period of time before being applied to the desired surgical field. The increased biocompatibility gained by using this simple treatment might significantly enhance the effectiveness of SIS without the need for complicated, time-consuming modifications. ## 5. Conclusions In conclusion, degassing the SIS mesh significantly promoted cell sheet attachment in vitro. In the tracheal patch repair model, degassed SIS significantly promoted wound healing by reducing luminal fibrosis and stenosis compared to the nondegassed control mesh. These results suggest that degassing the SIS might be a simple and effective way to improve its biocompatibility. ## 6. Patents Tseng How has patent #US9,546,349 B2 licensed to Taipei Medical University. ## References 1. Ding Y., Zhang X., Zhang Y., Shen F., Ding J., Hua K.. Cervicovaginal reconstruction with small intestinal submucosa graft in congenital cervicovaginal atresia: A report of 38 cases. Eur. J. Obstet. Gynecol. Reprod. Biol. (2021) 267 49-55. DOI: 10.1016/j.ejogrb.2021.10.015 2. 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--- title: 'Vitamin D Deficiency in Childhood Cancer Survivors: Results from Southern Thailand' authors: - Sirinthip Kittivisuit - Pornpun Sripornsawan - Natsaruth Songthawee - Shevachut Chavananon - Umaporn Yam-ubon - Edward B. McNeil - Somchit Jaruratanasirikul - Thirachit Chotsampancharoen journal: Nutrients year: 2023 pmcid: PMC10051581 doi: 10.3390/nu15061328 license: CC BY 4.0 --- # Vitamin D Deficiency in Childhood Cancer Survivors: Results from Southern Thailand ## Abstract ### Simple Summary Vitamin D deficiency, defined as a total 25-hydroxyvitamin D level of less than 20 ng/mL, is one of the major global health problems in children. There are few studies on vitamin D deficiency in childhood cancer survivors (CCSs), especially in tropical countries. Our study enrolled a total of 206 CCSs between January 2021 and March 2022 to evaluate the prevalence and risk factors for vitamin D deficiency. We found that CCSs had a high prevalence of vitamin D deficiency ($35.9\%$), even in tropical areas such as southern Thailand. Female gender, obesity, lack of outdoor activities, and lower dietary dairy intake were independent risk factors for vitamin D deficiency. We believe that our results will be of benefit to clinicians who take care of CCSs. Regular screening should be established in long-term CCS care to identify those who are at risk of vitamin D deficiency and should be receiving appropriate supplementation. ### Abstract There is limited information on vitamin D deficiency among childhood cancer survivors (CSS), especially in tropical countries. The aims of this study are to determine the prevalence and risk factors for vitamin D deficiency in CCSs. This study was conducted at the long-term follow-up clinic for CCSs at Prince of Songkla University, Songkhla, Thailand. All CCSs who were followed up between January 2021 and March 2022 were enrolled. Demographic data, dietary dairy intake, average weekly duration of outdoor activities, total 25-hydroxyvitamin D [25(OH)D] levels, parathyroid hormone levels, and blood chemistry were collected. A total of 206 CCSs with a mean age at follow-up of 10.8 ± 4.7 years were included. The prevalence of vitamin D deficiency was $35.9\%$. Female gender (odds ratio (OR): 2.11, $95\%$ CI: 1.08–4.13), obesity (OR: 2.01, $95\%$ CI: 1.00–4.04), lack of outdoor activities (OR: 4.14, $95\%$ CI: 2.08–8.21), and lower dietary dairy intake (OR: 0.59, $95\%$ CI: 0.44–0.80) were independent risk factors for vitamin D deficiency. Vitamin D deficiency was common in CCSs and associated with female gender, obesity, lack of outdoor activities, and lower dietary dairy intake. Regular 25(OH)D screening should be established in long-term care to identify those who require vitamin D supplements. ## 1. Introduction In recent years there have been increasing numbers of childhood cancer survivors (CCSs) as a result of advancements in cancer therapy [1]. Surveillance of long-term health effects, including bone health problems, is important in this population [2,3,4]. Although vitamin D is essential for maintaining bone health, vitamin D deficiency, defined as a total 25-hydroxyvitamin D [25(OH)D] level of less than 20 ng/mL, is one of the major global health problems in children, with a prevalence ranging from $7\%$ to $95\%$ in general populations [5,6,7]. Previous studies that assessed the vitamin D status of healthy children in Thailand reported that the prevalence of vitamin D deficiency (25(OH)D < 20 ng/mL) was 19.5–$33.4\%$ [8,9,10,11]. Female gender, older age, obesity, limited dietary dairy intake, limited sun exposure, geographic region, and seasonal period have been reported as risk factors for vitamin D deficiency [8,9,10,11,12,13,14,15]. In addition to these potential risks, CCSs have increased risks for vitamin D deficiency, including restrictions on outdoor activities and exposure to steroids, chemotherapy, and/or radiation. Therefore, screening for vitamin D deficiency in CSS is necessary. A meta-analysis that included 19 studies reported that the median prevalence of vitamin D deficiency in pediatric cancer patients was $14\%$, with a range of $0\%$ to $61.5\%$ [16]. However, these studies concentrated on specific cancer diagnoses and were heterogeneous in the definitions of vitamin D deficiency and the time point of vitamin D measurement (at diagnosis, during therapy, and on completion of therapy). There are few studies on vitamin D deficiency in CCSs. Previous studies have reported the prevalence of vitamin D deficiency in CCSs, varying from $14\%$ to $48\%$ [17,18,19,20,21]. Considering that there is limited information on vitamin D deficiency among CCSs in tropical regions with an abundance of sunlight, such as southern Thailand, this study aims to identify the prevalence and clinical risk factors of vitamin D deficiency in CCSs in southern Thailand. ## 2. Materials and Methods This cross-sectional study included all CCSs who were followed up at the long-term follow-up clinic for childhood cancer, Department of Pediatrics, Faculty of Medicine, Prince of Songkla University, Songkhla, southern Thailand. Our hospital is a major tertiary healthcare institution and referral center in southern Thailand. Songkhla is located at latitude 7.20° N and longitude 100.60° E and has a tropical climate, with only dry and rainy seasons. Although there are seasonal variations of ultraviolet radiation, there is plenty of sunshine all year [22]. The study was approved by the Ethics Committee, Faculty of Medicine, Prince of Songkla University. Written informed consent and written assent were obtained from all parents and participants. All CCSs who were followed up between January 2021 and March 2022 were enrolled. Each participant had completed therapy and was in remission. The cancer diagnoses were categorized into 3 groups: leukemia/lymphoma (acute lymphoblastic leukemia, acute myeloid leukemia, Hodgkin lymphoma, non-Hodgkin lymphoma), solid tumor (Ewing sarcoma, rhabdomyosarcoma, osteosarcoma, neuroblastoma, hepatoblastoma, Wilm tumor, retinoblastoma, germ cell tumor, Langerhans cell histiocytosis), and brain tumor (medulloblastoma, astrocytoma, primitive neuro-ectodermal tumor, germ cell tumor). Participants who were receiving vitamin D supplements were excluded from the study. The medical records of all enrolled participants were retrospectively reviewed for cancer diagnosis and treatment. The information recorded for each participant at the follow-up visit included demographic characteristics (age, weight, height, body mass index, pubertal status), amount of dietary dairy intake, average weekly duration of outdoor activities, 25(OH)D, parathyroid hormone (PTH) level, and blood chemistry readings. For dietary dairy intake, only milk consumption was recorded as milliliters per week. The duration of outdoor activities in which the participants were exposed to sunlight was recorded in hours per week. ## 2.1. Anthropometric Data Collection Body weight was measured using an electronic scale, with the participants wearing only light clothing and without shoes. Height was measured with a stadiometer. Body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared and then converted to a BMI percentile according to the Centers for Disease Control and Prevention growth charts for age/sex-adjusted children and teens aged 2 through 19 years [23]. A BMI of less than the 5th percentile was defined as underweight, the 5th through 84th percentiles as a healthy weight, and the 85th through 99th percentiles as overweight or obese. Pubertal development for each participant was determined according to the Tanner staging system. For females, prepubertal status was defined as Tanner stage I breast development, and for males, a testicular volume of less than 4 mL [24]. ## 2.2. Vitamin D Levels and Biochemistry Analyses Total serum 25(OH)D is the major circulating form of vitamin D and, thus, the best indicator for measuring vitamin D status. Total serum 25(OH)D levels were measured for all participants by chemiluminescent immunoassay using the LIAISON analyzer (DiaSorin, Stillwater, MN, USA) and were recorded in nanograms per milliliter (ng/mL). The inter-assay coefficients of variation for the serum 25(OH)D levels were in the range of 8.3–$9.7\%$. Following the 2011 Endocrine Society Guidelines, vitamin D levels of <20 ng/mL, 21–29 ng/mL, and ≥30 ng/mL were defined as deficient, insufficient, and sufficient, respectively [5]. Parathyroid hormone levels were measured by electrochemiluminescent immunoassay using the Elecsys PTH STAT e 411 analyzer (Roche Diagnostics, Mannheim, Germany). The inter-assay coefficients of variation for the serum PTH levels were in the range of 2.7–$3.4\%$. Other biochemistry values were measured using the Alinity analyzer (Abbott, Deerfield, IL, USA). Estimated glomerular filtration rate (eGFR) was used to determine kidney function by calculating creatinine clearance using the original Schwartz formula with a modified Jafe assay and a modified Schwartz formula with enzymatic creatinine results [25,26]. An eGFR was considered to have decreased if it fell below 90 mL/min/1.73 m2. ## 2.3. Statistical Analysis Descriptive statistics are presented using mean and standard deviation (SD) or median and interquartile range (IQR) for continuous variables, as appropriate, and frequency with percentage for categorical variables. Variables associated with vitamin D deficiency were analyzed using the chi-square test or Fisher’s exact test for categorical variables and Student’s t-test or the rank-sum test for continuous variables, as appropriate. Variables having a p-value of less than 0.1 from the univariate analysis were included in the initial multivariate logistic regression model for the assessment of independent risk factors. The final model was selected using a stepwise backward elimination method based on the likelihood ratio test. The risk factors for vitamin D deficiency are presented as adjusted odds ratios (ORs) with $95\%$ confidence intervals (CIs). A p-value less than 0.05 was considered significant. ## 3.1. Baseline Characteristics of the Study Participants A total of 206 CCSs were included in the study. None of the participants had received or were receiving vitamin D supplements. Most of the participants were male ($59.2\%$). The distribution of cancer diagnoses and treatment of the 206 study participants are presented in Table 1. The most common diagnoses were leukemia or lymphoma ($49.0\%$). Within the leukemia or lymphoma group, acute lymphoblastic leukemia was the most common type ($61.4\%$). Solid tumors were diagnosed in $40.3\%$ of the total study population. The three most frequent diagnoses in the solid tumor group were Langerhans cell histiocytosis ($16.9\%$), retinoblastoma ($15.7\%$), and germ cell tumor ($14.5\%$). Brain tumors were the least common cancer diagnoses ($10.7\%$), and medulloblastoma was the most common brain tumor ($40.9\%$). Approximately half of the participants received intrathecal chemotherapy and steroids. One-fourth of the participants were exposed to radiation during treatment. ## 3.2. Demographic Characteristics at the Follow-Up Visit The mean age at follow-up was 10.8 ± 4.7 years. The median (IQR) time from the end of cancer therapy to the follow-up visit was 2.3 (1.0–3.9) years. Most of the participants were classified as having a normal BMI ($55.8\%$), followed by obese ($31.6\%$) and underweight ($12.6\%$). The proportion of participants in the prepubertal and pubertal stages was comparable. Most of the participants ($68\%$) spent their time outdoors, with a median duration of 3.0 h per week, and consumed dietary dairy products, with a median of 1250.0 (750.0–2400.0) milliliters per week. The demographic and laboratory characteristics of the study population are presented in Table 2. ## 3.3. Vitamin D Status and Biochemistry Measurements Overall, the mean (SD) vitamin D level was 10.8 (4.7) ng/mL. Of the 206 children, 74 ($35.9\%$) had vitamin D deficiency, 96 ($46.6\%$) had vitamin D insufficiency, and 36 ($17.5\%$) had vitamin D sufficiency. Among the 74 children who had vitamin D deficiency, 8 ($10.8\%$) were defined as having severe deficiency (<12 ng/mL). Serum 25(OH)D levels were significantly inversely correlated with serum PTH levels (r = −0.3, $p \leq 0.001$) (Figure 1). The median (IQR) PTH level was 41.2 (32.0–53.8) pg/mL. Hyperparathyroidism (PTH level >65 pg/mL) was identified in $25.7\%$ ($\frac{19}{74}$) of vitamin-D-deficient children, $9.4\%$ ($\frac{9}{96}$) of vitamin-D-insufficient children, and none of the vitamin-D-sufficient children. ## 3.4. Risk Factors for Vitamin D Deficiency The participants were classified into two groups according to vitamin D status: those with vitamin D deficiency (serum 25(OH)D levels <20 ng/mL; $$n = 74$$) and those without vitamin D deficiency (serum 25(OH)D levels >20 ng/mL; $$n = 132$$). On univariate analysis, the mean age at follow-up among the children who had vitamin D deficiency was significantly higher than in those who did not (12.5 vs. 9.9 years, respectively, $p \leq 0.001$). Vitamin D deficiency in females was significantly more frequent than in males (52.7 vs. $47.3\%$, $$p \leq 0.014$$). Children who had vitamin D deficiency had significantly higher weight, height, and BMI than those who did not have vitamin D deficiency ($p \leq 0.001$). Vitamin D deficiency was more frequent in children who were obese. ( 41.9 vs. $25.8\%$, respectively, $$p \leq 0.025$$). Vitamin D deficiency was diagnosed in children who had already entered puberty significantly more frequently than in prepubertal children (67.6 vs. $38.6\%$, respectively, $p \leq 0.001$). Children who did not engage in outdoor activities were significantly more likely to have vitamin D deficiency compared with those who did (56.8 vs. $18.2\%$, respectively, $p \leq 0.001$). The median amount of dietary dairy intake per week was significantly lower among the children with vitamin D deficiency than in the other group (1000.0 vs. 1500.0 mL, respectively, $p \leq 0.001$). The children with vitamin D deficiency had significantly higher PTH levels and lower serum calcium levels compared with those who did not ($p \leq 0.001$ and $$p \leq 0.009$$, respectively). However, other biochemistry tests associated with vitamin D status, serum phosphorus, and alkaline phosphatase levels were not significantly different. Other variables, including cancer diagnosis, treatment, follow-up time, alanine aminotransferase, albumin, hemoglobin, serum iron, total iron binding capacity, transferrin saturation, ferritin, zinc, and estimated glomerular filtration rate, were not significantly different between children with and without vitamin D deficiency. A comparison of the demographic and laboratory characteristics between the 74 children who had vitamin D deficiency and the 132 children who did not is presented in Table 2. On multivariate analysis, the independent risk factors for vitamin D deficiency are shown in Table 3. There were four risk factors that were statistically significant for vitamin D deficiency: female gender, obesity, lack of outdoor activities, and lower dietary dairy intake. Females had an odds ratio of 2.11 ($95\%$ CI: 1.08–4.13) for vitamin D deficiency compared to males ($$p \leq 0.029$$). In comparison to those who were not obese, participants with obesity had an odds ratio of 2.01 ($95\%$ CI: 1.00–4.04) for vitamin D deficiency ($$p \leq 0.05$$). Participants who did not engage in outdoor activities had an odds ratio of 4.14 ($95\%$ CI: 2.08–8.21) in comparison to those who did ($p \leq 0.001$). Lower dietary dairy intake was a significant risk factor for vitamin D deficiency, with an odds ratio of 0.59 ($95\%$ CI: 0.44–0.80) ($p \leq 0.001$). ## 4. Discussion Our study included a large and diverse population of 206 childhood cancer survivors. We found that the prevalence of vitamin D deficiency and insufficiency in our study were $35.9\%$ and $46.6\%$, respectively. Our prevalence was higher than that reported in healthy Thai children [8,9,10,11]. Similarly, Sinha et al. reported that children with cancer had vitamin D levels of less than 10 ng/mL more frequently than a healthy control group [27]. Gunes et al. found that the vitamin D levels of 70 CCSs were lower than in normal controls [28]. In contrast, Simmons et al. found that the prevalence of vitamin D deficiency among 78 survivors of acute lymphoblastic leukemia (ALL) was similar to the reported prevalence in the general pediatric population [29]. Even though it has been observed that CCSs tended to have a higher prevalence of vitamin D deficiency than the general population, the causal relationship between vitamin D deficiency and CCSs remains unclear. It has been proposed that CCSs may be more susceptible to vitamin D deficiency due to several circumstances, including the impact of the disease, treatment-related factors (exposure to steroids, chemotherapy, and/or radiation), inadequate nutritional intake, and restrictions on outdoor activities [12,20,27,29]. There are few studies of vitamin D deficiency in CCSs. Previous studies have reported rates of prevalence varying from $14\%$ to $48\%$ [17,18,19,20,21]. Rosen et al. retrospectively reviewed 201 CCSs and reported that $14\%$ had vitamin D deficiency [17]. Similarly, Esbenshade et al. reported that $16\%$ of 171 CCSs in their study had vitamin D deficiency [18]. Vitamin D deficiency was more prevalent among CCSs in studies by Bhandari et al., Choudhary et al., and Modan-Moses et al., with rates of $24\%$, $29\%$, and $48\%$, respectively [19,20,21]. However, the majority of these studies were conducted in regions of temperate climates. Our study, conducted in a region of tropical climate, located at the latitude of 7.20° N, with plenty of sunlight, found that the prevalence of vitamin D deficiency was $35.9\%$, which was within the upper range of previous studies in CCSs. The varying prevalence of vitamin D deficiency observed in the literature might be, at least partly, accounted for by geographic differences. When focusing on subgroups of specific cancer diagnoses, a few studies have evaluated vitamin D deficiency in survivors of leukemia. Simmons et al., using a different definition of vitamin D deficiency, reported that $11.5\%$ of 78 ALL survivors had serum 25(OH)D levels of less than 15 ng/mL [29]. Delvin et al. investigated 251 ALL survivors and found that $32.7\%$ had vitamin D deficiency [30]. A study by Schündeln et al. reported that $71.8\%$ of 124 ALL survivors had vitamin D deficiency [31]. Our study, which included a total of 101 survivors of leukemia and lymphoma, found that the prevalence of vitamin D deficiency in this subgroup was $38.6\%$ ($\frac{39}{101}$), which was within the range of those previous studies. There are only a limited number of studies that have investigated vitamin D deficiency in survivors of solid or brain tumors. Bilariki et al. reported that $61.5\%$ of 52 survivors of solid or brain tumors in their study had vitamin D deficiency [32]. Our study found a lower prevalence of vitamin D deficiency in survivors of solid or brain tumors of $32.5\%$ ($\frac{27}{83}$) and $36.4\%$ ($\frac{8}{22}$), respectively. The differing prevalence may be due, at least partly, to the different methods of measuring serum 25(OH)D levels, the threshold for diagnosing vitamin D deficiency, and differences in associated factors affecting the vitamin D status, including geographic area, seasonality, sun exposure habits, skin pigmentation, and consumption of vitamin D either in natural or fortified food sources. Apart from infant formula, there are no regulations specifying food to be fortified with vitamin D (i.e., cereals, yogurts, cheeses, butter, and margarine) under the law in Thailand, as they do in some other countries. Furthermore, these foods are not commonly consumed by the majority of Thai children. Female gender, older age, obesity, limited dietary dairy intake, limited sun exposure, geographic region, and seasonal period have been reported as risk factors for vitamin D deficiency [8,9,10,11,12,13,14,15]. Similarly, our study found that female gender, obesity, lack of outdoor activities, and lower dietary dairy intake were risk factors for vitamin D deficiency. On the other hand, older age did not appear to be a significant risk factor for vitamin D deficiency in our study. There is still some controversy around the potential risk factors for vitamin D deficiency in the CCS population. Some studies have reported older age to be a significant risk factor for vitamin D deficiency in CCSs [17,18,21,24,27], while other studies did not find this association [19,20]. In our study, although CCSs who had vitamin D deficiency were generally older than those who did not, age was not identified as a risk factor for vitamin D deficiency in the multivariate analysis. We found that the female gender was a potential risk factor for vitamin D deficiency, which was also found in a previous study in a general pediatric population [12] but not in previous studies in CCS populations [17,18,19,20,21,27]. We also found that obesity was associated with vitamin D deficiency, similar to previous studies [18,19]. As a result of the fact that there is no consensus in previous studies on CCSs regarding the potential risk factors for vitamin D deficiency, further multicenter prospective studies involving larger and more diverse CCS populations are necessary to consolidate the risk factors for vitamin D deficiency in CCSs. We observed an inverse correlation between serum 25(OH)D and PTH levels. Children with vitamin D deficiency exhibited lower serum calcium levels; however, their serum phosphorus and alkaline phosphatase levels were similar to those of children without vitamin D deficiency. These findings could be explained by the effects of PTH, calcium, and phosphate metabolism in the vitamin-D-deficiency state. Although the lower serum calcium was statistically significant, the difference was not considered clinically significant. There is a limited number of studies that have investigated associations between outdoor activities and dairy intake and CCSs. Our study found that a lack of outdoor activities and a lower dairy intake were risk factors for vitamin D deficiency. Similarly, the amount of sun exposure was associated with higher serum 25(OH)D levels in a study by Modan-Moses et al. [ 21]. Steroid use has been reported to be associated with vitamin D deficiency [12]; however, exposure to steroids, chemotherapy, or radiation was not identified as a risk factor for vitamin D deficiency in our study. To the best of our knowledge, this is the first study to evaluate the prevalence of vitamin D deficiency and insufficiency among CCSs in a tropical region. The study was conducted using a cross-sectional design, and the sample size was large in comparison to studies on CCSs. However, our study also had some limitations. First, several statistical comparisons were performed without using multiple testing correction (which is appropriate for an exploratory study); however, these methods may uncover associations that could be spurious, and therefore, this potential limitation should be mentioned. Second, some information was self-reported. Therefore, some errors might have been introduced. Third, this study was performed in a limited geographic area of southern Thailand. The findings should be interpreted in consideration of these points. Fourth, several related variables, including the use of sunscreen and clothing, the diurnal variations of sun exposure, the consumption of other dairy products besides milk, and additional dietary sources of vitamin D, were not evaluated. However, the main food component for Thai children does not consist of cheese or other dairy products. The natural dietary sources of vitamin D include oily fish (sardines, tuna, mackerel, salmon), cod liver oil, egg yolks, and organ meats (liver, kidney), with varying vitamin D content. However, the majority of these foods are not commonly consumed by Thai children. In addition, food preparation, which was also not recorded, can have a significant effect on vitamin D content. Further studies incorporating these variables that may influence vitamin D levels are warranted to confirm our results. Additionally, the effects of vitamin D deficiency on health outcomes, such as decreased bone mineral density and fractures, were not assessed. ## 5. Conclusions The prevalence of vitamin D deficiency in childhood cancer survivors was one-third of the participants in our study. Female gender, obesity, lack of outdoor activities, and lower dietary dairy intake were significant risk factors for vitamin D deficiency. 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--- title: Vegan Diet Is Associated with a Lower Risk of Chronic Kidney Disease in Patients with Hyperuricemia authors: - Chia-Lin Wu - Wen-Hsin Tsai - Jia-Sin Liu - Hao-Wen Liu - Sin-Yi Huang - Ko-Lin Kuo journal: Nutrients year: 2023 pmcid: PMC10051587 doi: 10.3390/nu15061444 license: CC BY 4.0 --- # Vegan Diet Is Associated with a Lower Risk of Chronic Kidney Disease in Patients with Hyperuricemia ## Abstract Hyperuricemia is a well-known risk factor for chronic kidney disease (CKD). Little is known about whether a vegetarian diet is associated with a lower risk of CKD in patients with hyperuricemia. From 5 September 2005, to 31 December 2016, we retrospectively included clinically stable patients with hyperuricemia who received health check-ups at Taipei Tzu Chi Hospital. All participants completed a dietary habits questionnaire to determine whether they were omnivorous, lacto-ovo vegetarian, or vegan. CKD was defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2 or the presence of proteinuria. A total of 3618 patients with hyperuricemia were recruited for this cross-sectional study, consisting of 225 vegans, 509 lacto-ovo vegetarians, and 2884 omnivores. After adjusting for age and sex, vegans had a significantly lower odds ratio (OR) of CKD than omnivores (OR, 0.62; $$p \leq 0.006$$). The OR of CKD remained significantly lower in vegans after adjusting for additional confounders (OR, 0.69; $$p \leq 0.04$$). Additionally, age (per year OR, 1.06; $p \leq 0.001$), diabetes mellitus (OR, 2.12; $p \leq 0.001$), hypertension (OR, 1.73; $p \leq 0.001$), obesity (OR, 1.24; $$p \leq 0.02$$), smoking (OR, 2.05; $p \leq 0.001$), and very high uric acid levels (OR, 2.08; $p \leq 0.001$) were independent risk factors for CKD in patients with hyperuricemia. Moreover, structural equation modeling revealed that a vegan diet was associated with a lower OR of CKD (OR, 0.69; $p \leq 0.05$). A vegan diet is associated with a $31\%$ lower risk of CKD in patients with hyperuricemia. A vegan diet may be beneficial in reducing the occurrence of CKD in patients with hyperuricemia. ## 1. Introduction Chronic kidney disease (CKD) is a large global health burden [1]. CKD accounts for approximately 10–$15\%$ of the population in most nations around the world. In 2008, a large epidemiological surveillance in Taiwan, which screened up to 462,293 participants, showed that approximately $12\%$ of the Taiwanese population had CKD [2]. In general, CKD is an irreversible disorder. Progressive loss of nephrons exaggerates glomerular hyperfiltration and the activation of the renin–angiotensin–aldosterone system, leading to renal fibrosis, and end-stage renal disease (ESRD) inevitably develops. Patients with CKD and ESRD will have substantially higher rates of mortality and cardiovascular or cerebrovascular morbidities. These patients who survived morbidities would still have prolonged years lived with disability. It is more important to prevent the development of CKD than to treat the disease. Common risk factors for CKD include aging, male sex, hypertension, diabetes mellitus, obesity, and hyperuricemia [3]. Among these conditions, hypertension, diabetes mellitus, and obesity are modifiable risk factors, but aging and gender are not correctable ones. Since the prevalence of CKD increases worldwide, it is emerging as important to search for novel modifiable risk factors of CKD and their corresponding treatments. Hyperuricemia is a disorder of abnormally high uric acid in the blood. In general, hyperuricemia can be diagnosed in individuals with a serum uric acid level equal to or greater than 7 mg/dL [4]. Uric acid is the end product of purines and is almost freely filtrated by the glomerulus in humans [5]. Then, uric acid is reabsorbed and secreted via the proximal renal tubule, and ~$10\%$ filtrated uric acid appears in the final urine [6]. Hyperuricemia can result from reduced urinary excretion, increased production of uric acid, or both. Hyperuricemia and gout are more common in patients with impaired kidney function. Studies have shown that hyperuricemia can cause or accelerate the progression of CKD [7,8]. A previous study prospectively followed 21,475 healthy volunteers for a median of seven years and reported that a slightly elevated serum uric acid level (7–8.9 mg/dL) was associated with an odds ratio (OR) of 1.74 for incident CKD, and a markedly elevated uric acid level (greater than 9 mg/dL) was linked to a triple risk [7]. A recent basic study reported that hyperuricemia per se did not cause CKD, but hyperuricemia with crystalluria led to CKD and drove progressive CKD [9]. This means that the crystallization of uric acid in the urine is crucial for the development and progression of CKD in patients with hyperuricemia. Because uric acid is a weak acid with a pKa of 5.75, it appears mainly as monosodium urate in the urine at physiologic pH [5]. However, the solubility of uric acid decreases with decreasing urine pH, and low urine pH can exaggerate uric acid crystallization. Although emerging evidence reveals a causal relationship between hyperuricemia and CKD, urate-lowering therapy remains controversial in patients with asymptomatic hyperuricemia. The debate continues about whether a vegetarian diet is healthier than an omnivorous diet. Vegetarian or plant-based diets may have multiple beneficial effects on our bodies, though they could also contribute to the deficiency of nutrients, such as vitamin B12, vitamin D, iron, calcium, zinc, and ω-3 fatty acids [10]. Studies have reported that a vegetarian diet is associated with a lower risk of gout and hyperuricemia [11,12]. In addition, dietary habits can affect urine pH. Omnivores have lower urine pH and higher net acid excretion than vegetarians [13]. The situation may promote uric acid appearance with crystallization in the urine. Otherwise, the crystallization of uric acid in the renal tubule or interstitium would cause kidney damage and result in CKD or the progression of kidney disease. However, it is unknown whether vegetarian dietary habits are beneficial for kidney health in patients with hyperuricemia. Thus, this study aimed to assess the association of vegetarian dietary habits with CKD in patients with gout or hyperuricemia. ## 2.1. Participants We retrospectively included 53,854 participants who had a health check-up at Taipei Tzu Chi Hospital from 5 September 2005, to 31 December 2016. We excluded 4086 participants younger than 40 years (they may have distinct pathogenesis for their kidney disease, e.g., polycystic kidney disease, lupus nephritis, type 1 diabetes mellitus, or congenital anomalies), 33,105 participants without hyperuricemia or a diagnosis of gout, 1944 participants with incorrect or incomplete identity information (such as foreigners, registration errors, or missing values), and 1101 participants with missing biochemistry data. Thus, 3618 participants with hyperuricemia or gout were included in the final analyses (Figure 1). The study was approved by the Institutional Review Board of Taipei Tzu Chi Hospital (approval number: 06-XD12-033). Written informed consent was waived. This research is strictly adherent to the Declaration of Helsinki and the guidelines for academic ethics by Taiwan’s Ministry of Science and Technology. ## 2.2. Outcome Measures Hyperuricemia was defined by a serum uric acid concentration of greater than 7.0 mg/dL. The primary endpoint was CKD, which was defined as an estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 or the presence of proteinuria [14]. ## 2.3. Clinical and Biochemical Measurements All subjects completed structured dietary questionnaires [15,16,17] and underwent a comprehensive health examination. The dietary questionnaire on dietary practices in terms of type and duration as well as a quantitative food frequency questionnaire has been validated in previous studies [16,17]. The food frequency questionnaire consists of 64 food items, which are categorized into 10 food groups, with additional sections on the consumption of beverages and dietary supplements. A trained research nurse interviewed every participant to assess their age, sex, vital signs, body mass index (BMI), medical history, lifestyle (smoking, alcohol consumption, and physical activity), and dietary habits from the dietary questionnaire at the entry of the study. Obesity in this Taiwanese adult population was defined as a BMI of >27 kg/m2 (based on the criteria by Taiwan’s Ministry of Health and Welfare) [18]. The subjects were grouped according to their self-reported dietary habits as vegans (only consumed plant-based foods), lacto-ovo vegetarians (ate eggs and/or dairy products but no other animal products), and omnivores (ate both plant- and animal-based foods) [15,16]. Height, weight, and blood pressure were measured by using an electronic meter (SECA GM-1000, Seoul, Republic of Korea) and an automatic blood pressure machine (Welch Allyn 53000, New York, NY, USA), respectively. Blood sampling was performed after a 12 h fasting period. Serum uric acid, creatinine (Jaffe’s reaction), glycated hemoglobin (HbA1c), albumin, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol were measured by using a biochemistry analyzer (Dimension® RXL Max® integrated chemistry system, Siemens, Erlangen, Germany). The eGFR was calculated by using the equation from the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) [19]. We evaluated urine protein semi-quantitatively with a dipstick test (AX-4030, Arkray Inc., Tokyo, Japan), as we described previously [15]. Proteinuria was classified into 6 ordinal categories: absent (<10 mg/dL), trace (10 to 30 mg/dL), 1+ (30 mg/dL), 2+ (100 mg/dL), 3+ (300 mg/dL), or 4+ (1000 mg/dL). Patients with trace levels, 1+ levels, or more were determined to have proteinuria. ## 2.4. Statistical Analyses Data are presented as the number (percentage) or mean (standard deviation, SD) as appropriate. The means and proportions among the groups were compared by one-way analysis of variance (ANOVA) and Chi-square tests, respectively. In addition, Fisher’s exact test was used to compare the distribution among the groups instead of the Chi-square test if there was an observed value of <5 with regard to categorical variables. We used logistical regression to determine the crude OR of dietary habits (omnivorous, lacto-ovo vegetarian, and vegan diets) with the primary endpoint. Moreover, the crude OR was adjusted for traditional risk factors of CKD, such as age, sex, diabetes mellitus, hypertension, obesity, smoking, and uric acid [3]. The crude association was further adjusted for age and sex (Model 2) and for other well-known risk factors for CKD (diabetes mellitus, hypertension, BMI, current smoking, and uric acid; these confounders were also statistically significant in Model 3) in multivariate logistical regression models. Bayesian logistic regression was conducted for multiplicity correction. Furthermore, multilevel structural equation modeling (SEM) with a multivariate Bernoulli distribution and logit link function by logistic regression was used to estimate the direct and indirect effects of dietary habits and other variables on the risk of CKD in patients with hyperuricemia. This SEM was limited to specific patterns and presented the factor–variable notation in path diagrams, which included the main risk factors and their endogenous effects. Two levels of relationships were shown, including [1] the direct effects of all potential risk factors on CKD and [2] the indirect effects of dietary habits on those potential CKD risk factors. This model was identified, and these constraints are supplied. In accordance with the above conditions, the estimation of SEM by method of maximum likelihood was performed using the GSEM package of STATA. Sensitivity analysis was performed using the multiple imputation and the expectation–maximization (EM) algorithm. A two-tailed p-value of less than 0.05 was considered statistically significant. All statistical analyses were performed by using SAS software (version 9.4, SAS Institute Inc., Cary, NC, USA) and STATA (version 15.1, Stata Corp, College Station, TX, USA). ## 3.1. Patient Characteristics A total of 3618 patients with hyperuricemia were grouped into 2884 omnivores, 509 lacto-ovo vegetarians, and 225 vegans (Table 1). Compared with the omnivore group, the vegan group was older; had a lower proportion of smoking, alcohol drinking, obesity, gout, and very high uric acid levels (>9 mg/dL); and had lower diastolic blood pressure and uric acid, low-density lipoprotein, and creatinine levels. ## 3.2. Associations between Dietary Habits and CKD in Patients with Hyperuricemia We used logistic regression models to reveal the associations between the self-reported dietary behaviors and CKD in this cross-sectional research. Univariate logistic regression showed that age (OR, 1.06; $95\%$ confidence interval (CI), 1.05–1.07, $p \leq 0.001$), diabetes mellitus (OR, 3.04; $95\%$ CI, 2.46–3.77, $p \leq 0.001$), hypertension (OR, 2.69; $95\%$ CI, 2.31–3.14, $p \leq 0.001$), obesity (OR, 1.20; $95\%$ CI, 1.03–1.41, $$p \leq 0.02$$), and uric acid level >9 mg/dL (OR, 1.92; $95\%$ CI, 1.55–2.38, $p \leq 0.001$) were associated with higher ORs for CKD in patients with hyperuricemia (Table 2). In contrast, male sex was associated with a lower OR for CKD (OR, 0.71; $95\%$ CI, 0.61–0.83, $p \leq 0.001$). After adjusting for age and sex (Model 2, Table 2), a vegan diet was associated with a lower risk of CKD in patients with hyperuricemia (OR, 0.62; $95\%$ CI, 0.45–0.97, $$p \leq 0.006$$) compared with the omnivore diet. Moreover, after adjusting for all potential risk factors in the fully adjusted model (Model 3), the association between a vegan diet and the primary outcome remained statistically significant (OR, 0.69; $95\%$ CI, 0.48–0.99, $$p \leq 0.04$$). We also used Bayesian logistic regression for multiplicity correction. After correction, the association was consistent with the result in Model 3 (vegan vs. omnivore: OR, 0.71; equal-tailed $95\%$ confidence interval, 0.50 to 0.94). ## 3.3. Interactive Effects of Potential Risk Factors for CKD in Patients with Hyperuricemia We conducted SEM analysis to further investigate the effects between a vegetarian diet and other potential risk factors on the ORs for CKD in the path diagram (Figure 2). The specific patterns in the path diagram presented the estimated and compared effects of results in our identified SEM. A vegan diet was linked not only to a lower OR (0.69, $p \leq 0.05$) but also to lower ORs for serum uric acid levels >9 mg/dL (0.40, $p \leq 0.05$) and BMIs greater than 27 (0.67, $p \leq 0.05$), which were both associated with higher ORs for CKD (2.05, $p \leq 0.001$ and 1.23, $p \leq 0.05$, respectively). A lacto-ovo vegetarian diet was not significantly associated with the OR for CKD or serum uric acid level of greater than 9 mg/dL but was significantly linked to a lower OR for obesity, defined as BMI >27 (0.72, $p \leq 0.05$). In addition, diabetes mellitus (OR, 2.10, $p \leq 0.001$), smoking (OR, 2.05, $p \leq 0.001$), hypertension (OR, 1.74, $p \leq 0.001$), and age (OR per year, 1.06, $p \leq 0.001$) had higher ORs for CKD but did not significantly interact with a vegetarian diet. Compared with Model 3, the SEM analysis has shown that the effect was significant in the goodness-of-fit through the test of the Log likelihood ratio (Log likelihood from −1826.17 to −5351.02, $p \leq 0.001$). ## 3.4. Sensitivity Analysis We excluded 3045 subjects before the final analysis (Figure 1). Therefore, we conducted a sensitivity analysis by using multiple imputations and the EM algorithm. Table 3 shows the result of the sensitivity analysis, which was similar to the result of the primary analysis in Table 2. ## 4. Discussion For the first time, we found that a vegan, but not a lacto-ovo vegetarian, diet was independently associated with a lower OR for CKD in patients with hyperuricemia. Other risk factors for CKD in patients with hyperuricemia include age, diabetes mellitus, hypertension, obesity, smoking, and very high serum uric acid levels (>9 mg/dL). Moreover, a vegan diet was linked to lower risks for very high uric acid levels and obesity, which are two important risk factors for CKD. Plant-based diets, defined as vegan and lacto-ovo-vegetarian diets, are growing in popularity worldwide [20]. Plant-based diets do not necessarily eliminate animal products but focus on eating mostly plants, such as fruits, vegetables, nuts, seeds, and whole grains. Plant-based diets also highlight eating whole foods without much processing that are as close to their natural state as possible. Plant-based diets are beneficial for metabolic health over animal-based diets [21]. CKD patients consuming plant-based proteins had a lower rate of disease progression or mortality [22,23]. Consistent with previous studies, our research showed that vegan or lacto-ovo vegetarian diets were associated with lower ORs (0.4 and 0.72, respectively) for obesity, which was further associated with a higher OR for CKD. This suggests that the renoprotective effect of a vegetarian diet in patients with hyperuricemia may be due partly to the improvement of metabolic overload. In addition, hyperuricemia could lead to uric acid stone formation and CKD [9,24]. Very high (more than 9 mg/dL) serum uric acid tripled the OR for incident CKD [7]. Our research also found that a serum uric acid level >9 mg/dL doubled the OR for CKD in patients with hyperuricemia. Furthermore, a lower dietary acid load may also favorably affect insulin resistance, insulin sensitivity, glycemic control, and other factors associated with CKD [25]. Vegan or plant-based diets have been shown to have a lower dietary acid load burden and increase 24 h urine pH [26,27,28]. Alkali treatment with vegetables and fruits has been shown to increase plasma total carbon dioxide and preserve the eGFR in patients with Stage 3 CKD [29]. Thus, patients with hyperuricemia consuming a vegan diet may have less crystallization of uric acid in the urine and a lower risk for subsequent CKD. The association of hyperuricemia with vegetarians and omnivores remains controversial. Gajski et al. reported no significant difference in uric acid levels between vegetarians and omnivores [30]. Another study found that vegans had higher serum uric acid concentrations than meat eaters [31]. Similar to our study, Szeto et al. found that vegetarians had lower uric acid concentrations than omnivores [12]. In addition, few studies have reported that lacto-ovo vegetarians have lower risks of hyperuricemia or gout [11,15]. Unlike our previous study [15], a lacto-ovo vegetarian diet was not significantly linked to lower ORs for very high serum uric acid levels and CKD in patients with hyperuricemia. Although high-level dairy product consumption is associated with a lower risk of gout in men [32], our result shows that vegetarians eating egg and dairy products may not have significantly lower risks of hyperuricemia and CKD. We need further prospective, large-scale, longitudinal studies to clarify the actual impacts of the lacto-ovo dietary habit on serum uric acid levels and CKD. Our study concurs with the previous findings that traditional risk factors of CKD, such as older age, diabetes mellitus, hypertension, obesity, smoking, and a very high level of serum uric acid, were significant risk factors for CKD in patients with hyperuricemia [3]. It is possible that these risk factors contribute to CKD in patients with hyperuricemia and in other populations through similar mechanisms. In contrast, our study shows that the male sex was associated with a $17\%$ lower risk for CKD in patients with hyperuricemia. Women have a higher prevalence of CKD according to previous population-based studies [33,34]. However, it is possible that the use of the CKD-EPI equation (which has not been widely validated in the Taiwanese population) to determine the eGFR resulted in the overdiagnosis of CKD in women because the measurement bias could lead to significant underestimation of the eGFR and misclassification in women [35]. In addition, women have longer life expectancy with a natural decrease in GFR during aging [33]. In the current study, we used the presence of proteinuria in conjunction with a reduced creatinine-based eGFR value to determine the diagnosis of CKD. Further studies are needed to elucidate the sex effect on CKD in patients with gout or hyperuricemia. Using a new creatinine- and cystatin C-based eGFR equation may also be needed to reduce the bias from the estimation of GFR by equations [36]. Hypertension, diabetes mellitus, and obesity are well-known modifiable risk factors for CKD. For decades, blood pressure control with angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers, strict blood glucose control, and weight control have been shown to prevent the development of CKD or disease progression. To date, whether hyperuricemia is a modifiable risk factor continues to be unclear. Although growing evidence has shown a significant relationship between hyperuricemia and CKD and the pathogenesis of uric acid nephropathy, treatment of asymptomatic hyperuricemia with urate-lowering medications is still controversial around the world. Recently, a meta-analysis also revealed that urate-lowering treatment did not slow the progression of CKD in patients with asymptomatic hyperuricemia [37]. Since the role of pharmacological treatments in patients with hyperuricemia remains unclear, our results will shed some light on non-pharmacological interventions for the prevention of incident CKD or its progression. Whether a vegan diet prevents the development of CKD in patients with hyperuricemia is worthy of further study by a randomized controlled trial or a large-scale cohort study in the future. Plant-based diets have many additional benefits to our health. First, many vegetables are rich in antioxidants, such as vitamins A (e.g., carrots), C (e.g., broccoli), and E (e.g., spinach), carotenoids (e.g., tomatoes and carrots), phenolic acids (e.g., potatoes), and flavonoids (e.g., onions) [38]. These antioxidants might enhance immune activity and reduce inflammatory responses to pathogens and chronic diseases. Thus, the lower risk for CKD associated with a vegan diet in patients with hyperuricemia may be at least partly attributed to consuming antioxidant-rich vegetables. Second, most vegetables are also rich in dietary fiber. An increase in the consumption of dietary fiber is proposed to prevent the development or to slow the progression of CKD for decades. Chiavaroli et al. reported that dietary fiber supplements could decrease blood urea and creatinine concentrations in a meta-analysis of controlled trials [39]. Their results may also support the possible underlying mechanism of the renoprotective role of a vegan diet in patients with hyperuricemia in addition to ameliorating the crystallization of uric acid in the kidney. Third, recent studies have shown that a plant-based diet could improve gut microbiota to mitigate oxidative stress and inflammation and reduce uremic toxins in patients with CKD [40]. Gut microbiota might also be a therapeutic target to prevent CKD in our study population. Further studies are needed to clarify the underlying mechanisms of the renoprotective effect of a vegan diet in patients with hyperuricemia. There are limitations of this study. First, the cross-sectional study design cannot determine the causal relationship between the vegan dietary habit and the subsequent development and progression of CKD in our study population. Second, the dietary habits were self-reported. Their actual eating habits were not confirmed by professional dieticians. However, the food frequency questionaries in the current study included detailed food items and categories and could easily be conducted by a research nurse. This method has been validated in previous studies [16,17]. Third, based on the retrospective study design, there may be unmeasurable confounding factors not included in the adjustment models. Forth, retrospective analysis of secondary data excluded 3045 patients with missing information who might be eligible for analysis. This may increase the uncertainty of the association between the primary study variable of interest and outcome. Fifth, the creatinine-based CKD-EPI equation may lead to an underestimation of the eGFR and may not be the optimal equation for determining the presence of CKD in Taiwanese women. Sixth, some changes to the equipment for anthropometric and blood pressure measurements and laboratory tests had been made during the long study period, although all equipment has been validated by the Taiwan Food and Drug Administration. Finally, the current study recruited participants from a single medical center and mainly from the Han Taiwanese population, and our results might not be generalizable to other nations or ethnicities. In conclusion, a self-reported vegan dietary habit but not a lacto-ovo vegetarian diet was significantly associated with lower risks of obesity and very high serum uric acid levels. Moreover, patients with hyperuricemia consuming a vegan diet had a $31\%$ lower risk for CKD. Prospective cohort studies are warranted to confirm our results. ## References 1. 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--- title: Ru(II) Complex Grafted Ti3C2Tx MXene Nano Sheet with Photothermal/Photodynamic Synergistic Antibacterial Activity authors: - Xiaofang Liu - Hongchi Xie - Shi Zhuo - Yuanhong Zhou - Mohamed S. Selim - Xiang Chen - Zhifeng Hao journal: Nanomaterials year: 2023 pmcid: PMC10051588 doi: 10.3390/nano13060958 license: CC BY 4.0 --- # Ru(II) Complex Grafted Ti3C2Tx MXene Nano Sheet with Photothermal/Photodynamic Synergistic Antibacterial Activity ## Abstract For a long time, the emergence of microbial drug resistance due to the abuse of antibiotics has greatly reduced the therapeutic effect of many existing antibiotics. This makes the development of new antimicrobial materials urgent. Light-assisted antimicrobial therapy is an alternative to antibiotic therapy due to its high antimicrobial efficiency and non-resistance. Here, we develop a nanocomposite material (Ru@MXene) which is based on Ru(bpy)(dcb)2+ connected to MXene nanosheets by ester bonding as a photothermal/photodynamic synergistic antibacterial material. The obtained Ru@MXene nanocomposites exhibit a strengthened antimicrobial capacity compared to Ru or MXene alone, which can be attributed to the higher reactive oxygen species (ROS) yield and the thermal effect. Once exposed to a xenon lamp, Ru@MXene promptly achieved almost $100\%$ bactericidal activity against Escherichia coli (200 μg/mL) and Staphylococcus aureus (100 μg/mL). This is ascribed to its synergistic photothermal therapy (PTT) and photodynamic therapy (PDT) capabilities. Consequently, the innovative Ru@MXene can be a prospective non-drug antimicrobial therapy that avoids antibiotic resistance in practice. Notably, this high-efficiency PTT/PDT synergistic antimicrobial material by bonding Ru complexes to MXene is the first such reported model. However, the toxic effects of Ru@MXene materials need to be studied to evaluate them for further medical applications. ## 1. Introduction The COVID-19 pandemic pushed public health to a threshold of collapse in 2020. As the COVID-19 pandemic drives up the usage of antibiotics, it will eventually contribute to higher rates of bacterial resistance and affect the disease burden and mortality rates [1]. The emergence and widespread spread of superbugs has become a challenging health issue worldwide owing to the dramatic evolution of drug-resistant genes in bacteria [2,3,4,5]. Accordingly, it is imperative that new, reliable and effective antimicrobial approaches are available globally to combat the escalation of bacterial resistance. Compared to traditional antibiotic sterilization, light-controlled sterilization not only cures the infection and eliminates inflammation effectively in a short period of time, but it also has the advantage of less toxicity and fewer side effects [6,7,8]. Thus, numerous researchers have devoted themselves to the study of light-triggered sterilization strategies, such as activated oxygen species (ROS)-associated photodynamic therapy (PDT) and thermo-induced photothermal therapy (PTT), both of which strongly rely on the synthesis of light-activated nanomaterials [9,10,11,12]. Currently, the most well-known categories of photothermal materials include precious metal nanoparticles [13,14], metal oxides [15], metal sulphides [16,17], carbon materials [18,19,20,21,22,23], phosphorus monomers [24] and polymers [25,26]. Taking advantage of the functional nanomaterials, it is feasible to integrate PDT and PTT into a monolithic platform where synergistic treatment can remarkably enhance the antimicrobial capacity. To illustrate, Wang and his coworkers reported an urchin-shaped Au@Bi2S3 core-shell nanoparticle with a synergistic NIR-triggered function of photothermal/photodynamic effects for bacterial sterilization [27]. However, two–dimensional nanomaterials of transition metal carbides (MXenes) have gained increased attention recently for biological applications, as they are characterized by a large specific surface area, high electrical conductivity [28], outstanding biocompatibility [29,30], excellent photothermal conversion [31] and ease of functionalization [6,32]. Therefore, it can be used as a photo-induced antibacterial agent. The abundance of functional groups (-OH, =O and -F) on Ti3C2 MXene’s surface gives it anchor points. Reports have already been published on the photothermal antimicrobial therapy application of MXene combined with other materials. For instance, Liu et al. [ 33] developed a heterogeneous structured coating (MXene/CoNWs) that achieves a greater than $90\%$ antibacterial rate against Gram-positive/Gram-negative bacteria within 20 min due to the synergistic effect of NIR-triggered ROS and thermal therapy. However, visible light-assisted therapy is more accessible and available than NIR light. Cheng et al. [ 34] constructed organic–inorganic hybrids of ZnTCPP/Ti3C2TX by a hydrothermal method, which enhanced visible light absorption and catalysis, while ZnTCPP/Ti3C2TX could trap bacteria electrostatically and significantly improved visible light sterilization efficiency. These active antibacterial nanomaterials have the potential to be made available for diverse practical applications, such as medical devices, textiles and building materials, where its antimicrobial properties could help prevent the growth and spread of hazardous bacteria. As an illustration, active antibacterial nanomaterials can be coated on the surface of medical masks to eliminate bacteria or viruses against cross-infection; in addition, they can also be applied to prepare antibacterial walls, antibacterial flooring and antibacterial windows and doors, which may effectively kill bacteria and contribute to better indoor hygiene. Heretofore, light-responsive antibacterial properties of MXene covalently bonded with ruthenium complexes and coupling PTT and PDT properties by xenon lamp has barely been reported. Among the transition metal series, ruthenium can form very strong ruthenium(II) complexes due to its lower energy barrier (0.125 nm), easy solubility in water, small atomic size, and high nuclear charge [35]. The centrally located ruthenium atom is actually a structural center that supports a three-dimensional ligand skeleton with a rigid structure, allowing the ligand to be easily substituted or modified to generate numerous ruthenium(II) complexes with various structural properties. Among the modifications are some simple chemical modifications, the combination of complexes with organic small molecules, the introduction of chiral groups and the incorporation of some ligands with anticancer and antibacterial activities [36]. Antibacterial ruthenium(II) metal complexes provide the following characteristics [37,38,39,40,41,42,43]: [1] Carrier. The metal center acts as a carrier for active ligands (usually drugs) that enhance drug activity by temporarily coordinating with the metal portion. [ 2] Catalyst. Metal complexes act as catalysts, that is, substituting inert complexes can catalyze redox cycles and oxidize glutathione (GSH) to glutathione disulfide (GSSG), resulting in a significant increase in reactive oxygen species (ROS) and high cytotoxicity to bacteria. [ 3] Photosensitizer. Metal complexes are photoactive and can be used as photosensitizers, and polypyridine ruthenium(II) complexes can retain the ability to produce singlet oxygen due to their intense visible light absorption and abundant excited state properties [44,45]. The long-term trilinear excited states of Ru(II) complexes exhibit particularly robust redox properties and can facilitate intermolecular electron transfer or energy transfer [46,47,48]. Therefore, Ruthenium complexes can serve as potential candidates for photodynamic therapy (PDT) against diseases caused by microbial pathogens. Photodynamic therapy (PDT) is mainly performed by two mechanisms, SN-I or SN-II [11]. The SN-I mechanism is where the activated PS contacts directly with biomolecules and then reacts to yield free radicals which can eventually kill bacteria or react with oxygen molecules to produce superoxide ions (•O2-) or hydroxyl radicals (•OH). The SN-II mechanism involves the interaction of the excited PS with the ground state oxygen molecule (3O2) to release the extremely toxic singlet oxygen (1O2). In this study, the SN-II monoclinic oxygen mechanism is considered to be predominant. Inspired by above-mentioned considerations, and in order to solve the issue of bacterial resistance to antibiotics and the poor therapeutic effect of photosensitizers or nanomaterials alone, a synergistic photoinduced photothermal/photodynamic therapy (PTT/PDT) antimicrobial strategy was investigated. The ruthenium complex and MXene are self-assembled to form a covalent bond through a surface functional group reaction, such that the ruthenium complex is loaded onto the surface of MXene to produce the Ru@MXene nanocomposite system (Figure 1). Therefore, a synergistic antibacterial system with three-in-one antibacterial mechanism, including ultra-thin MXene nanosheets physically cutting cell membranes, PTT and PDT, can be achieved, which provides a new idea for alternative antibiotic therapy (Figure 2). ## 2.1. Materials RuCl3-3H2O, Dimethyl sulfoxide (DMSO, $99.9\%$, AR), 5,5′-Dithiobis (2-nitrobenzoic acid) (DTNB, $98\%$, AR), Glutathione (Reduced) (GSH, $98\%$, AR), 2,7-Dichlorodihydrofluorescein diacetate (DCFH-DA, $99\%$) and 4-Dimethylaminopyridine (DMAP, $99\%$) were supplied by Aladdin company (Shanghai, China). 2,2′-bpyrine (bpy, $99\%$, AR), 1,3-diphenylbenzofuran (DPBF, $97\%$, AR), $2.5\%$ Glutaraldehyde Solution, N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide hydrochloride (EDCI, $98.5\%$), N,N-Dimethylformamide (DMF, $99.5\%$, AR), Lithium chloride (LiCl, $99\%$) and Lithium fluoride (LiF, $99\%$, AR) were supplied by Macklin company (Shanghai, China). 2,2-bipyridine-4,4 dicarboxylic acid ($98\%$) was supplied by Energy Chemical company (Shanghai, China). Ti3AlC2 (MAX, 200 mesh, $98\%$) was supplied by Laizhou Kai Kai Ceramic Materials Co., Ltd. (Shandong, China). Hydrogen peroxide (H2O2, 30 wt%) and Hydrogen chloride (HCl, 37 wt%) was from Guangzhou Chemical Reagent Factory (Guangzhou, China). ## 2.2. Characterization Field emission scanning electron microscopy (FE-SEM, HT7700, Hitachi, Tokyo, Japan) was applied to measure the micromorphology of samples and the elements content of loading with an acceleration voltage of 15 kV at a magnification of 20,000×. Scanning electron microscopy (SEM, Phenom World ProX, Eindhoven, The Netherlands) was applied to observe the macroscopic morphology of multi-layer MXene with accelerating voltages of 15 kV at a magnification of 20,000×. The SEM samples were dispersed in ethanol, dropped on silicon wafers, dried at room temperature and pasted on conductive adhesive and the surface morphology of the samples was observed after spraying gold on the sample surface. The transmission electron microscope (TEM, HT7700, Tokyo, Japan) was used to observe the microstructures of samples and bacteria with accelerating voltages of 120 kV at a magnification of 8000×. The X-ray diffractometer (XRD, MiniFlex 600, Rigaku, Tokyo, Japan) applied to measure the crystallization of the sample was equipped with a Cu-Kα tube and a Ni filter (λ = 0.1542 nm) and operated at 40 kV, a current of 30 mA, a sweep speed of 5°/min and a test scan angle of 5° to 80°. The stripping state and thickness of MXene were evaluated by atomic force microscopy (AFM, Bruker Dimension FastScan, Karlsruhe, Germany). The X-ray photoelectron spectroscope (XPS, Escalab 250Xi, Thermo Fisher, Waltham, MA, USA) was used to test the elements’ compositions. Fourier transform infrared (FTIR) spectra measurements were performed with a resolution of 4 cm−1 and a range from 400 to 4000 cm−1 with 16 scans (Thermo Fisher Nicolet 6700, Waltham, MA USA). Nano particle size and Potential analyzer (BI-200SM Brookhaven, Brookhaven, Holtsville, NY, USA,) was applied to measure the potential of the sample. The ultraviolet–visible (UV–vis) absorption spectra was tested by UV–vis spectrophotometry (Lambda 950, PerkinElmer, Waltham, MA, USA) to determine the absorption of light by the sample. Photoluminescence (PL) spectra were recorded on a HORIBA spectrometer (Fluorolog-3, Edison, NJ, USA). Ultra-high-performance liquid chromatography (UPLC) ESI mass spectrometry was performed on a Shimadzu LCMS-2020 system (Shimadzu, Kyoto, Japan). The NMR structures were analyzed by a Bruker AVANCE III 400 MHz Superconducting Fourier spectrometer (NMR, Bruker, Fällanden, Switzerland). The bacteria were observed with an Airscan laser confocal microscope (Carl Zeiss, Jena, Germany) and an inverted fluorescence microscope (Olympus, Tokyo, Japan). The photothermal performance tests were conducted under the simulated sunlight provided by the xenon lamp (CEAULIGHT, CEL-HXUV300, Beijing, China). The infrared thermal imager (MAGNITY MAG12, Shanghai, China) was applied to record the change of sample temperature with time during the measurement. The photodynamic property measures were conducted under the simulated sunlight provided by the 532 nm semiconductor lasers (MW-SL-532, Changchun Laser Optoelectronics, Changchun, China). ## 2.3. Ti3C2Tx MXene Preparation The MXene nanosheets were prepared according to the previously reported procedure, which was developed to produce high yields of the MXene nanosheets [49]. Briefly, the HCl/LiF etchant was processed by adding 3.2 g LiF to 40 mL 12 M HCl. Next, 2 g Ti3AlC2 ceramic powders (200 mesh) were slowly added to the above mixture and stirred continuously at 40 °C for 48 h. Afterward, the resultant Ti3C2Tx suspension was rinsed with deionized water and centrifuged for 5 min until the pH of the supernatant was approximately 7. The obtained Ti3C2Tx sludge was dispersed in deionized water and treated by sonication and shaking in an ice bath for 3 h. The mixture was centrifuged for 1 h to obtain a supernatant with a monolayer of the Ti3C2Tx nanosheet and dried by vacuum freezing. ## 2.4. Synthesis of cis-[Ru(bpy)2Cl2]·2H2O A suspension of RuCl3-3H2O, 2,2′-bpyrine (bpy) and LiCl in DMF was heated and refluxed under argon atmosphere for 12 h. The mixture was cooled to room temperature and acetone was added. Subsequently, the mixture was stored overnight at −20 °C to obtain crude dark green crystals. The precipitate was filtered and washed with ice water and acetone until the filtrate was almost colorless. Eventually, the crystals were dried in vacuum dryers to give a good yield of pure dark green cis-[Ru(bpy)2Cl2]·2H2O crystals. ## 2.5. Synthesis of Ru(bpy)2(dcb)Cl2 Cis-[Ru(bpy)2Cl2]·2H2O and 2,2-bipyridine-4,4 dicarboxylic acid were added in 50 mL of ethanol and the pH adjusted to be alkaline with 1 M NaOH. The mixture was dissolved and refluxed at 80 °C for 6 h under the argon atmosphere. When the reaction was completed, the pH was adjusted to be acidic, and the solvent was removed. Subsequently, the precipitate was removed by successive centrifugation with water and ethanol. The clarified filtrate was filtered and dried in a vacuum desiccator to obtain orange-red crystals Ru(bpy)2(dcb)Cl2. ESI-MS (CH3OH): m/z: 329.04 (Figure S4). 1H NMR (400 MHz, DMSO): δ 8.85 (d, $J = 8.2$ Hz, 4H), 8.79 (s, 2H), 8.15 (dd, $J = 13.0$, 6.6 Hz, 4H), 7.74 (d, $J = 5.4$ Hz, 6H), 7.66 (d, $J = 5.7$ Hz, 2H), 7.53 (t, $J = 6.7$ Hz, 4H) (Figure S3). ## 2.6. Fabrication of Ru@MXene Nanocomposites The MXene nanosheets were further modified by esterification between the carboxyl group of Ru(bpy)2(dcb)Cl2 and the hydroxyl group of MXene nanosheets [50]. A uniformly dispersed MXene suspension was obtained by ultrasonication in an ice bath for 30 min and Ru(bpy)2(dcb)Cl2 was added. A water-soluble composite catalyst composed of EDCI and DMAP (mass ratio 1:1) was added to facilitate the reaction. The reaction was carried out at 100 °C for 3 h. The mixture was repeatedly washed with deionized water and centrifuged several times. Finally, the product was freeze-dried to obtain Ru@MXene. ## 2.7. Load of Ru on Ru@MXene The fluorescence spectrum of the Ru solutions at concentrations of 0.0625, 0.125, 0.25, 0.5, 1, and 2 μM was determined using a fluorescence spectrometer, and these data were used to construct standard curves of Ru solutions [51,52]. Briefly, 8 μL of a 5 mg/mL Ru@MXene dispersion was added to 10 wt% NaOH solution at a final concentration of 10 μg/mL. The mixture was incubated in a shaking incubator for 24 h to break ester bonds. The mixture was filtered, and the supernatant liquid was used to check the fluorescence spectrum of Ru(bpy)(dcb)Cl2. This was employed to determine the content of Ru in solution, calculated using the standard curve (Figure S5). ## 2.8. Detection of ROS The UV spectrum of 1,3-diphenylbenzofuran (DPBF) used as a monoclinic oxygen (1O2) trapping agent has a maximum absorption peak at 417 nm, while its oxidation by monoclinic oxygen leads to a lower absorption peak here. The entire test was carried out in a quartz cuvette in a dark environment. Briefly, 24 μL of DPBF (10 mM, dissolved in DMSO) was added to MXene/DMSO, Ru/DMSO, Ru@MXene/DMSO and DMSO. The solutions were then irradiated using a 532 nm LED lamp (laser power: 20 mw). The absorption spectra of the mixtures after 532 nm laser irradiation were measured using a UV–Vis spectrometer. the DPBF/DMSO group was used as a control experiment. ## 2.9. Photothermal Experiments Xenon lamps were used to irradiate different concentrations of Ru@MXene dispersions (0, 20, 50, 100 μg/mL) and different samples (Water, MXene, Ru, Ru@MXene) for 30 min, while the real-time temperature of the samples was recorded and photothermal images were obtained at intervals by infrared thermal imagers. The thermal stability of the sample was tested by cyclic heating and cooling tests, where the light source was removed after a heating cycle had been completed until it cooled to room temperature, then the light source was lit again; this process was repeated for 5 cycles. Meanwhile, an infrared thermal imager recorded the real-time temperature of the sample. A xenon lamp equipped with an AM 1.5 G filter (150 mW/cm2) was used as the light source. ## 2.10. Antibacterial Activity Assessments Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were used as bacterial models. The antibacterial activities of the samples were evaluated by the plate-counting approach, Live/Dead staining and the TEM observation of bacteria. The bacteria were cultured in LB medium at 37 °C for 12 h. Afterwards, the cell solution was centrifuged at 5000 rpm for 5 min, and the precipitate obtained was washed with sterile water three times. Finally, the cell precipitate was resuspended in sterile water and diluted to an approximate cell concentration of 107 CFU/mL. The bacterial solution was mixed with the materials (materials’ final concentration: 110 μg/mL for Ru@MXene, 15 μm for Ru, and 100 μg/mL for MXene. The concentrations of Ru and MXene are consistent with the ratio in Ru@MXene) and incubated at 37 °C for 1 h. The mixture was separated into a light group and a dark group. The light group was irradiated with a xenon lamp for 30 min while the dark group was untreated. A xenon lamp equipped with an AM 1.5 G filter (150 mW/cm2) was used as the light source. Next, 100 μL of the mixture was dispensed onto the solid medium and spread well. Finally, plates were incubated at 37 °C for 24 h. The experiments were carried out using the bacterial solution without any materials as a blank control. The TEM can more directly and clearly observe the changes of bacterial morphology. First, the bacterial suspension was mixed with the material and incubated for 1 h at 37 °C with shaking. The cells were washed three times with water, collected by centrifugation and then fixed in $2.5\%$ paraformaldehyde fixative for 5 h. The supernatant was discarded by centrifugation at low speed. The cells were dehydrated in a gradient of $20\%$, $30\%$, $50\%$, $70\%$, $90\%$ and $100\%$ ethanol for 15 min. Finally, the morphology of the treated bacteria was observed by transmission electron microscopy. Bacterial live/dead staining was also employed to test the antimicrobial activity of the samples. Following light exposure, propidium iodide (PI) and acridine orange (AO) were utilized to stain the bacteria (AO marked live bacteria as green and PI marked dead bacteria as red). The staining procedure took roughly 20–30 min. The dye was subsequently removed and the cells washed twice with PBS. The final observation was performed by Laser Confocal Microscopy. Reactive oxygen species (ROS) detection was undertaken using a reactive oxygen species detection kit. Samples in the light and dark groups after treatment were incubated with 10 μM 2,7-dichlorodihydrofluorescein diacetate (DCFH-DA) for 20–30 min and washed with PBS. Bacterial cells were inspected using a fluorescent inverted microscope. ## 2.11. Ellman’s Assay The materials were mixed with GSH solution (50 μL, 0.8 mM) and then incubated in the dark for 10 min to reach an equilibrium between adsorption and desorption. The mixture was then exposed to a xenon lamp (150 mW/cm2, 30 min) or treated in the dark. Subsequent to treatment, phosphate buffer solution (800 μL, pH = 8) and DTNB solution (20 μL, 10 mM) was added to the mixture. The mixture was filtered to remove the material. Finally, the supernatant absorbance was measured with a UV–Vis spectrophotometer at 412 nm. H2O2 and GSH were established as positive and negative controls, respectively. ## 3.1. Morphological Observations To address the bacterial resistance barrier, a novel Ru@MXene 2D nanoplatform with photothermal/photodynamic synergistic antimicrobial properties has been designed and developed as shown in Figure 1 and Figure 2. Initially, Ti3AlC2 ceramics were etched to remove the aluminum layer, utilizing a HCl/LiF solution to obtain multilayer Ti3C2Tx, and ultra-thin Ti3C2Tx nanosheets were obtained by means of ultrasonication. Subsequently, ruthenium complexes with photodynamic properties were grafted onto the Ti3C2Tx surface, and eventually the nanocomposite Ru@MXene with both photothermal and photodynamic properties was obtained (Figure 1). In order to observe the surface morphology and spatial structure of the prepared nanomaterials, SEM, TEM, Mapping and AFM were selected for characterization. The SEM image in the Figure 3a shows that the MAX phase Ti3AlC2 has been etched with HF (LiF + HCl) and has changed from a stacked structure to a unique accordion-like shape with a clearer and more defined layer structure. The TEM micrograph clearly shows that both Ti3C2Tx (Figure 3b) and Ru@MXene (Figure 3c) have translucent images with clear edges and unique shapes. The AFM pattern of the MXene nanosheets is illustrated in Figure 3e. It is evident that the area marked by the white line has a uniform height distribution between approximately 2.6–3.1 nm, which corresponds to a Ti3C2Tx monolayer of roughly 2.7 nm [53]. These imply that MXene has an ultra-thin structure. Subsequently, the elemental mapping (Figure 3d) revealed a dispersed distribution of N and Ru elements in Ru@MXene, proving the presence of Ru(bpy)2(dcb)2+ and the successful immobilization of Ru(bpy)2(dcb)2+ on the surface of the MXene nanosheets. Moreover, the well-dispersed Ti and C elements are evidence that MXene is a carrier for Ru(bpy)2(dcb)2+. ## 3.2. Chemical Structure Analysis The chemical structures of MXene, and Ru@MXene were confirmed by XRD, FT-IR, ζ-potential and XPS. X-ray diffraction (XRD) was used to analyze the crystal structures of Ti3AlC2, Ti3C2Tx and Ru@MXene. As shown in Figure S1, the [104] peak of Ti3AlC2 disappears in the XRD pattern of Ti3C2Tx, indicating the successful removal of the Al layer after etching. The [002] peak of the multilayered Ti3C2Tx shifts to a lower 2θ degree due to the increased layer spacing compared to the stacked Ti3AlC2 [50]. As shown in Figure 4a, it is noteworthy that the [002] peak of Ru@MXene is further shifted to a lower angle of 0.91° compared to the multilayer Ti3C2Tx, corresponding to a remarkable increase in the layer-to-layer spacing of Ti3C2Tx [54] ascribed to the super-thin nanosheet fabrication. As can be seen from the IR spectra in Figure 4b, both MXene and Ru@MXene show typical characteristic bands at 3431, 1632 and 562 cm−1, which correspond to the stretching vibrations of -OH, C=O and Ti-O, respectively. After modification with ruthenium complexes, absorption bands associated with ester bonds appear at 1088 and 1049 cm−1 [54,55], indicating successful esterification between Ru-COOH and the MXene nanosheets. The mapping results are consistent with the FT-IR results, that is, both show that Ru(bpy)2(dcb)2+ has been modified on the surface of MXene. More specifically, Ru(bpy)2(dcb)2+ is adsorbed onto MXene via ester bonding and electrostatic interaction. In addition, the ζ-potential was used to demonstrate the electrostatic interaction between MXene and Ru(bpy)2(dcb)2+. The zeta potential data in Figure 4c authenticate that MXene exhibits a robust negative charge of −25.5 mV, allowing MXene to be extremely stabilized in aqueous solution. As a result, during the synthetic stage of Ru@MXene, the surface of MXene is electronegative and may readily absorb Ru(bpy)2(dcb)2+ cations by electrostatic effects. The ζ-potential was turned from −25.5 to −13.3 mV via grafting Ru(bpy)2(dcb)2+ onto MXene, since the electronegative MXene was neutralized by Ru(bpy)2(dcb)2+. In contrast, Ru(bpy)2(dcb)2+ exhibited an opposite charge of 9.0 mV. Therefore, Ru@MXene tended to be electrically neutral after chemical bonding of MXene and Ru(bpy)2(dcb)2+. These are obvious evidence for the successful preparation of Ru@MXene composites. The formation of the ester linkage and chemical structure variation of Ru-MXenes is also further supported by X-ray photoelectron spectroscopy (XPS). The survey scan spectrum of Ru@MXene in Figure 4d exhibits a new N1s peak and increased O1s peak intensity compared with pure MXene, which is ascribed to the N and O elements presenting in Ru(bpy)2(dcb)2+. The chemical bond variations were further revealed by the different chemical coupling state of C atoms. As shown in Figure 4e, the C 1 s core-level pattern could be curve-fitted with six peak components, including 281.4 (C-Ti), 282.1 (C=C), 283.6 eV (C-Ti-O), 284.8 (C-C), 286.2 (C-O), and 288.7 (C-C=O/C-F) [50,56]. After modification by Ru(bpy)2(dcb)2+, a new-emerging peak at approximately 285.6 eV assigned to a C-N bond and the augmented C=O/O-C=O peak intensities in C 1 s spectra of Ru@MXene (Figure 4f) illustrate the successful esterification reaction between the hydroxy groups of MXene nanosheets and carboxyl groups of serine molecules. The UV–Vis absorption spectra of the Ru(II) complexes in aqueous solution at room temperature are shown Figure S2. The strong and sharp absorption bands in the UV region of the prepared Ru(II) complexes are attributed to electron transfer leaps within the C^N ligand and the N^N ligand. The strong absorption of Ru(bpy)2(dcb)2+ at 400–500 nm indicates its efficient photon absorption and utilization. In spite of the fact that TGA analysis is a valid approach to determine drug loading, we have established our drug loading via the fluorescence intensity measuring methods and a standard curve. According to the calculation, the concentration of Ru in MXene is 1.39 μmol/L (Figure S5). ## 3.3. Photodynamic Properties To evaluate the photodynamic properties of the materials, DPBF was employed as the ROS trapping agent to determine their ability to generate singly linear oxygen (1O2) under 532 nm laser irradiation (20 mw). If DPBF is oxidized by ROS, its UV absorption peak at 417 nm will diminish. Figure 5 shows the changes in UV absorption under 532 nm laser irradiation for pure DPBF, Ru/DPBF, MXene/DPBF and Ru@MXene/DPBF. Figure 5a of the control group (pure DPBF) showed almost no change in its absorption peak under 532 nm LED lamp illumination for 30 min, indicating that pure DPBF does not produce singlet oxygen. The absorbance at 417 nm of MXene/DPBF group only decreased by $8.14\%$, implying that the photodynamic performance of MXene is poor, as shown in Figure 5c. In contrast, the maximum absorption peak of DPBF decreased by $87.73\%$ after light exposure for the Ru/DPBF group in Figure 5b, revealing that Ru has excellent photodynamic properties and is able to generate more singlet oxygen at the same intensity and illumination time. Significantly, the absorbance of the Ru@MXene (Figure 5d) dropped by almost half. Ru@MXene generated reactive oxygen species at a rate slower than that of free Ru, though both yielded their own optimum amounts of reactive oxygen species, illustrating that incorporating Ru onto MXene nanosheets gives the Ru@MXene composite systems that preserve the capacity for the creation of reactive oxygen species by Ru alone. The modified Ru@MXene has a fall in the efficiency of 1O2 compared with Ru, which may be due to the shielding effect of MXene flakes. These phenomena can be interpreted through an in-depth insight into the photosensitization process of singlet production. There are three stages of the photosensitization procedure for PDT as shown in Figure 2. As soon as Ru has an electronic transition energy equivalent to that of the incident photon, absorption occurs. Electrons are shifted from the ground singlet state (S0) to an excited singlet state (S1) with higher energy [57]. Excited electrons from S1 transit to the excited triplet state (T1) via altering the orientation of the electron spin in the non-radiative inter-system crossing (ISC) pathway (II) [58]. The singlet oxygen (1O2) originates through an energy transfer route involving collisions from T1 to molecular oxygen (III) with a Type II mechanism [59]. ## 3.4. Photothermal Properties The photothermal properties of the samples were assessed using a xenon lamp light source that simulates sunlight, and a schematic model of the irradiated samples is shown in Figure 6f [60]. To assess the effect of optical power density on the photothermal properties, the Ru@MXene dispersion (110 μg/mL) was exposed to a gradient of power (50, 100, 150 mW/cm2). As shown in Figure 6a, it can be clearly seen that the 50 mW/cm2 group showed an increase in minimum temperature from 26.9 °C to 40.3 °C. As the optical power density increased to 100 mW/cm2, the maximum temperature increased to 45.4 °C. Meanwhile, the 150 mW/cm2 group reached a maximum temperature of 53.2 °C. Therefore, high-power intensity will raise the final temperature of the materials under xenon lamp illumination. After exploring the link between power intensity and photothermal properties, Ru@MXene solutions (0, 20, 50 and 100 μg/mL) of gradient concentrations were individually exposed to the xenon lamp (150 mW/cm2) to investigate the relationship between photothermal properties and sample concentration, as shown in Figure 6b. Final temperatures were improved from 26.9 to 38.0, 45.3, 48.0 and 50.4 °C for the 0, 20, 50 and 100 μg/mL concentration groups, respectively. Benefiting mainly from the broad solar spectral absorption and the localized surface plasmon resonance (LSPR) effect of MXene, the MXene nanomaterial has excellent photothermal conversion properties and is able to collect and convert solar energy efficiently [61]. Furthermore, the optical power density (L) is almost linearly related to the saturation temperature (T), as can be seen from the S-plot (Figure S6). To further demonstrate the photothermal effect of Ru@MXene, three samples of Ru (15 μM), MXene (100 μg/mL) and Ru@MXene (110 μg/mL) were employed for comparative photothermal testing and the results are shown in Figure 6c. These concentrations were calculated corresponding to the Ru loadings. The heating process can be visualized from the photothermal image in Figure 6d. It is evident that both MXene and Ru@MXene exhibit excellent photothermal properties compared with the Ru(II) complex. This is due to the laminar structure of MXene resulting in a continuous thermal conductivity interface, which enhances the thermal performance of Ru@MXene. Furthermore, the temperature change profile (Figure 6e) for five cycles under constant illumination of 150 mW/cm2 is essentially the same, also confirming the cyclically stable heating performance of Ru@MXene as a photothermal therapeutic material. Thus, all the above results and mechanisms confirm the potential of Ru@MXene as a photothermal antimicrobial agent. ## 3.5. Photoinactivation of E. coli and S. aureus As stated in the introduction, we assumed that high heat and ROS generated by light could inhibit the growth of bacteria. Therefore, the antibacterial performance of Ru, MXene, Ru@MXene materials was evaluated by the flat-counting method in the dark and under illumination, respectively. Escherichia coli (Gram-negative) and Staphylococcus aureus (Gram-positive) bacteria were made available as the model bacteria, and xenon lamps provided the light source. The minimum bactericidal concentration (MBC) of the samples was studied according to the protocol described elsewhere with appropriate adjustments (Figure S7) [27,62]. Bacterial colony photos (Table S1) recorded MBC values of 200 μg/mL for E. coli and 100 μg/mL for S. aureus, while the bacteria survival rate of E. coli and S. aureus treated with Ru, MXene and Ru@MXene under dark and light conditions gradually declined as depicted in Figure S8. It was revealed that Ru@MXene had exhibited excellent light-activated antibacterial capabilities against both Gram-positive and negative bacteria in the presence of light. The photoactive antibacterial effects of materials (Ru, MXene and Ru@MXene) via the flat-counting method under dark and light conditions were investigated as depicted in Figure 7 (E. coli: dark group (a1–a4), light group (b1–b4)) and Figure 8 (S. aureus: dark group (a1–a4), light group (b1–b4)). MXene displayed favorable antibacterial activity against E. coli and S. aureus under light exposure, which is attributed to the optimal photothermal properties of MXene. The antibacterial test results were in accordance with the photothermal performances indicated in Figure 6. According to the temperature captured by the infrared thermography, the final surface temperature for both MXene and Ru@MXene dispersions reached 53.2 °C (Xenon lamp, 150 mw/cm2). However, normal cells and tissues are also damaged when the photothermal temperature of the bacteria is heated to over 50 °C [63]. The light group of Ru@MXene was noteworthy for its more pronounced bactericidal effect than the monotherapy group (Ru group or MXene group). The photodynamic properties of Ru@MXene in Figure 5d showed that the UV absorption of the DPBF in the Ru@MXene group dropped by almost $50\%$ after 30 min illumination with the 532 nm laser, giving rise to a large amount of singlet oxygen, that is to say, the Ru@MXene composite system has excellent photodynamic antibacterial properties. This indicates that upon loading Ru on the surface of MXene sheet, the Ru@MXene composite system can generate a massive amount of singlet oxygen under illumination, and the antibacterial performance against E. coli and S. aureus is substantially improved. The Ru@MXene complex exhibits well-developed PTT/PDT synergistic antibacterial efficacy, owing to high temperature and ROS generation upon light exposure which are more likely accessible to bacteria. In other words, the attached bacteria are more vulnerable to be killed. Moreover, Ru@MXene proved to be more strongly antibacterial against S. aureus than E. coli, which is probably related to the structural variations in the cell walls of Gram-positive and Gram-negative bacteria [64]. A comparison of the antimicrobial efficiency among some PTT and PDT drugs are also listed. Table S2 includes conditions such as antimicrobial mechanism, nanomaterial concentration and antimicrobial activity [27,33,34,65,66,67,68,69,70]. It is observed that the antibacterial properties of MXene and its composites are outstanding under similar conditions. To further explore the effect of light-activated antibacterial activity, live/dead fluorescence detection of S. aureus and E. coli was carried out using Acridine Orange (AO) and Propidium Iodide (PI). The confocal laser scanning microscope (CLSM) was made available to visualize the color of the stained bacteria. Figure 7 (E. coli: dark group (c1–c4), light group (d1–d4)) and Figure 8 (S. aureus: dark group (c1–c4), light group (d1–d4)) displayed the fluorescent staining results of the bacteria after being treated with the light and dark in the presence of materials (Ru, MXene, and Ru@MXene). A large proportion of bacteria in the blank group were stained with green fluorescence, implying that the majority of bacteria were still alive. E. coli and S. aureus that had been treated with Ru@MXene in the light group were stained red by PI (and S. aureus was more affected than E. coli). Consequently, treatment of bacteria with Ru@MXene in the light group led to almost all their death. The bacteria treated with Ru@MXene generated redder signals than MXene and Ru in the light group, indicating its superior antibacterial activity. This was in accordance with the results of previous tests. Overall, the results reveal that Ru@MXene possesses excellent photo-activated antimicrobial activity. ## 3.6. Investigation of the Mechanism of Synergistic Antibacterial Effect TEM was utilized to visualize the variation in the morphology of both E. coli and S. aureus after treatment with materials. This experiment further confirms the ability of bacteria to survive after being treated with nanomaterials (but it also provides insight into the antibacterial mechanism of nanomaterials). As shown in Figure 9, E. coli and S. aureus showed varying degrees of deformation (marked by red arrows), while the S. aureus (spherical shape) wrapped in MXene or Ru@MXene nanosheets in dark conditions had a relatively smooth and well-integrated cell wall. After 30 min exposure to xenon light, the cell walls of S. aureus in contact with MXene and Ru@MXene were shrunken and deformed along with a variation in their size. In particular, the leakage of cell contents was observed in the majority of bacterial cells treated with Ru@MXene. This confirmed that bacteria were synergistically killed by the PTT/PDT effect within a short period of time, rendering the integrity of the cell wall and cytoplasmic membrane of both Gram-positive and Gram-negative bacteria heavily fragmented. Furthermore, the material has the capacity to break down cell membranes, allowing access to the inside of the cell, generating heat and ROS under light and eventually leading to self-destructive death. To further explore what biological alterations occur upon entry of materials into cells causing bacterial death, the variation of ROS levels in bacteria and whether oxidative damage leads to bacterial death were investigated. Some antibiotics have been reported to kill bacteria through inducing ROS production and, in turn, inhibiting oxygenase activity. Therefore, the total ROS content was monitored by use of a reactive oxygen probe. It is shown in Figure 10 that when bacteria and materials were co-cultured for 1 h, the ROS levels in the light group treated with MXene still remained low, and those of S. aureus and E. coli treated with Ru and Ru@MXene were considerably raised. These results demonstrated that the antimicrobial activity of these materials was correlated with the ROS generation and consistent with previous in vitro testing of ROS levels in Figure 5. Ru@MXene in the light group induces high levels of ROS in bacterial cells due to its entry into the cell and disrupts the cell membrane of bacteria, causing oxidative damage and affecting the activity and function of macromolecules in bacteria, ultimately killing them and exhibiting high antimicrobial activity. It is widely acknowledged that glutathione (GSH) is the predominant antioxidant sulfhydryl species in bacteria and serves an essential antioxidant role in the repair of oxidative protein damage [71]. It allows the material’s ROS production capacity to be tested indirectly by measuring the GSH consumption. The sulfhydryl group of GSH is able to react with 5,5′-dithiobis-(2-nitrobenzoic acid) (DTNB) to yield both yellow 2-nitro-5-mercaptobenzoic acid (TNB) and glutathione disulfide (GSSG), as shown in Figure 11c. TNB has a characteristic absorption peak at 412 nm and the GSH level can be quantified by the absorbance value variation. The color variations of the GSH solutions were photographed after being incubated with various materials in the presence or absence of light as shown in Figure 11a. The rate of GSH loss was calculated with absorption values as shown in Figure 11b. In the MXene group, almost no color alteration was observed with or without light, demonstrating the lack of oxidative activity of MXene alone, which is due to the fact that MXene only has PTT and PTT itself does not cause bacterial inactivation through oxidative stress. With respect to the Ru and Ru@MXene groups, the rate of GSH depletion in the dark was $2.57\%$ and $7.22\%$, respectively. After illumination, the corresponding ratios increased further to $96.03\%$ and $82.33\%$, as both had PDT, generating large amounts of ROS and thus oxidizing GSH. Accordingly, the outcomes of this assay prove that Ru@MXene has vigorous PDT effect and is capable of oxidizing GSH, the endogenous bacterial antioxidant, to boost oxidative stress. ## 4. Conclusions In this work, we have successfully integrated Ru into MXene through covalent bonding to achieve light-modulated high PTT/PDT antibacterial performance against Gram-positive (S. aureus) and Gram-negative bacteria (E. coli). On the basis of various antimicrobial testing methods, the composite material Ru@MXene was observed to be extraordinarily effective in killing E. coli and S. aureus. The antibacterial mechanisms of Ru@MXene are attributed to four factors as follows: [1] Physical cutting of bacterial cell membranes by MXene nanosheets with their “knife-like edge”; [2] hyperthermia produced by photothermal effect of MXene; [3] ROS production (including 1O2) by Ru after exposure to xenon lamp illumination (150 mW/cm2, 30 min); and [4] the germicidal effect by adhering to bacteria with negative potential. Since MXene is covalently combined with Ru(bpy)2(dcb)2+ through hydroxyl groups, Ru@MXene obtains more positive charge due to charge neutralization, resulting in photoactivated sterilization. Heretofore, light-responsive antibacterial properties of MXene covalently bonded with ruthenium complexes coupling PTT and PDT properties has barely been reported. Overall, the Ru@MXene complex with light-controlled synergistic PTT/PDT antibacterial outcome provides a new forward-looking strategy to design light stimuli-responsive multifunction platforms to combat over-resistant bacterial. While the biocompatibility and toxicity of Ru@MXene were not deeply investigated in this study, based on previous studies of similar materials and analysis of the material’s chemical structure, it is expected that this nanocomposite material may have good biocompatibility and low toxicity to the environment. 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--- title: Dynamics of the Lipidome in a Colon Simulator authors: - Matilda Kråkström - Alex M. Dickens - Marina Amaral Alves - Sofia D. Forssten - Arthur C. Ouwehand - Tuulia Hyötyläinen - Matej Orešič - Santosh Lamichhane journal: Metabolites year: 2023 pmcid: PMC10051596 doi: 10.3390/metabo13030355 license: CC BY 4.0 --- # Dynamics of the Lipidome in a Colon Simulator ## Abstract Current evidence suggests that gut microbiome-derived lipids play a crucial role in the regulation of host lipid metabolism. However, not much is known about the dynamics of gut microbial lipids within the distinct gut biogeographic. Here we applied targeted and untargeted lipidomics to in vitro-derived feces. Simulated intestinal chyme was collected from in vitro gut vessels (V1–V4), representing proximal to distal parts of the colon after 24 and 48 h with/without polydextrose treatment. In total, 44 simulated chyme samples were collected from the in vitro colon simulator. Factor analysis showed that vessel and time had the strongest impact on the simulated intestinal chyme lipid profiles. We found that levels of phosphatidylcholines, sphingomyelins, triacylglycerols, and endocannabinoids were altered in at least one vessel (V1–V4) during simulation. We also found that concentrations of triacylglycerols, diacylglycerols, and endocannabinoids changed with time (24 vs. 48 h of simulation). Together, we found that the simulated intestinal chyme revealed a wide range of lipids that remained altered in different compartments of the human colon model over time. ## 1. Introduction The human gut harbors trillions of microbes that exhibit a mutually beneficial relationship with the host [1]. A key contribution of the gut microbiota to the host is nutrient and xenobiotic metabolism, which plays a major role in training the immune system and promoting intestinal homeostasis [2,3]. Moreover, gut microbes are essential for the maintenance of the host’s metabolic homeostasis. Specific disturbances in the gut microbiome composition may contribute to a wide range of diseases, including inflammatory bowel disease [4], nonalcoholic liver disease [5], and psychiatric disorders [6]. Identifying the compositional changes in the gut microbiome alone, however, does not necessarily lead to a mechanistic understanding [1]. During the last decade, metabolomics has emerged as a powerful approach in the microbiome field, providing functional information about the human gut microbial phenotype [7]. Therefore, a combined microbiome and metabolome strategy to evaluate host–microbiome interactions are being increasingly utilized. To date, the focus of most metabolomics studies aimed at elucidating the role of the gut microbiome–metabolome co-axis has primarily been on water-soluble polar metabolites (e.g., tryptophan catabolites such as indole acetic acid and short-chain fatty acids (SCFA)). Other, nonpolar microbial metabolites, including lipids such as sphingolipids (SLs), endocannabinoids (ECs), cholesterol, bile acids, and acylcarnitines are less studied in comparison. However, lipids also have an important role in the gut microbiome–host interactions [8]. Gut microbiota not only regulate intestinal lipid absorption and metabolism but also impact levels and metabolism of a substantial proportion of circulating lipids [9,10]. Lipids are critical biomolecules involved in a wide range of cellular functions including structure, communication, and metabolism. The lipidomic analysis of feces can identify numerous microbial lipids, which can inform about the gut microbial phenotype [11]. However, only a limited number of studies have integrated the lipidome in microbiome analyses with respect to health outcomes. In addition, the dynamics of microbial lipids in the gut are poorly understood. This could be ascribed to the fact that it is not feasible to perform dynamic sampling across the human gastrointestinal tract. To overcome this challenge, in vitro colon models have been extensively applied to study microbial functions [12]. Here we employed a lipidomics approach on in vitro-derived intestinal chyme to examine the temporal lipid changes occurring in different compartments of the colon simulator representing the proximal to the distal part of the colon. We also studied whether in vitro gut lipidome profiles were affected by colon simulation time and polydextrose (PDX), a synthetic complex oligosaccharide. ## 2.1. In Vitro Colon Simulator The Enteromix model of the human large intestine (Figure 1) was described in detail previously [13,14]. In summary, each simulator unit consists of four connected glass vessels that are fed semi-continuously every third hour. The four vessels in the simulator (V1–V4) model different compartments of the human colon from the proximal (V1) to the distal part (V4), each having a different controlled pH and flow rate. The simulator is maintained anaerobically and at 37 °C. In the initial phase, the simulator is inoculated with preincubated fecal microbes from a fresh fecal sample, which forms the microbiota of the entire model. The microbes are incubated in an artificial ileal medium [15] that is composed based on the analysis of the ileal content from sudden death victims [16]. The same medium is used to feed the simulator during its running, and functions as a carrier for the polydextrose. In the present study, the fecal samples for inoculation were provided voluntarily by three healthy Finnish volunteers. One fecal sample from one volunteer was used to inoculate the entire simulator. Independent simulations were created by inoculating the simulator with a fecal sample from another volunteer. The study and all methods used in it were carried out in accordance with relevant guidelines and regulations, and informed consent was orally obtained from all research subjects. This simulation was performed at IFF, Kantvik, Finland. To understand the lipidomics changes over time, the microbial slurry was collected from all vessels (V1–V4) after 24 and 48 h with/without PDX treatment. Although gastrointestinal passage may be as short as 24 h, there is often a longer residence time in the intestine. Furthermore, due to the nature of the simulator being fed only every third hour, it takes time for the content to reach an equilibrium in the vessels, similar to the human colon. A total of 44 samples were gathered from vessels (V1–V4) of the in vitro colon simulator, and were kept at −80 °C until lipidomics analysis. These samples were obtained from 11 simulations, each involving four vessels. Among these simulations, eight were conducted for 48 h, while three were conducted for 24 h. In addition, media and inoculum were also used for the simulation and the pooled human fecal sample was collected as a quality control sample. ## 2.2. Lipidomics Analysis Simulated intestinal chyme lipid extracts were prepared using a method based on the Folch procedure [17], as detailed by Lamichhane et al. [ 18]. An internal standard mixture containing 2.5 µg/mL 1,2-diheptadecanoyl-sn-glycero-3-phosphoethanolamine (PE(17:$\frac{0}{17}$:0)), N-heptadecanoyl-D-erythro-sphingosylphosphorylcholine (SM(d18:$\frac{1}{17}$:0)), N-heptadecanoyl-D-erythro-sphingosine (Cer(d18:$\frac{1}{17}$:0)), 1,2-diheptadecanoyl-sn-glycero-3-phosphocholine (PC(17:$\frac{0}{17}$:0)), 1-heptadecanoyl-2-hydroxy-sn-glycero-3-phosphocholine (LPC(17:0)), 1-palmitoyl-d31-2-oleoyl-sn-glycero-3-phosphocholine (PC(16:0/d$\frac{31}{18}$:1)) and 1,2,3-triheptadecanoyl-sn-glycerol (TG(17:$\frac{0}{17}$:$\frac{0}{17}$:0)) was prepared in CHCl3:MeOH (2:1, v/v). Six-point calibration curves with concentrations between 100 and 2500 ppb in CHCl3:MeOH (2:1, v/v) were prepared for 1-Hexadecanoyl-2-octadecanoyl-sn-glycero-3-oethanolamine (PE(16:$\frac{0}{18}$:1)), octadecenoyl-sn-glycero-3-phosphocholine (LPC(18:1)), cholesteryl hexadecanoate (CE(16:0)), 1,2-Distearoyl-sn-glycero-3-phosphoethanolamine (PE(18:$\frac{0}{18}$:0)), N-stearoyl-D-erythro-sphingosylphosphorylcholine (SM(18:$\frac{0}{18}$:1)) and cholesteryl linoleic acid (CE(18:2)). The samples were prepared by spiking 10 µL of the sample with 10 µL of $0.9\%$ NaCl and 120 µL of internal standard solution. The samples were vortexed and were left to stand on ice for 30 min. Samples were centrifuged (9400× g, 5 min, 4 °C) and 60 µL from the lower layer was diluted with 60 µL of CHCl3:MeOH (2:1, v/v). For the liquid chromatography (LC) separation, a Bruker Elute UHPLC system (Bruker Daltonik, Bremen, Germany) equipped with an autosampler cooled to 10 °C, a column compartment heated to 50 °C and a binary pump was used. A Waters ACQUITY BEH C18 column (2.1 mm × 100 mm, 1.7 µm) was used for chromatographic separation. The flow rate was 0.4 mL/min and the injection volume was 1 µL. The needle was washed with $10\%$ DCM in MeOH and ACN: MeOH: IPA: H2O (1:1:1:1, v/v/v/v) + $0.1\%$ HCOOH after each injection for 7.5 s each. The eluents were H2O + $1\%$ NH4Ac (1M) + $0.1\%$ HCOOH (A) and ACN: IPA (1:1, v/v) + $1\%$ NH4Ac + $0.1\%$ HCOOH (B). The gradient was as follows: from 0 to 2 min, 35–$80\%$ B, from 2 to 7 min, 80–$100\%$ B, and from 7 to 14 min, $100\%$ B. Each run was followed by a 7 min re-equilibration period under initial conditions ($35\%$ B). Mass spectrometric detection was performed on a Bruker Impact II QTOF (Bruker Daltonik, Bremen, Germany). For data preprocessing, the raw data files were converted to a.mzml file using Bruker compass data analysis 5.1. The preprocessing was performed in MZmine2 (version 2.53) according to Thomas et al. [ 19]. Briefly, centroid mass detection was performed, followed by ADAP chromatogram builder, chromatogram deconvolution (local minimum search), and isotopic peaks grouper with join aligner. After this, a filtering step (feature list row filter), a custom database search, an adduct search, and gap filling (peak finder) were performed. Finally, the results were exported as a CSV file. After this, lipid class-based normalization was performed using the class-based internal standards; class-based calibration curves were created, and semi-quantification was performed using the calibration curves. Features that were annotated and had a relative standard deviation of less than $30\%$ in the quality control samples were selected for further processing. ## 2.3. Endocannabinoid Analysis The concentrations of endocannabinoids and endocannabinoid-like compounds were analyzed. Crash solvent (400 µL) consisting of acetonitrile (ACN), $0.1\%$ formic acid (FA), and isotopically labeled internal standards (Supplementary Materials Table S1) was added to a glass vial and 200 µL of chyme slurry was added. The samples were vortexed and left to settle at −20 °C for 30 min. The samples were filtered through protein precipitation filter plates and collected into 96-well plates with glass inserts. The samples were transferred to glass vials and dried at 35 °C under a gentle stream of nitrogen. The samples were reconstituted in 50 µL reconstitution solution ($60\%$ water, $20\%$ ACN, and $20\%$ isopropanol). The samples were analyzed using LC–MS. The chromatographic separation was performed on a Sciex exion (AB Sciex Inc., Framingham, MA, USA) consisting of a binary pump, an autosampler, and a thermostatic column compartment. The column used was an XBridge BEH C18 2.5 µm, 2.1 × 150 mm column with a precolumn made of the same material. The eluents were A: $0.1\%$ FA and $1\%$ ammonium acetate (1M) in water, and B: $0.1\%$ FA and $1\%$ ammonium acetate (1M) in ACN/IPA (50:50). The gradient is presented in Supplementary Materials Table S2. The injection volume was 1 µL, the flow rate was 0.4 mL/min, and the column oven temperature was 40 °C. The detection was performed on a Sciex 7500 QTrap operating in MRM mode. The parameters used are presented in Supplementary Materials Table S1 and S3. Quantification was performed using calibration curves from 0.01 ppb to 80 ppb (0.1 and 800 ppb for arachidonic acid (AA)) using the internal standard method. Quantification was performed with Sciex OS analytics. Due to the rapid isomerization of 2-AG to 1-AG, the results are presented as the concentration of total AG. ## 2.4. Data Analysis Lipid data values were log-transformed prior to multivariate analysis. The difference in the lipidome between the different vessels, time, and case (with/without PDX treatment) were analyzed using a multivariate linear model using the MaAsLin2 package in R (lipids ∼ Time + Vessel + case). Adjusted p-values of 0.25 were considered significant. Spearman correlation coefficients were calculated using the Statistical Toolbox in MATLAB 2017b and p-values < 0.05 (two-tailed) were considered significant for the correlations. The individual Spearman correlation coefficients (R) were illustrated as a heat map using the ‘‘corrplot’’ package (version 0.84) for the R statistical programming language. ## 3.1. Untargeted Lipidomics and Targeted Endocannabinoid Analysis in the Simulated Fecal Samples We analyzed simulated intestinal chyme lipids obtained from different vessels (V1–V4) in the in vitro colon, which mimics the compartments of the human colon from the proximal to the distal part (Figure 1). In total, 44 simulated intestinal chyme samples were collected from the in vitro colon simulator (vessels V1–V4) and ran for either 24 or 48 h with/without PDX treatment. The untargeted lipidomics assay of the simulated chyme extract resulted in the detection of 118 annotated lipids. These lipids were semi-quantified using class-specific internal standards and calibration curves. The semi-quantified lipids included a wide range of lipid classes: triacylglycerols (TG), ceramides (Cer), cholesterol esters (CE), diacylglycerols (DG), lysophosphatidylcholines (LPC), phosphatidylcholines (PC), phosphatidylethanolamines (PE), and sphingomyelins (SM). Of the 13 endocannabinoids (EC) studied, 11 were detected in at least one sample type. These included palmitoylethanolamide (PEA), arachidonoyl glycerol (AG), 2-arachidonic glycerol ether (2-Age), arachidonoylethanolamide (AEA), oleoylethanolamide (OEA), stearoylethanolamide (SEA), docosatetraenoylethanolamide (DEA), alpha-linolenoylethanolamide (aLEA), arachidonic acid (AA), N-arachidonoyl taurine (NAT) and N-arachidonoyl-L-serine (NALS). Nine (PEA, AG, 2-AGe, AEA, OEA, SEA, DEA, aLEA, and AA) were detected in human feces, which were used as quality control samples. ## 3.2. Lipidome in the In Vitro Colon Simulator Principal component analysis (PCA) of the preprocessed lipidomics data revealed a clear vessel-related pattern in the simulated intestinal chyme samples. To examine the contributions of various factors to simulated chyme lipidome profiles, multivariate linear modeling was performed (lipids ∼ Time + Vessel + treatment). We found that the vessel had a marked impact on the simulated chyme lipidome when compared to the simulation time (24 vs. 48 h) and treatment (with/without PDX treatment). Of the analyzed lipids, 40 showed a significant change in at least one of the vessels ($p \leq 0.05$, Figure 2A and Supplementary Materials Table S4). These lipids included one CE, two DGs, five Cer, eleven PCs, one PG, four PEs, four SMs, and nine TGs (Figure 2A–C). All of these lipids passed the FDR threshold of 0.25 (Supplementary Materials Table S1). With the exception of Cer(d18:$\frac{1}{20}$:0), LPE (16:0), and LysoPE(18:1), most of the lipids showed a decreased pattern from vessel V1 to V4, i.e., from the proximal to the distal part of the colon simulator (Figure 2B–D). Among the TGs, specifically, those TGs with a low double bond count (≤2 double bonds) showed changes within the vessels (V1–V4, Supplementary Materials Table S4). However, no clear pattern with respect to the double bond counts and/or carbon number compositions was observed in any other specific lipid class. We also found that chyme lipidome concentrations of 26 lipids, mainly TGs ($$n = 14$$), were different across two time points (24 vs. 48 h of simulation, Supplementary Materials Table S5), while only four lipids (DG(34:2), LacCer(d18:$\frac{1}{18}$:0), TG (55:6)/TG (16:$\frac{0}{19}$:$\frac{1}{20}$:5), and TG (51:1)) were found altered when the simulation was performed with/without PDX. Next, we analyzed the dynamics of ECs in the different compartments of the colon simulator over time. Among the 11 detected ECs, the levels of 7 ECs were altered in at least one of the vessels in the colon simulator ($p \leq 0.05$, Figure 3A and Supplementary Materials Table S6). These ECs include AEA, aLEA, DEA, OEA, PEA, and SEA. There was no persistent trend; however, the levels of OEA, aLEA, and PEA increased in vessels (V3–V4) when compared to vessel V1 (Figure 3B). A similar trend was seen for AEA with a higher level of variation appearing in vessel V3 (Figure 3C). On the other hand, the level of SEA was higher in V1 when compared to vessels V2-V4 (Figure 3 and Supplementary Materials Figure S1). In addition, we analyzed the EC concentrations over time in the simulated gut. Overall, the levels of five ECs (AEA, 2-AGe, AA, PEA, and NAT) were increased in the colon simulation when ran for 48 h compared to 24 h for the intestinal chyme slurry (Supplementary Materials Figure S2). Given the known link between gut microbiota and EC metabolism [20], we also examined the difference in ECs profiles between the media used for in vitro gut simulation and the simulated chyme slurry. We found most of the ECs detected in the simulated chyme slurry were lower in concentration than in the simulation media. Interestingly, we observed NALS was detected at low concentrations in the media; however, it was not detected in any of the vessels (Figure 4A). Meanwhile, 2-AGe was not detected in the media but it appeared in different vessels (Figure 4B, V1–V3). ## 3.3. Association of Lipidome and ECs in the In Vitro Colon Simulator Next, we performed a correlation analysis between ECs and individual simulated intestinal chyme lipid levels (Figure 5). We found that the levels of SEA and DEA were positively associated with the overall simulated chyme lipidome. OEA, aLEA, and PEA showed a positive association with Cers and LPEs, while those being inversely correlated were PCs, PEs, SMs, and TGs. This trend was less pronounced for AA and AG. Instead, there was a clear inverse trend association between SMs and PEs/AA levels in the in vitro simulator. In addition, DGs were negatively related to the level of AA and AG. No association between individual lipids and NAT was observed, except for Cer(d18:$\frac{1}{20}$:0). ## 4. Discussion In this study, we reported the dynamics of lipids in each compartment of the colon simulator. We found a more distinct lipids profile in the proximal colon (vessel V1) than in the distal part of the colon (vessel V4). Specifically, specific Cer, PCs, SMs, and TGs were decreased in the distal as compared to the proximal part of the colon simulator. Our observations also showed that in vitro-derived intestinal chyme lipids, particularly TGs, are strongly affected by time. Our results are in agreement with previous studies, showing that profound metabolic changes occur in different parts of the in vitro gut over time [12]. The level of SCFAs (acetate, butyrate, and propionate), branched-chain fatty acids (iso-valerate), biogenic amines (trimethylamine), organic metabolites (succinate, ethanol, formate, valerate, and n-acetyl compounds) and amino acids (lysine, leucine, isoleucine, phenylalanine, tyrosine, and valine) were reported to change in the four vessels (V1–V4) within 48 h (12, 24, 36, and 48 h) [12,14]. Similar dynamic changes in the metabolome along the intestinal tract have been reported in nonhuman primates [21]. The human gut is an endogenous source of systemic sphingolipids [22]. We observed distinct changes in the levels of the sphingolipids (Cer and SMs) while passing from vessel V1 to V4 over time (24 and 48 h). Sphingolipids were higher in the proximal colon (V1) than in the distal part of the colon (V4). Sphingolipids have many structural and signaling roles in eukaryotes [22], and microbially-derived sphingolipids may markedly impact the host sphingolipid levels [23,24]. In addition, sphingolipids have been shown to promote the survival of commensal bacteria [25]. Notably, the observed decreasing trend in our study may indicate increased microbial catabolism. Lipid is considered an alternative pathway for carbon, nitrogen, and an energy source for the gut microbes [26]. We acknowledge the lack of microbiome data as the main limitation of our study; therefore, we could not demonstrate a causal link between gut microbiota and sphingolipid metabolism. Notwithstanding this, our study introduced a simulated intestinal chyme lipidomics-based method to interrogate potential microbial lipids within the complex gut system. Our study also highlights that an in vitro colon model provides a controlled experimental condition, i.e., dynamic sampling for the characterization of gut microbiota-derived bioactive lipids. Thus, it provides a potentially significant strategy for understanding the intricate relationship between gut microbes and lipids, which may open new avenues to studying human metabolism. Growing evidence suggests that bidirectional interactions exist between gut microbes and the endocannabinoid system [27,28,29,30]. The endocannabinoid system comprises a network of cannabinoid-type receptors and their ligands (i.e., the endocannabinoids) that are present throughout the human body. The concept of the endocannabinoid system and the gastrointestinal tract is over a half-century old. Studies from the 1970s have already shown that ECs can have a profound impact on gut motility [20,31,32]. Current evidence suggests that gut transit times affect gut microbial composition and function [33]. Here, we found that the concentration of ECs varied between the proximal (V1) and distal colon (V4). We also found an endocannabinoid of potential microbial origin (i.e., 2-AGe). 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(2003) 83 1017-1066. DOI: 10.1152/physrev.00004.2003
--- title: Mitochondrial Methionyl-tRNA Formyltransferase Deficiency Alleviates Metaflammation by Modulating Mitochondrial Activity in Mice authors: - Xiaoxiao Sun - Suyuan Liu - Jiangxue Cai - Miaoxin Yang - Chenxuan Li - Meiling Tan - Bin He journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051599 doi: 10.3390/ijms24065999 license: CC BY 4.0 --- # Mitochondrial Methionyl-tRNA Formyltransferase Deficiency Alleviates Metaflammation by Modulating Mitochondrial Activity in Mice ## Abstract Various studies have revealed the association of metabolic diseases with inflammation. Mitochondria are key organelles involved in metabolic regulation and important drivers of inflammation. However, it is uncertain whether the inhibition of mitochondrial protein translation results in the development of metabolic diseases, such that the metabolic benefits related to the inhibition of mitochondrial activity remain unclear. Mitochondrial methionyl-tRNA formyltransferase (Mtfmt) functions in the early stages of mitochondrial translation. In this study, we reveal that feeding with a high-fat diet led to the upregulation of Mtfmt in the livers of mice and that a negative correlation existed between hepatic Mtfmt gene expression and fasting blood glucose levels. A knockout mouse model of Mtfmt was generated to explore its possible role in metabolic diseases and its underlying molecular mechanisms. Homozygous knockout mice experienced embryonic lethality, but heterozygous knockout mice showed a global reduction in Mtfmt expression and activity. Moreover, heterozygous mice showed increased glucose tolerance and reduced inflammation, which effects were induced by the high-fat diet. The cellular assays showed that Mtfmt deficiency reduced mitochondrial activity and the production of mitochondrial reactive oxygen species and blunted nuclear factor-κB activation, which, in turn, downregulated inflammation in macrophages. The results of this study indicate that targeting Mtfmt-mediated mitochondrial protein translation to regulate inflammation might provide a potential therapeutic strategy for metabolic diseases. ## 1. Introduction Type 2 diabetes (T2D) is becoming an increasingly prevalent medical and economic burden worldwide [1,2]. Many studies have revealed the association of metabolic diseases with inflammation, and at present metabolic diseases caused by chronic low-grade inflammation are defined as metaflammation [3,4,5,6]. Metaflammation is an inflammatory complication of metabolic disorders characterized by altered levels of inflammatory cytokines, adipokines, and lipid mediators [7]. Metaflammation, caused by immune cells, such as macrophages living in or infiltrating metabolic organs under obesity, impairs insulin action and results in insulin resistance [8]. In recent studies, obesity has been associated with increased secretion of monocyte chemoattractant protein-1 from adipocytes, which results in a higher number of infiltrating adipose tissue macrophages. The chemokines and cytokines secreted by infiltrating macrophages enhance local inflammatory responses and affect gene expression in adipocytes, resulting in insulin resistance systemically [9]. In addition, diet-induced hepatic steatosis and insulin resistance are prevented by the depletion of Kupffer cells (liver-specific macrophages) [10]. Mitochondria are key organelles involved in metabolic regulation, and their dysfunction is closely associated with metabolic diseases [11,12]. In obesity and insulin resistance, inhibition of mitochondrial electron transport chain (ETC) activity has been shown to have metabolic benefits [13,14]. The ETC uses a series of electron transfer reactions to generate cellular adenosine triphosphate via oxidative phosphorylation (OxPhos). Mitochondrial reactive oxygen species (mROS) are generated because of electron transfer [15]. Moderate levels of mROS are necessary for cell signaling and organismal health, but high levels of mROS result in damage to the body [16,17]. Thioredoxin 2 (Trx2) deletion in adipose tissue leads to an increase in mROS, which then contributes to increased secretion of systemic inflammatory factors via the activation of nuclear factor-κB (NFκB), resulting in the disruption of systemic glucose and lipid metabolism [18]. On the contrary, reducing mROS output alleviates high-fat-diet-induced cirrhosis and insulin resistance [19]. Metformin, a widely used drug for treating T2D, has been shown to delay diabetes and vascular dysfunction in rats by slowing mROS production [20]. In mammalian mitochondria, 13 proteins are synthesized that are essential subunits of oxidative phosphorylation [21]. It has been well established that the impaired translation of mitochondrial proteins leads to mitochondrial disorders and consequently affects organismal health [22]. Mitochondrial protein translation is similar to bacterial protein translation in that it involves the initiation, elongation, and termination of translation. However, the initiation of mammalian mitochondrial protein translation is different in that bacteria encode two different tRNAMets involved in initiation and elongation, whereas mammalian mitochondria encode only one tRNAMet that performs both functions. During mitochondrial protein translation, methionyl-tRNA formyltransferase (Mtfmt) formylates a part of Met-tRNAMet after it has been aminoacylated to initiate mitochondrial protein translation [23]. Studies have shown that Mtfmt double heterozygous mutation could lead to a series of visual, neurological, and muscular impairments and multiple mitochondrial respiratory chain deficiencies [24,25,26]. However, the involvement of Mtfmt-mediated mitochondrial protein translation in the development of metabolic diseases remains unclear. The purpose of the present study was to determine whether Mtfmt plays an important role in metabolic inflammation, as well as to explore the mechanisms underpinning its development. The heterozygous knockout mice displayed decreased Mtfmt protein expression as well as high-fat-diet (HFD)-induced inflammation, despite the homozygous knockout mice exhibiting embryonic lethality. The cellular assays revealed that the Mtfmt knockdown of macrophages in vitro reduced mROS production and NFκB activation, which in turn affected inflammation. These data demonstrated that targeting Mtfmt-mediated mitochondrial protein translation to regulate levels of mROS might be an innovative therapeutic option for treating metabolic diseases. ## 2.1. Expression Levels of Mtfmt Were Correlated with Diet and Glucose Levels We compared Mtfmt expression in the livers of mice fed an LFD with the expression levels of mice fed an HFD to investigate the correlation between Mtfmt and metabolic states. The abundances of Mtfmt mRNA and proteins were significantly higher in high-fat-diet (HFD, $60\%$ fat)-fed compared with low-fat-diet (LFD, $10\%$ fat)-fed mice (Figure 1A–C). Further, the expression of Mtfmt in the liver was negatively correlated with fasting glucose levels (Figure 1D). ## 2.2. Mtfmt Deletion Caused Embryonic Lethality in Mice The Mtfmt knockout mouse model was constructed to investigate a specific and causal role of Mtfmt deficiency in the development of metabolic states (Figure 2A). The genotyping results from the Het × Het breeding indicated that, out of 147 surviving mice, 94 ($63.95\%$) were Het KO mice and 53 ($36.05\%$) were wild-type (WT) mice (Figure 2B). Embryos from 9.5 to 13.5 dpc were collected for genotyping to further validate this observation. A total of 90 embryos were collected, of which 26 died prematurely, and all of them were Homo KO mice (i.e., $28.9\%$ of all embryos died prematurely). Further, out of the 64 surviving embryos, 20 ($22.2\%$) and 44 ($48.9\%$) embryos were WT and Het KO types, respectively (Figure 2C). A significant developmental delay was observed in the Homo KO embryos at 13.5 dpc compared with the WT and Het KO embryos (Figure 2D,E). However, no significant difference was observed between the Het KO and WT embryos (Figure 2D,E). Western blot results showed that the Mtfmt protein was barely detectable in Homo KO embryos (as some of the embryos might have had maternal tissue contamination) (Figure 2F). Since Mtfmt is involved in the initiation of mitochondrial protein translation, we hypothesized that the knockdown of Mtfmt would affect mitochondrial protein translation and thus mitochondrial morphology and function. The abundance of the COX1 protein, which is encoded by mitochondrial DNA (mtDNA), was significantly lower in Homo KO embryos at 13.5 dpc than at 12.5 dpc (Figure 2G). Transmission electron microscopy results showed mitochondrial swelling, shortened ridges, and ruptured mitochondrial membranes in Homo KO embryos, while slightly swollen mitochondria were observed in the Het KO embryos compared with the WT embryos (Figure 2H). Hence, these results indicated that the complete Mtfmt knockout resulted in embryonic lethality. Moreover, the knockout affected mitochondrial protein translation and thus mitochondrial morphology, whereas Het KO mice appeared to be normal in the basal condition. ## 2.3. Mtfmt Haploinsufficiency Improved Hepatic Metabolic Health The abundances of the Mtfmt protein in liver mitochondria were detected, and the results showed a slight downregulation of the Mtfmt protein in the liver of the Het KO mice compared with the WT mice (Figure 3A). In addition, the abundances of the ND6 and COX1 proteins, which are encoded by mtDNA, were significantly lower in the Het KO mice compared with the WT mice (Figure 3A). Interestingly, the abundances of succinate dehydrogenase complex subunit A (SDHA) and voltage-dependent anion channels (VDACs), which are encoded by nuclear DNA and transported to mitochondria, were higher in the Het KO mice compared with the WT mice (Figure 3A). As the expression of Mtfmt in the liver is negatively correlated with fasting glucose levels, the glucose tolerance test (GTT) and insulin tolerance test (ITT) were performed on WT and Het KO male mice at 23 weeks of age. The GTT results showed a slight but significant increase in glucose clearance in the Het KO mice compared with the WT mice (Figure 3B,C). No difference was observed in the ITT results (Figure 3D,E). Triglyceride contents in the serum (Figure 3F) and liver (Figure 3G) were significantly lower in the Het KO mice compared with the WT mice. Hematoxylin-eosin (H&E) staining of the liver showed reduced liver lipid deposition in Het KO mice (Figure 3H). The levels of alanine transaminase, but not aspartate transaminase, were significantly lower in Het KO mice (Figure 3I,J). Previous studies showed that interleukin (IL)-1β in human blood is positively correlated with insulin resistance [27]. In this study, the IL-1β levels were significantly lower in the serum of the Het KO mice compared with the WT mice (Figure 3K). Thus, these findings suggest that Mtfmt haploinsufficiency might improve hepatic metabolic health in mice. ## 2.4. Mtfmt Haploinsufficiency Alleviated HFD-Induced Metabolic Disorders Four-week-old WT and Het male mice were randomly divided into four groups to test whether Mtfmt haploinsufficiency could alleviate metabolic disorders: WT and Het male mice were fed a high-fat diet (HFD, $60\%$ fat; WT HFD and Het HFD, respectively) or a low-fat diet (LFD, $10\%$ fat; WT LFD and Het LFD, respectively). After feeding of the HFD for 17 weeks, the body weights of the WT HFD mice were significantly higher than those of the WT LFD mice (Figure 4A). No significant differences were observed between the body weights of the Het HFD mice and those of the WT HFD mice (Figure 4A). WT HFD mice exhibited increased blood glucose levels after chronic HFD during GTT (Figure 4B,C). On the contrary, the glucose levels were lower in the Het HFD mice compared with the WT HFD mice (Figure 4B,C). Moreover, the ITT results showed that glucose levels were significantly higher in the HFD group compared with the LFD group, while a significant increase in insulin sensitivity was observed in the Het HFD mice compared with the WT HFD mice (Figure 4D,E). The weights of epididymal fat (Figure 4F) and subcutaneous fat (Figure 4G) were significantly lower in the Het HFD mice compared with the WT HFD mice. H&E staining revealed that the Het HFD mice had significantly lower fat levels than the WT HFD mice (Figure 4H). Triglyceride contents were significantly lower in the livers of the Het HFD mice compared with the WT HFD mice (Figure 4I). Oxidative stress levels in the liver were assessed. Malondialdehyde levels were significantly lower in the Het HFD mice compared with the WT HFD mice (Figure 4J), but superoxide dismutase activity was not affected (Figure 4K). Hence, the data indicated that Mtfmt haploinsufficiency might protect against HFD-induced metabolic disorders. ## 2.5. Mtfmt Haploinsufficiency Alleviated HFD-Induced Inflammation We next detected the expression of pro-inflammatory factors IL-1β, IL-6, and tumor necrosis factor-α (TNFα) in the liver and epididymal fat. IL-1β, IL-6, and TNFα mRNAs were upregulated in the livers (Figure 5A–C) and epididymal fat (Figure 5D–F) of the WT HFD mice compared with the WT LFD mice. However, IL-1β and IL-6 expression were significantly downregulated in the livers (Figure 5A,B) and epididymal fat (Figure 5D,E) of the Het HFD mice compared with the WT HFD mice. Moreover, the IL-1β levels in the serum of mice further indicated that Mtfmt haploinsufficiency alleviated HFD-induced inflammation (Figure 5G). ## 2.6. Mtfmt Knockdown in Macrophages Decreased Mitochondrial Activity and mROS Signaling and Blunted NFκB Signaling We used Kupffer cells, the macrophages that reside in the liver and are involved in the immune regulation of the liver, to investigate whether the in vitro knockdown of Mtfmt in macrophages could alleviate the onset of inflammation to gain insight into the attenuated metaflammatory phenotype. After the transfection of Kupffer cells with siMtfmt for 24 h (Supplementary Figure S1A), quantitative polymerase chain reaction (qPCR) (Figure 6A) and Western blotting (Figure 6B,C) were used to verify knockdown efficiency. The abundances of the mtDNA-encoded proteins ND6 and COX1 were down-regulated by siMtfmt transfection (Figure 6C–E), but the mRNAs were unaltered (Figure 6F). This supported our hypothesis that Mtfmt knockdown blocks mitochondrial translation. The mitochondrial membrane potential and mROS levels were examined after Mtfmt knockdown. The results showed that the Mtfmt knockdown in Kupffer cells decreased the mitochondrial membrane potential (Figure 6G,H). Changes in OxPhos should be reflected in modifications in mROS generation, so we detected mROS contents. As expected, the production of mROS decreased under basal conditions after Mtfmt knockdown (Figure 6I and Supplementary Figure S1B). After 24 h of siMtfmt transfection, 100 ng/mL lipopolysaccharide (LPS) was used to treat Kupffer cells to further explore whether Mtfmt knockdown in Kupffer cells affected inflammation. The qPCR results showed that, compared with NC + LPS, Mtfmt knockdown after 6 h of treatment with LPS significantly decreased IL-1β and TNFα mRNA levels (Figure 6J,K). Meanwhile, Mtfmt knockdown also reduced the levels of TNFα in cell supernatants (Figure 6L). Furthermore, IL-1β precursor and p-IκBα protein levels in the Mtfmt knockdown cell treatment with LPS showed significant downregulation compared with NC + LPS (Figure 6M–O). A RelA/p65 nuclear translocation assay was performed to examine the alleviated inflammatory phenotype after Mtfmt knockdown and showed a significant reduction in RelA/p65 nuclear translocation after Mtfmt knockdown and treatment of Kupffer cells with LPS for 30 min (Figure 6P and Supplementary Figure S1C). Hence, these results suggested that Mtfmt deficiency in macrophages reduced mitochondrial activity and mROS production, which decreased NFκB activation and, in turn, affected inflammation. ## 3. Discussion In this study, we have shown correlations between hepatic Mtfmt and metabolic states. We generated a novel strain of global Mtfmt knockout mice to explore the potential role of Mtfmt in metabolic diseases. Mtfmt knockout resulted in embryonic lethality, consistent with previous findings that interference with mitochondrial biogenesis led to embryonic death in animals [28,29,30,31,32,33,34]. However, heterozygous mice, which displayed mild mitochondrial dysfunction, exhibited increased glucose tolerance and reduced inflammation induced by HFD. To maintain normal metabolism and health, mitochondrial function is essential [35,36]. There is a wide range of metabolic consequences associated with genetic diseases related to mitochondrial dysfunction. Obesity and type 2 diabetes are associated with mitochondrial ETC dysregulation [37,38]. Decreased OxPhos gene expression in skeletal muscle is associated with insulin resistance in humans [39]. Additionally, a variety of studies have linked reduced mitochondrial oxidative metabolism to insulin resistance in humans [40,41]. The data for two different mouse models in this study showed that in heterozygous knockout Mtfmt mice, a slight OxPhos deficit brought on by the downregulation of mitochondrial translation could result in a state of reduced adiposity and improved insulin sensitivity. It was found that these effects exactly coincided with the metabolic changes observed in mice with OxPhos defects caused by apoptosis-inducing factor deficiency, increased glucose utilization, and decreased lipid storage, for example [13]. In addition, a previous study indicated that mice with deletion of muscle-specific mitochondrial transcription factor A (TFAM), which controls the transcription of all mitochondrial encoded genes, did not develop insulin resistance [42]. Meanwhile, Vernochet et al. reported that adipose tissue TFAM-specific knockout mice exhibited decreased levels of mtDNA-encoded proteins and were protected from diet-induced insulin resistance, which results were similar to our findings [43]. Moreover, recent studies have shown that alternate-day fasting or SDHAF4 knockout in the liver can drive systemic metabolic benefits by inhibiting the assembly of mitochondrial complex II [44]. Hence, these results suggested that the downregulation of both transcription and translation of mtDNA reduced adiposity and increased insulin sensitivity in mice. Several studies have shown that mitochondria are key participants in innate immune pathways and important drivers of inflammation. Mild, transient perturbations to the mitochondrial ETC reduce inflammation in mice [45]. The nuclear transcription factor NFκB regulates immunity by controlling the expression of related inflammatory genes. It has been demonstrated that NFκB plays an essential role in inflammatory responses associated with insulin resistance in genetic mutant mice [4]. In this study, we found that Mtfmt deletion decreased the NFκB activity and inflammatory response induced by LPS in macrophages. This was consistent with the findings of animal experiments that Het mice could resist metabolic inflammation induced by HFD. Seo et al. showed that, under basal conditions, NFκB activity was decreased in Mtfmt-silenced Hela cells with defective mitochondria, which may explain their reduced ability to defend against intracellular infection in the early stages of infection [46]. However, the effect of Mtfmt deletion on NFκB activity has never been experimentally proved. The elevation of mROS contributes to increased secretion of systemic inflammatory factors via the activation of NFκB [18,47]. In this study, we found that Mtfmt knockdown in macrophages decreased mitochondrial activity and the production of mROS. Thus, we suggested that Mtfmt knockdown in macrophages reduced mROS production and led to reduced activation of NFκB. Hence, Mtfmt knockdown in macrophages reduced mROS production and led to blunted NFκB activation, which further led to downregulation of the levels of relevant inflammatory factors and consequently improved the metabolic impairment in mice. In conclusion, Mtfmt deficiency alleviated HFD-induced metabolic disorders. The reduction in Mtfmt levels in macrophages reduced mitochondrial activity and mROS production, which decreased NFκB activation and, in turn, affected inflammation. These data demonstrated that targeting Mtfmt-mediated mitochondrial protein translation to regulate metaflammation might be an innovative therapeutic option for treating metabolic diseases. ## 4.1. Animals According to the structure of the Mtfmt gene, exon 2-exon 4 of the Mtfmt-201 (ENSMUST00000074792.6) transcript is recommended as the knockout region. The region contains 436 bp coding sequences. Knocking out the region will result in the disruption of protein function. A brief summary of the procedure is as follows: sgRNA was generated in vitro. Fertilized C57BL/6 mouse eggs were microinjected with Cas9 and sgRNA. The F0 mice were obtained by transplanting fertilized eggs, which were confirmed by PCR and sequencing. By mating positive F0 generation mice with C57BL/6 wild-type (WT) mice, a stable F1 generation mouse model was obtained. Tails from the pups and embryo samples were obtained after mating with C57BL/6 WT mice, and genotyping was carried out on a 96-well thermal cycler (Thermal Cycler PTC0200, Bio-Rad, Hercules, CA, USA), utilizing two distinct amplification reactions for each mouse using two primer sets. In these two pairs of primers, FI and RI are located outside the knockout fragment, and F2 and R2 are located inside the knockout fragment, so the genotype of the mouse or embryo can be determined according to the size of the amplified PCR product fragment. The forward and reverse sequences were as follows: F1, 5′-AAAGTTCGTCCCTTCCTGGTG-3′ and R1, 5′-TTACTTCAGAGGTGGTTGGCAG-3′ (primer 1); F2, 5′-ATCGAACTCCTTGGCTTTCCTAC-3′ and R2, 5′-CATAATGGACTGGACATGGGAC-3′ (primer 2). PCR amplification was performed under the following conditions: 95 °C for 5 min, followed by 20 cycles of 98 °C for 30 s, 65 °C (decreased 0.5 °C each cycle) for 30 s, and 72 °C for 45 s, then followed by 20 cycles of 98 °C for 30 s, 55 °C for 30 s, and 72 °C for 45 s, then 1 cycle at 72 °C for 5 min. To characterize embryonic lethality, embryos were harvested at 13.5 dpc and small pieces were genotyped. As described above, the PCR conditions were the same. Later experiments were conducted with Mtfmt heterozygous knockout (Het KO) male mice, since homozygous knockout mice exhibited embryonic lethality. The WT and Het KO male mice were normally housed in standard cages with free access to food and water under a 12 h dark–light cycle for 28 weeks. The 4-week-old littermates of the WT and Het KO male mice were randomly assigned to feed on either the low-fat diet (LFD, $10\%$ kcal fat; XTCON50J, Jiangsu Xietong Pharmaceutical Bio-engineering Co., Ltd., Nanjing, China) or the high-fat diet (HFD, $60\%$ kcal fat; XTHF60, Jiangsu Xietong Pharmaceutical Bio-engineering Co., Ltd., Nanjing, China) for 17 weeks. The Nanjing Agricultural University Institutional Animal Care and Use Committee (IACUC) approved all experimental protocols, and all procedures followed the “Guidelines on Ethical Treatment of Experimental Animals.” [ 2006] No. 398 set by the Ministry of Science and Technology, China, and the “Regulation regarding the Management and Treatment of Experimental Animals” [2008] No. 45 set by the Jiangsu Provincial People’s Government. ## 4.2. Real-Time Polymerase Chain Reaction (RT-PCR) TRIzol reagent (Invitrogen, Carlsbad, CA, USA) was used to isolate total RNA from Kupffer cells and tissues, which was then reverse-transcribed to cDNA using random hexamer primers (Promega, Madison, WI, USA). The real-time PCR was conducted with diluted cDNA (1:20, v/v) using the Mx3000P Real-time Polymerase Chain Reaction (PCR) System (Stratagene). The reference gene used was glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Tsingke (Nanjing, China) synthesized all primers. The primer sequences for qPCR are listed in Supplementary Table S1. ## 4.3. Western Blot Analysis The Western blot analysis was carried out as per standard protocols on $10\%$ SDS/PAGE gels and then transferred to nitrocellulose membranes. The membranes were blocked in TBST with $0.1\%$ Tween-20 and $5\%$ non-fat dry milk for 2 h and then incubated with primary antibodies against Mtfmt (1:1000, cat. no.: PAH614Mu01, Cloud-Clone Corp, Houston, TX USA), p-IkBα (1:1000, cat. no.: 2859S, Cell Signaling, Danvers, MA, USA), IkBα (1:1000, cat. no.: 9242, Cell Signaling, Danvers, MA, USA), IL-1β (1:1000, cat. no.: ab254360, abcam, Cambridge, UK), SDHA (1:1000, cat. no.: 14865-1-AP, proteintech, Rosemont, IL, USA), VDAC (1:1000, cat. no.: 10866-1-AP, proteintech, Rosemont, IL, USA), ND6 (1:1000, cat. no.: BS1632, Bioworld, Nanjing, China), COX1 (1:1000, cat. no.: BS70809, Bioworld, Nanjing, China), β-actin (1:20,000, cat. no.: AC026, Abclonal, Wuhan, China), and GAPDH (1:1000, cat. no.: MB001H, Bioworld, Nanjing, China). ## 4.4. Transmission Electron Microscopy Embryos (13.5-day-old) were isolated from pregnant females and fixed in $2.5\%$ glutaraldehyde. Embryos were dehydrated and embedded in Araldite. Ultrathin sections were cut and stained with uranyl acetate and osmium tetroxide. Sections were examined in a Hitachi SU8010 electron microscope operated at 80 kV. ## 4.5. Glucose Tolerance Test (GTT) Mice fasted for 12 h received an intraperitoneal glucose injection of 2 g/kg body weight during GTT. Before glucose injection (0 min) and 15, 30, 60, and 120 min afterward, blood samples were collected from the tail vein. A glucose meter (ACCU-CHEK Active Blood Glucose Meter, Roche) was used to measure blood glucose concentration immediately. ## 4.6. Insulin Tolerance Test (ITT) Insulin (0.75 IU/kg, Aladdin, CAS 12584-58-6) was administered intraperitoneally for ITT. Glucose concentrations were measured before insulin injection (0 min) and 15 min, 30 min, 60 min, and 90 min after insulin injection. A glucose meter was used to immediately measure the blood glucose concentrations in the mouse tail veins after blood samples were collected. ## 4.7. Histological Analysis For histomorphological evaluation, we fixed fresh livers with $4\%$ paraformaldehyde, dehydrated them, embedded them in paraffin, and then stained them with hematoxylin and eosin. The cross sections were examined under a microscope (BX63F OLYMPUS Micro Image System, OLYMPUS, Tokyo, Japan). ## 4.8. Serum Biochemical Measurement Analyses of serum alanine aminotransferase (ALT) activity (H001), aspartate aminotransferase (AST) activity (H002), and triglyceride (TG, H201) were performed using an automatic biochemical analyzer (Hitachi 7020, HITACHI, Tokyo, Japan) and respective commercial assay kits purchased from Ningbo Medical System Biotechnology Co., Ltd. (Ningbo, China). ## 4.9. Detection of MDA, SOD, and TGs in Mouse Livers Liver triglycerides were assayed using a triglyceride assay kit (GPO-POD; Applygen Technologies Inc., Beijing, China). A Lipid peroxidation (MDA, malondialdehyde) Assay Kit and Superoxide dismutase (SOD) Activity Kit were purchased from Solarbio (Beijing, China). All detections were completed according to the manufacturer’s instructions. ## 4.10. Enzyme-Linked Immunosorbent Assay (ELISA) ELISA kits were used to detect levels of interleukin 1β (IL-1β) and tumor necrosis factor α (TNFα) (Cusabio, cat. no.: CSB-E08054m, CSB-E04741m, Wuhan, China), following the manufacturer’s protocols. Briefly, standards or samples were added to micro-ELISA strip plate wells and combined with specific antibodies. Antibodies conjugated to horseradish peroxidase (HRP) were added to each well, and free components were then washed away. TMB substrate solution was added to each well. The optical density (OD) of each sample was measured spectrophotometrically at 450 nm, and the concentration was determined by comparing the OD of each sample with the standard curve. ## 4.11. Cell Culture and Cell Transfection Kupffer cells (BeNa Culture Collection, Kunshan, China, BNCC340733) were cultured at 37 °C in a $5\%$ CO2 atmosphere in 1640 medium (Wisent, cat. no.: 350-000-CL, Nanjing, China) containing $10\%$ (v/v) fetal bovine serum. During $70\%$ confluent growth, Kupffer cells were treated for 6 or 12 h with 100 ng/mL LPS [48]. Using jetPRIME® transfection reagent (Polyplus Transfection, Beijing, China), specific small interfering RNAs (Mtfmt siRNA1, Mtfmt siRNA2, and Mtfmt siRNA3; GenePharma, Shanghai, China) were transfected into Kupffer cells to knock down Mtfmt. The scramble siRNA served as a negative control (NC siRNA). The sequences are listed in Supplementary Table S2. ## 4.12. Flow Cytometry Analysis To measure mitochondrial membrane potential, we incubated the cells with complete media containing 2.5 μM JC-1 dye (Thermo Fisher, cat. no.: T3168, Waltham, MA, USA), then harvested them with FACS buffer ($2\%$ FBS in phosphate-buffered saline) and analyzed them with flow cytometry (BD Biosciences, San Jose, CA, USA) after 30 min at 37 °C. ## 4.13. Immunofluorescence To fix Kupffer cells, $4\%$ paraformaldehyde was used for 10 min. Each section was treated with Tris-buffered saline containing $0.3\%$ Triton X-100 for 1 h, blocked with $5\%$ Bovine serum albumin, and then exposed to the primary antibody for an overnight incubation at 4 °C before being exposed to the secondary antibody. The cell nuclei were marked with DAPI. ## 4.14. Mitochondrial ROS Determination Kupffer cells were transfected with control or Mtfmt siRNA and treated with 1 μg/mL LPS [49] for 30 min, and then cell samples were stained with 5 μM MitoSOX red mitochondrial superoxide indicator (Thermo Fisher, cat. no.: M36008, Waltham, MA, USA) for 10 min at 37 °C in order to detect mitochondrial ROS. Three HBSS washes were performed on the labeled cells. Using a Zeiss Observer, which is an inverted microscope, fluorescence images were captured (Carl Zeiss, Thornwood, NY, USA). ## 4.15. Isolation of Mitochondria Mitochondrial isolation from cultured Kupffer cells was performed using a commercial Mitochondria Isolation Kit (Solarbio, cat. no.: SM0020, Beijing, China), as per the manufacturer’s protocol. Briefly, a total of 1 mL of precooled lysis buffer was used to resuspend Kupffer cells collected by trypsinization. In an ice bath, the cell suspensions were ground 30 times in a small-volume glass homogenizer. After centrifugation at 1000× g at 4 °C for 5 min, performed twice, the supernatants were further centrifuged at 12,000× g at 4 °C for 10 min to obtain the crude mitochondrial precipitates. The mitochondrial precipitates were resuspended in 50 μL of wash buffer, then centrifuged at 4 °C for 5 min at 1000× g. The supernatants were centrifuged at 12,000× g for 10 min at 4 °C to obtain mitochondrial precipitates of high purity. These obtained mitochondrial precipitates were resuspended in store buffer or used immediately. ## 4.16. Statistical Analysis GraphPad Prism 9 was used to analyze all data as means ± SEMs. To evaluate the normality of the distribution of values, Kolmogorov–Smirnov testing was employed for each variable. Two-way ANOVA with uncorrected Fisher’s LSD and unpaired Student’s t-tests were used. The differences were considered statistically significant when $p \leq 0.05.$ ## References 1. Kalyani R.R., Golden S.H., Cefalu W.T.. 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--- title: 'Donor-Derived Cell-Free DNA for Kidney Allograft Surveillance after Conversion to Belatacept: Prospective Pilot Study' authors: - Bilgin Osmanodja - Aylin Akifova - Michael Oellerich - Julia Beck - Kirsten Bornemann-Kolatzki - Ekkehard Schütz - Klemens Budde journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051604 doi: 10.3390/jcm12062437 license: CC BY 4.0 --- # Donor-Derived Cell-Free DNA for Kidney Allograft Surveillance after Conversion to Belatacept: Prospective Pilot Study ## Abstract Donor-derived cell-free DNA (dd-cfDNA) is used as a biomarker for detection of antibody-mediated rejection (ABMR) and other forms of graft injury. Another potential indication is guidance of immunosuppressive therapy when no therapeutic drug monitoring is available. In such situations, detection of patients with overt or subclinical graft injury is important to personalize immunosuppression. We prospectively measured dd-cfDNA in 22 kidney transplant recipients (KTR) over a period of 6 months after conversion to belatacept for clinical indication and assessed routine clinical parameters. Patient and graft survival was $100\%$ after 6 months, and eGFR remained stable (28.7 vs. 31.1 mL/min/1.73 m2, $$p \leq 0.60$$). Out of 22 patients, 2 ($9\%$) developed biopsy-proven rejection—one episode of low-grade TCMR IA and one episode of caABMR. While both episodes were detected by increase in creatinine, the caABMR episode led to increase in absolute dd-cfDNA (168 copies/mL) above the cut-off of 50 copies/mL, while the TCMR episode did show slightly increased relative dd-cfDNA ($0.85\%$) despite normal absolute dd-cfDNA (22 copies/mL). Dd-cfDNA did not differ before and after conversion in a subgroup of 12 KTR with previous calcineurin inhibitor therapy and no rejection (12.5 vs. 25.3 copies/mL, $$p \leq 0.34$$). In this subgroup, $\frac{3}{12}$ ($25\%$) patients showed increase of absolute dd-cfDNA above the prespecified cut-off (50 copies/mL) despite improving eGFR. Increase in dd-cfDNA after conversion to belatacept is common and could point towards subclinical allograft injury. To detect subclinical TCMR changes without vascular lesions, additional biomarkers or urinary dd-cfDNA should complement plasma dd-cfDNA. Resolving CNI toxicity is unlikely to be detected by decreased dd-cfDNA levels. In summary, the sole determination of dd-cfDNA has limited utility in the guidance of patients after late conversion to belatacept. Further studies should focus on patients undergoing early conversion and include protocol biopsies at least for patients with increased dd-cfDNA. ## 1. Introduction Donor-derived cell-free DNA (dd-cfDNA) is an emerging biomarker in kidney transplantation. It is currently used as a diagnostic test for antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR) [1,2,3,4,5]. Other suggested indications are guidance of immunosuppressive therapy, when no therapeutic drug monitoring (TDM) is available, for tapering of calcineurin inhibitors (CNI) or in clinically challenging dilemmas such as BK-nephropathy [6,7]. In those situations, detection of patients with overt or subclinical graft injury may support personalized immunosuppression. CNI have substantially improved graft survival but have several adverse effects, including nephrotoxicity, neurotoxicity, as well as cardiovascular side effects such as hypertension, dyslipidemia, and increased risk for post-transplant diabetes mellitus (PTDM) [8,9,10,11,12]. To avoid CNI, belatacept has been developed as an alternative immunosuppressant. Belatacept is a fusion protein of human IgG1 Fc-fragment and CTLA-4, mimicking the latter’s inhibitory effects on T-cell co-stimulation. It has been studied as primary immunosuppressant and as a CNI alternative in the later post-transplant phase [13,14]. When administered immediately after transplantation, a higher rate of TCMR of 17–$22\%$ in comparison to $7\%$ for cyclosporine and a higher risk for post-transplant lymphoproliferative disorders (PTLD) involving the central nervous system have been observed in the first year [13]. When converting from CNI to belatacept more than 6 months after transplantation, $8\%$ of kidney transplant recipients (KTR) developed TCMR in the belatacept group and $4\%$ in the CNI group during the first year after conversion. In both settings, belatacept led to overall improvement of estimated glomerular filtration rate (eGFR) [14]. With uniform dosing and no TDM being available for KTR treated with belatacept, there is currently no way to detect over- or underimmunosuppression and prevent the respective consequences of rejection or infection. Since dd-cfDNA is able to detect allograft injury, it was hypothesized that dd-cfDNA could help to determine the minimal necessary immunosuppression [6]. In line with this rationale, two studies are currently investigating whether a combination of dd-cfDNA and whole-blood transcriptome analysis are able to detect patients who are suitable for belatacept monotherapy (NCT04177095, NCT04786067). The aim of the present study was to assess dd-cfDNA and clinical outcomes in KTR who underwent conversion to belatacept for clinical indication. Our main hypothesis was that for patients with biopsy-proven or suspected CNI toxicity, dd-cfDNA decreases after discontinuing the CNI due to resolving toxicity. Furthermore, we wanted to explore the proportion of patients with increased dd-cfDNA after conversion to standard-dose belatacept and the corresponding clinical outcomes including eGFR changes and biopsy-proven rejection episodes. ## 2. Methods We enrolled 22 KTR who underwent conversion of immunosuppressive medication to belatacept for clinical indication from April 2020 until July 2022. At baseline, we collected donor data (age, sex, and living versus deceased donation), recipient data (age, sex, cause of chronic kidney disease, type of dialysis, duration of dialysis, induction immunosuppressive regimen, and time since transplantation), and clinical data (latest biopsy results and immunosuppressive regimen) from our proprietary electronic health record and transplant database TBase [15]. The patients received regular follow-up visits with laboratory assessments including plasma creatinine, estimated glomerular filtration rate (eGFR), and albumin-creatinine-ratio (ACR) as standard of care (SOC) at baseline and after one, three, and six months. Additionally, de novo donor-specific antibody (dnDSA) formation was assessed once per year in all patients, as previously described [16,17,18]. We assessed main clinical events (acute kidney injury, biopsy-proven rejection episodes, and death) as well. In addition to SOC, the patients received dd-cfDNA testing (Chronix Biomedical, Göttingen, Germany) at baseline and after one, three, and six months. The 6-month observation period was chosen since most rejections occurred during this timeframe in previous trials [14]. Tapering of previous immunosuppression was performed as summarized in Table S1. In the meantime, belatacept was initiated according to Rostaing et al. [ 19] Belatacept 5 mg/kg was given by intravenous infusion on days 1, 15, 29, 43, and 57 and then every 28 days thereafter. Measurement of dd-cfDNA was performed as described previously [1,20]. In brief, for each patient, four informative single-nucleotide polymorphisms (SNPs), defined as a SNP for which the recipient has a homozygous allelic state, and the graft carries at least one heterozygous allele, were selected from a predefined set of 40 SNPs. These four SNPs were used to quantify the dd-cfDNA (%) concentration, which is defined as donor-alleles/(donor-alleles + recipient-alleles). Results for SNPs with heterozygous graft genotypes were corrected by a factor of two. Total cfDNA was extracted from up to 8 mL plasma collected in certified blood collection tubes (Streck Corp., Omaha, NE, USA). The concentration was determined using droplet-digital PCR (ddPCR) and was corrected for extraction loss and cfDNA fragmentation as described previously [1]. Absolute concentration of dd-cfDNA per mL plasma was calculated by multiplying total cfDNA (copies/mL) and dd-cfDNA (%). An abnormal dd-cfDNA result was defined as a value of >50 copies/mL for absolute and >$0.5\%$ for relative quantification [1,21]. The institutional review board of the ethics committee of Charité-Universitätsmedizin Berlin, Germany, approved the study (approval number EA$\frac{2}{144}$/20), and all procedures were in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all patients. Statistical analysis was performed using R version 4.1.2. ## 3. Results In total, 22 patients were enrolled from April 2020 until July 2022. As maintenance immunosuppression, $\frac{17}{22}$ ($77\%$) received tacrolimus, $\frac{4}{22}$ ($18\%$) received cyclosporine, and 1 patient ($5\%$) received sirolimus before conversion to belatacept. Overall, 20 of 22 patients ($91\%$) were converted in the later post-transplant period (>1 year after transplantation), and 15 of 22 patients ($68\%$) had severe arteriolar hyalinosis (ah3) as a sign of chronic CNI-toxicity in the latest biopsy. Additionally, $\frac{1}{22}$ patients ($5\%$) showed moderate arteriolar hyalinosis (ah2), and $\frac{3}{22}$ patients ($14\%$) showed acute tubular necrosis (ATN) attributed to acute CNI toxicity in the latest biopsy. Four patients ($18\%$) underwent empiric conversion to belatacept due to suspected CNI-toxicity without performing kidney biopsy: three patients refused biopsy due to long transplant age of 18, 20, and 23 years, respectively, and for another patient, biopsy could not be obtained due to dual antiplatelet therapy. In $\frac{8}{22}$ patients ($36\%$), ABMR was proven or suspected in the latest kidney allograft biopsy. Patient characteristics are summarized in Table 1 and detailed in Table S2. After conversion to belatacept, eGFR remained stable in our cohort from baseline until month 6 (28.7 vs. 31.1 mL/min/1.73 m2, $$p \leq 0.60$$). All dd-cfDNA and total cfDNA measurements as well as creatinine and ACR values are provided in Table S1. Missing values occurred in 7 out of 88 scheduled measurements ($8\%$). Importantly, patients with ABMR had higher mean absolute dd-cfDNA over the study period than patients without ABMR (88 vs. 20 copies/mL, $$p \leq 0.01$$) (Figure 1A). A total of $\frac{3}{8}$ patients with ABMR had absolute dd-cfDNA values above the prespecified cut-off of >50 copies/mL before conversion, while the other 5 patients had values in the upper normal range. During the course of the study, all patients with ABMR always had values ≥ 25 copies/mL, and $\frac{5}{8}$ patients with ABMR were at least temporarily above the cut-off (Figure 1B). Comparable results were found when using relative dd-cfDNA and the prespecified cut-off of $0.5\%$. The mean relative dd-cfDNA over the study period was higher in patients with previous ABMR than in patients without ABMR ($0.92\%$ vs. $0.40\%$, $$p \leq 0.01$$) (Figure 2A). A total of $\frac{7}{8}$ patients with previous ABMR had at least one relative dd-cfDNA measurement above the cut-off over the study period (Figure 2B). During the observation period, two episodes of biopsy-proven rejection occurred in 22 patients ($9\%$). One episode of caABMR (Patient R1 in Figure 1B and Figure 2B) was accompanied by increase in creatinine (2.5 to 3.7 mg/dL) and dd-cfDNA (42 to 168 copies/mL), and one episode of TCMR IA (Patient R2 in Figure 2B) was indicated by increase in creatinine (1.73 mg/dL to 2.78 mg/dL), absolute dd-cfDNA levels below the cut-off (22 copies/mL at the time of biopsy), and relative dd-cfDNA levels above the cut-off ($0.85\%$ at the time of biopsy). While dnDSA were existent in $\frac{9}{22}$ patients ($41\%$) before switch to belatacept, no additional dnDSA formation or changes in specificity were observed after switch to belatacept in any of the 22 patients. From twelve patients with previous CNI therapy and without rejection (subgroup A), three patients ($25\%$) developed increase in absolute dd-cfDNA above the cut-off (Patients S1–S3 in Figure 1B and Figure 2B). Another patient (Patient S4 in Figure 2B) showed increased relative dd-cfDNA but not absolute dd-cfDNA over the entire study period. None of these four patients underwent indication biopsy—Patient S1 was under dual antiplatelet therapy and showed improving creatinine (4.72 to 3.62 mg/dL), Patient S2 showed slightly increased dd-cfDNA (53 copies/mL) with improving kidney function (creatinine 1.88 to 1.33 mg/dL), Patient S3 showed only transient dd-cfDNA increase (96 copies/mL at month 3, 20 copies/mL at month 6) and improving creatinine (3.59 to 3.1 mg/dL), and Patient S4 showed normal absolute dd-cfDNA and improving creatinine (2.46 to 2.15 mg/dL). Hence, the cause for dd-cfDNA increase remains undetermined in these patients. To assess whether CNI cessation leads to decreased levels of dd-cfDNA, we included only patients with CNI therapy before conversion to belatacept and excluded all patients with rejection from the subsequent analysis (subgroup A). In the remaining 12 patients, absolute dd-cfDNA levels before and 6 months after conversion to belatacept did not differ significantly (mean 12.5 vs. 25.3 copies/mL, $$p \leq 0.34$$). This was also the case when further restricting the analysis to the seven patients with improved eGFR (subgroup B) defined as higher eGFR at month 6 than before conversion (mean 15.4 vs. 38.7 copies/mL, $$p \leq 0.31$$). For relative dd-cfDNA, difference was found after CNI cessation neither in subgroup A ($0.31\%$ vs. $0.52\%$, $$p \leq 0.28$$) nor subgroup B ($0.35\%$ vs. $0.72\%$, $$p \leq 0.25$$). Moreover, no difference in total cfDNA was found in subgroup A (3893 vs. 6101 copies/mL, $$p \leq 0.40$$) or in subgroup B (4477 vs. 7231 copies/mL, $$p \leq 0.54$$). ## 4. Discussion In this pilot study, we report the first use of dd-cfDNA for graft surveillance in KTR after conversion to belatacept-based immunosuppression. Our initial hypothesis was that we could detect resolving CNI toxicity by decreasing levels of dd-cfDNA. However, in this small cohort of patients who mostly underwent late conversion to belatacept due to chronic CNI toxicity, we detected no difference in absolute or relative dd-cfDNA levels before and after conversion in non-rejecting patients. This suggests that plasma dd-cfDNA is not suited to detect subtle changes in graft injury due to CNI toxicity, which has probably two main reasons: chronic CNI toxicity with hyalinosis of the arteriolar walls is a slowly developing process, and acute CNI toxicity mostly affects the tubular cells. Due to the short half-life of cell-free DNA in general and the mainly endothelial origin of plasma dd-cfDNA, both forms are unlikely to be accompanied by a significant increase in dd-cfDNA. Additionally, immune activation during the conversion phase can further alter dd-cfDNA levels, making it even harder to detect subtle changes. Previously, Schütz et al. showed that total cfDNA decreases over time after transplantation, which leads to an apparent increase in relative dd-cfDNA despite stable absolute dd-cfDNA [22]. Such increase was also observed in the Trifecta study, where older grafts showed higher relative dd-cfDNA [5]. It was hypothesized that this effect is due to reduced CNI exposure and subsequent increase in leukocyte stability [22] because both CNI and mTOR inhibitors have a negative effect on cell stability [23,24]. In contrast, we were not able to find a decrease in total cfDNA after CNI cessation in this cohort. In line with previous studies, mean dd-cfDNA was higher in patients with preexisting ABMR than in those without ABMR [1,2,3,4,5]. While in our study, a recurrent ABMR episode was detected by increase in creatinine and also led to increase of dd-cfDNA, other studies indicate that dd-cfDNA increases also can precede clinical rejection [25]. Due to its ability to detect vascular graft injury, dd-cfDNA is currently discussed as an activity marker in ABMR [26]. Therefore, increased dd-cfDNA could indicate underimmunosuppression and active rejection in patients with ABMR who undergo conversion to belatacept for concomitant CNI toxicity. Previously, we have demonstrated, ongoing microvascular inflammation was a risk factor for graft loss after conversion to belatacept, while the presence of dnDSA and chronic ABMR was not [27]. Furthermore, no additional dnDSA formation was observed in our study, which is in line with the reduced rate of dnDSA formation after conversion to belatacept in comparison to CNI-based regimens [13,14]. However, due to the absence of evidence-based therapy options for ABMR, the clinical consequences are uncertain and warrant further investigation [28,29]. The rate of TCMR in our study was comparable to previous studies, although it is important to note that rejection frequency depends on time after transplantation and the proportion of patients with previous TCMR and ABMR [13,14,30]. TCMR episodes without vascular lesions are not reliably detected by plasma dd-cfDNA since inflammation occurs predominantly in the tubulointerstitial compartment [26]. This was shown exemplarily in our study, where an episode of low-grade TCMR (Banff IA) led to slight increase in relative dd-cfDNA but no increase in absolute dd-cfDNA. However, in the Trifecta study, patients with TCMR-related transcriptomic changes showed increased dd-cfDNA with a median of $1.61\%$, while patients with histological TCMR diagnosis had median dd-cfDNA of $0.88\%$ [5]. For low-grade TCMR episodes that occur after conversion to belatacept, the potential benefit of dd-cfDNA for graft surveillance is reduced. Urinary dd-cfDNA and other novel biomarkers such as whole-blood transcriptome analyses are potentially better suited to detect subclinical TCMR. Combining those with dd-cfDNA could potentially help to differentiate subclinical graft injury, which is currently being studied in two trials (NCT04177095, NCT04786067). Interestingly, three clinically improving patients without previous ABMR showed increased absolute dd-cfDNA, and another patient showed increased relative dd-cfDNA, none of which was accompanied by deteriorating renal function. Consequently, no indication biopsies were performed for these patients, leaving the reasons undetermined. However, such patients are of particular interest since they could experience subclinical graft injury due to rejection (ABMR, TCMR), infectious complications (e.g., BKV), or other causes and may need a personalized immunosuppressive regimen. While some of these changes were subtle, further studies may determine the clinical relevance by scheduling protocol biopsies in patients with increased dd-cfDNA. While for the assay used in this study, a cut-off of 50 copies/mL may be adequate to guide protocol biopsies, other assays may use different cut-offs. Sample size calculations can assume that $25\%$ of KTR without rejection who undergo conversion from CNI to belatacept will show at least transient increases in absolute dd-cfDNA above prespecified cut-offs. ## 5. Limitations The main limitations of this study are its small sample size and the lack of follow-up biopsies in patients with increased dd-cfDNA after conversion to belatacept. Another limitation is the limited amount of KTR undergoing early conversion to belatacept in this study. This could lead to false-negative dd-cfDNA results due to a high grade of interstitial fibrosis in older allografts. Advanced kidney lesions together with small numbers and a heterogeneous patient population explain that we did not observe a significant increase in eGFR after conversion to belatacept, contrary to most studies [13,14,30]. ## 6. Conclusions Despite its several limitations, this small pilot study indicates where to seek potential applications for dd-cfDNA for graft surveillance in the future. To detect subclinical TCMR changes in patients undergoing conversion to belatacept, additional biomarkers or urinary dd-cfDNA should complement plasma dd-cfDNA to enable detection of TCMR IA and IB. Furthermore, we suggest studying such combinations of biomarkers mostly in patients undergoing early conversion to belatacept to reduce the possibility of false-negative results due to high grades of interstitial fibrosis. Such future studies may also need to include protocol biopsies, at least in patients with increased dd-cfDNA, to further characterize the type of subclinical graft injury. ## References 1. Oellerich M., Shipkova M., Asendorf T., Walson P.D., Schauerte V., Mettenmeyer N., Kabakchiev M., Hasche G., Grone H.J., Friede T.. Absolute quantification of donor-derived cell-free DNA as a marker of rejection and graft injury in kidney transplantation: Results from a prospective observational study. Am. J. Transpl. (2019) 19 3087-3099. DOI: 10.1111/ajt.15416 2. Bloom R.D., Bromberg J.S., Poggio E.D., Bunnapradist S., Langone A.J., Sood P., Matas A.J., Mehta S., Mannon R.B., Sharfuddin A.. Cell-Free DNA and Active Rejection in Kidney Allografts. J. Am. Soc. Nephrol. 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--- title: Phenolic Content, Antioxidant, Antibacterial, Antihyperglycemic, and α-Amylase Inhibitory Activities of Aqueous Extract of Salvia lavandulifolia Vahl authors: - Firdaous Remok - Soukaina Saidi - Aman Allah Gourich - Khalid Zibouh - Mohamed Maouloua - Fadwa El Makhoukhi - Naoual El Menyiy - Hanane Touijer - Mohamed Bouhrim - Sevser Sahpaz - Ahmad Mohammad Salamatullah - Mohammed Bourhia - Touriya Zair journal: Pharmaceuticals year: 2023 pmcid: PMC10051605 doi: 10.3390/ph16030395 license: CC BY 4.0 --- # Phenolic Content, Antioxidant, Antibacterial, Antihyperglycemic, and α-Amylase Inhibitory Activities of Aqueous Extract of Salvia lavandulifolia Vahl ## Abstract Salvia lavandulifolia Vahl essential oil is becoming more popular as a cognitive enhancer and treatment for memory loss. It is high in natural antioxidants and has spasmolytic, antiseptic, analgesic, sedative, and anti-inflammatory properties. Its aqueous extract has hypoglycemic activity and is used to treat diabetic hyperglycemia, but few studies have focused on it. The objective of this work is to evaluate the various biological and pharmacological powers of Salvia lavandulifolia Vahl leaf aqueous extract. Quality control of the plant material was first carried out. Followed by a phytochemical study on the aqueous extract of S. lavandulifolia leaves, namely phytochemical screening and determination of total polyphenols, flavonoids, and condensed tannins contents. Then, the biological activities were undertaken, in particular the antioxidant activity (total antioxidant activity and trapping of the DPPH° radical) and the antimicrobial activity. The chemical composition of this extract was also determined by HPLC-MS-ESI. Finally, the inhibitory effect of the α-amylase enzyme as well as the antihyperglycaemic effect was evaluated in vivo in normal rats overloaded with starch or D-glucose. The aqueous extract obtained by use of the decoction of leaves of S. lavandulifolia contains 246.51 ± 1.69 mg EQ of gallic acid/g DE, 23.80 ± 0.12 mg EQ quercetin/g DE, and 2.46 ± 0.08 mg EQ catechin /g DE. Its total antioxidant capacity is around 527.03 ± 5.95 mg EQ of ascorbic acid/g DE. At a concentration of 5.81 ± 0.23 µg/mL, our extract was able to inhibit $50\%$ of DPPH° radicals. Moreover, it showed bactericidal effect against Proteus mirabilis, fungicidal against Aspergillus niger, Candida albicans, Candida tropicalis, and Saccharomyces cerevisiae, and fungistatic against Candida krusei. A marked antihyperglycemic activity (AUC = 54.84 ± 4.88 g/L/h), as well as a significant inhibitory effect of α-amylase in vitro (IC50 = 0.99 ± 0.00 mg/mL) and in vivo (AUC = 51.94 ± 1.29 g/L/h), is recorded in our extract. Furthermore, its chemical composition reveals the presence of $37.03\%$ rosmarinic acid, $7.84\%$ quercetin rhamnose, $5.57\%$ diosmetin-rutinoside, $5.51\%$ catechin dimer, and $4.57\%$ gallocatechin as major compounds. The antihyperglycemic and α-amylase inhibitory activities, associated with the antioxidant properties of S. lavandulifolia, justify its use in the treatment of diabetes in traditional medicine and highlight its potential introduction into antidiabetic drugs. ## 1. Introduction Aromatic and medicinal plants have played a crucial role in the treatment and prevention of a wide range of diseases for thousands of years [1]. The therapeutic uses of herbs are based on plant chemistry [2]. Having an awareness of the chemical make-up of plants enables one to have a greater comprehension of the therapeutic potential of certain plants. Secondary metabolites, in particular, have been shown to have a variety of biological effects and have been labeled as antioxidants, antibiotics, antifungals, and antivirals and thus are capable of protecting plants from pathogens [3]. Sixty percent to eighty percent of the world’s population uses herbal medicine as its primary source of healthcare [4]. The Lamiaceae family is a plant family with a global distribution that includes approximately 236 genera (6900–7200 species). Salvia is the family’s largest genus, with nearly 900 species [5]. It is widespread in the tropics as well as in the temperate zones of the world in the following order: the Mediterranean basin, central Asia, the American continent, the Pacific islands, and equatorial Africa and China [6]. Species of this genus have shown many biological activities [7]. In traditional medicine, sage is one of the oldest medicinal plants used by man and is considered a panacea. It is used for its antibacterial, antiviral, antioxidant, antimalarial, anti-inflammatory, antidiabetic, cardiovascular, and antitumor effects [8]. In addition, it helps preserve food thanks to its antioxidant properties [9]. S. lavandulifolia is a widely distributed species in the Mediterranean basin, in eastern Spain, extending to the western Mediterranean: southeastern Spain and northwestern Africa (Morocco and Algeria) [10,11]. In traditional medicine, S. lavandulifolia is used to treat and prevent various diseases. It is used as a fungicidal, virucidal, and bactericidal agent [12]. Additionally, the aqueous extract of this herb is used as a popular hypoglycemic remedy for diabetic patients [13]. In Morocco, this plant grows spontaneously in various regions [12]. It is generally used as a spice in the cosmetics industry [14]. Its leaves are used in traditional medicine as an antiseptic, healing, choleretic, astringent, and hypoglycemic remedy [15,16], and its antibacterial and antidiabetic activities had also been confirmed [17]. Diabetes is a group of metabolic diseases in which hyperglycemia is the main characteristic. The high level of glucose in the blood generates, among other consequences, oxygen free radicals by auto-oxidation of glucose, which is associated with the pathogenesis of diabetes complications [18]. The persistence of the high content of glucose in the blood leads to its auto-oxidation. It will also induce the generation of free radicals, thus causing diabetic complications. For this, the control of hyperglycemia by use of natural products is a good way to prevent their appearance in diabetic patients. The main objective of this work is the characterization of phytochemicals and the evaluation of the effects: antioxidant, antimicrobial, anti-hyperglycaemic, and α-amylase enzyme inhibitor in vitro and in vivo of the aqueous extract of S. lavandulifolia, which is highly valued in traditional medicine as an aromatic plant with a medicinal character. ## 2.1. Quality Control of Plant Material Plant material quality control results are shown in Table 1. The moisture content of the leaves of S. lavandulifolia is around $10.5\%$; this value is significantly lower than the limit value set at $12\%$ [19]. The pH of our plant is acidic (5.26: acidophilic); its titratable acidity is $0.61\%$ and contains $5.47\%$ of mineral matter. The dosage of metallic trace elements present in S. lavandulifolia showed quite low levels of arsenic (0.0055 mg/g), chromium (0.0012 mg/g), antimony (0.001 mg/g), cadmium (0.0001 mg/g), copper (0.004 mg/g), and titanium (0.0049 mg/g) against a slightly high iron content (0.5099 mg/g) and an absence of lead. It is to be noted that these results are below the limit values for each MTE. ## 2.2. Phytochemical Screening Phytochemical screening is a preliminary and of great importance step since it reveals the presence of constituents known for their various biological activities and medicinal properties. The results of the screening of the leaves of S. lavandulifolia are shown in Table 2. The phytochemical characterization tests carried out made it possible to highlight the richness of our plant in primary and secondary metabolites. Indeed, our plant is rich in proteins, lipids (sterols and triterpenes), sugars, and carbohydrates (oses and holosides) as well as polyphenols such as flavonoids (leucoanthocyanins, flavones), tannins, alkaloids, mucilages, and saponosides. These results agree with the literature, indeed, many researchers have confirmed the presence of sugars, polyphenols, and flavonoids in S. lavandulifolia [20,21,22]. ## 2.3. Contents of Polyphenols, Flavonoids, and Condensed Tannins Polyphenols are secondary metabolites abundantly present in almost all species of aromatic and medicinal plants. These metabolites are essential for human nutrition due to their antioxidant properties and are beneficial to health [23]. The results of the various assays are grouped in Figure 1. The extract of S. lavandulifolia is composed of 246.51 ± 1.69 mg EAG/g DE, 13.56 ± 0.08 mg EQ/g DE, and 2.46 ± 0.08 mg EC/g DE of total polyphenols, flavonoids, and condensed tannins, respectively. Our results are almost identical to those found by Boutahiri et al. [ 2021] in terms of total polyphenol content. They found that the aqueous extract of S. lavandulifolia obtained by decoction contains 252.67 ± 5.40 mg EAG/g DE [17]. Polyphenols are considered the most abundant group of secondary metabolites in plants, through which they defend themselves against predators and intrusions [24]. They are distinguished by the presence of hydroxyl groups, which enable them to be reactive by chelating metal ions and neutralizing free radicals through hydrogen atoms or electrons, thereby reducing their prooxidant activity [25,26]. Thanks to these characteristics, these molecules, endowed with preventive and curative effects of several diseases related to oxidative stress, have received great interest [27,28]. The family of polyphenols is divided into several classes of which flavonoids represent the majority ($60\%$). They are responsible for the attractive colors of flowers, fruits, and leaves. They are more precisely called “nutraceuticals” thanks to their different pharmacological effects on the body. The advantages of being readily absorbed by the intestine, their ability to combat free radicals, and their hypoglycemic effect are what define flavonoids [29] as well as their hypoglycemic effect [30]. Tannins also have antioxidant power. Indeed, they block the formation of superoxide and the peroxidation of lipids [31]. Condensed tannins are oligomeric and polymeric byproducts of the biosynthesis of flavonoids [32]. Additionally, their capacity to scavenge free radicals is well known. They may not be present, but their quantity in the extracts is lower than that of the other bioactive compounds [33]. ## 2.4. Chemical Composition of S. lavandulifolia Extract The HPLC chromatogram and the chemical composition of the aqueous extract of S. lavandulifolia are shown in Figure 2 and Table 3. The below results show that our extract contains rosmarinic acid ($37.03\%$), followed by quercetin rhamnose ($7.84\%$), diosmetin-rutinoside ($5.57\%$), catechin dimer ($5.51\%$), gallocatechin ($4.57\%$), luteolin ($4.12\%$), caffeic acid ($4.02\%$), carnosol ($3.97\%$), catechin ($2.62\%$), rhamnetin ($1.84\%$), rutin ($1.78\%$), azelaic acid ($1.61\%$), ferulic acid ($1.48\%$), and vanillic acid ($1.46\%$) covering more than $80\%$ of the overall composition of the extract. Several of these compounds are known for their important pharmacological activities. For example, rosmarinic acid, our major compound, is reputed to be antibacterial [34], antiviral [35], anti-inflammatory [36], anti-cancer [37], health-enhancing [38], and antioxidant [34,39]. Luteolin is known for its inhibitory effect on α-glucosidase and α-amylase enzymes [40]; it also has antioxidant, antimicrobial, anti-inflammatory, antidiabetic, neuroprotective, anticancer, and cardioprotective properties [41]. The antiradical activity of caffeic acid has been demonstrated [42]. Carnosol, for its part, is considered antioxidant, anticancer, anti-inflammatory, and antimicrobial [43]. Previous studies compiled by Claudia Musial and her collaborators indicated antitumor, antioxidant, anti-inflammatory, antimicrobial, antiviral, antidiabetic, antiobesity, and hypotensive effects related to catechins [44]. Our results agree with those of Salima Boutahiri et al., having identified rosmarinic acid, apigenin, luteolin, myricetin, herniarin, caffeic acid, protocatechuic acid, coumarin, cinnamic acid, vanillic acid, gallic acid, and chlorogenic acid in the aqueous extract of S. lavandulifolia leaves [17]. Salvador Cafligueral et al. revealed the presence of apigenin, luteolin, rosmarinic acid, quercetin-3-O-β-D-glucoside, luteolin-7-O-β-D-glucoside, luteolin-4′-O-glucoronide, luteolin-7-O-rutinoside, and other compounds such as nepetin and 5-Hydroxy-7, 4′-dimethoxyflavone in the soluble fraction of petroleum ether and chloroform extracts from the leaves of S. lavandulifolia [45]. ## 2.5. Antioxidant Properties The different antioxidant activities of Salvia lavandulifolia are shown in Table 4. ## 2.5.1. Total Antioxidant Capacity The PM (phosphomolybdate) test, such as CUPRAC (copper (II) ion reducing capacity) and FRAP (iron (III) reducing capacity), was selected to analyze the reduction capacity of S. lavandulifolia extract. This method involves the transfer of a single electron. In this system, the electron from the antioxidant that has been oxidized is transferred to the sub-strate, which prevents the oxidant from being reduced [46]. This assay quantifies the rate of reduction between antioxidant, oxidant, and molybdenum ligands and assesses the degree of reduction of Mo (VI) to Mo (V). It entails thermally generating auto-oxidation over an extended period of time at a high temperature. The advantage of this assay is to give a direct estimate of the antioxidant’s reducing capacity. Our extract showed a total antioxidant capacity of 527.03 ± 5.95 mg EQ AA/g ES as shown in Table 4. The latter is clearly high; this can be explained by the presence of luteolin known for its antioxidant capacity, chelator of transition metals [41]. ## 2.5.2. Free Radical Scavenging DPPH° DPPH° is a stable free radical that is frequently utilized to evaluate the antioxidant activity of natural compounds in a straightforward, quick, and accurate manner [47]. The results of this test, shown in Figure 3, indicate that S. lavandulifolia leaves have very significant antiradical activity, with an IC50 of 5.81 ± 0.23 µg/mL; however, its effect remains lower than that of acid ascorbic (IC50 = 3.06 ± 0.30 µg/mL). These results are consistent with the previous study by Pop et al., 2016 where the ability to scavenge DPPH° free radicals by the methanolic extract of S. lavandulifolia was demonstrated [48]. However, the antiradical property of this plant is linked to its richness in polyphenols. The latter is composed of hydroxyl groups that can neutralize free radicals [49]. Further UHLPC analysis shows the presence of caffeic acid and rutin potential responsible in minor part for this high capacity. As well as rosmarinic acid in particular, identified with a percentage of $37\%$, is reputed to have an important antiradical property [38,50]. ## 2.6. Antimicrobial Activity The antimicrobial activity of S. lavandulifolia extract was evaluated against strains of bacteria and fungi (Table 5). The results of the MIC values obtained show that the extract was more active against the strains tested. The lowest MIC found is 2.34 mg/mL against Staphylococcus aureus. The strains Escherichia coli, Pseudomonas aeruginosa, and Candida krusei are inhibited with an extract concentration of 18.75 mg/mL. In addition, the extract has also inhibited the following strains: Enterobacter cloacae, Klebsiella pneumoniae, Staphylococcus epidermidis, Candida albicans, Candida tropicalis, and Saccharomyces cerevisiae with an MIC = 37.5 mg/mL each. While Escherichia coli ESBL, Proteus mirabilis, Streptococcus agalactiae (B), Aspergillus niger, Candida dubliniensis, Candida kyfer, and Candida parapsilosis strains are inhibited starting from a concentration of 75 mg/mL. According to the MBC/MIC ratio, the extract of S. lavandulifolia reported a bactericidal effect against Proteus mirabilis and fungicidal against strains Aspergillus niger, Candida albicans, Candida tropicalis, Saccharomyces cerevisiae, and Candida krusei. Based on these findings, Salvia lavandulifolia extract could potentially be used as natural preservatives in foods against well-known causative agents of foodborne illnesses such as S. aureus and E. coli [17]. In this work, the inhibitory activities of this extract are probably due mainly to the action of the majority compounds in this extract: rosmarinic acid, quercetin rhamnose, diosmetin-rutinoside, and catechin dimer [21]. The antimicrobial activity of rosmarinic acid against various bacterial and fungi strains has been described by a number of authors. Additionally, a study was carried out by Giner and his associates [51] on the combination of hydroalcoholic extracts of S. lavandulifolia, S. rosmarinus, and T. mastichina. With an MIC value of 12.8 mg/mL, they demonstrated that it is effective against E. coli and E. aerogenes; these data are consistent with our findings. ## 2.7. Toxicity Traditional MAP-based treatments can induce toxicity problems leading to treatment failures. For this, we conducted pharmacological tests in vivo after first assessing the toxicity of the aqueous extract of S. lavandulifolia. This experiment aims to demonstrate that the therapeutic doses of S. lavandulifolia extract (0.5 g/kg, 1 g/kg, or 2 g/kg) do not cause short-term toxicity in healthy mice. According to the test’s findings, the extract is not toxic even at a dose of 2 g/kg. Throughout the entire follow-up period, it did not result in any toxicity symptoms (such as diarrhea, vomiting, abnormal mobility, etc.) or fatalities. According to Perry et al. [ 2001], long-term use of S. lavandulifolia as a food flavoring agent did not induce adverse effects [52]. ## 2.8. Antihyperglycemic Effect In normal rats, oral administration of the S. lavandulifolia aqueous extract at 400 mg/Kg 30 min before the glucose overload significantly reduced post-prandial hyperglycemia at 60 min ($p \leq 0.01$, 1.13 ± 0.14 g/L) and at 90 min ($p \leq 0.01$, 0.89 ± 0.17 g/L). In a similar manner, glibenclamide significantly reduced postprandial hyperglycemia for two hours after glucose overload at 60 min ($p \leq 0.01$; 1.08 ± 0.09 g/L) and 90 min ($p \leq 0.05$; 1.09 ± 0.10 g/L). In comparison to pretreated distilled water, there was no discernible difference in blood glucose levels between the two groups at 150 min; (0.76 ± 0.07 g/L) at 150 min (1.22 ± 0.11 g/L) at 90 min, and at 60 min (1.37 ± 0.16 g/L) (Figure 4A). In rats treated with the aqueous extract of S. lavandulifolia (54.84 ± 4.88 g/L/h) as opposed to rats treated with distilled water (62.91 ± 4.32 g/L/h), the area under the curve (AUC glucose) is significantly lower in the former group ($p \leq 0.01$) (Figure 4B). It is also less than the positive control (glibenclamide), which is significantly less (55.95 ± 1.69 g/L/h; $p \leq 0.01$) than the rats given distilled water. Additionally, it is less than the positive control (glibenclamide), which has a significantly lower concentration (55.95 ± 1.69 g/L/h; $p \leq 0.01$) than rats given distilled water as a treatment. These results are consistent with those of Jimenez et al. from 1986, who demonstrated that administration of an aqueous extract of S. lavandulifolia 60 min before glucose over-load induced marked antihyperglycemic activity, compared to administration of glucose alone. This finding suggests that intestinal glucose uptake may be a key factor that may explain this activity [53]. The majority of Salvia species used in traditional medicine to treat diabetes frequently work by boosting insulin secretion, boosting adipose tissue and skeletal muscle glucose uptake, and reducing intestinal glucose absorption and hepatic glycogenolysis [54]. In a different study, the hypoglycemic activity of S. lavandulifolia was attributed to its capacity to promote glucose uptake in peripheral tissues (muscle and adipose tissue), which results in the return of blood sugar to normal levels [54]. Studies on this plant’s aqueous extract have similarly demonstrated its hypoglycemic effects by raising pancreatic insulin secretion and peripheral glucose uptake [54,55]. ## 2.9.1. In Vitro Test An enzyme called pancreatic α-amylase breaks down polysaccharides (such as starch and glycogen) into disaccharides. Figure 5 depicts the impact of the S. lavandulifolia aqueous extract on the in vitro activity of this enzyme. In fact, our extract significantly inhibited the activity, with an IC50 of 0.99 ± 0.00 mg/mL compared to IC50 = 0.52 ± 0.01 mg/mL for acarbose. Inhibiting α-amylase activity is one of the most efficient therapeutic strategies to manage postprandial hyperglycemia in diabetic patients [56]. The concentration of fibers in S. lavandulifolia and the presence of inhibitors on these fibers reduce the accessibility of starch to the enzyme, decreasing the activity of α-amylase. These are just a few of the factors that contribute to this inhibition [57]. ## 2.9.2. In Vivo Test Oral administration of aqueous extract of S. lavandulifolia at $C = 400$ mg/kg 30 min before starch overload in normal rats significantly reduced postprandial hyperglycemia at 60 min ($p \leq 0.001$, 0.90 ± 0.06 g/L), at 90 min ($p \leq 0.001$; 0.83 ± 0.03 g/L), and at 150 min ($p \leq 0.001$; 0.84 ± 0.02). Similar to this, acarbose significantly reduced postprandial hyperglycemia during the two hours that followed starch overload at 60 min ($p \leq 0.001$, 0.89 ± 0.06 g/L), at 90 min ($p \leq 0.001$, 0.85 ± 0.08 g/L), and at 150 min ($p \leq 0.001$, 0.78 ± 0.09 g/L) (Figure 6A). Rats pretreated with distilled water only recorded remarkable hyperglycemia, unlike the first and second groups, at 60 min (1.07 ± 0.02 g/L), at 90 min (1.15 ± 0. 07 g/L), and 150 min (1.05 ± 0.04 g/L). In addition, the area under the curve (AUC glucose) was significantly lower ($p \leq 0.001$) in rats treated with plant extracts (51.94 ± 1.29 g/L/h) than those treated with acarbose (52.05 ± 4.27 g/L/h) and distilled water (61.82 ± 1.53 g/L/h) (Figure 6B). As mentioned above, S. lavandulifolia is rich in polyphenols and flavonoids. Moreover, phytochemical analysis of this aqueous extract showed that it contains apigenin, rosmarinic acid, and luteolin, responsible for the inhibitory effect of pancreatic α-amylase [40,58,59,60], hence, the drop in blood sugar levels. ## 3.1. Plant Material S. lavandulifolia is a species of the genus Salvia, family Lamiaceae, and order Lamiales. It is commonly called lavender sage or Spanish sage. Our drug was harvested in the rural town of Ouled Ali in the province of Boulemane-Morocco in May 2020 (Table 6) and was dried in the open air and protected from light for two weeks. ## 3.2.1. Humidity Level A quantity of 5 g of dry plants was put in Petri dishes and left in the oven at a temperature of 100 ± 5 °C for 24 h [61,62]. HL (%)=(m1−m2)m1×100 m1: initial mass of the plant before drying in the oven (g), m2: final mass of the plant after drying in the oven (g). ## 3.2.2. pH Determination A mass (5 g) of the sample was combined with 500 mL of distilled water. A stirrer and magnetic bar were used to stir the mixture for 5 min at room temperature. After that, the mixture was filtered. The pH was determined using an STPURE electrode-equipped benchtop pH meter, the Ohaus Starter 3100 [63]. The pH reading was then taken by placing the electrode of the pH meter into a volume of filtrate. ## 3.2.3. Determination of Titratable Acidity Ten grams of herbal drug powder was extracted by use of 100 mL of boiling water for 15 min. Following filtration, the mixture was combined with 20 mL of distilled water from 10 mL of the filtrate. Following the addition of a few drops of phenolphthalein, the titration procedure was continued using a solution of NaOH (0.01 N) until a persistent pink color was achieved. The volume of NaOH poured up to the equivalence point is converted into equivalent citric acid using the following formula [64]. Total acidity=dilution factor × weight of eq. Acid ×normality of NaOH × titration vol.(mL) sample mass (g) ## 3.2.4. Ash Content The organic matter content is determined by calculating the difference in weight before and after calcination. The latter consists of passing 2 g of ground sample in a muffle furnace at a temperature of 550 °C, up to the total destruction of any carbonaceous particles (light gray or whitish color) [65]. The organic matter content is calculated using the following formula:OM%=m1−m2TS×100 OM%: Organic matter; m1: Pre-calcination capsule and sample mass; m2: Post-calcination capsule and sample mass; TS: Test sample. The ash content was calculated as follows: MM% = 100 − MO% ## 3.2.5. Dosage of Metallic Trace Elements (MTE) by ICP-AES For the determination of MTE contents (As, Cr, Sb, Pb, Cd, Fe, Cu, and Ti), the mineralization protocol with aqua regia (HNO3 + 3HCl) was adopted. The method consists of mixing 0.1 g of crushed plant material with 3 mL of aqua regia and heating it under reflux (200 °C) for two hours. After cooling and settling, the supernatant is recovered and filtered on a membrane (0.45 µm) and then made up to 15 mL with water. Notably, the inductively coupled plasma atomic emission spectrometer (ICP-AES) was used to measure the MTE concentrations. [ 66]. ## 3.3. Preparation of the Aqueous Extract of Salvia lavandulifolia Briefly, 30 g of the crushed plant was introduced into a reflux assembly with 750 mL of distilled water. The mixture was heated at 80 °C with stirring for one hour and filtered [62]. The extract was dried in an oven at 70 °C overnight in a silicone mold and then collected in amber glass bottles. Y (%)=m2m1×100 Y: yield; m2: mass of the extract; m1: mass of the crushed plant. ## 3.4. Phytochemical Screening Phytochemical screening tests are qualitative tests that consist of detecting the different families of compounds present in plant material. They are based on coloring, precipitation, or complexation reactions [67,68]. ## 3.5.1. Determination of Total Polyphenol Content The Singleton et al. protocol was utilized to determine total phenolic content (TPC), with a few minor modifications [69]. Quantities of 15 µL ($C = 25$ mg/mL) of extract, 1.5 mL of Folin Ciocalteux’s reagent ($10\%$), and 1.5 mL of Na2CO3 ($7.5\%$) were introduced, respectively, into 50 mL volumetric flasks and supplemented with distilled water. The mixture was blended and incubated at room temperature for 40 min in the dark. The concentration of phenolic compounds in the S. lavandulifolia extract was expressed in equivalents of gallic acid (EGA), and the absorbance at a wavelength of 760 nm was measured. ## 3.5.2. Determination of Flavonoid Content To test tubes, 30 µL ($C = 25$ mg/mL) of extract, 2 mL of distilled water, and 10 µL of aluminum chloride prepared in methanol ($10\%$, m/V) were added. Pure methanol was used to dilute the mixture to a total volume of 5 mL. The solutions were mixed and incubated in the dark for 30 min. At 433 nm, absorbance was measured, and flavonoid concentration was expressed as quercetin equivalents (QE) [70]. ## 3.5.3. Determination of Condensed Tannin Content 100 µL ($C = 25$ mg/mL) of extract, 3 mL of vanillin methanolic solution ($4\%$, m/V), and 1.5 mL of HCl ($37\%$) were added in test tubes. The contents of the tubes were mixed and incubated at room temperature for 20 min in the dark. At 499 nm, absorbance was measured, and condensed tannin concentration was expressed in CE catechin equivalent [71]. ## 3.6. Identification of the Chemical Composition by HPLC-MS-ESI The HPLC-MS analysis was conducted by the Dionex UltiMate 3000 ULC/HPLC system coupled to an Exactive mass spectrometer with an ESI ionization source and an orbitrap analyzer. A volume of 10 μL of extract dissolved in distilled water ($C = 100$ μg/mL) was injected into a C18 column with 100 mm long, 2.1 mm in diameter, and with 1.7 µm pores. The temperature was programmed at 30 °C, while the flow rate was 0.45 mL/min. The mobile phase contained two solvents: solvent A (Water + formic acid ($0.1\%$), v/v) and solvent B (Acetonitrile + formic acid ($0.1\%$), v/v). The established elution gradient was “A+B” [98:2] (0–19 min), “A+B” [70:30] (20–24 min), “A+B” [5:95] (25 min), and “A+B” [98:2] (26–30 min). The detection was carried out using a diode array detector by scanning in the wavelength range of 280–360 nm, as well as by the spectrometer of mass (Exactive) after negative ionization. Data were acquired using MASS LYNX software(Version 4.2). The molecules were identified based on retention time, mass spectrum, molecular weight, and by comparison with standards (injected under the same conditions as the extract): caffeic acid, coumaric acid, ferulic acid, gallic acid, rosmarinic acid, sinapic acid, syringic acid, tannic acid, trans-cinnamic acid, vanillic acid, apigenin, catechin, coumarin, kaempferol, luteolin, myricetin, and rutin. ## 3.7.1. Total Antioxidant Capacity The test sample was mixed with 1 mL of ammonium molybdate (4 mM), 1 mL of sodium phosphate (28 mM), and 1 mL of sulfuric acid (0.6 M) in test tubes. The tubes’ contents were combined and incubated at 95 °C for ninety minutes before being normalized for 20 to 30 min at room temperature. At 695 nm, the measurement was made. The results were expressed in milligram equivalents of ascorbic acid per gram of dry extract (mg EAA/g DE), with ascorbic acid serving as the control [72]. ## 3.7.2. 2,2′-Diphenyl-1-Picryl Hydroxyl Test An increasing volume of extract was put into test tubes, and ethanol was added to reach a total volume of 200 µL. A quantity of 2.8 mL of ethanolic solution of DPPH° (24 µg/mL, m/V) was added to the mixture and left to incubate for 30 min in the dark. Notably, UV–Vis absorbance was measured at 515 nm [73]. % inhibition=AC−ASAC×100; EC50=IC50CDPPH AC: Absorbance of the negative control, AS: Absorbance of the sample, IC50: Inhibiting concentration $50\%$ of DPPH° radicals (mg/mL), CDPPH: Concentration of DPPH° (mg/mL). EC50 effective concentration was used to calculate the antiradical potency. The higher the ARP, the more effective the antioxidant [74]. ARP=100EC50 EC50: Effective concentration of the sample. ## 3.8.1. Preparation of Microbial Suspensions The antimicrobial activity of S. lavandulifolia aqueous extract was tested against nine bacteria and fungi (Table 7). These pathogenic microorganisms are frequently encountered in many infections, causing clinical and therapeutic issues. All strains were first frozen in $20\%$ glycerol stock at −80 °C and then regenerated on Mueller–Hinton or Sabouraud broths and finally subcultured. ## 3.8.2. Determination of MIC and MBC/MFC The minimum inhibitory concentration (MIC) was determined by use of 96-well microplates using the reference method of microdilution [75]. From an extract stock solution prepared in a 30:70 ethanol/distilled water mixture, a series of dilutions were carried out to obtain various concentrations ranging from 75 to 4.6875 mg/mL, with a final volume of 100.00 μL in Mueller–Hinton (MH) broth for the bacterial strain and Sabouraud broth for the fungal strain. Following that, 100 µL of microbial suspension (inoculum) with a final concentration of 106 CFU/mL for bacteria or 104 CFU/mL for fungi was added to the different wells (1 to 11), with the 11th and 12th wells serving as growth and sterility controls, respectively. After incubating for 24 h at 37 °C, 10 μL of resazurin was added to each well as a microbial growth indicator before reincubating for two hours at 37 °C. The change in color from purplish blue to bright pink revealed growth. The MIC is defined as the lowest concentration that prevents resazurin from changing color. To determine the MBC or MFC, 10 µL was taken from each well where no growth could be seen and put on MH agar for bacterial growth or Sabouraud for fungal growth for 24 h at 37 °C. After incubation, MBC/MFC is determined as the lowest concentration inhibiting colony formation on solid agar medium [76]. To evaluate antimicrobial potency, the MBC/MIC or MFC/MIC ratio can be calculated. Indeed, if the ratio is less than 4, the extract is bactericidal/fungicidal; if it is greater than 4, the sample is bacteriostatic/fungistatic [77]. ## 3.9. Animals Wistar rats (200–250 g) and albino mice (25–35 g) were used in this study and were reared under ideal conditions photoperiods of 12 h light/12 h dark and 22 ± 2 °C) with free access to water and food. This test was carried out in accordance with the Organization for Economic Cooperation and Development’s guidelines (OECD) [78]. ## 3.10. Acute Toxicity A quantity of 24 albino mice (20–35 g) on an empty stomach (14 h) were randomly distributed into four groups ($$n = 6$$; ♂/♀ = 1). The control group received distilled water (10 mL/kg) and the treated groups received the doses: 0.5 g/kg, 1 g/kg, and 2 g/kg. When the test first began, the mice were weighed. Immediately afterwards, they received a single dose of the test extract, orally. Then, they were continuously monitored for 10 h to report any apparent signs of toxicity. For the remaining 14 days, the mice were kept under daily surveillance for further clinical or behavioral signs of toxicity. This test was performed in accordance with the guidelines of the Organization for Economic Co-operation and Development (OECD) [78]. ## 3.11. Antihyperglycemic Effect The oral glucose tolerance test was performed to evaluate the antihyperglycemic (postprandial glucose) effect in vivo [79]. Normal rats were divided into three groups ($$n = 6$$; ♂/♀ = 1): control group: distilled water (10 mL/kg) and test groups: normal rats force-fed with the extract (400 mg/kg) or glibenclamide (2 mg/kg). First, blood glucose was measured at t0 just before administration of the test product (distilled water, aqueous extracts, or glibenclamide). A total of 30 min later, another measurement of glycemia was carried out then the rats were overloaded with D-glucose (2 g/kg). Subsequently, the variation in blood glucose was measured every half hour up to 90 min and then after one hour. ## 3.12.1. In Vitro Test The Nageswara Rao Thalapaneni et al. [ 80] method with some modifications was used to examine the inhibitory effect of S. lavandulifolia aqueous extract on pancreatic-amylase enzymatic activity. Increasing volumes of S. lavandulifolia extract/acarbose were added to test tubes, which were then filled to a capacity of 200 µL with distilled water. The tubes were then filled with 200 µL of pancreatic α-amylase solution (61.33 U/mL) and 200 µL of phosphate buffer (PB) solution (0.02 M; pH = 6.9), with the exception of the correction series, where the PB solution was used in its place. A time of 10 min at 37 °C were spent pre-incubating the tubes. The tubes were then re-incubated for 15 min at 37 °C with 200 µL of a $0.5\%$ starch solution. After adding 600 µL of DNSA ($2.5\%$) to halt the enzymatic reaction, the tubes were heated in a boiling water bath for 8 min. The tubes were placed in an ice bath to stop the reaction, and then 10 mL of diluted water was added to each tube. In order to compare the absorbance at 540 nm to the correction series, a spectrophotometer was used. The percentage inhibition was calculated using the equation shown below:Inhibitory activity percentage=(AbControl−AbBlank)−(AbTest−AbBlank of the corresponding tube)(AbControl−AbBlank)×100 with: AbControl: absorption of enzyme activity without inhibitor; AbTest: Absorption of enzymatic activity in the presence of the extract or acarbose; AbBlank/Blank of the corresponding tube: a series of corrections is carried out in parallel with each series where the enzyme is replaced by the PB. ## 3.12.2. In Vivo Test The purpose of this test is to confirm the enzymatic activity of pancreatic-amylase-inhibitory effect of S. lavandulifolia aqueous extract in vivo in normal rats by taking into account the effect of intestinal lumen on the extract’s inhibitory effect. Normal fasting rats (180–250 g, 14 h) were divided into three groups ($$n = 6$$; ♂/♀ = 1): the control group was given distilled water (10 mL/kg), while the treated groups were given the extract (400 mg/kg) or acarbose (10 mg/kg). After measuring blood glucose, an adequate volume of the extract/distilled water/acarbose was administered (t0) to begin the oral starch tolerance test. A second measurement of glycemia was taken 30 min later (t1), and the rats were then overloaded with starch (3 g/kg). The variation in glycemia was measured at t2 = 60 min, t3 = 90, and t4 = 120 min. ## 3.13. Statistical Analysis The results were statistically analyzed using ANOVA (one-way analysis of variance with Tukey’s post hoc test), and they are shown as means and standard deviation. Statistics were considered to be significant at p-values of $p \leq 0.05$, $p \leq 0.01$, and $p \leq 0.00.$ ## 4. Conclusions Aromatic and medicinal plants are a precious gift of nature for human beings; they have been used since antiquity in food, beverages, traditional medicine, and cosmetics. Salvia lavandulifolia Vahl is a widespread plant in Morocco; its leaves are often used for their high content of essential oil whose virtues are well known. The extracts, on the other hand, are very little studied by researchers, and their properties are found most of the time in articles—ethnopharmacological surveys or some very old ones. The aqueous extract of the leaves of S. lavandulifolia harvested in Ouled Ali-Boulemane-Morocco is very rich in polyphenols; it recorded a remarkable total antioxidant capacity and antiradical power. It is also considered bactericidal against Proteus mirabilis, fungicidal against Aspergillus niger, Candida albicans, Candida tropicalis, and Saccharomyces cerevisiae, and fungistatic against Candida krusei. Administered 30 min before an acute oral administration of glucose, our extract significantly lowered hyperglycemia in vivo in rats. Thanks to its content of rosmarinic acid, apigenin, and luteolin, it essentially could also inhibit the activity of the enzyme α-amylase in vitro and in vivo. ## References 1. Hassan I.-M., Shehu A., Zezi A.U., Magaji M.G., Yaâ J.. Ethnobotanical Survey of Medicinal Plants Commonly Used in Snakebites in North Western Nigeria. J. Med. Plants Res. (2020.0) 14 468-474 2. Fitzgerald M., Heinrich M., Booker A.. 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--- title: 'Assessment of Serum 25-Hydroxyvitamin D and Its Association in Type 2 Diabetes Mellitus Elderly Patients with Kidney Disease: A Retrospective Cross Sectional Study' authors: - Moyad Shahwan - Nageeb Hassan - Noor Mazin - Ammar Jairoun - Sahab Al Khoja - Monzer Shahwan - Osama Najjar - Tariq Al-Qirim journal: Metabolites year: 2023 pmcid: PMC10051622 doi: 10.3390/metabo13030357 license: CC BY 4.0 --- # Assessment of Serum 25-Hydroxyvitamin D and Its Association in Type 2 Diabetes Mellitus Elderly Patients with Kidney Disease: A Retrospective Cross Sectional Study ## Abstract The overall aim of this study is to determine the prevalence of vitamin D deficiency and its association with diabetic nephropathy in elderly patients with type 2 diabetes mellitus. This study is a single center retrospective cross-sectional design conducted at private medical center. The study group included all patients (18 years or older) suffering from type 2 diabetes mellitus that attended the diabetic clinic from September 2019 to January 2021. The main outcome variable is a trough level of (<20 ng/mL) for 25OHD. The patients were categorized as having diabetic nephropathy based on estimated glomerular filtration rate (eGFR). Total glycated hemoglobin (HbA1c), creatinine serum, Alb: Cr ratio, total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), systolic blood pressure (SBP) and diastolic blood pressure (DBP) were compared between vitamin D deficiency groups. Univariate and multivariate logistic regression was used to investigate the association between vitamin D deficiency and other significant anthropometric and biochemical factors. A p value < 0.05 was chosen as the criterion to make decisions regarding statistical significance. Among the 453 diabetic patients included in study, $48.6\%$ ($$n = 220$$) were male and $51.4\%$ ($$n = 233$$) were female. The mean age ± S.D of the patients was 54.5 ± 10.6 years old. Out of 453 diabetic patients, $71.1\%$ ($95\%$ CI: $66.9\%$–$75.3\%$) had vitamin D deficiency (25OHD < 20 ng/mL). There was a statistically significant association between 25OHD level and diabetic nephropathy in elderly patients with type 2 diabetes mellitus. Diabetic patients with e-GFR < 60 mL/min more likely to have vitamin D deficiency ($p \leq 0.001$). Similarly, individuals with Alb: Cr ratio > 30 mg/g were more likely to have vitamin D deficiency ($p \leq 0.001$). Moreover, diabetic patients with serum creatinine > 1.8 mg/dL were more likely to have vitamin D deficiency ($p \leq 0.001$). The study revealed a high prevalence of vitamin D deficiency in elderly patients with type 2 diabetes mellitus. A significant association was reported between 25-hydroxyvitamin D, e-GFR and Alb: Cr ratio. ## 1. Introduction Vitamin D deficiency (VDD) is a growing global public health problem. Various investigators have examined different cutoffs for vitamin D status, but the majority define VDD as serum 25(OH)D levels < 20 ng/mL and serum 25(OH)D levels between 20 and 20 ng/mL. We defined a deficit as 20 ng/mL. Around 1 billion people are affected worldwide, which is $15\%$ of the world’s population. Vitamin D plays a key role in many important homeostatic processes, including bone metabolism, cell proliferation, neuromuscular and immune function, and inflammation. As a result, low serum vitamin D levels predispose people to a variety of health complications, including multiple sclerosis, autoimmune diseases, infectious diseases, respiratory disease, cardiometabolic disease, and cancer [1]. However, epidemiological findings regarding the association of VDD with numerous clinical manifestations, particularly type 2 diabetes mellitus (T2DM), remain conflicting. Several longitudinal observational studies and their systematic reviews and meta-analyses support the assumption that VDD may increase the risk of type 2 diabetes and associated complications [2,3]. Diabetes is considered one of the growing epidemics worldwide; its prevalence has increased over and over, and it is expected to become the main cause of morbidity and mortality [4]. This high rate of morbidity and mortality is due to macrovascular and microvascular complications [5]. Diabetic kidney disease (DKD) is the most common microvascular complications in type 2 diabetic patients [6]. Approximately $40\%$ of diabetic patients are at end stage renal disease [7]. Most of these patients have vitamin D deficiency [8]. DKD is characterized by hypertrophy of the glomerular and tubular epithelium, basement membrane thickening, and extracellular matrix deposition, ultimately leading to glomerulosclerosis and tubulointerstitial fibrosis. The major clinical indications of DKD are progressive proteinuria and declining renal function. Risk factors for DKD include genetic polymorphisms, prolonged hyperglycemia, obesity, hypertension, and dyslipidemia. Pathophysiological changes in DKD are likely due to metabolic and hemodynamic abnormalities. However, the exact underlying mechanisms are complex and may involve multiple pathways. Studies have shown that when the intrarenal renin-angiotensin system ‘RAS’ is activated, it plays an important role in causing progressive renal damage in DKD [9]. Taking medications and implementing lifestyle changes such as weight loss, dietary modifications, smoking cessation and exercise will improve patients’ glycemic control, and hence will minimize diabetes complications [10]. In addition, supplementation with vitamin D will improve glycemic control in patients with diabetes type 2 [11]. Vitamin D receptors exist in the B-cell of the pancreas [12]; vitamin D is then hydroxylated in the liver into 25-hydroxyvitamin D (25(OH)D), and in the kidney into 1,25-dihydroxyvitamin D (1,25(OH)2D), and these metabolites will bind with the vitamin D receptors in the pancreas [13,14]. Vitamin D plays an important role in diabetes and its complications, it has been shown in some studies that vitamin D supplementation could decrease the occurrence of diabetes [15]. A low level of vitamin D l is a risk factor for glucose metabolism distraction and diabetes type 2 [16]. Mainly, vitamin D deficiency is due to low exposure to sunlight, skin color, and a low nutritional supply of food containing vitamin D [17]. An experimental study shows that diminished glucose-facilitated insulin secretion in the situation of vitamin D deficiency could be treated and minimized by taking vitamin D supplementation [18]. There are different assumptions regarding the role of vitamin D in diabetes. One study showed that vitamin D protects β-cells from death [19]; another one showed vitamin D may affect the growth and differentiation of β-cells [20]. The fact is that vitamin D is a main regulator of the metabolism of calcium, hence it is important to supply an adequate concentration of calcium for bone mineralization. Therefore, vitamin D is important for the metabolism of glucose, since calcium is critical for insulin secretion and synthesis [21]. Other study shows the effect of CKD on vitamin D levels. CKD patients are at increased risk of vitamin D deficiency for several reasons. The main reasons are as follows: loss of vitamin D binding protein (DBP), the major carrier protein for 25(OH)D, due to proteinuria in the nephrotic region associated with type 2 diabetes and certain types of glomerulonephritis. Patients should strictly limit foods containing vitamin D to avoid excessive phosphorus intake. They should have less sun exposure and, most importantly, significantly reduced expression of the endocytic receptor megalin in their renal proximal tubules. Renal megalin depletion occurs in the very early stages of CKD, and this condition is associated with decreased reabsorption of glomerular-filtered albumin and other low-molecular-weight proteins [22]. Diminishing vitamin D metabolism may be a new therapeutic goal to minimize the progression and development of DKD [23]. A study has shown that 25(OH) D concentration is lower in patients with diabetes and kidney disease compared to those patients without these two conditions [24]. Kidney disease affects vitamin D metabolism, hence monitoring of the vitamin D concentration in diabetic patients with nephropathy is important [25]. There is an inverse relation between concentration of vitamin D and albuminuria [26]. Several studies have found an opposite relationship between serum 25(OH) D concentration and the glycated haemoglobin (HbA1c) concentration in type 2 diabetic patients; this shows the need for the regular screening of vitamin D level among diabetic patients, to treat the depletion from the beginning in order to achieve better glycemic control and prevent development of complications from diabetes type 2 [27]. A cross-sectional study found that type 2 diabetic patients with kidney disease and vitamin D deficiency are have a significantly higher risk of developing cardiovascular disease compared with those with normal vitamin D levels [28]. Another study has the same result; it showed that low levels of vitamin D will increase the risk of cardiovascular disease as well as all-cause mortality and cardiovascular disease [29,30]. There are numerous studies showing the relationship between vitamin D and diabetes types; only a few have studied the relationship between these two and kidney diseases. Hence, in this study, we will focus on the relationship between vitamin D and kidney disease in type 2 diabetic patients. Our aim in this study is to investigate the relationship between serum 25OHD and kidney disease in type 2 diabetic patients ## 2.1. Subjects, Materials, and Methods This study is a retrospective cross-sectional design conducted at private medical center. The study group included all patients (18 years or older) suffering from type 2 diabetes mellitus attended the diabetic clinic from September 2019 to January 2021. The participants were outpatients, consecutively recruited by specialist diabetes physician at regular follow up visits. It comprised a systematic sample of 453 type 2 diabetic patients, of which 220 and 233 were males and females, respectively. Patients’ confidentiality was respected; all patients were reviewed anonymously, and data was gathered using their identification numbers and coding. Furthermore, the data processing and data entry were handled only by the principal investigator, so there were no complications of harm to the patients. Relevant sociodemographic and clinical and laboratory data were obtained from the medical records of the patients, including age, gender, height, weight, body mass index (BMI), total glycated hemoglobin (HbA1c), fasting blood glucose (FBS), medications history, c-reactive protein (CRP), creatinine, estimated glomerular filtration rate (eGFR), erythrocyte sedimentation rate (ESR), etc. ## 2.2. Data Collection Tool The collection sheet used as a tool in this study included the following variables: age, gender, marital status, weight, height, educational level, smoking status, physical activity, BMI and blood pressure Laboratory tests include total glycated haemoglobin (Hba1c), creatinine, glomerular filtration rate (GFR), ESR, CRP, blood urea nitrogen (BUN), creatinine urine, albumin/creatinine ratio, ALT, AST, total cholesterol, triglyceride, high density lipoprotein, low density lipoprotein, vitamin D, vitamin B12, calcium, albumin, potassium, and sodium. Medication history was collected, including past and current medication in addition to the past and present co-morbidities for all the study participants. ## 2.3. Sample Size Calculation The assumed prevalence of vitamin D deficiency among type 2 diabetes patients was $66\%$. An alpha level of $5\%$ was selected for this study, meaning a $95\%$ confidence interval (CI). With the precision (D) of $5\%$, $10\%$ was taken to be the maximum width of the $95\%$ CI. Thus, 435 patients were considered to be a sufficient sample size for the final study, assuming missing patients data at baseline of $24\%$. ## 2.4. Inclusion Criteria Male and female patients with type 2 diabetes and with chronic renal disease, age 18 or above were included in the article, irrespective of their vitamin D levels Laboratory tests for inflammatory markers such as CRP and ESR, as well as renal function tests such as glomerular filtration rate, albumin, creatinine, and BUN were performed on patients. ## 2.5. Exclusion Criteria Male and female patients with type 1 diabetes, patients without renal disease, patients aged 17 or under, pregnant females and children were excluded. In addition, the study excluded patients with renal disease unrelated to diabetes. ## 2.6. Statistical Analysis The data were analyzed using the SPSS version 26. Frequencies and percentages were used to summarize the qualitative variables. Graphical representations were provided for all relevant variables. Evaluation of the distribution and normality of the data was carried out using a Shapiro–Wilk test (with $p \leq 0.05$ indicating a normally distributed continuous variable) or by visual inspection of a normal Q-Q Plot. Chi-square and Fisher’s exact tests were used to compare the difference between categorical variables. Univariate and multivariate logistic regression was used to investigate the association between the vitamin D deficiency and other significant anthropometric and biochemical factors. A backward and forward stepwise procedure was applied to the multivariate logistic regression model. A p value < 0.05 was chosen as the criteria to make decisions regarding statistical significance. ## 2.7. Ethical Approval This study was approved by the Health and Ethics Review Committee of the participating healthcare center. All respondents gave their informed consent in accordance with the Declaration of Helsinki. ## 3.1. Anthropometric and Biochemical Characteristics of the Subjects (n = 453) Table 1 presents the anthropometric and biochemical characteristics of the study participants. Among the 453 diabetic patients included in study, $48.6\%$ ($$n = 220$$) were male and $51.4\%$ ($$n = 233$$) were female. The mean age ± S.D of the patients was 54.5 ± 10.6 years old. The mean ± S.D of HbA1c, creatinine, Alb: Cr ratio, e-GFR, TC, TG, HDL-C, LDL-C, SBP and DBP were 7.8 ± 1.3 (%), 0.84 ± 0.53 (mg/dL), 130.1 ± 14.61 (mg/g), 255.6 ± 21.3 (mg/dL), 180.1 ± 25.3 (mg/dL), 184.3 ± 25.4 (mg/dL), 41.4 ± 11.4 (mg/dL), 99.8 ± 41.5 (mg/dL), 129.4 ± 14.3 (mmHg), 80.8 ± 8 (mmHg), respectively. ## 3.2. Association between Vitamin D Deficiency and Renal Biochemical Markers (n = 453) Out of 453 diabetic patients, $71.1\%$ ($95\%$ CI: $66.9\%$–$75.3\%$) had vitamin D deficiency (25OHD < 20 ng/mL). Prevalence of different types of diabetic nephropathy stratified by patients’ vitamin D levels are shown in Table 2. Patients were divided into two groups, as per 25-hydroxyvitamin D; the first group consisted of patients with 25OHD < 20 ng/mL, and the second group consisted of patients with 25OHD ≥ 20 ng/mL. There was a statistically significant association between 25OHD level and diabetic nephropathy in patients with type 2 diabetes mellitus. Diabetic patients with e-GFR < 60 mL/min more likely to have vitamin D deficiency ($p \leq 0.001$). Similarly, individuals with an Alb: Cr ratio >30 mg/g were more likely to have vitamin D deficiency ($p \leq 0.001$). Moreover, diabetic patients with serum creatinine > 1.8 mg/dL were more likely to have vitamin D deficiency ($p \leq 0.001$). ## 3.3. Evaluation of Risk Factors Associated with Vitamin D Deficiency in Type 2 Diabetes Mellitus Table 3 displays the results of logistic regression analysis of the anthropometric parameters and biochemical markers that are associated with the vitamin D deficiency. From the univariate analysis, gender (OR = 1.23, CI = 1.14–3.75, p-value = 0.031), age (OR = 1.45, CI = 1.11–2.03, p-value = 0.004), HbA1c (OR = 1.78, CI = 1.13–1.98, p-value = 0.001), serum creatinine (OR = 1.68, CI = 1.19–4.52, p-value = 0.017), e-GFR (OR = 0.26, CI = 0.154–0.44, p-value < 0.001), Alb: Cr ratio (OR = 0.96, CI = 0.93–0.97, p-value < 0.001), total cholesterol (OR = 1.49, CI = 1.01–1.77, p-value = 0.009), triglycerides (OR = 1.61, CI = 1.11–1.99, p-value = 0.042), LDL cholesterol (OR = 1.24, CI = 1.09–1.74, p-value = 0.004) and diastolic blood pressure (OR = 11.120, CI = 1.069–1.173, p-value = 0.027) are strong determents of vitamin D deficiency. To select the set of factors that jointly influence vitamin D deficiency, we used the backward and forward stepwise procedure applied to the multivariate logistic regression model. The results of this procedure showed that HbA1c, e-GFR and mean Alb: Cr ratio are jointly highly associated with vitamin D deficiency. If the HbA1c increases by $1\%$, then the odds of having 25OHD < 20 ng/mL increase by $71\%$. If the e-GFR increases by 1 mL/min, then the odds of having 25OHD < 20 ng/mL decrease by $70\%$. If the Alb: Cr Ratio increases by 1 mg/g, then the odds of having 25OHD < 20 ng/mL decrease by $6\%$ (Table 3). ## 4. Discussion The current study specifically targeted T2DM with serum 25(OH)D levels and CKD. The main finding of this study was that lower serum 25(OH)D levels were significantly associated with an increased risk of CKD progression in type 2 diabetic patients. According to recent studies, there is a high prevalence of 25(OH)D deficiency around the world due to aging, diet, low physical activity and sun exposure, among other factors [31,32,33]. The present retrospective article aims to study the relation between the 25OHD and diabetic nephropathy in elder people with type 2 diabetes mellitus. Patients with kidney failure demonstrated a considerable association with the measured levels of 25OHD levels, as the patients with low eGFR had higher chances of developing vitamin D deficiency. The same results matched the results in Sung Gil Kim’s article, as it was found that the likelihood of having a vitamin D deficiency along with decreased eGFR is high [34]. Moreover, Jong Park had stated in his study that the levels of the estimated GFR decrease significantly when the levels of 25OH D levels are increased [35]. This relationship is generally shown by the fact that a glomerular filtration rate decrease results in a decreased amount of 1-α-hydroxylase substrate delivery. The later action limits the capability of the kidney to form 1,25-dihydroxyvitamin D [36]. Experimental results demonstrate that vitamin D is an effective inhibitor of the of the renin-angiotensin system (RAS) and nuclear factor (NF)-kB pathway, and in human trials, low levels of vitamin D have been autonomously linked to higher plasma renin and angiotensin 2 concentrations. These pathways play a significant role in the disease processes of kidney disease through mediating the immune, inflammatory, and proliferative effects that result in progressive renal damage. A 25(OH)D deficiency may accelerate the progression of albuminuria, which is by itself a recognized indicator of CKD progression and adverse cardiovascular outcomes, as well as the decline in renal function [37,38,39]. Age-related decreases in the functioning of kidneys have been shown to be associated with a decrease in the synthesis, metabolism, and transportation of 1,25 dihydroxyvitamin D. Patients with ESRD have a higher prevalence of vitamin D deficiency [9,40,41]. The current study revealed a high prevalence of vitamin D deficiency in elderly patients with type 2 diabetes mellitus. A significant association was reported between 25(OH)D, e-GFR and the Alb: Cr ratio. A study by Shaofeng et al. analyzed the relationship between albuminuria 25(OH)D, and concluded in their results that a low level of vitamin D is a major indicator of incident nephropathy in type 2 diabetic patients, and the prevalence of vitamin D deficiency in patients with albuminuria was greater than the patients without it [42]. Moreover, the odds ratio between the vitamin D levels and the Alb: Cr ratio were inversely related. Individuals with high levels of albumin excretion in urine had reduced recorded vitamin D levels. It has been found that after a 6 months’ therapy with vitamin D to diabetic nephropathy patients, the urine albumin, renin and serum creatinine levels were reduced, leading to a noticeable improvement of GFR for these patients. There are signs to researched further that high vitamin D treatments can be reno-protective [43]. Alborzi et al. ’s double-blind randomized clinical trial revealed that a half amount of albuminuria was reduced by the paricalcitol treatment for a solid month. At the end of the time for which the trial took place, the paricalcitol groups treated with 1 μg and 2 μg had 0.52 and 0.54 levels of albumin compared to the baseline levels at the beginning of the study, whereas the placebo groups showed an increase by 1.35 times compared to the same baseline. Nevertheless, the small sample size (consisting of eight sample sizes in each group) is the major drawback of this study [44]. Another trial, which included the administration of calcitriol using 0.5 μg two times a week for a length of 12 consecutive years, in 10 patients resulted in a major reduction of the urine albumin to creatinine ratio, proved by IgA nephropathy. However, the small sample size and the absence of placebo are the drawbacks of this trial [45]. Mao et al. showed in their prospective study that the additional supply of calcitriol resulted in reduction of the protein in the diabetic patients. This study was performed on patients with vitamin D deficiency and insufficiency [46]. On the other hand, Alexander Teumer et al. have found that circulating levels of vitamin D negatively relate to eGFR levels. However, the small sample size and exclusion of meta-analysis studies were the major drawbacks of this study. Further studies are needed to establish the underlying relation [47]. As expected, our article showed that diabetic patients are more likely to have vitamin D deficiency when their serum creatinine levels > 1.8 mg/dL. Regarding our study, certain factors were found to be associated with vitamin D deficiency. HbA1c, e-GFR and mean Alb: Cr ratio are together linked to vitamin D deficiency. On the other hand, in the study by Tricia L Larose [48], the resulting factors were found to be winter season, BMI and dietary intake, in order. The winter season was the most related factor in many other studies too [49,50]. However, another report showed that vitamin D deficiency is prevalent in countries with lots of sunshine such as Saudi Arabia. Younger women were associated with vitamin D hypovitaminosis to a larger degree than older women, which was explained by the increased quantity of supplemental vitamin D intake by the older women [50]. One of the limitations that may restrict the generalizability of the findings is that the research was performed in only one geographic area, so no long-term conclusions can be drawn, and the results may not extend to other regions. Results may differ for other countries due to the presence of factors that could affect vitamin D levels, hence additional investigations should be carried out for other countries. Secondly, this study was a cross-sectional study design. Thirdly, levels of serum insulin were not measured for the candidates. Fourth, serum glucose/insulin levels were not determined for type 2 patients, but these may affect the result of vitamin D levels in another patients. ## 5. Conclusions This study revealed a high prevalence of vitamin D deficiency in elderly patients with type 2 diabetes mellitus. A significant association was reported between 25-hydroxyvitamin D, e-GFR and Alb: Cr ratio. Therefore, regular checkups for vitamin D levels in elderly patients are necessary to maintain glycemic control and prevent development of complications, especially CKD. Further studies are needed to clarify the relationship between vitamin D and renal biochemical markers (glomerular filtration rate, albumin, creatinine, and BUN), and to illuminate the scientific support for prevention and treatment of CKD. In future works, to further investigate the utility of screening 25-hydroxyvitamin D, it would be useful to know if regular check-ups of 25-hydroxyvitamin D and long-term maintenance of an optimal 25 hydroxyvitamin D level could be helpful to achieve better glycemic control and prevent development of diabetes type 2 complications, especially kidney diseases. ## References 1. Marcus H., Varma M., Sekhar S.. Association of serum vitamin D status with development of type 2 diabetes: A retrospective cross-sectional study. Clin. Nutr. Open Sci. (2021) 36 1-3. 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--- title: A Diet Profiling Algorithm (DPA) to Rank Diet Quality Suitable to Implement in Digital Tools—A Test Study in a Cohort of Lactating Women authors: - Marta Alonso-Bernáldez - Andreu Palou-March - Rocío Zamanillo-Campos - Andreu Palou - Mariona Palou - Francisca Serra journal: Nutrients year: 2023 pmcid: PMC10051632 doi: 10.3390/nu15061337 license: CC BY 4.0 --- # A Diet Profiling Algorithm (DPA) to Rank Diet Quality Suitable to Implement in Digital Tools—A Test Study in a Cohort of Lactating Women ## Abstract Although nutrient profiling systems can empower consumers towards healthier food choices, there is still a need to assess diet quality to obtain an overall perspective. The purpose of this study was to develop a diet profiling algorithm (DPA) to evaluate nutritional diet quality, which gives a final score from 1 to 3 with an associated color (green-yellow-orange). It ranks the total carbohydrate/total fiber ratio, and energy from saturated fats and sodium as potentially negative inputs, while fiber and protein are assumed as positive items. Then, the total fat/total carbohydrate ratio is calculated to evaluate the macronutrient distribution, as well as a food group analysis. To test the DPA performance, diets of a lactating women cohort were analyzed, and a correlation analysis between DPA and breast milk leptin levels was performed. Diets classified as low quality showed a higher intake of negative inputs, along with higher energy and fat intakes. This was reflected in body mass index (BMI) and food groups, indicating that women with the worst scores tended to choose tastier and less satiating foods. In conclusion, the DPA was developed and tested in a sample population. This tool can be easily implemented in digital nutrition platforms, contributing to real-time dietary follow-up of patients and progress monitoring, leading to further dietary adjustment. ## 1. Introduction Unhealthy dietary patterns based on energy-dense and/or low-nutrient foods are one of the most modifiable risk factors directly associated with morbidity and mortality of noncommunicable diseases (NCD). Recent data show that 11 million deaths worldwide were attributable to dietary risk factors in 2017 alone [1]. Furthermore, the overall obesity prevalence has increased over the years reaching $41.5\%$, a trend that is expected to keep rising [2]. This staggering figure prompts an urgent need to identify new strategies aiming to change and improve dietary habits worldwide. Concerning global approaches, different ways to assess nutritional profiling are being developed to identify the healthfulness of foods and to help consumers make more informed food choices when grocery shopping [3,4]. The Ofcom model developed by the UK Food Standards Agency [5] was one of the first approaches in this regard, leading the way in the development of new applications, such as food labeling. This application of nutrition profiling is an effective strategy to reduce the intake of unhealthy nutrients [6]. In particular, it has been shown that front-of-package (FoP) food labels can help consumers from all ages make healthier choices [7,8,9] and are already being implemented in different types and forms across the world [10,11,12]. Nutri-Score is a FoP labeling system, developed and implemented by the French government [13], made up of colors and letters that make the classification of pre-packed products very visual and easy to understand in terms of healthfulness [14]. This strategy has been compared with other nutrient-profiling systems and validated by different studies, showing its effectiveness in terms of improving diet quality [4,10,15,16,17,18] and increasing unprocessed foods’ purchases [19]. However, the Nutri-Score algorithm is still an open concept and its refinement has been suggested to better align its outcome with dietary guidelines [20,21,22]. Overall, it is clear that nutrient-profiling systems can help consumers to make healthier choices, but the ranking of individual food products does not guarantee adherence to a healthy and balanced diet. Therefore, an approach focused on ranking the overall diet rather than individual products would be more suitable and comprehensive for this purpose [23]. Thus, the aim of this study was to develop a dietary profiling system/tool by defining an algorithm able to assess the nutritional quality of the diet and suitable for implementation in nutrition-related apps. This would allow us to take advantage of the fast and easily interpretable requirements of digital media, without losing the accuracy of more classical nutritional approaches, while giving support in a user-friendly manner. ## 2.1. Development of the Diet Profiling Algorithm Development of the diet profiling algorithm (DPA) was initially based on the main concepts and structure of the Nutri-Score [13]. In order to adapt this profiling system from individual food products to overall diets, the modification of specific parameters of the algorithm were implemented. A score from 0 to 5 was assigned to each nutrient, ratio, or parameter considered, and the cut-offs for score assignation were mainly based on the European Food Safety Authority (EFSA) and World Health Organization (WHO) guidelines [24,25]. Two categories of nutrients were defined based on the accumulated evidence of their impact on health, which are described in the following sections. In addition, an estimation of balanced macronutrient distribution was introduced (see Section 2.1.4), as well as certain guides aiming to go into deeper personalized advice (Figure 1). ## 2.1.1. Unhealthy Nutrients Assessment Total carbohydrate/total fiber ratio (CH/Fb), saturated fatty acids (SFA, % energy), and sodium (mg) were the three factors considered in this category as their excess intake may lead to unhealthy events [3] (Figure 1, Point 1A). Firstly, the CH/Fb ratio can help to determine how much of the total dietary intake of carbohydrates may be accompanied by a healthy food matrix, contributing to a better assessment of nutrient density [20,26]. The CH/Fb ratio gives a good proxy to distinguish between free or added sugars (e.g., from sugary beverages) and sugars naturally present in foods (e.g., from fruit). Intakes equal to or greater than 1 g of fiber per 10 g of carbohydrate can be considered as a healthy ratio (10:1) [27,28]. In the DPA, CH/Fb ratio cut-offs ranged from ≤10 to >18 (the best and worst score in this category, respectively) and was ranked from 0 to 5 points. Concerning fat, we focused on the % of total energy coming from SFA. Since the EFSA recommends its intake to be as low as possible [24], and in accordance with the WHO [25], the threshold of $10\%$ was selected as the most adequate. Consequently, cut-offs ranged from ≤10 to >$18\%$ and were ranked as described above from 0 to 5 points. To evaluate influence of sodium intake, the EFSA recommendation of ≤2000 mg of sodium per day for adults was adopted [29]. Thus, the best score was attributed to ≤2000 mg of sodium intake, whereas >3200 mg of sodium was assigned to the highest score. See Figure 1 for the intermediate range values. ## 2.1.2. Healthy Nutrients Assessment In this category, protein and fiber were considered as beneficial nutrients to rate the DPA (Figure 1, Point 1B). To assess protein intake, the intake ratio of protein/body weight (P/Bw) was used. The EFSA has established 0.83 g/Kg bw/day of protein for adults as the population reference intake (PRI) that will meet the requirements of $97.5\%$ of the individuals [30]. Hence, a ratio of 0.83 was established as the best and ranked with a 5 (the best score in this category). Higher ratios were ranked with lower scores, with >1.8 as the highest cut-off. In addition, to contemplate protein deficit, the average intake (AI) set by the EFSA [30] was used as a specific cut-off. Then, daily intakes <0.6 g/Kg bw were qualified with 0, whereas intermediate intakes (0.6–0.829) were ranked with 2. Fiber intake was considered following the EFSA guidelines of ≥25 g of total fiber as a daily adequate amount for the correct function of the organism [31]. Therefore, values of >25 g/day of fiber obtained the highest score and values of ≤5 g/day the lowest. ## 2.1.3. Attribution of DPA Scores and Color Code Points obtained from the assessment of the three unhealthy parameters were added (A value) and the same was done within the healthy category (B value) (Figure 1, Point 2). If the unhealthy points are lower than 7, the final score (FS) of the diet is Points A minus Points B. On the contrary, a score of ≥7 in Points A may be indicative of a high presence of unhealthy nutrients; thus, protein will not count as a positive item to avoid bonification for unhealthy food sources. In this case, the FS will result in only Points A—fiber points. This FS is then converted into a DPA score, which goes from 1 to 3 (from best to worst diet quality) (Figure 1, Point 3). If the FS ≤ 3: DPA = 1; from 4 to 7: DPA = 2; and if FS ≥ 8: DPA = 3. Each DPA score is attributed either to green, yellow, or orange, respectively. The final representation of diet assessment is intended to be integrated into a digital platform and, for example, to be able to be displayed to the user in a very intuitive manner within an app. A proposal would be coding the DPA score with graphic symbols, making use of pictorial codes, for instance, such as a colored plate. Plates of intuitive colors would be able to efficiently represent DPA scores (Figure 1, Point 4). ## 2.1.4. Balanced Macronutrient Distribution Parameter (BMDP) Aiming to introduce a parameter to evaluate the distribution of macronutrients in the diet, the ratio of total fat and total carbohydrate (F/CH) was defined, referred to the percentage of total energy provided by each of these nutrients (Figure 1, Point 5). The EFSA has established 20–$35\%$ and 45–$60\%$ of total energy intake coming from fats and carbohydrates, respectively, as part of adequate daily intakes [24]. Thus, an F/CH ratio between 0.33 and 0.77 was classified as suitable. These cut-offs would correspond to what an acceptable macronutrient distribution in a high-carbohydrate or high-fat diet would be, respectively. Diets with an F/CH ratio of <0.33 or >0.77 were classified as “U” (meaning unbalanced), while diets with an F/CH ratio between 0.33 and 0.77 were classified as “B” (standing for balanced). The information obtained from the BMDP is used as an additional informative factor, promoting more personalized advice. This can be implemented in the graphical coding, emphasizing the attribution of colors for instance. ## 2.2. Food Group DPA Assessment Dietary data from food groups allow for the analysis of food group consumption and its comparison with a reference. The software DIAL v3.0 (Alce Ingeniería, Madrid, Spain) was used for this purpose. The software intrinsically divides food into the food groups stipulated by the EFSA [3] plus three more, resulting in: cereals; fats and oils; milk and dairy products; sugars, sweets and pastries; beverages; meat and meat products; fruits and nuts; eggs; fish; legumes; vegetables; and miscellaneous. Beverages included every drink different from water and milk. Miscellaneous included agglutinated precooked products, appetizers, sauces, and dietetic products. To establish a food group pattern as reference, meals contained in three daily menus proposed by the Mediterranean Diet Foundation [32] were selected and analyzed with DIAL. The contribution of each food group to total energy intake was obtained for every menu and their average was set as the reference amount of total energy coming from the above-cited food groups. As expected, the three menus were ranked as green plates by the DPA. In summary, the DPA uses dietary information as the input to start the assessment, quantifies and qualifies the diet, and then reaches a final verdict whether the diet can be considered healthy or not. This is used to generate the nutritional guidance for each specific user. In case of an affirmative answer, the DPA proceeds to calculate the BMDP and analyze the food groups to assess whether an optimal diet is being followed or whether there is room for improvement. In any case, personalized advice adjusted to the consumer wishes and preferences can be delivered. If the answer is negative, then the DPA proceeds to give advice focused on improving the dietary habits. Thus, feeding the DPA with dietary data (see below) allows the running of the algorithm and its use as a tool for nutritional guidance and education. whether is in nutritional consultation or in a nutrition-related app (Figure 2). ## 2.3. DPA Implementation and Related Output The DPA has been designed to be used on digital platforms that record users’ food intake on a daily basis (i.e., with food pictures and post-image recognition technology or other methods). The information on recipes, dishes, and respective amounts would be then converted to nutritional data by the software of that specific platform. Then, this would go into the DPA to perform the diet assessment, give appropriate dietary advice, and suggest more appropriate menus/dishes (Figure 3). To facilitate follow-up by average users, three output levels are proposed. The orange (DPA = 3) diet would be characterized by very poor diet quality, generally due to prioritizing unhealthy foods rather than nutrient-rich foods. Since diet quality would be so low, the balanced macronutrient distribution parameter would not be calculated, nor the food groups. The immediate advice would be to improve dietary habits by highlighting the parameters that are contributing to this bad score (e.g., explaining to the user the weak aspects of their current diet (i.e., excess salt, low fiber, etc.). Then, high-quality menus representative of healthy diet(s) would be suggested by the app, encouraging diet changes by focusing on good food elections aiming to upgrade the DPA score (Figure 3A,B). In the case of a yellow (DPA = 2) score, the quality of the reported diet would be sub-optimal, and some specific aspects could be improved. Then, to give more personalized advice, two other parameters would be analyzed: the BMDP and the food groups. Hence, as a second step, the BMDP would be calculated and incorporated in the graphical display. In case of a “U”, an alert to watch macronutrient distribution would be made and specific advice would focus on modifying the current diet to a better fit, in contrast with the more drastic change that arises from DPA = 3. As a third step, food group analysis is performed and graphically displayed. The output would focus on recipes/tips involving food groups to be recommended by the app to better suit the food group pattern of reference (Figure 3C,D). If a green (DPA = 1) classification is obtained, the quality of the diet would be close to optimal. Then, BMDP, as well as the food groups, would be calculated. Ideal users would get a “B” BMDP and fitted food groups. No major changes to their diet would be necessary. Therefore, the app would propose healthy menus similar to the ones they eat and like, and it would follow-up any deviations from this set point. If macronutrients are correctly distributed (indicated by obtaining a “B” in the BMDP assessment), but the food groups do not fit with the set reference, then the advice would be to prioritize recipes containing a more balanced food group distribution, for example, by keeping macronutrient distribution while promoting higher legume intake as opposed to meat products, for instance. However, if a green score is obtained with unsatisfactory macronutrient distribution (“U” in the BMDP), a change in the dietary pattern would be promoted towards balancing the macronutrient distribution at the same time as the food groups fit the reference. ## 2.4.1. Population Characteristics and Diet Evaluation The DPA has been designed to empower consumers to make healthier choices, so it could be tested in any group of the general population. In the present study, the DPA performance was initially tested using previously collected data from a cohort of lactating women, which was part of an obesity-related research in our lab. The recorded diets of 59 lactating women were submitted to screening. The cohort was recruited within the observational Nutrigen-11 study carried out between 2011 and 2014 in three health centers in Mallorca (Spain) (agreement approval IB $\frac{1645}{11}$). Adult women without any infectious illness and wishing to participate were considered for inclusion in this study. Women were recruited after delivery when they attended the midwife consultation. Then, personal interviews were scheduled at months 1, 2, and 3 of lactation in which anthropometric measurements and the diet were recorded. In addition, a breast milk sample was collected at these time points when possible. Concerning dietary intake, three 24 h dietary recalls (24 h), one per month, were recorded on paper and transferred to the computer. Energy, nutrient composition, and food groups were obtained by using the aforementioned dietary software DIAL. This software applies Atwater factors to estimate energy intake (9 kcal/g for fat, 4 kcal/g for protein and carbohydrate, 2 kcal/g for fiber, and 7 kcal/g for alcohol). The mean values of this nutritional information were introduced as input to the DPA to obtain the diet score of each participant. To contemplate the 19 g extra protein requirement stipulated by the EFSA recommendations in the first months of lactation [24], the protein intake of each woman was adjusted by subtracting this quantity from the total protein amount consumed. The resulting grams were used for the DPA score’s calculation as if it were a normal adult population. ## 2.4.2. Determination of Leptin in Milk as Biomarker Breast milk leptin is an interesting biomarker to study the influence of the maternal diet on milk composition as it influences metabolic imprinting, childhood development, and future health status [33]. Leptin concentration was determined as previously described [34]. ## 2.4.3. Statistical Analysis The SPSS v21 for Windows (SPSS, Chicago, IL, USA) software was used for data analysis. To assess differences between DPA ranked scores, one-way analysis of variance (one-way ANOVA) followed by the least significance difference (LSD) post hoc test was used. If homogeneity of variances was violated, variables were logarithmically transformed. Single comparisons between DPA scores were assessed by Student’s t-test. Moreover, to determine the association between breast milk leptin and body mass index (BMI) for the different DPA scores, Spearman’s rank correlation measures were performed. Data are presented as the mean ± standard error of the mean (±SEM). The threshold of significance was set at p-value ≤ 0.05. ## 3.1. Diet Characterization and DPA Scores of the Population The mean (±SEM) population age was 32 ± 0.45 years old, with an average BMI of 24.1 ± 0.58 kg/m2. However, $36\%$ of the cohort was overweight with a BMI equal to or greater than 25 kg/m2. Daily energy intake was 2152 ± 70 kcal, which nearly met what the EFSA dietary guidelines recommend for lactating women aged between 18 and 39 [24]. However, the population did not show a balanced macronutrient distribution (Figure 4A) regardless of BMI. Carbohydrate intake accounted for $37.9\%$ of total daily energy (far from the 45–$60\%$ recommended), which included $16.5\%$ of energy coming from sugars (the sum of digestible sugars present in all the food groups analyzed), while total fat intake surpassed the recommended 20–$35\%$, reaching $43.8\%$ with a relevant proportion of SFA ($13.8\%$). Meanwhile, protein intake was $16.4\%$ (almost meeting the actual guidelines, 10–$15\%$) [24]. Regarding food groups, the majority of energy intake came from cereals, with $22\%$ of total energy intake, followed by $17\%$ of fats and oils, $14\%$ of milk and dairy products, and minor contributions from the other food groups (Figure 4B). The DPA scores of the cohort showed that $39\%$ of the population were following diets that could be considered of good nutritional quality and, therefore, classified as green plates. The rest of the cohort was equally ranked as $31\%$ yellow and $31\%$ orange (Figure 5A). A tendency to increased BMI as diet quality decreased was observed, although it did not attain statistical significance (Figure 5B). ## 3.2. Nutrient and Macronutrient Distribution Assessment through DPA To characterize the algorithm performance, healthy and unhealthy parameters were individually analyzed. Total points obtained were significantly different between DPA scores in the case of the CH/Fb ratio ($p \leq 0.001$), % SFA ($p \leq 0.001$), sodium ($p \leq 0.001$), and fiber ($p \leq 0.001$), whereas the P/Bw ratio did not present significant differences between DPA scores (Figure 5C). Therefore, the diets of women ranked with a green score (DPA = 1) were characterized by the lowest intake of negative nutrients (CH/Fb ratio, % SFA, and sodium) and the highest fiber intake in comparison with the rest of the DPA scores. Yellow and orange scores (DPA = 2 and 3) showed greater intake of negative nutrients, specifically of simple carbohydrates, tripling the CH/Fb ratio punctuation of green plates. Overall, orange plates (DPA = 3) ate more nutrients categorized as negative and less fiber than those obtaining lower DPA scores. Regarding total energy intake, poor nutritional quality positively correlated with energy ($p \leq 0.001$) (Figure 5D). Although more energy does not necessarily mean unhealthy, the algorithm detects that this population substantially exceeded the recommended fat intake as mentioned above (Figure 4A), which increased with DPA scores ($$p \leq 0.011$$) (Figure 5E). On the contrary, protein intake decreased with poorer diet quality ($$p \leq 0.032$$) (Figure 5E). The BMDP, aiming to assess macronutrient balance, was estimated in the population and, according to the results, none of the screened diets were balanced, even when obtaining the best DPA score. The lowest scores (DPA = 1 and 2) had the same F/CH ratio (≈1.30), whereas DPA = 3 had a higher ratio (1.56), far from the stipulated suitable range (Figure 5F). ## 3.3. Food Group Assessment through DPA Concerning food groups, DPA = 3 was associated with the worst food groups, attaining the highest energy intake from the unhealthier ones, such as sweets, beverages, and meat products. Whereas, the most recommended to maintain good health, such as vegetables, fruits and nuts, and legumes were displaced (Figure 6A). This pattern was in contrast with the preference observed with the food groups in diets ranked as green (DPA = 1) and yellow (DPA = 2). Accordingly, poor diet quality ranked by DPA was also reflected in food groups; particularly, women classified under the best score tended to choose less palatable, but more satiating foods, and rich in fiber and micronutrients. Remarkably, the DPA recognizes that the diets followed by the cohort are far from the Mediterranean dietary pattern; no diet perfectly suited the Mediterranean food groups, as a relative deficit in cereals, meat, and fruits and nuts was shown, whereas an excess in fats and oils, sugars, sweets and pastries, and beverages was present (Figure 6B). ## 3.4. Breast Milk Leptin Assessment Previous results from our group have underlined the relevance of adequate leptin levels in breast milk for infant development [35,36,37,38]. Therefore, we tested the involvement of maternal diet quality on milk leptin and analyzed its relationship with the DPA score. Results showed that diet quality influenced the association between maternal BMI and breast milk leptin levels (Figure 7). Specifically, a positive and statistically significant correlation appeared in women whose diets were ranked as DPA = 2 and 3 and their BMI, in contrast with the lack of correlation shown between the best diet quality (DPA = 1) and BMI. Therefore, a high-quality maternal diet appeared to counteract BMI’s influence on milk leptin concentration throughout lactation, whereas a higher BMI would imply higher and sustained milk leptin levels under inadequate diets. ## 4. Discussion Obesity affects millions of people globally and has become a major public health issue. Recent studies have associated the increasing rates of overweight people and people with obesity with unhealthy dietary patterns. These are mainly characterized by low vegetables, fruits, and whole grain intake [1,39,40], in addition to high ultra-processed food and drink (UPFD) content [41,42,43]. Different approaches have been adopted by international organizations and health-related institutions [44] to empower consumers to choose healthier food items, such as nutritional labeling in pre-packed foods. Moreover, several diet quality indicators (DQIs) and dietary recording methods have been developed to evaluate diet quality. The recently updated Healthy Eating Index [45] and the Mediterranean Diet Score [46] are good examples based on a number of representative items. DQIs have been successfully implemented in population studies and have enabled the development of guidelines to improve the health and nutritional status in such populations. However, the individual’s DQI outcome cannot be considered intuitive or comprehensible for average citizens if they have access to it [47]. In fact, data on food consumption indicate that people have little knowledge about nutrition and have difficulties in following a balanced diet. Nutrition in the digital age can use modern technologies to perform heavy computational load, analyze diet composition and quality, and reach individual users in a more personalized manner. In the last decade, digital technology developments have enabled the launching of uncountable nutrition-related mobile apps offering new features, which facilitate dietary recording and diet assessment in comparison with traditional methodologies [48,49,50,51]. These new systems may allow self-monitoring and also constant feedback from and to the user, constituting a dynamic exchange of information very valuable to dietitians to succeed in long-term dietary behavior changes [49,52,53]. However, in order to give personalized nutritional advice on the ubiquitous digital platforms, new, easy, and intuitive diet assessment methods are needed. In this context, a dietary profiling algorithm (DPA) has been developed to implement dietary intake analysis in digital nutrition tools and platforms. The aim is to empower people to eat healthier and motivate them to improve dietary and lifestyle habits in a customized way. Development of the DPA fits the current demand for nutritional advice in mobile devices along with real-time and user-friendly diet assessment tools. The DPA permits a quick and easily interpretable outcome of nutritional status at a glance. Diets are ranked in 3 DPA scores (from 1 to 3), each one with a different color attribution, which can be represented with pictorial elements, such as colored plates (DPA = 1, green; DPA = 2, yellow; DPA = 3, orange), enabling a first visual impression of diet quality and guiding dietary guidelines and recipes for improvement. To assess the performance and utility of the DPA, diets of a cohort of lactating women were analyzed by the algorithm. Although more than half of the screened population presented a good or moderate diet quality (DPA = 1 and 2, respectively), the DPA pointed out that $31\%$ of the cohort had poor diet quality (DPA = 3). The DPA efficiently highlighted the deficiencies of the diet, as the score positively correlated with the points attributed by the algorithm to unhealthy nutrients, and negatively with fiber. This indicates that the DPA was able to reflect the fact that low quality diets can be characterized by a large amount of free sugars, saturated fat, and sodium, and less fiber. In fact, the BMDP showed that diets classified by the DPA with the worst nutritional quality were significantly associated with higher fat intake at the expense of carbohydrate and protein intake. The introduction of a second level of analysis using the concept of the BMDP revealed that no women followed a balanced diet regardless of DPA score. Indeed, food group analysis showed that no diet perfectly suited the Mediterranean pattern. Suboptimal consumption of cereals, meats, fruits, and nuts was observed, along with the excessive consumption of fats and oils, sugary foods, and beverages. Therefore, although general recommendations on the pinpointed nutrients were met in the lower DPA scores, the food choices driving them may not be in accordance with the best diet quality, which gives room for dietary improvement. However, it is important to recall that the perfect combination of food groups does not exist, and many different food groups may be perfectly healthy. Nonetheless, fruits and nuts, vegetables, and whole grains, are considered the fundamental pillars in every diet and, therefore, should be present in any healthy and desirable food pattern [54]. Next, our interest was focused on milk leptin and its relationship with the dietary profile to confirm the utility of the DPA and to obtain further insight on the impact of diet quality during the perinatal period. In this regard, leptin has been widely used as an early predictive marker for obesity and metabolic syndrome since its involvement in early programing [33]. Breast milk leptin positively correlates with leptin serum in lactating mothers [55], which, in turn, positively correlates with the mother’s BMI [55,56,57] and body fat [58]. Therefore, obese women could be providing inadequate milk leptin levels to their infants [34,56], and this is of relevance since leptin has been associated with obesity prevention at the early stages of life through milk supply [38,59,60,61]. The DPA score was tested as a tool to relate maternal diet quality to milk leptin levels. Interestingly, the fact that women’s BMI with diets ranked as green plates correlated with milk leptin in a weaker manner, especially if overweight or obese, gives support to the protective effect of the best diet quality by maintaining adequate leptin concentrations. In contrast, DPA scores >1 did not show this beneficial effect. These results highlight the importance of maternal diet quality during lactation, since providing optimal leptin concentration to newborns is critical for their correct development and metabolic programing [33]. In this work, a diet profiling algorithm, called DPA, has been developed and its potential usefulness as a tool to assess diet quality was tested in a population. At this developmental step, one limitation of the algorithm is that it does not consider other nutrients or compounds that may be relevant for health status, such as polyunsaturated fatty acids [62]. However, the DPA considers nutrients whose information is usually regarded in nutritional databases or food labels, which makes it easy to implement. Still, with the current technology, macro- and micronutrient profiles can be easily obtained from databases, and thus, the intake of other essential nutrients (such as vitamins or minerals) could be assessed and introduced in future versions. Nutrient cut-offs were established based on the population reference intake (PRI) and general recommendations for adults. Nonetheless, these cut-offs can be adapted for populations with different requirements or recommendations, such as protein in weightlifters, for instance. Moreover, the Mediterranean food pattern was selected as a reference model, targeting the specific population tested. However, other food patterns, such as vegetarian, can be considered as adequate in a healthy diet and easily implemented in a diet profiling algorithm such as the DPA. Furthermore, it would be interesting to test the DPA in the general population to confirm its performance. Concerning this last point, the DPA score has been implemented into the Mefood platform (https://www.mefood.io, accessed on 15 January 2023), a precision nutrition software to guide health professionals, which introduces more personalized recommendations for their clients according to their specific characteristics. In this setting, the score has been automatically implemented thanks to the access to the food composition database of the recipes/menus suggested by the platform with good preliminary results. ## 5. Conclusions A diet profiling algorithm (DPA) has been developed as a good DQI in the present work to rank overall diets, and ideally designed for digital nutrition platforms in order to provide a visual and intuitive outcome of diet quality. The DPA can be automatically implemented by combining the use of new technologies coupled with the appropriate food database (e.g., by nationality) in order to extract the nutrient information to mathematically process the DPA. Then, a nutrition-related app can integrate the diet quality assessment and show the colored plates to the user in a friendly and individualized manner, reinforcing the good habits and promoting improvements where necessary. 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--- title: Glucose Biosensor Based on Glucose Oxidase Immobilized on BSA Cross-Linked Nanocomposite Modified Glassy Carbon Electrode authors: - Yang-Yang Li - Xin-Xin Ma - Xin-Yan Song - Lin-Lin Ma - Yu-Ying Li - Xin Meng - Yu-Jie Chen - Ke-Xin Xu - Ali Akbar Moosavi-Movahedi - Bao-Lin Xiao - Jun Hong journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10051639 doi: 10.3390/s23063209 license: CC BY 4.0 --- # Glucose Biosensor Based on Glucose Oxidase Immobilized on BSA Cross-Linked Nanocomposite Modified Glassy Carbon Electrode ## Abstract Glucose sensors based blood glucose detection are of great significance for the diagnosis and treatment of diabetes because diabetes has aroused wide concern in the world. In this study, bovine serum albumin (BSA) was used to cross-link glucose oxidase (GOD) on a glassy carbon electrode (GCE) modified by a composite of hydroxy fullerene (HFs) and multi-walled carbon nanotubes (MWCNTs) and protected with a glutaraldehyde (GLA)/Nafion (NF) composite membrane to prepare a novel glucose biosensor. The modified materials were analyzed by UV-visible spectroscopy (UV-vis), transmission electron microscopy (TEM), and cyclic voltammetry (CV). The prepared MWCNTs-HFs composite has excellent conductivity, the addition of BSA regulates MWCNTs-HFs hydrophobicity and biocompatibility, and better immobilizes GOD on MWCNTs-HFs. MWCNTs-BSA-HFs plays a synergistic role in the electrochemical response to glucose. The biosensor shows high sensitivity (167 μA·mM−1·cm−2), wide calibration range (0.01–3.5 mM), and low detection limit (17 μM). The apparent Michaelis–Menten constant Kmapp is 119 μM. Additionally, the proposed biosensor has good selectivity and excellent storage stability (120 days). The practicability of the biosensor was evaluated in real plasma samples, and the recovery rate was satisfactory. ## 1. Introduction Diabetes is a chronic disease caused by insulin deficiency and hyperglycemia. Attention to the blood glucose level is an indicator for the diagnosis and treatment of diabetes because of its multiple complications affects the normal life of many of diabetics [1,2,3]. The traditional techniques for detecting glucose (Glu), for example, colorimetry [4], fluorescence [5], and high-performance liquid chromatography [6] have disadvantages of sensitivity to interfering substances in samples, large sample size, and being time-consuming. Thus, the electrochemical method has attracted extensive attention because it complements the shortcomings of traditional methods and exhibits fast detection, simplicity, low cost, and excellent sensitivity [7,8,9,10]. Additionally, the biosensor based on glucose oxidase (GOD) develops rapidly due to its good selectivity and high sensitivity. However, the signal transmission between the enzyme and the electrode is difficult due to the large structure of the enzyme molecule. In recent years, nanomaterials have been widely used in the design of electrochemical sensors due to their inherent nano effect, good electrical conductivity, and high catalytic activity. Examples include multi-walled carbon nanotubes (MWCNTs) [11,12,13], platinum [14] and gold nanoparticles [15,16], reduced graphene oxide [17,18,19,20], fullerenes [21], Fe3O4 nanoparticles [22,23], etc. Among them, fullerene is a carbon-based nano material with a spherical three-dimensional structure. Its mechanical stability, high electron transfer ability, and inert behavior have aroused the interest of researchers [24]. Hydroxyl fullerenes (HFs) were modified with functional hydroxyl groups to make them hydrophilic in nature, which helped them bind to proteins into complexes and to protect proteins, thus successfully being applied in biosensors [25,26]. Gao et al. reported that GOD was immobilized on HFs-modified glassy carbon electrode (GCE) to detect Glu [27], but the sensitivity was low. It was reported that MWCNTs have become one of the important nano materials of electrochemical sensors because of their high conductivity, large specific surface area, and outstanding sensitivity [28,29]. In this work, MWCNTs were introduced to enhance the biosensor sensitivity. However, the hydrophobicity of MWCNTs are very strong and have poor biocompatibility, which affects the performance of the biosensor. It was reported that bovine serum albumin (BSA) is a globular protein in plasma and has been used in the construction of biosensors due to its non-toxicity, biocompatibility, and non-immunogenicity [30]. For example, He et al. reported that GOD was immobilized on the composite nanoparticles based on gold nanoparticles/BSA/Fe3O4 to detect Glu and proposed that the shell with BSA supplied a biocompatible environment for GOD and helped to improve the activity of immobilized GOD [31]. The Glu biosensor was prepared on alumina mem-branes/Pt/polypyrrole nanotube arrays by cross-linking GOD with BSA and glutaraldehyde (GLA). Palod et al. proved that cross-linked fixation of GOD could improve the overall performance of biosensors such as sensitivity and shelf life [32]. Therefore, BSA was introduced to better fix GOD on MWCNTs-HFs to improve the biocompatibility of MWCNTs and the performance of the biosensor. In this work, BSA was first used to cross-link and fix GOD onto HFs-MWCNTs nanocomposites, and then a layer of Nafion (NF)/GLA composite membrane was modified to protect the electrode. Finally, a Glu biosensor was constructed for the detection of rat plasma Glu concentration. Here, HFs was introduced to protect the conformation and properties of GOD [33], MWCNTs were used to enhance the electrical signal and sensitivity, and BSA was added to regulate the biocompatibility of the composite. MWCNTs, HFs, and BSA play a synergistic role in Glu molecular recognition. The modified materials were characterized by cyclic voltammetry (CV), UV-visible spectrophotometry (UV-Vis), and transmission electron microscopy (TEM). In addition, the test method and other factors, for instance, enzyme concentration, anti-interference ability, pH, stability, and so on, were systematically studied. Finally, the optimized biosensor successfully identified Glu molecules and determined Glu concentration in rat plasma. Thus, the biosensor has great potential in the measurement of human blood Glu concentration, clinical diagnosis, and management of diabetes. ## 2.1. Reagents and Materials NF, GOD (EC 1.1.3.4, from Aspergillus niger), HRP (EC 1.11.1.7, type VI-A), guaiacol, sodium disodium hydrogen phosphate (Na2HPO4·12H2O), and dihydrogen phosphate (NaH2PO4·2H2O) were purchased from Sigma-Aldrich (Shanghai, China). HFs, MWCNTs, and BSA were obtained from Bucky (Houston, TX, USA), Shenzhen Nanotech Port Co., Ltd. (Shenzhen, China), and Shanghai Baoman Biotechnology Co., Ltd. (Shanghai, China), respectively. Vitamin B1 (Vit B1), vitamin C (Vit C), and sodium chloride (NaCl) were purchased from Beijing Dingguo Biotechnology Co., Ltd. (Beijing, China), Beijing Aoboxing Biotechnology Co., Ltd. (Beijing, China) and Tianjin Deen Chemical Reagent Co., Ltd. (Tianjin, China), respectively. GLA ($0.1\%$) was obtained from Aladdin Reagents Co., Ltd. (Shanghai, China). All reagents in this study used without further purification. Millipore Milli-Q water (18 MΩ cm) was used in this work. ## 2.2. Apparatus and Measurements Electrochemical experiments were conducted on CHI660E electrochemical workstation (CH Instruments, Austin, TX, USA). In a traditional three-electrode electrochemical cell, a saturated Ag/AgCl electrode was reference electrode, a modified GCE (diameter 3.0 mm) was working electrode, a platinum wire was counter electrode. Electrochemical and electrochemical catalytic determination were carried out respectively in N2-saturated and air bubbling (30 min, 300 mL·min−1) 50 mM, pH 6 phosphate-buffered solution. TEM images of MWCNTs and HFs were collected by TEM (JEM2100, JEOL, Tokyo, Japan) at 200 KV. The effects of MWCNTs, HFs, and BSA on the catalytic activity of GOD were studied using an ultraviolet and visible spectrophotometer (UV-vis spectrophotometer) (Evolution 220, Thermo, Shanghai, China) [34]. ## 2.3. Preparation of Modified Electrode Before fixing GOD, the surface of GCE was mechanically polished to the mirror surface with 1, 0.3, and 0.05 μm aluminum oxide aqueous suspension successively. Next, the GCE was treated ultrasonically with double ultrapure water and $75\%$ ethanol for 10 min. Afterwards, the GCE was placed in a drying tower for drying [35]. Steps of modified GCE: firstly, 4 μL of GOD (10 mg·mL−1) and 2 μL of HFs (4 mg·mL−1) were mixed and then next mixed with 1 μL of BSA ($1\%$), and then 4 μL of BSA-HFs-GOD mixture was mixed with 2 μL of MWCNTs (4 mg·mL−1). Subsequently, 5 μL of the composite solution was taken out and dripped onto the surface of the GCE and dried in a refrigerator at 4 °C. Lastly, the 2.5 μL NF-GLA complex (1:1 volume ratio) was immediately dropped on the GCE for protection after mixing. Figure 1 showed preparation process of modified electrode. ## 2.4. Sample Preparation The requirements and experimental use of the animals were reviewed and approved The Biomedical Research Ethics Sub-Committee of Henan University (HUSOM2021-198). Glu plasma samples were prepared: firstly, the blood was obtained through orbital vein after mild anesthesia of rats [36]. Then, the blood of rats was combined with anti-coagulant and was centrifuged at 3000 r·min−1 for 30 min to obtain the plasma supernatant. Afterwards, plasma samples were frozen at −20 °C until used. ## 3.1. Characteristics of Modified Materials The morphologies of MWCNTs and HFs were obtained by TEM. MWCNTs were curved tubes with a diameter of about 10–20 nm. According to the literature, the size of monomolecular HFs is about 1 nm [37]. Figure 2B showed the HFs were a near-spherical shape with an average size of about 20 nm, which may be due to the fact that HFs had cohesive hydrogen bonds and were easy to aggregate in aqueous solution [38,39,40]. HFs aggregates can form complexes with GOD [27], which may promote the electron transfer of protein sites and the conductivity of HFs and improve the catalytic ability of GOD. UV-vis was used to detect the initial catalytic reaction rates (ICRR) of GOD in the presence of BSA (BSA/GOD), HFs (HFs/GOD), and MWCNTs (MWCNTs/GOD) to study the effects of BSA, HFs, and MWCNTs on the catalytic activity of GOD. The detection conditions were similar to our previous study [27]: HRP, GOD, guaiacol, and Glu were added to phosphate−buffered solution to start the reaction. Test wavelength and temperature were 470 nm and 25 °C, respectively. The initial oxidation rate of guaiacol was determined by the concentration of colored product (teraguaiacol, ε470nm = 26.6 mM−1·cm−1). Afterwards, ICRR of the GOD could be converted according to the formation rate of teraguaiacol, and the activity of GOD could be obtained. The relative reaction formula can be expressed by Equations [1] and [2] [34]:[1]Glu+O2 → Gluconolactone+H2O2 [2]4 H2O2+4 Guaiacol →HRP Teraguaiacol+8 H2O In Figure 3, the slopes of GOD, GOD-BSA, GOD-HFs, and GOD-MWCNTs had little change. The ICRR of GOD, GOD-BSA, GOD-HFs, and GOD-MWCNTs were all converted to 0.2 μM s−1. Thus, BSA, HFs, and MWCNTs hardly affect the ICRR of GOD, which may be due to the good biocompatibility of BSA, HFs, and MWCNTs with GOD. ## 3.2. Electrochemical Studies Figure 4 shows the CVs behavior of different modified GCEs in N2-saturated 50 mM pH 6 phosphate-buffered solution with a scan rate of 0.05 V·s−1. No redox peaks were observed at the bare GCE electrode (curve a) and NF-GLA/MWCNTs-BSAHFs/GCE electrode (curve c). However, compared with NF-GLA/GOD/GCE (curve b) and NF-GLA/BSA-HFs-GOD/GCE (curve d), NF-GLA/MWCNTs-BSA-HFs-GOD/GCE (curve e) showed a pair of stronger and stable redox peaks on the CVs. It indicated that the redox peaks of NF-GLA/GOD/GCE (curve b), NF-GLA/BSA-HFs-GOD/GCE (curve d), and NF-GLA/MWCNTs-BSA-HFs-GOD/GCE (curve e) were only from GOD. The background current of NF-GLA/MWCNTs-BSA-HFs-GOD/GCE (curve e) was higher than that of NF-GLA/BSA-HFs-GOD/GCE (curve d), which was attributed to the high conductivity of MWCNTs. The anodic and cathodic peak potentials (Epa and Epc) of the NF-GLA/MWCNTs-BSA-HFs-GOD-modified GCE were −0.334 V and−0.400 V, respectively, versus Ag/AgCl. The potential difference (∆E) was 0.066 V and the peak current ratio (Ipa/Ipc) was close to 1, indicating that the redox reaction of the NF-GLA/MWCNTs-BSA-HFs-GOD/GCE electrochemical process was almost reversible. The formal potential (E°′) of the electrode (E°′ = Epa/2 + Epc/2) was −0.367 V versus Ag/AgCl. This value is higher than that reported by Li et al. ( −0.419 V versus saturated calomel electrode, equivalent to −0.438 V versus Ag/AgCl) [41], and that reported by Cai et al. ( −0.438 V versus Ag/AgCl) [42]. The offset of the positive electrode potential is beneficial to promote the efficient biocatalytic [43], which may be due to the weak hydrophobicity of the MWCNT-BSA-HFs composite. CVs of NF-GLA/MWCNTs-BSA-HFs-GOD/GCE at different scan rates in N2-saturated 50 mM, pH 6 phosphate-buffered solution are shown in Figure 5A. In Figure 5B, the relationship between peak current and scan rate was linear in the range of 0.03–0.4 V·s−1, and peak current increased by improving the scan rate. This indicates that the reaction is a surface-controlled electrochemical process. The relationship between the peak potential (Ep) and the natural logarithm of the scan rate (ln v) had two straight lines with slopes of 0.102 and −0.083 (Figure 5C). Using Equation [3] based on Laviron theory in order to obtain ks at a high scan rate (within the range 0.9–1.8 V·s−1) [44], [3]Ep = E°′+RTαnF − RTαnF lnv where R is gas constant; T is the temperature (293 K); α, n, F are electron transfer coefficient, number of electrons, Faraday constants, respectively. The value of n, α were calculated 1 and 0.31, and the apparent heterogeneous electron transfer rate constant (ks) was calculated as 4.27 s−1 using Equation [4], which was greater than previously reported for that of GOD immobilized on graphene (1.96 s−1) [45], HFs (2.72 s−1) [27], and β-cyclodextrin-MWCNTs-modified electrodes (3.24 s−1) [46]. Therefore, the electron migration rate of our biosensor is faster. [ 4]lnks=α ln(1−α)+(1−α)lnα − ln(RTnFv) − α(1−α)nF∆EpRT The average surface concentration Γ of the FAD of GOD on the GCE surface was estimated to be 2.02 × 10−9 mol·cm−2 using Equation [5], [5]Ip=n2F2AΓv4RT where A, R, n, T, and F are the electrode surface area, gas constant, number of electrons, and temperature, respectively. This value was much higher than those of 2.97 × 10−11 mol·cm−2 at GOD/cobalt sulfide-MWCNTs/NF/GCE [41] and the GOD theoretical Γ value of 1.7 × 10−10 mol·cm−2 [27], which helped to load more GOD. All the significant improvements can be attributed to the large surface area and enhancement of the electrical signal of MWCNT-BSA-HFs. Figure 6A showed the CVs of NF/GLA-MWCNTs-BSA-HFs-GOD/GCE in N2-saturated 50 mM phosphate-buffered at different pH values. As shown in the Figure 6C, the Ep°′ was linearly related to pH with the equation of Ep°′ = −0.0587 pH − 0.0345 (R2 = 0.996). The slope value was −58.7 mV·pH−1. This value was near to the ideal Nernst value at 25 °C [34], indicating that the electron transfer of GOD immobilized on NF-GLA/MWCNTS-HFS-BSA-modified GCE electrodes was the process of proton and electron equivalence. ## 3.3. Optimization Some parameters were studied using CV to optimize the structure of the biosensor and working conditions. Firstly, the effect of the concentration of the GOD solution for NF-GLA/MWCNTs-BSA-HFs-GOD/GCE film formation in the range of 2–12 mg·mL−1 was first investigated. Figure 7 shows the cathodic peak current response of the modified electrode with different concentrations of GOD solution using CV. It was observed that modified electrode obtained the best cathodic peak current response when the concentration of GOD solution was 10 mg·mL−1. Therefore, this enzyme concentration was used for subsequent biosensor construction. Subsequently, we investigated the role of supporting electrolytes at different pH values through CV. Figure 6A showed CVs of NF-GLA/MWCNTs-BSA-HFs-GOD/GCE at different pH values. Figure 6B showed that the cathodic peak current increased by raising the pH within the range of pH 3–7, while the current decreased with pH above 7. Since the cathodic peak current intensities of the modified electrodes were similar in phosphate-buffered solution at pH 6 and 7, linear sweep voltammetry (LSV) was used to observe the electrocatalytic behaviors of the modified electrodes in air-saturated phosphate-buffered solution at pH 6 and 7, respectively. Table 1 lists the results. Finally, we used 50 mM phosphate-buffered solution (pH 6) as the condition for subsequent experiments. The pH selected was consistent with the optimal pH 5–6 of GOD (derived from Aspergillus niger) [47]. There are two causes: 1. The E°′ of the modified electrode in 50 mM phosphate-buffered solution (pH 6) is greater than that of the modified electrode in 50 mM phosphate-buffered solution (pH 7), which is conducive to promoting efficient biocatalytic reduction [43], and using a lower working potential when detecting Glu in the blood can reduce the interference of the electroactive substances in the blood to the electrodes [30]. 2. Compared with the modified electrode in 50 mM phosphate-buffered solution (pH 7), Kmapp of the modified electrode in 50 mM phosphate-buffered (pH 6) is smaller. Later, the electrochemical methods for detecting Glu were investigated. LSV and differential pulse voltammetry (DPV) were performed on the NF-GLA/MWCNTs-BSA-HFs-GOD/GCE for determination of Glu in the presence of air-saturated phosphate buffer. We found that using DPV could obtain higher current sensitivity and lower Kmapp (Table 2), so we chose DPV to detect Glu. ## 3.4. Electrocatalytic Behaviors The DPV of NF-GLA/MWCNTs-BSA-HFs-GOD/GCE in the presence of Glu in air-saturated 50 mM phosphate-buffered solution was studied. The electron transfer process between the electrodes of GOD in air-saturated phosphate-buffered solution is shown Equation [6]. The enzyme-catalyzed reaction of GOD with Glu when Glu was added can be shown by Equation [7]. Figure 8A shows that the cathodic peak value of NF-GLA/MWCNTs-BSA-HFs-GOD/GCE decreased with the increase of glucose concentration. This is because after adding Glu into the air-saturated phosphate-buffered solution, the GOD (FAD) on the electrode surface is reduced [48]. [ 6]GOD (FAD)+e−+H+ ↔ GOD (FADH) [7]Glu+GOD (FAD) → Gluconolactone+GOD (FADH) Calibration of Glu concentration ranges from 0.01 to 3.5 mM, and the statistical analysis of the cathodic peak current difference (∆I) versus the concentration showed three linear ranges (Figure 8B). ∆I increased linearly by raising Glu concentration from 0.01 to 0.05 mM, with the linear regression equation was ∆Ia (μA) = 11.8 C Glu (mM), and ∆I increased linearly by increasing Glu concentration from 0.1–0.9 mM, and the equation was ∆Ib (μA) = 2.3185 C Glu (mM) + 0.5788. As well as ∆I increasing linearly with the increase of Glu concentration from 1–3.5 mM, the linear regression equation was ∆Ic (μA) = 0.5981 C Glu (mM) + 2.1380. The low detection limit (LOD) was 17 μM (3 S0/S, S0 and S are respectively the standard deviation measured under blank condition and the slope of calibration curve), which is lower than that reported by Nashruddin et al. ( 65 μM) [49], Ge et al. ( 42 μM) [50], and Lin et al. ( 70 μM) [51]. The sensitivity of the biosensor was 167 μA·mM−1·cm−2, as shown in Table 3; this value was much higher than 56.12 and 8.5 μA·mM−1·cm−2 reported in Barathi et al. [ 52] and Chen et al. [ 48]. According to the electrochemical version of Lineweaver-Burk, the Kmapp can be calculated to be 0.119 mM (Figure 8C), lower than the results of most other biosensors of GOD [27,42,53]. The lower Kmapp value indicates that the modified electrode has a strong binding ability with the substrate, showing that this biosensor has a strong affinity for Glu [43]. The improved performance and affinity of the biosensor may be due to the synergistic effect of MWCNT-HFs-BSA and the improved microenvironment of GOD. ## 3.5. Anti-Interference Ability, and Stability of Biosensor Several electroactive substances commonly found in blood such as vitamin B1 (Vit B1), vitamin C (Vit C), and sodium chloride (NaCl) were introduced in phosphate-buffered solution to evaluate the anti-interference performance of this biosensor. Considering that the concentration of Glu in human blood is at least 30 times higher than that of physiological interfering substances [54,55], the effects of interfering substances were evaluated by adding 1 mM Glu solution, 0.1 mM Vit B1, Vit C, and NaCl solutions and 0.5 mM Glu solution to air-saturated phosphate-buffered solution and observing the signal intensity of the modified electrode by LSV method. The cathodic peak current hardly change significantly when the interfering substance was added, while the addition of two Glu solutions with different concentrations caused a strong cathodic peak current signal (Figure 9 inside the circle). The cathode peak current could not accurately describe the anti-interference ability of the modified electrode because the concentration of Glu solution and interfering substance is different. In order to intuitively study the anti-interference ability of the biosensor, we introduced an interference signal (IS) (Equation [8]) [30]. The IS values of Vit C, Vit B1, and NaCl were calculated to be $0.93\%$, $1.45\%$, and $3.95\%$, respectively. The IS value of the biosensor with strong anti-interference ability is low. It can be seen that the biosensor has good selectivity, which is ascribed to the low working potential of this biosensor and the outer layer protection containing NF. [ 8]IS (%)=iG+I−iGiG × $100\%$ Here, iG and iG+I represent the response current to Glu in the absence and presence of interference, respectively. The stability of the modified electrode was researched by CV method (Figure 10A). After 100 cycles, the cathodic peak of the modified electrode only decreased $3\%$. Additionally, the storage stability of the biosensors was evaluated using the CV method (Figure 10B). We found that the percentage of cathodic peak current only decreased $3\%$ when the biosensor was preserved at 4 °C for 120 days. It shows that this biosensor has excellent storage stability. ## 3.6. Determination of Glu in Plasma The practical ability of the proposed biosensor to detect Glu in plasma samples was evaluated. The plasma sample was prepared as described above. The rat blood Glu concentration was predefined using a commercial glucose meter (ACCU-CHEK Instant, Roche Diabetes Care GmbH, Jiangsu, China) as 8.2 mM. At present, plasma is usually used to measure Glu concentration in clinical practice, and the level of Glu in plasma is usually 10–$15\%$ higher than that in whole blood [56]. Therefore, the plasma Glu concentration of rats after correction was 9.3 mM using Equation [9]. Since some interfering substances in real blood samples may cover the electrode surface and obstruct electron transfer, the accuracy of the test results may be reduced. Plasma was diluted with phosphate-buffered solution 310, 62, 18.6, and 12.4 times to obtain plasma with different Glu concentrations, and the recovery rate with biosensors was measured to reduce such adverse effects and experimental errors and improve the accuracy of blood Glu concentration measurement. From Table 4, the recoveries of this method were 95.9–103.9 %. It can be seen that the proposed sensor shows a satisfactory recovery of Glu in plasma samples, validating that the biosensor has potential good practicability in the detection of real samples. [ 9][Glu]blood=[Glu]plasma / 1.14 ## 4. Conclusions In this work, GOD was immobilized on MWCNTs-BSA-HFs composites, and an NF-GLA composite membrane was used to prevent the leakage of immobilized GOD, and a new and simple Glu biosensor was constructed. 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--- title: Effect of Feeding Pomegranate (Punica granatum) Peel and Garlic (Allium sativum) on Antioxidant Status and Reproductive Efficiency of Female Rabbits authors: - Omnia Y. Abd-Elfadiel Hagag - Fawzy El-Essawy Younis - Rasha A. Al-Eisa - Eman Fayad - Nahla S. El-Shenawy journal: Veterinary Sciences year: 2023 pmcid: PMC10051658 doi: 10.3390/vetsci10030179 license: CC BY 4.0 --- # Effect of Feeding Pomegranate (Punica granatum) Peel and Garlic (Allium sativum) on Antioxidant Status and Reproductive Efficiency of Female Rabbits ## Abstract ### Simple Summary Because rabbit meat has a good nutritional value, low levels of fat and cholesterol, and a high protein content, it may assist to alleviate meat shortages in developing countries. Since the 1970s, the processing of rabbit meat has developed into a highly specialized sector in various European nations, making Europe the world’s second-largest producer of rabbit meat, behind China. Livestock productivity is currently compromised by low animal reproduction efficiency. Adding pomegranate peel, garlic powder, or a combination of the two to the diet of does alter their weight, the number of offspring, reproductive performance, hematological indices, and many antioxidant indicators, as well as the liver and kidney functions. In conclusion, pomegranate is a promising substance to include in a rabbit’s diet, followed by garlic to boost reproductive efficiency. ### Abstract Egypt’s animal protein shortfall cannot be overcome by expanding the production of large animals alone, but rather by increasing the production of highly reproducing animals in the livestock unit. The goal of this study was to examine how adding pomegranate peel (PP), garlic powder (GP), or a mixture of the two to the diet of does affect their weight, the number of offspring, reproductive performance, hematological indices, and several antioxidants indicators as well as the liver and kidney functions. A total of 20 adult and mature female mixed rabbits at age 4.5–5 months and averaging 3.05 ± 0.63 kg body weight, were allocated into four experimental groups ($$n = 5$$). The first group was provided with the basal diet and was considered as control animals, while the second, third, and fourth groups were fed the basal diet supplemented with PP $3.0\%$, GP $3.0\%$, and a mixture of PP $1.5\%$ + GP $1.5\%$, respectively. After 2 weeks of feeding the experimental diets, natural mating with untreated bucks was carried out. The kits were weighed immediately after parturition, and then every week. The study found that rabbits fed with $3\%$ PP led to a $28.5\%$ increase in the number of kits at birth compared to the control group. As an effect of supplementing PP $3\%$, GP $3\%$, and PP $1.5\%$ + GP $1.5\%$, the birth weight increased by $9.2\%$, $7.2\%$, and $10.6\%$, respectively, as compared to the control. Hemoglobin increased significantly in all treatment groups as compared to the control at the age of kit weaning. Lymph cells increased significantly in the rabbits that were fed with GP ($3\%$) than in other groups and even the control. The results showed that creatinine levels were significantly decreased in the PP ($3\%$) and GP ($3\%$) than in control rabbits. The level of triglycerides significantly declines in groups treated with PP ($3\%$) than in other treatment groups and the control. The addition of PP $3\%$ or GP $3\%$ increased the progesterone hormone. The addition of PP $1.5\%$ + GP $1.5\%$ improved the immunoglobulin IgG. The results of superoxide dismutase, catalase, glutathione, and total antioxidant capacity showed a significant decline in groups treated with GP ($3\%$) than other treated groups. In conclusion, pomegranate is a promising substance to include in a rabbit’s diet, followed by garlic to boost reproductive efficiency. ## 1. Introduction An additional 2 billion people should be fed over the next thirty years, necessitating a $70\%$ increase in meat and milk production. Rising demand for livestock products in the future, driven by rising incomes, population growth, and urbanization, will place a huge strain on feeding capital [1]. Meat is derived from various traditional sources, such as poultry, beef, sheep, and goats, which, considering the high density of the livestock population, are rather inadequate to satisfy the increasing demand for animal protein. Protein deficiency has been identified as the key contributing factor to malnutrition [2]. Rabbit production in developing nations could help to reduce meat shortages, especially because rabbit meat has a high nutritional value, with minimal fat, cholesterol, and high protein content [3]. In some European countries, the processing of rabbit meat has increasingly become a highly specialized industry since the 1970s, making Europe the second largest producer of rabbit meat in the world after China [4]. Currently, low reproductive efficiency in animal production undermines livestock productivity. Several attempts to resolve this obstacle (poor reproductive performance) have contributed to the identification of oxidative stress (OS) as the culprit since OS directly or indirectly impairs the efficiency of animals [5]. Many attempts to examine the activity of natural antioxidants, particularly those of plant origin, have been made [1,6,7]. The availability of a significant number of by-products from the fruit and vegetable processing sector across the world encourages their use as a new source of feed in animal ration formulation [1]. Pomegranate by-products can be a reliable source of nutrients and antioxidants for livestock feeding, such as rabbits [8]. Several phenolic activities are already demonstrated in the pomegranate and its derivative portions [6]. Arils comprise $40\%$ of the overall weight of the fruit, while the rest consists of seeds ($10\%$) and peels ($50\%$) [9]. The pomegranate peel (PP) has been associated with numerous health benefits. These beneficial by-products are functional elements in meats, nutraceuticals, and pharmaceuticals due to the high level of bioactive compounds in the peel and the documented health benefit [10]. The PP includes bioactive compounds that are abundant in the polyphenolic class of antioxidants, including tannins and flavonoids. In various pharmacological activities, such as anti-aging, anti-inflammatory, and anti-atherosclerotic activities, antioxidant activity has been suggested to play a vital function. Antioxidant supplementation’s ability to prevent free radical damage has made it a popular treatment strategy for lowering disease risk [11]. Allium sativum (garlic) is a popular spice in the Mediterranean region, as well as in rabbit diets and herbal medicine. As an antimicrobial, it plays a significant function in the prevention of a variety of diseases, extending from infections to heart disorders [12,13,14]. Garlic supplementation is crucial for broiler chicks because of its high immune-stimulating effects and beneficial effects on digestion in birds [15,16]. Despite the beneficial properties of Punica granatum L., there is currently limited research regarding its use in animal nutrition. In the current study, supplementation of rabbit diets with by-products (PP) or/and garlic powder (GP) was investigated for their effectiveness on female weight, the productivity of rabbits, hematological indices, of mother and kids rabbits, and several antioxidants indicators as well as the liver and kidney. ## 2.1. Chemicals Total protein (TP), albumin (A), urea, and creatinine kits were provided from Diamond, 6th Street, Pyramids Garden-Giza, Egypt. Cholesterol (TC), HDL-c, and triglyceride (TG) kits were purchased from Spinreact, Ctra, Sta, Coloma 7, 17176 St, Esteve de Bas, Spain. Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) kits as well as prolactin and progesterone ELISA (enzyme-linked immunosorbent assay kits were obtained from humans in the United States. However, Immunoglobulin G (IgG) and M (IgM) kits were taken from Bio-diagnostic, 29 El Tahrir, Ad Doqi, El Omraniya, Giza Governorate, Egypt. ## 2.2. Preparation of Diet Pomegranate fruits (P. granatum) were collected from and included in the pomegranate farm in Ras Sudr Research, Egypt. Pomegranate peels were washed well in running water and dried in a drying oven at 80 °C for 3 days. Then, the dried peels were grounded using a grinder mill at Ras Sudr Research Station Laboratory. Garlic powder (GP) was collected from the Rajab Al Attar store in Cairo, Egypt. ## 2.3. Chemical Analysis of PP and GP The samples of the PP and GP were subsequently analyzed in triplicate for crude protein (CP), ether extract (EE), moisture, and ash as described by the Association of Official Analytical Chemists [17] (Table 1). The following was written in the container pellet’s basic diet: rude fiber should be at least $22\%$, protein is $14\%$, fat is about $1\%$, and calcium is around $1\%$. ## 2.4. Experimental Design and Ethic All experimental procedures were approved and performed in compliance with the guidelines of the Research Ethical Committee of the Faculty of Veterinary Medicine, Suez Canal University, Ismailia, Egypt (the approval No. 2019033). The present study was conducted at the experimental Ras Sudr Research Station, located in the South Sinai Peninsula in Egypt and belonging to the Desert Research Center, Ministry of Agriculture and Land Reclamation, during the period from November 2020 to January 2021. A total of 20 adult and mature female mixed of commercial rabbits as Northland and American (at age 4.5–5 months) averaged 3.05 ± 0.63 kg body weight, distributed into four experimental groups ($$n = 5$$) Each group has been housed in galvanized batteries (60 × 40 × 24 cm) provided with feeders and automatic drinkers. The occurrence of harmful infections was generally prevented by utilizing high-standard cleanliness and careful management, and rabbits were never treated with any type of systematic immunization. The first group was provided with the basal diet and was considered as control, while the second, third, and fourth groups were fed the basal diet supplemented with pomegranate peel (PP) at $3.0\%$, garlic powder (GP) at $3.0\%$, or a mixture of PP $1.5\%$ + GP$1.5\%$, respectively (Table 2). The rabbits were kept in galvanized wire cages with a light/dark cycle of 12 h, a temperature of 24.5–27.5 °C, and relative humidity of 64–$76\%$. The cages were given for manual feeders and nipple drinkers. They had free access to fresh water and feed ad libitum. Natural mating with untreated bucks was conducted after two weeks after the beginning of feeding with the experimental diets. The buck/doe ratio was 1:5. Mating occurred between the hours of 8 a.m. and 9 a.m. Abdominal palpation was used to detect pregnancy 15 days after mating. After palpation, females that had not conceived were reintroduced to the same buck for another mating. The duration of experiment was 3 months (two weeks’ adaptation, 2 weeks to determine the abdominal palpation which was used to detect pregnancy after mating, a month of pregnancy, and a month for lactation till weaning. ## 2.5. Bodyweight Each experimental rabbit in each group was weighed before mating and before parturition. The kits were weighed immediately after parturition, and then every week early in the morning before feeding and suckling to the nearest 10 g. The balance is Escali Digital Scale (The Winco SCAL-820 Scale with 8” Dial.) is perfect for weighing rabbits. ## 2.6. Blood Collection For the does, blood samples were collected from the ear veins of each female rabbit after 21 days of the pregnancy, allowed to clot, and then centrifuged at 3000 rpm for 15 min to separate the serum. Serum samples were stored at −20 °C for further biochemical analysis. Frozen serum was thawed and assayed calorimetrically for all the biochemical parameters as described below. There was another patch collected in heparinized tubes for hematological estimation. The same two patches were collected from the kids after weaning. ## 2.7. Hematological Estimation Hematological parameters fresh blood samples were collected in a heparinized tube from each female rabbit, weaning rabbit kits (4 weeks of age), and all parameters of the blood profile [erythrocyte cell counts (RBCs), white blood cells (WBCs), hematocrit (Hct), hemoglobin (Hb), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC)], differential counts of white blood cells (WBCs), and platelet count (PLT) were measured in whole blood using the blood counter apparatus model Mindray Product BC-2800 Auto Hematology Analyzer (Guangdong Maikang Medical Co., Ltd, Guangdong, China). ## 2.8. Determination of Liver and Kidney Functions According to Doumas et al. [ 18], the total protein (TP), albumin (A), globulin (G), and (A/G) ratio were assessed. USA kit (Elabscience; 14780 Memorial Drive, Suite 108, Houston, TX, 77079, USA) was used to determine the activity of both aspartate aminotransferase (AST) and alanine aminotransferase (ALT) according to Reitman and Frankel’s technique [19]. All the ELISA kits were obtained from Humans (Elabscience; 14780 Memorial Drive, Suite 108, Houston, TX, 77079, USA). Spinreact (Ctra, Sta, Coloma 7, 17176 St, Esteve de Bas, Spain), the Spanish kit’s standard method, was used to measure serum total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), and triglyceride (TG) levels. Low-density lipoprotein cholesterol (LDL-c) was calculated using the Friedewald equation: LDL-c = TC-(HDL-c + TG/5) where (TG/5) = very-low-density lipoprotein cholesterol (VLDL-c). Kits were purchased from Spinreact, Spain. The levels of urea and creatinine were determined using the methods outlined by Patton and Grouch [20] and Bartles et al. [ 21], respectively. Kits were taken from Biodiagnostic, 29 El Tahrir, Ad Doqi, El Omraniya, Giza Governorate, Egypt. ## 2.9. Estimation of Immunoglobulin and Hormones Immunoglobulin G (IgG) and M (IgM) levels were determined using specific kits (Bio-diagnostic, Egypt). Prolactin and progesterone hormones were assayed by applying the ELISA method using ELISA kits ((Elabscience; 14780 Memorial Drive, Suite 108, Houston, TX, 77079, USA). ## 2.10. Oxidative Status and Antioxidants Total antioxidant capacity (TAC) was determined using a Kit from (Cell Biolabs, 10225 Barnes Canyon Rd, San Diego, CA, USA). Superoxide dismutase (SOD) was determined using ELISA Kit and glutathione (GSH) was determined using ELISA Kit (Cusabio, 7505 Fannin St Ste 610-322 Houston, TX 77054, USA). Malondialdehyde and catalase (CAT) were determined using ELISA Kits (MyBioSource, Inc., San Diego, CA, USA). ## 2.11. Statistical Analysis The data are represented as means of values ± S.E ($$n = 5$$). To compare the results, the One-way ANOVA test was applied to calculate basic statistic characteristics and to determine significant differences between the experimental and control groups. Differences were compared for statistical significance at the level of p ≤ 0.05 by using the statistical software SPSS. ## 3.1. Bodyweight Figure 1 depicts the effect of dietary PP, GP, and their combination on rabbit growth performance. The results showed that there was no significant difference in the weights of does before parturition between the treatments and the control group. The weight of rabbits in the combination group increased by $8\%$ before parturition compared to the pomegranate group. Figure 2 shows the number of kits at birth in each treatment and control group. When compared to those fed a control diet, the PP $3\%$ group had a substantial ($p \leq 0.05$) increase in the number of kits at birth, almost $28.5\%$. When compared to other supplements, there was no significant difference in the weights of the rabbits born as a result of the rise in the number of rabbits born (Figure 3). When compared to the control, supplementing with PP $3\%$, GP $3\%$, and PP $1.5\%$ + GP1.5 % increased birth weight by $9.2\%$, $7.2\%$, and $10.6\%$, respectively. ## 3.2. Hematological Parameters Changes in hematological parameters after the birth of does are represented in Table 3. No significant differences were observed in any parameters of the T2 except for mean corpuscular hemoglobin (MCV) was increased significantly as compared to T1. T2 is significantly different from the T1 in the RBC counts. A significant decrease in MCV was recorded in the PP $1.5\%$ + GP $1.5\%$ group in comparison with the GP $3\%$ group. The number of WBCs shows a significant decrease in the GP group as compared to the control. On the other hand, a significant increase in WBCs was recorded in the PP $1.5\%$ +GP $1.5\%$ group as compared with other groups. Also, there was a significant increase in counts of mid and grand WBCs in the PP $1.5\%$ GP $1.5\%$ group compared to the other animals. In comparison with the control trend, highly significant ($p \leq 0.01$) increases in the content of platelets were detected in all experimental groups. Table 4 shows the changes in hematological parameters after 4 weeks of weaning rabbit kits. HB content significantly increased ($p \leq 0.05$) in all treatment groups as compared to the control rabbits. The results showed the groups that were treated with PP $3\%$, GP $3\%$, and PP $1.5\%$ + GP $1.5\%$ increased HB by $9.9\%$, $10.86\%$, and $15.2\%$ as compared to the control group, respectively. MCHC and WBCs decreased significantly in the PP $1.5\%$ + GP $1.5\%$ group as compared to the other groups and the control. However, a significant decrease in grand WBCs was noticed between all treatment groups and the control rabbits. However, lymph cells were increased significantly in the rabbits that were fed with GP $3\%$ more than in other groups or even the control. ## 3.3. Liver and Kidney Functions Data in Figure 4 demonstrated the effect of dietary PP, GP, and their combination supplementation on serum TP, A, G, and A: G ratio, as well as AST and ALT activity. No significant differences were noted in any of the serum protein parameters except for TP and A. A significant increase ($p \leq 0.01$) was observed in rabbits fed in the GP $3\%$ group. The effect of GP $3\%$ on TP was nearly 1.1-fold, while the effect of its addition on A was about 1.37-fold as opposed to all other groups. Whereas results of liver function enzymes showed that AST activity significantly increased ($p \leq 0.05$) in the PP $1.5\%$ + GP $1.5\%$ group than in other groups. However, rabbits fed with PP $3\%$ or PP $1.5\%$ + GP $1.5\%$ showed a significant increase in ALT activity by about 1.23-fold and 1.43-fold, respectively, as compared to the control group (Figure 5). The effect of the PP $3\%$ and GP $3\%$ treatments on urea was about 1.32-fold, and 1.46-fold respectively, as compared to the control (Figure 6). On the other hand, the results showed creatinine levels significantly decreased in the PP $3\%$ and GP$3\%$ than in control rabbits (Figure 7). ## 3.4. Effect of Supplementation on Lipid Profile The effect of dietary PP, GP, and their combination on the lipid profile is shown in Figure 8. The level of TC and HDL-c increased significantly ($p \leq 0.05$) in groups treated with GP $3\%$ or the combination of both supplements as compared to the PP $3\%$ group by about 1.56-fold, and1.33-fold, respectively, for TC and 1.77-fold, and 1.46-fold for HDL-c. Whereas the level of TG and VLDL-c showed a significant ($p \leq 0.01$) decline in groups treated with PP $3\%$ more than in other treatment groups and the control. The groups that are fed with GP$3\%$, $1.5\%$ + GP $1.5\%$ increase the level of TG by about 1.27-fold and 1.69-fold, respectively, as compared to the PP $3\%$ group. Moreover, the level of TG and VLDL-c showed a significant ($p \leq 0.05$) increase in groups treated with PP at $1.5\%$ + GP $1.5\%$ than in other treatment and the control groups. ## 3.5. Effect of Supplementation on Progesterone and Prolactin Hormones Prolactin hormone levels showed that no significant differences were found in the treatment and the control groups (Figure 9). As seen in Figure 9, showed a significant increase in the level of progesterone in the group treated with PP $3\%$ by $52.9\%$ and $34.6\%$ more than $1.5\%$ PP + $1.5\%$ GP and the control, respectively. ## 3.6. Effect of Supplementation on Immunoglobulin IgG and IgM The level of IgM significantly decreased in the PP $1.5\%$ + GP $1.5\%$ treatment group than in other treatment groups as well as the control rabbits (Figure 10). In contrast, the PP $1.5\%$ + GP $1.5\%$ treatment group had significantly higher levels of IgG than the other treatment groups. The effect of PP $1.5\%$ + GP $1.5\%$ has increased the IgG by $66.19\%$ and $33.46\%$ as compared to the PP% and GP% groups, respectively. ## 3.7. Oxidative Stress/Antioxidant Status The results of SOD, CAT, GSH, and TAC showed a significant decline in group treatments with $3\%$ GP than other treatment groups and control (Table 5). In addition, the GSH and TAC levels showed a significant increase in the rabbits treated with the combination than in other treated groups. The results of MDA were found to be higher in the PP $3\%$ group than in control rabbits (Table 5). However, the level of the MDA significantly increases in group treatment with GP by $3\%$ than other treatment groups and control. ## 4. Discussion The increased need for animal protein demands the utilization of the potential of minute livestock species and supports their inclusion in animal research and economic development programs, particularly in developing nations. Rabbit farming is classified among nonconventional breeding in Côte d’Ivoire [22]. This breeding is not commonly practiced, although it has very significant potential in terms of the productivity and nutritional value of the rabbit. One of the reasons for this state of affairs is its high production cost, linked largely to the high price of industrial feed for rabbits made from cereals and soybean meal [22]. The major purpose of this research would be how adding PP, GP, and their combinations affected does’ weight, number of offspring, and reproductive performance. Moreover, hematological parameters, serum immunoglobulins, liver and kidney functions, additionally, antioxidant effects were evaluated. The effect of dietary PP and GP, as well as their combination, revealed that there was no significant difference in the weights of does before mating and before parturition between treatments. These results agree with those reported by Bahakaim et al. [ 23], who stated that adding PP powder to the rabbits’ diets during their pregnancy did not affect their final body weight or gain. Also, Bello et al. [ 24] found that when garlic was added to the diet, daily weight gain was not significantly different among rabbits of different sexes. These results contradicted an earlier study conducted on weaned rabbits by Onu and Aja [25], who reported that herbs mediated and restricted the growth and colonization of various pathogenic and non-pathogenic bacteria in the gut, resulting in an improved feed-to-meat ratio. This improvement by garlic supplementation may be due to providing some compounds that enhance digestion and absorption of some nutrients in the diets. Also, it may be attributed to the bioactive components (allicin) found in garlic that cause greater efficiency in the utilization of feed, resulting in enhanced growth [26]. Though there is a range of herbs that may be employed as natural growth boosters, the current findings indicated that the PP $3\%$ group had a higher litter size, although mean birth weights were not significantly different throughout the trial when compared to the other groups. This increase in the number of kits at birth was about $28.51\%$ as compared to the control. This result was partially consistent with the finding of Azoz and Basyony [27], who reported that when rabbits were fed a diet containing $1.5\%$ PP, their litter size increased by around $40.86\%$ when compared to rabbits fed a control diet. These could be attributed to antioxidants derived from natural sources, which are necessary for reproductive ability, immune response, and overall health [28]. Bahakaim et al. [ 23] found that adding PP powder or PP extract to the diet of a pregnant rabbit had no effect on the size of the litter at birth. There were no significant differences in litter size owing to the addition of PP on the 7th, 14th, or 21st days of breastfeeding. In this regard, Azoz and Basyony [27] reported that these changes could be traced back to the number of offspring per doe, but the decrease in pup weight is because young rabbits raised in bigger litters have less access to milk, resulting in reduced weight gain. The dietary PP has no significant effects on any of the hematological parameters except the PLT count. One possible explanation [29] is that pomegranate juice drinking for a short period may boost erythropoiesis or prevent RBC degradation in healthy adults without generating large changes in metabolic health and inflammatory indices. El-Gindy [30] suggested that the WBC count was non-significantly reduced in pregnant rabbits fed with PP ($1.5\%$ and $3\%$), despite a non-remarkable increase in lymphocytes. The current data was in line with that of Riaz and Khan [31], who demonstrated that decrease in platelet aggregation and fibrinogen concentration, in a dose-dependent manner. The outcomes of hematological and coagulation assays raise the possibility that PP has an antianemic and cardioprotective effect. The garlic group had a significant increase in the RBC count in the current investigation. Onyimonyi et al. [ 32] reported that there was a significant elevation in RBC in the treatment groups of broilers with $1\%$ and $5\%$ GP in comparison to the control group. According to Fazlolahzadeh et al. [ 33], one explanation for the current study’s findings is that garlic contains various substances that may have a role in the function of organs involved in blood cell formation, such as the thymus, spleen, and bone marrow. According to Al-Jowari [34] and Onyimonyi [32], the effect of $1\%$ GP on HB concentration, PCV, and PLT count in male rabbits has no significant differences. Manthou et al. [ 29] reported that the polyphenols in pomegranate juice may have protected HB from oxidative agents, resulting in enhanced HB levels in rabbit kids in the current study. This rise could be related to the activation of expression or catalytic activity of enzymes involved in GSH production that are known to be boosted by plant polyphenols [35]. The WBCs have the primary job of defending the body against foreign substances, which is accomplished by leukocytosis and antibody synthesis [36]. The current findings are consistent with those of El-Gindy [30], who discovered that PP therapy decreased the number of WBCs. When the quantity of PP in the diet was increased, the number of lymphocytes rose. Al-Jowari [34] found that the HB level, PCV, and PLT count in the $5\%$ GP group were elevated as compared to the control rabbit. This could be due to a byproduct of garlic metabolism in the body that stimulates the kidney directly, causing erythropoietin synthesis and release. The present study is concerned with the effect of PP and GP on liver and kidney functions. The obtained results revealed the effect of dietary PP and GP in female rabbit diets on TP, A, G, and A: G ratio. Except for TP, there were no significant variations in any of these measures. A significant increase ($p \leq 0.01$) was observed in rabbits fed the GP $3\%$ group as opposed to all other groups. These results agree with Nassrallah et al. [ 37], who reported that PP powder did not affect the albumin concentrations of rabbits. These findings are consistent with those of the previous study [38], which reported that the A: G ratio didn’t vary significantly among the rabbit groups fed various levels of PP and the control. However, in contrast, Ibrahim et al. [ 38] noticed that supplementing with PP increased plasma TP, A, and G levels when compared to the control group. The current data corroborated with the previous study in which dietary allicin (10 mg/kg body weight) significantly improved protein metabolism by increasing TP and A levels [39]. As a result, several studies found that increasing TP concentration was linked to higher A concentration when garlic organosulphur compounds were present, which has a protective effect on liver function [40]. El-Katcha et al. [ 41] published similar findings on broiler chickens treated with allicin, as well as rabbits [26] treated with garlic. PP has also been demonstrated to be less prone to oxidation. This binding is linked to an increase in the resistance of LDL-c to oxidation [42]. The PP significantly increased blood HDL-c after 60 and 120 days of rabbit treatment, according to Abdel-Maksoud [43]. Perhaps this connection could help interpret the study’s results due to its brief length. According to Azoz and Basyony [27], all groups given varying amounts of PP (0.5, 1.0, and $1.5\%$) had significantly lower plasma triglycerides and VLDL-c than the control group. In the current study, the level of TC, LDL-c, HDL-c, TG, and VLDL-c increased significantly in groups treated with GP $3\%$ as compared to the control. However, Alagawany et al. [ 26] reported that there was no change in serum biochemical markers (TP, TC, TG, ALT, and AST) between broilers fed a garlic-enriched diet and those fed a control diet. Hypertriglyceridemia may be caused by a decrease in lipoprotein lipase activity combined with an increase in hormone-sensitive lipase activity, resulting in decreased TG uptake from the circulation [44]. Codoñer-Franch et al. [ 45] reported that anti-oxidant enzymes are destroyed by excess synthesis of oxidized low-density lipoproteins (ox-LDL), which inhibits SOD expression, and could also be responsible for decreased SOD activity. Fed a base diet with varying doses (ranging from 1,000 to 1,500 mg/kg) of whole-pomegranate extract for 60 days in the summer to the rabbits. LPO, AST, ALT, TC, TG, and WBC, which were negatively impacted by summer heat stress in the control rabbits, were dramatically reduced by the extract [46]. The presence of many phenolic components (ellagic acid, punicalin, and punicalagin) rather than a single pure polyphenol accounts for the pomegranate’s superior antioxidant action [47]. Pomegranate was a good source of natural antioxidants due to its exceptional effectiveness in scavenging hydroxyl and superoxide anion radicals. Garlic, as previously reported, includes a diverse range of phytochemicals. These phytochemicals are detoxified or metabolized in the liver after ingestion. The increased activity of the liver as a result of the increased garlic levels accounts for the observed rise in these blood chemistry indices of the liver [32]. Biomarkers for kidney function include urea and creatinine. The results showed that urea levels were significantly increased in the PP and GP groups compared with the control. On the other hand, creatinine levels significantly decreased in the PP $3\%$ and GP $3\%$ than control. This data is in agreement with that of Ibrahim et al. [ 38], who found that when rabbits were fed different amounts of PP, their creatinine levels decreased significantly. This result agrees in part with Abdel-Wareth et al. [ 48] findings. When compared to non-garlic-added groups, dietary supplementation with garlic oil reduced serum urea, creatinine, and urea-nitrogen activity. Progesterone hormone levels were significantly increased in the PP group than in the control and the GP showed an increase in progesterone hormone. There were no significant variations in prolactin hormone levels between the treatment and the control groups. As reported by DeMayo et al. [ 49], progesterone and oestradiol are key hormones for sexual maturity and reproduction. The results follow the results of Liebler [50] who used vitamin E, where the protective effect of antioxidants against LPO in the cell membrane could explain the improved reproductive function in PP treatment. The results of the GP group are also similar to El-Ratel et al. [ 39], who were treated with allicin at both levels (5 and 10 mg per kg). In comparison to the control, there was an increase in blood progesterone levels at mating, mid-pregnancy, and 7-days post-partum. Also, both allicin levels 7 days after birth did not affect a significant increase in prolactin concentration. However, garlic extract was found to enhance gonadotropin secretion and ovarian hormones by activating the anterior pituitary [51]. The current study also examined the effects of PP and GP on rabbit immunity. The IgM levels in the PP and GP groups did not change. Meanwhile, IgG significantly declined in the PP group than in the control. The obtained results are supported by El-Sissi et al. [ 52]. At 12 weeks of age, rabbits fed high concentrations of PP and PP extract showed a significant decrease in IgG. Gracious et al. [ 53] reported that feeding pomegranate fruit rind powder orally increased typhoid antigen-antibody levels. Li et al. [ 54] demonstrated that protein and amino acid deficiencies have been known to disturb immune function, as amino acids such as arginine, glutamine, and cysteine. They play a crucial part in the immune system’s reaction by activating lymphocytes and macrophages, controlling gene expression, and synthesizing specific proteins such as cytokines, antibodies, and cytotoxic substances. Relatively consistent with Alagawany et al. [ 26], they found that garlic in rabbit diets increased IgG concentrations linearly and quadratically, but IgM concentrations were unaffected by GP in contrast to the control group. The antioxidant parameters (CAT, SOD, GSH, and TAC) showed a significant decline as compared to the control. MDA results, on the other hand, were found to be higher in the PP and GP groups than in the control rabbits. Hermes-Lima et al. [ 55] postulated that activation of antioxidant defenses, in which real oxyradical generation should decrease, is a protective mechanism against OS generated by physiological stress circumstances. Excess H2O2 in the intermembrane gap may pass through the external mitochondrial membrane and alter the redox status of the entire liver by lowering the GSH level, according to El-Hafidi et al. [ 56]. The PP can chelate metal ions like Cu2+ and Fe2+ that catalyze free radical production reactions. It also meets the structural requirements for optimal antioxidant and/or scavenging activity [57]. Reduced SOD activity, a sign of OS, was also a factor in the higher MDA levels observed in this study, according to Nabil et al. [ 58]. Furthermore, El-Hafidi et al. [ 56] found that decreased CAT activity in the sucrose-fed rats SFR hepatic homogenate may contribute to higher levels of LPO and protein carbonylation in whole liver cells. After the first month of pregnancy, Erisir et al. [ 59] investigated the levels of oxidants and antioxidants in sheep, finding lower CAT activities and enhanced GSH levels. It can also be considered that the elevation of urea in PP$3\%$ and GP$3\%$ groups affects antioxidant status, as Ahmed and Ali [60] explain that increased serum urea and creatinine accelerate renal LPO with the reduction in renal GSH content, CAT, and glutathione reductase. According to our knowledge, there is no data available on the combination of GP and PP as supplemented diet for the rabbit. Therefore, it was difficult to compare the present study with previous investigation. Each treatment has certain effect on the different biochemical parameters. In conclusion, one of the most promising additives in the rabbit diet is PP, as it improved the fertility of does and increasing the number of kits, resulting from the elevation of the progesterone hormone. It also reduced triglycerides. Pomegranate has the capacity to combat hyperlipidemia with therapeutic benefits. As for the garlic supplement, it had good results in increasing fertility. 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--- title: Selected Serum Markers Associated with Pathogenesis and Clinical Course of Type 1 Diabetes in Pediatric Patients—The Effect of Disease Duration authors: - Agnieszka Ochocińska - Marta Wysocka-Mincewicz - Jolanta Świderska - Bożena Cukrowska journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051659 doi: 10.3390/jcm12062151 license: CC BY 4.0 --- # Selected Serum Markers Associated with Pathogenesis and Clinical Course of Type 1 Diabetes in Pediatric Patients—The Effect of Disease Duration ## Abstract Biochemical abnormalities in the course of type 1 diabetes (T1D) may cause the production/activation of various proteins and peptides influencing treatment and causing a risk of complications. The aim of this study was to assess concentrations of selected serum substances involved in the pathogenesis and course of T1D and to correlate their concentrations with the duration of T1D. The study included patients with T1D ($$n = 156$$) at the age of 3–17, who were divided according to the duration of the disease into those newly diagnosed ($$n = 30$$), diagnosed after 3–5 ($$n = 77$$), 6–7 ($$n = 25$$), and over 7 ($$n = 24$$) years from the onset of T1D, and age-matched healthy controls ($$n = 30$$). Concentrations of amylin (IAPP), proamylin (proIAPP), catestatin (CST), chromogranin A (ChgA), nerve growth factor (NFG), platelet-activating factor (PAF), uromodulin (UMOD), and intestinal fatty acid binding protein (I-FABP) were measured in sera using immunoenzymatic tests. There were significant differences in concentrations of all the substances except UMOD and NGF between T1D patients and healthy children. The duration of the disease affected concentrations of CST, ChgA, PAF, and NGF, i.e., proteins/peptides which could have an impact on the course of T1D and the development of complications. In long-term patients, a decrease in concentrations of CST and ChgA, and an increase in PAF concentrations were found. In the case of NGF, a decrease was observed after the initial high values, followed by an increase over 7 years after T1D diagnosis. Concluding, the results show that concentrations of selected serum indicators may change in the course of T1D. Further studies are needed to establish whether these indicators could be used in the context of predicting long-term complications. ## 1. Introduction Type 1 diabetes mellitus (T1D)—one of the most widespread diseases of our time—is a chronic disease that results from the autoimmune destruction of insulin-producing β-cells in the islets of Langerhans in the pancreas [1]. By 2022 there were 8.75 million individuals worldwide with T1D (119,995 in Poland), 1.52 million (15,220 in Poland) were younger than 20 years of age [2]. Looking at worldwide data, 530,000 new cases of T1D were diagnosed across all ages, of which 201,000 were under the age of 20. Therefore, the scale of the problem is very large [2]. The discovery and development of more physiologically active insulins applied together with continuous subcutaneous infusion pumps, and the improvement of T1D care contributed to a significant extension of T1D patients’ life span and quality. However, untreated or improperly treated disease causes many complications, both acute and chronic [3,4]. Pathogenesis of T1D has not been fully elucidated so far, and factors inducting the disease are still the subjects of many studies [5]. It is already known that great importance in the pathogenesis of diabetic complications is not only the current metabolic control but also the careful and intensive treatment of the disease from the moment of its diagnosis [6]. It is proven that changes in metabolic control, in any of the stages of the diabetes course, influence complication risks in the future, even after 20–30 years of the duration of the disease. This phenomenon, called “metabolic memory”, is probably the consequence of an increase in oxidative stress factors caused by hyperglycemia, is partly irreversible, and persists even after normalization of glycemia [7]. Abnormal glucose concentrations and metabolites generated as a result of excess hormones activate many unfavorable metabolic processes (non-enzymatic glycation of proteins, changes of the polyol and hexosamine pathways, activation of protein kinase C, oxidative stress, and tissue hypoxia). These pathological pathways lead to the failure of various organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Disturbances in growth (short height or overgrowth) and puberty (premature or delayed puberty) can also be other types of T1D complications in children [8]. Late complications in the first 5 years of diabetes in both pediatric and adult patients are sporadic, but their number increases with the duration of the disease. Macrovascular changes usually manifest themselves clinically after the onset of microangiopathic changes, especially in diabetic nephropathy. However, before the clinical manifestation of structural changes in the vessels, functional changes in the microcirculation occur first. These changes are reversible, and therefore early markers are being sought to identify the early stages of biochemical disorders preceding endothelial dysfunction [6,8]. There are still no tools for diagnosing these early stages of the development of late complications, but only for the stages of functional changes preceding the appearance of permanent structural changes visible in imaging tests. Despite the availability of high-performance omics technologies, data inconsistency and a lack of unambiguous, highly promising protein markers are observed [9,10]. Postulated glycemic control refers to keeping blood glucose levels as close to the normal range as possible in order to prevent acute and chronic complications that would result from living with glucose levels significantly above or below the desired range. In practice, it can be achieved by measuring fasting blood glucose or using glycated hemoglobin (HbA1c), a measurement of average blood glucose, over about three months. Currently, HbA1c has also been presented to play the role of an indicator of disease progression in diabetes. HbA1c has been shown to be directly related to the survival of patients with an approximately 30-year history of T1D [11]. However, it is known that HbA1c is not an ideal indicator of metabolic control [12,13,14]. Therefore, the aim of our study was to assess concentrations of selected active substances such as proteins, peptides, hormones, and others, the participation of which in the pathogenesis and course of diabetes and its complications is known or postulated, and to correlate concentrations of these indicators to the duration of T1D, as well as to compare these concentrations to those of a healthy population. We analyzed the levels of islet amyloid polypeptide/amylin (IAPP) and its prohormone—proamylin (proIAPP)—substances influencing the mechanisms of carbohydrate metabolism [15,16,17,18]; chromogranin A (ChA)—a supposed autoantigen in T1D [19,20,21]; and the product of its proteolysis catestatin (CST) [22,23], intestinal fatty acid binding protein (I-FABP)—a protein responsible for increased permeability of intestinal epithelial cells, showed to be increased in children with T1D [24]. We also included in our analysis substances potentially evaluable as indicators of late complications, neurological—nerve growth factor (NGF) [25], and vascular—platelet-activating factor (PAF) [26,27]. Finally, we assessed uromodulin, a protein secreted by the cells of the distal nephron tubules, strongly correlated with eGFR, which could be related to diabetic nephropathy in T1D patients [28]. ## 2.1. Patients and Study Design The study included 156 patients with T1D whose median age was 11 years of age (range: 3–17); 60 ($46.6\%$) boys and 66 ($52.4\%$) girls that were hospitalized at the Clinic of Endocrinology and Diabetology of the Children’s Memorial Health Institute in Warsaw. T1D was diagnosed according to the recommendations of the International Society for Pediatric and Adolescent Diabetes [29,30]. Routine serological tests were performed in The Central Laboratory (glucose, HbA1c) and in The Department of Biochemistry, Radioimmunology and Experimental Medicine (peptide-C, anti-glutamic decarboxylase (anti-GAD), anti-tyrosine phosphatase (anti-IA2), and anti-islet cell (ICA) antibodies) at the Children’s Memorial Health Institute. At least 2 autoantibodies (anti-GAD, anti-IA2, or ICA) were positive in T1D patients. T1D patients with current inflammation, hypoxia, and coexisting diseases were excluded from the study. A detailed biochemical status of the T1D patients is presented in Table 1. We have not observed the relationship of presented biochemical parameters with selected active substances assessed in this study (the analysis of the value of all r indicators in Spearman’s correlation analysis was <0.2). The T1D group consisted of 30 patients (17 girls and 13 boys) with newly diagnosed T1D (duration of diabetes < 3 months, at least one week after correcting the acid-base imbalance, i.e., normalization of blood gas results), and 126 patients (66 girls and 60 boys) with T1D lasting more than 3 years (median duration—5 years, range: 3–14). The group of long-term patients was divided according to how long it had been since onset in the following way: patients with no expected complications (first 3–5 years of disease; $$n = 77$$; 15 girls and 62 boys), patients with expected first biochemical changes indicating complications (6–7 years of disease, $$n = 25$$; 13 girls and 12 boys), and patients in which complications are highly probable (patients > 7 years of disease, $$n = 24$$; 13 girls and 11 boys). All of the patients included in the study had no documented neuropathy, hypertension, or retinopathy on the day of performing the biochemical analysis. The control group consisted of 30 apparently healthy children (14 girls and 16 boys) at a median age of 8 years (range: 4–17 years) with no history of diabetes diagnosis and with the same exclusion criteria as the study group (no comorbidities of other causes, no signs of present inflammation, no clinically significant anemia, and no signs of hypoxia). ## 2.2. Methods All active substances were assessed using the enzyme immunoassay ELISA (IAPP, proIAPP, NGF, ChgA, PAF—Cloud Clone Corp, Katy, USA; CTS—RayBio, Norcross, USA; UMOD—BioVendor, Brno, Czech Republic; I-FABP—Hycult Biotech Inc., Wayne, PA, USA) according to the test manufacturer’s instructions. The remaining biochemical tests, including HbA1c, were assessed by routine laboratory methods (Abbott Alinity ci-series assays). ## 2.3. Statistical Analysis The minimum sample size was estimated at 86 participants using Epi Info 7 (available at: https://www.cdc.gov/epiinfo/index.html; accessed on 1 February 2023). Data were analyzed using Statistica v.10.0 software (StatSoft, Inc., Tulsa, OK, USA). Standard deviations of means were used as descriptive statistics. Normal distribution was checked using the Shapiro–Wilk test and revealed a non-normal distribution of data. Differences between two independent groups were tested by the Mann–Whitney U test and between three or more subgroups by Kruskal–Wallis ANOVA by Ranks for independent groups. Correlation analysis was done with the use of the Spearman rank correlation test. If the differences were significant, post hoc analysis using the Dunn–Bonferroni test was then performed. In all tests, p-values < 0.05 were considered significant. ## 2.4. Ethical Approval The study was approved by the Local Ethics Committee from the Children’s Memorial Health Institute (18/KBE/2019, date of approval: 24 April 2019) with the written informed consent obtained from participants over 16 years of age and/or their legal representative, as appropriate. ## 3.1. Patient Characteristics The subgroups distinguished on the basis of the duration of the disease statistically differed significantly ($p \leq 0.05$) in terms of biochemical parameters reflecting carbohydrate metabolism (glucose, HbA1C, insulin), lipid metabolism (HDL cholesterol and triglycerides), as well as reflecting kidney function (creatinine). In the case of blood glucose and HbA1C, the highest concentrations were observed in newly diagnosed patients. With the duration of the disease, as a result of the implemented treatment, their concentrations decreased. However, after 7 years after the T1D diagnosis, an increase in the concentrations of both parameters was observed. Statistically significant differences between individual groups are listed in Table 1. Despite statistically significant differences between insulin concentrations in individual subgroups, all values were within the reference range of 4–16 mIU/L. Lipid profiles, regardless of the T1D duration, were within the target values recommended in the current recommendations [29]. In the case of HDL cholesterol and triglycerides, the values changed among T1D subgroups reaching a statistically significant difference, but without clinical significance. Similarly, in the case of creatinine, statistically significant changes between the subgroups were not clinically significant. ## 3.2. Concentrations of the Selected Active Substances in T1D Patients and Healthy Controls Except for UMOD and NGF levels, concentrations of tested substances were statistically significantly higher in the T1D group compared with the control group (Table 2). In the case of NFG, the differences between T1D and control groups were not significant, but the p-value was at the level of the statistical trend ($$p \leq 0.056$$). This trend was confirmed by a later analysis in more detailed subgroups (new cases vs. patients with long-term disease) (Figure 1). When the levels of tested substances in children with newly diagnosed T1D were compared with the group of children with T1D treated for at least 3 years, it was shown that the duration of T1D affected the levels of NGF, ChgA, and PAF. The levels of PAF were significantly lower in newly diagnosed T1D compared with patients with T1D duration > 3 years: 0.20 (0.11–043) vs. 0.25 (0.12–5.18) ng/mL. In contrast, NGF and ChgA levels were significantly higher in newly diagnosed patients than in those treated over 3 years: 12.7 (3.45–17.9) vs. 4.69 (0.52–804) pg/mL for NGF and 74.5 (40.5–98.5) vs. 52.5 (15.5–104) ng/mL for ChgA, respectively). ## 3.3. The Effect of Disease Duration on the Selected Active Substances’ Concentrations in T1D Children As we observed differences in T1D subgroups with shorter and longer disease duration, the whole T1D group was divided into three smaller ones (3–5 years, 6–7 years, and >7 years) and then reanalyzed. Figure 1 illustrates the differences between concentrations of active substances in these subgroups, the healthy control group, and the newly diagnosed patients. Detailed numerical data (median and range) and exact p-values are presented in the Supplementary Table S1. No effect of disease duration on IAPP, proIAPP, and I-FABP levels was observed, but concentrations of each substance statistically differed significantly between the T1D patients (in each subgroup) and the control group, except for UMOD. In contrast, concentrations of CST, ChgA, PAF, and NGF were statistically significantly influenced by the time that had passed since the diagnosis, but the direction of changes depended on the type of biomarker. In the case of ChgA—the highest concentrations were observed in patients just after the diagnosis of T1D (median 74.5 ng/mL, range 40.5–98.5) and they statistically differed significantly both from the control group (34.5 ng/mL $$p \leq 0.005$$) and the groups of patients treated for 3–5 years (52.5 ng/mL, $$p \leq 0.0001$$), 6–7 years (54.5 ng/mL, $$p \leq 0.0005$$, and >7 years (50.3 ng/mL, $$p \leq 0.000009$$). With the duration of the disease, ChgA concentration decreased, and in each time interval, it was statistically significantly lower compared to newly diagnosed patients. Although serum CST concentration did not differ between newly diagnosed T1D patients, with a median of 35.2 ng/mL (range 0.001–70.1), and those treated > 3 years, with a median of 20.1 ng/mL (range 0.001–305), the detailed analysis in subgroups of long-term patients showed the possible effect of disease duration. The highest concentrations of CST were observed in patients with newly diagnosed T1D; CST levels decreased in patients treated for 3–7 years, but 7 years after diagnosis, high values of the biomarker were observed again (Table S1). Statistically significant differences were observed between newly diagnosed patients and those treated for 3–5 years: $$p \leq 0.0008$$, median 35.2 ng/mL (range 0.000–70.1) vs. 19.7 ng/mL (0.007–95.6), patients treated for 3–5 years and patients treated for >7 years: $$p \leq 0.0008$$, median 19.7 ng/mL (0.007–95.6) vs. 27.0 ng/mL (1.45–92.3), and the group treated for 6–7 years and those treated for >7 years: $$p \leq 0.019$$, median 20.0 ng/mL (0.005–305) ng/mL vs. 27.0 (1.45–92.3) ng/mL. In the case of PAF, patients with longer disease duration had higher concentrations of this substance (Figure 1, Table S1). A statistically significant difference ($p \leq 0.05$) was observed in the subgroups treated for 3–5 years (median 0.24 ng/mL, range 0.12–5.18), 6–7 years (median 0.25 ng/mL, range 0.18–2.67), and >7 years (median 0.29 ng/mL, range 0.12–3.9) in relation to those with newly diagnosed T1D (median 0.20 ng/mL, range 0.11–0.43). The highest NGF concentration was observed in newly diagnosed patients: 12.7 pg/mL (3.45–17.9), followed by a decrease of values for patients treated for 3–5 years: 4.49 pg/mL (1.09–804), 6–7 years: 4.49 pg/mL (0.52–37.5), and after 7 years from diagnosis: 6.21 pg/mL (0.52–45.8). A statistically significant difference was observed only in patients newly diagnosed—in relation to the control group ($$p \leq 0.000004$$) and those who had been ill for 6–7 years ($$p \leq 0.002$$). ## 4. Discussion In a number of studies, selected biologically active substances were indicated as contributing to the etiology (IAPP [16,31,32,33,34,35,36], proIAPP [17,18,37], I-FABP [24]), course (CST [38,39], ChgA [40,41,42]) or the development of various complications (neuropathy—NGF [43,44,45], cardiovascular complications—PAF [26,46,47], and cardiovascular complications and nephropatia—UMOD [28,48,49]). In the current study, we assessed the diagnostic usefulness of these indicators present in T1D patients’ sera and confirmed statistically significant differences between their concentrations in the group of children with T1D and healthy children, but only some of them (NGF, ChgA, CST and PAF) were affected by disease duration. To the best of our knowledge, no one has analyzed concentrations of IAPP, proIAPP, CST, ChgA, NGF, PAF, UMOD, and I-FABP in the context of T1D duration. Our study showed that among the selected indicators, only UMOD did not show statistically significant differences between children with T1D and healthy children, but we found that UMOD levels in T1D patients were associated with serum creatinine concentration (r = −0.477, $p \leq 0.005$). Thus, this could suggest that UMOD should be rather assessed in urine than in the sera of T1D patients. Disease duration had no effect on IAPP and its precursor—proIAPP, as well as I-FABP, although the levels of these indicators were significantly higher in the sera of T1D patients compared to healthy children. An increased level of mature IAPP in the T1D group is opposite to results presented by Courtade et al. [ 17], but, like this researcher, we observed an elevated ratio of proIAPP to mature IAPP, which clearly indicates impaired proIAPP processing. It seems likely that IAPP aggregates, by inducing islet inflammation, may be a trigger or accelerator of autoimmunity in T1D. It is known that early prefibrillary aggregates that are difficult to observe histologically, may be present in the early stage of the disease, and the inflammatory properties of IAPP aggregates may play a role in the pathology of T1D [17,33,36,50]. Significantly elevated I-FABP levels in T1D patients, independent of disease duration, confirm our previous reports on epithelial damage in pediatric T1D and the utility of I-FABP as a serological marker of intestinal barrier dysfunction [24]. It is noteworthy that those substances whose concentration was not affected by the duration of the disease (IAPP, proIAPP, and I-FABP) are markers described as taking part in the pathomechanism of T1D. Contrary to this observation, the concentrations of CST, ChgA, PST, and NGF varied in patients at different times since the onset of T1D. We did not observe one specific trend for all the indicated substances. This finding confirms previous reports showing that these substances could be associated with the T1D course and various late complications [26,38,39,40,41,42,43,44,45,46,47]. Our data on ChgA are consistent with the reports identifying ChgA as an autoantigen in T1D [19,51], and suggesting that altered ChgA levels may reflect changes in β—cell integrity [52]. Auto-reactive T cells targeting β-cell antigens are known to play a key role in β-cell destruction in T1D [53]. In this context, ChgA as an autoantigen localized in β—cell granules seems to be an attractive target for autoimmune reactions. Determination of ChgA concentration in patients’ sera may therefore potentially serve as an important biomarker of prediabetes. The highest concentration of ChgA observed by us in children with newly diagnosed T1D was also indicated by Xu et al. in adult T1D patients [52]. They reported that regular oral administration of verapamil in adult patients with T1D resulted in a decrease in ChgA levels, which remained at lower levels during treatment, and elevated levels of ChgA at the onset of the disease did not change in people from the control group who did not take verapamil. Our results in the group of healthy children are also consistent with their report, in which the level of ChgA in the serum of the healthy control group was about two times lower compared to those with T1D. Results opposite to our observations were obtained by Herold et al. [ 40], but it is worth noting that the researchers showed only a small but constant increase ($$p \leq 0.0410$$) in the level of ChgA depending on the duration of T1D. However, it should be noted that in this study, the duration of T1D in included patients was markedly longer (average 13.5 years) than in patients involved in our analysis. In addition, T1D patients with high levels of ChgA had enterochromaffin-like cell hyperplasia or autoimmune gastritis, i.e., conditions that were not found in the T1D children analyzed in our study. We speculate whether the lower concentrations observed in patients treated for more than 3 years are due to the breakdown of ChgA into protein cleavage products. The conditions under which ChgA decomposes are not fully known and described. Therefore, it would be worth assessing the concentration of other biologically active peptides, the precursor of which is ChgA: pancreastatin, WE-14, serpinin, and chromofungin [54,55]. Beta granule proteins (like ChgA) should not normally elicit an immune response, thus aberrant post-translational modification of the peptides is a possible hypothesis for how β—cell self-antigens are generated. Unlike ChgA, there are no clear data on CST in T1D. It is known that CST is critical to maintaining metabolic and immune homeostasis by regulating immune cell infiltration and macrophage differentiation [56]. In addition, according to Ying et al., CST may be able to control hepatic glucose production, improve sensitivity to insulin, and have direct anti-inflammatory effects [57]. In our study, CST concentrations were statistically significantly higher in T1D patients than in the group of healthy people. Thus, this is in contrast to the observation of decreased CST levels in T2D patients previously reported by the researchers [57,58,59]. It should be emphasized, however, that the pathomechanism of both types of diabetes is different, and T1D should rather be compared with other autoimmune diseases. In this context, our results on CST concentrations during T1D are consistent with those shown in other autoimmunology diseases—inflammatory bowel disease [60]. In our study, the highest concentrations of CST were observed in patients with newly diagnosed T1D and those treated for more than 7 years. In patients who had been ill for more than 3 years but less than 7 years CST concentrations decreased. It would be desirable to investigate more closely whether the observed elevated levels in children with T1D are a compensatory mechanism for disturbances in glycemic homeostasis. In the case of PAF, we showed that its concentrations were significantly higher in T1D patients who were ill for over 3 years compared to newly diagnosed patients, and this result is in line with other authors indicating that an increased level of PAF may indicate vascular complications in T1D patients. Cavallo-Perin et al. observed elevated PAF levels in patients with T1D and microalbuminuria, i.e., a manifestation of extensive vascular damage, and they suggested that PAF can be an indicator of micro- and macroangiopathy [46]. Nathan et al. indicate that elevated PAF levels may perpetuate hyperglycemia and promote or exacerbate micro- or macrovascular complications in T1D patients [26]. Ersoy et al. also emphasize that the high level of PAF detected in their study in T1D patients with long-term diabetes, compared to the group of healthy people, may be associated with vascular complications [47]. Since vascular complications are observed after many years of diabetes, and our pediatric patients did not present clinical vascular complications we suggest that PAF could be useful as a marker of early micro- and macrovascular changes in the course of T1D in children. However, further studies on T1D in children are needed to confirm this relationship. We also presented that the concentrations of NGF are influenced by T1D duration. The high NGF levels in newly diagnosed children can be explained by a stress-induced increase [61], and this result is in line with the observations of other researchers [62]. However, it should be emphasized that the observed decrease in NGF levels in the course of diabetes cannot be clearly interpreted. Many authors show that neurological complications induce a drop in serum NGF concentration [43,44,45]. It was shown that patients with T2D and neurological complications had lower levels of NGF compared to those without complications [63]. Moreover, there is no clear position on the NGF reference ranges for a healthy population. The concentrations described in the literature range from a few [64,65] to several dozen pg/mL [61,66,67]. Therefore, it is important to establish the norms of NGF for children and further research on this peptide. ## 5. Limitations and Strengths To the best of our knowledge, this is the first study analyzing concentrations of IAPP, proIAPP, CST, ChgA, NGF, PAF, UMOD, and I-FABP in relation to diabetes duration in a pediatric population. However, we are aware that results should be interpreted with caution due to the relatively small amount of data on the concentrations of selected substances in the population of a healthy population. Due to the lack of these data, it is difficult to compare the obtained concentrations in the group of patients, especially since the literature reports are often contradictory. Evidently further studies are necessary in order to confirm the role of study indicators in the pathophysiology and course of T1D. We recognize that the presented results would be more accurate if we were able to observe patients over a longer period of time. In order to confirm our suggested conclusions, we plan to follow the patients participating in this study and perform the same tests again before our patients are 18 years of age. Exciting new questions and new answers may arise when we additionally analyze the tested substances in relation to glycemic control or biochemical parameters. ## 6. Conclusions The current study presented that concentrations of selected serum substances such as CST, ChgA, NGF, and I-FABP, prohormones/hormones (IAPP, proIAPP), and other active substances (PAF) differ between T1D patients and healthy controls. The level of some of them (CST, ChA, PAF, and NGF) have been shown to be dependent on the duration of T1D. However, further research is needed to confirm the role of these indicators in clinical practice, in particular in terms of using them as biomarkers in the course of diabetes in children and predicting long-term complications. ## References 1. Del Chierico F., Rapini N., Deodati A., Matteoli M.C., Cianfarani S., Putignani L.. Pathophysiology of Type 1 Diabetes and Gut Microbiota Role. Int. J. Mol. Sci. (2022) 23. DOI: 10.3390/ijms232314650 2. 2. IDF IDF Diabetes Atlas10th ed.IDFBrussels, Belgium2022Available online: https://Diabetesatlas.Org/(accessed on 1 February 2023). IDF Diabetes Atlas (2022) 3. 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--- title: Application of Computational Data Modeling to a Large-Scale Population Cohort Assists the Discovery of Inositol as a Strain-Specific Substrate for Faecalibacterium prausnitzii authors: - Shaillay Kumar Dogra - Adrien Dardinier - Fabio Mainardi - Léa Siegwald - Simona Bartova - Caroline Le Roy - Chieh Jason Chou journal: Nutrients year: 2023 pmcid: PMC10051675 doi: 10.3390/nu15061311 license: CC BY 4.0 --- # Application of Computational Data Modeling to a Large-Scale Population Cohort Assists the Discovery of Inositol as a Strain-Specific Substrate for Faecalibacterium prausnitzii ## Abstract Faecalibacterium prausnitzii (F. prausnitzii) is a bacterial taxon in the human gut with anti-inflammatory properties, and this may contribute to the beneficial effects of healthy eating habits. However, little is known about the nutrients that enhance the growth of F. prausnitzii other than simple sugars and fibers. Here, we combined dietary and microbiome data from the American Gut Project (AGP) to identify nutrients that may be linked to the relative abundance of F. prausnitzii. Using a machine learning approach in combination with univariate analyses, we identified that sugar alcohols, carbocyclic sugar, and vitamins may contribute to F. prausnitzii growth. We next explored the effects of these nutrients on the growth of two F. prausnitzii strains in vitro and observed robust and strain-dependent growth patterns on sorbitol and inositol, respectively. In the context of a complex community using in vitro fermentation, neither inositol alone nor in combinations with vitamin B exerted a significant growth-promoting effect on F. prausnitzii, partly due to high variability among the fecal microbiota community from four healthy donors. However, the fecal communities that showed an increase in F. prausnitzii on inulin also responded with at least $60\%$ more F. prausnitzii on any of inositol containing media than control. Future nutritional studies aiming to increase the relative abundance of F. prausnitzii should explore a personalized approach accounting for strain-level genetic variations and community-level microbiome composition. ## 1. Introduction Faecalibacterium prausnitzii (F. prausnitzii) belongs to the Ruminococcaceae family (phylum Firmicutes) and is one of the most abundant bacteria in the human gut [1]. It has been demonstrated to be associated with (the severity or incidence) of different diseases in humans and to play a causative role in mouse models [1]. Reduced abundance of F. prausnitzii has consistently been found in disease conditions such as inflammatory bowel disease (IBD) [2], irritable bowel syndrome (IBS), metabolic syndrome and diabetes [3,4,5,6], non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) [7], colorectal cancer (CRC) [8], obesity, and frailty [9]. Functionally, F. prausnitzii contributes to the modulation of the immune system and attenuation of inflammation through multiple mechanisms that can work independently or synergistically. More precisely, butyrate produced by F. prausnitzii and other butyrate-producing bacteria reduces intestinal mucosal inflammation by inhibiting nuclear factor kappa-light-chain-enhancer of activated β-cells (NF-κβ) activation, upregulating peroxisome proliferator-activated receptor-γ expression, and inhibiting interferon-γ expression [9]. In addition, F. prausnitzii modulates inflammatory signals by releasing immune-suppressing molecules such as salicylic acid [10] and microbial anti-inflammatory molecules (MAM) [11]. The therapeutic potential of F. prausnitzii through the secretion of microbial anti-inflammatory molecules has been demonstrated in a mouse model of IBD [12]. Together with association-based evidence from observational and clinical studies, scientists have argued for the use of F. prausnitzii as a probiotic [9]. According to International Scientific Association for Probiotics and Prebiotics (ISAPP), the definition of probiotics is “live microorganisms that, when administered in adequate amounts, confer a health benefit on the host” [13]. F. prausnitzii is currently not accepted as a probiotic due to the lack of clinical evidence on its safety and efficacy. The extreme oxygen sensitivity of F. prausnitzii imposes practical challenges to the production, transportation, storage, and manufacturing of probiotic products to be evaluated in a clinical setting. Alternatively, the relative abundance of F. prausnitzii in the human gut can be affected by multiple factors such as antibiotic usage [14] and diet [15,16]. More precisely, some food ingredients have been shown to increase the abundance of F. prausnitzii in humans. Thus, a prebiotic approach aiming to enhance health by increasing the abundance of commensal F. prausnitzii could be a viable strategy. Indeed, F. prausnitzii’s relative abundance in the human gut appears to be associated with diet healthiness (based on a healthy eating index) [17]. More specifically, consumption of prebiotic-type ingredients such as inulin and fructo-oligosaccharides was found to increase F. prausnitzii in obese women [18], IBS patients [19], and healthy individuals [20]. Treatment with polydextrose and chickpea oligosaccharides (raffinose) also leads to the increase in F. prausnitzii abundance in fecal communities of healthy subjects [21,22]. Yet, deconvoluting the effects of individual nutrients or food items on F. prausnitzii in the gut from the rest of the diet remains challenging. Thus, our aim was to identify nutrients that could be used to boost F. prausnitzii abundance in the human gut. To this end, we applied a machine learning algorithm on dietary records and 16S rRNA gene sequencing data collected on 3816 participants of the American Gut Project (AGP) to identify new nutrients that may link to the relative abundance of F. prausnitzii. We next evaluated the impact of selected nutrients on the growth of F. prausnitzii in vitro using pure culture of single strains and fermentation of healthy human fecal communities. ## 2.1. Data The intersection of three datasets (metadata, microbiota, and VioScreen food frequency questionnaires (FFQ)) from American Gut Project (AGP) [23] was used in this study and represented a sample size of $$n = 3816$$ (Supplementary Figure S1). Raw 16S rRNA gene sequencing data from stool samples was downloaded from the Qiita repository https://qiita.ucsd.edu/study/description/10317 (accessed on 4 September 2019) [24]. Data were processed following the same analytical steps as in the original publication [23]. Briefly, raw sequencing reads were firstly denoised and sub-operational taxonomic units (sOTUs) were generated using deblur v. 1.0.2 [25]. Then, sOTUs matching bacteria potentially blooming under room temperature storage conditions were removed following the instructions of https://github.com/knightlab-analyses/bloom-analyses (accessed on 31 July 2019). Multiple rarefactions were performed 10 times at a threshold of 1250 sequences per sample. Finally, representative sequences of each sOTU were annotated using the QIIME2 v. 2017.4 RDP classifier on Greengenes $99\%$ v. 13.8 [26]. Nutrient data as provided through VioScreen FFQ analysis were downloaded from the AGP data File Transfer Protocol (FTP) site http://ftp.microbio.me/AmericanGut/raw-vioscreen/vioscreen_dump.tsv.gz (accessed on 31 July 2019). Coded names and full descriptions of the nutrients and the corresponding units of nutrients are shown in Supplementary Table S1. The metadata file “10317_20220801-114642.txt” was downloaded on from the Qiita repository https://qiita.ucsd.edu/study/description/10317 (accessed on 15 September 2022). ## 2.2. Modeling to Predict the Abundance of F. prausnitzii Using Nutrient Intake Data Predictive models were built to determine the relative abundance of F. prausnitzii of an individual subject based on nutrient intake values. In particular, the model predicted the F. prausnitzii relative abundance by several nutrient feature parameters to determine the F. prausnitzii abundance category of the subject as defined in Supplementary Table S2 (e.g., “Low” or “notLow”; “High” or “notHigh”; “Low” or “High”). A cube root transformation was applied to the F. prausnitzii abundances to make them normally distributed before binning them into these different categories (Supplementary Figure S2). Data were split into a training set “Train” ($80\%$) and a testing set “holdout/Test set” ($20\%$). For optimal model performance, we used random downsampling to match the number of subjects between the abundance groups. For example, we randomly downsampled in notLow group to match the subject number of Low group. The Train set was used by different machine learning algorithms (RandomForests, XGBoost; available from scikit-learn in Python programming language [27]) to train a model. The learning from the data was completed in a cross-validated manner where Train data were split into partitions with some parts used for training the model and others for internal testing (repeated k-fold cross-validation, i.e., 3 folds, 3 repeats). The holdout/Test set was used only for checking the performance of the final trained model and was not used during the model training phase. A total of 9 models (model A to model I) were made, and the cut-offs used to define the groups, the type of machine learning algorithm used, and other parameters for each of the models are provided in Supplementary Table S2. Receiver operating characteristic (ROC) curves were generated for these models and area under the curve (AUC) was reported. The best performing model was then selected from the different binning categories of Low vs. notLow, High vs. notHigh, and Low vs. High (Supplementary Table S2). ## 2.3. Culture Conditions for Testing Selected Nutrients F. prausnitzii strains A2-165 and 27768 were obtained from the Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSMZ, Leibniz Institute, DSMZ German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany) and American Type Culture Collection (ATCC), respectively. Culture of F. prausnitzii followed the method of Duncan et al. [ 28] using Hungate culture tubes in an anaerobic chamber (H2:CO2:N2, 5:10:$85\%$, Type B, Coy Laboratory Products, Grass Lake, MI, USA). To prepare the working cultures, lyophilized F. prausnitzii (ATCC 27768) were enumerated anaerobically with 20 mL ATCC media 2107 consisting of trypose 10 g/L, beef extract 10 g/L, yeast extract 3 g/L, dextrose 5 g/L, NaCl 5 g/L, starch 1 g/L, L-cysteine HCl 0.5 g/L, sodium acetate 3 g/L, resazuim ($0.025\%$) 4 mL/L in dd water for 3 days. For each experiment, 0.5 mL of homogenized live liquid culture was added to 9 mL freshly prepared yeast casitone fatty acid broth (YCFA) media in a Hungate tube under an anaerobic condition. Growth of bacteria was evaluated by the measurement of optical density at 600 nm (Biowave WPA CO8000—WPA Cambridge, UK) after incubation at 37 °C on a rotating platform inside of an anaerobic chamber. Glucose (Sigma-Aldrich, Schaffhausen, Switzerland) at 10 mM was used as a control carbohydrate source to verify that the strains grew under the assay conditions. To test the ability of F. prausnitzii to grow on different carbon sources, glucose was replaced by the same concentration of inositol, sorbitol, erythritol, pinitol, or xylitol prepared with sterile ddH2O that was pre-flushed with N2 gas. The effect of vitamins was tested at the final concentration of 1 μg/10 mL for vitamins B5 and B6, at 0.05 μg/10 mL for vitamin B12 or 0.1 μg/10 mL for vitamin A and D in the YCFA media with either glucose or inositol as the main carbon source. YCFA media were autoclaved at 121 °C for 15 min and were transferred to an anaerobic chamber till use. L-cysteine-HCl, thiamine hydrochloride (T4625-5G, Sigma-Aldrich, Schaffhausen, Switzerland), and riboflavin (R4500, Sigma-Aldrich, Schaffhausen, Switzerland) were first sterile filtered (0.2 μm, media bottle filtration unit with polyethersulfone (PES) membrane, VWR No. 514-0297) and added to the media prior to each experiment and the pH was adjusted to 6.7 with NaOH immediately before the start of the experiment. ## 2.4. Batch Fermentation Fecal samples of healthy volunteers were collected under a protocol approved by Lausanne ethical committee (CER-VD) (authorization number: 2020-00304). Inclusion criteria are healthy participants aged 18–60 years old who provide informed consent and are willing to follow the clinical study protocol. The exclusion criteria are [1] following a particular dietary regime such as vegan, vegetarian, ketogenic, or paleo diet; [2] experiencing chronic or recurrent diarrhea with spontaneous bowel movement more than twice a day; [3] antibacterial/antifungal therapy during the 3 months prior to study enrollment; [4] medications or supplements that are known to alter gut function or gut microbiota (i.e., acid antisecretory drugs, pre-/probiotics supplements, laxatives) during the 4 weeks prior to study enrolment, [5] prior gastrointestinal surgery, [6] alcohol intake higher than 2 servings per day; [7] artificially sweetened beverage intake higher than 1000 mL/per day; [8] current or history of gastrointestinal diseases. Preparation of stool samples for in vitro fermentation followed the procedure described by Van den Abbeele et al. [ 29]. Freshly collected stool samples were placed in an air-tight jar equipped with AnaeroGenTM (Sigma-Aldrich, Schaffhausen, Switzerland) to reduce exposure to ambient oxygen. Once inside an anaerobic chamber (Coy Laboratory Products, Grass Lake, MI, USA), fecal materials were diluted 10 times (w/v) in anaerobic phosphate buffer (0.1 M of NaH2PO4 and 0.1 M of Na2HPO4 in 2:1 ratio) containing $10\%$ glycerol and the aliquots of fecal stocks (25 mL) were stored at −80 °C for later use. In vitro fermentation experiment carried in Hungate tubes where 0.25 mL of fecal stock solution was inoculated to 10 mL of a casitone-supplemented oligotrophic medium: casitone (10 g/L), L-cysteine ($0.05\%$), NaCl (8 g/L), KCl (0.2 g/L), Na2HPO4 (1.15 g/L), KH2PO4 (0.2 g/L) at pH 7.3 as starting of fermentation [30]. A total of four different fecal samples were tested in this study. Inulin or inositol at 10 mM was added to the basic culture media, and vitamins B5, B6, B12, A, and D were included in the relevant groups at the same concentrations as pure culture experiments mentioned above. Samples were collected at times 0, 6 h, 24 h, and 48 h from the start of the experiment for the quantification of F. prausnitzii and metabolomic analysis. ## 2.5. Bacterial DNA Extraction Bacterial DNA was extracted using QIAamp Fast-DNA Mini Kit (Qiagen, no: 51604, Hilden, Germany) following the manufacturer’s recommended procedure. In short, in vitro fermentation samples (1 mL) were mixed an equal amount of InhibitEX buffer (Qiagen, Hilden, Germany) in a Lysing Matrix B tube before two steps of homogenization with Fastprep (M.P. Biomedicals, Irvine, CA, USA). Lysate was further prepared by centrifugation, proteolytic digestion with Protease K, and incubation (10 min). Then, DNA was extracted and purified with QIAamp spin column. The concentration of resulting DNA was measured by fluorescent method using Varioskan Lux (ThermoFisher Scientific, Zug, Switzerland) and PicoGreen (ThermoFisher Scientific, Zug, Switzerland). DNA samples were stored at −20 °C before the quantification of F. prausnitzii. ## 2.6. Quantification of Total Bacteria and F. prausnitzii by Real Time PCR Quantification of total bacteria and F. prausnitzii was performed with real-time PCR using the ABI-PRISM 7700 Sequence Detection System (Applied Biosystems, Foster City, CA, USA) in duplicates. Quantification of total bacteria was performed in a total volume of 25 µL reagent mix using the Perfecta MasterMix (Quantabio, PerfeCta® qPCR ToughMix® ROX, Beverley MA, USA), containing 300 nM of each of the forward (f: TCCTACGGGAGG CAGCAGT) and reverse primers (r: GGACTACCAGGG TATCTAATCCTGTT) and 175 nM of fluorogenic probe (FAM-CGTATTACCGCG GCTGCTGGCAC-BHQ) as described by Nadkarni et al. [ 31]. The amplifications of DNA were 95 °C for 10 min and 50 cycles of 95 °C for 15 s and 60 °C for 1 min. Detection of F. prausnitzii follows the method described by Lopez-Siles et al. [ 32]. In short, PCR reactions were carried out in 20 µL containing TaqMan Universal PCR Master Mix, 300 nM of each of the forward (Fpra 428 F TGTAAACTCCTGTTGTTGAGGAAGATAA) and reverse (Fpra 583 R GCGCTCCCTTTACACCCA) primers and 200 nM of Probe (Fpra 493 PR 6FAM-CAAGGAAGTGACGGCTAACTACGTGCCAG-TAMRA). Data analysis made use of Sequence Detection Software version 1.6.3 supplied by Applied Biosystems (Foster City, CA, USA). ## 2.7. 1H-Nuclear Magnetic Resonance (NMR) Metabolomics Frozen samples from in vitro fermentation were thawed at room temperature before centrifugation for 10 min at 10,000× g at 4 °C. The supernatants (300 μL) were added to 300 μL sodium phosphate buffer 0.075 M at pH 7.4, vortex mixed and 560 μL were transferred to 5 mm NMR tubes. The samples were then analyzed by 1D 1H-NMR in a 600 MHz Bruker spectrometer at 300 K. A set of 2D NMR experiments (1H J-Resolved, 1H-1H COSY, and 1H-13C HSQC) were acquired for selected samples to aid metabolite identification. All NMR spectral acquisition and pre-processing were completed under the control of TopSpin 4.0.9 (Bruker BioSpin, Rheinstetten, Germany), and the automated submission of a sequence of samples was performed using ICON-NMR 5 (Bruker BioSpin, Rheinstetten, Germany). Metabolite annotation was performed by comparing metabolite signals to those of Bruker BIOREFCODE library and public database Human Metabolome Database (HMDB) [33]. To analyze the data, 1D NMR spectra were imported into R statistical software environment (version 4.1.1, R Foundation for Statistical Computing, Vienna, Austria) [34] using the AlpsNMR package [35], and intensities and chemical shifts were interpolated to obtain a consistently shared ppm axis for all spectra between −0.5 and 10 ppm. Residual signal of water (4.70 to 4.9 ppm) was removed. Targeted peak integration was performed using a numeric integration automated routine in R statistical software. The integrated data were log-transformed prior to statistical analysis. Metabolic profile was visualized by a principal component analysis (PCA) performed using unit-variance scaling. ## 2.8. General Statistical Analysis Comparisons of F. prausnitzii relative abundance between groups were performed with Kruskal–Wallis rank sum test followed by post hoc Dunn test. Wilcoxon rank-sum test was used to compare the intake of nutrients between Low and notLow F. prausnitzii categories and Benjamini–Hochberg method was applied to control the false discovery rate (0.05). Descriptive statistics on the Healthy Eating Index-2010 were based on data published by the United States Department of Agriculture (https://fns-prod.azureedge.us/sites/default/files/media/file/HEI2010_Age_Groups_2011_2012.pdf, accessed on 1 December 2022). The above analyses were performed using the R statistical software, v 4.1.1., R Foundation fo Statistical Computing, Vienna, Austria. Data are expressed as mean ± Standard error of the mean (SEM) for data from in vitro culture and fermentation experiments. Comparisons between the groups were examined with one-way ANOVA followed by Tukey multiple comparisons test using GraphPad Prism version 9.2.0 for Windows (GraphPad Software, San Diego, CA, USA). ## 3.1. Characteristics of the Study Subjects We used microbiome and dietary data collected on 3816 individuals from the AGP cohort [23]. The full description of the cohort is shown in Supplementary Table S3. There is a higher percentage of females ($59.4\%$) than males ($38.9\%$), and participants’ self-reported country of residence is primarily from the US ($43.3\%$), followed by the UK ($21.7\%$) and Australia ($1.5\%$). The average age of the study population is 51.3 ± 15.6 years old (mean ± standard deviation (SD)), and a large portion falls into the normal Body Mass Index (BMI) category ($54.9\%$) with some being overweight ($28.9\%$), obese ($9.5\%$) and underweight ($4.4\%$). In terms of dietary preference, $76.8\%$ declared as omnivores and the remaining subjects follow vegetarian ($4.8\%$), vegan ($3.2\%$), and other, e.g., tribal diets (Supplementary Table S3). Quality of nutrition intake as measured by Health Eating Index (HEI) is 66.34 ± 1.38 for children (2–17 years, $$n = 68$$), 70.8 for adults (18–64 years, $$n = 2686$$), and 71.54 ± 0.32 for older adults (≥65 years, $$n = 853$$). The HEI scores appear to be higher in all age groups of AGP subjects than in the age-matched general US population (NHANES 2011–2012), although a statistical comparison was not possible due to the different methods in collecting dietary intake information (Table 1). Interestingly, we found significant declines in F. prausnitzii abundance with age (Kruskal–Wallis rank sum test, $$p \leq 6.9$$ × 10 − 5, Dunn test 20 s vs. 50 s adj $$p \leq 0.04$$; 20 s vs. 60 s adj $$p \leq 0.03$$, Supplementary Figure S3). ## 3.2. Discovery of Nutrients Associated with the Abundance of F. prausnitzii To identify nutrients that can predict the relative abundance of F. prausnitzii in the gut ecosystem as estimated from fecal sampling, random forest and XGBoost machine learning models with three-fold cross-validation were generated using 251 nutrition-related features extracted from FFQs. Among all considered models, model E (Low vs. notLow with cut-off based on mean—1SD, Supplementary Table S2) performed the best with an AUC-ROC of 0.65 ± 0.02 for the training ($$n = 896$$) and 0.68 ($$n = 764$$) for the test set (Figure 1a,b). Using the agnostic technique SHapley Additive exPlanations (SHAP) [36] to explain predictions of the model, we identified positive contributions of inositol, xylitol, saturated fatty acid 22:0, a-carotene, galactose, and vitamin A to the abundance of F. prausnitzii whereas d-tocopherol, lycopene, sucrose, and betaine displayed a negative relationship (Supplementary Figure S4A–L). To complement the above results, we performed univariate analysis (Kruskal–Wallis test) to compare nutrient intakes between the population split according to F. prausnitzii relative abundance being Low or notLow, using the same definition of the bins as the best abovementioned model. A total of 11 nutrients were significant after passing the false discovery rate (Wilcoxon rank sum test, adjusted p-value (p.adj) < 0.05, e.g., alcohol, inositol, aspartame, beta-cryptoxanthin (betacryp), beta-carotene (betacar), total vitamin A activity International Units (vita_iu), total vitamin A activity retinol equivalents (vita_re), alpha-carotene (alphacar), pectins, total vitamin A activity retinol activity equivalents (vita-rae) and lutein + zeaxanthin (lutzeax) (Supplementary Table S3)). When comparing the two F. prausnitzii groups (low and notlow) with nutrient intakes (Supplementary Table S4) or intake normalized to 2000 kcal, alcohol, inositol, aspartame, betacryp, and alphcar remained significantly different (Supplementary Table S5, Wilcoxon rank sum test, p.adj < 0.05). ## 3.3. Growth of F. prausnitzii on Inositol-Based Media Is Strain Dependent Out of the top nutrients featured in the above analyses, few have previously been shown to support the growth of F. prausnitzii in a culture condition, namely: sucrose, maltose, and galactose [28,37]. We, therefore, selected some of those nutrients to test their potential to enhance F. prausnitzii growth in vitro, namely: carbocyclic sugar (i.e., inositol) and sugar alcohols (i.e., xylitol, and sorbitol; Figure 1c and Supplementary Figure S4A,B,K). Briefly, we measured the growth of two strains of F. prausnitzii 27786 and A2-165 representing different phylogenic groups of the bacteria [38] for a period of 48 to 72h on either inositol, xylitol, erythritol, or sorbitol as a primary carbon source in a YCFA media. We observed that growth under the various tested conditions was strain dependent. Growth of F. prausnitzii A2-165 on media prepared with sorbitol was comparable to that observed with glucose as the most efficient carbon substrate followed by inositol and erythritol (Figure 2a) and was further diminished with xylitol to a level close to that with basic YCFA media without any carbon substrate ($$p \leq 0.0581$$). In contrast, the ATCC 27768 strain grew equally on glucose, erythritol, and sorbitol equally, while inositol and xylitol failed to support its growth (Figure 2b). We next investigated whether F. prausnitzii responds differently with increasing amounts of inositol or in combination with other carbon sources. On the inositol-based YCFA media, the growth of A2-165 and 27768 strains only marginally increased compared with YCFA alone (Figure 3a,b, $$p \leq 0.0006$$ for A2-165 and $$p \leq 0.0004$$ for 27768). Doubling the amount of inositol in the media led to $55\%$ more growth with the A2-165 strain (Figure 3a, $p \leq 0.0001$) but not with the 27768 strain (Figure 3b, $$p \leq 0.7151$$) when compared with normal amounts of inositol. To further illustrate the strain-specific substrate utilization, a combination of glucose with inositol also increased the growth of strain A2-165 by $21.4\%$ ($p \leq 0.0001$) compared to glucose alone, while the combination slightly reduced the growth of 27768 by $6.3\%$ ($p \leq 0.0001$). Finally, the addition of inositol to sorbitol promoted the growth of the A2-165 strain by $64.4\%$ and $23.7\%$ compared to sorbitol alone ($p \leq 0.0001$), while only a minimal effect of $6.1\%$ was observed on strain 27768 ($p \leq 0.0001$; Figure 3c,d). To further support the predictive potential of the machine learning approach, we also tested whether nutrients predicted to have a negative impact on F. prausnitzii would have similar effects experimentally. Results showed that lycopene significantly suppressed the growth of A2-165 by $31.4\%$ ($$p \leq 0.039$$), especially with glucose as the main carbon source (Supplementary Figure S5A) while betaine failed to alter the growth pattern of the A2-165 strain (Supplementary Figure S5B). ## 3.4. Responses of F. prausnitzii to Nutrients in a Mixed Community In a mixed community such as the human gut microbiota, F. prausnitzii may compete or work synergistically with other species for nutrients. Hence, the response of F. prausnitzii to nutrients may highly depend on an ecological context, which could explain the discrepancy between the model predictions and the in vitro observations described above. Therefore, we tested the effects of nutrient supplementation on F. prausnitzii growth by quantitative PCR (qPCR) in an in vitro fermentation system with adult human stool samples. Inositol was chosen as the main energy source instead of sorbitol because sorbitol has not been shown to affect the composition of gut microbiota [39] and inositol consistently differentiated F. prausnitzii categories in machine learning and univariate analyses. In addition, studying isolated sorbitol outsides of fruits and vegetables limits the translational value because sorbitol as a part of Fermentable Oligosaccharides, Disaccharides, Monosaccharides, and Polyols (FODMAP) is not well tolerated by some people [40]. Inositol was also tested alone (inositol) or in combination with B vitamins, specifically B5, B6, and B12 (VitBs + inositol). A dedicated group with only the three vitamin Bs without inositol (VitBs) was established because they were not only predicted by the model but also essential for F. prausnitzii [41]. Moreover, we included vitamins A and E which were also identified in the models together with inositol, and B vitamins (B5, B6, and B12) to create a comprehensive nutrition mixture (Full). Finally, inulin was used as positive control based on previous reports of a positive effect on the growth of F. prausnitzii [39]. Effects of nutrients on F. prausnitzii growth were tested for a period of 48 h using fecal samples from four individual donors as replicates in a casitone-based oligotrophic media. With most interventions, we observed a non-significant increase in F. prausnitzii compared to the control, especially after 24 h (Figure 4a,b). A high degree of heterogeneity in the response was observed across fecal donors (Supplementary Figure S6A–D). For instance, treatment with inulin resulted in a 24.5- and 10.6-fold increase in F. prausnitzii at 24 h compared to control in donor 2 (D2) and 3 (D3), respectively, while no effects were observed with donor 1 (D1) and 4 (D4). Inositol alone or inositol with vitamin supplementations also triggered an increase in F. prausnitzii by at least $50\%$ compared to control in D2 and D3 communities, and yet no effects were observed with D1 and D4 (Supplementary Figure S6A–D). Next, we performed regression analysis to examine the relationship between inositol and F. prausnitzii. Only data from the groups with added inositol and the time points 6, 24, and 48 h were included in the analysis. As shown in Figure 4c, the number of F. prausnitzii is weakly and inversely associated with the amount of inositol, a result in line with the single strain experiments mentioned above. To further understand the heterogeneity of these results, we next conducted metabolomics profiling of the fermented media at all time points. PCA with 34 identified and integrated NMR signals of metabolites suggested that time had more effects on the metabolomic variance during the fermentation than donor or treatment. While the 6 h time points clustered closely with the baseline samples, a drastic change in the overall metabolic profile was observed at 24 and 48 h (Figure 5a,b). PCA loadings showed that from 6 h to 24 h of fermentation, short-chain fatty acids, trimethylamine, alcohols, monamine aromatic amino acid-derivatives, diamines, and related metabolites increased, while glycerol and some amino acids (threonine, tryptophan, tyrosine, and arginine) decreased (Figure 5c). Lactate, formate, and succinate increased over 24 h before being consumed at 48 h. Focusing more precisely on the metabolization of the tested substrates, we observed in all four donors, that inositol was fully consumed over time (Supplementary Figure S7A–C) independently of vitamin supplementation, and the rate of consumption was not related to the level of F. prausnitzii. Finally, as F. prausnitzii is one of the key butyrate-producing bacteria [42], we examined the correlation between F. prausnitzii and butyrate in the batch fermenters. Butyrate levels were undetectable at times 0 and 6 h and were indistinguishable among groups at 24 h (Supplementary Figure S8A). At 48 h, butyrate was higher in the inulin group than in the Full and VitBs+inositol groups (Supplementary Figure S8B). Taking all samples into account, we observed a positive correlation between levels of F. prausnitzii and butyrate concentration (Pearson correlation, $r = 0.6252$, $p \leq 0.0001$; Figure 6). Even after removing the leverage point, the result is still significant ($p \leq 0.0001$, $r = 0.4661$). This correlation remained significant when considering D3 alone while only a trend was observed for D1 and D4 (Supplementary Figure S9). ## 4. Discussion F prausnitzii is amongst the most abundant anaerobic bacteria in the human gut, and scientific evidence supports its beneficial role in health. In the present study, we applied a machine learning algorithm to microbiome composition and food frequency questionnaires data collected on 3816 AGP participants and identified nutrients that may influence the abundance of F. praustnizii. Many of the top nutrients, such as galactose (rank #8), sucrose (rank #10), and maltose (rank #16) have been shown in the literature to support the growth of F. prausnitzii in a culture condition. We, therefore, focused on examining the potential effect of other nutrients on the growth of F. prausnitzii in vitro. Subsequent in vitro experiments with two strains of F. prausntizii demonstrated that inositol, sorbitol, and lycopene could enhance the growth of at least one of the selected bacterial strains as predicted by the model. On the contrary, xylitol, erythritol, and betaine failed to increase F. prausnitzii growth under in vitro conditions suggesting that other factors than these nutrients alone may be at play. More importantly, we observed strain-dependent responses of F. prausnitzii to most nutrients or nutrient combinations. In addition, when the effects of nutrients on F. prausnitzii were tested in the context of complex communities using in vitro fermentation, we observed a high degree of variations among the four fecal donors, rendering no significant changes in the number of F. prausnitzii. Interestingly, we observed a significant positive correlation between F. prausnitzii and butyrate concentration during fermentation, supporting the use of in vitro fermentation models to study microbial metabolism. A citizen science project such as AGP offers a large dataset for examining the relationships between gut microbiota and a wide variety of factors such as dietary patterns, lifestyle, diseases, etc. [ 23,43,44,45,46]. We included previously unprocessed 16S composition data and created a cohort of 3816 AGP subjects for this study. Compared to the typical American adult population (NHANES), the study cohort seemed to consume fewer calories and have healthier eating habits for children, adults, and to a lesser extent for older adults. Contrary to calorie intake, the AGP cohort reported a higher intake of fiber and vitamin B12 than NHANES, further supporting a healthy eating choice of AGP participants. It is, however, worthwhile to mention that different methods of collecting dietary intake in the two studies hindered us from performing direct comparisons between the two cohorts, similar to the conclusion of a recent study looking at dietary patterns of 1800 AGP participants [43]. Issues around over-optimism in microbiome analysis have recently been raised. Critiques on overfitting of data point out the potential pitfalls in reliability and reproducibility of the analysis [47]. In the current study, the performance of the model was stable with the AUC value of ROC being slightly higher in the test set than in the training set. Further, when using the same cuts-off to define Low, notLow, different algorithms (i.e., random forest and XGBoost) yielded similar statistical performance, implying that the conclusion was not derived from a selection bias on a particular overfitting model (Supplementary Table S2). Nevertheless, machine learning-based data analysis was meant to generate hypotheses, not conclusions. Through our modeling approach employed here, many nutrients identified in this study were newly associated with F. prausnitzii, such as sorbitol and inositol, while others such as alcohol and galactose have been previously reported to positively correlate with high F. prausnitzii abundance [32,48]. Inositol or myo-inositol is commonly found in vegetables and meat [49], and sorbitol and many sugar alcohols are found in fruits and vegetables. Evidence from a prospective study and a dietary intervention study showed a positive relationship between the consumption of fruits and vegetables and the abundance of F. prausnitzii [50,51], a result in agreement with the findings of our in vitro experiments. On the other hand, we did not observe any growth-promoting effect of xylitol on either strain of F. prausnitzii. These results highlight the importance of experimental validations on the outcomes of in silico modeling. F. prausnitzii has a high degree of genetic diversity, and the two strains used in the study (A2-165 and 27768) belong to different phylogroups [37]. The two isolates also showed different growth rates under various dietary and host-derived carbohydrate sources [37]. We also observed strain-specific growth response when inositol was given as a carbon source. Recently, a branch of F. prausnitzii, including the A2-165 strain has been reannotated into a new species Faecalibacterium duncaniae [52], further highlighting the diverse metabolic potential of F. prausnitzii. Interestingly, it was reported that neither F. duncaniae nor F. prausnitzii grew on inositol, which contrasts with our findings. The discrepancy is likely due to the difference in culture condition: in our study, the growth-promoting effect of inositol was observed after 48 h whereas Sakamoto et al. [ 52] reported results after 18–24 h incubation time. Use of in vitro fermentation in a test tube has been widely applied to examine microbial degradation and transformation of prebiotic fibers [53] due to many advantages such as short turnaround time, enhanced throughput, simple equipment setup compared to a continuous system, animal models, or clinical studies [30]. However, it is also the least physiological of all the models as pH is often not fully controlled and waste products are not removed during the fermentation. Another well-known criticism of in vitro systems is the negligence or improper estimation of digestion and absorption of nutrients in the small intestine. Furthermore, interactions between nutrients (e.g., D-glucose and inositol) affect the bioavailability of intestinal tissues [54], thus altering the potential impacts of target nutrients on colonic gut microbiota. Despite the shortcomings of the system, reductionist approaches such as testing nutrients in pure bacteria culture and in complex fecal microbiota provide experimental conditions for testing a causal relationship between nutrients and target bacteria and studying specific functions or metabolites of gut microbiota [55]. In the present study, we showed that inositol was efficiently utilized by all four fecal communities, and F. prausnitzii increased at least 1.6-fold over control in three out of four communities. One reason contributing to the interindividual variation could be the differences in microbial composition among all the donor samples. In the present study, we excluded people with conditions such as the use of antibiotics or certain drugs, abnormal bowel movements, GI diseases, and many others that are known to affect the gut microbiota. However, we did not collect dietary intake, lifestyle, ethnicity, and social economic status which are also known factors for causing a shift in microbiota composition. So, the starting microbiota composition in the in vitro experiments might have been less homogenous than we expected, which led to heterogenic responses to the treatments. F. prausnitzii is highly connected with other bacterial members in the energic trophic chain. This is best demonstrated in cross-feeding experiments where the F. prausnitzii population benefited from the presence of Bifidobacteria and other bacteria for acetate and vitamin Bs, respectively [41,56]. Since Bifidobacteria are primary utilizers of inulin in the adult gut ecosystem [57,58], it is not a surprise to see donor-specific responses to test nutrients and inulin. F. prausnitzii also compete with other bacteria for carbon sources. As shown by Lopez-Siles et al., F. prausnitzii out-competed Eubacterium eligens and Bacteroides thetaiotaomicron in co-culture experiments with apple pectin. However, it is possible F. prausnitzii does not have a competitive advantage over other nutrients. To concretely evaluate the effect of F. praustnitzii targeting nutrients, intervention trials in humans coupled with metagenomic and metabolomic analysis are needed to reveal nutrient–F. prausnitzii relationship in a complex gut ecosystem. ## 5. Conclusions In conclusion, we discovered the novel F. prausnitzii modulating nutrients using a machine learning approach applied to data from American Gut Project, and many of our predictions were confirmed in in vitro experiments, supporting the value of in silico approach without having a priori hypothesis. Interestingly, sorbitol robustly enhanced the growth of two different strains of F. prausnitzii whereas inositol’s effect was strain dependent. While validating the nutrients singly or in combinations, we experienced highly individualized responses among four fecal donors. Although interesting, the results were mainly derived from in silico and in vitro experiments, validation of our findings in humans is required before applying the learnings in this study as a general recommendation or to be considered as a personalized nutrition strategy for enhancing the beneficial gut bacteria such as F. prausnitzii. ## 6. Patents Two patents were filed related to the works discussed here:[1]Systems and methods for estimating, from food frequency questionnaire-based nutrients intake data, the relative amounts of Faecalibacterium prausnitzii (Fprau) in the gut microbiome ecosystem and associated recommendations to improve Faecalibacterium prausnitzii [59].[2]Compositions and methods using at least one inositol or sorbitol to enhance the growth of Faecalibacterium prausnitzii [60]. ## References 1. 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--- title: Potential Prognostic Value of Native T1 in Pulmonary Hypertension Patients authors: - John W. Cerne - Christina Shehata - Ann Ragin - Ashitha Pathrose - Manik Veer - Kamal Subedi - Bradley D. Allen - Ryan J. Avery - Michael Markl - James C. Carr journal: Life year: 2023 pmcid: PMC10051677 doi: 10.3390/life13030775 license: CC BY 4.0 --- # Potential Prognostic Value of Native T1 in Pulmonary Hypertension Patients ## Abstract Native T1, extracellular volume fraction (ECV), and late gadolinium enhancement (LGE) characterize myocardial tissue and relate to patient prognosis in a variety of diseases, including pulmonary hypertension. The purpose of this study was to evaluate if left ventricle (LV) fibrosis measurements have prognostic value for cardiac outcomes in pulmonary hypertension subgroups. 54 patients with suspected pulmonary hypertension underwent right-heart catheterization and were classified into pulmonary hypertension subgroups: pre-capillary component (PreCompPH) and isolated post-capillary (IpcPH). Cardiac magnetic resonance imaging (MRI) scans were performed with the acquisition of balanced cine steady-state free precession, native T1, and LGE pulse sequences to measure cardiac volumes and myocardial fibrosis. Associations between cardiac events and cardiac MRI measurements were analyzed within PreCompPH and IpcPH patients. IpcPH: LV native T1 was higher in patients who experienced a cardiac event within two years vs. those who did not. In patients with LV native T1 > 1050 ms, the rate of cardiac events was higher. ECV and quantitative LGE did not differ between groups. PreCompPH: native T1, ECV, and quantitative/qualitative LGE did not differ between patients who experienced a cardiac event within two years vs. those who did not. LV native T1 may have potential value for forecasting cardiac events in IpcPH, but not in PreCompPH, patients. ## 1. Introduction Pulmonary hypertension (PH) is a progressive, life-threatening, and multifactorial disease process that is characterized by an elevated resting mean pulmonary arterial pressure (mPAP) [1,2]. PH is broadly classified into pre-capillary PH (PrePH), isolated post-capillary PH (IpcPH), and combined pre- and post-capillary PH (CPH) based on clinical presentation and hemodynamic measurements [3,4]. Mechanistically, PrePH is defined as pulmonary vascular remodeling associated with an increase in pulmonary vascular resistance (PVR). IpcPH is defined as left-sided heart disease associated with increased pulmonary venous pressures (as measured by pulmonary capillary wedge pressure; PCWP). CPH represents a progression of IpcPH and is defined by concomitant increases in PVR and PCWP. While PrePH, IpcPH, and CPH all lead to right ventricular (RV) failure, elevated PVR heralds RV dysfunction in both PrePH and CPH (collectively termed: Pre-Capillary Component PH [5]; PreCompPH) while incipient left ventricular (LV) dysfunction characterizes the process in IpcPH. PH classification is used to guide optimal treatment and to predict prognosis [6]. Right heart catheterization (RHC) has been the gold-standard diagnostic and prognostic tool for PH. However, because of its invasive nature, there is increasing exploration of alternative prognostic markers in PH patients. In PH patients, cardiopulmonary exercise testing [7] and cardiac MRI measurements [8] have shown correlations with RHC measurements. Cardiac MRI, specifically, has been shown to provide sensitive biomarkers capable of distinguishing PH subgroups [9,10]. Ventricular fibrosis measurements have been shown to provide more sensitive prognoses in patients with LV diastolic dysfunction [11] and systemic sclerosis [12], compared to functional measurements alone. Cardiac MRI can be used to evaluate fibrosis through the detection of increased extracellular space (late gadolinium enhancement, LGE; extracellular volume fraction, ECV) through increased volume measures of extra- and intra-cellular space (native T1). These measures may have clinical value for outcome prediction in patients with cardiac disease [12,13,14,15]. Previous prognostic studies relate to RV functional measurements in PrePH [16,17,18]. Given the disparate pathophysiologic processes leading to an elevated pulmonary artery pressure, we hypothesized that LV fibrosis measurements would have prognostic significance in IpcPH, and not in PreCompPH. ## 2.1. Subjects Approval from the Institutional Review Board (IRB) was obtained, and all subjects provided written informed consent. The initial cohort was identical to that used in a previous study investigating 4D flow-derived velocities in PH patients [8]. Patients with suspected PH who had undergone standard-of-care RHC were identified. Patients with a mPAP ≥ 25 mmHg at rest or mPAP > 30 mmHg during exercise were recruited to undergo a cardiac MRI protocol with venous blood sampling for hematocrit within 28 days of cardiac catheterization. Patients were enrolled between August 2017 and March 2020. Exclusion criteria included: allergy to gadolinium-based contrast agents; severe kidney disease (estimated glomerular filtration rate < 30 mL/min/1.73 m2; acute kidney injury; kidney or liver transplant within 8 weeks; any contraindication to MRI (i.e., claustrophobia); pregnant or breastfeeding women; adults unable to provide consent; children; prisoners. ## 2.1.1. Right Heart Catheterization Standard-of-care RHC was performed with a 7–9 French sheath via the internal jugular or femoral veins. A Swan-Ganz catheter, connected to an analog pressure recorder, was used to obtain mPAP, systolic PAP, diastolic PAP, pulmonary capillary wedge pressure (PCWP) and right ventricular cardiac output (QP). PVR (in Wood Units (WU)) was calculated using the formula: PVRRHC = ΔP/QP, where ΔP is the trans-pulmonary pressure gradient (ΔP = mPAP − PCWP) and QP is the flow in the pulmonary artery measured by the Fick principle using the pulmonary artery oxygen saturation. ## 2.1.2. Classification PH patients were classified (MV: a cardiologist with 5 years of experience in cardiac imaging) based on a review of their clinical courses, therapeutic histories, and hemodynamic measurements. Patients’ clinical courses and therapeutic histories were considered in addition to hemodynamic measurements, during classification, because invasive parameters are known to vary with a patient’s fluid and metabolic status, and it has been suggested that hemodynamics should be interpreted in the context of the clinical picture [4]. Patients with pulmonary arterial hypertension, pulmonary hypertension due to chronic lung disease, and chronic thromboembolic PH) were considered pre-capillary PH [19]. Patients with pulmonary hypertension due to left heart disease were considered IpcPH or CPH, based on PVR measurements (PVR < 3 WU or PVR ≥ 3, respectively). CPH and PrePH patients were collectively designated as PreCompPH patients. ## 2.1.3. Clinical Data Collection The electronic medical record (EMR) was reviewed to determine if a cardiac event occurred after patients’ cardiac MRI scans. Cardiac events were defined as any of the following: heart failure requiring intravenous diuretics; palpitations prompting inpatient observation; or coronary revascularization. If any of these events occurred, the elapsed time between the MRI scan and the event was recorded. Comorbidities (history of smoking, hypertension, hyperlipidemia, diabetes mellitus) and functional status within 4 months of MRI (New York Heart Association (NYHA) functional class, six-minute walk distance, brain natriuretic peptide (BNP), supplemental oxygen use, ascites, peripheral edema) were also retrieved from the EMR (CS: a medical student with 2 years of experience). ## 2.2. Cardiac MRI Data Acquisition [10] The Cardiac MRI scans were performed by certified technicians using a 1.5 T MRI system (MAGNETOM Aera; Siemens Healthcare, Erlangen, Germany). A three-plane fast localization sequence was used to determine anatomic orientations for subsequent sequences, and four-chamber, two-chamber, and short-axis localizer views were obtained. The pre-contrast portion of the protocol consisted of multiplanar segmented balanced cine steady-state free precession (bSSFP) and native T1 mapping (Modified Look-Locker inversion recovery (MOLLI) technique). After contrast administration (Gadobutrol, 0.1 mL/kg), LGE and MOLLI T1 mapping sequences were performed (10 min and 15 min after contrast, respectively). The combined duration of the MRI sequences was 30 min. The bSSFP cine acquisition was performed in the two-, three-, four-chamber, and short-axis orientations. Data were acquired during breath holds at end-expiration using retrospective electrocardiogram (ECG) gating. Cine sequence MRI parameters were as follows: field of view (FOV) read = 340 mm × 340 mm, spatial resolution = 1.8 mm × 1.8 mm × 6.0 mm, temporal resolution = 35.49 ms, flip angle = 80°, echo time/repetition time (TE/TR) = $\frac{1.16}{35.49}$ ms. The gradient recalled echo (GRE) bSSFP MOLLI acquisitions were collected pre- and post-contrast (delay = 10 min) with sequence parameters as follows: TE 1.33 ms, flip angle 35°, slice thickness 8.00 mm, pixel size = 1.0 × 1.0 mm2, Generalized Auto-calibrating Partial Parallel Acquisition (GRAPPA) with an acceleration factor, $R = 2.$ Imaging reconstruction included the auto-calculation of parametric LV T1 maps. The LGE pulse sequences were performed with either of two Phase-sensitive Inversion–Recovery (PSIR) pulse sequences: [1] a 2D inversion–recovery (IR) balanced steady-state free precession (bSSFP) pulse sequence (Echo spacing: 2.5 ms, TE 1.05 ms, flip angle 40°, slice thickness 6.0 mm, pixel size = 2.0 × 2.0 mm2, GRAPPA with an acceleration factor, $R = 2$) a segmented 2D IR gradient recalled echo (turboFLASH) pulse sequence (Echo spacing: 8.4 ms, TE 3.25 ms, flip angle 25°, slice thickness 6 mm, pixel size = 1.3 × 1.3 mm2, GRAPPA with an acceleration factor, $R = 2$). ## 2.3.1. Volumetric Measurements The RV and LV endocardial borders were manually contoured on short-axis bSSFP cine images at the peak end-diastolic and end-systolic time frames using CVI42 (Circle Cardiovascular Imaging, Calgary, AB, Canada) (Figure 1). CVI42 generated ejection fractions, end-diastolic volumes, and end-systolic volumes of the right and left ventricles (RVEF, RVEDV, RVESV; LVEF, LVEDV, LVESV). Each patient’s body surface area (BSA) was calculated using the Mosteller equation, and volumes were divided by BSA to get end-systolic and end-diastolic volume indices (RVEDVI, RVESVI, LVEDVI, LVESVI). ## 2.3.2. Late Gadolinium Enhancement Quantitative: A semi-automated technique was used to quantify myocardial fibrosis through manual thresholding of the short-axis LGE images on CVI42 (Figure 1). A research fellow (JWC: 1 year of experience in cardiothoracic imaging) performed manual tracings of the epicardial and endocardial LV borders. Regions of fibrosis were defined by reference to a manually delineated region of the normal myocardium. Voxels with intensities that were 4 standard deviations above the average intensity of normal myocardium were considered fibrosis. Images were anonymized and analyzed in a blinded fashion and in a random order. For each scan, global LGE was calculated (Equation [1]) [20] [1]Global fibrosis mass %=Mass of enhancing myocardiumTotal Myocardial Mass×100 Qualitative: A radiologist (KS: 2 years of experience in cardiothoracic imaging) performed a qualitative analysis of LGE presence. Patients were determined to have: no LGE; or LGE at one insertional point; or LGE at both insertional points. To evaluate interobserver reliability, a second radiologist (BDA: 4 years of experience in cardiothoracic imaging) assessed the presence and location of LGE in a randomly selected subset of 10 subjects. ## 2.3.3. Native T1 Mapping Manual segmentation of T1 maps was performed (AP: a research fellow with 3 years of experience in cardiothoracic imaging) on CVI42 (Figure 1). The LV epicardium/endocardium was manually contoured, and regions of interest within the blood pool cavity were demarcated on native t1 and postcontrast images (AP) (Figure 1). The basal, mid, and apical slices from pre- and post-contrast T1 maps were used with patients’ hematocrit values to obtain pixel-wise ECV values (Equation [2]). [ 2]λ=1T1myocardium post C−1T1myocardium pre C1T1blood post C−1T1blood pre CECV=1−Hct×λ Pixel-wise values were converted by the software into average values, on a segment-by-segment basis, for each of the American Heart Association (AHA)-defined myocardial segments. Segmental values were averaged to obtain global ECV and native T1 values for each scan [21]. ## 2.4. Statistical Analysis Descriptive statistics were recorded based on the nature of the compared variables: mean ± standard deviation (continuous variables, normal distribution); median (interquartile range) (continuous variable, non-normal distribution); frequency (percentage) (categorical variables). Shapiro–Wilk test was used to assess continuous variables for normality. Continuous variables were compared between two groups with independent samples Student’s t-test preceded by Levene’s test (normally distributed) or Mann–Whitney U test (non-normally distributed). Chi-square statistics with Yates correction or Fisher’s exact test were used to compare categorical data, depending on the size of the groups being compared (>/=5 and <5, respectively). Kaplan–Meier curve analysis and log-rank test were used to assess cumulative cardiac events. Statistical analyses were performed with SPSS (IBM corporation, Chicago, IL, USA). All tests were two-tailed with $p \leq 0.05$ considered statistically significant. ## 3.1. Patient Characteristics Fifty-four patients were involved in the assessment (35 PreCompPH and 19 IpcPH patients). Patients’ clinical information is depicted in Table 1. Functional status data within 4 months of the MRI scan was not found for all patients: $\frac{40}{54}$ patients had a NYHA functional status designation; $\frac{12}{54}$ patients had a six-minute walk distance; $\frac{30}{54}$ patients had a BNP measurement. There was an inability to calculate ECV in five subjects due to the following reasons: missing post-contrast T1 MOLLI images ($$n = 2$$); severe zebra artifact ($$n = 1$$); misaligned slice positioning ($$n = 1$$); post-contrast dark blood misregistration ($$n = 1$$). Native T1 and volumetric indices could not be obtained due to zebra artifact in one subject ($$n = 1$$) (Figure 2). Receiver operating curve (ROC) analyses of mPAP and PVR within PreCompPH and within IpcPH patients showed no statistically significant area-under-curve (AUC) values for the occurrence of a cardiac event within 2 years of the cardiac MRI scan (Table 2 and Table 3). ## 3.2. Volumetric Measurements ROC analyses within PreCompPH patients showed no statistically significant AUC values for LVEDV (AUC = 0.419; $$p \leq 0.529$$), LVESV (AUC = 0.500; $$p \leq 1.000$$), LVEDVI (AUC = 0.324; $$p \leq 0.181$$), LVESVI (AUC = 0.500; $$p \leq 0.126$$), RVEDV (AUC = 0.571; $$p \leq 0.561$$), RVESV (AUC = 0.648; $$p \leq 0.236$$), or RVESVI (AUC = 0.632; $$p \leq 0.294$$) for the occurrence of a cardiac event within 2 years of the cardiac MRI scan. The AUC of LVEF approached significance (AUC = 0.679; $$p \leq 0.069$$), and the AUC of RVEF was statistically significant (AUC = 0.847; $$p \leq 0.000$$) (Table 2 and Figure 3). ROC analyses within IpcPH patients showed no statistically significant AUC values for LVEDV (AUC = 0.386; $$p \leq 0.424$$), LVESV (AUC = 0.371; $$p \leq 0.360$$), LVEDVI (AUC = 0.443; $$p \leq 0.694$$), LVESVI (AUC = 0.429; $$p \leq 0.624$$), LVEF (AUC = 0.284; $$p \leq 0.069$$), RVEDV (AUC = 0.414; $$p \leq 0.552$$), RVESV (AUC = 0.371; $$p \leq 0.371$$), RVEDVI (AUC = 0.429; $$p \leq 0.650$$), RVESVI (AUC = 0.429; $$p \leq 0.650$$), or RVEF (AUC = 0.420; $$p \leq 0.573$$) (Table 3 and Figure 3). ## 3.3. Late Gadolinium Enhancement Quantitative: Within PreCompPH patients, there was no statistically significant difference in global fibrosis mass percent between the patients who experienced a cardiac event within two years (1.5 (0, 3.4)%) and those who did not (1.4 (0.2, 2.6)%) ($$p \leq 0.920$$). Similarly, within IpcPH patients, there was no statistically significant difference between the patients who experienced a cardiac event within 2 years (1.6 ± $0.6\%$) and those who did not (2.9 (0, 8.5)%) (Figure 4). Qualitative: Within PreCompPH patients, the distributions of the numbers of patients with no LGE at insertional points (IPs), LGE at one IP, and LGE at both IPs between patients who experienced a cardiac event within two years vs. those who did not were: $14\%$ vs. $32\%$ ($$p \leq 0.645$$); $86\%$ vs. $61\%$ ($$p \leq 0.380$$); and $0\%$ vs. $7\%$ ($$p \leq 1.000$$), respectively. Within IpcPH patients, the distributions of the numbers of patients with no LGE at IPs, LGE at one IP, and LGE at both IPs between patients who experienced a cardiac event within two years vs. those who did not were: $63\%$ vs. $64\%$ ($$p \leq 1.000$$); $13\%$ vs. $36\%$ ($$p \leq 0.338$$); $25\%$ vs. $0\%$ ($$p \leq 0.164$$) (Table 4). ## 3.4. Native T1 Within PreCompPH patients, the amount of LV native T1 in patients who experienced a cardiac event within two years was higher than the amount of native T1 in patients who did not experience a cardiac event within two years (1061.0 ± 53.4 ms vs. 1049.2 ± 33.9 ms), though without statistical significance ($$p \leq 0.553$$). ROC analysis showed an AUC of 0.587 for the association between LV native T1 and the occurrence of a cardiac event within two years of cardiac MRI ($$p \leq 0.558$$) (Figure 5). Kaplan–Meier survival analysis showed no statistically significant survival difference between patients with a LV native T1 <1050 ms ($$n = 16$$) and patients with a LV native T1 >1050 ms ($$n = 19$$) ($$p \leq 0.835$$) (Figure 6). Within IpcPH patients, there was a statistically significant higher amount of LV native T1 in patients who experienced a cardiac event within two years of cardiac MRI (1055.7 ± 24.2 ms vs. 1032.1 ± 28.9 ms) ($$p \leq 0.041$$) (Figure 4). ROC analysis showed an AUC of 0.725 for the association between LV native T1 and the occurrence of a cardiac event within two years of cardiac MRI ($$p \leq 0.075$$) (Figure 5). Kaplan–Meier survival analysis showed a statistically significant lower rate of survival in patients with LV native T1 >1050 ms ($$n = 9$$) compared to patients with LV Native T1 < 1050 ms ($$n = 9$$) ($$p \leq 0.023$$) (Figure 6). ## 3.5. Extracellular Volume Fraction Within PreCompPH patients, there was no statistically significant difference in global LV ECV percent between the patients who experienced a cardiac event within two years of cardiac MRI (33.4 ± $4.4\%$) and those who did not (29.7 (24.4, 35.0)%) ($$p \leq 0.224$$) (Figure 4). ROC analysis showed an AUC of 0.632 for the association between LV ECV and the occurrence of a cardiac event within two years of cardiac MRI ($$p \leq 0.273$$). Within IpcPH patients, there was no statistically significant difference in global LV ECV percent between the patients who experienced a cardiac event within two years of cardiac MRI (28.9 ± $3.5\%$) and those who did not (32.0 ± $5.1\%$) ($$p \leq 0.093$$). ROC analysis showed an AUC of 0.314 for the association between LV ECV and the occurrence of a cardiac event within two years of cardiac MRI ($$p \leq 0.168$$). ## 4. Discussion The presented results show that fibrosis and volumetric assessments may be of value for the prediction of cardiac outcomes in PH patients, but this value may depend on whether a patient’s PH is marked by elevated PVR (and subsequent PreCompPH characterization). Volumetric and hemodynamic measurements appear less promising. The results of this study show that LV native T1 measurements may be able to forecast cardiac events in IpcPH patients, but not in PreCompPH patients. No association was found between LGE or ECV and the occurrence of a cardiac event in either subset of PH patients. Though several fibrosis quantification techniques have been simultaneously studied for their potential to prognosticate muscular dystrophy patients [21], amyloidosis patients [22], and a heterogeneous group of patients referred for cardiac MRI [23], our study is the first study to simultaneously assess the relationship between prognosis and all three fibrosis measurement techniques in a PH cohort. In a retrospective cohort study of 223 patients with PAH, Saunders et al. [ 24] found that septal T1, RV insertion point T1, and LV free-wall T1 were not associated with mortality. In this study, 59 patients died during a follow-up period of 29 months which allowed for univariate Cox proportional hazards regression analysis. The present study differed as native T1 values were assessed by an LV global summary measurement; however, global native T1 of the LV has been previously shown to correlate with insertional point T1 ($r = 0.75$; $p \leq 0.05$) [25]. The results of our study are similar to the results of Saunders et al. as no outcome association was observed in PreCompPH (of which PAH is a subtype). Yet our results suggest that this may not be the case in IpcPH patients. Previous studies have reported a predictive relationship between native T1 measurements in outcomes. These works have studied all-comer patients [26,27], patients with diabetes [28], and non-ischemic dilated cardiomyopathy patients [29]. We believe these cohorts are more akin to IpcPH given the collective absence of elevated PVR (and likely absence of fulminant right heart failure) in these patient populations, in which right ventricular function has less impact on prognosis. Our results showing a lack of statistically significant associations between LGE, ECV, and cardiac outcomes are consistent with the previous literature. In a study using native T1, ECV, and LGE measurement techniques in the non-infarcted myocardium of patients with coronary heart disease, native T1 and ECV were independent predictors of outcome [29]. Both tissue characterization techniques surpassed LGE assessment, and native T1 performed better than ECV. It was suggested that this may be due to effects other than fibrosis, such as inflammation, which affect native T1 values more than ECV. Our results suggest that this effect may not be limited to coronary artery disease patients, and that pathophysiological processes outside of fibrosis may be occurring in the LV of IpcPH patients. Furthermore, in a group of hypertrophic cardiomyopathy patients, $30\%$ of LGE-negative segments showed an elevated native T1 time [30], suggesting that native T1 is a more sensitive biomarker than LGE. ECV, native T1, and LGE all purport to measure myocardial fibrosis, but they achieve this through surrogate fibrosis measurements. Native T1 appears most relatable to the outcome and may therefore be the best means of fibrosis approximation. It has also become appreciated that RV functional measures assessed by cardiac MRI are associated with a functional state, exercise capacity, and survival in patients with PAH (a subset of PreCompPH) [31,32,33,34]. RVEF and RVESV have been shown capable of distinguishing PH severity grades [31], and the loss of RV function is associated with a poor outcome irrespective of any changes in PVR [34]. Whether RV functional measures continue to hold clinical value in IpcPH patients has been under-investigated. We indeed found that a lower RVEF was characteristic of PreCompPH patients who went on to experience a cardiac event in two years, but not of IpcPH experiencing a cardiac event in two years. Interestingly, invasive measurements were not prognostic in IpcPH or PreCompPH patients. Elevated pulmonary artery pressures have previously been shown to be associated with outcomes in patients with left heart disease and PH [35]. PVR measurements greater than 2.2 Wood Units portend a worse prognosis in all subgroups of PH [36]. Previous works showing the relationship between hemodynamic measurements have focused on all-cause mortality [36,37,38] or heart-failure-specific hospitalizations [36], singularly. These assessments were not possible in our cohort, considering the small number of observed deaths and hospitalizations secondary to heart failure. The present study defined outcomes as cardiac events because previous associations between fibrosis measurements and cardiac outcomes have been observed in heart transplant patients [13]. In our small cohort, the inclusion of ‘cardiac event’ outcomes extending to palpitations and coronary revascularization was necessary to investigate the relationship between outcomes and several cardiac MRI parameters. ## 5. Limitations [8,10] There are several limitations to our study. First, the small sample size of the present cohort, combined with a low death rate (6 out of 54 patients) during the follow-up period, precluded the use of regression and survival analyses in our study. Larger studies are needed to allow for robust statistical testing of our preliminary findings. Second, up to 28 days elapsed between cardiac MRI and RHC. Disease progression or remission may have occurred during this time. For this reason, patients were classified by a cardiology fellow with experience following PH patients. RHC values, volumetric measurements, and clinical factors were all considered during the classification process. Spruijt et al. [ 39] similarly classified idiopathic PAH, systemic scleroderma-related PH, and CTEPH all as PrePH-type, without reference to RHC measurements. It would have been ideal for RHC and cardiac MRI to have been collected close together, as has previously been done [40], but this was not possible given the recruitment protocol. This study is further limited by the recruitment protocol, as the mPAP threshold used to define PH has recently changed (in 2015, a resting mPAP >/= 25 mmHg defined PH [4]; in 2022, a resting mPAP of >20 mmHg defined PH [41]), with new guidelines established by the European Society of Cardiology and the European Respiratory Society. Our study used the older guidelines, as the recruitment protocol occurred during this time. It has been suggested that mPAP values used in isolation cannot characterize the PH clinical condition and do not define the pathological process per se [19]. 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--- title: Characterization of the Involvement of Tumour Necrosis Factor (TNF)-α-Stimulated Gene 6 (TSG-6) in Ischemic Brain Injury Caused by Middle Cerebral Artery Occlusion in Mouse authors: - Chiara Di Santo - Daniele La Russa - Rosaria Greco - Alessandra Persico - Anna Maria Zanaboni - Giacinto Bagetta - Diana Amantea journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051687 doi: 10.3390/ijms24065800 license: CC BY 4.0 --- # Characterization of the Involvement of Tumour Necrosis Factor (TNF)-α-Stimulated Gene 6 (TSG-6) in Ischemic Brain Injury Caused by Middle Cerebral Artery Occlusion in Mouse ## Abstract The identification of novel targets to modulate the immune response triggered by cerebral ischemia is crucial to promote the development of effective stroke therapeutics. Since tumour necrosis factor (TNF)-α-stimulated gene 6 (TSG-6), a hyaluronate (HA)-binding protein, is involved in the regulation of immune and stromal cell functions in acute neurodegeneration, we aimed to characterize its involvement in ischemic stroke. Transient middle cerebral artery occlusion (1 h MCAo, followed by 6 to 48 of reperfusion) in mice resulted in a significant elevation in cerebral TSG-6 protein levels, mainly localized in neurons and myeloid cells of the lesioned hemisphere. These myeloid cells were clearly infiltrating from the blood, strongly suggesting that brain ischemia also affects TSG-6 in the periphery. Accordingly, TSG-6 mRNA expression was elevated in peripheral blood mononuclear cells (PBMCs) from patients 48 h after ischemic stroke onset, and TSG-6 protein expression was higher in the plasma of mice subjected to 1 h MCAo followed by 48 h of reperfusion. Surprisingly, plasma TSG-6 levels were reduced in the acute phase (i.e., within 24 h of reperfusion) when compared to sham-operated mice, supporting the hypothesis of a detrimental role of TSG-6 in the early reperfusion stage. Accordingly, systemic acute administration of recombinant mouse TSG-6 increased brain levels of the M2 marker Ym1, providing a significant reduction in the brain infarct volume and general neurological deficits in mice subjected to transient MCAo. These findings suggest a pivotal role of TSG-6 in ischemic stroke pathobiology and underscore the clinical relevance of further investigating the mechanisms underlying its immunoregulatory role. ## 1. Introduction Cerebral ischemia triggered by stroke is a major cause of mortality and long-term disability, generating a global healthcare burden that is expected to grow if prevention and treatment strategies are not implemented in the near future [1]. In fact, currently approved therapies only rely on reperfusion of the lesioned tissue by pharmacological or mechanical thrombus lysis/removal [2,3,4,5], generating high expectations for the development of novel neuroprotective strategies. However, despite the great efforts made in recent decades to characterize the pathobiological mechanisms implicated in ischemic brain injury, to date, none of the identified putative targets have been successfully translated into effective therapies [6,7,8]. The immune system exerts a dualistic role in the progression of ischemic brain damage, playing detrimental or protective/regenerative roles depending on the specific soluble mediators (e.g., pro- or anti-inflammatory cytokines) or cellular phenotype (e.g., inflammatory M1 or reparative M2) involved [9,10,11]. Indeed, recent studies have validated the suitability of a rational immunomodulation by targeting central and/or peripheral immune responses involved in ischemic pathobiology [9,10,12,13]. Thus, the identification of novel targets to modulate the immune responses triggered by cerebral ischemia represents a desirable aim with strong translational value. Recent work has highlighted that the multifunctional protein tumour necrosis factor (TNF)-α-stimulated gene 6 (TSG-6) may play a role in acute neurodegenerative diseases [14]. TSG-6 is a member of the family of hyaluronate (HA) binding proteins, involved in cell–cell and cell–matrix interactions during inflammation and tumorigenesis [15,16,17]. TSG-6 is constitutively expressed in the brain, while its upregulation occurs upon inflammatory stimuli in a wide variety of cell types, including astrocytes, monocytes/macrophages, dendritic cells, mesenchymal stem/stromal cells (MSCs), vascular smooth muscle cells (VSMCs) and fibroblasts [18,19,20,21,22]. Among its various activities, TSG-6 regulates immune and stromal cells functions and affects extracellular matrix assembly and interaction with cell surface receptors and soluble mediators (e.g., chemokines) [23], exerting anti-inflammatory and immunosuppressive effects in diverse pathological contexts, including neuroinflammation [24,25,26,27,28,29,30,31]. Accordingly, this protein protects tissues from the injurious effects caused by spinal cord injuries [32] and, most notably, acute cerebral injuries [33,34,35,36,37,38]. Notably, TSG-6 expression is elevated in the peri-infarct and infarcted brain tissue of stroke patients [39] and in the plasma of non-cardioembolic acute ischemic stroke patients, where it is positively associated with disease severity and lesion volume [40]. In rodent models of global and focal cerebral ischemia, TSG-6 mediates the protective effects conferred by systemic administration of MSCs [37,41,42], although its direct effects and endogenous functions have not been fully clarified yet. Thus, here we aim to characterize the involvement of central and peripheral TSG-6 in ischemic brain injury. ## 2.1. Analysis of the Cerebral Expression of TSG-6 following Transient MCAo in Mice Transient cerebral ischemia caused by 1 h MCAo, followed by 6 to 48 h of reperfusion, resulted in a significant elevation of TSG-6 protein levels in the ipsilateral cortex of mice, reaching a peak 24 h after the beginning of reperfusion (Figure 1A). By immunofluorescence analysis, we observed that TSG6 was barely evident in a few NeuN immunopositive neurons of the contralateral hemisphere, and it was more abundantly expressed in neurons of the ipsilateral peri-infarct tissue (including the motor and frontal cortices) after 24 h or 48 h of reperfusion (Figure 1B). Moreover, expression of TSG6 was observed in Ly6B.2 immunopositive myeloid cells (i.e., granulocytes and monocytes/macrophages) populating the penumbral cortex at 24 h and 48 h of reperfusion and more intensely in the core region (i.e., parietal cortex) at 48 h of reperfusion (Figure 1C). A schematic representation of the cellular and regional expression of TSG-6 in mice brains after ischemia-reperfusion injury is reported in Figure 1D. These TSG-6 immunopositive myeloid cells were likely infiltrating from the blood vessels, as shown in Figure 1C (arrows and arrowheads). ## 2.2. Analysis of Blood Expression of TSG-6 after Ischemic Stroke in Mice and Patients These findings highlight that, in addition to the local (i.e., neuronal) elevation of TSG-6, ischemia affects the expression of this protein in the periphery. Accordingly, we found that TSG-6 protein levels in plasma were acutely (i.e., within 24 h after the beginning of reperfusion) reduced in mice subjected to 1 h MCAo when compared to sham surgery (Figure 2A). By contrast, at later stages (i.e., after 48 h of reperfusion), TSG-6 protein levels were significantly higher than sham (Figure 2A). Using the TargetScanMouse database (https://www.targetscan.org/mmu_80/ (accessed on 2 September 2022)), we performed a reverse target prediction analysis to identify miR-23a and miR-23b based on their potential to regulate TSG-6. Interestingly, reduced TSG-6 protein levels observed at 24 h of reperfusion were coincident with higher miR-23a (Figure 2B) and miR-23b (Figure 2C) expression in plasma when compared to sham. Conversely, after 48 h of reperfusion, circulating levels of these miRNAs were not significantly different from sham-operated animals (Figure 2B,C). To further characterize TSG-6-mediated responses in blood and to strengthen the clinical relevance of our findings, we explored expression of TSG-6 in circulating peripheral blood mononuclear cells (PBMCs) from ischemic stroke patients. As shown in Figure 3, TSG-6 mRNA expression was significantly increased in PBMC 48 h after stroke onset, which was coincident with the plasma TSG-6 protein level elevation observed in mice after 48 h of reperfusion (Figure 2A), strengthening the hypothesis that ischemic brain injury affects TSG-6 levels in the periphery. ## 2.3. Neuroprotective Effects of Systemic Administration of TSG-6 in Mice Subjected to MCAo Based on these findings, we hypothesised that late elevation of TSG-6 levels may represent a compensatory mechanism to counteract damage, whereas acute plasma reduction of TSG-6 may be detrimental, thus contributing to the progression of ischemic brain damage. To clarify this issue, we intravenously (i.v.) administered recombinant mouse TSG-6, at a dose of 30 μg/mouse, selected on the basis of previously published observations [35,43,44]. Thus, TSG-6 suspended in a vehicle (phosphate buffered saline, PBS) was administered (30 μg TSG-$\frac{6}{100}$ μL PBS/mouse) i.v. upon reperfusion (i.e., after 1 h MCAo) and infarct brain damage and neurological deficits were measured 48 h later. Figure 4 (panels A–C) shows that systemic administration of TSG-6 significantly reduced brain infarct damage caused by 1 h MCAo, whereas the cerebral oedema was not affected. Neuroprotection was also associated with attenuation of general neurological deficits caused by the ischemic insult (Figure 4, panels D and E). Interestingly, neuroprotection by i.v. administration of TSG-6 was associated with a significant elevation of cerebral levels of the M2 marker Ym1 (Figure 4, panel F), strongly supporting the hypothesis that this multifunctional protein exerts an important immunomodulatory function that may underlie its neuroprotective effects against ischemic injury. ## 3. Discussion The present study originally demonstrates that ischemic stroke injury affects TSG-6 expression levels both in the brain and in the blood. In mice, MCAo resulted in a significant elevation of the neuronal expression of TSG-6 protein in the lesioned hemisphere, with the most intense response observed in the peri-ischemic regions up to 48 h after the beginning of reperfusion. Elevated expression of TSG-6 was also associated with Ly6B.2 myeloid cells populating the ischemic penumbra after 24 h of reperfusion or the entire lesioned region (i.e., both the core and the penumbra) after 48 h of reperfusion. Most of these myeloid cells were clearly infiltrating from the blood, strongly suggesting that ischemic brain injury also affects TSG-6 in the periphery. Accordingly, TSG-6 mRNA expression was elevated in PBMC from ischemic stroke patients 48 h after symptoms onset. In agreement with these findings, TSG-6 protein expression was elevated in the plasma of mice subjected to 1 h MCAo followed by 48 h of reperfusion. However, plasma levels of TSG-6 were surprisingly reduced in the acute phase (i.e., 6 to 24 h after reperfusion) when compared to sham-operated mice. In this context, circulating levels of miR-23a and miR-23b were correlated with plasma TSG-6 levels in the acute phase (i.e., up to 24 h after the beginning of reperfusion), whereas this correlation was lost 48 h after the insult. Given the protective and anti-inflammatory effects of TSG-6 in other neuropathological contexts, we hypothesized that its reduction during the acute phase might be involved in the detrimental effects of the ischemic insult. Accordingly, systemic acute administration of recombinant mouse TSG-6 elevated brain levels of the M2 marker Ym1 and provided significant neuroprotection by reducing brain infarct volume and general neurological deficits in mice subjected to transient MCAo. TSG-6 is a secretory hyaluronate (HA)-binding protein, constitutively expressed in various tissues, including the brain and spinal cord. In the developing rat brain, it shows different expression patterns, being involved in oligodendrocyte maturation and neuronal precursor cell migration [45]. Despite the debated expression during embryonic development, TSG-6 has been observed in astrocytes of the mature rat brain and spinal cord [21], contributing to their maturation, since TSG-6 null mice display a lower density of cerebral GFAP+ astrocytes [21]. Nevertheless, the selective localization of TSG-6 in astrocytes reported by some studies was not confirmed by others that reported a more widespread distribution, also including microglia and neurons, especially under neurodegenerative/inflammatory conditions [23,34,39,46]. Accordingly, we observed that TSG-6 was almost exclusively expressed in a few NeuN immunopositive neurons of the control (i.e., sham or contralateral) brain tissue. However, we detected an increase in TSG-6 protein levels in the ischemic hemisphere, as the signal was located in neurons and also in Ly6B.2 immunopositive myeloid cells (i.e., granulocytes and monocytes/macrophages) populating the penumbral cortex at 24 h and 48 h of reperfusion and more intensely in the core region (i.e., parietal cortex) at 48 h of reperfusion. Our findings are consistent with the evidence showing an upregulation of TSG-6 in the cerebral cortex of rats following global cerebral ischemia [37]. More importantly, our findings are in agreement with the observation that TSG-6 mRNA and protein levels increase in the peri-infarct and infarcted brain tissue when compared to the contralateral hemisphere of ischemic stroke patients, as protein staining was associated with damaged neurons and inflammatory mononuclear cells 3 to 29 days after the insult [39]. Interestingly, TSG-6 elevation was coincident with increased HA levels in the lesioned brain and in the serum of stroke patients, together with an elevated expression of the HA receptor CD44 in damaged neurons and inflammatory mononuclear cells 3 to 17 days after stroke [39]. Increased HA synthesis and up-regulation of CD44 in microglia, macrophages and microvessels of the ischemic brain tissue were also reported to occur in rodents following focal cerebral ischemia [47,48]. TSG-6 elevation in the ischemic tissue and the preferential synthesis of high molecular weight HA are probably involved in the regulation of inflammatory responses and in tissue remodelling after ischemic stroke [39,47,48]. TSG-6 expression can be induced by a diverse range of inflammatory stimuli (i.e., TNF, IL-1 and LPS) in a wide variety of cell types, such as monocytes/macrophages, dendritic cells, astrocytes, mesenchymal stem/stromal cells (MSCs), vascular smooth muscle cells (VSMCs) and fibroblasts [18,19,20,21,22]. Thus, TSG-6 regulates immune and stromal cell functions and exerts anti-inflammatory and immunosuppressive effects by direct modulation of inflammatory cells or by regulation of the organization/assembly of extracellular HA matrices [23,24,25,26,27,28,29,30,31]. Although the anti-inflammatory and immunoregulatory functions of TSG-6 have been observed in various neurological disorders, including acute brain injury due to trauma, ischemia or haemorrhage [14], the majority of these findings focussed on the role of this protein as mediator of the beneficial effects of MSCs, whereas knowledge of the endogenous or direct functions of TSG-6 is poor. Indeed, upregulation of the cerebral expression of TSG-6 was reported to mediate the protective effects of intravenous administration of MSCs in rats subjected to global cerebral ischemia by attenuating the expression of neutrophil elastase and of the inflammatory cytokines IL-1β, IL-6 and TNF-α in the lesioned brain [37,41]. In addition, TSG-6 was demonstrated to mediate the anti-inflammatory effects of MSCs by inhibiting NF-κB signalling pathways and downstream cerebral inflammatory reactions caused by intracerebral or subarachnoid haemorrhage [33,49] or traumatic brain injury [38,50] in rats. Modulation of TSG-6 was not only restricted to the ischemic brain, as we observed that protein levels were significantly modulated in the plasma of mice subjected to 1 h MCAo. In particular, plasma TSG-6 protein levels were found to be reduced during the acute phase (i.e., within 24 h of the beginning of reperfusion), while they increased at later reperfusion stages (i.e., after 48 h) when compared to sham-operated mice. The latter finding is consistent with our data showing elevated mRNA expression level of TSG-6 in PBMC of ischemic stroke patients and with the evidence that non-cardioembolic acute (i.e., within 24 h from symptoms onset) ischemic stroke patients display higher plasma TSG-6 levels than control subjects [40]. In those patients, plasma TSG-6 levels were positively correlated with stroke severity at admission, the lesion volume, the neutrophil count, the neutrophil-to-lymphocyte ratio and interleukin-8 levels. Moreover, increased TSG-6 plasma levels were independently associated with a 3 months poor prognosis, while an elevated TSG-6 to IL-8 ratio predicted a favourable outcome after 3 months [40]. Circulating TSG-6 levels, also reported to be increased in patients with coronary artery disease or carotid stenosis, have been suggested to be derived from endothelial and arterial smooth muscle cells or from monocyte-derived macrophages stimulated by inflammatory mediators [51,52]. The latter evidence is in agreement with our findings demonstrating elevation of TSG-6 mRNA levels in PBMC from ischemic stroke patients and with the observation that cerebral elevation of TSG-6 depends on its local release by neurons and by blood-borne infiltrating myeloid cells, especially at later reperfusion times. This may also explain the elevation of plasma TSG-6 occurring after 48 h of reperfusion, which might actually represent a compensatory anti-inflammatory mechanism, as also underscored in other inflammatory contexts [45], likely through immunoregulatory effects that promote polarization of myeloid cells towards M2-like protective phenotypes. Conversely, we speculate that the reduced levels of circulating TSG-6 observed in the acute phase after stroke may represent a crucial mechanism implicated in the detrimental acute inflammatory reaction. To verify this hypothesis, we have administered recombinant TSG-6 at the time of reperfusion and we observed that it caused a significant elevation of cerebral levels of the M2 marker Ym1 and a reduction in cerebral lesions and neurological deficits. This is the first evidence of neuroprotection provided by systemic administration of TSG-6 in ischemic stroke; the few other studies available demonstrate its efficacy in other acute neurodegenerative contexts. In fact, intravenous treatment with TSG-6 was reported to decrease neutrophil extravasation, matrix metalloproteinase (MMP)-9 expression and the resulting BBB leakage caused by TBI in mice, thus promoting neurogenesis and attenuating long-term consequences, such as memory impairments and depressive-like behaviour [35]. Moreover, intracerebroventricular (i.c.v.) administration of recombinant TSG-6 in rats subjected to SAH inhibited the microglia shift towards inflammatory phenotypes, attenuated TNF-α expression and upregulated IL-10 expression, thus reducing brain oedema and neurological deficits [34,53]. In turn, knockdown of endogenous TSG-6 by siRNA elevated the (CD86+) M1 vs. (CD163+) M2 ratio in cerebral microglia and aggravated neurological deficits 24 h after SAH [34,53]. In agreement with these previous findings, we observed significant immunomodulatory and neuroprotective effects of exogenously administered TSG-6. However, in order to shed light on the central vs. peripheral mechanisms implicated in such beneficial effects, further investigation would be necessary to understand the systemic responses elicited by intravenously administered TSG-6. The immunomodulatory functions of TSG-6 have been widely investigated. Notably, myeloid immune cells produce high levels of TSG-6 in response to inflammatory stimuli [54], whereby TSG-6 has been suggested to act in an autocrine mode on macrophages to promote their transition from inflammatory to anti-inflammatory and immunoregulatory phenotypes [51,55,56,57], likely through suppression of Toll-like receptor (TLR)-4/NF-κB pathways [25,27,56,58,59,60]. Notably, TLR2-related pathways regulate microglia polarization, whereas NF-κB and p38 are implicated in the polarization shift of microglia/macrophages occurring after ischemic stroke [61,62,63,64,65,66]. In fact, BV2 microglia exposed to MSCs before being challenged with LPS reduced their expression of typical early and late M1 markers (iNOS, IL-1β, CD16 and CD86), while elevating M2 polarization markers (CD206 and Arg1) [67,68]. Thus, there is strong evidence to support a pivotal role of TSG-6 in the regulation of M1 to M2 polarization shift of myeloid cells under neuroinflammatory conditions. Our findings strongly suggest that the immunomodulatory functions of TSG-6 may be crucial to its neuroprotective properties in ischemic stroke. ## 4.1. Animals Adult C57Bl/6J male mice (8–10 weeks old) were purchased from Charles River (Calco, Como, Italy) and were housed under standard environmental conditions (i.e., an ambient temperature of 22 °C, a relative humidity of $65\%$ and 12 h/12 h light/dark cycle), with ad libitum food and water access. Animal care and the experimental in vivo procedures were performed following the guidelines of the Italian Ministry of Health (Decree Law n. $\frac{26}{2014}$), in accordance with the European Directive $\frac{2010}{63}$, and all efforts were made to minimize the number of animals used and their suffering. The protocol was approved (Authorization Numbers: $\frac{1277}{2015}$-PR and $\frac{701}{2020}$-PR) by the Committee set by the Italian Ministry of Health at the National Institute of Health (Rome). Animals were randomly allocated to the following experimental groups:[1]MCAo 6 h: mice were subjected to 1 h MCAo followed by 6 h of reperfusion;[2]SHAM 6 h: sham surgery 6 h before sacrifice;[3]MCAo 24 h: mice were subjected to 1 h MCAo followed by 24 h of reperfusion;[4]SHAM 24 h: sham surgery 24 h before sacrifice;[5]MCAo 48 h: mice were subjected to 1 h MCAo followed by 48 h of reperfusion;[6]SHAM 48 h: sham surgery 48 h before sacrifice;[7]MCAo + TSG-6: mice were subjected to 1 h MCAo followed by 48 h of reperfusion and intravenously (i.v.) injected upon reperfusion with 30 μg recombinant mouse TSG-6 (2326-TS, R & D Systems, Minneapolis, MN, USA) dissolved in 100 μL PBS;[8]MCAo + vehicle: mice were subjected to 1 h MCAo followed by 48 h of reperfusion and i.v. injected upon reperfusion with vehicle (100 μL PBS). The minimum sample size was evaluated using an a priori power analysis adjusted to obtain a power of $80\%$ at a significance level of 0.05 (OpenEpi software 3.01, Open Source Statistics for Public Health). On the basis of our earlier experience with the MCAo model, we hypothesized a difference in ischemic volume between mice subjected to MCAo and mice exposed to a neuroprotective procedure (i.e., ischemic PC) of about 28 mm3 (approximately $30\%$ reduction in infarct size) and a variability (standard deviation) of 15. This led to an estimated minimum sample size of five animals per experimental group. ## 4.2. Surgical Procedure for MCAo in Mice Focal cerebral ischemia was induced by proximal occlusion of the middle cerebral artery (MCAo) in mice anesthetized with isoflurane as previously described [60,69]. Briefly, vessel occlusion was accomplished by introducing a silicone-coated nylon filament (diameter: 0.23 mm, Doccol Corporation, Redlands, CA, USA) into the internal carotid artery (ICA) for 10–11 mm from its bifurcation from the common carotid artery, whereby a moderate resistance was indicative of proximal MCAo at the level of the Willis circle. In addition to correct positioning of the filament, animals were considered ischemic, and hence included in the study, if presenting >3 of the following deficits assessed after 45 min MCAo: ellipsoidal shape of the palpebral fissure, lateral extension of one or both ears, asymmetric body bending or laterally extending limbs [70]. To allow reperfusion, the filament was withdrawn 1 h after MCAo. Sham mice received the same anaesthetic regimen and surgery as MCAo mice, without introduction of the filament. ## 4.3. Brain Infarct and Neurological Deficits Assessment To assess cerebral ischemic damage, animals were sacrificed 48 h after the beginning of reperfusion and their brains were dissected and immediately frozen at −20 °C. Fifteen (20 μm thick) coronal slices were cut at 0.5 mm intervals from the frontal pole using a cryostat, then mounted on slides and stained with cresyl violet [71]. Images of cresyl violet-stained sections were captured by a digital scanner and blindly analysed using an image analysis software (ImageJ, version 1.53, NIH, USA) to calculate the infarct volume and oedema [72]. Neurological deficits were assessed 48 h after MCAo or SHAM surgery using the dichotomized De Simoni composite neuroscore to evaluate the general and focal neurological dysfunctions caused by the ischemic insult. Briefly, the total score ranges from 0 (healthy) to 56 (the worst performance in all the 13 categories) and represents the sum of six general deficits (fur (0–2), ears (0–2), eyes (0–4), posture (0–4), spontaneous activity (0–4) and epileptic behaviour (0–12)) and seven focal deficits (body asymmetry (0–4), gait (0–4), climbing (0–4), circling behaviour (0–4), forelimb symmetry (0–4), compulsory circling (0–4) and whisker response (0–4)) [70,71,72,73]. ## 4.4. Western Blot Analysis After 6, 24 or 48 h from MCAo or SHAM surgery, animals were deeply anaesthetized with isoflurane and sacrificed to dissect whole brains or ipsilateral (ischemic) and contralateral frontoparietal cortices (3.2 to −3.8 mm from the Bregma) [74]. Blood was collected in EDTA Vacutainer® tubes (VWR International, Milan, Italy), and plasma was separated by centrifugation at 1500× g for 15 min at 4 °C, followed by centrifugation at 16,000× g for 15 min at 4 °C to discard the debris and insoluble components. Brain samples were homogenized in ice-cold RIPA buffer containing protease inhibitor cocktail (PI, Sigma-Aldrich, Milan, Italy) and lysates were centrifuged for 20 min at 20,817× g at 4 °C. The supernatants were collected for protein quantification (Bradford protein assay, Bio-Rad Laboratories, Milan, Italy) and an equal amount (30 μg) of proteins was mixed in Laemmli buffer (Sigma-Aldrich, Milan, Italy). Plasma samples were diluted (1:10) in ice-cold RIPA buffer containing PI, and 10 μL of this solution was mixed in 10 μL Laemmli buffer. Samples suspended in Laemmli buffer were loaded onto Mini-PROTEAN® TGX™ Precast Protein Gel for separation in a Mini-PROTEAN Tetra Cell apparatus (Bio-Rad Laboratories, Milan, Italy). Protein gels were next electroblotted using the Trans-Blot Turbo transfer apparatus and a Nitrocellulose Transfer kit (Bio-Rad Laboratories, Milan, Italy). Membranes were rapidly transferred to a blocking buffer ($5\%$ non-fat milk in $0.05\%$ Tween-20 TRIS-buffered saline) and incubated with a gentle agitation for 1 h at room temperature. The blots were then incubated overnight at 4 °C, with the following primary antibodies: mouse anti-TSG-6 (1:1000; MABT108, Merck Millipore, Milan, Italy), rabbit anti-Ym1 (1:1000; 60130, StemCell Technologies, Meda, MB, Italy) and mouse anti-β-actin (1:3000; A3853, Sigma-Aldrich, Milan, Italy). This was then followed by incubation with the appropriate secondary antibodies (1:3000; Sigma-Aldrich, Milan, Italy) for 1 h at room temperature [13]. Immunodetection and quantification of protein bands were performed using the iBright™ FL1500 (Thermo Fisher Scientific, Monza, MB, Italy) and ImageJ software. ## 4.5. Real-Time Polymerase Chain Reaction (PCR) in Mouse Plasma Samples Quantitative real-time PCR analyses were carried out on mouse plasma samples collected (as described above) 6, 24 and 48 h after 1 h MCAo or SHAM surgery. MicroRNA was extracted from plasma samples using a miRNeasy Serum/Plasma Kit (Qiagen, Inc., Hilden, Germany). Briefly, 5 volumes of QIAzol lysis reagent were added to plasma and 5 pM A. Thaliana miR-159a (478411_mir, Life Technologies, Monza, MB, Italy) was spiked into the mixture [13]. Subsequently, chloroform was mixed in the solution which was then centrifuged for 15 min at 12,000× g at 4 °C to obtain three layers. The colourless upper aqueous phase was isolated, mixed with 1.5 volumes of $100\%$ ethanol, transferred into an RNeasy MinElute spin column and centrifuged at 8000× g for 15 s at room temperature. The spin column was washed with the supplied wash buffers (RWT and RPE), and then with $80\%$ ethanol. Finally, miRNA was eluted in 14 μL RNase-free water. According to the manufacturer’s protocol, miRNA quantification was performed using a TaqMan Advanced miRNA Assays Kit (Life Technologies, Monza, MB, Italy) on a QuantStudio™ 3 real-time PCR system (Thermo Fisher Scientific, Monza, MB, Italy). By using the comparative cycle threshold (Ct) method, the relative expression level of miR-23a-3p (mmu478532_mir, Life Technologies, Monza, MB, Italy) and miR-23b-3p (mmu478602_mir, Life Technologies, Monza, MB, Italy) were calculated by normalization to the expression of miR-669c-3p (mmu483332_mir, Life Technologies, Monza, MB, Italy) which remained stable in all the tested samples. ## 4.6. Immunofluorescence Mouse brains were quickly dissected 24 and 48 h after 1 h MCAo, fixed with paraformaldehyde, cryoprotected in $30\%$ sucrose solution and cryostat-cut into 40 µm-thick coronal sections collected at the level of the regions supplied by the middle cerebral artery (1.18 to −0.10 mm from the Bregma) [74]. Using a previously described method [75,76], colocalization studies were performed on free-floating brain slices by incubating a combination of the following primary antibodies: rabbit polyclonal anti-TNFAIP6 (1:200 dilution; PA599494, Life Technologies, Monza, MB, Italy), rat anti mouse Ly-6B.2 (1:200; clone $\frac{7}{4}$; Bio-Rad AbD Serotec, Segrate, Milan, Italy) to label myeloid cells (i.e., granulocytes and monocytes/macrophages), mouse anti-NeuN (anti-neuronal nuclei; 1:200; MAB377, Merck Millipore, Milan, Italy) to label neurons, rabbit anti-platelet and endothelial cell adhesion molecule 1 (PECAM1; 1:200; #5700639; Merck Millipore, Milan, Italy) to label the endothelium. Afterwards, primary antibodies were labelled with the corresponding secondary antibodies conjugated with AlexaFluor 488, AlexaFluor 568 or AlexaFluor 594 (1:200 dilution; Life Technologies, Monza, MB, Italy), while 4′,6-diamidino-2-phenylindole (DAPI, 1:500; Sigma-Aldrich, Milan, Italy) was used to counterstain nuclei. Immunostaining was observed under a confocal laser scanning microscope (Fluoview FV300, Olympus, Segrate, Milan, Italy) equipped with the dedicated software (cellSens v 4.1.1, Olympus) for image analysis. ## 4.7. Ischemic Stroke Patients and Control Subjects Human blood samples were collected in the frame of a cross-sectional case control study conducted on 25 patients of both sexes with a diagnosis of acute ischemic stroke (within the first 48 h from symptom onset) and 13 age-matched healthy control subjects (CT). Patients were recruited from the U.C. Malattie Cerebrovascolari e Stroke Unit, IRCCS Fondazione Mondino, Pavia, Italy. The study was approved by the local ethics committee (N. p-20170026158) and was conducted following the principles of the Declaration of Helsinki. All patients were assessed for stroke severity and degree of disability using NIHSS and mRS, respectively [77,78]. At the time of enrolment, samples of blood (18 mL) from the cubital vein were collected in sterile tubes from all subjects. ## 4.8. Gene Expression Analysis in Human Peripheral Blood Mononuclear Cells (PBMCs) PBMCs were isolated immediately after collecting blood samples in EDTA-containing tubes and diluted (1:1) with PBS (Sigma Aldrich, Milan, Italy). Diluted blood samples were slowly loaded into 15 mL Ficoll separating solution (Sigma Aldrich, Milan, Italy) and centrifuged at 800× g for 30 min at room temperature. PBMCs, accumulated in the middle white monolayer, were washed twice in sterile PBS at 300× g for 15 min and re-suspended in Trizol (Bio-Rad Laboratories, Segrate, Milan, Italy) to be stored at −80 °C until use (up to 2 weeks). The total RNA was extracted from pellets using the Direct-zol RNA Mini prep plus (Zymo Research, Aurogene, Rome, Italy) and the RNA quality was assessed using a spectrophotometer (Nanodrop One/One, Thermo Fisher Scientific, Monza, MB, Italy); cDNA was generated using an iScript cDNA Synthesis Kit (Bio-Rad Laboratories, Segrate, Milan, Italy) following the supplier’s instructions. The gene expression of TSG-6 was analysed using the Fast Eva Green Supermix (Bio-Rad Laboratories, Segrate, Milan, Italy), using Ubiquitin C (UBC, whose expression remained constant in all experimental groups) as a housekeeping gene. The primer sequences obtained from the Primers3 software were TSG-6 forward primer: GTGTGGTGGCGTCTTTACAG, TSG-6 reverse primer: AGCAACCTGGGTCATCTTCA, UBC forward primer: AGAGGCTGATCTTTGCTGGA and UBC reverse primer: GTGGACTCTTTCTGGATG. The amplification was performed with a light Cycler 480 Instrument rt-PCR Detection System (Roche, Basel, Switzerland) following the supplier’s instructions. All samples were assayed in triplicate and the gene expression levels were calculated according to the 2 − ∆∆Ct = 2 − (Ct gene − Ct housekeeping gene) formula by using Ct values. ## 4.9. Statistical Analysis Data are expressed as means ± S.E.M. for quantitative variables or as medians with interquartile range (IQR) for categorical ordinal variables (i.e., neuroscore) or non-normally distributed data (i.e., TSG-6 mRNA expression in human PBMCs). Data were subjected to statistical analysis using Graph-Pad Prism software for Windows (version 6.0, GraphPad Software, San Diego, CA, USA). 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--- title: Short-Term Effects of Human versus Bovine Sialylated Milk Oligosaccharide Microinjection on Zebrafish Larvae Survival, Locomotor Behavior and Gene Expression authors: - Rosario Licitra - Valentina Naef - Maria Marchese - Devid Damiani - Asahi Ogi - Stefano Doccini - Baldassare Fronte - Jingyu Yan - Filippo M. Santorelli journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051688 doi: 10.3390/ijms24065456 license: CC BY 4.0 --- # Short-Term Effects of Human versus Bovine Sialylated Milk Oligosaccharide Microinjection on Zebrafish Larvae Survival, Locomotor Behavior and Gene Expression ## Abstract Milk oligosaccharides are a complex class of carbohydrates that act as bioactive factors in numerous defensive and physiological functions, including brain development. Early nutrition can modulate nervous system development and can lead to epigenetic imprinting. We attempted to increase the sialylated oligosaccharide content of zebrafish yolk reserves, with the aim of evaluating any short-term effects of the treatment on mortality, locomotor behavior, and gene expression. Wild-type embryos were microinjected with saline solution or solutions containing sialylated milk oligosaccharides extracted from human and bovine milk. The results suggest that burst activity and larval survival rates were unaffected by the treatments. Locomotion parameters were found to be similar during the light phase between control and treated larvae; in the dark, however, milk oligosaccharide-treated larvae showed increased test plate exploration. Thigmotaxis results did not reveal significant differences in either the light or the dark conditions. The RNA-seq analysis indicated that both treatments exert an antioxidant effect in developing fish. Moreover, sialylated human milk oligosaccharides seemed to increase the expression of genes related to cell cycle control and chromosomal replication, while bovine-derived oligosaccharides caused an increase in the expression of genes involved in synaptogenesis and neuronal signaling. These data shed some light on this poorly explored research field, showing that both human and bovine oligosaccharides support brain proliferation and maturation. ## 1. Introduction Milk is fundamental in the early nutrition of all baby mammals, being their primary source of nutrients and bioactive compounds [1]. Proteins, lipids, carbohydrates, minerals, and vitamins are the main milk nutrients necessary to support the newborn’s development until the weaning period [2]. Milk oligosaccharides, counted as the third component in quantity of the solid part of milk, are a complex class of glycans that have no direct nutritional value for the offspring, but act as bioactive factors in numerous defensive and physiological functions [3]. Although indigestible by infants, on reaching the large intestine, they act as prebiotics, stimulating the growth of beneficial microbiota [3,4], and as defensive agents against various toxins, pathogenic bacteria and influenza viruses, thus limiting the onset of enteric infections [5,6]. Moreover, milk oligosaccharides not only modulate the immune system [7], promoting beneficial effects on allergic disorders [3] and autoimmune diseases [8], but also contribute to brain development and cognition [9]. These molecules are synthesized in the mammary gland starting from monosaccharide units, which are combined with a lactose core through numerous possible linkages, resulting in a wide range of different structures that reflect the multitude of their biological functions [10]. Milk oligosaccharides in human breast milk have been extensively investigated and more than 200 different types have already been found [11]. On the other hand, domestic animal milk oligosaccharides have been less studied and only 48 types have been characterized in cow, goat, sheep, pig, horse, and camel milk [12]. Two classes of oligosaccharides are naturally found in milk: neutral and acidic. Chemically, the first has a fucosylated end, whereas the latter has a sialic acid terminal residue. Neutral oligosaccharides are the most common in human milk, whereas sialylated oligosaccharides account for about 80–$90\%$ of total oligosaccharides in non-primate animal milk [12]. The total sialylated oligosaccharide content of milk from traditional dairy animals is 10–100 times lower than that of human milk [12,13,14]. Sialylated milk oligosaccharides (SMOs) seem to play an essential role in brain development as they act as the main suppliers of sialic acid, an important constituent of key brain proteins as gangliosides and myelin associated glycoprotein [7,15,16] involved in the formation of brain structures sustaining cognition. In this context, it is well known that early nutrition can modulate nervous system development [17] and, through changes in gene expression patterns and nutrient-sensitive signaling pathways, can lead to epigenetic imprinting that may have lifelong effects on health status [18]. Moreover, several studies have shown that the duration of breastfeeding is the main associated variable to the infant intelligence and cognition performances [19]. Wang [20] has postulated that low levels of sialic acid may be a main disadvantage of infant formula milks. These data have been supported by brain imaging studies showing that breast milk promotes infant brain development, particularly white matter growth [21]. An increasing body of literature suggests that newborns could benefit from exogenous sialic acid supplementation in order to meet the demands of the rapidly growing brain [4], and also that several diseases of the brain (such as mental retardation, schizophrenia, and Alzheimer’s and senile dementia) are associated with lower brain sialic acid and/or ganglioside content [22,23]. It seems that intake of compounds containing sialic acid may reduce the decline in brain activity that occurs with aging [15]. Sialylation is a process essential not just for the brain, but also for normal muscle function [24] and skeletal development [25]. Importantly, while adult mammals can endogenously synthesize sialic acid from glucose and other products of glycolysis, newborns largely lack this capability, and thus require an exogenous source of sialic acid [16]. Studies in animal models suggest that administration of SMOs and/or sialic acid was associated with enhancement of specific and non-specific immunological resistance [26], increases in cerebral and cerebellar ganglioside content [13,15], and positive effects on microbiota, behavioral responses during stressor exposure [27], and cognitive abilities [20,28]. Rodents receiving neonatal exogenous supplementation of sialic acid showed improved novel object recognition memory and long-term potentiation (a cellular process thought to be associated with memory) [16,29]. Furthermore, mouse pups fed with a milk deprived of the most abundant SMOs, i.e., 6′-sialyllactose (6′SL) or 3′-sialyllactose (3′-SL), exhibited impairments in memory, attention, and hippocampal long-term potentiation [30]. In the current study, using a microinjection technique, we attempted to increase the sialylated oligosaccharide content of zebrafish yolk reserves at early stages of embryogenesis, with the aim of evaluating the short-term effects of the treatment on mortality, locomotor behavior, and gene expression. The zebrafish is already considered an ideal organism for neurobiology and genetics research and for exploring possible new drug treatments [31,32,33,34,35]. The use of zebrafish, rather than mammalian models, for genetic and drug studies offers numerous advantages, such as high fecundity, egg transparency, rapid ex utero embryogenesis (which allows noninvasive drug treatments at early embryonic stages) and affordability [36,37,38]. In this context, numerous behavioral protocols have already been validated for this species, even in its larval stage [39,40]. Despite the large differences in embryo development and nutrition between fish and mammals, sialic acid is found in all vertebrates (even birds, reptiles, and amphibians) and essentially in all tissues, with the highest concentration in the central nervous system [17]. While the delivery of external nutrients in mammal newborns is limited to maternal nutrient transfer (prenatal) and consequently to the onset of milk feeding (postnatal), in zebrafish it is possible to easily exert a nutraceutical stimulus during embryogenesis, injecting a specific compound directly into the egg yolk, prior the hatching event [18]. Research on the effects of SMOs administration on health and brain functions is still limited and no experimental data on important vertebrate models, such as zebrafish, are available in literature to the best of our knowledge. ## 2.1. Locomotor and Thigmotactic Behavior As the developing nervous system presents high sensitivity to drug exposures, a developmental neurotoxicity analysis was performed on wild-type zebrafish larvae microinjected into the yolk with either sialylated milk oligosaccharides solutions (at doses equal to 100 mmol/L, purified from human or bovine milk) or saline solution (placebo group). The same analyses were performed even in untreated wild-type larvae, as the control group. For this purpose, two standardized behavioral tests were used. The first one was the tail-coiling test, which allows to evaluate the action mode of compounds interfering with neurotransmission. This test is based on the analysis of the spontaneous embryo tail coiling inside the egg, and it involves side-to-side contractions of the trunk, consisting of the first motor behavior of embryos [41]. Coiling analysis at 30 h post fertilization (hpf) showed similar burst activity between the controls and treated embryos, with no significant differences observed between groups (Figure 1). The second behavioral test used in this study was the visual motor response (VMR) test, carried out on hatched larvae of 5 days post fertilization (dpf). This assay allows to analyze the larvae locomotor behavior in different light conditions, with the aim of evaluating the sensorimotor function of zebrafish larvae, and to characterize neurobehavioral responses to chemicals. Typically, untreated zebrafish larvae exhibit higher locomotor activities during the dark phase than in the light phase, because a dark environment offers a better chance of survival for the larvae [42]. Indeed, calculation of average locomotor activity per minute revealed that the zebrafish larvae covered a greater distance and moved at greater speed during dark than light phases, regardless of the experimental treatment (Supplementary Figure S1). However, locomotion data from the VMR test reported in Figure 2, showed that during the dark phase, both distance and velocity of movement were found to be significantly different between the control and SMO-treated larvae. In particular, throughout the dark phase, larvae treated with both SMOs displayed increased test plate exploration, with greater distance moved and faster velocity of movement compared with the control group values. In order to highlight a potential stress response to SMO treatments, the thigmotaxis behavior, which is a well-established index of anxiety, was evaluated in both light and dark conditions, by using the data obtained from the VMR test. The thigmotaxis data showed that all larvae spent significantly more time in the outer versus the inner zone (i.e., more thigmotactic behavior) throughout the test (Figure 3), and no significant differences were found between the controls and treated groups, in either the light or dark phases. Analysis of average thigmotactic behavior per minute showed that zebrafish larvae spent more time in the outer zone during light versus dark phases, regardless of the experimental treatment (Supplementary Figure S2). This obviously implies that all the larvae (controls and treated groups) explore the center of the well plate more during darkness. ## 2.2. Larval Survival Rate The larval survival rate at 5 dpf was high (>$80\%$) in all the groups of zebrafish larvae, therefore no significant differences were found between controls, placebo, and the two SMO groups (Figure 4). The highest survival rate was observed in the control group ($90.59\%$) and the lowest in the placebo group microinjected with saline solution only ($80.14\%$), while intermediate values were observed in the two groups treated with milk oligosaccharides: $85.96\%$ in larvae treated with sialylated human milk oligosaccharides (SHMOs) and $88.62\%$ in larvae treated with sialylated bovine milk oligosaccharides (SBMOs). ## 2.3. Comparative Analysis and Bioinformatic Categorization of Differentially Expressed Genes In order to better characterize the effects of the different SMO treatments on zebrafish development, we planned to obtain transcriptomic profiles out of mRNAs taken from larvae either microinjected with human or with bovine SMOs, or from non-microinjected controls. Sequencing libraries were therefore generated from three different pools of zebrafish larvae per each experimental condition, with each pool containing 12 individuals. After sequencing, reads were trimmed, aligned, annotated on the zebrafish database, and compared for differential expression with the DESeq2 method. To allow comparison of gene expression profiles, the normalized gene abundance level of each microinjected embryo pool, compared with the profile of non-microinjected ones, was calculated, and reported as log2 fold change (log2(FC)). Transcripts showing a log2(FC) ≥ 0.58 and an adjusted p-value (p-adj) ≤ 0.05 were assigned as differentially expressed. A further profile was obtained by comparing the treatments, in order to discriminate the specificity of changes found. The transcriptomic profiles identified 1137 differentially expressed transcripts in SHMO-treated embryos (508 were up-regulated and 629 down-regulated, Supplementary Table S1), and 2296 in SBMO-treated embryos (883 up-regulated and 1413 down-regulated, Supplementary Table S2). The comparison of the two treatments showed that 879 transcripts were specifically dysregulated (248 up- and 631 down-regulated, Supplementary Table S3). Differentially expressed genes (DEGs) were categorized using the IPA bioinformatic suite (https://www.qiagen.com, accessed on 31 May 2022). In SHMO-treated larvae, this step revealed three different macro-categories related to: (i) embryonic development (BAG2 Signaling Pathway, Cell Cycle Control of Chromosomal Replication); (ii) redox homeostasis (Antioxidant Action of Vitamin C, Glutathione Redox Reactions I, Unfolded Protein Response, Heme Degradation, Ferroptosis Signaling Pathway); and (iii) regulation of lipids, glucose and cholesterol metabolism (Heme Degradation, LXR/RXR Activation, HIF1α Signaling, Superpathway of Cholesterol Biosynthesis) (Figure 5A). Instead, the SBMO transcriptomic profile showed multiple differentially expressed genes shared with the SHMO group profile, and related to: (i) nervous system development (Glutamate Receptor Signaling, Endocannabinoid Neuronal Synapse Pathway, Synaptogenesis Signaling Pathway, Calcium Signaling); (ii) redox homeostasis (Antioxidant Action, Production of Nitric Oxide and Reactive Oxygen Species in Macrophages); (iii) metabolism (Calcium Signaling, LXR/RXR Activation, Xenobiotic Metabolism PXR Signaling Pathway, Xenobiotic Metabolism AHR Signaling Pathway); and (iv) inflammatory response (GP6 Signaling Pathway) (Figure 5B). Further scrutiny of the main annotations in the profiles of the SMO-treated larvae pinpointed disease and functional annotations related to nervous system, neurodevelopmental and movement disorders as the main high-ranked categories affected by the treatment (Figure 5C). For a better understanding of biological processes and diseases commonly affected by the treatments, we performed a comparison of the previously assessed core analyses, using the z-score values of common annotations. Several biological functions were severely affected in both SHMO- and SBMO-treated embryos and predicted to be activated or inhibited with a similar trend. Detailed information about expression of DEGs within the main categories can be found in Supplementary Figures S3–S21. Functions mainly related to neuronal development and free-radical scavenging were also annotated using this comparative approach (Figure 5D). Whole datasets from RNA-seq experiments related to the two different treatments on zebrafish larvae are also represented as Volcano plots (Figure 6). In addition, the relationship between DEGs and main categories were reported with gene ontology (GO) chord plots, also allowing graphical representation of the level of expression of single genes. In particular, the top50 up- and down-regulated genes for both the SHMO (Figure 7A and Figure 7B, respectively) and SBMO treatment (Figure 8A and Figure 8B, respectively) were taken into account for the analysis. The differential effect of the two treatments was clearly shown in these plots. For instance, DEGs belonging to the class of Cell Cycle Control of Chromosomal Replication were mostly up-regulated in the SHMO treatment, together with genes related to BAG2 Signaling (Figure 7A). In the SBMO treatment, instead, up-regulation occurs mostly for Glutamate Receptor and Calcium Signaling pathways (Figure 8A), with not even one DEG in the first category reported as downregulated (cyan chords are absent in Figure 8B; for details, also see Supplementary Figures S3–S21). ## 3. Discussion Sialylated milk oligosaccharides seem to play an essential role in brain development, and it is well known that early nutrition can modulate nervous system development [17] and can have lifelong effects on health status. It has been hypothesized that adequate intake of sialic acid is crucial for infant brain growth and development [43]. In this work, we used zebrafish embryos as a model to study the effects of milk-derived sialylated oligosaccharides on embryo development. The SHMOs and SBMOs were injected into fertilized zebrafish eggs, and larvae were collected at 5 dpf for behavioral and transcriptomic analyses. Zebrafish embryos develop rapidly inside the eggs and show their first spontaneous movements at an early stage of development. This locomotor behavior begins at 17 hpf, peaks at 19 hpf, and then decreases gradually thereafter [44]. It has recently been suggested that the period from 26 to about 30 hpf is characterized by relative stability of all embryo coiling activity parameters, analysis of which could constitute a rapid new way to screen for developmental neurotoxicity induced by drugs [45]. Analysis of tail flicks at 30 hpf in treated embryos did not show significant alterations in burst activity (i.e., the percentage of time an embryo is moving) compared with controls, excluding a putative neurotoxicity effect of used milk oligosaccharides. Furthermore, the current study seems to confirm the appropriateness for zebrafish embryos of the chosen injection timepoint (4.7 hpf) and volume (4.6 nL), given that no negative effects on survival or development were recorded. In fact, survival rates were similar across controls, placebo and both SMO treatment groups, and comparable with the results obtained by other researchers [18,46]. Locomotor behavior analysis was performed using the VMR test, which is based on “a stereotypical series of larval motor responses provoked by changes in ambient illumination” [47]. The VMRs triggered by drastic changes in illumination could be elicited both at light onset and at light offset [48]. The VMR at light offset has been shown to consist of a significant increase in locomotion for about 30 min, after which locomotor activity returns to the baseline level [49]. Conversely, at light onset, the increase in locomotion lasts for about 30 s [49]. Hyperlocomotion upon sudden transition to the light condition has been attributed to increased stress/anxiety [50]. That said, regardless of the stimulus-response model, zebrafish larvae typically exhibit higher locomotor activity during dark phases [51,52], as occurs in mice [30]. Accordingly, all our three experimental groups of 5 dpf larvae showed a significant increase in locomotor activity during dark compared with light exposure. Moreover, no group showed a decrease in locomotor activity on the light-dark transition (a response that could indicate possible sedation or tissue damage) [53]. During the dark phase, both SHMO- and SBMO-treated larvae showed enhanced locomotor behavior (distance moved and velocity) compared with the control group. Therefore, in accordance with Basnet and colleagues [50], we could possibly argue that the light-dark transition seemed to induce a clearer stress response in treated compared with control group larvae. Nevertheless, this argument is contradicted by the results of our analysis of thigmotaxis, which is a well-established sign of anxiety-like behavior [54]: we did not observe any increase for time spent in the outer zone by treated larvae in either phase. A possible explanation for these contrasting data is that the drastic change in illumination produced not an enhanced escape behavior in response to a threatening stimulus, but rather an enhancement of exploratory behavior, with the larvae seeking a dark environment that offers a better chance of survival [54]. Furthermore, even allowing for the stress response, we could argue that our results could be ascribed to an improvement in coping behavior, i.e., the automatic action taken to deal with a threatening stimulus. In line with our results, the intake of 6′SL during the early life of mice was associated with changes of locomotor activity [30]. Unfortunately, a discrimination between light and dark phase was not carried out in this latest study on rodents. However, adopting a comprehensive approach, these authors observed that behavioral alterations are associated with modifications of the serotoninergic system. According to our RNA-seq data, both treatments seemed to exert antioxidant effects (e.g., vitamin C action) in developing fish. Nevertheless, striking differences were observed between the two treatments. The SHMOs seemed to increase expression of genes related to cell cycle control and chromosomal replication. The analysis also showed increased expression of genes related to both Unfolded Protein Response (UPR) and BAG2 Signaling Pathway, and an anti-apoptotic action. This suggests that SHMO supplementation could play an important role in supporting a high proliferation rate, as in the developing cerebral cortex for example. Rapid increases in cell numbers in tissues of this kind need to be accompanied by strict regulation of the folding of newly produced proteins, to ensure their proper functioning, together with close control of the genomic identity of daughter cells, so as to avoid increases in cells with imbalanced numbers of chromosomes [55]. Thus, decreased expression of UPR-related genes has indeed been found to induce premature neurogenesis, leading to microcephaly [56], and a reduction in the cortical size is typically seen in several models with alteration of replicative forks and/or mitotic checkpoints [57,58,59,60]. On the other hand, the zebrafish larvae treated with SBMOs seemed to display a quite different transcriptomic profile, with increased expression of genes involved in synaptogenesis and neuronal function such as glutamate receptors and genes involved in calcium signaling and endocannabinoid signaling pathways. Interestingly, the discrepancies observed might reflect species-specific features of human and bovine newborn brains. In the former, the brain tissue proliferation rate remains high, as shown by the dramatic growth occurring during the peri- and postnatal periods, especially in the cerebral cortex [61,62,63]. For this reason, the human newborn can be considered an external fetus. Conversely, calves might require higher energy because they need to have the ability to stand and run within minutes of birth, a function requiring full maturation of neural circuits. Differences on RNA-seq data between the SHMO and SBMO groups may also be due to the different concentration of 3′SL and 6′SL in human and bovine milk. According to our results, investigating the long-term consequences of a 6′SL-deficient milk in mice, it was found that maternal 6′SL adjusts cognitive development through a short-term up-regulation of genes modulating formation and patterning of neuronal circuits in the prelimbic medial prefrontal cortex (PFC) [30]. Interestingly, gene expression differences were not observed in the hippocampus (neither at eye-opening nor in adulthood) and the PFC-specific differences nearly vanished in adulthood. Recently, a connection between gene expression and behavior was reported in zebrafish larvae exposed to drugs of abuse [64]. According to these latter authors, the exposure to drugs may affect behavioral outcomes, but it was difficult to predict the direction of the effect. In particular, the developmental exposition to drug caused a dysregulation of the locomotor behavior and a differential expression of the innate immune genes, immediate early genes (regulators of synaptic plasticity) and circadian genes, essentially due to neuroinflammation. In our opinion, both SHMO- and SBMO-treated larvae, showing an enhanced locomotor behavior during the dark phase and an increased expression of genes involved in cell cycle control, chromosomal replication, synaptogenesis, and neuronal function, could be considered more adventurous and/or less scared compared with the control group individuals. However, the impact of SMO administration needs further mechanistic investigation. ## 4.1. Zebrafish Care and Maintenance Adult wild-type (WT) AB strain fish were maintained at the Neurobiology and Molecular Medicine facility at the IRCCS Stella Maris Foundation (Pisa, Italy) according to standard procedures [65]. Zebrafish eggs were obtained from the natural spawning of 8-month-old adults. Once collected, fertilized eggs were incubated at 28° C in petri dishes (Ø 10 cm) filled with 50 mL of egg water (60 mg of “Instant Ocean®” sea salt added to 1 L of distilled water), with an initial stock density of 100 eggs per dish. Sea salt used for the preparation of the egg water was purchased from Spectrum Brands (Blacksburg, VA, USA). Handling of zebrafish complied with the guidelines of our institution’s internal animal care committee, and experiments were performed under the supervision of the Animal Care and Use Committee of the University of Pisa, in accordance with European Directive No. 63 of $\frac{22}{09}$/2010 on the protection of animals used for scientific purposes. Every effort was made to minimize both animal suffering and the number of animals needed to collect reliable scientific data. ## 4.2. Milk Oligosaccharide Purification and Analysis Human and bovine milk samples, each with a volume of about 20 L, were employed by the laboratory of the Dalian Institute of Chemical Physics (Chinese Academy of Sciences, Dalian, China) to obtain the milk oligosaccharide fractions used in the current study. The whole isolation-separation process was carried out in accordance with Li et al. [ 66]. Briefly, both milk samples, initially stored at −40 °C, were first thawed at 4 °C and then filtered using a 750 KDa and a 50 KDa hollow fiber membranes (Shandong Bona Biology, Shandong, China) to remove most of the lipids and proteins. Subsequently, the filtrates, mainly containing lactose and oligosaccharides, were injected into an electrostatic repulsion hydrophilic interaction chromatography preparation column, in order to separate the SMO fraction from lactose and neutral oligosaccharides, following Yan et al. [ 5]. An ACQUITY Ultraperformance system, coupled with a Xevo TQ-XS Triple Quadrupole Mass Spectrometry (Waters Corporation, Milford, MA, USA), was used to analyze the oligosaccharide samples obtained. The chromatographic separation was performed on an ACQUITY BEH Amide column with a pore size of 130 Å (particle size: 1.7 μm; inner diameter: 2.1 mm; length: 150 mm) (Waters Corporation). Reagents and standards were obtained from Sigma–Aldrich (Saint Louis, MI, USA) and pure water (18.2 MΩ) was generated by an ELGA ultrapure water system from Veolia Water Technologies (Birmingham, UK). The composition of the two mobile phases were: 5 mmol/L ammonium acetate in acetonitrile, and 5 mmol/L ammonium acetate in pure water. The elution program was performed as follows: 7 min linear gradient from $30\%$ (v/v) to $80\%$ (v/v); 2 min isocratic $80\%$ (v/v) for column washing; back to $30\%$ (v/v) and retain 1 min for column equilibrium. The main oligosaccharides in both milks were 3′-SL [Neu5Acα[2,3]Galβ[1,4]Glc] and 6′-SL [Neu5Acα[2,6]Galβ[1,4]Glc]. The specific quantification of 3′SL and 6′SL for the SHMO sample was equal to 141.10 and 210.57 mg/g respectively, while the SBMO contained mainly 3′SL (207,30 mg/g of 3′SL and 25.88 of 6′SL). ## 4.3. Microinjection of SMOs For the microinjection procedure, embryos were handled as described by Schubert et al. [ 67]. Briefly, zebrafish embryos were aligned at the edge of a microscope slide, placed in a petri dish, so that the eggs were immobilized during the microinjection procedure. Microinjection into the yolk was performed under a Leica M205FA stereo-microscope (Leica, Wetzlar, Germany) at 4.7 hpf, according to Rocha et al. [ 18], with 4.6 nL of either saline solution (Danieau solution: 58 mmol/L NaCl, 0.7 mmol/L KCl, 0.4 mmol/L MgSO4, 0.6 mmol/L Ca(NO3), 2.5 mmol/L Hepes, pH 7.6) or SMO solutions. The SHMO and SBMO solutions were each prepared with the corresponding purified SMO fraction dissolved in the Danieau solution, to obtain a concentration of 100 mmol/L. The chosen concentration was based on the maximum solubility of the SMOs in the Danieau solution. Typically, the microinjection procedure in zebrafish is used for the inclusion of RNA/DNA, antisense morpholinos or CRISPR/Cas9, and the period selected for performing microinjection range from 1- to 2-cell stages, according to standard procedures [65]. In this study, the embryo microinjection was performed at 4.7 hpf (approximately at $30\%$ epiboly stage) since it has been demonstrated that injection into the yolk during the epiboly stage leads to successful diffusion of the injected material within the yolk without later outward flux [18]. Furthermore, at the $30\%$ epiboly stage the yolk syncytial layer (implicated in transporting nutrients from the yolk to the embryonic cells and later to larval tissues) is already formed [18]. ## 4.4. Locomotion Analysis In embryos at 30 hpf, coiling behavior was measured as recently described by Iacomino et al. [ 68] using the Danioscope software (Noldus Information Technology, Wageningen, The Netherlands). At 120 hpf, larval locomotion (distance and velocity) and thigmotactic behavior were measured using the Daniovision system connected with Ethovision XT12 (Noldus Information Technology), a specific video tracking software. Briefly, single larvae were taken from the rearing dishes and transferred into a 24-well plate along with 1 mL of egg water per well (1 larva/well). The plate was then placed in the DanioVision system and larval behavior was monitored for a total of 10 min, following Schnörr et al. [ 54]. The procedure was performed in two steps, including a 6-min acclimatization phase (minutes 0–6) and a 4-min interaction phase (minutes 7–10). In the acclimatization period, lights were kept ON (intensity level: $100\%$) and at minute 7 lights were turned OFF abruptly and were kept OFF until the end of the procedure. In order to measure thigmotaxis, a distinction was made between the inner and outer zone of each well. The width of the outer zone was set at 4 mm from the border of the well, while the diameter of the inner zone was set at 8 mm (see Figure 9). ## 4.5. Behavioral Endpoints All swimming patterns were recorded automatically, and the following behavioral endpoints were measured:Burst activity during 30 s of the test procedure, expressed as %.General locomotor activity: this was measured as the total distance moved (mm) and velocity (mm/s) of movement over the whole area of the well during each minute of the test procedure, and under different conditions (lights ON vs. lights OFF).Thigmotaxis: this was presented as time spent (s) in the outer zone of the well during each minute of the test procedure, and under different conditions (lights ON vs. lights OFF). ## 4.6. RNA-Seq Analysis The whole transcriptomic analysis was carried out on zebrafish embryos microinjected with SMO solutions. Specifically, we investigated both SHMO- and SBMO-microinjected embryos. The WT non-microinjected embryos were also analyzed as a reference (Ctrl). Total RNA was extracted from larvae at 5 dpf (36 larvae per group) using the Quick RNA miniprep kit (ZymoResearch, Irvine, CA, USA), according to the manufacturer’s instructions, and checked for purity using NanoPhotometerTM Pearl, version 1.2 (IMPLEN, Westlake Village, CA, USA); integrity (RNA integrity number > 7) was assessed using the RNA 6000 Pico Kit on a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). Indexed cDNA libraries were prepared from 350 ng of total RNA using the TruSeq Stranded kit (Illumina, San Diego, CA, USA), quantified by real-time PCR, pooled at equimolar concentration, and sequenced with Illumina technology applying standard manufacturer protocols. The quality of reads was assessed using FastQC software Version 0.11.9 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/, accessed on 5 May 2022). Raw reads with more than $10\%$ of undetermined bases or more than 50 bases with a quality score < 7 were discarded. Subsequently, reads were clipped from adapter sequences using Scythe software Version 0.994 (https://github.com/vsbuffalo/scythe, accessed on 5 May 2022), and low-quality ends (Q score < 20 on a 15-nt window) were trimmed with Sickle (https://github.com/vsbuffalo/sickle, accessed on 5 May 2022). Table S4 shows the number of sequenced and trimmed fragments. Filtered reads were aligned to the current zebrafish reference genome assembly (GRCz11) using the STAR aligner (http://code.google.com/p/rna-star, accessed on 5 May 2022). ## 4.7. Bioinformatic Analysis and Categorization of Transcriptomic Data Within the comparisons, i.e., the SHMO treatment vs. Ctrl, SBMO treatment vs. Ctrl, and SHMO treatment vs. SHMB treatment, sets of DEGs (corresponding to identified transcripts) were evaluated by QIAGEN’s Ingenuity® Pathway Analysis (IPA®, Spring Release, April 2022), to identify biological processes and disease and functional annotations related to a specific treatment. Specifically, we performed three independent core analyses, based on gene FC to calculate directionality (z-score) of dysregulated pathways, whereas the Ingenuity Knowledge Base reference set was used for p-value calculation. The most meaningful functional annotations (p-value < 0.05; z-score ≥ 1.5) were taken into account to estimate the predicted pathway activation or inhibition, and graphically represented. Moreover, to investigate whether significant DEGs found in the different experimental conditions might have a potential modifier role in both locomotion and neurodevelopment, we filtered disease and functional annotations, selecting only those involved in movement disorders, neurological diseases, and neurodevelopment, and reported with a z-score ≥ 1.5 for SMO vs. Ctrl analyses (but not for SHMO vs. SBMO ones). For both SHMO and SBMO vs. Ctrl analyses, GO chord plots were plotted by using a free online platform for data analysis and visualization: https://www.bioinformatics.com.cn/en, accessed on 19 July 2022. ## 4.8. Statistical Analysis All data were analyzed applying either parametric or non-parametric methods, depending on the distribution of the response variable in question, shown by the Shapiro–Wilks test. Homogeneity of variance was assessed using the Levene test. Post-hoc comparisons were performed using the Mann–Whitney U test with Bonferroni’s correction, or an unpaired t-test following non-parametric analysis of variance. All statistical analyses were performed using GraphPad Prism (GraphPad Software, Inc., CA, USA). ## 5. Conclusions In this work, we used zebrafish as a model to study the effects of milk-derived sialylated oligosaccharides on embryo development. The study confirms that the administration of SMOs extracted from human and bovine milk seems to be safe, given that no negative effects on survival or development were observed. Larval locomotor behavior analysis suggest that SMOs supplementation produced an enhancement of exploratory behavior in the dark environment, which offers a better chance of survival for the little fishes. The RNA-seq data showed that SMO-treatments pinpointed disease and functional annotations related to nervous system, neurodevelopmental and movement disorders as the main high-ranked categories affected by the treatment. In particular, SHMO supplementation could play an important role in supporting a high cell proliferation rate, as occurs in the developing cerebral cortex. On the other hand, SBMO treatment seemed to display a quite different transcriptomic profile, with increased expression of genes involved in synaptogenesis and neuronal function, such as glutamate receptors and genes involved in calcium signaling and endo-cannabinoid signaling pathways. Interestingly, the discrepancies observed might reflect species-specific features of human and bovine newborn brains. However, the impact of SMO administration needs to be explored for longer periods, from embryo to adulthood. In addition, new data on zebrafish brain morphology and imaging could be of interest to better evaluate SMO supplementation on neurodevelopment, also in disease conditions. ## References 1. Walker A.. Breast milk as the gold standard for protective nutrients. J. Pediatr. (2010) 156 S3-S7. DOI: 10.1016/j.jpeds.2009.11.021 2. Pereira P.C.. Milk nutritional composition and its role in human health. Nutrition (2014) 30 619-627. DOI: 10.1016/j.nut.2013.10.011 3. 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--- title: 'Secondary Metabolite Profiling, Antioxidant, Antidiabetic and Neuroprotective Activity of Cestrum nocturnum (Night Scented-Jasmine): Use of In Vitro and In Silico Approach in Determining the Potential Bioactive Compound' authors: - Saheem Ahmad - Mohammed Alrouji - Sharif Alhajlah - Othman Alomeir - Ramendra Pati Pandey - Mohammad Saquib Ashraf - Shafeeque Ahmad - Saif Khan journal: Plants year: 2023 pmcid: PMC10051713 doi: 10.3390/plants12061206 license: CC BY 4.0 --- # Secondary Metabolite Profiling, Antioxidant, Antidiabetic and Neuroprotective Activity of Cestrum nocturnum (Night Scented-Jasmine): Use of In Vitro and In Silico Approach in Determining the Potential Bioactive Compound ## Abstract This study aims to describe the therapeutic potential of C. nocturnum leaf extracts against diabetes and neurological disorders via the targeting of α-amylase and acetylcholinesterase (AChE) activities, followed by computational molecular docking studies to establish a strong rationale behind the α-amylase and AChE inhibitory potential of C. nocturnum leaves-derived secondary metabolites. In our study, the antioxidant activity of the sequentially extracted C. nocturnum leaves extract was also investigated, in which the methanolic fraction exhibited the strongest antioxidant potential against DPPH (IC50 39.12 ± 0.53 µg/mL) and ABTS (IC50 20.94 ± 0.82 µg/mL) radicals. This extract strongly inhibited the α-amylase (IC50188.77 ± 1.67 µg/mL) and AChE (IC50 239.44 ± 0.93 µg/mL) in a non-competitive and competitive manner, respectively. Furthermore, in silico analysis of compounds identified in the methanolic extract of the leaves of C. nocturnum using GC-MS revealed high-affinity binding of these compounds with the catalytic sites of α-amylase and AChE, with binding energy ranging from −3.10 to −6.23 kcal/mol and from −3.32 to −8.76 kcal/mol, respectively. Conclusively, the antioxidant, antidiabetic, and anti-Alzheimer activity of this extract might be driven by the synergistic effect of these bioactive phytoconstituents. ## 1. Introduction Oxidative stress induced by reactive oxygen species (ROS) is deleterious to proteins, lipids, cell membranes, and DNA, and contributes to the development of several chronic and degenerative disorders [1]. An imbalance between oxidative stress and the antioxidant defense system causes cellular dysfunction, resulting in the development of many chronic diseases, including diabetes mellitus (DM) and neurological disorders [2,3]. DM is a metabolic disorder characterized by impaired carbohydrate metabolism resulting in elevated fasting and postprandial blood sugar levels. During persistent hyperglycemia, glucose can react with proteins nonenzymatically through the process of glycation [4,5]. Glycation of proteins and formation of advanced glycation end products are involved in the pathogenesis of several diabetic complications, including neurological dysfunction [6,7]. The prevalence of diabetes is increasing globally—approximately 537 million adults lived with diabetes in 2021 and the disease accounted for more than 6.0 million fatalities, half of which were in cases that were still undiagnosed. These numbers are predicted to increase to ~645 and ~785 million by 2030 and 2045, respectively [8]. Alzheimer’s disease (AD) is the most common form of dementia, with memory loss, language inability, cognitive dysfunction, visuospatial skill deficiency, and difficulty in judgement being the most common symptoms [9,10]. Moreover, abnormal accumulation of β-amyloid in the synaptic cleft of the neurons and of tau-neurofibrillary tangles plaques inside it disrupt the neuronal function [11]. Acetylcholine (ACh) is a chemical released at the neuromuscular junction that acts as a neurotransmitter (chemical message) allowing interneuronal communication. In the synaptic cleft, free ACh is synthesized by acetylcholinesterase (AChE) and it is ensured that no excess ACh is present for continuous activation of receptors [11]. Although the underlying cause of AD remains unclear, the pathogenesis is firmly associated with cholinergic transmission dysfunction. The inhibition of AChE is a widely accepted therapeutic strategy for symptomatic treatment of AD [12]. The incidence of both DM and AD is increasing. Moreover, diabetic patients have a five-fold higher risk of developing AD than nondiabetic individuals [3,13,14,15]. Diabetes patients also show reduced baseline cognitive abilities, such as those related to memory, learning, and judgment [13]. The relationship of hyperglycemia and insulin signaling anomalies with AD has been reported to be strong; because of which, AD is often considered as a metabolic brain disease [10,16,17]. DM and AD share a common pathophysiology, involving oxidative stress, inflammation [18], high cholesterol levels, neuronal degeneration, β-amyloid accumulation [19], phosphorylation of tau protein, and glycogen kinase-3 synthesis [20]. Antidiabetic drugs that reduce insulin resistance in the brain could prevent AD or dementia [15]. However, despite their impactful therapeutic response against DM and AD, such drugs fail to reverse the complications and are associated with prominent side effects [21]. Thus, alternative natural sources are being explored for therapeutic compounds effective against both DM and AD that would less likely be associated with complications. Strategies aimed at reducing oxidative stress and delaying the absorption of glucose and ACh synthesis via inhibition of α-amylase and AChE have the potential for effective management of DM and AD. In this context, in the present study, we screened the antidiabetic and anti-Alzheimer’s potential of Cestrum nocturnum, a solanaceous shrub widely found in tropical and subtropical countries, including Australia, China, India, and America [22]. The leaves are simple, narrow lanceolate, smooth, and glossy, with an entire margin. C. nocturnum has garnered the attention of researchers in view of its antioxidative [23], antimicrobial [24], antifungal [22,24], anti-inflammatory [25], and hepatoprotective properties [26]. The antidiabetic and antihyperlipidemic activities of C. nocturnum have been reported in rodents [27,28]. In addition, several bioactive phytoconstituents such as flavonoids, glycosides, tannins, coumarins, anthocyanins, sapogenins, and sterols have been also identified, which have numerous biological activities such as antibacterial, antifungal activities [22]. In this study, for the first time, we evaluated the efficacy of extracts of the leaves of C. nocturnum as potent dual inhibitors of α-amylase and AChE. In addition, molecular docking studies of secondary metabolites in the methanolic (MeOH) extract of leaves of C. nocturnum identified using gas chromatography-mass spectrometry (GC-MS) analysis were performed to obtain mechanistic insights into their inhibitory activities. ## 2.1. Phytochemical Screening and Total Phenolic Content in Extracts of the Leaves of C. nocturnum C. nocturnum leaves were sequentially extracted in n-Hexane, dichloromethane (DCM), ethyl acetate (EtOAc), methanol (MeOH), and water. The percent yield of extraction is shown in Table 1. Phytochemical screening revealed significant amounts of bioactive compounds, including flavonoids and polyphenols (Table 2) with free radical quenching ability, in the MeOH extract. The reductones serve as antioxidants by donating a hydrogen to the free radical, often corresponding with the reducing capacity of compounds, which may be a significant signal of its antioxidant potential [29,30,31]. ## 2.2. α,α-Diphenyl-β-picrylhydrazyl (DPPH) Assay DPPH is a relatively stable radical that is widely used to evaluate the quenching ability of antioxidants from natural sources such as fruit and plant extracts. The DPPH scavenging ability of different extracts of the leaves of C. nocturnum, at various concentrations, is presented as % inhibition in Figure 1. The MeOH extract, with an IC50 value of 39.12 ± 0.53 µg/mL, was found to be the most potent in neutralizing the DPPH radical. The IC50 of the reference standard, ascorbic acid, was 15.12 ± 0.65 µg/mL (Table 3). ## 2.3. ABTS Radical Scavenging Assay The ABTS radical cation scavenging assay is widely used to evaluate the antioxidant potential of plant and fruit extracts and purified compounds. All the extract of the leaves of C. nocturnum neutralized the ABTS radical in a dose-dependent manner via electron donation to the radical (Figure 1). The inhibition of the ABTS radical was highest for the MeOH fraction (IC50 20.94 ± 0.82 µg/mL) and that for the standard, ascorbic acid, was $94.33\%$ (IC50 22.76 ± 0.43 µg/mL) (Table 3). The percent inhibition by each fraction has been shown in the Figure 1. ## 2.4. Ferric Reducing Antioxidant Power (FRAP) The FRAP assay was used to evaluate the ferric-reducing potential of distinct extracts of the leaves of C. nocturnum. The outcomes demonstrated that MeOH has considerably higher FRAP values, 478.50 ± 4.56 µmol Fe (II)/g, compared to other extracts (Figure 2). ## 2.5. Total Phenolic Content The TPC was the highest in the MeOH extract (5.81 ± 0.2 µg gallic acid (GA) equivalents/mg extract) and lowest in the n-Hexane extract (1.43 ± 0.23 µg GA equivalents)/mg extract) (Figure 2). ## 2.6. Evaluation of α-Amylase Inhibition and Kinetics Studies to Explore the Mode of Action of the Extract To investigate the antidiabetic activity, the α-amylase inhibitory potential of different extracts was evaluated. The MeOH extract effectively inhibited α-amylase in a dose-dependent manner and had the lowest IC50 value of 188.77 ± 1.67 µg/mL compared with those of the other extracts (Figure 3, Table 3). The standard drug, acarbose, showed $75.58\%$ inhibition of α-amylase (IC50 41.54 ± 0.54 µg/mL) (Figure 3, Table 3). Furthermore, kinetics studies revealed noncompetitive inhibition of α-amylase by the MeOH extract unlike the competitive inhibition by acarbose (Figure 4). ## 2.7. Evaluation of Acetylcholinesterase Inhibition and Kinetics Studies to Explore the Mode of Action of the Extract The AChE enzyme activity was evaluated using a colorimetric method in which a yellow-colored 5-thionitrobenzoate anion, with an absorption maximum at 412 nm, is produced when thiocholine reacts with 5,5-dithio-bis-(2-nitrobenzoic acid) (DTNB). Amongst the five C. nocturnum leaf extracts, the MeOH extract exhibited the highest AChE inhibitory activity in a dose-dependent manner, with an IC50 of 239.44 ± 0.93 µg/mL (Figure 3, Table 3). The standard drug, tacrine, showed the lowest IC50 of 4.03 ± 0.47 µg/mL (Figure 3, Table 3). A kinetics study was performed to determine the mode of inhibition by tacrine and the MeOH extract. As is evident from the Lineweaver–Burk double reciprocal plot of 1/V vs. 1/[S] (Figure 4), the MeOH fraction showed a competitive inhibition, whereas Tac exhibited a noncompetitive inhibition, indicating that it binds to the allosteric site of the enzyme (Figure 4). ## 2.8. GC-MS Analysis The MeOH extract, which showed the highest antioxidant potential and significantly inhibited α-amylase and AChE, was subjected to the GC-MS analysis to determine its phytoconstituents. A total of 23 compounds were identified by comparing the GC-MS spectra against a reference (NIST) library (Table 4). The three major compounds in the MeOh extract were found to be 2,4-Di-tert-butylphenol ($20.05\%$), Precocene I ($18.76\%$), and Hexaglycerine ($14.46\%$), whereas Methyl 3-(3,5-ditert-butyl-4-hydroxyphenyl) propanoate ($6.73\%$), DL-arabinose ($4.11\%$), and Eicosanebioic acid ($3.70\%$) were present in lesser amounts. Some other compounds were also found to be present in minute quantities (0.10–$2.44\%$ peak area) (Table 4). The chromatograms of the GC-MS identified compounds has been provided in Supplementary material (Supplementary File S1). ## 2.9. ADME Profiling of Compounds Identified via GC-MS Analysis In this technical era, various computational strategies for the assessment of absorption, distribution, metabolism, excretion, and toxicology (ADMET) have been developed to reduce the time, money, and manpower in the field of drug discovery. In this context, we have performed the ADME analysis via an online web server, SwissADME, to unravel the physiochemical properties and pharmacokinetic profile of compounds identified via GC-MS analysis. In the BOILED-Egg analysis, 3 compounds were in the white region, predicted to have a higher intestinal absorption, whereas 11 compounds were in the yolk region, which were predicted to have a higher potential for penetration across the blood–brain barrier. Four compounds were outside the acceptable range and five compounds did not come under the definition of a “BOILED-Egg.” In the analysis of drug-like properties, Lipinski’s rule of five, bioactivity profile, and ADMET properties of the selected compounds were determined using the AI-based software. The five criteria in the Lipinski’s rule, viz. molecular weight <500 Da, H-bond donors (HBD) <5, H-bond acceptors (HBA) < 10, and Log P (octanol–water partition coefficient) <5, were evaluated for each of the compounds. In the drug-likeness analysis, compounds 1, 2, 8, 11, 16, 18, 21, and 23 violated the one rule (MlogP < 4.15), whereas compounds 15, 17, 20, and 22 violated two rules (MlogP < 4.15 and MW < 500) of Lipinski (Table 5). ## 2.10. Toxicity Assessment of the Selected Compounds The compounds that resided in the BIOLED-Egg region were subjected to the toxicity analysis via ProTox-II, an online web server tool that predicts the toxicity class, LD50, and distinct toxicity parameters, such as hepatotoxicity, carcinogenicity, immunogenicity, mutagenicity, and cytotoxicity. Four compounds (dibutyl phthalate, phthalic acid di-isobutyl ester, p-chloromethoxybenzene, and precocene I) were predicted to be carcinogenic. Precocene I was also predicted to be immunogenic (Table 6). These compounds were, therefore, eliminated from further docking analysis. ## 2.11. Selected Compounds Actively Occupied the Active Pocket of α-Amylase and AChE In this attempt, we found that all the selected compounds actively occupied the catalytic site of both the α-amylase and AChE crystal structure, with binding energy values ranging from −3.10 to −6.23 kcal/mol (Table 7) and −3.32 to −8.76 kcal/mol (Table 8), respectively. The grid box dimensions for α-amylase and AChE were 60 × 60 × 60 points (x, y, and z), with a grid spacing of 0.563 Å and 0.525 Å, respectively. The grid center at dimensions of x, y, and z for α-amylase and AChE were 14.56, 86.21, 153.11, and 3.4, 67.1, and 67.0, respectively. The docked complexes showed that a compound, namely 7,9-Di-tert-butyl-1-oxaspiro [4,5] deca-6,9-diene-2,8-dione, was found to be the most potent inhibitor of α-amylase and AChE, with binding affinity of -6.23 and -8.76 kcal/mol, respectively, which is better than their respective standard and substrate, while other compounds also showed significant binding affinity (Table 7 and Table 8). The docked complex of α-amylase and AChE with 7,9-Di-tert-butyl-1-oxaspiro [4,5] deca-6,9-diene-2,8-dione was found to be surrounded by 9 amino acid residues (Leu165, Gln63, Thr163, Trp58, Trp59, Asp300, His299, Arg195, Tyr62) (Figure 5) and 17 amino acids residues (Ser122, Asp72, Asn85, Trp84, Ser81, Gly80, Phe330, Tyr334, Tyr442, Trp432, Ile439, Ser200, His440, Glu199, Ile444, Gly441, Tyr121), respectively (Figure 6). ## 3. Discussion Oxidative stress induced by ROS damages proteins, lipids, and DNA and is one of the major causes of several chronic diseases, such as DM [29,32]. The prevalence of DM is rising globally and this trend is predicted to continue in the coming decades [8]. Oxidative stress and DM are independent risk factors for several complications, including cardiovascular diseases, diabetic encephalopathy, and AD [2,32,33,34,35]. Antioxidants from natural sources, such as plants, and their secondary metabolites are efficient quenchers of free radicals and interrupt their production. Their consumption helps in the management of oxidative stress and in preventing the onset of several diseases such as DM and AD [2,36,37,38,39]. Numerous in vitro and in vivo studies have shown that C. nocturnum leaf extracts have antifungal, antibacterial, antidiabetic, and wound healing properties [22,24,27,28,40]. In this study, sequential extraction of C. nocturnum leaves was performed using n-Hexane, DCM, EtOAc, MeOH, and water. Phytochemical screening showed that the MeOH extract contains significant amounts of bioactive compounds, including flavonoids and polyphenols (Table 2), which are known for their free radical quenching ability, and that it has the highest TPC (Figure 2). The reductones serve as antioxidants by donating a hydrogen atom to free radicals, and their content corresponds with the reducing capacity of the extracts and their antioxidant potential [29,30,31]. The MeOH extract exhibited significant total antioxidant activity (Figure 1). These results are in concordance with those of previously studies [22,23,28,40]. A recently published study also showed that leaves of C. nocturnum are a rich source of phytochemical constituents [40]. Because phenolic compounds are believed to be responsible for the majority of antioxidant properties of plant extracts, the antioxidant potential of the MeOH extract might be attributable to polyphenolic compounds [32,41]. Compounds with the ability to reduce oxidative stress via quenching of free radicals can delay or stop the progression of several chronic diseases [1,8,42,43]. The MeOH extract of C. nocturnum leaves exhibited strong DPPH and ABTS radical quenching ability (Figure 1, Table 3), indicating its potent antioxidant activity. These results are in agreement with previously published reports [23,44,45]. Several strategies have been developed to manage DM, among which, the strategies based on the inhibition of key enzymes are the most common. The inhibition of the most important carbohydrate metabolizing enzymes (α-amylase and α-glucosidase) is the first line drug therapy for the management of blood glucose levels in DM patients [29,46,47]. Oxidative stress and DM contribute to the development of several complications, including cognitive disorders, such as AD. AD is the most common cause of dementia. Epidemiological studies suggest that DM patients are more prone to develop AD [9,48]. The most prominent therapeutic strategy for AD is the inhibition of cholinesterase, as this enzyme catalyzes the conversion of ACh into choline and acetate. Several studies have established a strong relationship between DM, particularly type 2 DM, and AD, as they share common pathophysiological features, such as oxidative stress, abnormal signaling events related to insulin, advanced glycation end products, and mitochondrial anomalies [49,50]. Although the initial management of hyperglycemia is performed through diet control and exercise, this is not sufficient, and oral drug therapy is recommended [51]. Several synthetic drugs are commercially available for the management of hyperglycemia (glinides, carbohydrate metabolizing enzyme inhibitors, sulfonylureas, and thiazolidinediones) [52] and AD (tacrine, donepezil, rivastigmine, and galantamine) [16]. Several studies have shown that these antihyperglycemic drugs reduce the risk of dementia [53,54]. Despite their excellent profile, the long-term use of these anti-diabetes and anti-Alzheimer’s medications causes several prominent side effects, including hepatotoxicity, nephrotoxicity, and hypoglycemia [55,56]. To date, there is no FDA approved drug that can manage both hyperglycemia and AD via targeting of α-amylase and AChE. In this context, our findings that the sequentially extracted C. nocturnum extracts exhibit antidiabetic and anti-Alzheimer’s activity via targeting α-amylase and AChE are significant. Among all the extracts, the MeOH extract exhibited the most potent α-amylase inhibitory action. This extract inhibited the α-amylase activity in a dose-dependent manner (Figure 3, Table 3), consistent with previous reports that α-amylase inhibitory potential was higher in more polar plant extracts [32,57,58]. Thus, the enzyme inhibitory potential of the MeOH extract could be due to the presence of polyphenols, flavonoids, and glycosides. Interestingly, the DCM extract also showed marked inhibition at a concentration of 50 µg/mL. Besides this further increasing, the concentration did not show significant inhibitory potential. It might be due to lower number of phytoconstituents in the DCM extract. Preliminary screening also revealed that the MeOH extract of leaves of C. nocturnum inhibited the AChE activity in a dose-dependent manner (Figure 3, Table 3). To find the mechanism of inhibition of α-amylase and AChE by the MeOH extract, we performed enzyme kinetics studies. The MeOH extract was found to be a noncompetitive inhibitor of α-amylase and a competitive inhibitor of AChE (Figure 4). On the contrary, the standard drugs, acarbose and tacrine, showed competitive and noncompetitive inhibition of α-amylase and AChE, respectively, which is in agreement with previous reports [32,39]. It is evident that plant extracts exhibit competitive and noncompetitive inhibition due to the presence of a variety of bioactive compounds [59]. A decrease in Vmax and no change in Km are characteristics that differentiate noncompetitive inhibition from competitive (no change in Vmax and an increase in Km) and uncompetitive (decrease in both Vmax and Km) inhibition [60]. Using GC-MS analysis, 23 compounds were identified as the bioactive substances probably responsible for the aforementioned effects of the MeOH extract (Table 4). Several studies have reported the antioxidant, antidiabetic, antifungal, and antibacterial activities of these compounds present in C. nocturnum [23,40]. However, our GC-MS analysis did not record the flavonol glycoside and steroidal saponins described in an NMR analysis of methanolic extract of leaves by Mimaki et al., [ 2001] [61]. However, these chemicals were also not documented in a previously published publication either, although our data are consistent with the same class of substances reported by Chaskar et. al. [ 2017], such as hexadecenoic acid, 1-Hexadecanol, and carboxylic acid [62]. Based on our results, we surmise that the bioactive compounds in the MeOH extract of C. nocturnum leaves, either individually or in combination, substantially ameliorate the oxidative damage and inhibit the activities of α-amylase and AChE. However, the most persuasive step in the development of drugs is the prediction of the pharmacological properties of a chemical entity using several AI-based software. Among the various AI-based strategies, ADMET is currently being used to avoid wastage of time, resources, and manpower [61,62]. For this reason, we performed the ADMET analysis to investigate the drug-likeness properties of the bioactive components of the MeOH extract predicted using GC-MS. The SWISS ADME generates results in the form of a BOILED-Egg graph. The white region denotes high gastrointestinal tract absorption of the compounds and the yellow region (yolk) indicates high BBB penetration. The ADMET analysis revealed that all the compounds had acceptable drug-likeness properties and conformed to Lipinski’s rule of five [29]. However, some compounds violated either one or two of these rules, but these violations do not warrant exclusion of these compounds as potential candidates. Only 13 compounds were localized in the BOILED-Egg graph, and these were subjected to toxicity analysis (Table 5). All the compounds were in the range of classified LD50 values. Four compounds (dibutyl phthalate, phthalic acid di-isobutyl ester, p-chloromethoxybenzene, and precocene I) were active against the carcinogenicity parameter. Precocene I was also active against the immunogenicity parameter. These compounds were eliminated at this level from further docking analysis. Molecular docking analysis was performed to determine the interactions of the selected constituents of the MeOH extract that interact with the active site of α-amylase and AChE, and consequently inhibit their activity. Such docking analyses to search for molecular targets of constituents in plant extracts have been reported previously [32]. Molecular docking is a crucial tool for examining the interaction of ligands with a target protein and helps in comprehending the mechanisms underlying their binding and inhibitory activities. Redocking co-crystallized acarbose and tacrine into their respective binding sites in α-amylase and AChE allowed us to validate the docking approach (Figure 5 and Figure 6). We found that all the redocked structures interacted with the same amino acids as in the respective crystal structure. The molecular docking study was carried out using Pyrex and further validated using Autodock 4.2. Furthermore, our results illustrated that the selected ten compounds were strongly occupied the active pocket of the α-amylase crystal structure with binding energy (ΔG) values ranging from −3.10 to −6.23 kcal/mol, which is quite a bit better than the standard (ΔG -2.71 kcal/mol) as well as their substrate (ΔG −2.79 kcal/mol). Among these compounds, 7,9-di-tert-butyl-1-oxaspiro [4,5] deca-6,9-diene-2,8-dione was most potent inhibitor of α-amylase, as evidenced by its lowest binding energy. Its binding to the active pocket was stabilized by interaction with nine amino acid residues (Leu165, Gln63, Thr163, Trp58, Trp59, Asp300, His299, Arg195, Tyr62) (Figure 5). Interestingly, the same compound also showed the lowest binding affinity for AChE, and its binding was stabilized through interactions with 17 amino acid residues (Ser122, Asp72, Asn85, Trp84, Ser81, Gly80, Phe330, Tyr334, Tyr442, Trp432, Ile439, Ser200, His440, Glu199, Ile444, Gly441, Tyr121) (Figure 6). The other selected compounds also interacted efficiently with the active pocket of AChE, showing varied ΔG values (Table 8). Although all the selected compounds interacted with the catalytic site of the both the target enzymes, resulting in inhibition of their activity, we cannot comment if all or few of these compounds are responsible for the actual inhibitory activity of the extract. Nonetheless, the results of our in vitro and in silico studies convincingly highlight the antidiabetic and anti-Alzheimer potential of the MeOH extract of C. nocturnum leaves. ## 4.1. Chemicals n-Hexane, DCM, EtOAc, MeOH, acetone, and dinitro salicylic acid (DNS) were obtained from Merck. DPPH, 2,4,6-tripyridyl-s-triazine (TPTZ), ascorbic acid, ferric chloride (FeCl3), and ferrous sulfate (FeSO4) were purchased from the Hi-Media Laboratories. Pancreatic α-amylase was obtained from Sisco Research. Lab Pvt. Ltd. DTNB, acetylcholine iodide (AChI), 9-amino-1,2,3,4-tetrahydroacridine hydrochloride (tacrine hydrochloride), ABTS, and AChE were purchased from Sigma-Aldrich (USA). All the chemicals were of analytical grade. ## 4.2. Collection, Identification, and Preparation of Cestrum nocturnum Extract The C. nocturnum leaves were collected (voucher no. IU/PHAR/HRB/$\frac{22}{21}$) and washed to remove filth and dust particles and shed dried for seven days. After drying, leaves were ground to powder form. The dried powder (25 g) was sequentially extracted with the appropriate amount of n-Hexane, dichloromethane (DCM), ethyl acetate (EtOAc), methanol (MeOH), and water using the Soxhlet apparatus. The filtered crude extract was scratched out and kept at −20 °C for further analytical use. The following formula was used to determine the percentage yield of various extracts. % yield =Weight of crude extractWeight of raw material×100 ## 4.3. Qualitative Screening of Phytochemicals Each extract of leaves of C. nocturnum was qualitatively screened for the presence of phytoconstituents, such as phenols, glycosides, and steroids, following the methods described previously [63]. ## 4.4. DPPH Radical Scavenging Activity The method described by Brand-Williams et al. [ 64] was used to assess the DPPH radical quenching ability of the extracts. The reference standard ascorbic acid was used for the comparative study. The percent inhibition of the DPPH was calculated using the equation below:%DPPH=ΔAbsorbance of control−ΔAbsorbance of sampleΔAbsorbance of control×100 ## 4.5. ABTS Radical Scavenging Activity The ABTS stock solution (7 mM) was prepared by mixing it with 2.45 mM potassium persulfate. Before the experiment, the solution was suitably diluted to yield an absorbance of 0.70 at 734 nm. Different concentrations of the extracts (in a 100 μL volume) were added to 900 μL of ABTS solution and the mixtures were incubated for 30 min at 37 °C. The absorbance was taken at 734 nm using an Eppendorf Bio-spectrophotometer. The reference standard used was ascorbic acid [65]. The equation used for calculating the % inhibition was the same as that used for DPPH. ## 4.6. Ferric Reducing Antioxidant Potential The ferric reducing potential was determined according to the standard protocol [66] with a slight modification [32]. The absorbance was taken at 593 nm. The results were calculated using the standard curve of FeSO4 and indicated as μmol Fe (II)/g dry weight of the C. nocturnum leaves powder. ## 4.7. Total Phenolic Content The total phenolic content was determined by using the Follin–Ciocalteu standard protocol [32]. The results were calculated using standard gallic acid curve. The results are manifested as μg GA equivalent/mg extract. ## 4.8. α-Amylase Inhibition Assay The α-amylase inhibitory potential of the different C. nocturnum leaf extracts was determined according to the standard protocol [29,32]. The enzyme (5 unit/mL) was freshly prepared in 20 mM of ice-cold PBS (pH 6.7) containing 6.7 mM NaCl. The enzyme (250 μL) was mixed with different concentrations of the inhibitors (acarbose or extract), except in the blank, and incubated for 20 min at 37 °C. Thereafter, starch solution ($0.5\%$ w/v) was added and the mixture was incubated for 15 min at 37 °C. Following the addition of the DNS reagent, the mixture was vortexed and incubated at 100 °C for 10 min in a water bath. At the end of incubation, the absorbance at 540 nm was measured using an Eppendorf Bio-spectrophotometer. The % inhibition rate was evaluated using the following equation:% inhibition = 100 − % reaction where % reaction = (mean product in sample/mean product in control) × 100 ## 4.9. Determination of Anti-Acetylcholinesterase Activity The acetylcholinesterase test was prepared according to Ellman et al. [ 1961] with a slight modification [67]. For use as a blank control, 33 μL of 10 mM DTNB, 100 μL of 1 mM AChI, 767 μL of 50 mM Tris HCl buffer (pH 8.0), and 100 μL of extract (different concentrations) were mixed in a 2 mL cuvette. For the test reaction, 300 μL of the buffer was replaced with an equal volume of AChE solution (0.28 U/mL). Tacrine was used as a reference standard. The reaction was monitored for 20 min by measuring the OD at 405 nm every minute. The values are presented as the mean of three replicates. The % inhibition of enzyme activity was calculated using the following equation:% inhibition=ΔAbsorbance of control−ΔAbsorbance of sampleΔAbsorbance of control×100 ## 4.10. Kinetics Studies to Assess the Mode of Inhibition of α-Amylase Activity by the MeOH Extract of C. nocturnum Leaves Michaelis–Menten kinetics (the Lineweaver–Burk plot) [30,32] were determined to decipher the mode of inhibition of α-amylase activity by the MeOH extract of C. nocturnum leaves. α-Amylase was preincubated with the inhibitor (extract/acarbose) for 20 min. One hundred microliters of starch (0.625–5 mg/mL) was added to each tube, including the blank, and incubated at 37 °C for 15 min. After the addition of DNS solution, the absorbance was recorded at 540 nm. The Lineweaver–Burk plot was made to determine the effect of the extract or acarbose on Vmax and Km. ## 4.11. Kinetics Studies to Assess the Mode of Inhibition of AChE Activity by the MeOH Extract of C. nocturnum Leaves The kinetic study was carried out using the varied concentration of substrate, AchI (i.e., 0.5, 1.0, and 2.0 mM), and inhibitor C. nocturnum leaves extract (0.0, 50, and 100 µg/mL of reaction). The hydrolysis of AChI by AChE, either in the absence or presence of an inhibitor, was spectrophotometrically monitored for 20 min at 405 nm. The absorbance was taken at 1 min intervals. The mode of inhibition was determined according to the Michaelis–Menten kinetics [39]. ## 4.12. GC-MS Analysis of the MeOH Extract The phytoconstituents in the MeOH extract, which exhibited the maximum inhibitory potential against α-amylase and AChE, were identified using GC-MS. The GC-MS analysis was performed at the Central Instrumentation Laboratory Facility (CIL), Central University of Punjab, Bhatinda, India. The sample was injected into a Restek column (30 m × 0.25 mm; film thickness, 0.25 μm) on a GC-MS system (Shimadzu QP 2010 Ultra GC-MS). The constant column flow of the carrier gas (helium) was 1 mL/min. The mass spectra peaks were compared against the reference National Institute of Standards and Technology (NIST) libraries to identify the compounds. ## 4.13. Retrieval and Preparation of Ligands Structure Numerous organic compounds’ structures and their functional details are available in the PubChem database (http://pubchem.ncbi.nlm.nih.gov) that accessed on 10 November 2022. A unique identification number (CID) has been designated for each compound in the database. The 3D-structures of GC-MS-identified compounds were retrieved in 3D SDF file format. Using BIOVIA Discovery Studio Visualizer, the SDF file of ligands was converted into PDB file format. The CHARMM force field was applied in order to singe step minimization using the steepest descent method for 500 steps and an RMS gradient of 0.01. ## 4.14. Preparation of Target Protein The 3D-structure of both enzymes (target proteins) was downloaded from the PDB database (https://www.rcsb.org/search) that accessed on 10 November 2022 [68] by taking the proteins IDs, α-amylase (5U3A), AChE (1ACJ), and saved. The structure was investigated and visualized in BIOVIA Discovery Studio Visualizer 2020 (BIOVIA, Dassault Systems; https://discover.3ds.com/discovery-studio-visualizer-download, accessed on 12 October 2022. Moreover, an online tool, Play-Molecule (https://www.playmolecule.com) accessed on 8 November 2022, provided the DEEPSITE to predict the active site of the AchE. ## 4.15. Target Protein and Ligands Preparation The target protein was prepared by deleting heteroatoms and adding polar hydrogen, as well as kollman charges, by using Autodock 4.2 [69]. Further 3D structure of the proteins was converted into PDBQT file format. The ligands were prepared according to the well-defined standard protocol [70]. ## 4.16. ADME and Drug-Likeness Studies of Selected Ligands The selected ligands were subjected to pharmacokinetic profiling by using a web-based tool, as defined in earlier studies [71]. Furthermore, the ligands’ drug-likeness properties were also depicted by the Swiss ADME tool (http://www.swissadme.ch) that has been accessed on 20 November 2022. ## 4.17. Predicted Toxicity of the Selected Compounds Toxicity prediction was performed by the ProTox-II (https://tox-new.charite.de/protox_II/index.php?site=compound_input) on 25 November 2022, an online web-based server for the prediction of toxicities of small molecules. It provides the numerous details of the compounds about the toxicity such as LD50, Carcinogenicity, Immunotoxicity, Mutagenicity Cytotoxicity, as well as, most importantly, Hepatotoxicity [72]. ## 4.18. Molecular Interaction Analysis To determine the antidiabetic and anti-Alzheimer’s potential of the selected compounds, we performed in silico molecular docking of these compounds at the catalytic sites of α-amylase and AChE, respectively, using the standard protocol [73]. For validating the results of docking, the structures of acarbose and tacrine were extracted from the structures of their respective complexes with α-amylase and AChE and redocked within the active pocket of the respective targets using Autodock. After the completion of docking, the structures of the complexes were visualized using the BIOVIA Discovery Studio Visualizer and ranked on the basis of binding energies. ## 5. Conclusions For the first time, we demonstrate the potent antidiabetic and anti-Alzheimer’s activities of sequentially extracted C. nocturnum methanolic leaf extracts via the inhibition of α-amylase and AChE, respectively. The results of our in vitro analyses show that the methanolic extract of C. nocturnum leaves has potent antioxidant, antidiabetic, and anti-Alzheimer’s activities. These results were further corroborated by the antidiabetic and anti-Alzheimer’s properties of the bioactive compounds identified using GC-MS. 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--- title: Novel Functional Grape Juices Fortified with Free or Immobilized Lacticaseibacillus rhamnosus OLXAL-1 authors: - Anastasios Nikolaou - Gregoria Mitropoulou - Grigorios Nelios - Yiannis Kourkoutas journal: Microorganisms year: 2023 pmcid: PMC10051719 doi: 10.3390/microorganisms11030646 license: CC BY 4.0 --- # Novel Functional Grape Juices Fortified with Free or Immobilized Lacticaseibacillus rhamnosus OLXAL-1 ## Abstract During the last decade, a rising interest in novel functional products containing probiotic microorganisms has been witnessed. As food processing and storage usually lead to a reduction of cell viability, freeze-dried cultures and immobilization are usually recommended in order to maintain adequate loads and deliver health benefits. In this study, freeze-dried (free and immobilized on apple pieces) Lacticaseibacillus rhamnosus OLXAL-1 cells were used to fortify grape juice. Juice storage at ambient temperature resulted in significantly higher (>7 log cfu/g) levels of immobilized L. rhamnosus cells compared to free cells after 4 days. On the other hand, refrigerated storage resulted in cell loads > 7 log cfu/g for both free and immobilized cells for up to 10 days, achieving populations > 109 cfu per share, with no spoilage noticed. The possible resistance of the novel fortified juice products to microbial spoilage (after deliberate spiking with Saccharomyces cerevisiae or Aspergillus niger) was also investigated. Significant growth limitation of both food-spoilage microorganisms was observed (both at 20 and 4 °C) when immobilized cells were contained compared to the unfortified juice. Keynote volatile compounds derived from the juice and the immobilization carrier were detected in all products by HS-SPME GC/MS analysis. PCA revealed that both the nature of the freeze-dried cells (free or immobilized), as well as storage temperature affected significantly the content of minor volatiles detected and resulted in significant differences in the total volatile concentration. Juices with freeze-dried immobilized cells were distinguished by the tasters and perceived as highly novel. Notably, all fortified juice products were accepted during the preliminary sensory evaluation. ## 1. Introduction Development of functional foods has been a matter of intense scientific and commercial interest for several decades now [1,2]. The term “functional foods” includes a wide variety of products consisting of various components (e.g., nutraceuticals, prebiotics, vitamins, bioactive compounds, probiotics, etc.) [ 3] that may potentially confer positive effects on the consumers’ body functions, reduce the risk of a disease, or promote well-being in general [4]. A vast part of the functional foods’ market consists of products fermented or enriched with probiotic microorganisms, mainly but not exclusively, of the Lactobacillus and Bifidobacteria species [5,6]. Nevertheless, according to FAO/WHO, “probiotics are microorganisms (bacteria or yeasts) which, when administered in adequate concentrations, provide health benefits to the host” [7]. Recently, a novel wild-type Lacticaseibacillus rhamnosus OLXAL-1, isolated from olives [8], demonstrated significant antidiabetic capability to alleviate Type-1 diabetes symptoms, an illness that has dramatically increased in developed countries over the past decades. While the majority of probiotic products traditionally relies on dairy [9], due to modern lifestyle and health reasons (e.g., lactose intolerance, milk allergies, high cholesterol, veganism, etc.), there is an increasing consumer interest in alternatives like fruit juices [10,11,12,13]. Fruit juices are very popular, eagerly consumed and contain significant amounts of dietary fibers, antioxidants, polyphenols, minerals, enzymes and vitamins, while the addition of probiotics may further enhance their benefits and value [14,15]. Thus, an upsurge in the development of non-dairy functional beverages, like fruit juices, has been noticed [9,16,17,18,19,20,21,22,23,24]. In fact, grapes and grape juice (in particular), are part of a healthy diet in many countries, and could potentially be exploited for functional food development [25,26,27]. Other than being highly nutrient, the fruit juices’ matrix may also provide a suitable environment for probiotics growth and survival [16]. This is a very important matter, as probiotic microorganisms must survive the entire food processing chain (manufacture, storage, serving) and retain adequate numbers (at least 107 cfu/mL at the time of consumption), in order to deliver their functional features [1]. For that reason, cell immobilization technology is suggested in the production of novel functional foods, as it is known to enhance probiotic survival and thus result in longer preservation times, protection against microbial contamination, etc. [ 28]. The selection of a suitable immobilization carrier (e.g., fruit pieces) is however a matter of high importance, too, as it affects the cell adhesion and the colonization properties of functional cells [29,30] and could be utilized for the production of symbiotic (prebiotic + probiotic) functional components [31]. Likewise, freeze-drying technology is recommended, as it results in the maintenance of cell viability and operational stability, extends product shelf life, creates easy-to-handle and transport conditions, diminishes storage costs, etc. [ 32]. In general, fruit juices, due to their low pH values, do not favor the growth of spoilage and pathogenic microorganisms, making them rather safe and attractive to consumers [33]. Nevertheless, yeasts and molds can be considered the major reasons for fruit juice spoilage. They can grow in harsh environments with low pH, low water activity, and high sugar content. Saccharomyces cerevisiae and Aspergillus niger represent the most common spoilage microorganisms in fruit juices [34]. To overcome this problem, apart from pasteurization, the use of chemical additives (such as nitrite, sodium chloride, and organic acids) is a common practice in the food industry [35]. Due to consumers’ awareness, though, today there is mounting pressure on food manufacturers to either completely avoid the use of chemical preservatives or to adopt “natural” alternatives [36]. Functional cultures and microbial derivatives seem to play a significant role in the prevention of food-spoilage. Biopreservation uses the antimicrobial potential of some microorganisms to prevent spoilage and pathogenic microbe growth in foods [37]. The majority of biopreservation research has been focused on lactic acid bacteria’s antagonistic activities against spoilage and pathogenic microorganisms [38]. The antagonistic activities of lactic acid bacteria against other microbes in foods have been related to several mechanisms, such as the production of organic acids, H2O2, antibacterial bacteriocins, antimicrobial metabolites, such as diacetyl and reuterin and the reduction of pH [39]. In the present study, a novel juice product fortified with Lacticaseibacillus rhamnosus OLXAL-1 cells (previously evaluated for their antidiabetic properties) was developed. Data indicating the effective survival of L. rhamnosus through storage (at 20 °C and 4 °C) and possible resistance against food-spoilage microorganisms (Saccharomyces cerevisiae or Aspergillus niger), are presented. ## 2.1. Microbial Cultures Lacticaseibacillus rhamnosus OLXAL-1 [8], Saccharomyces cerevisiae Uvaferm NEM (Lallemand, Montreal, QC, Canada), and Aspergillus niger 19111 were used in this study. L. rhamnosus OLXAL-1 was grown on a synthetic medium ($2.0\%$ w/v glucose, $0.2\%$ w/v KH2PO4, $0.03\%$ w/v MgSO4, $0.6\%$ CH3COONa, $2.5\%$ w/v yeast extract, $0.1\%$ v/v Tween 80 and $0.005\%$ w/v MnSO4) at 37 °C for 24 h. Saccharomyces cerevisiae Uvaferm NEM was grown on Yeast extract Peptone Dextrose (YPD) broth (yeast extract 10 g/L, peptone 20 g/L, dextrose 20 g/L) at 28 °C for 24 h. Aspergillus niger 19111 was grown on Malt Agar (Condalab) at 37 °C for 7 days. Prior to use, all culture media were sterilized at 121 °C for 20 min. ## 2.2. Cell Immobilization and Production of Freeze-Dried Cultures Grown L. rhamnosus OLXAL-1 cells were harvested by centrifugation (8000× g for 15 min at 4 °C), rinsed with sterile ¼ Ringer’s solution (VWR International GmbH, Radnor, PA, USA) and subsequently centrifuged again (wet free cells). For the immobilization process, rinsed and harvested cells were resuspended in sterile ¼ Ringer’s solution up to the initial culture volume (immobilization solution). Apple pieces (0.4 ± 0.1 cm side length) were then submerged in the immobilization solution (in a ratio of $60\%$ w/v) and left undisturbed for 4 h at 20 °C. After the immobilization process was completed, apple pieces were strained and rinsed with sterile ¼ Ringer’s solution, in order to remove any free non-immobilized cells (wet immobilized cells). Freeze-dried immobilized cells were prepared on a BenchTop Pro (Virtis, SP Scientific, Warminster, PA, USA), as recently described [40]. For comparison reasons, free L. rhamnosus OLXAL-1 cells were also subjected to freeze-drying. Wet and freeze-dried immobilized or free cells were finally stored at room (20 °C) or refrigeration (4 °C) temperatures and their counts were monitored at various intervals. ## 2.3. Novel Juice Products Concentrated grape juice of the Muscat Hamburg variety (Tyrnavos Cooperative Winery and Distillery, Tyrnavos, Greece) was diluted with sterilized deionized water to a final ~140 g/L. Freeze-dried immobilized cells on apple pieces were directly incorporated in grape juice (reaching a proportion of $20\%$ w/v in the reconstituted juice product). For comparison reasons, juice products fortified with free freeze-dried L. rhamnosus OLXAL-1 cells (~$0.033\%$ w/v) were also prepared. Juice products containing only freeze-dried apple pieces or no cultures at all were used as controls. All products were stored at room (20 °C) or refrigeration (4 °C) temperatures for 14 and 30 days, respectively, in order to determine the product’s shelf life. ## 2.4. Susceptibility to Spoilage Novel juice products were deliberately inoculated either with S. cerevisiae (inoculum of 104 cfu/mL) or Aspergillus niger (inoculum of 104 spores/mL) and their levels were monitored during storage at room (20 °C) or refrigeration temperatures (4 °C). Juice products without L. rhamnosus OLXAL-1 cells (free or immobilized) were used as control samples. ## 2.5.1. L. rhamnosus OLXAL-1 Cell Counts Levels of free and immobilized cells were determined as recently described [41]. In brief, 5 g of immobilized cultures were blended with 45 mL sterile ¼ Ringer’s solution. Accordingly, 1 mL of free cell culture was transferred to 9 mL of sterile ¼ Ringer’s solution. Decimal serial dilutions in ¼ Ringer’s solution were performed, followed by plate counting on MRS agar plates after incubation at 37 °C for 72 h. Cell loads were expressed as log cfu/g immobilization carrier or log cfu/mL culture. The survival rates of freeze-dried L. rhamnosus OLXAL-1 cells during storage were calculated as recently demonstrated [8]. In order to determine L. rhamnosus OLXAL-1 counts, 50 g of the novel juice products were homogenized with an iMix bag mixer (Interlab, Mourjou, France), serially diluted and subsequently plated on MRS Agar (Condalab, Madrid, Spain). ## 2.5.2. Populations of Food-Spoilage Microorganisms In juice products deliberately spiked with food-spoilage yeast/fungi, populations were determined as follows:S. cerevisiae counts were determined on YPD Agar (yeast extract 10 g/L, peptone 20 g/L, dextrose 20 g/L, agar 20 g/L) after incubation at 28 °C for 72 h.A. niger spores were determined after enumeration on Neubauer plate (spores/g). A. niger counts (log cfu/mL) were determined on Malt Agar after incubation for 72 h at 37 °C [34]. ## 2.5.3. Microbial Contaminants The presence of other foodborne microorganisms during storage of freeze-dried cells or novel juice products was monitored as follows:Total mesophilic counts on Plate Count Agar (PCA) (Condalab, Madrid, Spain) after incubation at 30 °C for 72 h.Yeasts/molds counts on Malt Agar (Condalab) after incubation 30 °C for 72 h.Clostridia on TSC Agar (Condalab) after anaerobic incubation at 37 °C for 24 h.Enterobacteriacae on Violet Red Bile Glucose Agar (V.R.B.G.A.) (Condalab) after incubation at 37 °C for 24 h.Coliforms on Violet Red Bile Agar (V.R.B.A.) (Condalab) after incubation at 30 °C for 24 h.Staphylococci on Baird-Parker Agar (BP) (Condalab) after incubation at 37 °C for 24 h.Salmonella spp. In X.L.D. agar (LabM, UK) at 37 °C.Escherichia coli on HarlequinTM Chromogenic Media (Condalab) after incubation at 37 °C for 24 h.Pseudomonas aeruginosa on Pseudomonas agar base—Pseudomonas CN Agar (VWR International GmbH, USA) after incubation at 37 °C for 40–48 h.Listeria monocytogenes on L-Palcam agar (LabM) fortified with X144 supplement (VWR) after incubation at 37 °C for 48 h. ## 2.6. Physicochemical Analysis pH was determined on a pH-300i pH meter (WTW GmbH, Weilheim, Germany). Water activity (aw) was determined using the HygroLab 3 (Rotronic AG, Basserdorf, Switzerland), according to the manufacturer’s guidelines. ## 2.7. Minor Volatiles Samples of novel juice products (20 g) were analyzed for minor volatiles content using the HS-SPME GC/MS technique [6890N GC, 5973NetworkedMS MSD (Agilent Technologies, Santa Clara, CA, USA)], as previously described [42] (Table S1 (Supplementary Materials)). ## 2.8. Preliminary Sensory Evaluation Novel juice products were assessed for their quality characteristics (aroma, taste, and overall quality) on a 0–5 scale (0: unacceptable, 5: wonderful), as previously reported [43]. All samples were coded, offered in a dark glass under low light and served at 12–15 °C. Between samples, tasters were given water and crackers. ## 2.9. Statistical Analysis All data were analyzed statistically using Analysis of Variance (ANOVA) through Statistica (v.12.0, StatSoft, Tulsa, OK, USA). Significant differences ($p \leq 0.05$) were determined with the Bonferroni correction. Component Analysis (PCA) was performed using XLSTAT 2015.1 (Addinsoft, Paris, France). ## 3.1. Storage of Freeze-Dried L. rhamnosus OLXAL-1 Cultures Initially, free and immobilized L. rhamnosus OLXAL-1 cultures (previously evaluated for their antidiabetic properties [8]) were prepared (in wet and freeze-dried form) and their survival rate was monitored. High levels of immobilized cells, ≥ 9 log cfu/g, were recorded in both wet and freeze-dried L. rhamnosus OLXAL-1 cultures on apple pieces. In general, during storage for 30 days (Table 1), both free and immobilized L. rhamnosus OLXAL-1 cell levels were significantly ($p \leq 0.05$) affected by the state of the culture (wet or freeze-dried), the storage temperature (4 °C or 20 °C) and the storage duration. During storage at 20 °C for 30 days, freeze-dried immobilized L. rhamnosus OLXAL-1 cells exhibited significantly ($p \leq 0.05$) higher survival rates ($78.8\%$) than the corresponding freeze-dried free cells ($70.5\%$). In contrast, wet free L. rhamnosus OLXAL-1 cells showed $0\%$ survival rate during storage at 20 °C for 30 days, while in the case of the wet immobilized L. rhamnosus OLXAL-1 culture, the presence of yeasts/molds was detected (data not shown). During storage at 4 °C for 30 days, the highest ($p \leq 0.05$) survival rate for immobilized cells on apple pieces was recorded in the case of freeze-dried L. rhamnosus OLXAL-1 culture ($88.5\%$), while the survival rate of wet immobilized cultures was diminished down to $0\%$ by day 30 and yeasts/molds were also detected. In the case of freeze-dried free L. rhamnosus OLXAL-1 cultures, significantly higher levels were detected (survival rates > $98\%$ recorded) compared to 20 °C, as expected. Similar survival rates of immobilized lactic acid bacteria (LAB) compared to free cultures have also been recently documented during storage at room or refrigeration temperatures [41]. In the same study, a positive effect of immobilization was also observed on the maintenance of cell viability during storage (for 180 days), which resulted in higher survival rates of the freeze-dried immobilized cultures on natural carriers (zea flakes and pistachios) in comparison to the free cultures. Regarding storage, low temperatures are known to prolong cell survival and are thus strongly preferred [44,45], but the nature of the carrier should not be neglected, as it may affect the cell viability throughout the final products’ shelf life and survival [46]. Nevertheless, the possibility of the viability of probiotic cultures (either in free form or immobilized on food ingredients) during long-term storage relying on strain-specific characteristics cannot be excluded [41,47]. In addition to the determination of viable L. rhamnosus OLXAL-1 cell levels during storage, water activity (aw) (Table 1) and moisture levels (Table 1) were also monitored. In general, water activity and moisture levels are key factors that affect both the shelf life of food products and the viability of probiotic cells during storage [48,49]. In particular, it has been reported that for long-term storage of dried probiotic cells, the values of water activity and moisture content are recommended to be < 0.25 and $10\%$, respectively [48]. For both free and immobilized L. rhamnosus OLXAL-1 cells, the lowest levels of moisture and aw were recorded when freeze-drying was applied. This result is in accordance with the higher survival rates recorded in both freeze-dried free and immobilized L. rhamnosus OLXAL-1 cells on apple pieces compared to wet cells. ## 3.2. Viability of L. rhamnosus OLXAL-1 Cells in Novel Functional Grape Juice Products Freeze-dried immobilized cells on apple pieces were directly added in grape juice, reaching a final proportion of $20\%$ w/w in the reconstituted novel product. Likewise, freeze-dried free cells were directly added in grape juice and served as controls. Samples of both products (containing free or immobilized L. rhamnosus OLXAL-1 cells) were then stored at room (20 °C) or refrigeration temperature (4 °C). The microbial stability alongside the effect of storage temperature on any product represents an important aspect of the food industry [16,50], and thus L. rhamnosus OLXAL-1 counts were monitored at frequent intervals (Figure 1). Initial levels of both free and immobilized L. rhamnosus OLXAL-1 cells in both grape juice products were ~7.5 log cfu/g. At ambient temperature, counts of free L. rhamnosus cells decreased significantly ($p \leq 0.05$), while levels of immobilized L. rhamnosus cells on apple pieces remained significantly ($p \leq 0.05$) higher (> 7 log cfu/g) after 4 days of storage. This could be attributed directly to cell immobilization which is well known to protect microbial cells against stresses induced by food production processes [16], resulting in maintenance [51,52,53] or in some cases even enhancement of their counts [32]. In contrast, refrigerated storage resulted in cell loads > 7 log cfu/g for both products (with free and immobilized cells) for up to 14 days, in accordance with previous studies on non-fermented probiotic grape juices [22,24]. In this way, populations > 109 cfu were achieved in a daily product serving (200 mL of juice) [54], thus complying with the minimum recommended concentration needed, in order to confer beneficial health effects on the consumer [9,55]. However, after 14 days of storage, yeasts/molds populations were detected (at concentrations < 3 log cfu/g) and no other data were collected. This is not abnormal, as fruit juices are known to be susceptible to yeasts/molds contamination, despite their acidic environment [56]. Other than that, no changes were recorded on the pH values of our samples (4.3 ± 0.1) throughout storage (in room or refrigeration temperatures), thus indicating a high buffering effect of the novel juice products [57]. Notably, at all other time points (up to 10 days), no spoilage or pathogenic microorganisms were detected. In general, the conditions of the raw concentrated grape juice (high osmotic pressure, reduced water activity, etc.) do not favor the survival of pathogens. In some cases, adaptation may occur and for that reason a full screening is officially recommended [56]. However, such a result was not observed in our study, thus implying an extended shelf life for the novel juices (typically 1–5 days) [58], a feature that could surely be exploited by the food industry. ## 3.3. Resistance of Fortified Juices to Microbial Contamination Possible resistance to microbial spoilage of grape juice containing freeze-dried free or immobilized Lacticaseibacillus rhamnosus OLXAL-1 cells on apple pieces after deliberate spiking with Saccharomyces cerevisiae or Aspergillus niger was investigated (Figure 2). Deliberate contamination of juices fortified with freeze-dried immobilized cells with S. cerevisiae or A. niger cells resulted in significant growth limitation both at room and refrigeration temperatures compared to the unfortified products, thus exhibiting an antagonistic effect against the spoilage microbes [59,60]. Significant differences on microbial growth, especially in the case of S. cerevisiae at 20 °C, were observed between juices with freeze-dried immobilized cells and juices with free cells. In any case, the positive effect of probiotic cultures, as well as the enhanced resistance of immobilized cells against spoilage have previously been reported [61]. These results were also in accordance with a previously published study [8], where L. rhamnosus OLXAL-1 cell free supernatant (CFS) exhibited strong inhibitory activity against S. cerevisiae and A. niger. Notably, no other spoilage or pathogenic microorganisms were detected and no pH changes were recorded, as mentioned above. Despite previous efforts investigating the use of probiotics against food-spoilage microorganisms [59,60], to the best of our knowledge, none have implicated the use of immobilized cultures against deliberate spiking of juice products. ## 3.4. Minor Volatiles Determination and Chemometrics Novel juice products were subjected to HS-SPME GC/MS analysis, in order to determine minor volatiles responsible for aroma (Table S1). Keynote compounds, normally present in grape juice, like ethyl acetate (known for contributing to aromatic complexity), 2-phenylethyl acetate (known for its rose aroma), furfural (known for adding notes of freshly baked bread), 2-phenylethanol (known for rose scents), as well as 2- and 3-methyl-1-butanol (known for adding whiskey malt notes and a burnt aroma) were detected in all juice products [62,63,64,65,66,67,68]. Other compounds like hexanal (grassy, green) and (E)-2-hexenal (green) are usually linked to the apples (immobilization carrier) and were identified only in the products fortified with immobilized cells [69]. However, their presence could also be a result of microbial metabolism and their inhibitory effect against Saccharomyces and Aspergillus species has been previously well documented [70,71,72,73,74]. Linalool and α-terpineol (known to add lime tree notes and lilac aroma, respectively), usually found in grape berries [68], were also identified in all juice products, without significant differences in their concentration, in most cases. In general, the existence of terpenes in the juice may be associated with an enhancement of the product’s shelf life, as their antimicrobial [75,76] and/or antioxidant role [77] has been well documented, or even be associated with significant health benefits for the consumer [78]. Principal Component Analysis (PCA) applied to HS-SPME results revealed that the nature of the freeze-dried cells (free or immobilized) used, as well as the storage conditions (room or refrigeration temperature) significantly affected ($p \leq 0.05$) the aromatic characteristics of the novel juice products (Figure 3). Specifically, juice products fortified with freeze-dried free L. rhamnosus OLXAL-1 cells were gathered in the lower left part of the diagram, while juice products fortified with freeze-dried immobilized cells were concentrated in the upper and right regions, respectively. In addition, the juice products fortified with freeze-dried immobilized L. rhamnosus OLXAL-1 cells formed two distinct subgroups in the diagram, depending on the storage temperature applied (room temperature or refrigeration temperature). In particular, storage of samples fortified with freeze-dried immobilized cells at 4 °C caused a concentration increase in most volatiles [79] and resulted in the highest ($p \leq 0.05$) total volatiles content (Table S1) for each timepoint. ## 3.5. Preliminary Sensory Evaluation Despite the importance of factors like the physicochemical/microbial stability and the product’s nutritional value, the sensory characteristics play an important role in the consumers’ acceptability [80]. Thus, all new juice products were evaluated regarding their aroma (fruity, floral, wine-like, caramel, other) and taste (sweet, sour, bitter, salty) by a mixed panel of 20 untrained tasters. According to the results (Table 2), all products were characterized by a predominant wine-like/fruity (grape) aroma, as a result of the esters, alcohols and terpenes found in the juice (Table S1). Distinct apple notes were distinct in the case of products containing immobilized cells, deriving from characteristic compounds found in the immobilization carrier (apple pieces). The taste was strongly sweet in all cases, as no juice fermentation occurred, with a pleasant aftertaste and a refreshing feeling. Both aroma and taste were described as “fully natural” by the tasters in all samples and no off notes were detected. At the same time, feedback on the products’ novelty was gathered. Notably, products with freeze-dried immobilized L. rhamnosus OLXAL-1 cells on apple pieces emerged in the testers’ preference, most likely due to the originality of the product. After all, the appearance of a product (color, shape, size, etc.) is known to constitute the basic characteristic responsible for the product’s identification and selection, and strongly affects concepts like craveability and appetite [81]. In our case, juice products containing immobilized cells were significantly preferred ($p \leq 0.05$) against the juice products with free cells and gathered significantly higher scores regarding the overall evaluation. Notably, the serving of freeze-dried apple pieces (containing immobilized cells) and grape juice in different containers, with the testers’ direct involvement in the process of reconstituting the final juice product, was characterized as highly interesting compared to the directly served juice product with freeze-dried free cells. As a matter of fact, attributes like the style of presentation are sought to be exploited, in terms of sensory marketing, as they can influence the consumers’ perception, judgment and behavior, affect their satisfaction and result in indirect product promotion [1,82]. ## 4. Conclusions A novel grape juice product fortified with freeze-dried free or immobilized L. rhamnosus OLXAL-1 cells (previously evaluated for their antidiabetic properties) was developed. The use of immobilized cells on apple pieces resulted in significantly higher counts compared to the free cells at 20 °C, while refrigerated storage resulted in cell loads > 7 log cfu/g for both products for up to 10 days, thus achieving populations > 109 cfu per share. L. rhamnosus OLXAL-1 cells resulted in significant growth limitation of S. cerevisiae and A. niger in deliberately spiked products, exhibiting an antagonistic effect. Minor volatiles detected by HS-SPME GC/MS were mostly linked to either the grape juice or the immobilization carrier (apple pieces), while the nature of the freeze-dried cells (free or immobilized) and the storage conditions (room or refrigeration temperature) significantly affected the aromatic characteristics of the novel juice products. Notably, all novel juice products werecharacterized as highly original and were accepted during the preliminary sensory evaluation. In conclusion, data supporting the development of a novel functional juice containing freeze-dried immobilized L. rhamnosus OLXAL-1 cells on apple pieces with great market potential are presented. The wild-type culture used may serve as a biopreservative agent to prolong the shelf life of juices and prevent spoilage. However, more research is still required to verify their health-promoting effects in humans and their effectiveness in industrial production. ## References 1. 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--- title: Effects of Malocclusion on Maximal Aerobic Capacity and Athletic Performance in Young Sub-Elite Athletes authors: - El Mokhtar El Ouali - Hassane Zouhal - Loubna Bahije - Azeddine Ibrahimi - Bahae Benamar - Jihan Kartibou - Ayoub Saeidi - Ismail Laher - Sanae El Harane - Urs Granacher - Abdelhalem Mesfioui journal: Sports year: 2023 pmcid: PMC10051721 doi: 10.3390/sports11030071 license: CC BY 4.0 --- # Effects of Malocclusion on Maximal Aerobic Capacity and Athletic Performance in Young Sub-Elite Athletes ## Abstract Oral pathologies can cause athletic underperformance. The aim of this study was to determine the effect of malocclusion on maximal aerobic capacity in young athletes with the same anthropometric data, diet, training mode, and intensity from the same athletics training center. Sub-elite track and field athletes (middle-distance runners) with malocclusion (experimental group (EG); $$n = 37$$; 21 girls; age: 15.1 ± 1.5 years) and without malocclusion (control group (CG); $$n = 13$$; 5 girls; age: 14.7 ± 1.9 years) volunteered to participate in this study. Participants received an oral diagnosis to examine malocclusion, which was defined as an overlapping of teeth that resulted in impaired contact between the teeth of the mandible and the teeth of the upper jaw. Maximal aerobic capacity was assessed using the VAMEVAL test (calculated MAS and estimated VO2max). The test consisted of baseline values that included the following parameters: maximum aerobic speed (MAS), maximal oxygen uptake (VO2max), heart rate frequency, systolic (SAP) and diastolic arterial pressure (DAP), blood lactate concentration (LBP), and post-exercise blood lactate assessment (LAP) after the performance of the VAMEVAL test. There were no statistically significant differences between the two study groups related to either anthropometric data (age: EG = 15.1 ± 1.5 vs. CC = 14.7 ± 1.9 years ($$p \leq 0.46$$); BMI: EG = 19.25 ± 1.9 vs. CC = 19.42 ± 1.7 kg/m2 ($$p \leq 0.76$$)) or for the following physical fitness parameters and biomarkers: MAS: EG = 15.5 (14.5–16.5) vs. CG = 15.5 (15–17) km/h ($$p \leq 0.47$$); VO2max: EG = 54.2 (52.5–58.6) vs. CG = 54.2 (53.4–59.5) mL/kg/min ($$p \leq 0.62$$) (IQR (Q1–Q3)); heart rate before the physical test: EG = 77.1 ± 9.9 vs. CG = 74.3 ± 14.0 bpm ($$p \leq 0.43$$); SAP: EG = 106.6 ± 13.4 vs. CG = 106.2 ± 14.8 mmHg ($$p \leq 0.91$$); DAP: EG = 66.7 ± 9.1 vs. CG = 63.9 ± 10.2 mmHg ($$p \leq 0.36$$); LBP: EG = 1.5 ± 0.4 vs. CG = 1.3 ± 0.4 mmol/L ($$p \leq 0.12$$); and LAP: EG = 4.5 ± 2.36 vs. CG = 4.06 ± 3.04 mmol/L ($$p \leq 0.60$$). Our study suggests that dental malocclusion does not impede maximal aerobic capacity and the athletic performance of young track and field athletes. ## 1. Introduction Recent advances in sports medicine have allowed athletic performance to be monitored using a variety of assessments, including physical, technical, tactical, physiological, psychological, and medical parameters [1,2]. An athlete’s performance depends on the complex interaction of various physiological systems (e.g., proprioceptive, visual, and vestibular) to enable adequate neuromuscular actions [3,4]. The medical committee of sports clubs and federations primarily monitor performance and physiological measures such as the cardiorespiratory and musculoskeletal system with little attention paid to oral health. However, there is evidence that oral pathologies lead to athletic underperformance, suggesting that the monitoring of oral health should be an integral part of the performance testing of athletes [5]. The maxillary and mandibular teeth interact with each other almost 2000 times a day, mainly during chewing and swallowing [6], but this can also occur before and during physical effort. The normal coordination of dental occlusion is essential during physical activity [6], so that athletes have a greater ability to control balance under different conditions [7] such as the mastery of posture developed by gymnasts and dancers [8,9]. The World Health Organization (WHO) reports that malocclusion is a prevalent oral condition in both children and adults. In fact, it is the second most common disorder in children and the third most common in adults, following cavities and periodontal diseases [10]. Occlusion was defined by Boissonnet in 2011 as “Occlusion is the meshing of teeth so that the teeth of the mandible come into contact with the teeth of the upper jaw” [11]. In other words, if the upper (maxillary) and lower (mandibular) teeth do not make proper contact during closure, it is referred to as malocclusion [12,13,14,15]. More specifically, malocclusion is characterized by a poor alignment between the teeth of the upper and lower dental arches. Dental malocclusion refers to the misalignment of dental arches, which can cause various disturbances. Angle’s classification of occlusion and malocclusion is based on the position of the canines and the first molar in the anteroposterior direction [10]. Children who walk with a proper physiology tend to exhibit regular occlusion and are less likely to experience overloading injuries to their temporomandibular joint (TMJ) or vertebral column. Additionally, these children frequently maintain an appropriate posture [16,17]. Dental occlusion maintains the correct position of the mandible and provides comfort to athletes and/or patients [6]. An untreated malocclusion can affect body balance [18]. A study by Yoshida et al. [ 19] suggested that a reduced number of remaining natural teeth decreases balance control despite the use of dentures. Periodontal ligaments, masticatory muscles, and ensuring proprioception contribute to the regulation of posture and body movements [20]. The position of the mandible is controlled by the trigeminal nerve, which is influenced by posture [21]. A disorder of dental occlusion stimulates the trigeminal nerve and induces a chain of muscular and articular responses [22]. Maintaining good oral health is crucial for athletes, as oral diseases can have a direct impact on their overall health and prevent them from achieving their full athletic performance [23,24]. Sports dentistry focuses on the critical involvement of dentists in the research, prevention, treatment, rehabilitation, and understanding of the impact of oral diseases on the athletic abilities of professional and amateur athletes whilst improving their performance and reducing the risk of injury [25,26]. Later studies have indicated that dental malocclusion affects posture, contractile muscles, and athletic performance [27]. The peak force in occlusion is significantly higher in professional athletes compared with amateurs. A relationship has been described between the muscles involved in occlusion and the force produced by the postural muscles of the spine [28], so that a dental malocclusion influences the spatial position of the spine [29], body balance [19,20,21], vision [3,30], and eccentric strength of postural muscles [22,31,32,33,34,35,36,37,38]. The impact of dental malocclusion on postural stability and performance has been studied in rifle shooting [38], golf [18], and running [39]. Dental malocclusions can affect the development of the upper jaw, cardiorespiratory efficiency during exercise, and physical capabilities [40]. A large number of high-level athletes wear dental appliances to optimize their dental occlusion, thus maintaining their postural balance and athletic performance [6]. Of the elite athletes who participated in the London 2012 and Rio de Janeiro 2016 Olympic Games, $32\%$ believed their oral health had an impact on their athletic performance and $27\%$ said their oral health had an impact on their overall quality of life [41]. A total of $3\%$ of athletes reported difficulties in participating in training due to oral health problems [26,42] and over $40\%$ of them expressed dissatisfaction with their oral health condition [43]. In Brazil, investigations among footballers, basketball players, and triathletes revealed that $74\%$, $40\%$, and $38\%$, respectively, considered that oral problems interfered with physical performance [44]. Nadia Ouaziz represented Morocco in international 5 km and cross-country competitions in the 1990s. She suffered from chronic neck and back pain that affected her performance and recovery between sessions. A dental malocclusion was diagnosed as the source of her problems and orthodontic treatment with an individualized neuromuscular appliance worn during training sessions and at night produced immediate improvements, as stated by the athlete: “I had a lot more power in my legs. I felt refreshed and recovered between sessions” [40]. In 2009, Aly Cissokho’s transfer to AC Milan football club was cancelled due to the detection of a dental problem by the Italian doctors, which, according to them, could have caused numerous physical problems such as injuries [45]. Over the years 1985–1986, the American sprinter Carl Lewis underwent orthodontic treatment to correct his dental malocclusion and later went on to dominate world sprinting competitions in the 1980s and 1990s [46]. Randomized experimental studies on dental occlusion related to performance are limited, particularly on physical tests and biomarkers evaluating the athletic performance of athletes. According to the different hypotheses above, which suggest a negative impact on one or more parameters of athletic performance [3,6,27,30,40], the objective of our investigation was to examine the impact of malocclusion on the maximal aerobic capacity of young sub-elite athletes from the same training center with great similarity in terms of anthropometry, diet, training (same mode and training load), recovery methods, and medical intervention. We hypothesized that orthodontic pathologies such as malocclusion can negatively influence maximal aerobic capacity. ## 2.1. Study Design The main objective of the present investigation was to assess the impact of malocclusion on the physical and physiological capacities of young athletes. We chose a very homogeneous and identical population of athletes (young athletes living in the same training center with the same diet, lifestyle, athletic specialty, training, and medical follow-up) in order to show whether a difference in athletic performance between the control group and the experimental group would be due only to malocclusion. ## 2.2. Inclusion and Exclusion Criteria of Participants Participants were recruited according to the following inclusion criteria: young sub-elite middle-distance runners under 18 years of age from the same training center with the same anthropometric data (difference not significant), nutrition, load training, and recovery techniques. The exclusion criteria were a history of musculoskeletal injuries and disorders, significant difference in anthropometric data, smoking, and consumption of alcohol or the regular use of medication for any reason. The participants were required to avoid any physical activity for 48 h before the day of the test and were excluded from the study if they were uncomfortable with any aspect of the experimental protocol. ## 2.3. Procedures Written parental informed consent was obtained from all subjects. This study was approved by the Ethics Committee of the Doctoral Centre for Human Biomedical Research at the Faculty of Science, Ibn Tofail University (Kenitra, Morocco) and met the requirements for conducting biomedical research involving human subjects. A total of 50 young ($$n = 50$$; age range: 12–17 years old) highly trained/national-level athletes according to a 6-tiered Participant Classification Framework developed by Alannah et al. [ 47] participated in the study. A CONSORT flow diagram was included (Figure 1). All subjects were from the Athletics Training Center in Rabat (Center of the Royal Armed Forces, Morocco) and had the same diet and followed regular training programs of the same intensity (five times a week) and were followed by the same medical staff using the same recovery techniques (emersion in cold water and massage). The participants were affiliated with the Royal Moroccan Athletics Federation and competed in middle-distance races at the National Championship level. Orthodontic specialists from the Rabat Dental Consultation and Treatment Centre initially assessed the occlusal status of the athletes using Angle’s molar classification, and were classified as class I (no malocclusion, but crowding or misalignment of teeth), class II (distoocclusions) divisions 1 and 2, and class III (mesiocclusion) [10,46]. The maximum aerobic capacity was measured by baseline values of the following parameters: maximal aerobic speed (MAS), VO2max, heart rate, systolic blood pressure (SAP), diastolic blood pressure (DAP), blood lactate concentration (LBP), and post-exercise blood lactate concentration (LAP). ## 2.4. Maximal Aerobic Capacity We used the VAMEVAL test to evaluate the MAS [48]. This test assesses the MAS to estimate VO2max by running at a progressively faster pace in one minute increments. The rhythm was stored as an MP3 file containing sound signals. The physical test took place on a track that met the standards of the International Athletics Federation. Runners proceeded to blocks that were spaced every 20 m when prompted by the sound of a beep. The speed was then gradually increased by 0.5 km/h every minute. Participants stopped when they were no longer able to maintain the imposed rhythm, at which point the MAS and VO2max were evaluated using a reference table. ## 2.5. Blood Pressure and Heart Rate Measurements To obtain the baseline values of systolic and diastolic blood pressure and heart rate, measurements were only taken after the athletes rested for 15 min on chairs, using digital arm blood pressure monitors (Bosch, Sohn, Germany). The recorded values were the average of three measurements. Our measurement method respected and adhered to the recommendations for blood pressure measurements [49,50]. ## 2.6. Blood Lactate Measurements With the help of the health staff and following the safety recommendations, we sampled 2 mL of blood from our athletes from 9 am to 10 am. Blood lactate concentrations were measured at rest and 3 min after the VAMEVAL physical fitness test. A total of 50 tubes containing heparin were used to store 3 mL blood samples, which were then centrifuged (Hettich® ROTOFIX 32A, Tuttlingen, Germany) for five minutes at 3000 revolutions/min. The plasma was then separated by micropipettes and placed in Eppendorf tubes. The Eppendorf tubes were then placed in coolers and taken to the laboratory for the analysis. Lactate levels were measured using an enzymatic colorimetric method (Roche Diagnostics Cobas C311, Creatinine Jaffe Gen.2, Singapore) [51]. ## 2.7. Statistical Analyses To assess the normality of the data, we used the visual method (QQ-Plot) and the Agostino–Pearson statistical test. The heart rate, SAP, DAP, LBP, and LAP were normally distributed whereas the MAS and VO2max were not normally distributed. For the normally distributed baseline data, we used a t-test (parametric test); a Mann–Whitney test (non-parametric test) was used for the non-normally distributed baseline data. To analyze the differences in blood lactate before and after physical effort in both groups, we conducted a mixed-effects analysis for repeated measures analysis of variance (ANOVA), and subsequently performed Tukey’s multiple comparison test. Accordingly, the data were presented as means and standard deviations (SD), t-statistic (t), and degrees of freedom (df) for the normally distributed data or as medians and interquartile ranges (IQR (Q1–Q3)) for the non-normally distributed data. In addition, the comparison of the baseline and pre–post data (blood lactate) between the EG and CG was displayed with $95\%$ confidence intervals of the difference ($95\%$ CI). The statistical significance was set at $p \leq 0.05$ for all analyses. The statistical analysis was performed with GraphPad Prism 9.2.0 statistical software (GraphPad Software Inc., San Diego, CA, USA). ## 3. Results A total of 50 young athletes volunteered to participate in this study. After a diagnosis of malocclusion, 13 athletes (5 females and 8 males) without malocclusion formed the control group (CG) and 37 athletes (21 females and 16 males) with malocclusion formed the experimental group (EG). The anthropometric data in the control and experimental groups were similar (age: $$p \leq 0.46$$; BMI: $$p \leq 0.76$$), as shown in Table 1. The values for the MAS, VO2max, heart rate, SAP, DAP, LBP, and LAP in the control and experimental groups are summarized in Table 2 and Table 3. After analyzing our data, we found that the differences in the athletic performance and biomarkers were not statistically significant between the athletes with malocclusions and those without malocclusions, as summarized in Figure 2, Figure 3, Figure 4 and Figure 5. The values were the mean ± SD for the normally distributed parameters (heart rate, SAP, DAP, LBP, and LAP) and the median and IQR (Q1–Q3) for the non-normally distributed parameters (MAS and VO2max), with a $95\%$ confidence interval difference ($95\%$ CI) for the comparison of data in the EG and CG during the baseline and pre–post measurements (blood lactate; Table 4). ## 4. Discussion Studies examining the association between malocclusion and athletic performance based on several parameters and biomarkers (physical, physiological, and biomechanical) are relatively limited. The aim of this study was to assess the impact of malocclusion on physical and physiological abilities in an identical population of sub-elite runners from the same training center. The results of our study indicated that the MAS, VO2max, heart rate, SAP, DAP, LBP, and LAP were not significantly different ($p \leq 0.05$) in elite athletes with good dental occlusion compared with those with malocclusion. However, the findings of this investigation were not in agreement with several studies. Eberhard et al. [ 52] showed that VO2max levels were impaired in subjects with mild, moderate, and severe periodontitis. Athletic performance was demonstrated to be related to a healthy occlusal balance, which is required for optimal postural balance, injury prevention, and also improved muscle strength [30,53]. Mouth breathing and temporomandibular dysfunction were influenced by malocclusions [46]. Dental trauma had a negative impact on athletic performance, which could be remediated by orthodontic treatment [18]. Poor oral health reduced the physical and physiological capacity of professional soccer players [43,54], and dental malocclusion was associated with a loss of muscle strength in the elderly [55]. There were significant alterations in muscle strength after the disturbance of dental occlusion in healthy women [37], and increases in the muscle activity of the masseter, anterior, temporal, and trapezius muscles occurred in professional ballet dancers six months after gnathological treatment [56]. The oral health of athletes and/or individuals can be improved by the application of an occlusal splint [57]. In accordance with our results, Parrini et al. [ 58] showed that in athletes with malocclusion, no statistically significant differences were observed between the untreated control group and the treated group when performing countermovement and drop jumps or 10 m and 30 m sprint tests. A recent study reported that changes in dental occlusion did not affect the body posture and muscle activity of the upper limbs in male shooters [59]. The heart rate is regulated by the sympathetic and parasympathetic nervous systems. A consideration of heart rate variability (HRV) (the variation between two consecutive heartbeats, or “R–R”) is useful in controlling the training load, monitoring recovery kinetics, and assessing the training condition of athletes. HRV is influenced by temporomandibular joint dysfunction [60] and malocclusion [61]. Orthodontic treatment leads to improvements in oral function and also in HRV [62]. Ekuni et al. [ 60] found that the heart rate was higher in young adults with malocclusion. Normal concentrations of blood lactate are 1 to 2 mmol/L at rest, but reach higher values during intense exercise; for example, average values of between 4 and 8 mmol/L have been recorded in soccer matches [63,64]. The blood lactate level is a biochemical marker of muscle fatigue. According to Durst et al. [ 65], the blood lactate concentration and heart rate are the best biomarkers of the internal load during physical effort. The lactate levels were similar in both groups in our study, and no association was noted between malocclusion and blood lactate levels. To our knowledge, no study has examined changes in lactate levels in relation to dental malocclusion. A recent study reported that occlusal disturbances negatively influenced athletic performance, where there were increases in athletes with asymmetric muscle contractions ($$p \leq 0.025$$) coupled with decreased muscle power ($$p \leq 0.030$$) [18]. A significant influence of dental/facial trauma on physical performance ($$p \leq 0.006$$) in young professional volleyball and soccer athletes has also been reported [66]. Malocclusion and its treatments can influence body posture, foot–ground contact, center of mass, footprint, etc. [ 67,68]. Orthodontic treatment involves aligning or moving teeth to improve their appearance and function. Several studies have suggested that orthodontic treatment has a significant positive impact on the technical correction of malocclusion [69,70,71,72,73,74]. Hard stabilization splints (HSS) are utilized to ease tension in the masticatory muscles whilst directing the mandible to a stable position; these splints boast a simple preparation and easy adaptation, making them effective in reducing clinical symptoms [75,76]. In certain cases, prior to orthodontic treatment, therapeutic interventions such as HSS, counseling, or specific exercises may be employed to alleviate TMJ symptoms and minimize the associated discomfort [77,78]. After isokinetic testing, an increase in quadriceps muscle strength was observed when patients wore occlusal treatment splints [7]. Several factors such as genetics and the environment or a combination of both may be responsible for the high prevalence rates of malocclusion [79,80]. ACTN3 is a gene that codes for an α-actinin-3 protein, a cytoskeletal protein that binds to actin filaments and crosslinks them into dense bodies at the Z-disc of the sarcomere to maintain the myofibrillar network during muscle contraction [81], and is only expressed in type 2 muscle fibers that undergo rapid glycolysis and oxidation [81,82]. A R577X polymorphism (rs1815739) of the ACTN3 gene results from the replacement of arginine by a premature stop codon [83]. The expression of the ACTN3 (RR) genotype is higher in elite power/sprint athletes than in healthy non-athletes [84]. A low expression of the α-actinin-3 protein occurs in individuals of genotype (XX); on the other hand, in homozygous individuals, the genotype (RR) and/or heterozygotes (RX) have a higher expression of α-actinin-3 [85]. The absence of α-actinin-3 protein expression does not lead to any pathology, but can reduce muscle strength and cause intolerance to physical effort, with a dominance of explosive muscle actions [86] and lower bone mineral density [87]. A study by Zebrick et al. [ 81] reported a strong correlation between the ACTN3 577 (XX) genotype and skeletal class 2 malocclusion ($p \leq 0.01$) and significantly smaller type 2 fast-fiber diameters in masseter muscles in genotype (XX) subjects ($$p \leq 0.002$$). In a similar context, Cunha et al. [ 88] evaluated two genetic variants of the ACTN3 gene (rs1518739 and rs678397) with malocclusion. Concerning the rs1518739 variation, they found a significant association between genotype (XX) and skeletal class 2 malocclusion ($p \leq 0.05$); for the rs678397 variation, they observed a significant association with malocclusion ($p \leq 0.05$). Our results indicated that malocclusion does not negatively affect the physical and physiological markers of performance in young athletes. ## 5. Limitations To our knowledge, our study is the first to examine the relationship between malocclusion and the maximal aerobic capacity of athletes, based on a study of a limited number of biomarkers of sports performance. There are a few limitations to our study, which are: (i) the relatively small number of study participants ($$n = 50$$), which may be related to an invasive component of the study that may have triggered a degree of anxiety in adolescents; and (ii) the imbalance in the number of athletes without malocclusion ($$n = 13$$) compared with the athletes with malocclusion ($$n = 37$$). According to Bichara et al. [ 89], the average treatment time for malocclusions was 30.27 months; however, a comparative study assessing the impact of malocclusion on athletic performance before and after orthodontic treatment follow-up would be very relevant. The follow-up of a large number of athletes undergoing orthodontic treatment and the assessment of several performance parameters and biomarkers before and after treatment would be very useful to answer the question of the association between malocclusion and athletic performance. ## 6. Conclusions Our study indicated that malocclusion does not negatively affect the maximal aerobic capacity of young sub-elite athletes. Other studies have indicated a significant negative influence of malocclusions on athletic performance. These contradictory findings suggest that further studies are needed. ## References 1. Desgorces F.-D., Berthelot G., Helou N.E., Thibault V., Guillaume M., Tafflet M., Hermine O., Toussaint J.-F.. 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--- title: Modulation of Immunity, Antioxidant Status, Performance, Blood Hematology, and Intestinal Histomorphometry in Response to Dietary Inclusion of Origanum majorana in Domestic Pigeons’ Diet authors: - Hala Y. Amer - Rasha I. M. Hassan - Fatma El-Zahraa A. Mustafa - Ramadan D. EL-Shoukary - Ibrahim F. Rehan - František Zigo - Zuzana Lacková - Walaa M. S. Gomaa journal: Life year: 2023 pmcid: PMC10051733 doi: 10.3390/life13030664 license: CC BY 4.0 --- # Modulation of Immunity, Antioxidant Status, Performance, Blood Hematology, and Intestinal Histomorphometry in Response to Dietary Inclusion of Origanum majorana in Domestic Pigeons’ Diet ## Abstract This experiment was conducted to evaluate the effect of adding Origanum majorana (OM) powder to domestic pigeon diets on growth performance, feeding and drinking behaviour, blood hematology, blood biochemical parameters, blood inflammatory and oxidative markers, carcass characteristics, the weights of lymphoid organs, and and intestinal cecal, and bursa of Fabricius histology. A random distribution of fifty-four unsexed pigeon squabs (30 days old, average body weight; 321 g ± 7.5) into three groups was done. The first group was fed the grower basal diet without adding OM powder, while OM powder was added at levels of 0.5 and $1\%$ to the basal diets of the second and third groups, respectively. The changes in growth performance parameters and feeding and drinking behavior under OM powder’s effect were insignificant. However, the lymphoid organs (spleen and thymus) significantly increased in weight ($p \leq 0.05$) in the OM-fed groups. Moreover, blood examination showed positive responses to OM powder in terms of blood cell counts (RBCs andWBCs), and the values of hemoglobin, hematocrit, mean corpuscular volume, lymphocyte numbers, levels of globulin, and glutathione peroxidase enzyme were significantly increased. The numbers of heterophils, the ratio of heterophil to lymphocyte, malondialdehyde levels were reduced ($p \leq 0.05$). Histomorphometry examination revealed increases in intestinal villi height, cecal thickness, and bursal follicle area and number. These results indicated that adding OM powder to the pigeon diet may improve their immunity, increase their antioxidant status, and correct some hematological disorders. ## 1. Introduction Recently, the animal industry has expanded worldwide, including the production of livestock, companion animals, and poultry. Among these sectors, the most significant contributor to this expansion was poultry production [1]. It is known that poultry production is characterized by its lower cost, better feed conversion, and fewer associated environmental and health problems than other livestock productions [2,3]. Because of all these factors contributing to the growing population, poultry production has grown with rapid conversion to the commercial production type in developing countries [4]. Therefore, for improving the performance, immune response, and health of poultry, it was essential for researchers to examine new feed additives and include them into poultry diets. Herbal plants and their extracts are considered promising additives in poultry production; they can be used as growth promoters and immune modulators as replacements for antibiotics, which have adverse effects on poultry [5,6]. Origanum majorana [OM], or sweet marjoram, is a creeping aromatic medicinal herbal plant [7] that belongs to the family Lamiaceae. It is very popular in Western Asia and North Africa [8]. Because of its richness in phenolic compounds, flavonoids, and essential oils, with borneol, terpinene, pinene, sabinene, and terpineol contents [9], Origanum majorana is characterized by its antioxidant, antibacterial, antifungal, antiseptic, analgesic, immune modulator, and metabolism-inducing properties [10,11]. Moreover, OM extract could protect against renal and liver damage [8], lead acetate injury [12], and hyperlipidemia [13]. The broiler response to diets supplemented with prebiotics, probiotics, or herbal mixtures (Origanum majorana, Carum carvi, and Foeniculum vulgare) as alternatives to antibiotics indicated that the herbal mixture group recorded the highest productive performance [14]. Moreover, Saleh et al. [ 15] added a mixture of OM and another medicinal herbal plant to laying hen diets and noticed an improvement in their productivity and performance, including the feed conversion ratio and egg quality and quantity. Because of its highly palatable and delicious meat (which indicates high nutritional value), effortless management and rearing, and rapid weight gain, the marketing of domestic pigeons is very common in Egypt [16]. To our knowledge, few studies have been conducted in order to study the nutritional, behavioral, antioxidant, and immunomodulatory impacts of adding OM powder to the pigeon diet. In this study, we hypothesized that adding OM powder to pigeon diets may modulate their growth performance, feeding and drinking behavior, immune response, antioxidant status, and intestinal absorption in a desirable manner. Therefore, this experiment studied the effect of adding OM to the pigeon diet on performance, feeding and drinking behavior, carcass parameters and lymphoid organ weights, blood hematology, blood biochemical parameters, antioxidant and inflammatory markers, and intestinal, cecal, and bursal histomorphometry. ## 2.1. Origanum majorana Powder Origanum majorana (OM) powder was purchased from a commercial source (Organic, Natural Oil Factory, Assiut, Egypt), and prepared and analyzed (using the methods described by the AOAC [17]) in the Animal Nutrition and Clinical Nutrition Lab., New Valley University, Egypt. The OM chemical analysis indicated that it contains $95.5\%$ dry matter (DM), $3.3\%$ ether extract (EE), $14\%$ crude protein (CP), $10.3\%$ ash, and $17.5\%$ crude fiber (CF) using the following official methods: AOAC 930.15, AOAC 920.39, AOAC 984.13, AOAC 942.05, and AOAC 978.10. Metabolizable energy (ME) (2712 Kcal/Kg diet) was calculated based on the chemical composition, as described by the NRC [18]. In addition, the active principles of OM powder were analyzed in the Chemistry Lab., Faculty of Science, Assiut University, Assiut (see Supplementary Information Report S1). The active components included thymol ($4.2\%$), terpineol contents (alpha-terpineol $3.6\%$, alpha-terpinene $6.8\%$, alpha-terpinolene $1.5\%$, and gamma-terpinene $5.5\%$), carene ($1.1\%$), caryophyllene ($1.5\%$), alpha-phellandrene ($2.07\%$), aminopropyl phenol ($0.09\%$), fluoro-5-ethyl phenol ($0.2\%$), (1-Pyrrolyl) phenol ($1.7\%$), 5-methyl phenol ($0.14\%$), and cathine ($0.02\%$). The previous studies [19,20] were used to decide the inclusion level of OM powder in the diets. ## 2.2. Birds, Diets, and Design Fifty-four unsexed pigeon squabs (age: 30 days; average body weight; 321 g ± 7.5) from a local source (El-Matieuh rural villages—Assiut, Egypt) were randomly distributed into three groups ($$n = 18$$, 3 replicates, $$n = 6$$/group). The grower basal diet without supplementing OM powder was offered for the 1st group, while OM was added to the basal diets of the 2nd and 3rd groups at levels of 5 and 10 g/kg diet, respectively. The mashed form of the diet was used. The ingredients of the grower basal diet, which was formulated based on the recommendations of [21,22], are shown in Table 1. The temperature was adjusted according to the bird’s needs (18–23 °C). Natural and mechanical ventilations were supplied. Free access to both water and feed was provided. The schematic cartoon (Figure 1) of the experimental study was designed by BioRender.com. ## 2.3. Growth Performance The body weight was recorded for each bird at the study beginning. After that, body weight (individual and cumulative), along with the feed intake of pigeon squabs, was recorded weekly. The feed conversion ratio (FCR), relative growth rate (RGR), and European production efficiency index (EPI) were calculated [23,24]. ## 2.4. Feeding and Drinking Behavior Assessment During the experiment, feeding and drinking behaviors were observed [25]. Pigeons involved in eating behavior (act\30 min) were recorded by observing their contact with feed and water, following the recommendation of Spudeit et al. [ 26]. ## 2.5. Carcass Parameters and Lymphoid Organs The experimental period was 45 days. At the experimental end, 3 birds per group were euthanized by slaughter after their random selection and weighing. The lymphoid organs (spleen, bursa of Fabricius, and thymus), liver, heart, and gizzard were weighed and expressed as a percentage of the live body weight [27]. ## 2.6. Blood Examination During slaughtering, blood was collected from the cervical vein and preserved in heparinized and non-heparinized tubes (Vacutainer, Becton Dickinson, Stuart, FL, USA). ## 2.7. Blood Hematology The heparinized tubes were used for evaluating red blood cells (RBCs), white blood cells (WBCs), blood hemoglobin (Hb), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCH), hematocrit value (HCT), and differential white blood cell count. The ratio of heterophils/lymphocytes was calculated. Using a hemocytometer and staining blood films with the Wright–Giemsa stain, numbers of RBCs and WBCs were counted. ## 2.8. Blood Biochemical Parameters The blood samples in the other tubes were centrifuged for 15 min, at 3000 rpm at 4 °C, and kept at −20 °C till further analysis. Total proteins, albumin, globulin, total cholesterol, urea, and creatinine were determined by using commercial kits (Biotechnology Company, Assiut, Egypt). ## 2.9. Serum Inflammatory and Oxidative Markers For inflammation detection, tumor necrosis factor α (TNF-α) and interleukin 6 (IL6) were determined by an ELISA Kit for chicken (Biotechnology Company, Assiut, Egypt). The malondialdehyde (MDA) and glutathione peroxidase (GPx), as oxidative markers, were measured by commercial colorimetric kits) Biotechnology Company, Assiut, Egypt) using a spectrophotometer (Unico UV 2000; Spectra Lab Scientific Inc., Alexandria, VA, USA). ## 2.10. Histomorphometry Analyses Eight pigeons were randomly chosen to collect samples from the intestine (duodenum), cecum, and bursa of Fabricius. Immediately after slaughtering, samples were dissected, fixed in Bouin’s fluid, alcohol-dehydrated, cleared in methyl benzoate, and paraffin wax-embedded. After that, cutting at 4–5 μm thickness and staining with Harris hematoxylin were done [28]. Measurements of duodenal villi height/um, wall thickness/um, cecal muscle thickness/um, and follicle numbers/500 um and follicle area/um2 of the bursa of Fabricius were done using ImageJ software. Measurement data are described as means ± SDM. ## 2.11. Statistical Analyses Origanum majorana’s effects on performance, behavior, carcass characteristics, blood hematology, blood parameters, and inflammatory and oxidative markers in pigeons were analyzed using SPSS [26.0]. For treatment comparison, Duncan’s multiple range test was used. The $5\%$ level was used as an indication of significance [29]. The statistical model was Yij = μ + Ti + Eij, where Yij = response variables; μ = the overall mean; Ti = treatment effect; Eij = the experimental error. ## 3.1. Growth Performance Parameters Origanum majorana powder’s effect on the performance of pigeon squabs is shown in Table 2. A numerical increase in growth performance parameters under the OM powder effect was observed. However, no significant differences were detected among groups in terms of body weight, weight gain, feed intake, feed conversion, production index, or relative growth rate. ## 3.2. Feeding and Drinking Behavior The assessment of pigeons’ feeding and drinking behavior under the effect of Origanum majorana powder is indicated in Figure 2. Adding OM powder increased the birds’ feeding and drinking acts, but this increase was insignificant. ## 3.3. Carcass Parameters and Lymphoid Organs The effect of Origanum majorana powder on the carcass parameters and lymphoid organs is presented in Table 3. The dressing percentages for liver, gizzard, bursa, and heart did not show any significant changes among the experimental groups. However, there was a significant increase in spleen and thymus relative weights (p ≤ 0.05) in the OM powder groups. ## 3.4.1. Hematological Parameters The Origanum majorana powder effect on blood hematology is shown in Table 4. Red blood cells [RBCs], hemoglobin [Hb], hematocrit [HCT], mean corpuscular volume [MCV], white blood cells [WBCs], and lymphocyte % showed higher values with OM powder [$p \leq 0.05$]. While heterophils % and heterophils to lymphocyte ratio were significantly [$p \leq 0.01$] decreased. ## 3.4.2. Blood Biochemical Parameters, Serum Inflammatory Markers, and Oxidative Markers Blood parameters and markers affected by adding Origanum majorana powder to pigeon diets are presented in Table 5. Supplementation of OM powder had no effect on serum total protein, albumin, creatine, or urea levels. In contrast, globulin was higher [$p \leq 0.05$], and the albumin-to-globulin ratio was lower [$p \leq 0.05$] in the treated groups. Moreover, adding OM powder to pigeon diets at both levels reduced [$p \leq 0.05$] the cholesterol level. Interleukin 6 was not affected, while tumor necrosis factor tended to be [$$p \leq 0.09$$] increased by adding OM powder. In addition, serum oxidative markers, malondialdehyde, and glutathione peroxidase enzyme were significantly [$p \leq 0.01$] decreased and increased, respectively. ## 3.5.1. Duodenal and Cecal Histomorphometry A slight increase in intestinal villi length [about 510.134 ± 6.239 μm] was observed in the group fed $1\%$ OM powder. However, intestinal villi height was nearly similar in the control group [about 504.036 ± 31.292 μm], and the group provided $0.5\%$ OM powder [about 504.713 ± 4.021 μm] [Figure 3A–C and Figure 4]. The cecal wall thickness was increased with both levels of OM [about 1699.357 ± 4.468 μm and 1426.958 ± 8.336 μm with 0.5 and $1\%$ OM, respectively] in comparison with the control [about 1321.432 ± 7.518 μm]. In addition, a slight increase in muscular layer thickness was detected in the $0.5\%$ OM group [nearly 109.639 ± 1.426 μm] and $1\%$ OM group [nearly 110.050 ± 6.347 μm] in comparison with the control group [nearly 107.265 ± 3.050 μm] [Figure 3D–F and Figure 4]. ## 3.5.2. Bursal Follicle Histomorphometry The number of follicles was about 8.8 follicles per 500 μm in the control group. By adding OM powder, the number was increased to about 9 follicles per 500 μm with $0.5\%$ OM and about 12 follicles per 500 μm with $1\%$ OM. Moreover, the area of the follicle in the control group was about 249.500 ± 3.190 μm2 and increased to about 251 ± 5.332 μm2 in the $0.5\%$ OM group. The largest follicle area was demonstrated with a $1\%$ OM group [about 254.500 ± 5.816 μm2] [Figure 4 and Figure 5]. ## 4.1. Effect of Origanum majorana Powder on Growth Performance Characteristics The numerical values showed that pigeons fed OM powder had higher feed intake, body weight, weight gain, and relative growth rate than the control group; no significant differences were detected among the three groups. Our results agreed with those obtained by Khattab et al. [ 30]; they investigated feeding different levels of Origanum majorana, Pimpinella anisum, and Mentha piperita in relation to growth performance improvements in broiler chicks. They indicated that neither feed conversion nor body weight were affected by adding Origanum majorana to the broiler diet. Moreover, Ali [19] reported a reduction in the daily feed intake of broilers by supplementing Origanum majorana at levels of 0.5, 1.0, and $1.5\%$. Contrary to our results, Shawky et al. [ 20] and Abdel-Wahab [31] indicated that adding dietary Origanum majorana to broiler diets improved their weight and weight gain. No clear explanation was found for the variant effect of Origanum majorana on growth performance among the different research works. Still, it may be related to the variation in the level used in each experiment or other factors, such as stress. Vase-Khavari et al. [ 32] indicated that the efficacy of herbal plants and probiotics is correlated to different factors, such as their level and concentration used, the composition of the diet, environmental factors, and the hygiene of the poultry houses. ## 4.2. Effect of Origanum majorana Powder on Feeding and Drinking Behavior Bird physiological conditions, diet composition, feeder space, and heat stress can affect birds’ feeding and drinking behavior [33,34,35]. The assessment results for feeding and drinking behavior were consistent with the performance results, as OM powder increased feeding and drinking behavior, but this increase was insignificant. Ramadan [36] and Harrington et al. [ 37] indicated that aromatic herbs and their extracts could increase feeding behavior in poultry. Ramadan [36] reported the presence of a negative correlation between fear and feeding behaviors in poultry, as a decrease in the fear response will increase feeding behavior. Scientists suggested that aromatic plants have a depressing effect on neural activity through the activation of GABA receptors, resulting in reduced fear behavior and increased feeding times [36,37,38]. The fear response was not assessed in our experiment. ## 4.3. Effect of Origanum majorana Powder on Carcass Characteristics and Lymphoid Organs The dressing percentage and liver, heart, gizzard, and the bursa of Fabricius did not differ among pigeons supplemented with OM powder and the control group. The absence of the OM effect on carcass traits was expected, because of the similar growth performances among the three groups. Several studies reported that adding herbal plants either in powder or oil extract did not affect broilers’ internal organ weights [39]. Moreover, Shawky et al. [ 20] reported that the weights of the liver, heart, and gizzard did not show any significant difference when dietary supplementation of OM was used in broiler diets. The avian immune response can be affected by several extrinsic or intrinsic factors; one of the significant extrinsic factors affecting bird immunity is the diet and its composition [40]. The lymphoid organs responsible for avian immunity include primary and secondary organs. The primary organs are the thymus and bursa of Fabricius [41]. These organs are the sites for maturation, differentiation, and immunocompetence of T and B types of lymphocytes [42]. Functional T and B cells depart from the primary to the secondary lymphoid organs, including the bone marrow and spleen [43]. Ahsan et al. [ 44] indicated that the relative weight of lymphoid organs reflects the bird’s immunity status. In our experiment, the thymus and spleen showed significant increases in their weights with the OM powder supply, which means that the pigeon immune responses were improved under the effect of Origanum majorana. The impact of OM may be related to the presence of flavonoids and phenolics, with their antibacterial, antioxidant, and immune-modulating effects. However, Ali [19] indicated that the spleen weight in broilers was not affected by adding variant Origanum majorana powder levels. ## 4.4. Effect of Origanum majorana Powder on Blood Hematology Nutrition’s effect on bird physiology and metabolism can be indicated by examining blood hematology and biochemical blood parameters [45]. As a result, adding Origanum majorana to birds’ diet affected the pigeons’ hematology. Origanum majorana powder significantly increased both RBC (with $1\%$ OM) and WBC counts, which are responsible for oxygen transfer and protection against infection, respectively. The elevation in the numbers of RBCs with OM may refer to its antioxidant activity, preventing lipid peroxidation in blood cell membranes. Moreover, the increased WBC number may be related to thymol (active component in OM), which is responsible for immune response enhancement [46]. The favorable effect of Origanum majorana on blood hematology also included raising the values of Hb, HCT, MCV, and lymphocyte percentage. The positive impact of OM on Hb may be related to its higher content of iron, which is considered an essential nutrient for hemoglobin production [47]. At the same time, the increased MCV suggests that OM has a hematopoietic impact, as RBCs (both new and young) are more prominent and contain a higher Hb amount [48]. According to Altan et al. [ 49], the H/L ratio is a valuable tool for explaining the different stress factors to which birds are exposed. In our experiment, adding OM powder to the pigeon diet decreased heterophils, increased lymphocytes, and, consequently, decreased the H/L ratio, which means that it may play a vital role in alleviating bird stress. Stef et al. [ 50] indicated that lymphocytosis could enhance interferon production. Furthermore, it was reported that hematological disorders caused by toxins, metals, or bacterial infections in different animals could be corrected by adding herbs to their diets [51,52]. ## 4.5. Effect of Origanum majorana Powder on Biochemical Parameters, Inflammatory and Oxidative Markers Total protein, albumin, creatinine, and urea were not changed by adding OM powder. Similarly, Shawky et al. [ 20] reported no significant difference in total protein and urea between the OM-supplemented group and the control group. Globulin was increased, while the ratio of albumin/globulin was decreased with OM powder. The same author suggested that the significant elevation in globulin indicates the Origanum’s ability to enhance the immunity of broiler chicks. Origanum majorana has been reported to induce hypocholesterolemia [15,31]. Our cholesterol result agreed with these reports. It was indicated that carvacrol and thymol present in OM could reduce cholesterol levels by inhibiting hepatic 3-hydroxy-3-methyl-glutaril198 CoA reductase [46,53]. In our experiment, interleukin 6 was not affected, while tumor necrosis factor-α levels tended to be increased with OM powder. Substances that promote leukocytosis may stimulate cytokine secretion from these cells, such as interleukin 6 and TNF-α [54]. Therefore, the tendency of TNFα to increase may be a compensatory reaction due to leukocytosis. Contrary to our results, Arranz et al. [ 55] indicated that the essential oil extracted from Origanum majorana has anti-inflammatory activity, as it contains terpineol and sabinene hydrate, which adversely affect cytokine production. Malondialdehyde is considered a lipid peroxide. When its level increases, it can impair nucleic acid metabolism and function, destroy membrane proteins, and lead to autoimmune diseases [56]. To overcome lipid peroxidation and toxic free radicals, the secretion of some enzymes such as superoxide dismutase and glutathione peroxidase is enhanced, which play essential roles in the body’s defense mechanism against peroxidation. In the current study, OM powder significantly decreased the MDA level and increased the glutathione peroxidase level. The association between OM’s richness in phenolics and flavonoids (such as carnosol, carnosic acid, and hydroxycinnamic acid) and its antioxidant effect was investigated [9]. Therefore, Origanum majorana can play an essential role in maintaining the normal physiology, production, health, and welfare of animals. ## 4.6. Effect of Origanum majorana Powder on Duodenal, Cecal, and Bursal Follicle Histomorphometry Feed utilization efficiency depends on feed digestion and absorption, which are affected by the intestinal surface [57]. Our histological results indicated that the intestinal villi length was slightly increased with OM powder. Abdelatty et al. [ 58] reported that improvements in growth performance are associated with increases in intestinal villi length and intestinal absorption. It was observed that the slight increase in intestinal villi length in the Origanum groups was associated with a numerical increase in body weight. In the muscular layer, the cecal wall was thickened with OM powder supplementation. Scarce studies take morphometrical measurements for the cecum, despite its role in immune response, water absorption, digestion, and fermentation [59,60,61]. As a primary lymphoid organ, the bursa has a crucial role in B cell maintenance and establishment [41]. The area and number of follicles in the bursa of Fabricius were increased with OM powder. Attia et al. [ 62] reported that induction of humoral immunity and B lymphocyte production is associated with increases in the area of the bursal follicle. ## 4.7. Limitations of the Study There was no possibility to confirm the results through q-PCR or to perform LC-MS analysis of serum, in order to see whether feeding OM increased the metabolites related to brain modulators, antioxidants, and immune modulators. In addition, the fear response was not assessed in our experiment in order to confirm as to whether it is correlated with increased feed intake. However, this research is essential and acts as the first step to realizing the influence of OM on improving the health status and welfare of pigeons; therefore, further experiments are required to emphasize the neural activity of birds. ## 5. Conclusions Adding OM powder to the pigeon diet increased the relative weights of the lymphoid organs (spleen, thymus, and the number and area of bursal follicles), the WBC count, the lymphocyte count, and the serum globulin level. These effects suggest that OM powder may enhance bird immunity. The increased Hb, HCT, and MCV may have a hematopoietic effect. A decreased H/L ratio and MDA, as well as increased GPx, indicated that OM powder might have an antioxidant effect. Histological examination of the intestine suggested that nutrient absorption may be affected by adding OM powder, but this point needs further investigation. 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--- title: SARS-CoV-2 Disease Severity in the Golden Syrian Hamster Model of Infection Is Related to the Volume of Intranasal Inoculum authors: - Alastair Handley - Kathryn A. Ryan - Elizabeth R. Davies - Kevin R. Bewley - Oliver T. Carnell - Amy Challis - Naomi S. Coombes - Susan A. Fotheringham - Karen E. Gooch - Michael Charlton - Debbie J. Harris - Chelsea Kennard - Didier Ngabo - Thomas M. Weldon - Francisco J. Salguero - Simon G. P. Funnell - Yper Hall journal: Viruses year: 2023 pmcid: PMC10051760 doi: 10.3390/v15030748 license: CC BY 4.0 --- # SARS-CoV-2 Disease Severity in the Golden Syrian Hamster Model of Infection Is Related to the Volume of Intranasal Inoculum ## Abstract The golden Syrian hamster (Mesocricetus auratus) is now commonly used in preclinical research for the study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the assessment of vaccines, drugs and therapeutics. Here, we show that hamsters inoculated via the intranasal route with the same infectious virus dose of prototypical SARS-CoV-2 administered in a different volume present with different clinical signs, weight loss and viral shedding, with a reduced volume resulting in reduced severity of disease similar to that obtained by a 500-fold reduction in the challenge dose. The tissue burden of the virus and the severity of pulmonary pathology were also significantly affected by different challenge inoculum volumes. These findings suggest that a direct comparison between the severity of SARS-CoV-2 variants or studies assessing the efficacy of treatments determined by hamster studies cannot be made unless both the challenge dose and inoculation volume are matched when using the intranasal route. Additionally, analysis of sub-genomic and total genomic RNA PCR data demonstrated no link between sub-genomic and live viral titres and that sub-genomic analyses do not provide any information beyond that provided by more sensitive total genomic PCR. ## 1. Introduction SARS-CoV-2 was first identified in the lower respiratory tract of patients presenting with viral pneumonia in December 2019, before triggering a pandemic declaration by the World Health Organisation on the 11 March 2020 [1]. The disease (COVID-19) which results from infection with SARS-CoV-2 virus in humans causes a broad spectrum of respiratory symptoms, from very mild to severe, life-threatening and fatal illness. Fatality and severe disease have been shown to be associated with human host risk factors including obesity and elderly ages [2]. An unprecedented global effort was initiated early in the pandemic to develop drugs, vaccines and therapeutics to prevent death, aid treatment and prevent the spread of COVID-19. With new SARS-CoV-2 variants continuing to arise, continuous research and development are needed to ensure vaccines and therapeutics remain effective. The golden Syrian hamster has become the species of choice for in vivo preclinical assessment of virulence of variants of SARS-CoV-2 and preclinical research assessing the efficacy of vaccines, antivirals and therapeutics. The hamster experiences mild to severe disease with measurable clinical signs, significant weight loss, viral shedding, lung pathology and immune response after intranasal (IN) inoculation with SARS-CoV-2 virus [3]. Unlike other animal species such as ferrets [4,5] and non-human primates [6], which usually develop mild disease, the wide range of quantitative and qualitative outputs provided by the hamster intranasal infection model allows for sufficient discriminatory power to measure the efficacy of vaccines, drugs or therapeutics against SARS-CoV-2 [7]. Published reports comparing BA.1 and BA.2 variants of SARS-CoV-2 in the hamster model of IN infection have produced different results in relation to the severity of the resulting disease. For example, Yamasoba et al. [ 8] found SARS-CoV-2 variant Omicron BA.2 caused more severe disease than the BA.1 variant after inoculation using a volume of 100 µL (1 × 104 TCID50/mL dose), while Kawaoka et al. [ 9] found both variants similarly pathogenic after inoculation using a volume of 30 µL (both 1 × 103 and 1 × 105 plaque forming units (PFU)/mL dosages used). There is currently no widely accepted standard method for the IN challenge inoculation dose and volume beyond the maximum volumes acceptable for animal welfare standards. This has resulted in a wide variance in volumes used between different laboratories. In many published results, there is a lack of specific information such as whether inoculation volumes refer to the total inoculation volume or volume given per nare, how the hamsters were restrained and whether or not anaesthesia or sedation was used (Table 1). This lack of specific information about volume and administration is highly likely to compromise the ability to compare findings between studies. In this study, when we challenged hamsters with the same infectious virus dose administered in inoculation with a different (four-fold) inoculum volume, we observed different disease severity outcomes. Fifty microlitres (25 µL per nare) resulted in mild disease but two hundred microlitres (100 µL per nare) resulted in moderate disease. In our further studies, we found that in order to achieve a similar difference in severity using the same volume (200 µL) we needed to use a 500-fold dilution of live virus. These findings suggest that to compare different SARS-CoV-2 variants and assess the efficacy of vaccines, drugs and therapeutics, the same volume of the challenge as well as the viral dose in the inoculum should be used. ## 2. Materials and Methods Viruses and Cells: SARS-CoV-2 Australia/VIC$\frac{01}{202035}$ was generously provided by The Peter Doherty Institute, Melbourne, Australia at P1 after primary growth in Vero/hSLAM cells and subsequently passaged twice at UKHSA Porton in Vero/hSLAM cells [ECACC 04091501]. Infection of cells was with ~0.0005 MOI of virus and harvested at day 4 by dissociation of the remaining attached cells by gentle rocking with sterile 5 mm borosilicate beads followed by clarification by centrifugation at 1000× g for 10 min. Whole genome sequencing was performed, on the P3 challenge stock, using SISPA amplification on both Nanopore and Illumina technologies as described previously [18]. The virus titre of the VIC01 challenge stocks was determined by plaque assay on Vero/E6 cells [ECACC 85020206]. Cell lines were obtained from the European Collection of Authenticated Cell Cultures (ECACC) UKHSA, Porton Down, UK. Cell cultures were maintained at 37 °C in MEM (Life Technologies, Carlsbad, CA, USA) supplemented with $10\%$ foetal bovine serum (Sigma, Hertfordshire, UK) and 25 mM HEPES (Gibco, Paisley, UK), 2 mM L-Glutamine (Gibco), 1× non-essential amino acids solution (Gibco). In addition, Vero/hSLAM cultures were supplemented with 0.4 mg/mL of geneticin (Invitrogen, Oxford, UK) to maintain the expression plasmid. Animals: Twelve healthy, golden Syrian hamsters (Mesocricetus auratus) were obtained from a UK Home Office accredited supplier (Envigo RMS, Oxon, UK). Animals were housed individually at the Advisory Committee on Dangerous Pathogens (ACDP) containment level 3. Cages met with the UK Home Office Code of Practice for the Housing and Care of Animals Bred, Supplied or Used for Scientific Procedures (December 2014). Access to food and water was ad libitum and environmental enrichment was provided. All experimental work was conducted under the authority of and in compliance with a UK Home Office approved project licence that had been subject to local ethical review at UKHSA Porton Down by the Animal Welfare and Ethical Review Body (AWERB) as required by the Home Office Animals (Scientific Procedures) Act 1986. A second set of six hamsters originally used in a separate study were included for comparative purposes [14]. Experimental Design: Before the start of the experiment, animals were randomly assigned to challenge groups to minimise bias. An identifier chip (Plexx IPTT-300 temperature transponder) was inserted subcutaneously into each animal. Prior to the challenge, animals were sedated by isoflurane. The challenge virus was delivered by intranasal instillation (200 µL total, 100 µL per nostril for the standard volume inoculation and 50 µL total, 25 µL per nostril for the reduced volume inoculation) diluted in phosphate-buffered saline (PBS). During intranasal inoculation, the hamsters are held in a ventral dorsal decubitus position with the head forming a 45° angle. The intranasal administration procedure is performed slowly, drop by drop, to ensure each aliquot of inoculum has entered the nasal cavity before the next drop is administered. The standard target dose of 5 × 104 PFU/mL VIC01 was delivered to both groups ($$n = 6$$) of hamsters. Hamsters were throat swabbed at days 2, 4, 6 and 7 post-challenge. A second set of one group ($$n = 6$$) of hamsters was included from a previous study, receiving the standard volume inoculation and a reduced dose of 1 × 102 PFU/mL. These hamsters were throat swabbed at days 2, 4, 6 and 8. Clinical observations: Hamsters were monitored for temperature via Plexx IPTT-300 temperature transponders and for clinical signs of disease twice daily (approximately 8 h apart). Clinical signs of disease were assigned a score based upon the following criteria (score in brackets): healthy [0], lethargy [1], behavioural change [1], sunken eyes [2], ruffled [2], wasp-waisted [3], dehydrated [3], arched [3], coughing [3], laboured breathing 1-occasional catch or skip in breathing rate [5] and laboured breathing 2-abdominal effort with breathing difficulties [7]. Animals were weighed at the same time each day until euthanasia. Post-mortem examination and pathology. Hamsters were given an anaesthetic overdose (sodium pentabarbitone Dolethal, Vetquinol UK Ltd., Titchmarsh, UK, 140 mg/kg) via intraperitoneal injection and exsanguination was effected via cardiac puncture. A necropsy was performed immediately after confirmation of death. Each animal was assigned a histology ID number for blinding purposes. Lung (left lobe and caudal right lobe) and nasal cavity samples were fixed in neutral buffered formalin. The nasal cavity was decalcified using an EDTA solution prior to embedding in paraffin wax. Tissue sections were stained with haematoxylin and eosin (H&E) and scanned by a Hamamatsu NanoZoomer S360 and viewed with NDP.view2 software (v2.9.29). The pathologist was blinded to treatment and group details and the slides were randomised prior to examination in order to prevent bias (blind evaluation). A semi-quantitative, subjective scoring system is used to evaluate the severity of lesions observed in the lung and nasal cavity [19]. Additionally, the percentage of area comprising pneumonia in the lung was calculated using digital image analysis (Nikon-NIS-Ar, Nikon UK, Surrey, UK). RNAscope (an in situ hybridisation method used on formalin-fixed, paraffin-embedded tissues) was used to identify the SARS-CoV-2 virus in all tissues. Briefly, tissues were pre-treated with hydrogen peroxide for 10 min (RT), target retrieval for 15 min (98–101 °C) and protease plus for 30 min (40 °C) (all Advanced Cell Diagnostics, Abingdon, UK). A V-nCoV2019-S probe (Advanced Cell Diagnostics) targeting the S-protein gene was incubated on the tissues for 2 h at 40 °C. Amplification of the signal was carried out following the RNAscope protocol (RNAscope 2.5 HD Detection Reagent–Red) using the RNAscope 2.5 HD red kit (Advanced Cell Diagnostics). RNAScope stained sections were also scanned and digital image analysis was carried out in order to calculate the total area of the lung section positive for viral RNA. For the nasal cavity, a semiquantitative scoring system was applied to evaluate the presence of virus RNA: 0 = no positive staining; 1 = minimal; 2 = mild; 3 = moderate and 4 = abundant staining. RNA Extraction: Throat swabs were inactivated in AVL plus ethanol and RNA was isolated. Downstream extraction was performed using the BioSprint™96 One-For-All vet kit (Indical, Leipzig, Germany) and Kingfisher Flex platform as per the manufacturer’s instructions. Quantification of Viral RNA by RT-qPCR: Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) targeting a region of the SARS-CoV-2 nucleocapsid (N) gene was used to determine viral loads and was performed as previously described [4]. Positive swab and fluid samples detected below the limit of quantification (LLOQ) of 12,857 copies mL were assigned the value of 5 copies/µL, which equates to 6429 copies/mL, whilst undetected samples were assigned the value of <2.3 copies/µL, equivalent to the assay’s lower limit of detection (LLOD), which equates to 2957 copies/mL. Additional PCR data was taken from a separate, previous study for analysis of the relationship between live viral titre, total genomic RNA titre and sub-genomic RNA titre. Samples were processed and analysed using the same methods listed here. Confirmation of Challenge Dose by Plaque Assay: The challenge dose was confirmed by plaque assay prepared on the day of challenge. Dilutions of the challenge material were plated in triplicate on each assay plate for confirmation of the challenge titre. The challenge dose was diluted in MEM containing added antibiotic/antimycotic (Life Technologies) and no serum and incubated in 24-well plates (Nunc, ThermoFisher Scientific, Loughborough, UK) with Vero E6 cell monolayers. The virus was allowed to adsorb at 37 °C for 1 h, then overlaid with MEM containing $1.5\%$ carboxymethylcellulose (Sigma), $4\%$ (v/v) foetal bovine serum (Sigma) and 25 mM HEPES buffer (Life Technologies). After incubation at 37 °C for 5 days, the plates were fixed overnight with $20\%$ (w/v) formalin/PBS, washed with tap water and stained with methanol crystal violet solution ($0.2\%$ w/v) (Sigma). Focus forming assay (FFA): The virus titre for live SARS-CoV-2 throat swab samples was determined by focus forming assay on Vero/E6 cells [ECACC 85020206]. Ninety-six well plates were seeded with 2.5 × 104 cells/well the day prior to infection and then washed twice with Dulbecco’s PBS (DPBS). Ten-fold serial dilutions (1 × 10−1 to 1 × 10−6) of virus stocks were prepared in MEM (supplemented with 25 mM HEPES (Gibco), 2 mM L-Glutamine (Gibco), 1× non-essential amino acids solution (Gibco)). A hundred microliter virus inoculum was added per well in duplicate and incubated for 1 h at 37 °C. The virus inoculum was removed, and cells overlaid with MEM containing $1\%$ carboxymethylcellulose (Sigma), $4\%$ (v/v) heat-inactivated foetal calf serum (FCS) (Sigma), 25 mM HEPES buffer (Gibco), 2 mM L-Glutamine (Gibco), 1× non-essential amino acids solution (Gibco). After incubation at 37 °C for 26 h, cells were fixed overnight with $8\%$ (w/v) formalin/PBS, washed with water and permeabilised with $0.2\%$ (w/v) Triton X-100/PBS at room temperature for 10 min. Cells were washed with PBS, incubated with $0.3\%$ hydrogen peroxide (Sigma) at room temperature for 20 min and washed with PBS. Foci were stained with 50 µL/well rabbit anti-nucleocapsid (Sino Biological, 40588-T62) diluted 1:1000 in $0.2\%$ (w/v) Triton X-100/PBS for 1 h at room temperature. Antibody dilutions were discarded and cells were washed with PBS and incubated with 50 µL/well goat anti-rabbit IgG HRP (Invitrogen, G-21234) diluted 1:4000 in $0.2\%$ (w/v) Triton X-100/PBS for 1 h at room temperature. Cells were washed with PBS and incubated with TrueBlue peroxidase substrate (SeraCare, 5510-0030) for 10 min at room temperature then washed with water. Infectious foci were counted with an ImmunoSpot® S6 Ultra-V analyser with BioSpot counting module (Cellular Technologies Europe). Titre (FFU/mL) was determined by the following formula: titre (FFU/mL) = No. of foci/(Dilution factor × 0.1). Statistical Analysis: Statistical analysis was performed on Log10 transformed PCR data using R version 4.1.3. To compare group throat swab viral loads post-challenge with their respective re-challenge viral loads, data were analysed using Tukey’s honest significant difference (HSD)-corrected pairwise multiple comparisons mixed-effects analysis of variance (ANOVA). The fixed effects in the model were sample days post challenge (DPC) and the group and the random effect was the individual animal. Culls were performed at 7 DPC and 35 DPC (groups 1 and 5 at 7 DPC and groups 2 to 4 at 35 DPC). Viral RNA copies in collected lung tissue from each group were compared by ANOVA with post hoc pairwise Tukey’s HSD to compare viral RNA measured in different groups and DPC. Weight percentage change data were also analysed by Tukey-corrected pairwise multiple comparison ANOVA. Parametric statistical analyses were selected as the data were expected to conform to a log-normal distribution (for qPCR results) or a normal distribution (for weights) based on historical observations of data from similar hamster challenge studies. Ordinal clinical score data were analysed using a non-parametric (Kruskal–Wallis) test. Histopathological results were analysed by a Mann–Whitney’s U test. No statistical analysis was undertaken on temperature data as no trends were observed. ## 3. Results Study Design: Hamsters ($$n = 6$$ per group with an equal male/female ratio) were challenged intranasally with Australia/VIC$\frac{01}{202035}$ SARS-CoV-2 (VIC01), in two volumes, a 200 μL or 50 μL volume at the standard dose (5 × 104 PFU). A further group was challenged using a 200 μL inoculum volume at a reduced (500-fold less) viral dose (1 × 102 PFU) and not culled during the study timeframe. Groups inoculated with the standard viral dose in 200 μL and in 50 μL were culled 7 days after challenge for evaluation of lung disease severity. Plaque forming unit (PFU) back-titration was completed on the day of the challenge on samples of the inoculum, confirming the target dose of SARS-CoV-2 was administered to each group. A lower challenge inoculation volume produced milder clinical signs of infection and respiratory pathology in hamsters compared to a higher inoculation volume: all hamsters lost weight after inoculation with SARS-CoV-2. Hamsters inoculated with the standard dose of SARS-CoV-2 in 200 µL volume lost weight faster and to a greater extent than hamsters inoculated with the same dose in 50 µL volume. The difference was statistically significant from four days post-challenge (DPC) onwards (Figure 1a,b). At 6 DPC hamsters had experienced significantly higher ($$p \leq 0.0004$$) group mean peak weight loss (Figure 1b), demonstrating more severe disease developing as a result of a higher volume inoculation. No significant difference in weight loss was observed between hamsters inoculated with the standard dose in 50 µL and those inoculated with the 500-fold reduced dose in 200 µL. Qualitative measures of clinical signs of disease excluding weight loss were assigned a score using an arbitrary scale weighted such that clinical signs considered to hold greater clinical significance received higher scores (Table 2) [14] (Figure 1c). An earlier onset of clinical signs was also observed in hamsters inoculated with the standard dose in 200 µL than in hamsters inoculated with the standard dose in 50 µL (Figure 1d–f). There was no significant difference between the groups’ average assigned clinical observation scores. Pathological investigation of post-mortem tissues taken at 7 DPC revealed a significantly lower ($$p \leq 0.0087$$) total area of pneumonia found in the samples of lung from hamsters inoculated with the standard dose of SARS-CoV-2 (5 × 104 PFU) in a 50 µL total volume (25 µL per nare) compared to those inoculated using a 200 µL total volume (100 µL per nare) (Figure 2a,e). The percentage of the lung containing SARS-CoV-2 RNA as measured by in situ hybridisation also showed significantly lower ($$p \leq 0.0022$$) virus in the lung tissue of hamsters inoculated with 50 µL of SARS-CoV-2 than those inoculated with 200 µL (Figure 2b,e). In contrast, the percentage of the nasal cavity containing SARS-CoV-2 RNA as measured by in situ hybridisation showed no significant difference between either inoculation volumes (Figure 2c,e). A marked decrease in pathology scores [19] in the lung tissue of hamsters inoculated with 50 µL of SARS-CoV-2 compared to those inoculated with 200 µL was also observed scoring different parameters of airway and pulmonary parenchyma histopathology (Figure 2d). Viral Shedding titres are unaffected by varied inoculation volumes: Decreasing either the volume (four-fold) or dose (500-fold) of SARS-CoV-2 inoculum in relation to the standard dose and volume (5 × 104 PFU in 200 µL) did not affect viral shedding titres from the upper respiratory tract (URT) measured in throat swabs (Figure 3a) and no significant differences were found between the amount of total viral RNA shed between groups. Additionally, according to qPCR performed on lung homogenate, we found the viral burden in the lung was unaffected by varying the challenge volume (Figure 3b). Sub-genomic E-gene PCR provides no additional value over total genomic PCR: Sub-genomic E-gene PCR titres closely correlated with total genomic viral load titres but fall below the limits of quantification and detection too rapidly to accurately compare to live viral titres from ex vivo samples. The correlation between total viral genome copies and sub-genomic E gene copies was highly significant ($$p \leq 3.81$$ × 10−127), but a high level of variance was observed between live viral titres measured by focus forming assay and both total and sub-genomic RNA titres (Figure 4a). In vitro comparison of total RNA, sub-genomic RNA and live virus titres also demonstrated a very high correlation between total genomic and sub-genomic titres but here live viral titres remained high enough for quantification and showed a decline in live viral titres while both total and sub-genomic titres remained stable (Figure 4b). A large-scale analysis of samples from the CEPI Agility variant screening program [20] also demonstrated a significant linear relationship between total viral RNA titres and sub-genomic RNA titres. The fitted linear regression model determined a Y-intercept of −2.897 indicating three log10 lower sensitivity and an R2 of 0.95 ($$p \leq 3.81$$ × 10−127) (Figure 4c). ## 4. Discussion The golden Syrian hamster provides a robust host species in the intranasal model of infection for SARS-CoV-2 to facilitate rapid in vivo analysis of new variants and the efficacy of vaccines, prophylactics and treatments. This species helps to reduce the global scientific communities’ reliance on larger animal models of infection including non-human primates. In this study, we show that changing the volume, whilst maintaining the same viral load, of a SARS-CoV-2 intranasal challenge inoculation significantly alters the severity of disease caused. Hamsters inoculated intranasally with a challenge virus titre of 5.0 × 104 PFU delivered in 50 µL demonstrated a significantly lower peak weight loss–similar to that seen in the animals inoculated with a 500-fold lower dose of SARS-CoV-2. These hamsters also demonstrated markedly reduced severity and slower onset of clinical signs than those intranasally inoculated with the same viral titre in 200 µL. Moreover, histopathological analysis revealed that hamsters receiving the 50 µL inoculation showed significantly lower histopathology scores, smaller areas of pneumonia, and lower viral RNA loads in the lung. No difference was observed in the nasal cavity pathology between hamsters receiving different inoculation volumes. These observations are consistent with the lower volume inoculation not being able to reach as deeply into the lung, remaining mostly in the nasal cavity, an effect previously seen with influenza in ferrets [21]. This may be due to the inoculum being inhaled either intratracheally or as a large particle aerosol and from there entering the lower lung in a similar manner to an aerosol infection and/or directly as a small particle aerosol through inhalation during administration. This suggests that where the virus is able to reach the nasal tract due to direct inoculation, virus replication will occur with similar results. Consideration should be given to whether some of the larger volumes of inoculum may have been swallowed during inoculation making its way into the gastrointestinal tract. It has been shown that ACE2 receptors are found throughout the hamster gut [22]; however, there are conflicting reports on whether oral inoculation with SARS-CoV-2 leads to weight loss and clinical signs in the hamster [23,24]. Intranasal inoculation performed in these studies was performed slowly, allowing each drop of inoculum to enter the nasal cavity prior to the next drop being administered, reducing the likelihood of the inoculum being swallowed. Therefore, these conflicting reports combined with the method in which the inoculum was administered make it unlikely that the increased clinical disease and weight loss in the hamsters receiving the higher volume of inoculum observed here is due to infection via the gastrointestinal tract. These data suggest that a larger volume (200 µL, 100 µL in each nare) of intranasal inoculum facilitates an extended viral distribution, faster onset and increased severity of disease. We theorise that the delayed onset of disease, as a result of inoculation with the smaller volume (50 µL, 25 µL in each nare), is due to the initial localised replication of the virus in the upper respiratory tract with later migration towards the lung, at which point weight loss and clinical signs are observed. The effect of inoculum volume on disease outcome is not novel and previous findings with intranasal administration of influenza confirm this. Increased morbidity was observed when mice were administered larger (50 µL or 35 µL) volumes of inoculum intranasally compared to those receiving a smaller volume (25 µL) despite identical doses being given [25]. Miller et al. theorised that the physiological differences in the microarchitecture of the upper and lower respiratory tract contributed to the altered outcome of disease which is likely a contributing factor here too. Ferrets administered with larger volumes of influenza inoculum experienced increased severity of clinical disease and pathology, and it was noted that the larger volume of inoculum was optimal for uniform delivery of the virus to the lower respiratory tract [21]. Cook et al. also reported differences in clinical disease outcomes in mice infected with the same titre of pneumovirus in 10 µL, 25 µL and 50 µL. The severity and duration of the disease were reduced when lowering the volume from 50 µL to 25 µL, and no disease was detected at the 10 µL volume [26]. Despite the reduced severity of disease seen in hamsters receiving the 50 µL inoculum, little difference was seen in viral shedding in the URT compared to the 200 µL inoculated hamsters by qPCR analysis or live viral titre. Reducing the volume of the inoculation did not appear to affect shedding. However, shedding appeared to remain similar between hamsters inoculated with the standard dose and those receiving a reduced infectious dose, suggesting that viral loads measured by PCR lack sensitivity to detect alterations in shedding. Viral load qPCR in the lung also demonstrated no difference between the two inoculum volumes at the post-mortem at 7 DPC. This is particularly interesting as the viral load measured by in situ hybridisation showed significantly lower RNA levels in the lungs of the 50 µL inoculated hamsters. This apparent mismatch between results may be due to limitations of the qPCR assay or the in situ hybridisation method and warrants further investigation. Sub-genomic RNA has been suggested as a way to determine actively replicating viruses as the leader sequence is believed to only be added to replicating RNA [27,28]. The absolute mechanism of coronavirus replication and the involvement of the sub-genomic RNA remains unresolved [29,30]. A very strong relationship between total viral RNA and sub-genomic RNA was identified, with sub-genomic RNA titre forming an almost 1000-fold lower titre subpopulation of total viral RNA. This indicates a simple scalar relationship between them. Further, live viral titres were undetectable two days after challenge, while sub-genomic RNA remained detected until the end of the study at seven days post-challenge. Sub-genomic PCR does not provide a specific indicator of live virus titres consistent with other studies [31,32] and provides no additional information beyond that of the total genomic RNA titre. The procedural details of the inoculation are likely to enhance the chance of inhalation into the lung parenchyma. 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--- title: 'Laparoscopic Sleeve Gastrectomy versus Laparoscopic Roux-en-Y Gastric Bypass: An Analysis of Weight Loss Using a Multilevel Mixed-Effects Linear Model' authors: - Camille Pouchucq - Olivier Dejardin - Véronique Bouvier - Adrien Lee Bion - Véronique Savey - Guy Launoy - Benjamin Menahem - Arnaud Alves journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051768 doi: 10.3390/jcm12062132 license: CC BY 4.0 --- # Laparoscopic Sleeve Gastrectomy versus Laparoscopic Roux-en-Y Gastric Bypass: An Analysis of Weight Loss Using a Multilevel Mixed-Effects Linear Model ## Abstract Background: Regarding weight loss outcomes, the results published after laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y (LRYGB) are conflicting. At this time, no clear evidence exists that outcomes from LSG are similar to those for LRYGB. The main objective of this study was to compare the percent of total weight loss (%TWL) between LRYGB and LSG over the first 2 years using a multilevel mixed-effects linear regression. Methods: Data were collected from a prospectively maintained database of patients who underwent primary laparoscopic bariatric surgery from January 2016 to December 2017 at a French accredited bariatric center. The medical records of 435 consecutive patients were analyzed. % TWL was calculated at each follow-up surgical consultation and used as a repeated outcome variable in our models to assess the long-term %TWL. Due to this hierarchical structure of the data (%TWL at each visit = level 1) within patients (level 2), a multilevel linear regression adjusted for age, sex, preoperative BMI and comorbidities was used. Results: Among the medical records of 435 consecutive patients included, 266 patients underwent LRYGB and 169 underwent LSG. The average %TWL at 2 years was $31.7\%$ for the LRYGB group and $25.8\%$ for the LSG group. The final multivariate model showed that, compared with LRYGB, LSG was associated with a decreased %TWL at over 2 years of follow-up (β: −4.01; CI$95\%$: −5.47 à −2.54; p ≤ 0.001). Conclusion: This observational study suggests that compared with LRYGB, LSG was associated with a decreased %TWL at 2 years using a multilevel model. Further studies are required to confirm the results observed with this statistical model. ## 1. Introduction The last 30 years have brought a dramatic increase in the worldwide prevalence of obesity, causing considerable social and economic burden [1,2,3]. There is strong evidence that bariatric surgery, compared with medical treatment alone, results in substantial and long-term weight loss in morbidly obese patients [4,5,6]. Laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y gastric bypass (LRYGB) are currently the two most frequently performed procedures in bariatric surgery, and weight loss is considered to be the primary indicator of its success [7,8]. At least 70 randomized controlled trials (RCTs) or observational studies (OS) have directly compared LRYGB and LSG [9,10,11,12,13,14,15,16]. While the majority of RCTs have shown that patients undergoing LRYGB and LSG experience similar weight loss [13,14,16,17], OS have shown that LRYGB patients achieve greater weight loss than LSG patients [9,11]. Furthermore, in daily practice, the choice of procedure is based on a shared decision-making process [18] (i.e., patients’ own preferences and values, comorbidities, intraoperative findings, and surgeons’ expertise and habits) that may not be measured in RCTs; hence, there is interest in complementary observational studies. Finally, traditional approaches to assess long-term weight loss in bariatric surgery have relied on a single time-point analysis, either through bivariate or regression models. However, this analysis requires, from a statistical point of view, to take into account the presence of repeated weight measurements for the same individual over time. To preserve this hierarchical structure, multilevel mixed-effects linear models should be used to assess weight loss over time [19]. To our knowledge, no superiority in terms of long-term weight loss efficacy has been demonstrated between LSG and LRYGB, so there is no consensus. The main objective was to compare the %TWL between LRYGB and LSG over the first 2 years using a multilevel mixed-effects linear regression. ## 2.1. Study Design The medical records of 435 consecutive patients who underwent laparoscopic bariatric surgery between January 2016 to December 2017 were analyzed. The data were recorded prospectively. The inclusion criteria for this survey specified patients older than 18 years who underwent, at our specialized and accredited bariatric center, either LRYGB or LSG as a primary operation and had one or more weight measurements obtained during postoperative visits. All indications for bariatric surgery were assessed according to the International Federation for the Surgery of Obesity and Metabolic Disorders criteria [7,8] and endorsed in an interdisciplinary consensus meeting. ## 2.2. Surgical Technique All procedures were standardized to be performed in the same way at our center. “ The decision to perform LSG or RYGB took into account both the patient’s choice, maximum preoperative BMI and related comorbidities as well as the proposal of the multidisciplinary consultation meeting”. The surgical techniques used for this study were as previously described in the literature [20,21,22]. ## 2.3. Data Collection All relevant data included patient features (sex, age and comorbidities), pre- (surgery weight) and postoperative biometric values [weight, height, body mass index (BMI) and percentage of total weight loss (%TWL)]. The %TWL was calculated according to the following formula: [(surgery weight-follow-up weight)/surgery weight] × 100. % TWL was calculated at each follow-up surgical consultation and used as a repeated outcome variable in our models to assess the long-term %TWL. All patients were assessed as part of a routine surgical follow-up program in the outpatient clinic and were seen on a regular schedule at approximately 1, 3, 6, 12, 18 and 24 months postoperatively. The exact day of each consultation was retrospectively collected for all patients. Thus, a delay corresponding to the difference between the day of the surgery and the day of the consultation was calculated. ## 2.4. Statistical Analyses Chi-square and Fisher’s exact tests were used to identify statistically significant differences for descriptive comparisons between both groups. $p \leq 0.05$ was defined as statistically significant. Efficacy in terms of weight loss was assessed using %TWL. The %TWL readings at each postoperative follow-up consultation for the same patient corresponded to the use of repeated data. Due to this hierarchical structure of the data (%TWL at each visit = level 1) within patients (level 2, $$n = 435$$), a multilevel mixed-effects linear regression adjusted for age, sex, preoperative BMI and comorbidities was used. Subsequently, the continuous variable %TWL was introduced into the model as the most flexible form of a three-node restricted cubic spline (Mkspline in STATA). $$p \leq 0.05$$ was considered significant in the final model. All statistical analyses were performed with Stata/SE version 13 (StataCorp, College Station, TX, USA). This study was approved by the local medical ethics committee and was declared to the CNIL (2204611v0). The requirement for patient consent was waived owing to the retrospective nature of the study. ## 3.1. Demographic and Clinical Characteristics Between January 2016 and December 2017, 266 patients underwent LRYGB and 169 underwent LSG. Both groups were similar regarding age and obesity-related comorbidities (Table 1). The LRYGB group had a significantly higher prevalence of females. Conversely, the LSG group was significantly associated with both higher preoperative biometric values and ASA score. Both groups were similar regarding age and obesity-related comorbidities. ## 3.2. Weight Loss The average %TWL at 2 years was $31.7\%$ for the LRYGB group and $25.8\%$ for the LSG group. Negative β coefficients indicate lower long-term %TWL. Schematically, a significant variable with a negative β means that the patient lost less weight. ## 3.2.1. Two Years %TWL The final multivariate model shows that compared with LRYGB, LSG was associated with a decreased %TWL at over 2 years of follow-up (β: −4.01; IC $95\%$: −5.47 à −2.54; p ≤ 0.001) (Table 2). ## 3.2.2. Weight Loss Curve To test the hypothesis of linearity due to the inclusion of the %TWL in a continuous form, we used a four-node cubic spline model. Using a spline (Figure 1), we found that after the two procedures, the patients routinely experienced weight loss in a gradual fashion during the first 2 years. For each procedure, the mean %TWL peaked during the first year (approximately 16 months) after surgery and then fell within the normal distribution, similar to a bell curve. ## 4. Discussion Using a multivariate linear regression in our study sample, we found that LSG compared with LRYGB was associated with a decrease in %TWL at 2 years of follow-up. These findings are compelling because the majority of current studies (including RCTs) have reported little or no difference in short-term weight loss between LRYGB and LSG [13,14,15,23,24,25,26,27,28,29]. A subset of other studies have found that LRYGB results in greater weight loss than LSG at 1 to 4 years of follow-up [9,10,12,30,31,32,33]. Patients of our survey with LSG were characterized by higher preoperative BMI as compared to those with RYGB, while baseline obesity-related comorbidities were similar. Importantly, even after adjusting for age, sex and preoperative biometric values, LSG remained associated with lower %TWL than LRYGB. A number of RCTs have been devoted to compare weight loss outcomes between LSG and LRYGB, most of which have shown similar weight loss between the two techniques [13,14,34]. In a recent meta-analysis, including nine RCTs, Han and al. reported no significant difference in terms of %PEEP between the two procedures [−0.16 ($95\%$ CI: −0.52 to 0.19; $$p \leq 0.36$$)]. This conclusion is supported by two previous RCTs, with a follow-up over 5 years greater than $80\%$ [13,14]. Even though they are randomized trials, these results should be interpreted with caution due to the limited number of patients included in each arm (between 20 and 100 patients) and the short follow-up time that has been traditionally reported [34,35,36]. Conversely, observational studies generally show greater weight loss in patients who received RYGB [9,11,12,37]. Thus, the multicenter study, PCORnet Cohort Study, compared the weight results in 32,208 patients who received RYGB against 29,693 patients who received SG [11]. The results show an average total weight loss at 5 years of $25.5\%$ ($95\%$ CI, 25.1–$25.9\%$) for RYGB versus $18.8\%$ ($95\%$ CI, 18.0–$19.6\%$) for LSG. That is a difference of $6.7\%$ in terms of %PPT ($95\%$ CI, 5.8 to 7.7; $p \leq 0.001$) in favor of RYGB. Overall, the results of observational studies suggest that the difference observed between the two techniques is greater in a non-randomized setting and may be the consequence of unmeasured differences. Indeed, in daily practice, the choice of procedure is based on a process of shared decisions taking into account preoperatively the preferences of the patient, his comorbidities, the habits and the expertise of the surgeon and/or his center but also intraoperative findings [18]. It is therefore a set of essential factors that cannot be taken into account during an RCT; hence, the interest of complementary observational studies. Today, one of the difficulties in synthesizing the literature on the subject is based on the lack of uniformity in the analysis tools used. Most experts agree that weight loss and gain should be expressed as a percentage of preoperative weight (which also has the advantage of being easy to use in clinical practice) [38,39]. However, primary studies have evaluated weight loss in other forms, in particular using the %PEP, the average loss of BMI, the weight lost or the percentage loss of excess BMI (%PE-BMI) [16]. Finally, traditional approaches to assess long-term weight loss have relied on a single time-point analysis, either through bivariate models or through regression models that do not respect the fundamental assumption of independence of observations [40]. Very few studies have applied statistical methods for the analysis of repeated measures [11,13,14]. The use of models that did not take this statistical specificity into account may have led to erroneous results. Furthermore, several studies gave results about excess weight loss after bariatric surgery without multilevel analyses [13,14,41,42]. Thus, statistical analyses were performed with logistic regression model or variance analysis. Although the data recording is done prospectively, it is a single-center retrospective study with all its inherent limitations. It is also an observational study, which risks unobserved confounding. Finally, the resolution of comorbidities could not be assessed due to a lack of available data, even though this is a parameter for determining the effectiveness of bariatric surgery. Our results must also be interpreted with caution due to the lack of data on long-term complications and quality of life, which are fundamental parameters to be taken into consideration. Similarly, the problem of loss to follow-up patients cannot be excluded, as reported in a recent review of the literature [43,44,45]. However, the study has also several strengths. Our cohort benefited from a relatively high number of patients ($$n = 435$$) and a low rate of loss to follow-up 2 years after surgery associated with a satisfactory 2-year follow-up rate (approximately $70\%$) compared to literature data [13,14,37,43]. This can be explained in particular by standardized patient monitoring within our team for several years; this is done both on a regular basis and over the long term. Indeed, the follow-up of patients has been standardized within our team for several years [20,21,22]. Finally, we applied a multilevel mixed-effects linear model. To our knowledge, only three studies previously considered recorded weights as repeated measures by applying an adapted statistical method with conflicting results. The SLEEVEPASS study was considered to have failed to meet the equivalence criteria set out in the study design, whereas LRYGB was significantly associated with greater excess weight loss at 5 years [13]. The SM-BOSS found no differences in the percentage of body mass index loss, and slight differences in the 5-year body mass index (approximately 1 kg/m2) were found between studies [14]. Conversely, the PCORnet Cohort Study, a large multicenter observational study, found that patients lost more weight with LRYGB than with LSG at 1, 3 and 5 years [36]. The main strengths of our study are based, in our opinion, on the application of a statistical model taking into account the presence of longitudinal data, on the use of recommended monitoring tools (%PPT in particular) [38,39] and on a comprehensive analysis of the literature. ## 5. Conclusions In this observational study reflecting daily practice, we found that the use of LSG compared with the use of LRYGB was associated with a decreased %TWL at 2 years using a multivariate linear regression. 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--- title: Nutritional Status and Frailty Improvement through Senior-Friendly Diet among Community-Dwelling Older Adults in South Korea authors: - Hye-Ri Shin - Young-Sun Kim - Yoo-Kyung Park - Seul-Ki Koo - Woo-Hyun Son - Jae-Won Han - Eun-Ha Son - Hae-Jin Kang - Kyeong-Hee Choi - Jin-Soo Han - Hyun-Sun Lee - Hee-Sook Lim journal: Nutrients year: 2023 pmcid: PMC10051771 doi: 10.3390/nu15061381 license: CC BY 4.0 --- # Nutritional Status and Frailty Improvement through Senior-Friendly Diet among Community-Dwelling Older Adults in South Korea ## Abstract Considering that Korea’s aging population is rapidly increasing, health serves as an indicator of older adults’ quality of life, and dietary life directly affects their health. For health maintenance and improvement, preventive healthcare measures including safe food selection and nutritional supply are needed. This study aimed to evaluate the effect of senior-friendly diet on nutrition and health status improvement in older adults receiving community care. A total of 180 older adults were analyzed, with 154 and 26 in the senior-friendly diet intervention group and the general diet group, respectively. Surveys, blood tests, and frailty evaluations were conducted before and after the study. After 5 months of intervention, the blood status, nutrient intake, and frailty level were evaluated. The participants’ mean age was 82.7 years, and $89.4\%$ of them were living alone. In both groups, energy, protein, vitamin A, vitamin D, vitamin C, calcium, and magnesium intake were insufficient initially but generally improved after the intervention. Especially in the intervention group, energy, protein, vitamin D, vitamin C, and folic acid intake significantly increased. The frailty level also slightly improved, and the malnutrition rate was reduced. Even after the passage of time, the improvement effect size significantly differed between the groups. Therefore, resolving and supporting meals corresponding to the physiological needs of the older adults has a great impact on improving their quality of life, and such special consideration is a reasonable way to respond to a super-aged society. ## 1. Introduction Owing to the improvement of living quality and the development of medical technology as a result of economic growth, the average life expectancy in South Korea has increased; thus, population aging is becoming more pronounced [1]. In 2020, approximately $16\%$ of the total population in Korea was aged 65 years or older, and this percentage is estimated to increase to $21\%$ by 2025, thereby entering a super-aged society [2]. As one grows older, their activity level and basal metabolic rate decreases [3]. Masticatory-swallowing and digestive abilities also decline, so food intake decreases and the burden of eating increases [4,5]. Furthermore, grocery shopping and meal preparation have become difficult, leading to malnutrition and nutritional imbalance [4,5]. Poor dietary management in old age leads to various diseases, including lifestyle-related diseases and simple malnutrition, resulting in weakness and eventually, a significant decrease in the quality of life [6]. According to the 2014 Survey on the Elderly results in Korea, approximately half of the older adults in Korea had an “adequate level” of nutritional management; however, $29\%$ required attention in nutrition management, and $20\%$ required improvement in nutrition management [7]. Therefore, managing older adults’ diets in ways that are suitable for a good level of self-reliance and health is crucial to help older adults lead a healthy daily life. Accordingly, various policy studies and implementations are being conducted to promote proper welfare for older adults in Korea. “ Community integrated care” (community care) is a project implemented by the Ministry of Health and Welfare in June 2019, and is a Korean-style service that provides integrated services such as housing, health care, nursing care, and care according to the individual needs of adults aging in place [8]. As part of the community care project, meal delivery services are provided for older adults at home through the “Elderly Health Function Recovery Support Project” and “Customized Nutritious Food Support Project.” In the Welfare of the Elderly Act, the “older adults at home” is defined as an older adult leading a daily life at home [8,9]. Depending on the degree of independent living and health level, these older adults are classified into those who can live independently, those who can live independently but are not healthy, those who cannot live independently and have difficulty moving, and those who cannot live independently and live in long-term care facilities [10]. Usually, meal delivery services are mainly for older adults at home who cannot live independently but are not healthy and those who cannot live independently and have difficulty moving around [11]. Meanwhile, according to the community care project, nutritional support programs are being implemented for older adults at home by local governments in South Korea, but meal providers rarely identify the nutritional status of the target and reflect it in program operation. To increase the effectiveness of the nutritional support program, healthcare providers need to evaluate the nutritional status of older adults first, develop and promote programs that select individuals according to the evaluated nutritional status, and provide customized support for each individual. In Korea, the Ministry of Agriculture, Food, and Rural Affairs established an age-friendly industry standard in December 2017 which has been used as a voluntary labeling system for food industries [12]. Furthermore, Korea’s senior-friendly food standard (KS H 4897) was introduced, and is divided into stages based on physical properties; it also includes minimum quality standards for nutritional components in consideration of nutritional imbalance, which is common among older adults [13]. The size of Korea’s senior-friendly food industry ranks second among all industries, and is reportedly 17.6 billion won in 20 years [14]. Although the standard policy for senior-friendly food is being continuously expanded, conducting practical field application evaluations and empirical studies is necessary to secure scientific basis data to revitalize the industry and enhance competitiveness [15]. Therefore, this study aimed to scientifically verify whether nutritional intake and clinical indicators were affected by the development of a diet in which senior-friendly foods were provided to older adults. ## 2.1. Participants This study targeted older adults living at home who were receiving community care. Considering the lack of an identical model at home and abroad, we reviewed the most similar model and calculated the number of participants [16]. The rate of change from malnutrition to normal through malnutrition management was approximately $30\%$, and the conversion rate from malnutrition to normal was assumed when nutrition was not managed. The ratio of the intervention and control groups was assumed to be 5 according to a type I error of $5\%$ and a power of $90\%$. The calculated final sample size was 150 in the intervention group and 30 in the control group; when a dropout rate of $9\%$ was applied, the size was 165 and 33, respectively. The inclusion criteria were adults aged 65 years or older and those who agreed with the researcher and their guardians. Those with impaired oral intake, cognitive impairment (e.g., dementia), and nonpermanent residence were excluded. We initially recruited 204 participants and randomly assigned them to the intervention and control groups. At the end of the study, 24 were excluded because of survey refusal ($$n = 20$$), death ($$n = 1$$), and hospitalizations ($$n = 3$$). Thus, the study ended with a total of 180 participants (intervention group: 154, control group: 26). ## 2.2. Meal Provision Our participants were vulnerable; thus, they were cared for and given lunch boxes every day. Conventional lunch boxes have been provided with nutritious values suitable for older adults. Accordingly, the control group was given the existing meal, while the intervention group was given a meal consisting of senior-friendly foods. Senior-friendly foods in Korea refer to foods manufactured/processed by adjusting their physical properties for easy digestion or by adjusting its nutritional content to help the older adults eat or digest food [17,18]. With the enactment of the Aging-Friendly Industry Promotion Act, products with high convenience and safety in senior-friendly foods are designated as excellent foods [18,19]. To balance the diet of only two groups, we replaced the senior-friendly foods with applicable dishes and reviewed food groups and nutritional values to ensure no significant differences. Meals were provided to all participants for 5 months, and a total of 64 senior-friendly foods were applied to the diet. ## 2.3. Effective Indicators The primary endpoints used to verify effectiveness were frailty and blood parameters, and the secondary endpoints were nutritional status and nutrient intake status. Frailty can be evaluated in various ways, but a method of evaluating it through a physical function test is recently recommended, that is, the Short Physical Performance Battery (SPPB) [20,21]. SPPB evaluates physical function, frailty, sarcopenia, and fall risk in various clinical situations and predicts health risks that may occur in the future. In particular, it measures the static balance test in three postures, the gait speed test, and the time to get up from a chair five times [22]. In this study, an electronic SPPB (eSPPB) meter was used. The total score is 12 points; a score of 6 or less was considered disability and frailty, and a score of 7–9 was considered prefrailty [20,21]. The participants’ systolic blood pressure, diastolic blood pressure, and grip strength were measured twice using a sphygmomanometer and a grip dynamometer; then, the average value was calculated. Blood was also collected to check the levels of blood glucose, c-reactive protein, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride, hemoglobin, and hematocrit through an analyzer. Blood pressure, glucose, lipid status, and anemia status were then evaluated. The nutritional status was investigated using the Mini Nutritional Assessment (MNA®) and evaluated as either a good nutritional status, at risk for malnutrition, or malnutrition [23]. The nutrient intake status was evaluated using CAN PRO 5.0 (Computer Aided Nutritional Analysis Program for Professionals, The Korean Nutrition Society, Seoul, Korea) after examining food intake for 2 days using the 24 h recall method. In addition, age, sex, activity level, family status, disease history, oral condition, swallowing condition, quality of life, and body mass index (BMI) were measured as general variables. We used the oral health impact index (OHIP-14) tool for the oral condition; the total response score is between 14 and 17 points [24]. The higher the total score, the lower the oral-health-related quality of life. For the swallowing status, we used dysphagia handicap index (DHI), and a total of 25 items were surveyed [25]. The higher the score, the more severe the swallowing disorder. All indicators were compared and evaluated before and after the intervention. ## 2.4. Nutritional Education Program Ten nutrition education programs were conducted for the participants’ smooth research progress and investigation, promotion of compliance, and dietary life management. A nutrition expert visited the participants’ house twice a month and provided 1:1 personal nutrition education and counseling. The program mainly consists of topics such as dietary guidelines for the older adults, nutritional management methods for geriatric diseases, introduction of senior-friendly foods, food purchasing, and hygienic and safe meals. Both the control and intervention groups were equally conducted. ## 2.5. Statistics Analysis We used linear mixed models for endpoint indicators (MNA, energy, protein, eSPPB, hand grip, quality of life, blood pressure, cholesterol, triglyceride, hemoglobin, and hematocrit) to perform between-group comparisons by an intention-to-treat approach. The linear mixed model included group, time, and group-by-time interaction. Each group’s data presented changes from baseline to 5 months, and they were determined by the model’s time-by-group interaction coefficients. Comparisons of the intervention and control groups were analyzed using t-test for continuous data and χ2 for categorical data. All comparisons were two-sided, and $p \leq 0.05$ was considered statistically significant. All statistical data were analyzed using the STATA 17.0 software. ## 3.1. General Characteristics of the Participants The mean age was 82.7 years, and those over 85 years old accounted for $40.6\%$ (Table 1). Females numbered more than males ($62.8\%$). As for the active state, the rate of independent living was $88.3\%$, and single-person households accounted for $89.4\%$. Regarding disease history, cardiovascular diseases such as hypertension and dyslipidemia were the highest ($66.7\%$), and the polypharmacy rate (≥3 drugs) was $80.6\%$, as observed in most of the participants with chronic diseases. The mean BMI was 23.5 kg/m2. Before the study, the baseline characteristics were not significantly different between the two groups. ## 3.2. Nutritional Status and Dietary Quality Table 2 and Figure 1 shows the results of analyzing the nutritional status and nutrient intake. In assessing nutritional status through MNA, the proportion of malnutrition (risk of malnutrition and malnutrition) decreased from $53.9\%$ to $50.0\%$ in the control group, but this result was not significant. In the intervention group, it was significantly reduced from $52.6\%$ to $42.9\%$. As a result of nutrient intake analysis, the intervention group’s calorie intake increased by about 200 kcal and protein by 10 g, and most nutrient intake tended to increase as the overall meal amount increased. In the control group, there was no change in calories and protein, but carbohydrates decreased, and fat intake increased. Figure 1 shows the nutrient recommendation value as $100\%$ and the percentage of satisfaction compared to the standard as a graph. Energy intake in the intervention group increased from $80\%$ to $92.7\%$ compared with the recommended amount for older adults in the Korean nutrient intake standards. In addition, protein exceeded $100\%$, and the intake generally increased after the intervention period. Conversely, nutrients that remained less than $100\%$ were vitamin A, vitamin D, vitamin C, niacin, calcium, and magnesium. The control group’s intake was at a more vulnerable level, and energy was lowered from $83.8\%$ to $79.6\%$. ## 3.3. Improving Physical Function and Blood Test The baseline results of eSPPB were not significantly different between the intervention and control groups, and the mean total score indicated frailty. Specifically, physical function tended to decrease over time in the control group, and the frailty and prefrailty ratios significantly improved in the intervention group. In the blood test, the total cholesterol and triglyceride levels of the intervention group significantly decresed, while the hemoglobin level of the control group significantly decreased (Table 3). ## 3.4. Analysis of Differences in Indicators for Each Group Table 4 shows the results of analyzing the significant differences between groups using the double-difference analysis method. The nutritional status evaluation score, energy intake, protein intake, eSPPB score, grip strength, hemoglobin, and hematocrit were the indices showing significant differences between the groups. In the control group, most of the indicators tended to decline over time, whereas in the intervention group, the nutritional status and functional health status improved. However, hemoglobin and hematocrit decreased in both groups, but the decrease in the control group was significantly greater. ## 4. Discussion South Korea ranks first in the world in the rate of aging, with a life expectancy of 86.6 years among Korean females [26]. In this study, the mean age of our participants was 82.7 years, and $40.6\%$ of them were aged 85 years or older, indicating a high level. In addition, females accounted for $62.8\%$. Thus, Korea’s actual population aging rate reached a very high level compared with the data obtained in this study. Furthermore, single-person households accounted for $89.4\%$, which is approximately 4.5 times higher than the $19.8\%$ in the 2020 Korea Elderly Survey [27]. Our study population had a large proportion of older adults living alone, suggesting that the proportion of those living alone in South Korea is generally higher than the proportion of those living with other household members. In the 2020 National Health Statistics, more than half of the older adults aged 65 years or older had hypertension, and dyslipidemia accounted for $65.2\%$ and $75.0\%$ [28]. In addition, more than $80.6\%$ of our participants took three or more drugs, consistent with the study by M.S.K et al. The total mean score of swallowing disorders was 17.4 points. This result is similar to that of a previous study by Kim et al. [ 29], that is, 17.1 points [29], which is judged as the mean swallowing disorder score for Korean older adults. Moreover, the mean BMI value was 23.5 kg/m2, which corresponds to overweight, similar to the study result of P.J et al. [ 30]. Among the participants, the proportion of obese was high at $31.7\%$ on average, and the proportion of underweight was relatively low. MNA, an index for assessing nutritional status, is a simple, useful, and reliable tool for older adults. This indicator can be divided into normal, at risk of malnutrition, and malnutrition, and effective nutritional interventions can be obtained. More than half of our participants were at risk of malnutrition or already had malnutrition. In an international study by C and G et al. [ 31,32], approximately $61\%$ of older adults aged 65 years or older were malnourished, similar to our study. However, our study revealed that the number of participants with malnutrition decreased in both groups after the intervention. In particular, a significant decrease in the intervention group suggests an effect of improvement after provision of nutrition education and senior-friendly diet. Senior-friendly excellent foods are customized products manufactured by adjusting the hardness, viscosity, shape, and ingredients of meals to facilitate older adults’ intake, nutrition, digestion, and absorption. Food intake starts with the teeth, followed by the gums and the tongue. Currently, 113 products have been selected as senior-friendly foods [33], and various aspects such as chewability level food groups should be developed in the future. According to the 2020 Nutrient Intake Standards for Koreans, the nutrient intake standards are aimed at healthy individuals and groups to maintain and improve their health, reduce the risk of chronic diseases related to diet, and ultimately improve their healthy lifespan. Energy is set at 1900 and 1500 Kcal for males and females [34], respectively, as well as 130 g of carbohydrates and 60 g of protein for males and 50 g of both for females. Compared with this criterion, the pre-energy intake in our study was 1360.7 Kcal in the intervention group and 1423.8 Kcal in the control group; regarding nutrients, 227.5 and 236.5 g of carbohydrates and 49.9 and 51.6 g of protein were consumed by the intervention and control groups, respectively. This result is similar to the results of previous studies [35,36] investigating vulnerable older adults with reduced mobility. However, as a result of applying the senior-friendly diet, energy and protein significantly improved in the intervention group. If the intake rate was set at $100\%$ according to the Korean nutrient intake standard, in the intervention group, energy intake increased from $80\%$ to $92.7\%$, protein exceeded $100\%$, and intake generally increased after the intervention period. However, the intake rate of vitamin A, vitamin D, vitamin C, niacin, calcium, and magnesium remained below $100\%$. Meanwhile, the intake of the control group was at a more vulnerable level. However, it is noteworthy that the intervention group had a significant increase in energy intake due to an increase in protein and fat intake, and a significant increase in sodium intake. The main foods of protein are meat, fish, tofu, eggs, etc., and many of the developed senior-friendly foods are composed of these foods as raw materials. As is known, these foods contain both protein and fat as major nutrients, so it is judged that the energy contribution rate for them has no choice but to go up. Excessive sodium intake can aggravate chronic diseases such as diabetes and hypertension, and inappropriate fat intake can lead to indigestion and an imbalance in nutrient intake. In order to meet the nutritional needs of the elderly, it is necessary to increase the amount of food, have a balanced diet, and supplement insufficient nutrients; however, on the contrary, monitoring is necessary to prevent inadequate nutritional intake. Senior-friendly foods used for meals are actually reflected in the nutrient intake; therefore, providing age-friendly foods to meals for older adults with difficulty eating should be implemented. According to the eSPPB analysis, the preliminary results of the two groups showed no difference, and the average score indicated frailty. The control group tended to have physical function decline over time; conversely, the frailty and total frailty rates of the intervention group significantly improved. The eSPPB tool, which has been verified to be reliable in various studies, can be measured in four ways: Robust, Prefrailty, Frailty, and Disability. Although eSPPB can be accurately and easily measured, installing it takes a long time, and evaluating older adults with limited activities can be difficult. Compared with previous studies such as that of H.W.J. [37], our participants were relatively more vulnerable, possibly because of the relatively high rate of frailty resulting from a high proportion of super-aged people in this study and the fact that they were receiving community care services. Community care provides housing, medical care, nursing care, and care services so that older adults can experience a healthy state while they age at home, thereby relieving widespread care anxiety and improving their quality of life in the face of a super-aged society. It is a policy that can be drastically improved. Actively supporting the vitalization of these policies and appropriate services for older adults is necessary. Furthermore, after the intervention, the total cholesterol, LDL-C, HDL-C, triglyceride, and hemoglobin levels were 143.4 mg/dL, 71.6 mg/dL, 48.8 mg/dL, 140.88 mg/dL, and 12.3 g/dL in the intervention group, respectively. Between groups, the indicator showing the most significant difference was the nutritional status evaluation score, followed by energy intake, protein intake, eSPPB score, grip strength, hemoglobin, and hematocrit. Most of the indicators in the control group tended to decrease or worsen over time, whereas nutritional and functional health status improved in the intervention group. Factors influencing the prevention of sarcopenia include exercise [38] and nutritional intake [39], and among dietary factors, energy [40,41], protein [42,43], and antioxidant nutrients [44] are especially important for sarcopenia and reported to be related. The recovery of energy is related to muscle mass over long periods of time, and the potential for energy distribution has been found to combine the electrical phases, despite of course not insignificant supplies. Therefore, there is a need to recover a fixed amount of energy and power to maintain adult gym muscle mass. The improvement in nutritional status or frailty indicators in this study was considered to be due to the complex application of an increase in diet intake, which was a problem, eventually leading to an increase in nutrients intake, and a management education program to maintain. In addition, education should be developed into multi-dimensional education programs such as nutrition management, frailty, chronic disease management, and oral hygiene. Providing a diet using senior-friendly excellent foods significantly improved frailty, nutritional status, nutrient intake, and blood tests. We also observed the effectiveness of various health indicators for older adults in improving and developing various systems for the expansion of the senior-friendly food industry in Korea. Many difficulties were encountered during the process of conducting research on a large number of older adults who were receiving government care. Special meals for older adults are absolutely necessary and must be adopted according to the circumstances of each country. The improvement of various health conditions when using senior-friendly foods leads to medical cost reduction. For instance, the decrease in blood glucose will result in saving KRW 610,000 per person annually and KRW 706.8 billion for older adults aged 65 years or older by our report. We believe that consuming a precise and complete diet by supplementing foods that can fill up the lack of nutrients is essential, considering that most of the foods are semiprepared, although senior-friendly foods should be easy to ingest. 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--- title: A New Productive Approach and Formulative Optimization for Curcumin Nanoliposomal Delivery Systems authors: - Raffaella De Piano - Diego Caccavo - Gaetano Lamberti - Katrien Remaut - Hanne Seynaeve - Anna Angela Barba journal: Pharmaceutics year: 2023 pmcid: PMC10051773 doi: 10.3390/pharmaceutics15030959 license: CC BY 4.0 --- # A New Productive Approach and Formulative Optimization for Curcumin Nanoliposomal Delivery Systems ## Abstract The use of natural resources and the enhancing of technologies are outlining the strategies of modern scientific-technological research for sustainable health products manufacturing. In this context, the novel simil-microfluidic technology, a mild production methodology, is exploited to produce liposomal curcumin as potential powerful dosage system for cancer therapies and for nutraceutical purposes. Through simil-microfluidic technology, based on interdiffusion phenomena of a lipid-ethanol phase in an aqueous flow, massive productions of liposomes at nanometric scale can be obtained. In this work, studies on liposomal production with useful curcumin loads were performed. In particular, process issues (curcumin aggregations) were elucidated and formulation optimization for curcumin load was performed. The main achieved result has been the definition of operative conditions for nanoliposomal curcumin production with interesting loads and encapsulation efficiencies. ## 1. Introduction In recent years, the demand of dietary supplements such as phytomedicines and vegetal ingredients from nutraceutical industries has grown enormously. This depends upon the rising worldwide community request of natural, safe, and healthy bioactive products. The global nutraceutical market of botanical drugs, based on traditional herbal medicine, is undergoing a huge expansion hand in hand with the development of new technologies. The final goal is focused on the realization of more highly bioavailable dosage forms of nutrients and therapeutics that are able to improve people health, longevity, and quality of life [1,2,3,4]. Thus, this dual aspect, namely the use of natural resources for healthy benefits and updating of technologies, is influencing the strategies of modern scientific-technological research. Research responds to the goal of the sustainable development objectives at the center of the current socio-economic policy promoted by the United Nations as a strategy “to achieve a better and more sustainable future for all” [5]. In this context, natural resources, due to their variety and peculiar richness in secondary metabolites, are currently objects of scientific and industrial interest. Among the countless vegetal species with formidable biological features, curcumin (CUR), the main components of curcuminoids, polyphenolic compounds found in the rhizomes of turmeric (Curcuma longa, Zingiberaceae family), is one of the natural compounds that have been extensively studied from a pharmacological perspective, and is well known as a spice and as a dye [6,7]. In the latest scientific literature, more than three thousand papers (source: WOS core collection, curcumin as keyword, years 2022–2023) testify the great interest in this natural compound. The reasons for this considerable attention are the ascertained therapeutic efficacy in arthritis, liver, and neurodegenerative diseases; in several types of cancers, obesity, wound-healing, anti-inflammatory treatments; and as an antibacterial, antioxidant, antispasmodic, and anticoagulant agent [8,9,10]. In addition, recently, studies on CUR’s preventive effects on extensive immunosuppression are ongoing to investigate therapeutic potential against SARS-CoV-2 (COVID-19) [6]. In Figure 1, the pharmacology benefits of curcumin are summarized. Despite its beneficial properties, CUR uses in clinical applications are strongly limited due its high hydrophobicity (0.125 mg/L, [9]). This poor solubility in aqueous media results in low bioavailability into plasma and living target tissues. Curcumin also has rapid metabolism, which significantly affects its half-life and bioavailability. Moreover, as for most the antioxidant agents, curcumin is unstable and quickly degraded through oxidative processes [7] during manufacturing and storage [9]. In this regard, to overcome curcumin dosage limitations, evolutions of nanotechnologies and of their outputs, i.e., nanoparticles (NPs), are extensively discussed in the literature in terms of possible benefits and disadvantages [10,11]. Nanoparticles offer considerable advantages over conventional drug-delivery systems due to their small size and consequently large surface area. They can allow transportation and release of drugs with tailorable release kinetics of active ingredients to target side as well as enhanced solubility and stability of most drugs, resulting in improved pharmacokinetic profiles [12,13]. In particular, dedicated investigations for curcumin delivery have emphasized that nanoliposomes are the better administration platforms, even if their use can also manifest adverse effects [9,10,11,14]. Liposomes are artificial self-assembled colloidal particles consisting of one or more lipid bilayers surrounding an aqueous core. They are useful as biocompatible drug-delivery vehicles for hydrophilic, amphiphilic, and lipophilic molecules which are poorly absorbed and/or rapidly metabolized in their naked form (such curcumin). Due to their low intrinsic toxicity and immunogenicity and their resemblance to cell membranes in terms of structure and composition, a characteristic that favors the drug penetration through biological barriers, liposomes are attractive candidates in the controlled release of many kinds of active ingredients [15,16,17]. Moreover, liposomes’ size, which has a key role in carriers’ uptake after their administration, can be easily modified according to need, i.e., it has flexible features. In particular, liposomes of nanometric size are preferred. As discussed above, nano dimensions allow larger interfacial surface area that improves solubility, bioavailability, and release properties [18]. Nanoliposomes are able to maintain the transparency of clear beverages in the case of nutrients enrichment [19] and also enhance the intestinal absorption of the active principles [20]. It is noteworthy to mention that nanoliposomal formulations have successfully been used in clinical applications as an FDA-approved nanocarrier for a variety of drugs [13]. LipocurcTM is the most known curcumin liposomal product that has undergone clinical trials [10,14]. To cite several outcomes, nanoliposome-based delivery systems for CUR have revealed: enhanced bioavailability, better anticancer effects [9,11]; lower adverse effects but also higher cytotoxicity (trials on cell lines for several cancer type) [9]; enhanced anti-inflammatory proprieties (test in vivo) [21]; better internalization by cells into cytoplasm, and attenuation of neuroinflammatory reactions (in cell lines/in murine brain tissue) [13]. Since the introduction of liposomes to the scientific community, many techniques and methodologies have evolved for their production such as the Thin Film Hydration (TFH) or Bangham method [22], the Ethanol Injection (EI) [23], the High-Pressure Homogenization (HPH) [24], the Reverse Phase Evaporation (RFE) [25], the Supercritical Fluid (SF) [26], the Microfluidic Channel (MC) [27], just to cite a few. Details and discussions on principle and equipment of the reported production methods can be found in literature sources as books and reviews [28,29,30]. Despite the ever-increasing interest in the field and the enormous research that has been undertaken, the manufacturing process represents the principal barrier in the large scale production of liposomes. Ultimately, liposomes production methods are bulk discontinuous techniques characterized by long times of process, high-energy request and the use of toxic solvents or low/high values of pH and pressure during the preparation which affect the chemical structure of the entrapped substance [18,31]. Moreover, the majority of these methods suffer from the impossibility to scale up the process, and are characterized by small volumes in output whereby they cannot give products directly at nanoscale, thus requiring further laborious steps for vesicles sizing, i.e., sonication or membrane extrusion. Even the most recent techniques, i.e., based on microfluidics approach, require very expensive devices which are difficult to scale up. Recently, considering the lack of a continuous and practical large-scale manufacturing technique, a new simil-microfluidic method, characterized by potential continuous regime, massive and rapid production features, was developed. It was described in detail in [32] and in the patent document WO2019049186 [33]. The developed method exceeds the limits of conventional techniques also offering lower production costs and environmental impact by avoiding the use of special micro-fabricated devices and drastic process conditions. This study is focused on the production aspects of liposomal curcumin in aqueous prevalent medium. It presents, in particular, the application of the novel simil-microfluidic method, as mild and throughput technology, to produce encapsulated curcumin in nanoliposomal structures. After a process-issues presentation, with the aim to optimize the load of curcumin component and its encapsulating capability, several investigations varying curcumin concentration were performed. All types of achieved products were characterized in terms of size, polydispersity index, load, and encapsulation efficiency. ## 2.1. Materials Cholesterol (CHOL) (CAS no. 57-88-5), L-a-Phosphatidylcholine (PC) from soybean, type II-S, 14–$23\%$ choline basis (CAS no. 8002-43-5), ethanol of analytical grade (CAS no. 64-17-5) and curcumin (CUR) (CAS no. C1386) were acquired from Sigma Aldrich (Milan, Italy) and used as received. Deionized water was product by lab deionizer. Curcumin, also called diferuloylmethane, is a yellow polyphenolic powder extracted from the rhizome of Curcuma longa and other Curcuma species [9,34]. Three are the main types of curcuminoids: curcumin (CUR I), desmethoxycurcumin (CUR II), and bisdemethoxycurcumin (CUR III) (structures in Figure 2). Their abundance in turmeric is around 77, 17, and $3\%$ respectively [9]. The most abundant one is thus CUR I, a lipophilic molecule with a molecular weight of 368.38 g/mol and a molecular formula of C21H20O6 [35]. The curcumin (CUR I) structure is a linear diarylheptanoid which consists of two aromatic rings (aryl groups) joined by a seven carbon-unit chain [3] with hydroxyl and carbonyl functional groups as shown in Figure 2 [36]. In Table 1, the main properties of curcumin are summarized [37]. ## 2.2.1. Liposomes Production by Simil-Microfluidic Technology: Principles and Setup To address the limitations of existing techniques for producing nanoliposomes—such as the need for harsh operating conditions, toxic solvents, multiple post-processing steps, poorly controlled conditions, low output volumes, and high costs associated with microfluidic devices—a new technology called “simil-microfluidic” has been developed [16,32,38]. This novel technology allows for the production of homogeneous, antioxidant-loaded nanoliposomes in a single step at room temperature, directly at the nanoscale. The process involves the controlled contact of two phases through a coaxial insertion system using pumps to introduce the lipid and hydration solution feeds. A diagram of the setup piping is shown in Figure 3a, and details on the inlets systems (pump-dampener groups) and lipid flow insertion are shown in Figure 3b,c, respectively. The simil-microfluidic technology offers precise control of fluid dynamics and eliminates the need for toxic solvents, making it a promising approach for nanoliposome manufacturing. ## 2.2.2. Massive Production The simil-microfluidic setup has the potential to operate continuously at high throughput by maintaining a fixed ratio between the volumetric flow rates of the two phases. In this study, batches of curcumin-loaded liposomes were produced using a hydration solution volumetric flow rate (Vhs) and lipid solution volumetric flow rate (Vls) ratio of 10:1 (Vhs/Vls). Specifically, the volumetric flow rates of Vhs and Vls were set at 45 mL/min and 4.5 mL/min, respectively. Under these conditions, a significant amount of liposomal suspensions—approximately 3 L/h—can be produced in a short amount of time. In this study, several production batches were prepared. The first batch was produced using a recipe outlined in a previous study [16]. To prepare the lipid ethanol solution, 940 mg of PC, 188 mg of cholesterol, and 140 mg of curcumin were dissolved in 20 mL of ethanol, resulting in a theoretical concentration in CUR of 6.99 mg/mL. The hydration solution consisted of 200 mL of deionized water. The ethanol solution was stirred for an entire night to ensure complete lipid dispersion into the alcoholic phase, resulting in an initial lipid/ethanol solution concentration of approximately 50 mg/mL lipids (5 mg/mL lipids in the final hydroalcoholic solution). Other production batches (referred to as “Prod.” in the following) of curcumin in lipids/ethanol phase were prepared with varying compositions, as shown in Table 2. The same recipe for lipid composition (PC, CHOL) was used for all production batches, but the amount of curcumin was reduced for each batch, resulting in theoretical concentrations of 4.98 mg/mL, 2.85 mg/mL, 1.42 mg/mL, 0.73 mg/mL, and 0.49 mg/mL in ethanol prior to encapsulation. The final production batch (batch 7) was carried out to study the effect of lipid amount on encapsulation efficiency. To this purpose, a different recipe was employed. As indicated in Table 2, a theoretical curcumin concentration of 0.71 mg/mL in ethanol phase was selected (corresponding to CUR load of prod. 5), but only half of the initial amount of lipids was used. ## 2.3.1. Separation Steps Curcumin is a compound that is soluble in lipids and can be easily dissolved in organic solvents such as ethanol, methanol, and acetone. In particular, its solubility in ethanol is reported to be 10 mg/mL, as shown in Table 1. As reported in the Introduction, curcumin is insoluble in water, and thus, it tends to aggregate in hydrophilic solvents. Its aggregates have a typical sharp needle-structure [35]. This behavior in aqueous environments can cause significant issues during the manufacturing and storage stages, as well as in curcumin assay protocols, and there are gaps in the scientific literature regarding this point. During our experimental work on nanoliposome preparation using an aqueous medium, we encountered issues with the formation of aggregates. To distinguish between aggregates and vesicular structures, a filtration stage was added to the preparative protocol. Before and after filtration, suspensions were characterized to assess the impact and effect of the separation stages. Initially, all the liposomal suspensions produced were subjected to a rough syringe filtration using a membrane filter (Whatman®, Merk, Maidstone, UK) with a pore size of 450 nm. This was done to retain any coarse structures that might be present in the suspensions. Next, to separate the pellet from the supernatant, we used an additional filtration step employing tangential flow filtration (TFF) membrane. This process produced a retentate (pellet) and a permeate (supernatant or filtrate). The TFF membrane was placed in a custom-made filtration loop that included two plungers operating in opposite directions. When one plunger fills, the other empties, creating a continuous flow. This approach is efficient and easy to use [39]. The TFF membrane (Minimate TFF Capsule with Omega membrane—modified polyether-sulfone) allows for continuous tangential flow of the liposomal suspension over the membrane. The tangential flow filtration method was preferred over the classic ultracentrifugation because it is gentler on the vesicle structure and reduces the risk of contamination between the pellet and the supernatant. It is worth noting that the centrifugation method deposits all particles on the bottom, making it impossible to discriminate between particles or different aggregates of higher dimensions, as occurs with CUR in aqueous bulk, which can falsify encapsulation yields. We opted for tangential flow filtration instead of crossflow filtration because the latter can quickly saturate the membrane and cause vesicle rupture due to increasing pressure over the membrane. ## 2.3.2. Vesicles Size and Suspension Inspection For the nanolipid vesicles, the Z-average size, which is defined as the average hydrodynamic diameter, and the numerical size distribution were measured using the dynamic light scattering (DLS) method. The DLS measurements were conducted under environmental conditions after dilution and sonication of both the liposomal suspensions and syringe filtrates with distilled water in ratios ranging from 1:3 to 1:4. Each sample was measured at least three times, and the results were expressed as average values. The produced suspensions were observed by optical and transmission electron microscopy (TEM). The Leica microscope DMLP equipped with the digital camera Leica DFC 480 was used for optical microscopy investigations at a magnification of 40×. TEM images were achieved by the EM 208, Philips instrument, equipped with a camera Olympus Quemesa (EMSIS GmbH and Software RADIUS). Approximately 10 μL of washed pellet sample were diluted with distilled water and were placed on a carbon support over a copper specimen grid mesh 200 (Electron Microscopy Sciences) and, finally, negatively stained with a solution uranyl acetate ($1\%$ w/v). ## 2.3.3. Encapsulation Efficiency and Load Samples were taken from all liposome batches produced to measure the amount of curcumin encapsulated and unencapsulated. The sampling process included three stages:-first, aliquots were taken from each prepared liposomal suspension batch;-second, aliquots were taken from each syringe-filtered bulk;-third, aliquots were taken from each TFF permeate bulk. These samples were then subjected to spectrophotometric analysis. Samples of the liposomal suspension were diluted in ethanol and sonicated for 1 min (at $100\%$ amplitude -VCX 130 PB Ultrasonic Processors, 130 W, Frequency 20 kHz, Sonics & Materials Inc., Newtown, CT, USA) before undergoing UV-VIS spectrophotometric analysis (Lambda 35, PerkinElmer, Monza, Italy) to measure the encapsulated and unencapsulated amounts of curcumin. Absorption spectra were acquired between 200 nm and 600 nm, and the absorption maximal wavelength for curcumin was considered to be 426 nm, according to the literature [40]. The filtrated and permeate samples, as well as the liposomal suspension samples, were also diluted in ethanol and subjected to UV-VIS spectrophotometric analysis, with sonication applied only to the syringe-filtrated samples to disrupt the vesicles. Proper dilutions were used to stay within the calibration curve. The percentage of drug encapsulated in liposomal vesicles, known as encapsulation efficiency (e.e.), was determined using Equation [1]. This equation gives the ratio of the difference between the initial (o total drug) and the drug detected in the permeate, to the initial amount of drug added in the formulation: [1]e.e$.\%$=Total,mg−Permeate,mgTotal,mg·100 Since the filtration steps can retain CUR, Equation [1] must take in account the two steps of separation. Thus, the effective efficiency has to be calculated as the product of the first efficiency, the syringe separation, and the efficiency after the TFF, by Equation [2]: [2]e.e$.\%$=Curinsyringefiltrate,mgTotalCUR,mg·CURinsyringefiltrate,mg−CURinTFFpermeate,mgCurinsyringefiltrate,mg·100 In particular, in Equation [2] the first part pertains to the separation efficiency of the filter syringe (e.s. syringe), while the second part refers to the TFF separation efficiency (e.e. TFF). The term “theoretical load” denotes the initial quantity of CUR present in the formulation divided by the total mass of all the ingredients utilized:[3]TheoreticalLoad%=TotalCur,mgTotalCur,mg+lipidsPCCHOL,mg·100 Effective or practical load was then determined as the effective encapsulation efficiency multiplied by the theoretical load, as reported in Equation [4]: [4]EffectiveLoad%=e.e.·TheoreticalLoad Table 3 provides a summary of the composition of the seven production batches along with the corresponding theoretical load calculations. ## 2.3.4. Stability The features of liposomal preparations that were stored for one month after syringe-filtration were examined. The samples were kept at 4 °C and protected from light, and were visually inspected weekly to detect any potential aggregation or segregation. At the end of the fourth week, samples were collected from all the formulations and analyzed for their size and load using the same methods as for the fresh samples. ## 2.4. Statistical Analysis The statistical significance of the experimental data was evaluated by comparing the independent variable of the CUR/PC ratio (mg of curcumin/mg of phosphatidylcholine) with the dependent variable of the particle sizes. This analysis was performed using Student’s T-test and one-way analysis of variance (ANOVA), with statistical significance considered at $p \leq 0.05.$ ## 3.1. Production Insights In our simil-microfluidic apparatus, laminar flow occurs due to the small scale of the channels and low volumetric flow rates, as similarly happen into microfluidic systems, unlike the chaotic flows observed in conventional bulk preparation methods. It is noteworthy to observe that fluid dynamic in microchannels constitutes a non-trivial topic that is not referable to the classic studies of intubated flows. The definition of the fluid dynamic behavior of flows, in particular in coaxial configuration, requires attention in understanding regime developed and mixing time [41]. In this study, the tested operative conditions, i.e., volumetric flow rates of 45 mL/min and 4.5 mL/min Vls for aqueous (Vhs) and ethanolic phase (Vls), respectively, allow a laminar regime for the resulting hydroalcoholic suspensions (flow velocity ratio 7.56—considering, for the calculation, the mentioned rates for lipid ethanol as inner flow and water as outer flow, and the appropriate values for physical and geometric parameters for feeds and tubes; and Reynolds number 240). This result allows us to hypothesize that the mixing between the two phases is primarily governed by diffusion mechanisms. During these diffusion processes, lipid vesicles on a nanometric scale begin to form through self-assembly, according to Lasic et al. ’s theory [1998] [42]. Briefly, lipids dissolved in an organic solvent are in the form of bilayer fragments (Phospholipid Bilayer Fragments, BPFs), the interdiffusion of the water and the organic solvent reduces the solubility of the lipids in the solvent and this reduction, along with the thermodynamic instability of BPFs edges, induces curvature and closure of bilayer fragments which allows the formation of liposomal vesicles. Typically, the technique exhibits high encapsulation efficiency for lipophilic active ingredients, which are primarily dissolved in the lipid phase. However, both the molecule being encapsulated and the lipid materials’ physicochemical characteristics may impact the encapsulation yield’s success. Curcumin is a lipophilic ingredient with a quite small molecular mass: these features favor its entrapment and accommodation in phospholipidic bilayer [9,36,40]. This study aimed to determine the maximum amount of curcumin that could be added to liposomes produced by the simil-microfluidic method. Based on the obtained results, which are discussed in detail in the following sections, the first observation was focused on the production of highly heterogeneous products. Additionally, the liposomal structures exhibited low encapsulation efficiencies and load values, which could be attributed to the formation of curcumin aggregates. To explain this, an antisolvent effect was hypothesized, in line with previous literature works on the achievable maximum load of liposomal curcumin [40,43]. When the alcoholic and water phases come into contact, curcumin and lipids gradually lose their solubility in the forming ethanol/water suspension. This effect not only promotes the closure of bilayer fragments but also leads to a “supersaturation” of curcumin, which then aggregates upon contact with the aqueous phase. These phenomena are governed by thermodynamics and kinetics, which in turn can depend on the concentration of materials (lipids, curcumin) and mixing time, respectively. This study aimed to address the issue of curcumin aggregate formation in liposomal suspensions by introducing a separation stage to exclude large curcumin particles from the final product. This approach prevented interference with vesicle characterization protocols and misleading results on low encapsulation efficiency and load values. Then, various initial curcumin concentrations were tested to optimize the encapsulation yield limiting losses due to aggregation (as detailed in Table 3, which lists the composition of the seven production batches). ## 3.2.1. Encapsulation Efficiency and Load In Table 4 encapsulation efficiencies and effective loads of all production batches were reported. For the first production batch an encapsulation efficiency of $11.12\%$ and a load of $1.23\%$ were obtained. These values are different from those obtained by simil-microfluidic approach with other liposoluble compounds as, for example, vitamin D3, for which an efficiency of $88.4\%$ and an effective load of $9.20\%$ were achieved as shown in a previous work [17]. The nature of the molecules being encapsulated plays a crucial role in their arrangement within the liposomal bilayer. CUR, diversely from D3 that largely interacts with phospholipid bilayer [44], tends to lie perpendicular to the bilayer normal [36]. This is due to curcumin’s polar groups to be close to the hydrophilic groups of phospholipidic chains in order to form a larger number of hydrogen bonds. The described accommodation may thus limit the molecules’ inclusion. We observed that aggregates formation is related to the amount of initial CUR. As it can be seen from the separation efficiency data (e.s$.\%$, in Table 4), the retention of curcumin (as aggregates) decreases from batch 1 to 6, i.e., in the filtrate CUR (entrapped inside the vesicles as demonstrated by CUR absence in TFF permeate) increases its value from $11.13\%$ to $89.74\%$. Subsequent TFF filtration allows to separate loaded vesicles from hydroalcoholic suspensions without further losses of CUR. Indeed, the detected CUR in the permeate was negligible, confirming its encapsulation in liposomal vesicles (retentate product). In order to optimize the encapsulation efficiency of curcumin, the initial amount of curcumin was gradually decreased while keeping the masses of the other compounds fixed (as shown in Table 3 for Prod. 1–6 compositions). This approach has been adopted in research where similar liposomal formulations were used to study interaction and localization of curcumin with/in liposomal bilayers. These studies examined the effects of curcumin concentration on the average hydrodynamic diameter of vesicles [43] and their mechanical properties [40]. Curcumin has been shown to preferentially locate in the lipid bilayer of the liposome, and thus the loading capacity of the carrier is directly related to its interaction with the lipid components of the vesicles. In Karewicz et al. ’s studies [43], the size of vesicles decreased with an increasing amount of curcumin, due to its condensing effect on the liposomal bilayer. Moreover, the loading capacity of curcumin in vesicles was affected by its starting amount. After reaching a critical value, higher quantities added to the formulation caused precipitation and an increase in average size, likely due to the formation of aggregates resulting from destabilization of the system. Arab-Tehrany et al. [ 40] observed that as curcumin was added/inserted into the lipid bilayer, both elasticity and rupture force progressively decreased. This was explained by a progressive homogenization of the lipids’ packing due to the interactions between curcumin and the alkyl chains of the lipids (hydrophobic molecules can modify the membrane curvature generating rearrangements in the packing of lipids). In addition, this effect was hypothesized to be controlled by a critical concentration of curcumin. When its amount in the membrane becomes significant, destabilizing effects occur, reducing elasticity and the resistance to rupture forces. In this study, the effect of the curcumin starting concentration on liposomal products were elucidated by measuring loading capacity, encapsulation efficiency and particle size. In Figure 4 (and Table 4), encapsulation efficiency and effective loads vs. curcumin effective concentration were reported. An increase in encapsulation efficiency until a maximum of $89.71\%$ (prod. batch 6) was achieved reducing the starting amount of CUR. The load values, instead, were roughly constant with a value fluctuating around $1.3\%$. The achieved results confirm the presence of a “critical load-limit” with respect to the lipid composition, as shown in literature. Curcumin can be located in the bilayer until a critical amount; the highest values lead to curcumin losses for aggregations. The best loading capacity and encapsulation efficiency were achieved for the prod. Batch 5 (e.e. $89.47\%$; load of $1.15\%$) indicating as a load-limit, for our lipid formulation, the effective concentration of the prod. batch 4. This conclusion is also substantiated from DLS particles size analysis. It is worth noting that in literature articles variable efficiency of encapsulation efficiencies and loads for CUR nanovesicular systems, ranging from $54\%$ to $95\%$ and $1.9\%$ to $4\%$, respectively, have been achieved. These remarkable outcomes were, however, obtained through the use of complex and multistep methods, involving multiple components and coating processes to ensure stability of the CUR-nanosystems [9]. ## 3.2.2. DLS Analysis and Suspension Inspections Table 5 reports the results of DLS investigations on size (numerical and Z-average) and PDI for particles (CUR aggregates and vesicles) suspended in the produced batches. In Table 5, the column named x1,0 reports the mean size value of the numerical probability distribution function; the column xmod,6 indicates the (maximum) modal value of the intensity probability distribution function (PDF), i.e., the size corresponding to the maximum peak in the intensity PDF (q6: these values can be easily identified by inspection of Figure 5 and Figure 6, being the quotes of the highest peaks). It is important to note that each value (both for x1,0 and xmod,6) is the outcome of an average of three different productions that were carried out under identical operating conditions to ensure repeatability. In DLS, the values of q6, which are obtained through autocorrelation function analysis, are directly proportional to the sixth power of particle size. Hence, the xmod,6 value, which corresponds to the modal value of the intensity probability distribution function, directly reflects the presence of large particles or aggregates. As expected, the values of xmod,6 decreased significantly for each experiment following syringe filtration, as seen in Figure 5 for production batches 1–4. Otherwise, in productions 5 and 6 (Figure 6), the values of xmod,6 were already low before the filtration step, indicating the absence of any aggregates in the produced batches. In contrast, the values of x1,0, which represent the small and abundant particles, remain nearly unaffected by both the formulation parameters and the filtration process. Regardless of the production conditions, the process generates numerous small liposomes, resulting in a size mean value that generally falls between 100 and 250 nm, as indicated by the peaks located just above 100 nm in each experiment before and after filtration. The sole exception is the production batch 1, characterized by a higher concentration of CUR, in which the abundance of aggregates substantially influences the mean numerical value x1,0 (at least before filtration). The stability studies performed on aged samples of all production batches (filtered samples) support the DLS data obtained for size (numerical and Z-average) and PDI of the fresh productions (filtered samples). Additionally, the CUR detected in the filtrates was negligible, indicating its stable retention within the liposomal nanovesicles under refrigerated conditions. Microscopic images were captured to validate the presence of CUR aggregates identified by DLS findings in various liposomal suspension samples (before filtration). Figure 7 displays irregular, needle-shaped aggregates in the liposomal suspensions of production batches 1 (Figure 7a), 3 (Figure 7b), and 4 (Figure 7c). The image in Figure 7d is related to the production batch 5 sample, where aggregates were not observed, as verified by DLS analysis. This finding reinforces the hypothesized critical concentration of CUR necessary for the successful implementation of the similar-microfluidic technique. In general, these results indicate the importance of optimizing the formulations of liposomal curcumin. By using appropriate concentrations, the loss of CUR as aggregates can be avoided, which are not beneficial for health purposes due their low bioavailability in “naked” form, and also reduces the impact on material costs. In Figure 8 a TEM image of production batch 5 (sampling from washed pellet) is shown. The image confirms that the simil-microfluidic technique produces spherical nanosized vesicles. ## 3.3. Effect of Lipid Concentration The aim of this part of the work was to assess the impact of reducing the lipid fraction (as outlined in Table 2) on the characteristics of CUR loaded vesicles. Production batch 5 was selected as control production due to its best achieved features in terms of e.e. and load, as well as the absence of aggregates. The findings of this investigation (production batch 7) showed an effective load of $0.70\%$ and an e.e. of $29.14\%$ as reported in Table 6. Moreover, the presence of aggregated was detected (see e.s$.\%$ value in Table 6 and Figure 9). This implies that the successful loading of curcumin, as expected, was closely linked to the formation of vesicles too [45]. When the lipid fraction was reduced, there weren’t sufficient bilayers to encapsulate all of the curcumin. As a result, the non-encapsulated CUR began to aggregate upon contact with water, as evidenced by the DLS results presented in Table 7 (and Figure 9). This sequestration, in turn, further impacted the amount of curcumin that could be potentially encapsulated. The experimental data (values obtained before the syringe filtration step, see Table 5 and Table 7) were subjected to statistical analysis to determine their significance. Specifically, the ratio of CUR/PC (mg of curcumin/mg of phosphatidylcholine) was used as an independent variable, while Z-Average, xmod,6, and x1,0 were used as dependent variables in three separate series. The statistical analysis was performed using Student’s t-test and one-way analysis of variance (ANOVA), and any differences were considered significant at $p \leq 0.05.$ The statistical analysis of the data indicated that the results for Z-Average and xmod,6 were statistically significant ($$p \leq 0.005$$ and $$p \leq 0.002$$, respectively, both less than 0.05). This was expected, as the formulative conditions had an impact on the average hydrodynamic size (Z-Average) and the formation of aggregates (related to xmod,6). However, it should be noted that there is always a certain percentage of particles in the small size range (between 100 and 250 nm) regardless of the formulation conditions used. In these cases, there is no statistical significance in the data (as determined by the t-test for the ratio of CUR/PC and x1,0 series, with a p-value of 0.086, which is greater than 0.05). Upon inspections of production batch 7 (as produced, before filtration) by optical microscope, it was observed that the suspensions contained large and small needle-like aggregates (Figure 10), confirming the DLS results. The aged products of batch 7 (filtered samples) maintained the same properties of the fresh filtrate, such as size and retention of CUR in vesicles. ## 4. Conclusions Dosage of curcumin, a powerful active ingredient for pharmaceutical and nutraceutical purposes, is limited by its low bioavailability. Many literature results show that the nanoliposomal curcumin has exhibited great potentiality for several cancer therapies (in in vitro/in vivo tests; clinical trials). Thus, effective, feasible, and sustainable liposomal productions for nanoliposomal curcumin represent a challenge on industrial manufacturing point of view. In our research, we have developed and patented a technology called simil-microfluidics, which allows for the rapid and easy production of large quantities of nano-scale liposomal suspensions at room temperature and with minimal energy requirements. Furthermore, the setup simplicity makes the technology an excellent starting point for industrial scalability. In this work, our attention was focused on the production aspects of liposomal curcumin. In particular, by varying curcumin initial concentration, optimized conditions for interesting loads and encapsulation efficiency were defined, and curcumin aggregation formation effect was elucidated. We have found that, by using a precise CUR/lipidic components ratio, nanoliposomes with a load higher than $1\%$ and with a considerable e.e. ( roughly $90\%$) can be obtained. Furthermore, CUR aggregates formation can be avoided, reducing material costs. 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--- title: Synergy between Membrane Currents Prevents Severe Bradycardia in Mouse Sinoatrial Node Tissue authors: - Limor Arbel Ganon - Moran Davoodi - Alexandra Alexandrovich - Yael Yaniv journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051777 doi: 10.3390/ijms24065786 license: CC BY 4.0 --- # Synergy between Membrane Currents Prevents Severe Bradycardia in Mouse Sinoatrial Node Tissue ## Abstract Bradycardia is initiated by the sinoatrial node (SAN), which is regulated by a coupled-clock system. Due to the clock coupling, reduction in the ‘funny’ current (If), which affects SAN automaticity, can be compensated, thus preventing severe bradycardia. We hypothesize that this fail-safe system is an inherent feature of SAN pacemaker cells and is driven by synergy between If and other ion channels. This work aimed to characterize the connection between membrane currents and their underlying mechanisms in SAN cells. SAN tissues were isolated from C57BL mice and Ca2+ signaling was measured in pacemaker cells within them. A computational model of SAN cells was used to understand the interactions between cell components. Beat interval (BI) was prolonged by 54 ± $18\%$ ($$n = 16$$) and 30 ± $9\%$ ($$n = 21$$) in response to If blockade, by ivabradine, or sodium current (INa) blockade, by tetrodotoxin, respectively. Combined drug application had a synergistic effect, manifested by a BI prolonged by 143 ± $25\%$ ($$n = 18$$). A prolongation in the local Ca2+ release period, which reports on the level of crosstalk within the coupled-clock system, was measured and correlated with the prolongation in BI. The computational model predicted that INa increases in response to If blockade and that this connection is mediated by changes in T and L-type Ca2+ channels. ## 1. Introduction The sinoatrial node (SAN) maintains the heart rate at rest in a range that allows for an instantaneous increase when a person performs work or generates a fight or flight response. While low heart rate at rest, also termed sinus bradycardia, is not a risk factor per se, when induced by specific drugs, it is associated with incident cardiovascular diseases and elevated mortality [1]. Severe symptomatic bradycardia can lead to atrial fibrillation and a decrease in oxygen supply [2]. The body may engage a “fail-safe” mechanism to prevent such conditions. SAN function is maintained by a coupled-clock system that consists of membrane ion channels, exchangers, and pumps (M clock), and an internal Ca2+ clock, namely, the sarcoplasmic reticulum (SR). Both clocks communicate via Ca2+ and Ca2+-activated adenylyl cyclase (AC)-cAMP-PKA signaling, with local Ca2+ releases (LCRs) from the SR indicating the degree of coupling [3]. Due to the connectivity of the clocks, a change in a single membrane component can affect the others, and impair or upregulate clock function [4]. Thus, if one component in the coupled-clock function fails, another component can compensate for the reduced pacemaker function. Here, we focus on I pacemaker (“funny”) current (If), which is one of the elements that contribute to the generation of spontaneous diastolic depolarization and an important stabilizer of heart rhythm [5]. Reduction in If was previously shown in heart failure conditions [6,7], aging [8], pulmonary hypertension [9], diabetes [10], and atrial fibrillation [11]. However, in such clinical scenarios, the SAN is still beating, and most patients show no signs of severe bradycardia. This may be ascribable to If, which, when in synergy with other clock components, may upregulate their function and prevent severe bradycardia. We hypothesize that SAN pacemaker cells bear an inherent fail-safe mechanism driven by synergy between ion channels and If, and that this synergy is mediated by a coupled-clock mechanism and specifically by Ca2+-dependent channels. To prove these hypotheses, we isolated SAN tissues from C57BL mice (Figure 1A) and used confocal microscopy to measure Ca2+ signaling in pacemaker cells within the tissue (Figure 1B,C). We applied ivabradine (IVA), which reduces If, alone or in combination with tetrodotoxin citrate (TTX), or tetramethrin (TMR), blockers of sodium current (INa) and T-type Ca2+ current (ICaT), respectively, which are two potential synergy components. A computational model of SAN cells (Figure 1D) was used to understand the internal interactions between cell components. Here, we experimentally show synergy between If and INa. Our model predicted that synergy exists between If and INa and that this synergy is mediated by the ICaT and L-type Ca2+ current (ICaL). We also found that synergy between If and INa exists at the level of the LCR period (Figure 1C), and promotes the positive feedback between ICaL, SR Ca2+, and Na+-Ca2+ exchanger current (INCX) [12]. Taken together, our data show that a fail-safe mechanism is driven by a connection between ion channels and is mediated by membrane Ca2+-related mechanisms. ## 2.1. ICaT and INa Are Upregulated When If Is Inhibited: Computational Evidence If is one of the regulators of the spontaneous beating of the SAN. Inhibition of If by pharmacological drugs or by genetic inhibition of HCN4 does not stop the spontaneous beating. To explore whether a “fail-safe” mechanism is engaged to prevent severe bradycardia when If is reduced, we used our previously published computational model of the single mouse SAN cell [13] (Figure 1D). Inhibition of If was simulated by reducing the If maximal conductance coefficient (gIf, see supplements) to $10\%$ of its basal value (Figure 1E). Figure 2 shows the effect of If inhibition on main coupled-clock mechanisms. The model predicted that a reduction in gIf prolonged the beat interval (BI), calculated as the time interval between two peaks of action potential (AP), and also associated it with increased amplitudes of ICaT (+$114\%$), INa (+$48\%$), and Ca2+ flux through the ryanodine receptors (RyR (+$32\%$)), INCX (+$18\%$), ICaL (+$10\%$), and other transmembrane currents and of Ca2+ cycling parameters (<$10\%$). The increase in ICaT and INa in response to If inhibition implies a connection between these currents, engaged in a potential mechanism to restrain the prolongation of BI. ## 2.2. There Is No Synergy between If and ICaT The model suggested that there is synergy between If and ICaT in single pacemaker cells. As shown before [14], pacemaker cells within the SAN demonstrate significant heterogeneity in the densities of If, ICaL, potassium currents (IK), and other currents, which might be dictated by their localization in different pacemaker cells clusters. Thus, we chose to use pacemaker tissues that contain different clusters to assess the possibility of an association between the channels. IVA (3 µM) and TMR (10 µM) were applied to intact mouse SAN tissue to block If and ICaT, respectively, and their individual and combined effects on the spontaneous BI were measured. Previous works demonstrated that 3 µM IVA blocks the HCN4 channel [15] without affecting the T-type, L-type, delayed outward potassium current densities [16], or SR Ca2+ content, while 10 µM IVA was shown to affect the T or L-type channels [16]. TMR at 0.1 µM was shown to block ICaT in single rabbit SAN cells, while 50 µM TMR abolished both ICaT and ICaL [17]. Yet, as we detected no change in the BI or LCR period of mouse SAN cells residing in the SAN tissue after administration of 0.1 µM TMR ($$n = 6$$, Figure S1), the current experiments were performed with 10 µM TMR. Figure 3A shows representative time courses of Ca2+ signaling before (control) and after the administration of IVA and following the administration of IVA+TMR. Figure 3B shows representative time courses of Ca2+ signaling before (control) and after the administration of TMR and following the administration of TMR+IVA. Note that the same cell was traced before and after each treatment (paired measurements). IVA increased the BI by 49 ± $20\%$, compared to its control, while TMR increased the BI by 28 ± $5\%$ compared to its control. Administration of both IVA and TMR increased the BI by 64 ± $13\%$ (Figure 3C). Beats per minute (BPM, calculated as 60,000/BI per cell) decreased by 24 ± $7\%$ with IVA, 20 ± $3\%$ with TMR, and 34 ± $4\%$ with both IVA and TMR, compared to the control. Namely, there was no additive effect upon application of both blockers together. BI variability (BIV), estimated by the average standard deviation of the BIs in each cell, was then calculated to determine whether each blocker and blocker combination affect BI periodicity as well. Compared to the control, BIV was increased by 105 ± $47\%$ with IVA, by 69 ± $29\%$ with TMR, and by 462 ± $134\%$ with both IVA and TMR (Figure 3D). Namely, there was an additive effect of the two blockers on BIV. To determine the effect of each blocker and blocker combination on Ca2+ transient and LCR properties, global and local Ca2+ signaling parameters were measured before and after each drug treatment. Ca2+ transient amplitude (estimated by the fluorescence ratio [F/F0]) and $50\%$ Ca2+ transient relaxation time were not affected (Figure 3E,F) by IVA, TMR, or by IVA+TMR. The LCR period, defined as the time from the previous Ca2+ transient peak to the LCR onset (as illustrated in Figure 1C), was prolonged only upon administration of IVA (88 ± $42\%$) and IVA+TMR (79 ± $21\%$), but not upon treatment with TMR alone (Figure 3G). ## 2.3. If and INa Blockers Have a Synergistic Effect on BI To determine whether synergy exists between If and INa, 3 µM IVA and/or 5 µM TTX were applied to pacemaker cells within intact mouse SAN tissue and the spontaneous BI was measured. Figure 4A shows representative time courses of Ca2+ signaling before (control) and after the administration of IVA and following the additional administration of TTX. Figure 4B shows representative time courses of Ca2+ signaling before (control) and after the administration of TTX and following the additional administration of IVA. Compared to untreated cells, IVA prolonged the BI by 54 ± $18\%$ (Figure 4C), while TTX prolonged the BI by 30 ± $9\%$. In contrast to TMR, a synergistic effect was observed upon administration of both IVA and TTX, which prolonged the BI by 143 ± $25\%$. BPM decreased by 25 ± $6\%$ with IVA, 18 ± $4\%$ with TTX, and 50 ± $6\%$ with both IVA and TTX, compared to the control. No difference was found between the change in BI in cells treated with TTX following IVA (IVA+TTX) versus cells first treated with IVA and then with TTX (TTX+IVA). Taken together, the combined treatment enhanced the mono-drug blockade, suggesting that INa can play a role in the fail-safe mechanism when If is reduced. Figure 3: The effect of tetramethrin (TMR) on pacemaker cells residing in the SAN tissue. (A) Representative time course of Ca2+ transients in pacemaker cells under basal conditions, and after administration of 3 µM ivabradine (IVA) or following additional administration 10 µM TMR (IVA+TMR). (B) Representative time course of Ca2+ transients in pacemaker cells under basal conditions, after administration of 10 µM TMR (TMR), and following additional administration of 3 µM IVA (IVA+TMR). (C) Percent change from control in the beat interval (BI), (D) BI variability, (E) Ca2+ transient amplitude, (F) 50% Ca2+ transient relaxation time, and (G) local Ca2+ release (LCR) period in control pacemaker cells (white) and after administration of IVA (yellow, N = 12), TMR (green, N = 16), and both IVA and TMR (purple, N = 16). BIV increased by 106 ± $40\%$ with IVA, by 176 ± $83\%$ with TTX, and by 100 ± $36\%$ with the IVA and TTX combination (Figure 4D). Namely, the combined drug treatment did not further enhance the BIV increase obtained with each blocker separately. The Ca2+ transient amplitudes did not change after the administration of IVA or IVA+TTX. In contrast, TTX alone decreased the Ca2+ transient amplitude by 13 ± $3\%$ compared to the control (Figure 4E). In addition, TTX treatment led to a 5 ± $2\%$ increase in the $50\%$ Ca2+ transient relaxation time (Figure 4F), while IVA and IVA+TTX had no effect. The LCR period was prolonged by 81 ± $31\%$ on application of IVA, by 49 ± $18\%$ with TTX, and by 164 ± $46\%$ with both IVA and TTX (Figure 4G). Thus, the nonlinear change in BI in response to each blocker compared to their combination was also reflected in a nonlinear change in the LCR period. ## 2.4. The Molecular Mechanisms That Mediate the Synergy between If and INa: Computational Evidence The nonlinear effect of If and INa blockers on BI and Ca2+ dynamics is likely due to feedback in the pacemaker cell mediated by still unknown mechanisms. Because specific blockers do not exist for each ion channel type, and because the clock mechanisms are coupled, it is experimentally impossible to test the underlying mechanisms. Therefore, we used our model to predict the internal mechanisms mediating the crosstalk between If and INa that was found experimentally. The TTX effect was simulated by reducing the channel maximal conductance coefficients (see supplements and Figure 1E); gNa1.1, the TTX-resistant maximal channel conductance coefficient, was reduced to $80\%$ of its basal value and gNa1.5, the TTX-sensitive maximal channel conductance coefficient, was reduced to $50\%$ of its basal value. Lower values led to model instability. Figure 5A shows a simulation of the main coupled-clock mechanisms under basal conditions, and on application of IVA and/or TTX. The model predicted a BI increase of $32\%$ with If inhibition, $31\%$ with INa inhibition, and $70\%$ with If and INa inhibition together (Figure 5A, internal figure), supporting the nonlinear commutative effect of IVA and TTX shown experimentally. In parallel, INa inhibition significantly decreased the amplitude of ICaT (−$74.5\%$), Ca2+ flux through the RyR (−$48\%$), and INCX (−$37\%$), together with a mild decrease in the amplitudes of If (−$17\%$), ICaL (−$17\%$) and intracellular Ca2+ (−$16\%$) (Figure 5A). Taken together, a reduction in If leads to a major increase in INa, while a reduction in INa does not increase If. To determine whether an increase in INa is key to prevention of severe bradycardia, we simulated a ‘current clamp’ by fixing INa to its basal state, while If was blocked in parallel. In this way, the increase of INa is blocked, and its effect on the BI can be evaluated. The model predicted that If inhibition with INa clamped causes a longer BI than If inhibition with varying INa, which indicates that the increase in INa in response to If inhibition restrains the increase in BI at the cellular level (Figure 5B). We then explored whether the synergy between If and INa also exists if If is increased. Figure S2 shows that INa decreased in response to a ten-fold increase in gIf. Thus, the negative feedback between If and INa serves as a fail-safe mechanism for both bradycardia and tachycardia. To uncover the internal mechanisms that mediate between the reduction in If and the increase in INa, we tested the individual effects of various cellular parameters by ‘clamping’ each parameter to its basal state, while blocking If in parallel. Only fixation of both ICaT and ICaL restrained the indirect increase in INa amplitude caused by If inhibition, by bringing the INa amplitude closer to its basal value and decreasing the BI (Figure 6). Fixation of ICaT (Figure S3) or ICaL (Figure S4) led to a smaller decrease in INa amplitude, while fixation of INCX (Figure S5) or RyR flux (Figure S6) did not reduce the indirect increase in INa caused by If inhibition. Taken together, ICaT and ICaL primarily mediate the increase in INa in response to a decrease in If. ## 3. Discussion The present study investigated the synergy between ion channels in pacemaker cells within mouse SAN tissue. The experimental measurements showed that the change in the spontaneous BI when both If and INa were blocked was higher than the sum of changes induced by each blocker individually (synergistic effect). Together with the model prediction that INa increases in response to If blockade, these results support the first hypothesis that a fail-safe mechanism is an inherent feature of SAN pacemaker cells and is driven by feedback among ion channels. The experimental effect on the LCR period when both If and INa were blocked compared to their individual effects and the model prediction that the feedback between If and INa is eliminated when ICaT and ICaL are clamped support the second hypothesis that this effect is mediated by coupled-clock mechanisms, specifically ion channels that are affected by intercellular Ca2+ dynamics. Our combined experimental measurements and numerical model simulations suggested that synergy exists between If and INa. The experiments showed that when both If and INa were blocked, the effect on the spontaneous BI was higher than the summed effect of the two blockers. The model showed a similar phenomenon when If and INa were inhibited by reducing their maximal conductance coefficients. It predicted that when If is reduced, INa increases. An increase in INa eliminates further deceleration of diastolic depolarization and prevents further bradycardia. However, when INa was reduced, the model predicted only a small change in If. Thus, the negative feedback between If and INa is unidirectional. Furthermore, the model predicted that an increase in If will reduce INa. Thus, the predicted synergy between If and INa also protects against tachycardia. Note that at the tested IVA concentration, there is a negligible direct effect on INa [18]. Although If plays an important role in pacemaking in the SAN, spontaneous beating is still maintained upon its inhibition with even higher (and non-specific) IVA concentrations [15,16] or elimination by genetic manipulation of HCN4 [11]. The synergy between If and INa may also act here as a “fail-safe” mechanism. Our second main finding was that Ca2+-activated channels mediate the synergy between If and INa. Our experiments showed that the effect of simultaneous If and INa blockage on the LCR period was higher than the summed effect of each blocker. The LCR period is linked to changes in the BI in response to numerous perturbations that affect both the M and Ca2+ clocks (i.e., a decrease in cAMP/PKA levels or β adrenergic receptor stimulation) [19] and is, thus, considered a readout of the degree of clock coupling [4]. An increase in the LCR period prolongs the diastolic depolarization through delayed activation of ICaL and INCX (positive feedback between ICaL and INCX [12]) and through direct activation of BK channels [20], which consequently lead to a longer BI. Thus, the LCR period itself reports on the synergy. The model predicted that when ICaT and ICaL are clamped, the INa increase in response to a decrease in If is moderated and restrains further bradycardia. Clamping ICaT and ICaL to their basal values blocks the positive feedback between ICaL-SR-INCX. Our suggested theory of the synergy between If and INa is based on the regulation of pacemaker activity by ICaL and ICaT and their regulation of ICaL-SR-INCX feedback. The increase in ICaL and ICaT in response to decreased If maintains intracellular Ca2+ levels. This, in turn, maintains Ca2+ release from the SR (RyR flux), preserves the LCR period, and via maintenance of INCX, accelerates the diastolic depolarization, which prevents further bradycardia. Note that clamping either INCX or RyR flux did not prevent the feedback between If and INa. Our experiments showed that removal of cytosolic Ca2+, measured as the Ca2+ transient relaxation time (T90), did not significantly change in response to IVA or IVA+TTX, suggesting that the SERCA pump function does not directly control the feedback between If and INa either. Clamping INa (Figure 5) reduced ICaT, ICaL, INCX, and RyR flux. Reduction in INa compared to its higher unclamped value prolongs BI, and thus, affects the diastolic depolarization voltage and activation of ICaT and ICaL. These reductions eliminate the positive feedback between ICaL-SR-INCX, and thus, lead to reduced INCX and RyR flux. Considering both the experimental results and the numerical model simulation, it can be concluded that the coupled-clock system per se is the fail-safe mechanism that prevents bradycardia in response to a decrease in If. Note that even under normal conditions, If is not the only regulator of SAN automaticity. There are several other currents, including ICa,T, ICa,L, and INCX, that contribute to spontaneous diastolic depolarization [21]. Thus, other coupled-clock mechanisms can act as fail-safe mechanisms even when in some, cell If is close to zero [14]. The model predicted that in parallel to the increase in INa, there was an increase in ICaT, INCX, and RyR flux in response to If inhibition. If inhibition leads to prolonged BI through increases in ICaT and ICaL, which lead to increased outflux currents and subsequently to increased INCX. Prolongation of BI allows the SR to slowly refill, resulting in an increase in Ca2+ available to activate ICaT and INCX. Note, however, that it also allows for less Ca2+ release per time interval. Ion channels are also coupled through changes in voltage and other internal signals, and positive feedback has also been shown to exist between INCX and ICaL [12]. Note, however, that this feedback was bidirectional and was measured if one of the currents increased or decreased. A positive feedback mechanism in cardiomyocytes was also described between the SK channel and ICaL [22] and together with RyR [23]. The model predicted that ICaT increases in response to a reduction in If. However, experimentally, when If was blocked together with ICaT, the effects on the spontaneous BI and LCR period were similar to the summed effect of each blocker. Thus, no synergy exists between If and ICaT. A decrease in If prolongs the BI and deaccelerates the diastolic depolarization. A longer diastolic depolarization phase allows for the activation of more T-type Ca2+ channels, increasing their amplitude. It has been suggested that ICaT stabilizes the rate of depolarization when the maximal diastolic potential is more positive [17]. Such conditions were achieved here when IVA was applied. Note that TMR by itself prolonged BI to a similar degree as TTX. However, compared to TTX, it does not have synergistic effect with IVA. Thus, the prolongation of BI by one drug does not necessarily lead to a non-linear effect on BI when combined with another drug. The BI of SAN is not constant and has some variability, which, itself, is considered an important index that correlates with various heart diseases [24]. Although the absolute change in the average spontaneous BI when both If and INa were blocked was different from the sum of changes induced by each blocker individually, the variability was similar between IVA, TTX, and IVA+TTX treatments. Because there is no linear relationship between BI and BIV [24,25,26], it is possible that cell perturbations differentially affect BI and its variability. In contrast, blockade of both If and ICaT resulted in a change in BI variability significantly greater than the sum of the changes caused by each of the respective blockers individually. It was previously shown that T-type channels contribute to setting the SAN firing rate [27], and that high variability exists upon target inactivation of T-type Cav3.1 channels [28]. Thus, T-type and funny channels may be important stabilizers of heart rhythm and may have a synergistic impact on variability increase when both are disabled. Taken together, it is likely that both If and ICaT play a significant role in pacemaker synchronization. Voltage clamping is the conventional method used to study ion channels [29]. This method is useful for measurement of the direct effect of drugs on specific channel populations. However, because ion channels are coupled through changes in voltage and other internal signals, this method is not suitable for measuring the dynamic feedback between the cell parameters. SAN bradycardia is often associated with a shift in the leading pacemaker, from the superior SAN inferiorly towards the subsidiary atrial pacemakers, including the atrioventricular node [30]. In this work, a cell in the central SAN area was imaged (see Figure 1A), and the same cell was traced before and after drug perturbation, thereby circumventing the impact of a potential shift in the leading pacemaker on our conclusions. Two components of INa have been reported in the mouse SAN: TTX-resistant and TTX-sensitive Na+ channels. It was recently shown [31] that TTX-sensitive channels may contribute to SAN pacing, while TTX-resistant INa is likely to be responsible for AP propagation from the SAN to the atrium. Note that we did not use cells in the periphery and only cells that responded to TTX were used. Moreover, at transmembrane potentials reported for mouse SAN cells [32], TTX-resistant Na+ channels are expected to be inactive and non-contributing to pacemaker activity. This work focused on inhibition of HCN4 by IVA. However, $20\%$ of HCN channels in the mouse are HCN2 [33]. However, specific inhibitors of HCN2 have not been tested on SAN cells yet and, thus, its potential interaction with other channels cannot be tested here. ## Limitations Aside from its inhibitory effect on voltage-dependent sodium channels, TTX has also been shown to inhibit Ca2+ currents [34]. However, this inhibition requires TTX doses higher than those used in this work. If it did inhibit Ca2+ channels, then the magnitude of the synergy between If and INa would be expected to be higher since the INa effect is mediated by increased activity of Ca2+ channels. High doses of TMR have been found to reduce ICaL together with ICaT [17]. While high TMR doses were not applied here, some nonspecific drug effects may have occurred. Differences in the values of global parameters in the model compared to the experiments may have arisen due to use of SAN tissue in the experiments versus single SAN cells in the model. They also may be ascribable to the technical limitations of the model to generate extremely short or long BIs, and to the lack of certain cell mechanisms, such as metabolic pathways, bioenergetics, and BIV, in the models. Yet, the experimental and computational trends were similar. In this work, BI was calculated from Ca2+ measurements of SAN tissue that was treated with fluo-4. It is known that when compared to patch or external electrodes, this technique yields prolonged BI in SAN tissue and cells. Yet, our BIs were in the range of previous publications of mouse SAN tissue measurements [6,35,36,37]. Others have published shorter BIs [38,39], but based on their illustration, the tissue was stretched, which could shorten the BI [40]. Moreover, their tissue had multiple rhythms while we only used tissues with synchronically beating cells. Note that since blebbistatin or any other drug that eliminates contraction was not used, we were able to clearly see the spontaneously beating area and to determine if there was more than one rate of the pacemaker (multiple sites). Note that INa inhibition may also suppress SAN-to-atrium propagation. However, this suppression is not affected by If. The experiments showed that when both If and INa were blocked, the effect on the spontaneous BI was higher than the summed effect of each blocker. Thus, synergy must exist between the currents that are involved in SAN-to-atrium propagation. Because Na1.5 is TTX-resistant [41], a higher concentration of TTX is needed to block these channels. However, 10 µM TTX completely stopped the SAN electrical activity in our experiments. Pacemaker shifts can occur with changes in BI [42]. However, we found no movement of the cell before and after drug perturbation and the same cell was traced before and after treatment. Moreover, we did not use blebbistatin or any other drug that eliminate contraction, which enabled us to clearly see the pacemaker contraction. Note that TMR by itself prolongs BI to a similar degree as TTX. When TMR was applied together with IVA, the effect on the spontaneous BI and LCR period was similar to the summed effect of each blocker (IVA or TMR). Thus, the prolongation of BI by one drug does not necessarily lead to a pacemaker shift that leads to a non-linear effect on BI when combined with another drug. ## 4.1. Mouse SAN Isolation Adult (12–14 weeks, 25–30 g) male C57BL mice were anesthetized with sodium pentobarbital (50 mg/kg, intraperitoneal) diluted with $5\%$ heparin. The hearts were quickly removed and placed in 37 °C Tyrode solution (NaCl 140 mmol/L, MgCl2 1 mmol/L, KCl 5.4 mmol/L, CaCl2 1.8 mmol/L, HEPES 5 mmol/L, and glucose 5 mmol/L, pH 7.4, titrated with NaOH). The SAN tissues were isolated from the intact hearts as previously described [37]. Briefly, the SAN and the surrounding atrial tissue were dissected and pinned down in custom-made silicone-covered optical chambers, bathed in Tyrode solution (Figure 1A). ## 4.2. SAN Confocal Ca2+ Imaging To measure Ca2+ signals, intact SAN preparations were loaded with fluo-4-AM (ThermoFisher, 30 μmol/L) over 1 h, at 37 °C, on a shaker set to 60 RPM. The tissues were washed twice with Tyrode solution before imaging. Ca2+ fluorescence was imaged using an LSM880 confocal laser scanning microscope (Zeiss) with a 40×/1.2 N.A. water immersion lens (Figure 1B). Baseline recordings were performed after 30 min rest at 37 °C. Tissues were excited with a 488 nm argon laser and emission was collected with a low-pass 505 nm filter. Images were acquired in line scan mode (1.22 ms per scan; pixel size, 0.01 µm) along the pacemaker cells. The same cell was imaged before (baseline) and after drug perturbation(s). Each recording lasted at least 3 s. ## 4.3. Ca2+ Analysis Ca2+ signaling was analyzed using a modified version of the software “Sparkalyzer” [43]. The fluorescence signal (F) was normalized by the minimal value between beats (F0). Ca2+ transients were semi-automatically detected and Ca2+ sparks were manually marked. BI was calculated as the average time between Ca2+ transient peaks, and the BIV was calculated as its standard deviation. The Ca2+ transient amplitude, Ca2+ transient $50\%$ relaxation time, and LCR period were automatically calculated by the software as described before (Figure 1C) [43]. ## 4.4. Drugs If was blocked with 3 μmol/L IVA (Toronto Research Chemicals, North York, ON, Canada). INa was blocked with 5 μmol/L TTX (Alomone Labs, Jerusalem, Israel). ICaT was blocked with 10 μmol/L TMR (Sigma-Aldrich, Saint Louis, MO, USA). All drugs were initially dissolved in dimethyl sulfoxide (DMSO). Images were recorded at least 5 min after TTX or TMR application, and at least 15 min after IVA application. ## 4.5. Statistics Experimental results are presented as mean ± SEM. Statistical comparisons between baseline and post-treatment were performed with one-way ANOVA and paired t-tests. Differences were considered statistically significant at $p \leq 0.05.$ In each experiment, N refers to the number of SAN preparations. ## 4.6. Computational Model To investigate the internal dynamics of SAN cells treated with different blockers, we used our previously published computational model of the mouse SAN cell [13], which itself based on previous publications [5,44,45,46,47,48,49,50,51,52]. The model contains 43 state variables and differential equations describing the dynamics of cell membrane potential, ion currents, Ca2+ cycling, and post-translational modifications during an AP (Figure 1D). The model initial conditions (Table S1) and constants (Table S2) were based on the experimental results. The IVA effect was simulated by reducing the If maximal conductance coefficient, gIf, to $10\%$ of its value (Figure 1E). The TTX effect was simulated by reducing gNa11, the TTX-resistant channel maximal conductance coefficient, to $80\%$ of its value and gNa15, the TTX-sensitive channel maximal conductance coefficient, to $50\%$ of its value (Figure 1F). Current clamps were simulated by bringing the specific current to its basal state by an alternation of its maximum conductance coefficient. The software was run in MATLAB (The MathWorks, Inc., Natick, MA, USA). 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--- title: Spleen Toxicity of Organophosphorus Flame Retardant TDCPP in Mice and the Related Mechanisms authors: - Lanqin Cao - Lai Wei - Qiaoyun Du - Ying Su - Shuzi Ye - Kaihua Liu journal: Toxics year: 2023 pmcid: PMC10051780 doi: 10.3390/toxics11030231 license: CC BY 4.0 --- # Spleen Toxicity of Organophosphorus Flame Retardant TDCPP in Mice and the Related Mechanisms ## Abstract Tris(1,3-dichloro-2-propyl) phosphate (TDCPP) is an organophosphorus flame retardant that has been utilized in recent years as a primary replacement for polybrominated diphenyl ethers (PBDEs) in a wide variety of fire-sensitive applications. However, the impact of TDCPP on the immune system has not been fully determined. As the largest secondary immune organ in the body, the spleen is considered to be an important study endpoint for determining immune defects in the body. The aim of this study is to investigate the effect of TDCPP toxicity on the spleen and its possible molecular mechanisms. In this study, for 28 consecutive days, TDCPP was administered intragastrically (i.g), and we assessed the general condition of mice by evaluating their 24 h water and food intake. Pathological changes in spleen tissues were also evaluated at the end of the 28-day exposure. To measure the TDCPP-induced inflammatory response in the spleen and its consequences, the expression of the critical players in the NF-κB pathway and mitochondrial apoptosis were detected. Lastly, RNA-seq was performed to identify the crucial signaling pathways of TDCPP-induced splenic injury. The results showed that TDCPP intragastric exposure triggered an inflammatory response in the spleen, likely through activating the NF-κB/IFN-γ/TNF-α/IL-1β pathway. TDCPP also led to mitochondrial-related apoptosis in the spleen. Further RNA-seq analysis suggested that the TDCPP-mediated immunosuppressive effect is associated with the inhibition of chemokines and the expression of their receptor genes in the cytokine–cytokine receptor interaction pathway, including four genes of the CC subfamily, four genes of the CXC subfamily, and one gene of the C subfamily. Taken together, the present study identifies the sub-chronic splenic toxicity of TDCPP and provides insights on the potential mechanisms of TDCPP-induced splenic injury and immune suppression. ## 1. Introduction Tris(1,3-dichloro-2-propyl) phosphate (TDCPP) is one of the commonly used organophosphorus flame retardants (OPFRs) in a broad range of products, including furniture, buildings, textiles, cars, clothing, and other items [1]. Some polybrominated diphenyl ethers (PBDEs), such as Penta- and Octa-BDE, have been restricted or banned in the EU due to overwhelming evidence that they are environmentally persistent organic pollutants (POPs) [2,3,4]. With its widespread use, TDCPP has been universally distributed to the environment—in the atmosphere, soil, surface water, groundwater and even glaciers that migrate long distances to the poles [1,5]. Besides its prevalence in the environment, TDCPP and its metabolites have also been found in human biological samples such as placenta, breast milk, plasma, and urine in recent years [6,7]. Furthermore, emerging evidence suggests that TDCPP exposure can cause neurological, reproductive, endocrine, hepatic and renal damage [1,8,9]. Notably, it was listed as a known carcinogen on the Proposition 65 list of substances [10,11]. A number of studies have shown that TDCPP induces cytotoxicity through the activation of the mitochondrial apoptosis pathway [12]. Meanwhile, there is also evidence suggesting that TDCPP can induce neuronal damage by triggering the microglia-mediated inflammatory response [13] and secretion of inflammation-like adipokines [14]. In addition, it was demonstrated that TDCPP can disrupt the phagocytosis of human THP-1-derived macrophages through immunosuppression and promote cytokine/chemokine secretion and inflammatory responses [15]. The spleen, a secondary lymphoid organ with hematological and immunological activities, is the body’s largest immune organ. It has the immunological function of identifying pathogens and aberrant cells and removing them; hence, it plays a significant role in the innate and adaptive immune response [16]. Patients treated clinically with splenectomy have a reduced clearance of malaria-hosted red blood cells and a higher risk of other infectious diseases [17]. Therefore, the spleen, as a key immune organ, stores many immune cells and is often regarded as an endpoint for assessing immunotoxin injury [18]. Despite the advances in TDCPP research over the past few years, there is still a lack of adequate understanding of the splenic immunotoxicological properties of this emerging contaminant. Transcriptome analysis techniques are currently an important research tool for conducting toxicity explorations of emerging contaminants. In this study, we identified differential genes based on a transcriptome sequencing platform to provide a basis for understanding the mechanisms of TDCPP-induced inflammatory responses and immune damage in the mice spleen. ## 2.1. Animals and Exposure Male, 4-week-old C57BL/6J mice (initial weight: 18 ± 2 g) were purchased from the Hunan SJA Laboratory Animal Co., Ltd. (SCXK(XIANG)2019-0004). All animal experiments were approved by the Laboratory Animal Welfare Ethical Committee of Central South University (Ethics Approval Code: XYGW-2021-113). The mice were housed in a climate control and pathogen-free room (6 animals/cage, 12 h dark–light cycle, 24 ± 2 °C, 65 ± $25\%$ humidity). After at least 1 week of acclimatation, animals were randomly allocated into two groups using random number tables: the control and the TDCPP groups. The TDCPP group was intragastric administrated (i.g) with TDCPP (purity: $95\%$; Bide Pharmaceutical Technology Co., Ltd., Shanghai, China) of 300 mg/kg a day for 28 consecutive days. Corn oil was used in this study as the TDCPP solvent. TDCPP had a reported oral LD50 of 2670 mg/kg in male mice [19]. A rather high dose of 300 mg/kg (approximately $\frac{1}{10}$ LD50) was used as the oral dose in this investigation to examine the subacute toxic effects. The 24 h water and food intakes on the 7th, 14th, 21st and 28th days of exposure were measured. Every three days during the same period, the weight of the mice was measured. ## 2.2. Tissue Collection Anesthesia was induced in mice using sodium pentobarbital (i.p. 40 mg/kg). Peripheral blood sampling was performed after the mice were anesthetized. Upon tissue harvest, the spleen was divided into two pieces. One piece was instilled with cold $0.9\%$ saline, fixed in $4\%$ paraformaldehyde for 4 h at 4 °C and stored for further processing. The other piece of spleen was flash frozen in liquid nitrogen and stored at −80 °C until further processing. ## 2.3. Hematoxylin-Eosin (H&E) Staining All specimens underwent $4\%$ paraformaldehyde fixation at 4 °C for 4 h before being moved to an ethanol gradient for dehydration. Dehydrated samples were then placed in a mixed solution of xylene and paraffin for paraffin permeation, followed with dewaxing with xylene and ethanol gradients in turn. After soaking and staining with hematoxylin and eosin dye, respectively, ethanol, xylene and neutral resin were used to dehydrate and seal the sections and make them transparent. An OLYMPUS BX53 digital camera and the DP73 controller software were used to take all of the digital pictures (×200). According to the standard classification, normal [0], mild [1], moderate [2], severe [3], and very severe [4] categories were used to determine the degree of splenic tissue damage. Six visual fields/mouse pathology scores were used to compute the severity of the damage for each group of at least three mice. The specific operation is based on the methods used in a prior investigation [20]. ## 2.4. Immunohistochemistry (IHC) Staining During the IHC staining of spleen tissue, the sample was paraffin-embedded, sectioned, and dewaxed in the same manner as the previous H&E staining. Then, the sections were heated in a microwave oven for antigen retrieval. Prior to the incubation of the primary antibody, sections were immersed in $3\%$ hydrogen peroxide solution for 15 min at room temperature and incubated in $1\%$ BSA for 15 min at room temperature to block. Primary antibody solutions at different dilutions were prepared and incubated overnight at 4 °C in humid boxes; then, the appropriate secondary antibody was added, and the mixture was left to sit at room temperature for 60 min in the dark. This was followed by DAB coloring, counterstaining with hematoxylin, dehydration with ethanol, and making it transparent with xylene, and resin that is neutral was used for sealing. Finally, under a 400-fold microscope (OLYMPUS, Tokyo, Japan, BX53 & DP73), at least three regions of the spleens of each group of mice were observed and statistically analyzed. The intensity of the stained signals was measured and analyzed using Image-Pro Plus 6.0 image analysis software (Media Cybernetics, Inc. Silver Spring, MD, USA) according to previous studies and the average density of the digital images was calculated [21]. The mean density of the digital images (×400) was designated as representative NF-κB/IFN-γ/TNF-α/IL-1β staining intensity (indicative of relative NF-κB/IFN-γ/TNF-α/IL-1β expression levels). All picture capture sessions used the same microscope settings, and the experimenters were unaware of the treatment groups in order to perform image quantification. Antibodies used in this study: anti-NF-κB p65 (Wanleibio, China, WL01980), anti-IFN-γ (Wanleibio, China, WL02440), anti-TNF-α (Wanleibio, China, WL01896), anti-IL-1β (Wanleibio, China, WLH3903), and HRP Goat Anti-Rabbit IgG (H + L) (thermoFisher, Waltham, MA, USA, #31460). ## 2.5. Terminal dUTP Nick-End Labeling (TUNEL) Assay The principle of the TUNEL assay is that, when apoptosis occurs, some DNA endonucleases will be activated. These endonucleases will cut off genomic DNA between nucleosomes. When genomic DNA breaks, exposed 3′-OH can be added with fluorescein dUTP under the catalysis of terminal deoxynucleotidyl transferase (TdT), Td, which can be detected with a fluorescence microscope and through flow cytometry. The specific operation was carried out according to previous research methods [22]. To quantify the image (×400) of the final spleen tissue, unified microscope settings (OLYMPUS, Tokyo, Japan, BX53 & DP73) were maintained in all image acquisition processes, with an excitation wavelength of 450 nm and emission wavelength of 520 nm. The spleen apoptosis of each group of three animals was examined for quantitative analysis by TUNEL assay as follows: The number of apoptotic cells and the total number of cells in at least three fields of view were counted for each animal, and the apoptotic rate in the three fields of view was calculated and the mean value was taken. The apoptosis rate was calculated according to the following formula: Apoptosis rate = number of apoptotic cells/total number of cells. ## 2.6. Western Blot (WB) Analysis The radio immunoprecipitation assay (RIPA) strong lysate (Beyotime Biotechnology, Shanghai, China, P0013B) was used to lyse the spleen tissues for 30 min, after which they were centrifuged at 12,000× g for 15 min at 4 °C. The quantification of protein concentrations was performed using a BCA protein concentration detection kit (Beyotime Biotechnology, Shanghai, China, P0010). The tissue proteins were first incubated to primary antibodies at 4 °C overnight, and then to matching secondary antibodies for 1 h, and finally they were incubated using the LumiBest ECL substrate solution kit for visualization (ShareBio, Shanghai, China, SB-WB011). The protein band intensity was measured using Image-J software. Antibodies used in this study: anti-TNF-α (Immunoway, Suzhou, China, YT4689, 1:1000), anti-IL-1β (Beyotime Biotechnology, Shanghai, China, AF7209), anti-NF-κB p65 (ABclone, Wuhan, China, A2547, 1:1000), anti-IFN-γ (Immunoway, Suzhou, China, YT2279, 1:1000), anti-Caspase-3 (Proteintech, Wuhan, China, 19677-1-AP, 1:1000) anti-Bcl-2 (ABclone, China, A19693, 1:1000), anti-Bax (Proteintech, China, 50599-2-lg, 1:1000), anti-Cytochrome C (Proteintech, China, 10993-1-AP, 1:1000), anti-β-actin (MultiSciences, Hangzhou, China, #HA-R1207-1-200, 1:1000), HRP Goat Anti-Rabbit IgG (H + L) (Abclone, China, #AS014, 1:4000), and HRP Goat Anti-Mouse IgG (H + L) (Abclone, China, #AS003, 1:4000). ## 2.7. RNA Extraction and cDNA Library Generation Total RNA was isolated from each group of two mice spleen tissues, 100 mg/spleen tissue, using the TRIzol® Reagent (Magen) in accordance with the manufacturer’s instructions. The Nanodrop ND-2000 system from Thermo Scientific (Waltham, MA, USA) was used to measure RNA concentrations based on the A260/A280 absorbance ratio, and the Agilent Bioanalyzer 4150 system was used to determine the RNA integrity number (RIN) (Agilent Technologies Inc., Santa Clara, CA, USA). Only approved samples were utilized to build the library. Following the manufacturer’s instructions, paired-end libraries were created using an ABclonal mRNA-seq Lib Prep Kit (ABclonal, Wuhan, China). Using oligo (dT) magnetic beads and divalent cations at high temperatures in ABclonal First Strand Synthesis Reaction Buffer, the mRNA was isolated from 1 μg of total RNA. Then, using mRNA fragments as templates, first-strand cDNAs were created using random hexamer primers and Reverse Transcriptase (RNase H), and second-strand cDNAs were created using DNA polymerase I, RNAseH, buffer, and dNTPs. The prepared paired-end library was created by adapter-ligating the generated double stranded cDNA fragments. For PCR amplification, adaptor-ligated cDNA was utilized. On the Agilent Bioanalyzer 4150 system, library quality was evaluated after PCR products were purified to use the AMPure XP system. Finally, 150 bp paired-end reads were produced using the Illumina Novaseq 6000 (Illumina, San Diego, CA, USA) to sequence the library preparations. ## 2.8. RNA-Seq Data Analysis On the Illumina platform, RNA-Seq data analysis was carried out. Shanghai Applied Protein Technologies was used for all analyses. These are the main software elements and parameters. ## 2.8.1. Quality Control Fastq-format raw data (or raw reads) were initially processed using custom Perl scripts. In this step, the adapter sequence must be removed, followed by the filtering out of low-quality read (low-quality reads are those where the proportion of lines with a string quality value of less than or equal to 25 accounts for more than $60\%$ of the entire reading) and N read (N reads are those where the base information cannot be determined) ratios greater than $5\%$ in order to produce clean reads suitable for further analysis. ## 2.8.2. Mapping HISAT2 software (version: 2.1.0, http://daehwankimlab.github.io/hisat2/ format: 29 November 2022.) was then used to align clean reads sequentially to the reference genome in orientation mode to produce mapped reads [23]. ## 2.8.3. Quantification of Gene Expression Level The amount of reads that were mapped to each gene was counted using Feature Counts (version: 2.0.0, http://subread.sourceforge.net/ format: 29 November 2022.). The length of each gene and the number of reads mapped to it were used to compute the FPKM of each gene. ## 2.8.4. Differential Expression Analysis Differentially expressed genes (DEGs) with \|log2FC\| > 1 and p-value 0.05 were regarded to be significantly different expressed genes. Differential expression analysis was carried out using DESeq2 (version: 1.34.0, format: 29 November 2022.) [ 24]. ## 2.8.5. Enrichment Analysis The functional enrichment of differential genes can be explained through the Gene Ontology (GO) and KEGG enrichment analysis of differential genes, which can also shed light on the variations between samples at the level of gene function. For KEGG pathway enrichment analysis and GO function enrichment, we used the cluster Profiler R software package. The GO or KEGG function is deemed considerably enriched when $p \leq 0.05$ [25,26]. ## 2.9. Quantitative Reverse-Transcription PCR(RT-qPCR) Analysis Using RNA isolater Total RNA Extraction Reagent (Vazyme, Nanjing, China, R401-01) and the FastKing RT kit (with gDNA) (Tiangen, Beijing, China, KR116), spleen tissue from six mice in each group at 100 mg/spleen tissue was extracted from total RNA samples and reverse-transcribed into cDNA. The reverse-transcription reaction conditions were 42 °C for 3 min, 42 °C for 15 s, 95 °C for 30 min, and 0 °C throughout. SuperReal PreMix Plus (SYBR Green) (Tiangen, China, FP205) was used to perform qPCR on the CFX96 System (Bio-Rad, Hercules, CA, USA). The main mixtures were prepared and the cycle conditions were set (predenaturation stage at 95 for 15 min × 1 cycles; PCR reaction stage denaturation at 95 for 15 s; annealing/elongation at 63 for 30 s × 45 cycles; and melting curve stage at 95 °C for 15 s, 60 °C for 60 s, and 95 °C for 15 s × 1 cycles). The sequences of the primers used for the qPCR validation of RNA-Seq Data are listed in Table 1. The 2−∆∆CT method was used to compute the relative expressions of genes, and they were then normalized to the Glyceraldehyde-3-phosphate dehydrogenase reference gene (Gapdh). ## 2.10. Statistical Analysis In this work, all data were collected from at least three different experiments and are expressed as mean ± standard deviation (SD). A two-sample t-test was used to statistically analyze differences between the two groups. At a level of p-values < 0.05, differences were deemed significant. The experimental data were analyzed and plotted using SPSS 26 and GraphPad 9.0 software. ## 3.1. Oral Exposure to TDCPP Caused Systematic Response and Induced Splenic Damage In Figure 1A, the chemical formula for TDCPP is displayed. One of the most crucial measures of an animal’s health status is its body weight. Therefore, at the same time of day, we measured the weight of mice in each group on Days 0, 3, 6, 9, 12, 15, 18, 21, 24 and 27 of TDCPP exposure. The body weights of all animals were similar at the beginning before TDCPP exposure. Starting from day 3, compared to the control group, the average body weight of mice in the TDCPP group was significantly lower (Figure 1B). Similarly, animals in the TDCPP group started to have significantly reduced 24 h water and food intake since day 14 and day 7, respectively (Figure 1C,D). In addition, as shown by the H&E staining of spleen tissue (Figure 1E), the white pulp of mice spleen in the TDCPP group was expanded and fused, with a blurry boundary, and the red pulp color was significantly deepened due to vascular expansion. Additionally, there was a significant difference in the splenic pathological damage scores between the two groups of animals, which showed a significantly higher TDCPP than the control group. ## 3.2. Exposure to TDCPP Activated the NF-kB Pathway and Induced Inflammation in the Spleen The NF-κB signaling pathway is involved in physiological and pathological processes, such as infection, immune regulation, inflammatory reaction and tumor formation [27]. Therefore, to investigate the role of potential mechanisms of inflammatory response in splenic tissue injury by TDCPP, we analyzed the protein expression of NF-κB/IFN-γ/TNF-α/IL-1β in mice spleens using IHC and WB, respectively. As indicated by the IHC staining and quantification in Figure 2A, the expressions of NF-κB, IFN-γ, TNF-α and IL-1β were all more highly expressed in the TDCPP group compared to the control group. Similar trends were found by immunoblotting NF-κB, IFN-γ, TNF-α and IL-1β in total protein lysates of spleen tissues from control or TDCPP-treated mice (Figure 2B). IL-1β is a pro-inflammatory cytokine produced mainly by activated monocytes and epithelial cells. Pro-IL-1β is cleaved by caspase-1 into cleaved-IL-1β, which is the mature form of IL-1β and a good indicator of caspase-1 activity. Overall, these results indicate that the subchronicintragastric exposure of TDCPP may trigger an inflammatory response in the spleen through the activation of the NF-κB/IFN-γ/TNF-α/IL-1β pathway. ## 3.3. TDCPP-Induced Apoptotic Cell Death in the Spleen TDCPP was shown to increase the activities of caspase-3 and caspase-9, promote the expression of Bax, inhibit the expression of Bcl-2, and finally lead to apoptosis through the mitochondrial apoptosis pathway [1]. Apoptosis can also be induced through the activation of death receptors, such as the interaction of TNF-α with TNF-αR [28]. As shown in Figure 3A, the proportion of TUNEL-positive cells in the spleen tissues from the TDCPP group was significantly higher than that of the control group. Consistent with the TUNEL staining, pro-caspase 3 and cleaved-caspase 3 expressions were increased in the TDCPP group in comparison to the control group. The expression of BAX and cytochrome C was also increased in TDCPP group. Further, there was a decrease in Bcl-2 expression in the TDCPP group. The above results show that TDCPP exposure leads to the apoptosis of mice spleen tissue cells via the mitochondrial apoptotic pathway. ## 3.4. RNA-Seq Analysis of Mice Spleen Tissue To get a broader picture of the changes post TDCPP exposure in the spleen at the transcriptome level, we performed RNA-seq analysis on RNAs isolated from the spleens. A total of 47,708,220 genes were identified, $97.29\%$ of the sequence bases could be aligned to the genome, and the junction reads added up to more than $27.71\%$ (Table S1). Gene expression levels were calculated for each sample in both groups, and the overall distribution of sample gene expression and inter-sample correlation were analyzed. As a result, 1025 DEGs in mice spleen were identified after TDCPP stimulation (Table S1). Overall, 23 upregulated and 1002 downregulated DEGs were identified in the TDCPP vs. control groups, as is shown in the DEG volcano plot (Figure 4A), statistical table of differential gene expression (Table S2), and DEG cluster heatmap (Figure 4B). ## 3.5. GO Analysis To identify the function of DEGs in the spleen of mice after TDCPP exposure, a GO enrichment analysis of DEGs was carried out based on the GO database. The results show the top 10 GO terms according to secondary classification terms, biological process (BP), molecular function (MF) and cellular component (CC). In the BP annotation category, the upregulated genes were mainly associated with cell adhesion, while the downregulated genes were enriched for the immunologic process in the TDCPP vs. control groups (Figure 5A–C). In the MF and CC categories, the upregulated genes were in the intracellular junctional components, while the downregulated genes were enriched for cell membrane components in the TDCPP vs. control groups (Figure 5D–F). ## 3.6. KEGG Enrichment Analysis We found 264 markedly impacted metabolic and signaling pathways using the KEGG pathway as a unit and the reference genome as the background. The KEGG enrichment pathway includes the top 40 up- and downregulated genes, as shown in Figure 6A, including: environmental information processing (signal transduction, signaling molecules and interaction), cellular processes (cellular community–eukaryotes, transport and catabolism, cellular community–eukaryotes), human diseases (infectious disease: parasitic, cardiovascular disease, environmental adaptation, cancer: overview, immune disease, infectious disease: bacterial), organismal systems (development and regeneration, immune system, digestive system, circulatory system, endocrine system), and metabolism (lipid metabolism, xenobiotics biodegradation and metabolism). To further explore the effects of TDCPP on splenic immune and inflammatory responses, we noted the following ten KEGG pathways: complement and coagulation cascades, hematopoietic cell lineage, platelet activation, chemokine signaling pathway, neutrophil extracellular trap formation, ECM-receptor interaction, viral protein interaction with cytokine and cytokine receptor, cytokine-cytokine receptor interaction. Chemokines play a key role in inflammation and immunity by interacting with receptors to regulate the targeted migration of immune cells, remove sources of infection, and promote wound healing, among other functions [29]. Therefore, to investigate the effect of TDCPP on the spleen, we chose the cytokine–cytokine receptor interaction pathway for validation (Figure 6B,C). We validated nine candidate genes for the cytokine–cytokine receptor interaction pathway, including: Ccr1l1, Ccr3, Ccr10, Ccl24, Ppbp, Pf4, Cxcl10, Ackr3, and Xcr1. ## 3.7. Validation of Gene Expression As shown in Figure 6D, TDCPP significantly inhibited the expressions of Ccr1l1, Ccr3, Ccr10, Ccl24, Ppbp, Pf4, Cxcl10, Ackr3, and Xcr1 mRNAs in splenic tissue transcriptome sequencing, demonstrating the ability of TDCPP to inhibit the cytokine–cytokine receptor interaction pathway. As noted, we validated nine candidate genes. Consistent with RNA-Seq data, according to qRT-PCR analysis, compared to the control group, the expressions of chemokine-related genes, Ccr1l1, Ccr3, Ccr10, Ccl24, Ppbp, Pf4, Cxcl10, Ackr3, and Xcr1 in spleen tissue were significantly reduced ($p \leq 0.05$) (Figure 6D). ## 4. Discussion TDCPP has been widely used in fire-susceptible items as one of the main PBDE alternatives over the past 20 years [1]. TDCPP, however, could leak out of items into different environmental media over the course of their lifetimes, in the same way that PBDEs do. For instance, through the industrial processing of food products, TDCPP entered food and was eaten by humans as a result [30]. Over the past few decades, studies on the toxicological effects of this product have mainly focused on reproduction [31], development [32], nerve toxicity [33], and endocrine disruption [34]. Research on immune system damage is still unclear, especially regarding the mechanisms of injury. In the present study, we employed environmental toxicology and transcriptome analysis techniques to determine the immunotoxicity of TDCPP exposure to mice spleen. As the largest secondary immune organ in our body, the spleen is an important line of defense for organisms against disease and invasion by harmful foreign bacteria and viruses, and it is susceptible to environmental perturbations. The spleen histomorphology of TDCPP-treated mice showed pathological changes. These pathomorphological alterations in the spleen are similar to previous findings, which showed that BDE-209 suppresses splenic cell immune and physiological functions by inducing inflammation and apoptosis, ultimately leading to splenic atrophy [35] and cadmium-induced spleen toxicity in mice [36], suggesting that these environmental pollutants cause splenic toxicity in a similar way. Body weight is one of the important indicators of the health of organisms and is influenced by several factors, such as excessive or insufficient energy intake and abnormal energy consumption, such as excessive exercise and disease. Therefore, when monitoring the weight of each group of mice, we also monitored their 24 h water intake and food intake every 7 days, respectively. After excluding the effects of drinking and feeding from the i.g operation, we found that TDCPP treatment might inhibit drinking and feeding in mice. This might be one of the main reasons for the weight change of TDCPP mice in a short time after treatment. Similarly, Sun et al. also noted in their study that rapid weight loss is primarily caused by a decrease in energy intake and not by an increase in energy expenditure or cachexia [37]. The inflammatory cytokine TNF-α can promote the inflammatory response by activating the NF-κB signaling pathway and further regulating the expression of downstream interleukin-related genes, adhesion factor-related genes, and other genes [38,39,40]. Our results are supported by previous reports of increased expression of NF-κB, TNF-α, and IL-1β in splenic tissue after TDCPP treatment, which further leads to splenic inflammation [39]. Moreover, some studies have also carried out in vivo and ex vivo tests that showed that TDCPP can increase the expressions of the pro-inflammatory factors Il-1beta and Tnf-mRNA in hippocampus neuronal cells, resulting in the induction of neurological inflammation [13]. IFN-γ is a cytokine with immune-regulatory, antivirus, antitumor, and antiparasitic effects, and it plays an essential role in maintaining the cellular immunity of the body, secreted by activated NK cells and T cells [41]. In a mouse model of aplastic anemia induced by irradiation and spleen–thymus lymphocyte infusion, the levels of the cytokines IL-6, IL-8, IL-17, TNF-α, and IFN-γ were increased in peripheral blood and bone marrow, and an immunoinflammatory response occurred [42]. Interestingly, this is consistent with our finding of increased IFN-γ and TNF-α expression in the spleen when the spleen was subjected to TDCPP. The above evidence suggests that TDCPP-induced inflammatory responses in the spleen are accompanied by the activation of the NF-κB signaling pathway. In addition, TDCPP caused apoptosis by altering the transcriptional levels of bcl-2, bax, and caspase 3 genes, which ultimately led to apoptosis in SH-SY5Y cells [13]. In normal human-skin keratinocytes, TDCPP caused the protein expression of D1, CDK2, CDK6, and Bcl-2, in addition to boosting Bax and Caspase-3 expression to cause apoptosis and cell cycle arrest [43]. Corresponding to this, in our study, we discovered that in the spleen tissues of mice given TDCPP, the relative expressions of caspase 3, BAX, and cytochrome C proteins were elevated, whereas the relative expressions of Bcl-2 proteins were lowered. Thus, the activation of mitochondrial apoptosis pathways is important for TDCPP-induced cytotoxicity. It is worth noting that some studies suggest that the impairment of splenic immune function may be via immunosuppression and the activation of the NF-B signaling pathway [44,45]. According to the GO analysis, the DEGs were mainly related to the immunologic process, metabolic process, and cellular components. Therefore, these results are almost consistent with our conjecture that TDCCP induces immunoinflammatory toxicity in mouse spleen. It also provides a foundation for the selection of candidate genes to further study the molecular mechanism of immunoinflammatory-related toxicity of TDCPP in the spleen. In addition, the KEGG pathway analysis identified eight pathways related to immunoinflammatory responses. Considering the purpose of this study and the number of differentially enriched genes, we selected the cytokine–cytokine receptor interaction pathway as the subsequent point of interest. We only focused on nine candidate genes for the cytokine–cytokine receptor interaction pathway, including four genes of the CC subfamily, four genes of the CXC subfamily, and one gene of the C subfamily. The development and homeostasis of the immune system depend on chemokines, which are involved in all immunological and inflammatory responses, whether they are protective or damaging [46]. CD4+ and CD8+ lymphocytes, dendritic cells, eosinophils, macrophages, monocytes, and NK cells are immune system cells that depend on CC family chemokines for survival [47], as does tumor development. In individuals with immunological thrombocytopenia, the expression of the Th1- and Th2-associated chemokine CCR3 gene was reduced [48], and animals lacking the chemokine receptor CCR1 had elevated Th1 responses and glomerular damage in nephritis [49]. In addition, CCL24 can combine with CCR3 to recruit eosinophils and tumor-associated macrophages, and immune function is limited when CCR3/CCL24 is suppressed [50]. Moreover, research has demonstrated that CXC chemokines either promote or inhibit immunity, which in turn affects the development of cancer [51]. The XCL1-XCR1 axis plays an important role in ensuring effective CD8 T cell-mediated cytotoxic immune responses, such as the ability of XCR1 to promote the CD8 DC activation of early CD8 T cell-mediated defense against intracellular pathogenic bacteria [52]. In this study, TDCPP significantly inhibited Ccr1l1, Ccr3, Ccr10, Ccl24, Ppbp, Pf4, Cxcl10, Ackr3, and Xcr1 genes expression in spleen tissue homogenates according to RNA-Seq and qRT-PCR, which indicates that the cytokine–cytokine receptor interaction pathway is a critical toxic target of TDCPP. ## 5. Conclusions In summary, by combining cell biological assessment and transcriptome analysis techniques, we revealed the gene expression changes that were affected by TDCPP. First, mice treated with TDCPP i.g for 28 consecutive days were found to have altered general conditions and induced pathological changes in the spleen. Second, analysis of relevant inflammatory factors in splenic tissues showed that TDCPP can activate mitochondrial apoptotic pathways and alter apoptosis-related proteins. Third, RNA-seq analysis showed that TDCPP induced changes in eight KEGG pathways associated with immune and inflammatory responses in the spleen. Subsequently, qRT-PCR was used to validate 17 genes of the cytokine–cytokine receptor interaction pathway and revealed that TDCPP caused immunosuppression and induced an inflammatory response to toxins in the spleen. Accordingly, our study confirmed the immunotoxicity of TDCPP exposure to mice characterized by an inflammatory reaction, the activation of mitochondrial apoptosis pathways, and the inhibition of the expression of chemokines and their related receptors, causing an immunosuppressive effect. ## References 1. Wang C., Chen H., Li H., Yu J., Wang X., Liu Y.. 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--- title: The Polymorphic Membrane Protein G Has a Neutral Effect and the Plasmid Glycoprotein 3 an Antagonistic Effect on the Ability of the Major Outer Membrane Protein to Elicit Protective Immune Responses against a Chlamydia muridarum Respiratory Challenge authors: - Anatoli Slepenkin - Sukumar Pal - Steven Hoang-Phou - Abisola Abisoye-Ogunniyan - Amy Rasley - Patrik D’haeseleer - Matthew A. Coleman - Luis M. de la Maza journal: Vaccines year: 2023 pmcid: PMC10051784 doi: 10.3390/vaccines11030504 license: CC BY 4.0 --- # The Polymorphic Membrane Protein G Has a Neutral Effect and the Plasmid Glycoprotein 3 an Antagonistic Effect on the Ability of the Major Outer Membrane Protein to Elicit Protective Immune Responses against a Chlamydia muridarum Respiratory Challenge ## Abstract Chlamydia trachomatis is the most common bacterial sexually transmitted pathogen. The number of chlamydial infections continuous to increase and there is an urgent need for a safe and efficacious vaccine. To assess the ability of the Chlamydia muridarum polymorphic membrane protein G (PmpG) and the plasmid glycoprotein 3 (Pgp3) as single antigens, and in combination with the major outer-membrane protein (MOMP) to induce protection, BALB/c mice were immunized utilizing CpG-1826 and Montanide ISA 720 VG as adjuvants. Following vaccination with MOMP, significant humoral and cell-mediated immune responses were observed, while immunization with PmpG, or Pgp3, elicited weaker immune responses. Weaker immune responses were induced with MOMP+Pgp3 compared with MOMP alone. Following the intranasal challenge with C. muridarum, mice vaccinated with MOMP showed robust protection against body-weight loss, inflammatory responses in the lungs and number of Chlamydia recovered from the lungs. PmpG and Pgp3 elicited weaker protective responses. Mice immunized with MOMP+PmpG, were no better protected than animals vaccinated with MOMP only, while Pgp3 antagonized the protection elicited by MOMP. In conclusion, PmpG and Pgp3 elicited limited protective immune responses in mice against a respiratory challenge with C. muridarum and failed to enhance the protection induced by MOMP alone. The virulence of Pgp3 may result from its antagonistic effect on the immune protection induced by MOMP. ## 1. Introduction C. trachomatis is the most common sexually transmitted bacterial pathogen in the world and can also cause ocular, respiratory and gastrointestinal infections [1,2]. C. trachomatis infections during pregnancy can significantly affect neonatal outcomes [3]. Although screening programs may have decreased the number of patients who develop long-term sequelae, they have failed to control the spread of this pathogen and the accumulated costs of caring for infected patients continues to increase [4,5,6]. Vaccination trials in humans and non-human primates to protect against C. trachomatis (trachoma), using inactivated whole organisms yielded important findings [7,8,9]. Several vaccine formulations were protective for 2–3 years after immunization, and the protection was serovar/serogroup specific. However, upon re-exposure to Chlamydia, some individuals developed a hypersensitivity reaction and the possibility that an antigenic component of Chlamydia present in these inactivated vaccines mediated these adverse reactions motivated the search for a subunit vaccine [7,9,10,11,12,13,14,15,16,17]. A subunit vaccine that will provide protection against all C. trachomatis serovars will require the selection of well-conserved antigens among clinical isolates. The chlamydial major outer membrane protein (MOMP) was initially identified as a potential protective antigen when the serovar/serogroup protection observed during the trachoma vaccine trials was found to correlate with the DNA sequence of this protein [18,19,20]. MOMP is a 40 kDa protein that forms a 120 kDa homotrimer and constitutes ~$60\%$ of the outer membrane protein mass of chlamydia. MOMP has four surface-exposed variable domains (VD), and five constant domains (CD) located in β-barrels that cross the outer membrane [21,22,23,24]. This protein is highly antigenic, containing both B and T-cell epitopes, and is currently the most promising vaccine antigen having completed a Phase I clinical trial [12,16,17,21,24,25,26,27,28,29,30,31,32]. Wang and Grayston [33,34,35] published findings based on protection studies in mice and serological analyses that grouped the 15 C. trachomatis serovars into three complexes C (C, J, H, I, A, K, L3), B (B, Ba, E, D, L1, L2) and G/F. They identified a senior to junior relationship within each complex such that the senior serovar, for example, C, protected against all the junior serovars, while the junior serovar, L3, protected only against itself. These findings have been supported in several studies, including in the genital challenge mouse model using recombinant MOMP [36]. Mice immunized with C. trachomatis serovar D MOMP were protected against shedding and infertility when challenged with serovars D or E, but not when challenged with serovar F [36]. To elicit protection against all 15 major serovars, a vaccine will require at least MOMP from the senior serovars of each of the three complexes. As an alternative, or in conjunction with MOMP, other more conserved chlamydial antigens may induce broad cross-serovar protection [17,37,38,39]. Humans and mice infected with Chlamydia mount an immune response to hundreds of proteins [40,41,42]. Using the C. trachomatis and C. muridarum mouse models, several investigators have reported that some of the more conserved proteins, such as the polymorphic membrane proteins (Pmp) and the plasmid glycoprotein 3 (Pgp3), can protect mice against genital and/or respiratory challenges [43,44,45,46,47,48]. C. trachomatis and C. muridarum, have nine pmp genes encoding Pmps (A, B, C, D, E, F, G, H, I) with MWs ranging from ~100–150 kDa [19,45,49,50,51,52]. Pmps have three functional domains: 1) a cleavable sec-dependent N-terminal signal for translocation through the cytoplasmic membrane, 2) a C-terminal β-barrel sequence for outer membrane insertion, and 3) a passenger domain for cell surface localization. Pmps are located on the chlamydial cell surface and have the capacity to adhere to the host cell [49,53,54,55,56]. In 2006, Crane et al. [ 53] reported in vitro assays whereby antibodies to PmpD neutralized all C. trachomatis serovars. Karunakaran et al. 2008 [57], using an immunoproteomic approach, discovered T-cell epitopes in four C. muridarum Pmps (E, F, G and H). Vaccination of C57BL/6, BALB/c, and C3H/HeN mice with the passenger domains from each of these four proteins (E, F, G and H), accelerated vaginal clearance of C. muridarum, while PmpG elicited the best overall protection [57]. In the intranasal challenge model, the passenger domains of the nine C. trachomatis serovar E Pmps, adjuvanted with CpG-1826 plus Montanide ISA 720 VG, were used to vaccinate BALB/c mice [58]. Based on disease burden and the number of C. muridarum IFU recovered from the lungs, mice immunized with C. trachomatis serovar E PmpC, were the best protected against a respiratory challenge. Limited protection was also observed in mice immunized with PmpG or H, suggesting that Pmps could elicit C. trachomatis cross-serovar and cross-species protection. Most of the C. trachomatis isolates, and C. muridarum, have a plasmid that encodes for eight proteins including Pgp3 [59,60,61]. Pgp3 (MW 28 kDa) forms an ~84 kDa homotrimer and has been found in the membrane of Chlamydia, and in the cytoplasm of the host cells [62,63,64]. Antibodies from humans and mice bind to the homotrimer but not to the monomer [41,65]. Donati et al. [ 43] vaccinated C3H/HeN mice with a DNA plasmid expressing C. trachomatis serovar D Pgp3 and a control group with the same plasmid containing an irrelevant insert. Mice vaccinated with the Pgp3 plasmid developed systemic and mucosal immune responses. As determined by the number of positive salpinx cultures, mice vaccinated with the Pgp3 plasmid were partially protected against a vaginal challenge with serovar D. Intranasal vaccination of mice with a plasmid expressing C. trachomatis serovar D pORF5 (coding for Pgp3), were challenged vaginally with C. muridarum [66]. Following immunization, significant antigen-specific Th1 responses and antibody levels were detected. Bacterial shedding, length of time of shedding, and upper genital tract inflammation were reduced in the pORF5 immunized animals. Similar results were obtained by Luan et al. [ 44] using purified Pgp3 for vaccination. In this study, we used C. muridarum recombinant MOMP, PmpG and Pgp3 proteins, alone and in combination, as vaccine antigens to establish their ability to induce humoral and cell-mediated immune responses, and to protect mice against a respiratory challenge with C. muridarum. The respiratory challenge route was used as a screening method to identify protective antigens that can then be tested in the genital challenge model. To induce both humoral and cell-mediated immune responses, CpG-1826, a TLR-9 agonist that elicits Th1 responses, and Montanide ISA 720 VG, a non-TLR agonist that stimulates Th2 responses, were used as adjuvants [25,67]. Our results show that mice vaccinated with MOMP mounted robust protective immune responses, while animals vaccinated with PmpG, or Pgp3, exhibited weaker immune responses. Furthermore, these two antigens in combination with MOMP, failed to enhance the protection induced by MOMP alone. Importantly, Pgp3 exerted an antagonistic effect on the protection elicited by MOMP, a finding that may explain its role as a Chlamydia virulence factor [68]. ## 2.1. C. muridarum Stocks The C. muridarum (MoPn; strain Nigg II; previously called Chlamydia trachomatis mouse pneumonitis) was purchased from the American Type Culture Collection (Manassas, VA, USA), and was grown in HeLa-229 cells. Elementary bodies (EB) were purified and stored at −80°C in sucrose phosphate–glutamate (SPG) buffer, as previously described [24]. ## 2.2. Cloning, Expression and Purification of C. muridarum Proteins C. muridarum EB, were used to isolate genomic DNA with the Wizard Genomic DNA Purification kit (Promega Corporation, Madison, WI, USA). C. muridarum DNA fragments used for cloning were obtained by PCR. MOMP was amplified, cloned, expressed and purified as previously described [26]. PCR-amplified DNA harboring C. muridarum pgp3 and PmpG (TC263) genes were cloned into the NcoI-XhoI sites of the pET-45b(+) vector (Novagen, Madison, WI, USA) under the control of the T7 promoter, using the following primers (Integrated DNA Technologies Inc., Coralville, IA, USA): Pgp3-forward—5′-GCAGGTACCATGACAGAACCTCTTACAGATC-3′; Pgp3-reverse—5′-GCACTCGAGTTAAGTGTTTTTTTGAGGTATC-3′ (GenBank AAF39719.1). PmpG-forward—5′-GAGGGTACCATGGCTCGAATAGGTGGAGG-3′, PmpG-reverse—5′-GACCTCGAGTTAAGCTACGCGCTCCGGACCAGGA-3′ (GenBank AE002160). The pgp3 DNA fragment codes for 240 amino acids and the PmpG for 410 amino acids, corresponding to the passenger domain of PmpG. The ligated vectors were used to transform E. coli DH5-alpha (New England BioLabs, Ipswich, MA, USA) competent cells. Resulting clones were selected and checked by PCR using DreamTaqTM Green PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, USA) for the appropriate insert size. To confirm the proper sequence of the insert and assure the in-frame cloning, selected clones were sequenced by GENEWIZ Inc., from Azenta Life Sciences (South Plainfield, NJ, USA). E. coli BL21(DE3) (New England BioLabs) harboring either pET-45b(+)-pgp3, or pET-45b(+)-pmpG, were cultured at 37 °C with aeration and induced with 0.5 mM isopropyl-β-d-thiogalactopyranoside (IPTG) at 37 °C for 6 h. Lysozyme treatment and sonication were used to disrupt bacterial cells suspended in 20mM Na phosphate buffer [pH 7.4], containing 50 mM NaCl, $5\%$ glycerol and $0.05\%$ Z3-14 (Anatrace, Inc., Maumee, OH, USA) detergent followed by centrifugation at 20,000× g for 30 min at 4 °C. His-tagged Pgp3 and PmpG were purified using IMAC (Immobilized Metal Affinity Chromatography) over a His60 Ni SuperflowTM resin (Clontech Laboratories, Inc., Mountain View, CA, USA) column and gel filtration column with Sephacryl 300 [26]. Eluted proteins were purified using Pierce Endotoxin Removal Resin (Thermo Fisher Scientific). LPS was quantified using the Limulus Amebocyte Lysate Pyrotell assay (Associates of Cape Cod. Inc., East Falmouth, MA, USA). The antigens contained: 6xHis-Pgp3 protein (300 EU/mg/protein equal to 6.0 EU/20 μg/dose/mouse); 6xHis-PmpG (10 EU/mg/protein equal to 0.2 EU/20 mg/dose/mouse) and MOMP less than 0.5 EU/mg/protein. The purity and stability of the 6xHis proteins were assessed by polyacrylamide gel electrophoresis (PAGE). Final antigens preparations were concentrated and transferred into NaPi (20 mM), NaCl (50 mM), glycerol ($5\%$), Z3-14 ($0.05\%$), pH 7.4 buffer, and stored at −80°C until used for immunization. ## 2.3. Vaccination Protocols Four to five-week-old female BALB/c (H-2d) mice (Charles River Laboratories; Wilmington, MA, USA) were housed at the University of California, Irvine, Vivarium. The University of California, Irvine IACUC approved all animal protocols. The adjuvants CpG-1826 (TriLink, San Diego, CA, USA; 10 μg/mouse/immunization) and Montanide ISA 720 VG (SEPPIC Inc., Fairfield, NJ, USA; $70\%$ of total vaccine volume) were directly mixed with single antigens (PmpG, Pgp3 or MOMP: 20 μg of each antigen/mouse/immunization) and antigens combinations (10 μg of each antigen/mouse/immunization). Groups of 5 to 9 mice were immunized twice by the intramuscular (i.m.) route in the quadriceps muscle at a 4-week interval. An adjuvant control group was immunized with CpG-1826 and Montanide ISA 720 VG in phosphate buffered saline (PBS). Sera and vaginal washes were collected before immunization and the day before the challenge and were stored at −20 °C until use. To determine the cell-mediated immune responses, four mice per group were randomly selected and euthanized the day before the challenge. Four weeks after the last immunization mice were challenged intranasally (i.n.) with 104 IFU of C. muridarum. All animal experiments were replicated once. ## 2.4. Determination of the Humoral Immune Responses Induced by Vaccination To determine humoral responses, 96-multiwell plates were coated with C. muridarum EB (1 μg/well), or purified MOMP, Pgp3, or PmpG (0.1 μg/well), and incubated with serially diluted pre-immune sera, as a negative control, and sera collected the day before the challenge [69]. Horseradish peroxidase-conjugated goat anti-mouse IgG (KPL, diluted 1:5000), IgG1 and IgG2a (BD Pharmingen, diluted 1:2000) antibodies were added and the binding was measured in an EIA reader (Labsystem Multiscan, Helsinki, Finland). The geometric mean titers (GMTs) are expressed as the reciprocal of the dilution. In vaginal washes, the levels of C. muridarum-specific IgG and IgA (ICN Pharmaceutical, OH; diluted 1:3500) antibodies were determined using the same procedures. In vitro neutralization assays were performed as described [70]. Two-fold serial dilutions of mouse sera, made with Ca2+- and Mg2+-free PBS, pH 7.2 and supplemented with $5\%$ guinea pig serum, were added to 1 × 104 IFU of C. muridarum. Following incubation for 45 min at 37 °C, the mixtures were inoculated by centrifugation into HeLa-229 cells grown on 96-multiwell plates. After 30 h of incubation at 37 °C, the monolayers were fixed and stained with a pool of monoclonal antibodies to C. muridarum generated in our lab. The titer of a sample was the dilution that yielded $50\%$ neutralization relative to the negative control serum from PBS immunized mice. Antibodies elicited by vaccination against linear epitopes of C. muridarum MOMP were determined using synthetic 25-mers overlapping peptides corresponding to the entire amino acid sequence of mature MOMP (SynBioSci Corp., Livermore, CA, USA). Peptide 25 overlapped the N-terminus and C-terminus of MOMP. Each peptide (1 μg/well) was adsorbed onto a high binding affinity 96-microttiter plate and antibody binding was assessed in triplicate using anti-mouse IgG. ## 2.5. Evaluation of C. muridarum—Specific Cellular Immune Responses Induced by Vaccination Four mice per group were used to determine cellular immune responses. Animals were euthanized the day before the intranasal challenge and T-cell suspensions prepared from spleen cells purified using a nylon wool column as described [25]. T-cells were aliquoted into 96-well plates at a concentration of 2.5 × 106 cells/well. The T-cells were stimulated with C. muridarum UV-inactivated EB, or purified MOMP. Concanavalin A (5 μg/mL) and culture media served as positive and negative controls, respectively. After two days of incubation at 37 °C, in a $5\%$ CO2 incubator, supernatants were harvested and stored at −20 °C. Levels of IFN-γ and IL-4 in supernatants were determined by an ELISA (BD Pharmingen, San Diego, CA, USA) [25]. ## 2.6. Intranasal Challenge and Evaluation of the Infection and Disease Four weeks after the last immunization, anesthetized mice were challenged i.n. with 104 IFU of C. muridarum [26]. The mice were weighed for 10 days, euthanized, their lungs weighed, homogenized in 5 mL of SPG (Seward Stomacher 80; Labsystems), and serial 10-fold dilutions were used to infect Hela-229 cell monolayers. The cultures were incubated for 30 h at 37 °C in a $5\%$ CO2 incubator, the inclusions visualized with C. muridarum-specific monoclonal antibodies and counted using a light microscope. The limit of detection was, <50 C. muridarum IFU/lungs mouse [71]. To determine the local cellular immune responses, levels of IFN-γ in lungs’ supernatants at 10 days post-challenge (d.p.c.) were determined by an ELISA as describe above. ## 2.7. Statistical Analyses Parametric and non-parametric statistical tests were used as follow. The Student’s t-test was employed to evaluate changes in body weight at day 10 p.c., lungs’ weights and amounts of IFN-γ in lungs supernatants. Repeated measures ANOVA was used to compare changes in mean body weight over the 10 days of observation following the C. muridarum i.n. challenge. The Mann–Whitney U-Test was used to compare antibodies titers, levels of IFN-γ and IL-4 in T-cell supernatants, and the number of C. muridarum IFU in the lungs. Values below the limit of detection (BLD) were assigned ½ the value of the BLD, as described by Beal [72]. A p value of < 0.05 was considered to be significant. A p value of <0.1 indicates approaching significance. ## 3.1. Analyses of the Three C. muridarum Recombinant Antigens Used for Immunization Recombinantly produced C. muridarum protein antigens were used for this study. Using a sliver stain, the mature MOMP, and the passenger domain of PmpG, had similar MW (~40 kDa), while the full length Pgp3 had a MW of ~26 kDa (Figure 1A). Loading the samples, with and without boiling, in a $10\%$ SDS-PAGE, both the denatured monomer and the non-denatured trimer forms of Pgp3 were detected by silver stain (Figure 1B). Using a Western blot, sera from mice vaccinated with a single, or two antigens, recognized their respective proteins in C. muridarum EB (Figure 1C). ## 3.2. Characterization of the Humoral Immune Responses Induced by Vaccination Following vaccination, humoral immune responses were determined the day before the i.n. challenge using C. muridarum EB as antigens (Figure 2 and Supplemental Table S1). MOMP vaccinated animals had an IgG2a antibody geometric mean titer (GMT) of 409,600 and an IgG1 GMT of 64,508. Mice immunized with Pgp3 had lower serum IgG2a [9870] and IgG1 [1131] GMT to C. muridarum EB. Similar levels of these antibodies were seen in mice vaccinated with PmpG (6400 and 436, respectively). High IgG2a antibody levels to EB were observed in animals vaccinated with MOMP+Pgp3 [223,336] or MOMP+PmpG [265,593]. IgG1 GMT were also high for these two groups, 23,475 and 39,481, respectively. The IgG2a/IgG1 ratios ranged from 6.4 to 14.7, indicative of Th1-biased humoral immune responses in all vaccinated animals. Very high GMTs were detected when using the homologous protein as the antigen (Figure 3 and Supplemental Table S2). MOMP-vaccinated mice had an IgG titer of 139,900. The GMT to Pgp3 in mice immunized with this protein was 2,826,500 and for mice vaccinated with PmpG it was 905,100. When protein combinations were utilized to vaccinate animals, the antibody levels to the two respective homologous antigens were similar, or slightly lower, than when the individual protein was utilized for immunization. For example, mice vaccinated with MOMP+PmpG had a GMT of 89,800 to MOMP and a GMT of 543,500 to PmpG. Epitope mapping, using MOMP synthetic peptides, demonstrated that mice vaccinated with MOMP produced antibodies to the four VDs (Figure 4). Peptides in the first constant domain (CD1) were also recognized. Animals immunized with MOMP+PmpG showed a similar pattern of antibody specificity. In contrast, the group of mice immunized with MOMP+Pgp3 failed to generate significant amounts of antibodies to VD3 and weak to VD4. Neutralizing antibodies were determined in serum samples using live EB as the antigen (Figure 5 and Supplemental Table S1). Only the three groups of mice vaccinated with MOMP alone [159], or in combination with PmpG [63], or Pgp3 [79], had neutralizing antibodies, indicating that they were elicited by MOMP. No significant differences in neutralizing titers were observed between these three groups of mice. Immunization with PmpG, or Pgp3 did not induce neutralizing antibodies. IgG and IgA antibody levels to C. muridarum EB were determined in pooled vaginal washes. As shown in Figure 6 and Supplemental Table S3, only mice immunized with MOMP alone, or in combination with Pgp3 or PmpG, showed IgG in the vaginal washes. IgA levels were negative or very low in all groups of mice. ## 3.3. Cell-Mediated Immune Responses following Vaccination The day before the intranasal challenge, four mice per group were euthanized, their spleens collected, and T-cells separated using nylon wool. T-cells from mice immunized with MOMP, and stimulated with EB, secreted 796.05 pg/mL of IFN-γ (Figure 7 and Supplemental Table S4). T-cells from mice immunized with Ppg3 or PmpG, stimulated with EB, did not secrete significant amounts of IFN-γ (<15 pg/mL). In contrast, T-cells from mice immunized with MOMP in combination with Ppg3 or PmpG, stimulated with EB, secreted significant levels of IFN-γ, 60.70 and 811.38 pg/mL, respectively. No significant differences were observed in amounts of IFN-γ produced between mice immunized with MOMP alone or with MOMP+PmpG ($p \leq 0.05$); however, the group immunized with MOMP+Pgp3 secreted lower IFN-γ levels ($p \leq 0.05$). Levels of IL-4 were low, or negative, in all groups. When T-cells were stimulated with ConA, as a positive control, levels of IFN-γ and of IL-4 were significant indicating that the T-cells were viable. ## 3.4. Changes in Body Weight following the Intranasal Challenge Four weeks after the last immunization, mice were challenged intranasally with 104 C. muridarum IFU. Body weight changes were used as a parameter indicative of the systemic effects of the infection. All groups of mice rapidly lost body weight from day 2 to day 4 post challenge (p.c.) ( Figure 8). The negative control receiving PBS with adjuvants continuously lost body weight for the entire 10 days of observation. Mice vaccinated with MOMP, gained weight starting at day 5 p.c. Mice immunized with Pgp3 gained body weight from day 4 to day 6 p.c. but then lost body weight, while the group vaccinated with PmpG lost body weight for most of the 10 days p.c. In contrast, mice vaccinated with MOMP+PmpG, gained weight from day 4 to day 10, while those immunized with MOMP+Pgp3 gained body weight from day 4 to day 6 p.c., but then lost weight until the end of the experiment. Using the repeated-measures ANOVA to calculate differences in body-weight losses over the 10 p.c. days of observation, the weight loss of all immunized mice was significantly lower than the negative control receiving PBS with adjuvants ($p \leq 0.05$). The two groups of mice that best maintained their body weight were those immunized with MOMP, and MOMP+PmpG. Mice vaccinated with Pgp3, or PmpG alone, lost more body weight than their respective combination groups immunized with MOMP ($p \leq 0.05$). By day 10 p.c., in comparison with the PBS control animals (body-weight loss $21.4\%$), the five groups of mice immunized with one or two chlamydial antigens were protected ($p \leq 0.05$) (Figure 9A and Table 1). The body-weight losses of mice vaccinated only with Pgp3 ($16.4\%$), or PmpG ($18.6\%$), or with the combination of MOMP+Pgp3 ($9.1\%$), were significant when compared with MOMP alone ($4.2\%$) vaccinated animals ($p \leq 0.05$). Only mice immunized with MOMP+PmpG ($6.1\%$) had a body-weight loss that was not significantly different when compared to the MOMP only vaccinated group ($p \leq 0.05$). ## 3.5. Lung’s Weights As a measure of the local inflammatory responses, the weights (g) of the mice lungs were determined at D10 p.c. ( Figure 9B and Table 1). The lung weights of all groups immunized with a chlamydial antigen were significantly different from the negative control receiving PBS plus the adjuvants ($p \leq 0.05$). The mean lung weights of mice vaccinated with MOMP was 0.23 g and 0.36 g for those receiving PBS ($p \leq 0.05$). The lung weights of mice immunized with Pgp3 (0.33 g), or PmpG (0.31 g) alone, or in combination with MOMP (0.29 g and 0.27 g, respectively), were significantly different from the controls immunized with MOMP ($p \leq 0.05$). Animals immunized with MOMP+PmpG had significantly lower lung weights than those vaccinated with PmpG alone ($p \leq 0.05$). No significant differences were observed between the lung weights of mice vaccinated with Pgp3 or PmpG ($p \leq 0.05$). ## 3.6. Burden of C. muridarum in the Lungs At D10 p.c., the median number of C. muridarum IFU recovered from the lungs of mice vaccinated with MOMP was 0.09 × 106, while in the negative control group receiving PBS plus the adjuvants, it was 498.30 × 106 ($p \leq 0.05$) (Figure 9C and Table 1). In comparison with the negative control group, except animals immunized with Pgp3 (114.76 × 106), all mice vaccinated with a chlamydial antigen were protected ($p \leq 0.05$). Mice immunized with MOMP+PmpG (0.05 × 106) showed a similar level of protection as those vaccinated with MOMP alone ($p \leq 0.05$). Mice immunized with MOMP+PmpG were also better protected than those vaccinated with MOMP+Pgp3 (16.50 × 106) ($p \leq 0.05$). ## 3.7. Local Immune Responses in the Lungs To evaluate local immune parameters that correlate with protection, levels of IFN-γ were determined in supernatants from lungs harvested at D10 p.c. ( Figure 9D and Table 1). We expect that protected mice will have controlled the C. muridarum infection and, therefore, have low amounts of IFN-γ in lungs supernatants. Levels of IFN-γ (pg/mL) in lungs supernatants of mice immunized with MOMP (112.5) were significantly lower from those receiving PBS (1444.4) ($p \leq 0.05$). No significant differences in the levels of IFN-γ in the lungs were determined when comparing mice vaccinated with MOMP only versus PmpG+MOMP immunized mice (46.0) ($p \leq 0.05$). Amounts of IFN-γ in mice vaccinated with MOMP, were statistically significantly lower than in animals immunized with Pgp3 (1184.8) or PmpG (836.2) only, or with the MOMP+Pgp3 (719.8) combination, indicative that in these three groups the infection was still active ($p \leq 0.05$). ## 4. Discussion The goal of this study was to determine the ability of MOMP, PmpG and Pgp3 antigens, alone and in combination, to induce protective immune responses against a C. muridarum intranasal challenge. As determined by changes in body weight, weight of the lungs and number of Chlamydia IFU recovered from the lungs, vaccines formulated with MOMP elicited robust protective immune responses while those induced by PmpG, or Pgp3 were weak. Combining MOMP with each of these two antigens elicited significant humoral and cellular immune responses that were protective. However, MOMP alone induced more robust protective immune responses than its combination with PmpG or Pgp3. Pgp3 had an antagonistic effect that significantly decreased the humoral and cell mediated protective immune responses elicited by MOMP. MOMP, PmpG and Pgp3 have been shown to elicit protective immune responses in mice against genital and/or respiratory challenges [17,73,74,75,76,77]. Here, we wanted to determine if PmpG and/or Pgp3, well-conserved proteins among all the C. trachomatis serovars, could broaden the protection induced by MOMP, an antigen that only induces serovar/serogroup protection. Mice vaccinated with MOMP developed high antibody titers to C. muridarum EB while those immunized with PmpG, or Pgp3, mounted low antibody responses. Similar results were observed when levels of IgG and IgA were determined in vaginal washes using EB as the antigen, and when T-cell mediated immune responses were evaluated. These differences likely represent the relative quantities and accessibility of these three proteins in EB [78]. This possibility was confirmed when the antibody responses were determined against the purified proteins. In this case, both PmpG and Pgp3 immunized mice had high antibody titers against the homologous protein, confirming previous results in humans [40,79]. However, only vaccination with MOMP elicited neutralizing antibodies in serum. This is not surprising, since it is known that human and murine antibodies against the Pgp3 trimer are not neutralizing and we are not aware of any publication showing that PmpG elicits neutralizing antibodies [63,65,80]. Cell-mediated immune response, using EB as the stimulating antigen, followed a similar pattern. The stronger humoral and cellular immune responses to EB, elicited by MOMP, correlated with protection against the respiratory challenge. While mice vaccinated with MOMP mounted robust protection against body-weight losses, inflammatory responses in the lungs and number of C. muridarum IFU in the lungs, those immunized with PmpG, or Pgp3, were weakly protected. Using multivalent vaccines, synergistic, additive, neutral or antagonistic effects may be observed [81,82,83,84,85]. For example, Finco et al. [ 83] identified C. muridarum antigens that elicited both humoral and cell-mediated immune responses. Mice immunized with each of these four antigens, TC0106, TC0210, TC0313, or TC0741 (10 μg of each antigen/dose), adjuvanted with LTK63+CpG, had 0.5–0.9 log10 reduction in the number of IFU recovered from the lungs. A four-antigen combination (TC0106, TC0210, TC0313 and TC0741; 10 μg of each antigen/dose) was then used to immunize mice. This multivalent combination resulted in a 4.1 log10 reduction in the number of C. muridarum IFU recovered from the lungs, indicative of synergistic effects. Yu et al. [ 82] also found additive effects of three C. muridarum antigens PmpE/F, PmpG, and MOMP in the genital model (single antigen, 5 μg/dose; three antigens, 1.67 μg/each per dose). As determined by vaginal shedding, the combination of the three proteins, adjuvanted with CAF01, exhibited the highest level of protection against a genital challenge. Coler et al. [ 84] also showed that MOMP, combined with CT875, (10 μg of each antigen, alone or in combination/dose), and adjuvanted with AS01B, elicited better protection against a vaginal challenge with C. trachomatis serovar K (UW-31/Cx), than the individual antigens. Neutral effects resulting from immunization with C. muridarum antigens combinations have also been reported. For example, Cheng et al. [ 86] vaccinated mice with components of the C. muridarum putative ATP synthase complex TC0580, TC0581, TC0582, TC0584, or only with MOMP (10 μg of each antigen/dose). In addition, TC0582 was formulated in combination with TC0580, TC0581 or MOMP (10 μg of each antigen/dose). Animals immunized with combinations of two of these three antigens were only protected as well as mice vaccinated with MOMP, the most protective protein in the formulations. Li et al. [ 87] reported that the addition of CPAF to MOMP, or IncA, (15 μg of protein/dose), from C. trachomatis serovar D (UW3-Cx), did not enhance the CPAF (15 μg of protein/dose) induced protective effects on C. muridarum clearance, or oviduct pathology. Here, we observed a neutral effect in immune responses and protection when combining MOMP with PmpG, while the formulation of MOMP with Pgp3 induced an antagonist effect. Qiu et al. have also described an antagonist effect when testing HCV antigens [85]. Although a group of mice vaccinated with a 10 μg/dose of MOMP, was not included, we have performed several experiments in mice immunized with 10 μg of MOMP and saw similar levels of protection as that observed here with 20 μg of MOMP [58,88]. Therefore, we favor the interpretation that PmpG had a neutral effect, while Pgp3 had an antagonistic activity when combined with MOMP. Analyses of the immune responses support this premise. Antibody responses in serum and vaginal washes against EB, or MOMP, declined in mice immunized with MOMP+PmpG, or MOMP+Pgp3, when compared with those vaccinated only with MOMP. Neutralizing antibodies in serum, were also lower in mice vaccinated with the antigens combinations. These differences in humoral immune responses, for the most part, however, were not statistically different. Epitope mapping, using MOMP peptides, showed marked decreases against VD3 and VD4 in mice immunized with MOMP+Pgp3 versus those vaccinated with MOMP alone. The most striking differences, however, were observed in the cellular immune responses. Mice immunized with MOMP+PmpG had similar IFN-γ levels, in T-cell supernatants stimulated with EB, compared to those vaccinated with MOMP alone (811.38 versus 796.05 pg/mL; $p \leq 0.05$). In contrast, levels of IFN-γ from mice vaccinated with MOMP, were significantly higher than in mice immunized with MOMP plus Pgp3 (796.05 versus 60.70 pg/mL; $p \leq 0.05$). Liu et al. [ 68] demonstrated, in the mouse model, that C. muridarum Pgp3 is a virulence factor. Chen et al. [ 63] postulated that the high antibody titers to Pgp3, present in Chlamydia infected humans and mice, may be exhausting the host humoral immune responses and, thus, providing an immune escape mechanism for this pathogen. These authors also reported the presence of Pgp3 trimers in the chlamydial outer membrane complex (COMC) where MOMP is the predominant component [63]. Although we do not have data about the interactions that occurred in the vaccine formulation between MOMP and Pgp3, and the mechanisms involved in the immune suppression, based on these findings, we hypothesize that the virulence of Pgp3 could be due to its interference with the protective humoral and cell-mediated immune responses elicited by MOMP. A limitation of this study is the need to verify in a mouse model the interaction between MOMP, and Pgp3, observed here. Mutant C. muridarum constructs not expressing Pgp3, or monoclonal antibodies to Pgp3, could be utilized to specifically address this issue [89]. It may also be important to verify if Pgp3 has a similar effect on other potential vaccine antigens. When formulating a multivalent subunit chlamydial vaccine, it will be necessary to carefully evaluate the interactions between the antigens in animal models before implementation in humans. 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--- title: 'Weight-Control Behaviors and Dietary Intake in Chinese Adults: An Analysis of Three National Surveys (2002–2015)' authors: - Miyang Luo - Yixu Liu - Ping Ye - Shuya Cai - Zhenzhen Yao - Liyun Zhao - Jiayou Luo - Dongmei Yu journal: Nutrients year: 2023 pmcid: PMC10051790 doi: 10.3390/nu15061395 license: CC BY 4.0 --- # Weight-Control Behaviors and Dietary Intake in Chinese Adults: An Analysis of Three National Surveys (2002–2015) ## Abstract Weight control through dietary management is becoming increasingly common worldwide. This study aimed to evaluate and compare the dietary intake and diet quality between Chinese adults with and without weight-control behaviors. Data were collected from the China National Nutrition Survey 2002, 2012, and 2015. Dietary intake was assessed using a combination of 24 h dietary recall of three consecutive days and a weighing method. Diet quality was calculated based on China healthy diet index (CHDI). A total of 167,355 subjects were included, of which 11,906 ($8.0\%$) adults reported attempting to control weight within the past 12 months. Participants with weight control had lower daily total energy intake, as well as lower percentages of energy from carbohydrates, low-quality carbohydrates, and plant protein, but higher percentages of energy from protein, fat, high-quality carbohydrates, animal protein, saturated fatty acids, and monounsaturated fatty acids than those without weight control. Additionally, the CHDI score in the weight-control group was higher than those without (53.40 vs. 48.79, $p \leq 0.001$). Fewer than $40\%$ of participants in both groups met the requirement for all specific food groups. Chinese adults who reported weight-control behaviors had an energy-restricted diet characterized by reduced carbohydrate intake and overall higher diet quality compared with those without dietary-control behaviors. However, both groups had significant room for improvement in meeting dietary recommendations. ## 1. Introduction Overweight and obesity have become a public health concern in recent years, and weight control is an essential component for addressing this issue [1]. Effective weight control relies heavily on dietary management, which can be achieved through various energy-restricted and healthy dietary interventions such as low-fat, low-carbohydrate, and Mediterranean diets [2,3]. Despite the availability of such dietary options, individuals attempting weight control may lack the scientific knowledge to adopt favorable dietary behaviors [4]. Furthermore, even those who possess a clear understanding of healthy dietary principles may find it challenging to implement them in practice due to personal food preferences and an irresistible appetite [5,6]. Several previous studies have examined dietary intake among individuals attempting weight control [7,8,9,10]. These studies have shown that, regardless of the dietary management strategy used, people with weight-control attempts generally have lower energy intake compared with those without [7,8,9]. However, mixed findings have been reported regarding diet quality and adherence to dietary guidelines [11,12,13,14]. While some studies have observed improvements in diet quality among participants with weight control compared with those without [11,12], other studies have found no differences in refined grain, sodium, and cholesterol intakes or diet quality between populations with and without weight control [13,14]. Furthermore, some studies have even suggested that individuals with weight-control behaviors may be at increased risk of dietary inadequacy due to unhealthy dietary practices [7]. It is worth noting that most of these studies were conducted in developed countries or on people with overweight or obesity [7,8,15], and there is a particular lack of representative studies on the general population in China. Therefore, assessing dietary intake among populations with weight-control behaviors in China may help to identify the deficiencies in their dietary management practices and provide targeted guidance on dietary intake and weight management. In this study, we used three rounds of nationally representative data from 31 provinces in China to learn the current status of dietary nutrition intake among Chinese adults with weight-control behaviors. We compared the dietary intake and diet quality between adults with and without weight-control behaviors and evaluated their adherence to dietary guidelines. This study provided a theoretical basis for improving the nutritional intake of people attempting weight control, promoting balanced diets, and encouraging the use of healthier and more scientific dietary management practices for weight control. ## 2.1. Study Population This study was based on three consecutive rounds of the China National Nutrition Surveys (CNNS) in 2002, 2012, and 2015. CNNS is a national survey carried out by the Chinese Center for Disease Control and Prevention every 5–10 years since 1959, and multistage stratified cluster sampling methods were used to select residents across all provinces in China. The details of the survey design and methods have been described elsewhere [16]. Initially, 69,583, 67,177, and 96,631 subjects participated in the household dietary survey from 2002 to 2015. Participants in this study had the following inclusion criteria: (a) completed at least two days of the three-day dietary recall; (b) age greater than 18 years old; and (c) with complete personal information. Participants were excluded with the following criteria: (a) they were pregnant or breastfeeding; (b) with missing information on weight control behaviors; and (c) with extreme daily total energy intake, i.e., <800 kcal or >5000 kcal. The flow of inclusion is shown in Figure 1. The series of nationwide surveys was approved by the Ethics Committee of the National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention (Approval number: 201519-B and approval date: $\frac{06}{2015}$). All participants signed informed consent prior to the investigation. ## 2.2. Data Collection and Dietary Assessment A questionnaire was conducted by trained researchers using face-to-face interviews in which sociodemographic characteristics and personal health status were surveyed. Height and weight were measured by trained researchers afterward. Sociodemographic characteristics included gender, age, educational level, occupation, marital status, and family income level; personal health status included weight-control behavior and a history of chronic diseases. Weight control was assessed using the question in the questionnaire “Have you tried to lose weight during the past one year?” If the answer was “yes”, the participant was considered to have weight-control behavior and was classified in the “yes” group of weight control; if the answer was “no”, the participant was considered to have no weight-control behavior and was classified in the “no” group of weight control. Dietary intake was assessed using a combination of 24 h dietary recall of three consecutive days and a weighing method. Food intake during the past 24 h was recorded for each dietary recall day, including two weekdays and one weekend. The recall was assisted by the interviewer to ensure that accurate information was collected. Cooking oil and condiments were weighed at the household by researchers at the beginning and end of each 24 h dietary survey. Nutrient intakes were calculated using the China Food Composition tables (FCTs) [17,18]. The percentage of energy from carbohydrate, fat, and protein was calculated using the following equations: the total amount of carbohydrate intake × 4/the total energy intake × 100, the total amount of fat intake × 9/the total energy intake × 100, and the total amount of protein intake × 4/the total energy intake × 100, respectively. The recommended intake data of the percentage of energy intake from macronutrients were obtained from the Chinese dietary reference intakes—Part 1: Macronutrient (WS/T 578.1–2017) [19]. Specifically, 50–$65\%$ of total energy intake was recommended to come from carbohydrates, 10–$15\%$ from proteins, and 20–$30\%$ from fats [19]. We further subdivided proteins into plant and animal proteins; carbohydrates into low-quality and high-quality carbohydrates; and fats into monounsaturated, saturated, and polyunsaturated fatty acids, as detailed in a previous study [20]. The recommended daily food intake was derived from the 2016 Dietary Guidelines for Chinese Residents, and the recommendations were as follows: cereals and tubers 250–400 g/day; soybeans and nuts 25–35 g/day; vegetables 300–500 g/day; fruits 200–350 g/day; livestock and poultry meats 40–75 g/day; dairy products greater than 300 g/day; eggs 40–50 g/day; aquatic products 40–75 g/day; oil 25–30 g/day; and salt less than 6 g/day [21]. Diet quality was assessed using the China healthy diet index (CHDI) [22]. The CHDI includes 13 items with a total score of 100, and a higher score indicates better diet quality. The details of the scoring method are shown in Table S1. Diet quality was categorized into two groups, i.e., satisfied and not satisfied, based on the CHDI score at the cutoff of 60. ## 2.3. Statistical Analysis The poststratification population sampling weights were derived from the sampling probability based on census data of 2010 in each survey round, and standardized data with adjustments for age and gender distribution were presented. Sociodemographic characteristics were compared between participants with and without weight control using chi-square tests. Intake of food and macronutrients and dietary score were described using means and $95\%$ confidence intervals (CIs) with adjustment for the sample weights. General linear regression models were used to compare the difference in dietary intake and dietary score between groups, with adjustments for age, gender, education level, occupation, and family income level. Multivariate logistic regression was used to analyze the influence of weight-control behavior on diet quality. A two-sided $p \leq 0.05$ was considered to indicate statistical significance. Statistical analyses were conducted using SPSS 25.0 statistical software (IBM SPSS Inc., Chicago, IL, USA). ## 3.1. Participant Characteristics A total of 167,355 adults aged 18 to 107 were included in this analysis, with 45,148 in 2002, 53,578 in 2012, and 68,629 in 2015. Demographic characteristics were similar across participants from the three survey rounds (Table S2). Overall, the prevalence of overweight plus obesity was $41.7\%$, and $8.0\%$ of the included participants reported being on weight-control diets. The comparison of participant characteristics between adults with and without weight control behavior is shown in Table 1. Participants with weight-control behavior were more likely to be females, aged below 40 years old, had higher education levels and higher income levels, and lived in urban areas. The prevalence of overweight plus obesity in those with and without weight-control behavior was $70.4\%$ and $39.2\%$, respectively. ## 3.2. Comparison of Dietary Intake in Participants with and without Weight-Control Behavior As shown in Table 2, participants with weight-control behavior had lower average daily total energy intake compared with those without (1958.4 kcal/day vs. 2115.8 kcal/day, $p \leq 0.001$). They also showed a significantly lower percentage of energy intake from carbohydrates ($51.9\%$ vs. $55.6\%$, $p \leq 0.001$) and a higher percentage from protein ($13.0\%$ vs. $12.2\%$, $p \leq 0.001$) and fat ($35.1\%$ vs. $32.1\%$, $p \leq 0.001$), although the amount of total protein intake was slightly higher (63.3 g/day vs. 64.4 g/day, $p \leq 0.001$) compared with those without weight-control behavior. More specifically, participants with weight-control behavior showed a higher percentage of energy intake from high-quality carbohydrates ($5.7\%$ vs. $4.6\%$, $p \leq 0.001$) and a lower one from low-quality carbohydrates ($47.5\%$ vs. $52.0\%$, $p \leq 0.001$) than those without weight-control behavior. The percentage of energy intake from plant protein was higher than animal protein in both groups, and the weight-control group had a higher percentage of energy intake from animal protein ($5.4\%$ vs. $4.4\%$, $p \leq 0.001$) and lower energy intake from plant protein ($7.0\%$ vs. $7.5\%$, $p \leq 0.001$) than the group without weight-control behavior. In addition, the percentage of intake of both saturated fatty acids ($9.1\%$ vs. $8.6\%$, $$p \leq 0.009$$) and monounsaturated fatty acids ($14.8\%$ vs. $9.4\%$, $$p \leq 0.001$$) was higher than those without weight-control behavior. In terms of food intake, lower intake of cereals and tubers (359.1 vs. 430.6 g/day, $p \leq 0.001$), vegetables (269.2 vs. 272.2 g/day, $$p \leq 0.003$$), oil (40.4 vs. 41.7 g/day, $p \leq 0.001$), and salt (12.1 vs. 13.2 g/day, $p \leq 0.001$) and higher intake of fruits (78.8 vs. 44.3 g/day, $p \leq 0.001$), meat (101.6 vs. 91.3 g/day, $$p \leq 0.045$$), dairy products (41.7 vs. 23.4 g/day, $p \leq 0.001$), eggs (30.8 vs. 23.9 g/day, $$p \leq 0.009$$), and aquatic products (39.7 vs. 30.9 g/day, $p \leq 0.001$) were observed in participants with weight-control behavior compared with those without. ## 3.3. Adherence to Dietary Recommendations in Participants with and without Weight-Control Behavior In terms of macronutrients, around one-third of participants met the recommendation of carbohydrates and fats, and around $60\%$ of participants fulfilled the requirement for protein (Figure 2). A higher percentage of participants met the requirement for carbohydrates in the weight-control group than the group without weight-control behavior ($32.6\%$ vs. $29.5\%$, $p \leq 0.001$), while the percentages were lower for protein ($60.4\%$ vs. $62.4\%$, $p \leq 0.001$) and fats ($26.4\%$ vs. $28.9\%$, $p \leq 0.001$). Moreover, a higher percentage of participants showed lower than the recommended level of carbohydrate intake in the weight-control group than in the no-weight-control group. Fewer than $40\%$ of participants met the requirement for all specific food groups in both groups. More specifically, more than half of the participants consumed lower than recommended levels of soybeans and nuts, fruits, vegetables, dairy products, eggs, and aquatic products, while around $90\%$ of participants consumed more salt than dietary guidelines prescribe. ## 3.4. Comparison of Diet Quality in Participants with and without Weight-Control Behavior Overall, we observed that only $20.0\%$ of participants had diet quality scores above 60 (Table S3). The total diet quality score was 53.40 in the weight-control group and 48.79 in the other group ($p \leq 0.001$) (Table 3). Participant with weight-control behavior showed higher scores in food variety (6.73 vs. 5.01, $p \leq 0.001$), total vegetables (3.43 vs. 3.29, $p \leq 0.001$), dark vegetables (2.16 vs. 1.94, $p \leq 0.001$), fruits (3.04 vs. 1.69, $p \leq 0.001$), dairy products (1.63 vs. 0.85, $p \leq 0.001$), soybeans (3.72 vs. 3.20, $p \leq 0.001$), meat and eggs (4.08 vs. 3.56, $p \leq 0.001$), and aquatic products (1.88 vs. 1.43, $p \leq 0.001$) compared with those without weight-control behavior. The scores were lower among those with weight-control behavior in refined grains (4.84 vs. 4.93, $p \leq 0.001$), estimated percentage of energy from saturated fatty acid (8.52 vs. 8.58, $p \leq 0.001$), and sodium (4.98 vs. 5.03, $$p \leq 0.020$$) compared with those without weight-control behavior. Multivariate analysis showed participants with weight-control behavior had better diet quality scores after adjustment for demographic factors and BMI (Table S4). ## 4. Discussion In this study, we evaluated and compared the dietary intake and diet quality of participants with and without weight-control behavior using three consecutive rounds of national surveys in China. We found that $8\%$ of subjects tried to control their weight within the last year. Those with weight-control behavior reported lower total energy intake, and the percentage of energy intake from carbohydrates was lower, while the percentage of energy intake from protein or fat was higher compared with those without weight-control behavior. Participants with weight-control behavior showed better diet quality; however, the overall adherence to dietary guidelines was below satisfactory in both groups. The prevalence of self-reported weight-control attempts varies across different studies considering the difference in dietary patterns, sociodemographic characteristics, socioeconomic status, and the prevalence of overweight and obesity across countries [23]. A 2017 systematic review and meta-analysis of 72 studies showed that $34.6\%$ of participants in the general population attempted to lose weight, while $24.7\%$ attempted to maintain their weight [24]. However, there is limited information on the prevalence of weight-control attempts in China, particularly among the general population. Most existing studies are based on individuals with overweight or obesity [25,26]. For instance, a national survey on chronic disease surveillance found that $16.3\%$ of adults with overweight or obesity attempted weight-control behaviors in China [25]. In our study, the prevalence of weight-control attempts in the general population was found to be $8.0\%$, while the prevalence was $12.0\%$ among participants with overweight and obesity. The relatively low prevalence of weight-control attempts, especially among those with overweight and obesity in China, may be due to misconceptions about body weight and a lack of scientific knowledge on weight management [27,28,29]. It is therefore necessary to promote education on weight-control among the general population and provide targeted interventions for weight control among individuals with overweight or obesity to improve overall health. Dietary management for weight control involves various energy-restricted dietary interventions. In this study, we found that participants with weight-control behavior had a lower total energy intake compared with those without weight-control behavior, mainly by reducing carbohydrate intake. Previous studies also compared dietary intake between participants with and without weight-control behavior [30]. However, in some studies, the lower total energy intake among participants with weight-control behavior was accompanied by reduced fat intake, with no significant differences in carbohydrate intake [7,14,30,31,32]. This may reflect differences in dietary patterns for weight control among countries, as the intake of carbohydrates in China is relatively higher than many Western countries [33]. Our study also found that the percentages of energy from fat were higher in individuals with weight-control behavior than in those without, possibly because the weight-control individuals conducted an energy-restricted diet focused on reducing carbohydrate intake, resulting in a relatively higher proportion of energy intake from fat [34]. However, the proportion of energy intake from fat exceeded the recommended range in both groups, consistent with the results of previous studies [35]. This suggests that there is an unreasonable percentage of energy sources in the Chinese population, which is an important risk factor for obesity and other chronic diseases [36]. Therefore, it is essential to strengthen guidance on nutrition-related knowledge to help people scientifically adjust the composition of energy from macronutrients and promote their dietary structure in a more health-friendly direction. Regarding specific dietary intake, we found that participants with weight-control behavior showed a higher percentage of energy from high-quality carbohydrates and monounsaturated fatty acids and a lower percentage of energy from low-quality carbohydrates than those without weight-control behavior, indicating healthier eating habits. Moreover, participants with weight-control behavior had a higher percentage of energy from animal protein and slightly higher percentages of energy from saturated fatty acids, probably due to a higher intake of meats, eggs, and milk than those without. Plant protein has been associated with various benefits, including weight management [37]. Therefore, it is crucial to promote increasing the proportion of plant protein intake, such as increasing soybean and nut intake for Chinese adults with weight-control behavior, and increasing the proportion of high-quality carbohydrate intake for all Chinese adults. Consistent with previous studies, participants with weight-control behavior in our study had a better diet quality than those without [11,12,13]. We observed improvement in food variety and found that participants with weight-control behavior had a higher score for intakes of vegetables, fruits, dairy products, soybeans, meat and eggs, and aquatic products compared with those without weight-control behavior. These differences between the two groups suggested that participants with weight-control behavior had a healthier and more balanced diet. However, there was no significant difference between the two groups in their whole grain intake, and weight controllers in China may consider increasing their intake of whole grains to achieve better weight loss, as whole grain intake can help improve weight management [38]. It is also important to note that the overall diet quality score was below an optimal level, and adherence to dietary guidelines was poor in both groups, suggesting that there is a need for improvement in both groups. Specifically, the average intake of fruits and dairy products was much lower than the recommended level, and more than two-thirds of participants consumed lower than recommended levels of fruits, soybeans and nuts, eggs, dairy products, and aquatic products, while more than $80\%$ of participants consumed a higher level of salt than the dietary guidelines prescribe. These gaps in meeting the recommended levels of dietary guidelines among Chinese adults were also observed in previous studies [39,40]. These findings suggest that effective measures are needed to promote diet quality and adherence to dietary guidelines in the population. Additionally, our study indicated that gender, age, education level, occupational status, household income level, and urban/rural areas had varying degrees of influence on diet quality among Chinese adults, which is consistent with a prior study [41]. Therefore, it is necessary to improve the nutritional health literacy of residents in a targeted manner and increase the promotion of healthy dietary guidelines to achieve a healthier diet. This study has several strengths, including the use of national representative data from 31 provinces in China, which allows for a more comprehensive evaluation of dietary intake and quality. We acknowledge that this study has the following limitations. Firstly, weight control can be achieved through various measures, including physical activity and medical treatment, and this study primarily focused on dietary interventions. Therefore, the results may not be applicable to individuals who utilize other weight-control methods. Additionally, self-reported weight-control behaviors may be subject to recall bias, and future studies should consider incorporating objective measures to verify weight-control status. Finally, dietary recall is also prone to recall bias, and future studies should consider incorporating additional measures, such as food diaries or biomarkers, to more accurately assess dietary intake. ## 5. Conclusions To summarize, our study found a low prevalence of weight-control behavior among Chinese adults, particularly among those who were overweight or obese. 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--- title: Bidirectional Regulation of Sodium Acetate on Macrophage Activity and Its Role in Lipid Metabolism of Hepatocytes authors: - Weiwei Li - Mingjuan Deng - Jiahui Gong - Yichao Hou - Liang Zhao journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051801 doi: 10.3390/ijms24065536 license: CC BY 4.0 --- # Bidirectional Regulation of Sodium Acetate on Macrophage Activity and Its Role in Lipid Metabolism of Hepatocytes ## Abstract Short-chain fatty acids (SCFAs) are important metabolites of the intestinal flora that are closely related to the development of non-alcoholic fatty liver disease (NAFLD). Moreover, studies have shown that macrophages have an important role in the progression of NAFLD and that a dose effect of sodium acetate (NaA) on the regulation of macrophage activity alleviates NAFLD; however, the exact mechanism of action remains unclear. This study aimed to assess the effect and mechanism of NaA on regulating the activity of macrophages. RAW264.7 and Kupffer cells cell lines were treated with LPS and different concentrations of NaA (0.01, 0.05, 0.1, 0.5, 1, 1.5, 2, and 5 mM). Low doses of NaA (0.1 mM, NaA-L) significantly increased the expression of inflammatory factors tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin 1 beta (IL-1β); it also increased the phosphorylation of inflammatory proteins nuclear factor-κB p65 (NF-κB p65) and c-Jun ($p \leq 0.05$), and the M1 polarization ratio of RAW264.7 or Kupffer cells. Contrary, a high concentration of NaA (2 mM, NaA-H) reduced the inflammatory responses of macrophages. Mechanistically, high doses of NaA increased intracellular acetate concentration in macrophages, while a low dose had the opposite effect, consisting of the trend of changes in regulated macrophage activity. Besides, GPR43 and/or HDACs were not involved in the regulation of macrophage activity by NaA. NaA significantly increased total intracellular cholesterol (TC), triglycerides (TG), and lipid synthesis gene expression levels in macrophages and hepatocytes at either high or low concentrations. Furthermore, NaA regulated the intracellular AMP/ATP ratio and AMPK activity, achieving a bidirectional regulation of macrophage activity, in which the PPARγ/UCP2/AMPK/iNOS/IκBα/NF-κB signaling pathway has an important role. In addition, NaA can regulate lipid accumulation in hepatocytes by NaA-driven macrophage factors through the above-mentioned mechanism. The results revealed that the mode of NaA bi-directionally regulating the macrophages further affects hepatocyte lipid accumulation. ## 1. Introduction Non-alcoholic fatty liver disease (NAFLD) includes a wide range of disorders associated with fat deposition in the liver, spanning from isolated steatosis to non-alcoholic steatohepatitis (NASH) characterized by steatosis with hepatocellular injury and inflammatory changes with or without fibrosis [1]. NAFLD affects around $32.4\%$ of the general population worldwide. NASH is the active form of NAFLD characterized by histological lobular inflammation and hepatocyte ballooning and associated with faster fibrosis progression, which affects around 1.5–$6.5\%$ of the general population [2,3]. Alarmingly, the incidence of NAFLD in adults and children has been continuously increasing due to ongoing epidemics of obesity [4,5]. Moreover, NASH is among the most common causes of liver cirrhosis and hepatocellular carcinoma, ultimately leading to liver failure [6,7,8]. Thus far, there is still no effective treatment for NAFLD [2,9]. Over the past decade, the essential role of innate immunity in developing hepatic steatosis and NASH has been extensively validated [10,11,12]. As one of the most studied cell types in innate immunity, macrophages have drawn particular attention because macrophage pro-inflammatory activation is strongly associated with hepatic steatosis and inflammation. When pro-inflammatory activation increases, macrophages can generate mediators that trigger or exacerbate hepatocyte inflammatory responses and fat metabolic dysregulation [10,11,12]. Resident tissue macrophages (Kupffer cells) along with monocytes (bone-marrow-derived macrophage, BMDM) recruited from the bone marrow are also important drivers of inflammatory and tissue regenerative responses [13]. Following tissue injury, large numbers of inflammatory monocytes (macrophage precursors) are recruited from the bone marrow via chemokine gradients and various adhesion molecules, and these recruited cells often greatly exceed the population of tissue-resident macrophages [14]. To date, several regulators, such as c-Jun N-terminal kinase 1 (JNK1), Period 1 and 2, and adenosine 2A receptor, have been found to alter the inflammatory status of macrophages, which in turn interact with hepatocytes to protect against or contribute to hepatic steatosis and inflammation [15,16,17]. These findings demonstrate the importance of the innate immune system, particularly macrophages, in the pathophysiology of NAFLD. Accumulating evidence shows a close relationship between the gut and NAFLD [18,19,20]. As the liver receives most of its blood flow ($70\%$) from intestinal vascularization, it is constantly exposed to nutrients, toxins, and gut microbiota products [18]. Moreover, the gastrointestinal tract receives a liver product in the form of bile acid [19], and this functional bidirectional correlation between the liver and gastrointestinal tract is known as the gut-liver axis (GLA) [18]. Gut microbiota is composed of trillions of microorganisms that create a symbiotic relationship with the host or reside as commensals and can execute various functions influencing human physiology and pathology. SCFAs, the main product of dietary fiber metabolized by intestinal flora, are considered important substances related to the gut-liver axis [20,21]. SCFAs might have an essential role in regulating inflammation and metabolism, contextually exerting regulative effects on NAFLD. Acetate, propionate, and butyrate are the main SCFAs in the human gut, accounting for more than $90\%$ of the total SCFAs [22]. Acetate is a two-carbon SCFA known to be used for de novo synthesis for lipids and as a signaling molecule involved in several physiologic processes, including reductions in insulin resistance and appetite, thus contributing to glucose homeostasis, control of body weight, and progress of NAFLD [21,23,24]. Meanwhile, acetate regulates immune response, which might affect NAFLD from another aspect. Acetate supplementation leads to an effective decline in methionine-choline deficient (MCD)-induced macrophage aggregations and pro-inflammatory responses [25]. Besides, acetate supplementation can effectively reduce inflammation and improve insulin sensitivity in HFD-induced diabetic mice by reducing the levels of IL-1β and IL-6 [26]. In contrast, a recent study emphasized that high fecal SCFAs content can impact NAFLD progression by maintaining intestinal low-grade inflammation [22]. Moreover, the principal hepatic metabolite of ethanol, acetate incubation can simulate the effect of ethanol, and increase the production of cellular inflammatory factors by increasing the synthesis of Acyl-CoA Synthetase Short Chain Family Member 2 (ACSS2), the consequent enhancement of the inflammatory response in macrophages [27]. While acetate has been posited to closely related inflammatory response, its role in inflammatory liver pathogenesis remains unclear. The total SCFAs concentration in the colon’s lumen decreases progressively from the proximal to the distal end from 70~140 mmol/L to 20~70 mmol/L, respectively [28], with the ratio of acetate, propionate, and butyrate in the colon of 60:25:15 [29]. SCFAs are absorbed by the colonic epithelial cells, where they pass the portal vein; however, they are mostly metabolized by the hepatocytes in the liver. The concentration range of acetate in humans has a large variation. There is evidence that the acetate is closely related to the activation state of macrophages [30], and our previous studies suggested that there may be a dose effect for acetate to work and that high doses of sodium acetate might be required [25,31]. Currently, there is a lack of research and exploration of relevant mechanisms for the inconsistent results of acetate on NAFLD, especially the dose-effect relationship. The present study verified the dose effect of acetate in regulating macrophage activity of bone marrow origin and liver origin, investigated the mechanism of the bidirectional regulation of acetate in regulating macrophage activity from the perspective of signaling pathways and fatty acid synthesis, and assessed the effect of the dosage effect on fat accumulation in hepatocytes at the cellular level. Our findings revealed the role of acetate in regulating NAFLD at the cellular level. ## 2.1. NaA Regulates the Inflammatory Responses of Macrophages in a Dose-Dependent Manner A CCK-8 assay was performed to evaluate the potential cytotoxic effect of NaA on macrophages. The results showed that after treatment with the maximum concentration of NaA (10 mM) for 24 h, >$80\%$ of the macrophages (RAW264.7 and Kupffer cells) survived (Figure 1A,B), indicating that NaA did not affect cell viability. Regarding the inflammation-modulating effects of the different doses of NaA on LPS-induced RAW264.7 and Kupffer cells activation, the gene expression level of TNF-α, the marker of inflammation, was analyzed by qRT-PCR. LPS treatment significantly elevated TNF-α in the MOD group compared to the CON group, which indicated macrophage activation by LPS. Furthermore, low doses of NaA treatment significantly promoted the overexpression of TNF-α in LPS-activated RAW264.7 and Kupffer cells, while high-dose NaA significantly inhibited the overexpression of TNF-α in LPS-activated RAW264.7 and Kupffer cells compared to the MOD group. Specifically, 0.01~0.05 mM NaA could slightly increase the expression of TNF-α, but there were no significant changes between these two groups and the MOD group (Figure 1C,D). Moreover, a low dose of NaA (0.1 mM) increased the levels of TNF-α, which were $48.7\%$ (RAW264.7) and $66.4\%$ (Kupffer cells) higher than those in the MOD group, respectively. In contrast, high doses of NaA (2~5 mM) reduced approximately $48\%$ or $53\%$ TNF-α levels in RAW264.7 or Kupffer cells compared to the MOD group, respectively. In addition, 0.5~1.5 mM NaA did not affect the expression of TNF-α, compared with the MOD group (Figure 1C,D). The results explicitly showed that NaA regulated the pro-inflammatory response of macrophages in a dose-dependent manner, while 0.1 mM NaA (NaA-L) and 2 mM NaA (NaA-H) were selected for further experiments. ## 2.2. High Dose or Low Dose of NaA Show Opposite Effects on Inflammatory Proteins and Gene Expression in Macrophages The levels of inflammatory cytokines IL-6 and IL-1β in macrophages RAW264.7 (Figure 2A,B) and Kupffer cells (Figure 2C,D) were measured by qRT-PCR. The data showed that the high levels of IL-6 and IL-1β in macrophages (RAW264.7 and Kupffer cells) evoked by LPS were markedly scavenged by the post-treatment with NaA-H. Moreover, NaA-H significantly blocked the increased phosphorylation level of c-Jun and NF-κB induced by LPS in macrophages RAW264.7 (Figure 2E) and Kupffer cells (Figure 2F). In contrast, NaA-L notably exacerbated high levels of IL-6 (Figure 2A,B) and IL-1β (Figure 2C,D) compared with the MOD group. Correspondingly, NaA-L also promoted phosphorylation levels of c-Jun and NF-κB, compared to the MOD group (Figure 2E,F). These data clearly demonstrated that high or low doses of NaA have opposed effects on inflammation in macrophages. ## 2.3. NaA Regulates M1 but Not M2 Macrophages To further investigate the effects of various concentrations of NaA on the activity of macrophages, murine macrophage RAW264.7 cells were co-cultured with different doses of NaA for 24 h and then stimulated with LPS for 6 h, respectively. It is known that M1/M2 macrophage balance polarization governs the fate of inflammation [32]. So, in this study, a flow cytometric assay was used to analyze the effect on macrophage inflammatory response. The results of flow cytometry showed that the ratios of M1 macrophage polarization significantly increased after LPS induction (MOD), while NaA-H inhibited M1 macrophage polarization (from $54.6\%$ to $48.1\%$) compared with the MOD group. NaA-L treatment aggravated M1 macrophages (from $54.6\%$ to $58.1\%$) compared to the MOD group (Figure 3). ## 2.4. NaA Alters Intracellular Free Acetate Content by Entering Macrophages and Regulating Lipid Synthesis Next, we examined whether GPR43, a promising acetate receptor [33], participates in NaA regulating RAW264.7 cell activity. The GPR43 siRNA was used to silence its target mRNA, specifically in RAW264.7; three siGPR43 sequences, i.e., siGPR43-1, siGPR43-2, and siGPR43-3, were designed. The qRT-PCR results showed that RAW264.7 cells had very low background expression of GPR43 in the context of this experiment (Figure S1A), and the gene silence did not affect the role of NaA. This indicated that NaA-induced activation of RAW264.7 was independent of GPR43. In addition to G proteins, histone deacetylase enzymes may also act as target sites of SCFAs. Since the GPR43 receptor does not influence the function of NaA, the impact of NaA on HDACs, which is speculated to be involved in the beneficial effects of SCFAs, was further investigated [34]. Compared to the CON group, LPS or NaA treatment did not significantly alter the expression of HDACs (Figure S1B). These results indicated that GPR43 or HDACs might not participate in the modulation of NaA on macrophages. On the other hand, NaA may enter into the cells and exert its role. To verify this hypothesis, we used GC-MS to detect the intracellular acetate content after RAW264.7 cells incubated with NaA. Compared to the CON and MOD groups, treatment with NaA-H caused a significant increase in the content of acetate. Intriguingly, the levels of intracellular acetate descended in the NaA-L group compared with the MOD or CON groups. The content was about 21.3 g/g prot, accounting for only $\frac{1}{4}$ of the CON group and $\frac{1}{2}$ of the MOD group. On the contrary, NaA-H treatment significantly increased intracellular acetate compared to the MOD or CON group (Figure 4A). We observed that the intracellular acetate content of RAW264.7 cells treated with NaA was consistent with the trend that acetate regulated RAW264.7 cell activity. These results showed that NaA might modulate RAW264.7 activation by altering intracellular acetate content. Acetate might be used as a substrate for cell lipid synthesis, and lipid accumulation can aggravate the inflammatory response of macrophages. In order to clarify whether NaA regulated the inflammatory response of cells by affecting lipid synthesis, we determined the enrichment of RAW264.7 cells for TG, TC, lipid synthesis protein ACSS2, and lipid synthesis-related genes (FAS, Scd1, and ACC1). The results showed that NaA-L or NaA-H markedly increased the levels of TC or TG compared with CON and MOD groups (Figure 4B,C). Next, we investigated the role of ACSS2 in the upregulation of fat deposition in RAW264.7, where WB results showed that ACSS2 was highly expressed in the group of NaA (Figure 4D). Similarly, the mRNA levels of Scd1, FAS, and ACC1 in RAW264.7 with LPS were significantly elevated by NaA (Figure 4E). Our findings indicated that NaA has a critical function in fat accumulation linking activation of macrophages, while both high and low doses of NaA can increase cell lipid synthesis. The inhibition of macrophage inflammatory response by NaA-H may depend on other pathways. ## 2.5. NaA Regulates Macrophage Inflammation Response Dependent on the AMPK Signaling Pathway We wanted to investigate whether the metabolic effects of NaA might be mediated through the activation of AMPK, which is considered the target of SCFAs involved in the alleviation of metabolic disease. Our previous study showed that NaA could have a regulatory role in organismal diseases by regulating the phosphorylation of AMPK [31]. Furthermore, we used HPLC to measure the intracellular ratio of AMP/ATP. We observed that the AMP/ATP ratio was significantly decreased in the MOD group compared with the control treatment and further reduced in the NaA-L group, while it was restored in the NaA-H group. This result is consistent with the trend of inflammatory activation of macrophages. The ratio of AMP/ATP could contribute to the changes in the AMPK phosphorylation level (Figure 5A,B). To make sure whether AMPK was involved in NaA-mediated RAW264.7 inflammation, Compound C was used to block the expression of AMPK. Pre-treatment with Compound C significantly attenuated the expression of phospho-AMPK and eliminated the NaA-suppressed overexpression of phospho-c-Jun and phospho-NF-κB (Figure 5C,D). When taken together, these data suggest that NaA regulates the activation of macrophages in an AMPK-dependent manner. ## 2.6. NaA Modulates Macrophages Inflammation Activation by Activating the PPARγ-UCP2-AMPK-NF-κB-IκBα-iNOS Pathway NaA treatment changed macrophages’ ATP concentrations and altered AMP/ATP ratios. The latter is a direct activator of AMPK [35]. Reduced ATP concentrations can result from increased mitochondrial proton leakage, leading to mitochondrial uncoupling and subsequently reduced ATP synthesis [36]. In line with this, treatment with NaA led to altered expression of UCP2 (Figure 6A), a mitochondrial uncoupling protein [36]. Next, we studied how NaA activated the UCP2-AMPK pathway. Possible candidates were PPARγ, well-known regulators of UCP2 expression, fatty acid oxidation, and whole-body lipid metabolism [35]. NaA did change the expression of PPARγ (Figure 6B), suggesting that PPARγ may be the mediating factor between NaA and the UCP2-AMPK pathway. Since AMPK deletion leads to NF-κB activation and there is a possibility that AMPK inhibits IKK-dependent IκBα phosphorylation either directly or indirectly, we investigated if the macrophages’ activation by acetate regulation is mediated through AMPK and the specific mechanisms by which AMPK functions [37]. Subsequently, we examined the role of NaA in the activation of the transcription factor, NF-κB mediated by IκBα, which is required for the transcriptional expression of genes related to inflammation. LPS and NaA-L treatment markedly induced the phosphorylation of IκBα compared with the CON group. Nonetheless, these increases could be attenuated by treatment with 2 mM of NaA (Figure 6C), thus demonstrating that NaA regulates the activation of NF-κB regulated by IκBα. The anti-inflammatory activity of AMPK is exerted through multiple signaling pathways, including phosphorylation and activation of inducible nitric oxide synthase (iNOS) and nitric oxide (NO) production. In addition, NO may act as an endogenous activator of AMPK, suggesting a reciprocal relationship between AMPK and iNOS [38]. Accordingly, the iNOS/NO system is likely to participate in such an acetate mechanism, which we also evaluated. The qRT-PCR results showed basal iNOS levels in the CON group. Treatment with NaA and LPS did change iNOS levels compared to the basal level of the CON group. qRT-PCR data showed that treatment with LPS and NaA-L significantly reduced the expression of iNOS compared with the basal level. In contrast, RAW264.7 from the NaA-H group exhibited a significant addition in iNOS levels compared with the NaA-L group (Figure 6D). ## 2.7. NaA-Driven Macrophage Factors Regulated Hepatocyte Fat Deposition in Co-Culture Experiment We clearly showed that NaA could bi-directionally regulate macrophage activity. Next, we verified whether this process might have a role in NAFLD and whether it also has a two-way regulatory effect on fat accumulation in hepatocytes. First, we verified the direct effect of NaA on fat accumulation in hepatocytes. The AML-12 hepatocytes were treated with NaA in the presence of PA. The viability of AML-12 cells was not significantly reduced by incubating with either 0~10 mM NaA. However, incubation of AML-12 hepatocytes with PA medium resulted in a marked increase in hepatocyte fat deposition, and this increase was significantly enhanced upon treatment with NaA at various concentrations (0.1 and/or 2 mM). The enhancement effect of NaA was in a concentration-dependent manner from 0.1 to 2 mM (Figure 7A). In line with this, the incubation of AML-12 hepatocytes with PA and NaA led to the increased production of TC and TG, and the increase in TC and TG was also positively correlated with the concentration of NaA (Figure 7B,C). Next, we sought to examine changes in the expression of genes related to lipid metabolism. Compared with the control medium, the PA-added medium markedly increased the mRNA levels of FATP2, FAS, ACC1, SREBP-1c, and Scd1. Compared with the MOD group, NaA treatment increased the production of FATP2, FAS, ACC1, SREBP-1c, and Scd1 by 53.94, 32.48, 90.06, 55.60, and $74.29\%$ at 0.1 mM, respectively and by 128.74, 121.89, 188.63, 210.03 and $189.75\%$ at 2 mM, respectively. Similarly, overexpression of genes was promoted, and there was a dose-response relationship from 0.1 to 2 mM (Figure 7D). The functions of the liver can be achieved through cellular communication between hepatocytes, macrophages, and vascular endothelial cells. Because macrophages are believed to patrol systemic conditions [39], Kupffer cells, liver-resident macrophages, are likely to sense and react to inflammation. Therefore, we hypothesized that macrophages secrete molecules in response to extracellular inflammation that affects hepatocytes’ lipid accumulation. Thus, AML-12 cells were treated with a conditioned medium from RAW264.7 cells. Incubation of AML-12 hepatocytes with PA resulted in a marked increase in hepatocyte fat deposition and TC and TG content, and this increase was significantly reduced upon treatment with NaA at 2 mM concentrations. Interestingly, NaA-L exacerbated PA-induced lipid accumulation in AML-12 hepatocytes (Figure 7A–C). Concerning the expression of genes for lipogenesis, treatment with NaA-L significantly upregulated the mRNA levels of FATP2, FAS, ACC1, SREBP-1c, and Scd1 compared with MOD treatment in a PA-contained medium. In contrast, incubation of AML-12 with NaA-H significantly decreased macrophage-induced overexpression of FATP2, FAS, ACC1, SREBP-1c, and Scd1 (Figure 7E). Next, we performed macrophage and hepatocyte co-cultures to further examine whether NaA facilitates macrophages’ generation of factors to promote NAFLD aspects. PA-induced hepatocyte fat deposition in NaA-L treated co-cultures of RAW 264.7 and AML-12 hepatocytes were much greater compared to the MOD group. However, this increase in hepatocyte fat deposition was not observed in NaA-H-treated co-cultures of RAW 264.7 and AML-12 hepatocytes. Conversely, NaA-H significantly reduced AML-12 hepatocytes lipid deposition through co-culture with RAW 264.7 (Figure 7A–C,F). Together with the findings presented in Figure 7E, these results strongly indicated that NaA-H could alleviate fat deposition in hepatocytes, especially lipogenesis, by inhibiting the inflammatory response of macrophages, while NaA-L exacerbated LPS-induced macrophages (RAW 264.7) inflammatory activation, which in turn aggravated AML-12 hepatocytes lipid deposition. ## 3. Discussion The present study demonstrated that NaA could bi-directionally regulate macrophage activity. We also found that NaA entry into cells alters intracellular acetate concentration independent of GPR44 or HDACs. Besides, NaA regulates the inflammatory pathways induced by LPS in macrophages by modulating AMPK-dependent IκBα/NF-κB activation. Moreover, NaA was found to regulate hepatocyte lipid accumulation through macrophage-hepatocyte interactions bi-directionally. To the best of our knowledge, this study first reported a dose-dependent bidirectional regulation of macrophage inflammatory response and mechanism by NaA. Our results showed that NaA could regulate macrophages in both directions over a range of concentrations (0.1~2.0 mM). Importantly, these concentrations reflect the range of SCFA concentrations observed in human blood [8,30]. In addition, this study observed that NaA could increase lipid accumulation in hepatocytes at high and low doses when it acts directly on hepatocytes. Differently, we found that high and low doses of NaA inhibited or aggravated the inflammatory response of macrophages and then inhibited or aggravated the fat accumulation of hepatocytes through the interaction between macrophages and hepatocytes, showing a potential bi-directionally regulatory effect on NAFLD. Lipid accumulation can cause cells to be more sensitive and susceptible to inflammatory responses [15,40]. Previous studies reported inconsistent effects of NaA on the inflammatory response and lipid accumulation. For example, NaA can be converted to an excess of acetyl-CoA, which increases pro-inflammatory cytokine gene histone acetylation by increased substrate concentration and HDAC inhibition, leading to enhanced gene expression and perpetuation of the inflammatory response of macrophages [27]. In addition, ACSS2 facilitates the consumption of extracellular acetate as an alternative carbon source and leads to lipid deposition, causing an inflammatory response in tumor cells [41,42]. On the contrary, NaA can improve cellular lipid deposition and inflammatory response by activating AMPK [31,35] and exerting an anti-inflammatory role as a GPR43 ligand [20]. The results of this study may explain the inconsistent results from previous studies reporting that NaA improved or aggravated fatty liver with dose-dependent effects. NaA regulates macrophage activity independently of the classical GPR43 receptor or as an inhibitor of HDACs but exerts a bidirectional regulation by entering the cell and changing the intracellular acetate concentration. The biological responses of NaA on host cells result from the inhibition of HDACs or the activation of GPRs, such as GPR41 and GPR43 [43]. The results in this study are consistent with the previous report, wherein SCFAs attenuated intestinal inflammation by entering Caco-2 cells [44] through monocarboxylate transporter 1 (MCT1) or sodium monocarboxylate transporter 1 (SMCT1) transport protein and acted independently of GPR43 or HDACs [31]. Similarly, another study indicated that acetate was absorbed mainly by passive diffusion, accumulated inside m-ICcl2 cells, and stimulated lipid consumption in enterocytes [45]. The altering intracellular concentration of NaA demonstrated that NaA partially influenced RAW264.7 cell activation by entering the cells. The bidirectional regulatory effect of NaA on macrophages mainly occurs by altering the intracellular free acetate content. NaA increases fatty acid synthesis by entering cells, leading to lipid deposition in macrophages and lipid accumulation in macrophages, eventually activating cellular inflammation. On the one hand, NaA can promote cellular inflammatory response by synthesizing lipids and promoting lipid accumulation in macrophages, either high dose or low dose. NaA may increase lipid generation through increased ACSS2 expression, which could be through increased substrate supply (although this acetate must be in the form of acetyl-CoA) [36]. In line with this, previous studies also demonstrated that SCFAs, especially acetate, contributed to obesity and liver steatosis as they provide approximately $10\%$ of daily caloric consumption and might enhance nutrient absorption by promoting the expression of glucagon-like peptide 2, obesity, and liver steatosis that could trigger liver inflammation and NAFLD [35]. On the other hand, using NaA to synthesize substrates leads to changes in the actual intracellular acetate content. Low doses of NaA are mainly used to promote lipid synthesis, leading to the consumption of acetate and lower intracellular free acetate content. Accordingly, low doses of NaA are mainly used to synthesize lipids [46], and lipid accumulation contributes to the progression of inflammation and disease [47]. High doses of NaA similarly act as a substrate for lipid synthesis but can increase the intracellular free acetate content after offsetting consumption. However, a high dose of sodium acetate reduced the inflammatory response of macrophages. A previous study also showed that NaA could alleviate NASH in mice by alleviating macrophage inflammation [25] or inhibiting the inflammatory response induced by lipid deposition in hepatocytes [31,35]. Yet, whether NaA directly changes intracellular acetate concentration or regulates intracellular metabolism to change acetate concentration needs to be further verified using isotope labeling or other ways. Our results also indicated other mechanisms through which NaA inhibits macrophage inflammation, achieving an even stronger inhibitory effect than the pro-inflammatory effect of lipid synthesis. Further research is required to establish the relationship between lipids and inflammation in more detail. AMPK is a key site in acetate’s bidirectional regulation of macrophage activity. It is identified as a crucial regulator of metabolism. Previous studies reported that enterocytes exposed to acetate induced a marked increase in phosphorylated AMPK and ameliorated lipid metabolism [48]. We previously reported that high-dose NaA treatment could affect the activation state of macrophages and hepatic astrocytes by activating AMPK. Of particular importance, it was shown that low doses of NaA had no significant effect on AMPK [25,31]. Therefore, the present study focused on investigating whether acetate’s bidirectional regulatory effects on the regulation of macrophage activity were related to AMPK. Recent reports have detected that AMPK activation is key in inflammation inhibition, particularly via the NF-kB signal pathway [49], and regulates M1/M2 macrophage polarization [36,49]. We observed that high and low NaA concentrations regulate the AMP/ATP ratio bidirectionally, controlling the phosphorylation level of AMPK. Moreover, after the inhibition of AMPK activity, the macrophage-modulating effect of NaA disappeared, confirming that AMPK was an important key site for bidirectional regulation. We observed that NaA could alter the intracellular free acetate content through entry to alter the expression of lipid synthesis genes (Scd1, FAS, and ACC1) and proteins (ACSS2), thus changing the intracellular acetate content. Furthermore, NaA could affect UCP2 expression by regulating PPARγ activity. Recent reports suggest that PPARγ is a central regulator of the role of SCFAs in regulating organismal immunity, which is also a known regulator of UCP2 expression, fatty acid oxidation, and whole-body lipid metabolism [31,35]. In addition, changes in UCP2 expression can lead to cell uncoupling, thus affecting intracellular ATP concentration [35] and altering intracellular AMP/ATP concentration, which is the main cause of AMPK activation. Hence, we found bidirectional regulation of intracellular acetate concentration and direct regulation of PPARγ by NaA. Our findings demonstrated that the PPARγ-UCP2-AMPK pathway mediated the pharmacological effect of NaA on macrophage activation. NaA achieves a bidirectional modulatory effect on inflammation through bidirectional regulation of AMPK activity. Given that NF-κB and c-Jun are major effector molecules of NaA in LPS-treated RAW264.7 cells, we tried to investigate how these effectors stimulate the other molecules relevant to inflammatory processes. NF-κB is a multifaceted transcriptional regulator that moves into the nucleus during the activation of IκBα to regulate gene expressions related to the apoptotic and inflammatory responses [17]. AMPK has an extensive role in numerous pathways and is especially closely related to metabolic diseases [50]. In addition, it has been identified as a central modulator in macrophage function. AMPK is exerted through multiple signaling pathways, including the phosphorylation and activation of iNOS and NO production. NO may act as an endogenous activator of AMPK, suggesting a reciprocal relationship between AMPK and iNOS [38]. Moreover, NO can directly inhibit the activity of NF-κB through the phosphorylation of IKβα, an NF-κB inhibitory protein [17,38]. Our results revealed that NaA regulates the level of iNOS and the phosphorylation of IKβα mediated by AMPK to regulate the activation of NF-κB as evoked by LPS. Considering the effect of c-Jun on the NF-κB activity, many previous studies demonstrated that activated c-Jun could stimulate the transcriptional activation of NF-κB in promoting inflammation [17,38,51]. Consistent with this, our results suggest that NaA can influence the activation of c-Jun. Hence, it is conceivable that NaA harbors an important function in blocking the NF-κB-mediated apoptotic pathway by inhibiting oxidative c-Jun activation. Overall, our results suggest that AMPK is responsible for the modulation of the c-Jun and NF-κB pathways induced by NaA. ## 4.1. Materials and Reagents RAW264.7 cells, a cell line of mouse macrophages, were purchased from the Stem Cell Bank, Chinese Academy of Sciences (Shanghai, China). Kupffer cells, a cell line of mouse liver macrophages, were purchased from BeNa Culture Collection (Beijing, China). AML-12 cells, a line of mouse hepatocytes, were purchased from Stem Cell Bank, Chinese Academy of Sciences, Dulbecco’s modified Eagle’s medium (DMEM), Roswell Park Memorial Institute (RPMI) 1640, and fetal bovine serum (FBS) were purchased from Gibco (Grand Island, NY, USA). 100 U/mL penicillin and streptomycin, Lipopolysaccharides (LPS), Enhanced Cell Counting Kit 8 Assay, and Goat anti-rabbit horseradish peroxidase-conjugated secondary antibody were from Beyotime (Beijing, China). Sodium acetate was acquired from Sigma-Aldrich (St. Louis, MO, USA). SYBR Premix Ex Taq was purchased from TaKaRa (Beijing, China). TRIzol Reagents were purchased from Ambion (Austin, TX, USA). The commercial kits for TC/TG were obtained from Nanjing Jiancheng Bioengineering Co., Ltd. (Nanjing, China). The rabbit polyclonal antibodies specific to NF-κB p65, Pp65, phosphorylated c-Jun (Ser63) (p-c-Jun), c-Jun, β-Actin, phosphorylated Adenosine5’-monophosphate activated protein kinase (pAMPK), AMPK, ACSS2, uncoupling protein 2 (UCP2), peroxisome proliferator-activated receptor γ (PPARγ), a phosphorylated inhibitor of nuclear factor kappa B (pIκBα) and IκBα were obtained from Abcam (Shanghai, China). $\frac{6}{12}$/96-well plates were purchased from Corning (Corning, NY, USA). ## 4.2. Cell Culture and Treatment RAW264.7 cells were cultured in DMEM containing $10\%$ FBS and $1\%$ 100 U/mL penicillin and streptomycin in a $5\%$ CO2 incubator at 37 °C. In addition, Kupffer cells were cultured in RPMI 1640 containing $10\%$ FBS and $1\%$ 100 U/mL penicillin and streptomycin in a $5\%$ CO2 incubator at 37 °C. In order to study the effects of NaA on LPS-induced inflammation, RAW264.7 or Kupffer cells were seeded in 6-well plates at a density of 1 × 106 cells/2 mL DMEM or RPMI 1640 medium. After achieving 70~$80\%$ confluency, the cells were subjected to 12 h of serum starvation, after which the CON group (control group) was incubated with fresh DMEM or RPMI 1640 medium, and the cells in the other group were incubated with DMEM or RPMI 1640 medium with varying concentrations of NaA (0, 0.01, 0.05, 0.1, 0.5, 1, 1.5, 2 or 5 mM) for an additional 24 h in the presence of LPS (100 ng/mL) for the last 30 min to examine inflammatory signaling or LPS (20 ng/mL) for 6 h to quantify the expression of genes for fat metabolism and cytokines. Subsequently, the cells were harvested for Western blot analysis and/or total RNA isolation. In order to examine the effects of molecules released from RAW264.7 cells on the AML-12 cells, the conditioned medium was prepared from RAW264.7 cells. First, RAW264.7 cells were cultured with the control DMEM or LPS-contained DMEM in the absence of FBS for 24 h. Next, the culture supernatant was obtained by centrifugation at 3000× g for 3 min using conditioned medium. Finally, some AML-12 cells were incubated without a conditioned medium and served as the control. All groups were incubated with fresh media for 24 h and treated with sodium palmitate (PA, 250 mmol/L) or control in the presence of different concentrations of NaA (0.1, 2 mM) for the last 24 h and assessed for fat deposition. In order to examine the direct effect of macrophage activation on hepatocyte fat deposition, AML-12 cells were incubated with RAW264.7 cells and assayed for hepatocyte fat deposition. Confluent RAW264.7 were seeded above transwell 12 well inserts with a pore size of 0.4 μm for incubation in DMEM. Once RAW264.7 monolayers were established, cells were washed once with phosphate-buffered saline (PBS). Cells in the CON group (control group) were incubated with fresh DMEM medium, while cells in NaA-L and NaA-H groups were incubated with DMEM or RPMI 1640 medium with 0.1 mM or 2 mM of NaA, respectively, for 24 h in the presence of LPS (20 ng/mL) for the last 6 h. Cells treated with LPS without NaA were used as the model group (MOD). Confluent AML-12 cells were seeded in DMEM with PA in lower transwell chambers so that RAW264.7 were suspended above AML-12 on the porous transwell membrane and stimulated with NaA and PA as mentioned above. Controls comprised RAW264.7 and AML-12 cultured alone in upper and lower transwell chambers. Lysates from lower transwell chambers were separately collected at 24 h [8,52]. The detailed process was included in Figure S2. ## 4.3. Cell Cytotoxicity Assays An Enhanced Cell Counting Kit 8 Assay (Beyotime, Shanghai, China) was used to determine the cell cytotoxicity of NaA. RAW264.7 or Kupffer cells were seeded at a density of 5 × 103 per well onto flat-bottom 96-well culture plates (Corning, Corning, NY, USA). Cells were treated with NaA (0, 0.01, 0.05, 0.1, 0.5, 1, 2, 5, or 10 mM). The absorbance values of viable cells were finally determined at 450 nm using a microplate spectrophotometer (BioTek, Winooski, VT, USA). The cell inhibitory rates were calculated using the following formula: Cell inhibition rate (%) = (1 − A450 (sample)/A450 (control)) × 100. ## 4.4. Western Blot Total protein was isolated from cultured cells using a lysis buffer supplemented with protease and phosphatase inhibitors. The protein concentration was measured using a protein assay kit (Bio-Rad, Hercules, CA, USA). An equivalent of 30 μg protein extract was separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene difluoride membranes (PVDF). The membranes were incubated with the following primary antibodies: NF-κB p65, Pp65, p-c-Jun, c-Jun, β-Actin, pAMPK, AMPK, ACSS2, UCP2, PPARγ, pIκBα and IκBα (Abcam, Shanghai, China). After incubation with a goat anti-rabbit horseradish peroxidase-conjugated secondary antibody (Beyotime, Shanghai, China) at a dilution of 1:10,000 for 1 h, the proteins were finally visualized using a Luminata Forte Enhanced Chemiluminescence Kit (Millipore, Billerica, MA, USA) and detected by Imager 600 (Amersham, Switzerland). The band intensities were analyzed using ImageJ 1.54b (NIH). ## 4.5. Quantitative Real-time Polymerase Chain Reaction (qRT-PCR) Total RNA was extracted using TRIzol Reagents (Ambion, Austin, TX, USA) and subjected to reverse transcription using a Prime Script RT-PCR kit (TaKaRa, Beijing, China). The qRT-PCR was carried out using SYBR Premix Ex Taq (TaKaRa, Beijing, China) on the Light-Cycler 480 (Roche Diagnostics) and analyzed by the LightCycler® 96 1.1 (Roche Diagnostics). The primers were synthesized by Sangon Biotech, China (Table S1). The fluorescence data of the target genes were analyzed by the 2−ΔΔCt method for relative quantification using Actin or GAPDH as an internal control. ## 4.6. Measurement of Intracellular Acetate Content Sodium acetate extraction was performed as follows: 108 cells were mixed with 2 mL extraction reagent (water: phosphoric acid = 1:3) and homogenized for 20 s at 6500× g using a Precellys 24 homogenizer (Bertin Technologies, Montigmyle Bretonnexux, France). The cell extract was prepared by adding 2 mL ether on ice for 10 min, followed by centrifugation at 4000× g for 20 min [53]. The remaining aqueous layer was further extracted with ether, after which the ether layers were pooled and diluted to 2 mL. Next, samples were subjected to gas chromatography-mass spectrometer (GC-MS) analysis using a 7890B gas chromatograph/5977 mass selective detector (Agilent Technologies, Santa Clara, CA, USA) with an HB-5 ms capillary column (30 m × 0.25 mm × 0.25 µm film thickness) (Agilent Technologies, Santa Clara, CA, USA). Pure water was used as a blank sample to correct the background. A blank sample was processed similarly to that of fecal samples. The corrected peak area of acetate was calculated by the peak areas of samples minus that of the blank sample detected under the same conditions. ## 4.7. Flow Cytometry Analysis RAW264.7 cells were detected by flow cytometry. Fc receptors of the above cells were first blocked with anti-mouse CD$\frac{16}{32}$ antibody (BioLegend, San Diego, CA, USA), after which the cells were respectively stained with fluorescent antibodies, including PE-conjugated anti-mouse CD86 antibody (BioLegend, San Diego, CA, USA), Brilliant Violet 421-conjugated anti-mouse CD206 (BioLegend, San Diego, CA, USA). The fluorescence antibodies were performed using intracellular staining as previously described [54]. Meanwhile, cells were respectively stained with isotype-matched control antibodies. Finally, prepared samples were measured and analyzed using a Cyto FLEX flow cytometer (Beckman Coulter, Brea, CA, USA). ## 4.8. Small Interfering (si) RNA Transfection siRNA targeting GPR43 or control siRNA were synthesized by Biolino Biotech (Tianjin, China) (Table S2). Transfections were performed using the Lipofectamine® 2000 RNAiMax reagent (Invitrogen, Karlsruhe, Germany) following the manufacturer’s instructions. As previously described, cells were treated with different concentrations of NaA and LPS for 24 h after 24 h post-transfection. qRT-PCR confirmed the downregulation of the GPR43 targeted by siRNA. ## 4.9. Measurement of Intracellular AMP:ATP Ratio Following exposure to sodium acetate, RAW264.7 cells were washed three times with ice-cold PBS, and intracellular nucleotides were extracted by adding 3 mL of ice-cold aqueous acetonitrile ($50\%$, v/v) (VWR, Radnor, PA, USA) to cells. The resulting suspension was maintained on ice for 10 min, followed by centrifugation at 14,000× g for 1 min at 0 °C. Next, the supernatant was collected and dried using a refrigerated Savant SpeedVac vacuum concentrator (Thermo Fisher Scientific, Waltham, MA USA), after which the dried extract was resuspended in 240 μL of deionized water and filtered using a 0.22 μm syringe filter unit for high-performance liquid chromatography (HPLC) analysis [45]. The chromatographic separation and analysis were performed on an Agilent system (1200 series) equipped with a diode-array detector and a C18 reverse-phase column (Kromasil, 5 μm, 100 Å; 4.6 × 150 mm) at a flow rate of 1 mL/min and a linear gradient of acetonitrile (0~$7\%$) in 10 mM triethylammonium acetate buffer (Glen Research, Sterling, VA, USA) over 20 min. AMP and ATP were identified based on their retention times. ## 4.10. Biochemical Assays The levels of TG and TC were quantified using a triglyceride assay kit and a total cholesterol assay kit, respectively, according to the manufacturer’s protocols (Jiancheng, Nanjing, China). Hepatocyte lipid accumulation was analyzed using Oil Red O staining (Solarbio, Beijing, China), and the colorimetric assay was used to quantify triglyceride content. ## 4.11. Statistical Analyses All experiments were conducted in parallel at least three times, and the data were presented as the mean ± the standard deviation (SD). The normality of the data was checked using the Kolmogorov–Smirnov test. One-way analysis of variance (ANOVA) and LSD post-tests were used to analyze the data after it passed the normality test by SPSS 20.0(Norman Nie, Chicago IL, USA). Differences were considered significant at a two-tailed p-value less than 0.05. ## 5. Conclusions In this study, we found for the first time that NaA has a bidirectional modulatory effect on macrophage activity with dose-dependent effects, and high doses of NaA can inhibit macrophage inflammatory response and suppress hepatocyte fat accumulation based on macrophage-hepatocyte interactions. The macrophage AMPK activation state was found to be a key site of the bidirectional regulatory mechanism. The present study provides reliable evidence for the effective dose as well as a mechanism of NaA amelioration of NAFLD. It also revealed a bidirectional regulatory effect and dose effect of NaA on macrophage activity. 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--- title: α-Mangostin Inhibits the Activation of Myofibroblasts via Downregulation of Linc-ROR-Mediated TGFB1/Smad Signaling authors: - Yu-Hsien Lee - Pei-Ling Hsieh - Shih-Chi Chao - Yi-Wen Liao - Chia-Ming Liu - Cheng-Chia Yu journal: Nutrients year: 2023 pmcid: PMC10051815 doi: 10.3390/nu15061321 license: CC BY 4.0 --- # α-Mangostin Inhibits the Activation of Myofibroblasts via Downregulation of Linc-ROR-Mediated TGFB1/Smad Signaling ## Abstract Oral submucous fibrosis (OSF) is a premalignant disorder and persistent activation of myofibroblasts is implicated in this pathological progression. Increasing attention has been addressed towards non-coding RNA-regulated myofibroblasts activities and the effects of phytochemicals on non-coding RNA modulation are of great importance. In the present study, we examined the anti-fibrosis property of α-mangostin, a xanthone isolated from the pericarp of mangosteen. We found that α-mangostin exhibited inhibitory potency in myofibroblast activities and expression of fibrosis markers at the concentrations that caused neglectable damage to normal cells. Apart from the downregulation of TGF-β1/Smad2 signaling, we found that α-mangostin attenuated the expression of long non-coding RNA LincROR as well. Our results demonstrated that the effects of α-mangostin on myofibroblast activation were reverted when LincROR was overexpressed. Additionally, we showed the expression of LincROR in OSF specimens was elevated and silencing of LincROR successfully attenuated myofibroblast characteristics and TGF-β1/Smad2 activation. Taken together, these findings indicated that the anti-fibrosis effects of α-mangostin merit consideration and may be due to the attenuation of LincROR. ## 1. Introduction Oral submucous fibrosis (OSF) is a potentially malignant disorder that was first reported by Schwartz in 1952. This chronic scarring disease is characterized by juxta-epithelial inflammation and collagen deposition, leading to difficulty in mouth opening. Aside from the development of vertical fibrous bands, patients often have burning sensations, ulceration, and pain. Moreover, its malignant transformation rate is around $5\%$ [1] and the hazard rate ratio of tongue lesions is higher than buccal lesions [2]. The etiology of OSF is multifactorial, such as genetic susceptibility [3], human papillomavirus (HPV) infection [4], consumption of tobacco, alcohol, and areca nut [5]. Among these factors, the habit of areca nut chewing has been postulated as the main causative event. It has been demonstrated that collagen phagocytosis of buccal mucosal fibroblasts (BMFs) was reduced in response to areca nut alkaloids stimulation [6]. Moreover, the expression of tissue inhibitor of metalloproteinase-1 (TIMP-1) was elevated and matrix metalloproteinase 2 (MMP-2) was inhibited in BMFs treated with arecoline, a major alkaloid ester in areca nut [7,8]. These results suggested areca nut chewing resulted in an impairment of matrix degradation in BMFs. Furthermore, constituents of areca nut were found to activate the transforming growth factor-β1 (TGF-β1)/Smad2 pathway in epithelial cells [9] and increase the transdifferentiation of gingival fibroblasts into myofibroblasts [10]. As the pivotal cells to secrete collagen, myofibroblasts have long been a subject of investigation for OSF study in terms of their origin, dynamics, and biological mechanisms. It is well-accepted that fibroblasts differentiate into highly contractile myofibroblasts following injury in order to remodel the extracellular matrix (ECM) scaffold and maintain the structural integrity [11]. In addition to resident fibroblasts, cells that undergo epithelial-to-mesenchymal transition (EMT) appear to be a potential source of myofibroblasts in liver or kidney fibrosis diseases [12,13]. EMT confers cells with mesenchymal phenotype, including migratory and invasive properties. Various transcription factors, such as Slug, Snail, and Twist, are known as repressors of E-cadherin and inducers of EMT [14]. It has been shown that arecoline stimulation elicited the expression of Slug, Snail, and Twist in BMFs [15,16]. Moreover, Slug and Snail were found to mediate myofibroblast transdifferentiation through directly binding to the E-box of type I collagen or alpha-smooth muscle actin (α-SMA) promoter, respectively [15,16]. Snail also has been demonstrated to bind to the interleukin-6 (IL-6) promoter, leading to an increase in α-SMA and type I collagen in fBMFs [17]. TGF-β1 is essential for induction of EMT and fibrosis [8], and several natural compounds have been exploited to suppress OSF via inhibition of TGF-β1 signaling [18,19]. A better understanding pertaining to the inhibitory effect of natural compounds on myofibroblast activation through regulation of the TGF-β1 pathway is of great importance. Over the past decades, numerous studies have revealed that non-coding RNAs serve significant roles in the modulation of myofibroblasts. These non-protein-coding RNAs can be categorized into short (<200 bp; e.g., microRNAs) and long non-coding RNAs (lncRNAs; >200 bp) based on their length. MicroRNAs interact and restrict their target genes via direct binding to sequences located in the 3’ untranslated regions (3’UTR) of mRNAs [20]. LncRNAs can be divided into three categories, including antisense that are transcribed across protein-coding genes on the reverse strand, pseudogenes that are non-translated protein-coding genes and long intergenic non-coding RNAs (lincRNAs) that are located between protein-coding genes [21]. The functions and mechanisms of lncRNAs are more complex. For instance, lncRNAs can act as decoys/competing endogenous RNAs, and bind to their target genes or even microRNAs to downregulate their action [22]. Up to now, a great effort has been made to address the implication of microRNAs in the pathogenesis of OSF (see review [23]). Accumulating research also revealed the significance of lncRNAs in the pathogenesis of OSF. For example, upregulation of lncRNA H19 in BMFs was reported as a result of areca-nut-induced TGF-β/Samd activation, which impeded the suppressive property of microRNA-29b on type I collagen [24]. Another lncRNA, LINC00974, also has been shown to promote arecoline-elicited myofibroblast transdifferentiation via the TGF-β pathway [25] and inhibition of LINC00974 by natural compound successfully mitigated myofibroblast activities [26]. Unlike genic lncRNAs share sequences with coding loci, lincRNAs constitute more than half of lncRNA transcripts but they do not overlap annotated coding genes [27]. To date, the regulation and function of lincRNAs remain an area of interest. Numerous bioactive substances and phytochemicals have been demonstrated to exert pharmacological effects and improve various kinds of diseases, such as cancer or fibrosis disorders. α-, β- and γ-mangostin are xanthones isolated from mangosteen (Garcinia mangostana) and they exhibit a wide range of biological properties. α-mangostin has been revealed to induce apoptosis and cell cycle arrest of oral cancer cells [28]. A study using mucoadhesive film containing α-mangostin also demonstrated the anti-cancer effect on oral cancer cells and anti-inflammatory activities in RAW 264.7 cells [29]. In addition to anti-tumor effects, α-mangostin also possesses inhibitory properties. For instance, it has been revealed to attenuate the bleomycin-induced pulmonary fibrosis [30] and improve cardiac hypertrophy and fibrosis in diabetic rats [31]. Moreover, α-mangostin has been demonstrated to reduce the acetaldehyde-induced liver fibrosis by inhibiting myofibroblast transdifferentiation of hepatic stellate cells along with decreased expression of TGF-β and increased anti-oxidant capacity [32]. Similarly, it markedly suppressed the TGF-β-induced myofibroblast differentiation and oxidative stress in cardiac fibroblasts [33]. Nevertheless, whether α-mangostin can ameliorate oral fibrogenesis has not been elucidated. In this study, we first examined the suppressive effects of α-mangostin on cell viability, myofibroblast activities, TGF-β1/Smad2 pathway and type I collagen. Furthermore, we showed the expression of lincRNA-RoR (LincROR) was downregulated in α-mangostin-treated cells. Linc-RoR is implicated in tumorigenesis and was found to be overexpressed in oral cancer with a strong association with poor prognosis [34]. However, whether the level of lincRNA-RoR was also upregulated in precancerous OSF has not been investigated. Herein, we assessed the expression of lincRNA-RoR in OSF specimens and demonstrated its critical function in the α-mangostin-mediated myofibroblast inhibition. ## 2.1. Tissue Collection, Primary Culture and Reagents All procedures were followed the protocol that is granted from IRB of Chung Shan Medical University Hospital (approval number: CSMUH No. CS18124). After acquiring patients’ consent, the healthy and OSF tissues obtained from surgery were immediately immersed in phosphate buffered saline (PBS) for primary culture or liquid nitrogen for the subsequent quantification of LincROR expression. Normal buccal mucosal fibroblasts (BMFs) and fibrotic buccal mucosal fibroblasts (fBMFs) were isolated from fresh healthy buccal mucosa and OSF tissues, respectively. In brief, the tissues were cut into small pieces (0.5–1.0 mm2) and incubated with trypsin-EDTA ($0.05\%$) at 37 °C for 30 min. After centrifugation at 1200 rpm, the tissue pellets were plated into a 10-cm culture dish with a growth medium at 37 °C/$5\%$ CO2. After 7–14 days of incubation, cells with a spindle shape that crawled out from the tissues were harvested and routinely maintained in growth medium which was composed of the following components: $90\%$ Dulbecco’s Modified Eagle Medium (DMEM), $10\%$ fetal bovine serum (FBS), 100 U/mL penicillin and 100 μg/mL streptomycin. Cells between the third and eighth passages were used in this study. All reagents were purchased from Sigma (St. Louis, MO, USA) unless stated otherwise. ## 2.2. Cell Proliferation and Survival Assay Cells were seeded into a 96-well plate at a density of 1.0 × 104 cells/well for 24 h of incubation, and then replaced with a fresh culture medium containing a series concentration of α-mangostin (0~80 μM) for another 24 h of incubation. Subsequently, the proliferation rate and IC50 value were estimated using 3-(4,5-Dimethyl-2- thiazolyl)-2,5-diphenyltetrazolium bromide (MTT) assay, according to the manufacturer’s protocol (Sigma-Aldrich, St. Louis, MO, USA). The absorbance at 570 nm was determined using a microplate reader (Molecular Devices, San Jose, CA, USA). ## 2.3. Collagen Gel Contraction Assay We embedded cells to type I collagen gel solution (2 ng/mL) at a density of 2.0 × 105 cells/well in a 24-well plate. We mixed the cells and gel solution gently and incubated the plate at 37 °C for 2 h to allow the polymerization of gels. Then, we added 0.5 mL culture medium in each well to cover the gel and incubated for another 48 h for gel contraction by cells. The contraction index was quantified using ImageJ software (NIH, Bethesda, MD, USA) [35]. ## 2.4. Transwell Migration Assays 1 × 105 cells suspended in 150 μL serum-free medium were added into the Transwell inserts (Corning, Acton, MA, USA), and then we added the 750 μL completed growth medium (with $10\%$ FBS) into the lower chamber to create a chemo-gradient that attracted cell migration. After incubation for 24 h, cells were fixed with cold-$100\%$ methanol and stained with $0.1\%$ crystal violet. Then, the non-migrated cells on the topside of the Transwell insert were gently removed using a cotton swab. We counted the number of migrated cells on the underside from five randomly selected fields under the microscope. ## 2.5. Enzyme-Linked Immunosorbent Assay (ELISA) According to the manufacturer’s instructions, the amount of TGF-β in the culture medium secreted from fBMFs treated with 0-4 μM α-mangostin was to be measured by Human TGF-β1 ELISA Kit (Abcam, Cambridge, UK). The absorbance at 450 nm was determined using a SpectraMax M5 microplate reader (Molecular Devices, San Jose, CA, USA). ## 2.6. RNA-Sequencing Total RNA from three independent fBMFs treated with or without α-mangostin was extracted using TRIzol™ Reagent according to the manufacturer’s protocol (Invitrogen Life Technologies, Carlsbad, CA, USA). The RNA quality of each cell was ensured by the manufacturer of Genomics Inc. After RNA-seq library preparation and construction, the changes in transcriptome of cells were analyzed using the FPKM method (fragments per kb of transcript per million mapped reads) on Illumina HiSeq platform (HiSeq2500 platform, Illumina, San Diego, CA, USA) as previously described [17]. ## 2.7. Real-Time Quantitative Polymerase Chain Reaction (Qrt-PCR) Total RNA was extracted from tissues and cells using TRIzol™ Reagent according to the manufacturer’s protocol (Invitrogen Life Technologies, Carlsbad, CA, USA). Complementary DNA (cDNA) synthesis and quantitative polymerase chain reactions were conducted using Superscript III first-strand synthesis system (Invitrogen Life Technologies, Carlsbad, CA, USA) and ABI StepOne™ Real-Time PCR Systems (ThermoFisher Scientific, Carlsbad, CA, USA), respectively. Primer sequences used were listed as follows: LincROR, 5′-CTGGCTTTCTGGTTTGACG-3′ (forward), 5′-CAGGAGGTTACTGGACTTGGAG-3′ (reverse); GAPDH, 5′-CTCATGACCACAGTCCATGC-3′ (forward) and 5′-TTCAGCTCTGGGATGACCTT-3′ (reverse). The expression of LincROR related to GAPDH was calculated using the delta Ct and comparative methods. ## 2.8. Western Blot Analysis The whole cell lysates were obtained using 1×RIPA buffer with protease and phosphatase inhibitor cocktail (Abcam, Cambridge, MA, UK). The total protein concentration of each sample was quantified according to the Bradford assay (Bio-Rad Laboratories Inc., Hercules, CA, USA). Cell lysates containing 20 μg protein were loaded onto $10\%$ SDS-polyacrylamide gel and transferred onto the PVDF membrane (Millipore, Billerica, MA, USA). The PVDF membranes were blocked in $5\%$ bovine serum albumin (BSA) at room temperature for 1 h, followed by incubation with primary antibodies at 4 °C for 16 h and HRP-conjugated secondary antibodies at room temperature for 1 h. The chemical luminescence of each immunoreactive band was developed by adding the ECL chemiluminescent agent and captured by using a LAS-1000plus Luminescent Image Analyzer (GE Healthcare Biosciences, Piscataway, NJ, USA). The primary antibodies are listed as follows: anti-α-SMA (Abcam), anti-COL1A1 (Abcam), anti-p-Smad2 (Cell Signaling Technology, Danvers, MA, USA), anti-Smad (Cell Signaling), and anti-GAPDH (GeneTex Inc., Irvine, CA, USA). ## 2.9. Lentiviral-Mediated Silencing and Overexpression of Lncrna-ROR To construct the lentivirus-LincROR silencing vector (pLV-Sh-LincROR), oligonucleotide sequence shRNA that targets human lincROR was synthesized and ligated into pLV-RNAi vector following the manufacturer’s protocol (Biosettia, San Diego, CA, USA). The target sequences for LincROR are listed as follows: Sh-LincROR-1 5′-AAAAGGAAACTGGCAATGTTGAATTGGATCCAATTCAACATTGCCAGTTTCC-3′; Sh-LincROR-2 5′-AAAAGGAGGATGCAGAGAAATTATTGGATCCAATAATTTCTCTGCATCCTCC-3′. To construct the lentivirus-LincROR overexpressing vector (pLV-LincROR-cDNA), the full-length LincROR cDNA was amplified using RT-PCR and then cloned into a pLV-EF1a-MCS-IRES-Puro vector (BioSettia). The pLV-Sh-LincROR or pLV-LincROR-cDNA vector was co-transfected with the packaging and envelope vectors into 293T cells using Lipofectamine 2000, according to the manufacturer’s protocol (LF2000, Invitrogen, Calsbad, CA, USA) to produce lentiviral particles. Overexpression and knockdown of LincROR were conducted by infecting cells with lentiviral particles carrying full-length LincROR or shRNA sequences targeting LncRNA-ROR, respectively [24]. ## 2.10. Statistical Analysis Data were obtained from at least three individual experiments and were presented as mean ± standard deviation. A Student’s t-test or analysis of variance (ANOVA) were performed to determine the statistical significance of the difference using Statistical Package of Social Sciences software (version 13.0, SPSS, Inc., Chicago, IL, USA). ## 3.1. α-Mangostin Reduces the Cell Viability of Fbmfs and Has Minimal Effect on Normal Oral Cells To determine the cytotoxic effect of α-mangostin (Figure 1A) on normal BMFs and fibrotic BMFs (fBMFs)-derived from OSF tissues, cell proliferation rate was measured after treatment of α-mangostin with various concentrations for 24 h using an MTT assay. In both BMFs and fBMFs, a concentration-dependent inhibitory effect on cell survival was observed. The IC50 values for α-mangostin in BMFs and fBMFs were 21.3 ± 1.2 and 7.3 ± 1.4 μM, respectively (Figure 1B). These results showed that a lower concentration (0–4 μM) of α-mangostin was sufficient to reduce the cell viability of fBMFs without causing severe damage to normal oral cells. ## 3.2. α-Mangostin Suppresses the Myofibroblast Activation of fBMFs Aside from cell proliferation, activated myofibroblasts will migrate to the wound area to restore tissue integrity and close the wound. Hence, we examined the effects of α-mangostin on collagen gel contraction ability, which is a well-established assay to investigate fibroblast-matrix interactions by Bell et al. [ 36]. As shown in Figure 2A, the relative gel area was increased in fBMFs treated with α-mangostin in a concentration-dependent manner, suggesting a higher dose of α-mangostin relieved the contractile activity of fBMFs. Additionally, fBMFs were subjected to transwell migration assay, and the result showed that α-mangostin dose-dependently downregulated the migration capacity of fBMFs (Figure 2B). ## 3.3. Incubation of α-Mangostin Downregulates the Expression of TGF-β1 Signaling, Myofibroblast Marker, and LincROR A plethora of factors have been identified to regulate myofibroblasts, and TGF-β1 is the most notable stimulator of fibrosis. We showed that α-mangostin attenuated the production of TGF-β1 in fBMFs in a dose-dependent fashion (Figure 3A). α-SMA is a well-known myofibroblast marker and its expression upregulates contractile activity [37]. We observed the expression of α-SMA gradually decreased when α-mangostin was applied, suggesting the reduced numbers of myofibroblasts (Figure 3B). Type I collagen is the primary ECM protein deposited by myofibroblasts and it has been revealed that cells from OSF samples generated about $85\%$ type I collagen and $15\%$ type III collagen. Additionally, the ratio of its major components α1 (I) to α2 (I) chains was higher (3:1) in OSF cells than in normal fibroblasts (2:1) [38]. We found that α1 type I collagen (COL1A1) was suppressed by various concentrations of α-mangostin (Figure 3B). In accordance with the reduction of TGF-β1, the protein expression of phosphorylated Smad2 was downregulated as well (Figure 3B). Moreover, the result of RNA sequencing showed that the expression of LincROR was decreased (Figure 3C) and qRT-PCT analysis verified α-mangostin dose-dependently inhibited LincROR (Figure 3D). ## 3.4. The Inhibitory Property of α-Mangostin on Myofibroblast Activities and TGF-β Signaling Is Mediated by LincROR To investigate whether LincROR was implicated in the suppressive effect of α-mangostin on myofibroblast activation, a transwell migration assay was used to show that forced expression of LincROR enhanced the migration capacity of the α-mangostin-treated fBMFs (Figure 4A). Likewise, ectopic expression of LincROR intensified the collagen gel contractility (Figure 4B) and TGF-β1 secretion (Figure 4C) compared to the fBMFs incubated with α-mangostin only. Moreover, the expression levels of α-SMA and phosphorylated Smad2 were re-increased in α-mangostin-treated fBMFs with overexpression of LincROR (Figure 4D). These results demonstrated that the elevation of LincROR counteracted the effects of α-mangostin on myofibroblast activities and TGF-β/Smad2 signaling. ## 3.5. LincROR Is Aberrantly Overexpressed in OSF Specimens After validating LincROR involved in the α-mangostin-mediated suppression of myofibroblast activities, we then assessed the expression of LincROR in OSF samples. As expected, LincROR was differentially expressed between OSF and normal tissues using RNA-Sequencing analysis (Figure 5A). In addition, the expression of LincROR was positively associated with numerous fibrosis-related markers, such as α-SMA (ACTA2), COL1A1, or TGF-β1 (TGFB1) (Figure 5B). To authenticate the result from RNA-Sequencing, qRT-PCR was conducted and showed that the expression of LincROR was elevated in OSF specimens (Figure 5C). Similarly, the expression of LincROR in fBMFs derived from OSF tissues was upregulated compared to normal BMFs (Figure 5D). ## 3.6. Silencign of LincROR Inhibits Myofibroblast Activation Subsequently, we investigated the functional role of LincROR in myofibroblast activation and found that suppression of LincROR relieved the collagen gel contraction ability in fBMFs (Figure 6A). Additionally, fBMFs with sh-LincROR displayed a significant reduction of cell migration capability (Figure 6B) and TGF-β1 production (Figure 6C). Moreover, the expression of α-SMA and phosphorylated Smad2 in fBMFs was decreased when LincROR was silenced (Figure 6D). In brief, these findings suggested the aberrantly overexpressed LincROR may contribute to the persistent activation of myofibroblasts in OSF. In addition, our results suggest that α-mangostin has an inhibitory effect on fBMFs via the regulation of LincROR. ## 4. Discussion Several studies have demonstrated the pharmacological effects of α-mangostin, including antioxidant, anti-carcinogenic and anti-fibrosis activities. Here, we showed that α-mangostin exerted suppressive properties against OSF through the downregulation of lincROR. Our data revealed that the expression of lincROR was aberrantly upregulated in OSF specimens and positively correlated with various fibrosis factors, such as ACTA2, COL1A1 and fibronectin (FN1) (Figure 7). Administration of α-mangostin markedly attenuated the myofibroblast activation of fBMFs as evidenced by lower migratory and contractile capacities along with reduced expression of α-SMA and type I collagen. Suppression of TGF-β1/Smad2 signaling was in favor of our finding regarding the downregulation of myofibroblast activities, and these benefits may be due to the inhibition of lincROR by α-mangostin (Figure 7). Our results were in line with various studies showing that α-mangostin inhibited myofibroblast transdifferentiation and TGF-β-induced fibrotic response via suppressing nicotinamide adenine dinucleotide phosphate oxidase4 (NOX4)-generating reactive oxygen species (ROS) or enhancing antioxidant enzymes, leading to the alleviation of the liver [32], lung [30] or cardiac fibrosis [33]. Likewise, α-mangostin was demonstrated to reduce the expression of IL-6 and IL-8 expression in P. gingivalis LPS-stimulated human gingival fibroblasts [39]. It goes without saying that the anti-inflammatory and antioxidant features of α-mangostin contribute to its inhibitory ability of OSF since part of the pathogenesis of OSF is attributed to the elevation of inflammation and oxidative stress [40]. Our work further demonstrated that α-mangostin can mitigate fibrosis through the modulation of non-coding RNAs. Currently, only a limited number of studies have shown the relationship between α-mangostin and non-coding RNAs. For instance, α-mangostin has been found to restore the hyperglycemia-induced growth inhibition of human umbilical vein endothelial cells via regulation of lncRNA H19 [41]. Our results showed that administration of α-mangostin can modulate lincROR using fBMFs (myofibroblasts). LincRoR is a 2.6 kb lncRNA located in chromosome 18 and was first identified in 2010 for its function as a key “Regulator of Reprogramming” [42]. Later, this pluripotency-associated lincRNA was often regarded as a carcinogenic factor as it was predominantly upregulated in various types of tumors, including oral cancer [34]. It has been shown that the expression of lincRoR was associated with several stemness-related genes, such as Oct4, Sox2, and Nanog. The promoter of the lincRoR gene contained the binding sites for Oct4, Sox2, and Nanog, and the transcription of lincRoR was activated upon binding of these transcriptional factors [42,43]. Apart from being a direct target of key pluripotency transcription factors, lincRoR also prevented these transcriptional factors from microRNA-145-mediated degradation. Accordingly, it has been suggested that lincRoR and these transcriptional factors may form an autoregulatory feedback loop during the self-renewal of embryonic stem cells [42,43]. In agreement with this finding, we showed that lincROR was abnormally overexpressed in precancerous OSF and fBMFs derived from OSF tissues. It also has been demonstrated that the expression levels of Oct4, Sox2, and Nanog were markedly elevated in tumor-adjacent tissues and may be associated with tumor progression of oral cancer [43]. Furthermore, a previous study has shown that chronic exposure of oral epithelial cells to arecoline led to upregulation of Oct4, Sox2, and Nanog as well as an increase in several EMT markers (e.g., Snail, Slug, and Twist) [44]. As such, the elevation of the abovementioned transcriptional factors following stimulation of arecoline may lead to the upregulation of lincRoR in OSF specimens and verification of this hypothesis is worthy of investigation in the future. Considerable attention has been paid toward the emerging roles of lincRNAs in fibrogenesis, especially myofibroblast activation. LincRNAs may exert their modulatory property through the direct binding of target molecules or interaction with microRNAs. For instance, LINC00084 has been proven to function as a sponge of microRNA-204 and titrating the inhibition of microRNA-204 on EMT inducer zinc–finger E–box–binding 1 (ZEB1) in fBMFs [45]. Another study demonstrated that LINC00312 mediated myofibroblast activities via direct interaction of YBX1, a negative regulator of collagen expression [46]. Several studies also suggested that lincROR induces tumorigenesis via the regulation of EMT-associated factors. For example, lincRoR has been found to act as a competing endogenous RNA of microRNA-205, which prevented the degradation of EMT inducer ZEB2 and enhanced the aggressiveness of breast cancer cells [47]. Additionally, lincRoR promoted cell proliferation of pancreatic cancer through the elevation of ZEB1 [48]. Both ZEB1 and ZEB2 have been demonstrated to be implicated in myofibroblast transdifferentiation during OSF development [49,50]. Moreover, another EMT inducer twist family BHLH transcription factor (Twist) was found to be increased after arecoline treatment [51]. One of the recent studies has indicated that lincROR contributed to the chemoresistance of hepatocellular carcinoma through Twist-mediated EMT [52]. As a consequence, it is reasonable to postulate that the overexpressed lincROR may confer to the persistent activation of myofibroblasts through the mediation of EMT-associated factors, such as ZEB1, ZEB2 or Twist. On the other hand, a number of microRNAs also hold the potential of acting as downstream mediators in the lincROR-associated fibrogenesis due to their predicted binding sites shared by lincROR, such as microRNA-145, microRNA-181 [43] and microRNA-205 [47]. LincRoR has been shown to modulate cancer progression via interaction with microRNA-145 [47], and microRNA-145-5p was shown to ameliorate hypertrophic scar through suppression of myofibroblast activation and reduction of Smad$\frac{2}{3}$ [53]. Furthermore, microRNA-181a has been demonstrated as an anti-fibrotic factor in fBMFs [54], and participated in TGF-β-induced EMT in hepatocytes [55]. As for miR-205, it was found to attenuate the angiotensin II-induced fibrosis in vivo and myofibroblast activation in atrial fibroblasts [56]. Given that we observed the decreased myofibroblast activities and TGF-β/Smad2 signaling in fBMFs with sh-lincROR, whether lincROR contributes to the development of OSF via functioning as a competing endogenous RNA of microRNA-145, microRNA-181, or miR-205 requires further investigation. Altogether, our data showed that administration of α-mangostin may alleviate the persistent activation of myofibroblasts through inhibition of the TGF-β/Smad2 pathway and downregulation of the aberrantly overexpressed lincROR. These results suggested that α-mangostin-containing foods may be good nutritional supplements for OSF patients. ## References 1. Iocca O., Sollecito T.P., Alawi F., Weinstein G.S., Newman J.G., De Virgilio A., Di Maio P., Spriano G., Pardiñas López S., Shanti R.M.. 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--- title: Effects of Ethanolic and Aqueous Extracts of Garcinia gardneriana Leaves in an In Vivo Experimental Model Induced by a Hyperlipidic Diet authors: - Bruna Larissa Spontoni do Espirito Santo - Lidiani Figueiredo Santana - Wilson Hino Kato Junior - Felipe de Oliveira de Araújo - Mariana Bento Tatara - Júlio Croda - Danielle Bogo - Karine de Cássia Freitas - Rita de Cássia Avellaneda Guimarães - Priscila Aiko Hiane - Arnildo Pott - Wander Fernando de Oliveira Filiú - Bernardo Bacelar de Faria - Patrícia de Oliveira Figueiredo - Valter Aragão do Nascimento - Frederico Louveira Ayres - Paulo Roberto Haidamus de Oliveira Bastos journal: Nutrients year: 2023 pmcid: PMC10051817 doi: 10.3390/nu15061308 license: CC BY 4.0 --- # Effects of Ethanolic and Aqueous Extracts of Garcinia gardneriana Leaves in an In Vivo Experimental Model Induced by a Hyperlipidic Diet ## Abstract The study of medicinal plants, such as the genus Garcinia (Clusiaceae), in the treatment of non-communicable chronic diseases has aroused the interest of researchers. However, there are no studies in the literature that have investigated the effects of Garcinia gardneriana in experimental models of obesity for possible metabolic alterations. Swiss mice receiving a high-fat diet were supplemented with aqueous or ethanolic extract of G. gardneriana at doses of 200 or 400 mg/kg/day. It was found that there was a reduction in food consumption in experimental groups compared with the control groups, and the group supplemented with aqueous extract at a dose of 200 mg/kg/daydisplayed a reduction in weight. The results showed an increase in the values of high density lipoprotein (HDL-c), total cholesterol, triglycerides and fasting blood glucose. G. gardneriana did not protect against insulin resistance, and caused in an increase in monocyte chemoattractant protein-1 (MCP-1) concentrations and a reduction in interleukin 10 (IL-10). In addition, hepatic steatosis and microvesicular steatosis were indicated. It was revealed that, under the experimental conditions in the study, G. gardneriana did not prevent weight gain or comorbidities; that is, a different behavior was obtained from that described in the literature with regard to the medicinal potential of the Garcinia species, which is probably related to the phytochemical properties. ## 1. Introduction Garcinia is a genus of Clusiaceae plants, belonging to the Guttiferae family, comprising approximately 40 genera and 1200 species distributed in regions such as tropical Asia, Africa, New Caledonia, Polynesia and Brazil [1,2]. The Garcinia species are rich in secondary metabolites, such as prenylated and oxygenated xanthones [3], which have antifungal [4], anti-inflammatory [5], antitumor [6], antioxidant [7] and antilipidemic activities [6,7,8,9], as well as human immunodeficiency virus (HIV) inhibitory properties [8]. Native to the Atlantic Forest, Garcinia gardneriana (Planchon and Triana) Zappi. ( Clusiaceae), or Rheedia gardneriana, is a species of the genus Garcinia that is native to the Atlantic Forest, is easily found and is popularly known as “bacupari”, “bacopari”, “bacopari miúdo” or “yellow mangostão” [10]. In different parts of the plant, xanthones, steroids, triterpenes and flavonoids are found, as secondary metabolites that manifest anti-inflammatory, antinociceptive, antibacterial and antiparasitic effects [3,11,12,13,14]. Such a composition can manifest beneficial effects in the prevention and treatment of obesity, which is a chronic, multifactorial disease (triggered by the influence of social, behavioral, environmental, cultural, psychological, metabolic and genetic issues) and its metabolic changes [15]. Furthermore, it is known that being overweight or obese has increased significantly in recent years and affects both adults ($27.5\%$) and children ($47.1\%$) worldwide [16]. In Brazil, $20.3\%$ of the population is obese, and $55.4\%$ are overweight [17]. Obesity is a chronic disease defined as an abnormal or excessive accumulation of fat, representing a risk for health. The excessive accumulation of fat, mainly in the visceral region, is directly related to the expression of several proteins, favors increased expression of tumor necrosis factor alpha (TNF-α), monocyte chemotactic protein (MCP-1/CCL-2) and interleukin-6 (IL-6) by monocytes and macrophages, manifesting a pro-inflammatory effect. It is also directly related to the development of insulin resistance (IR), which is decisive for the risk of developing several diseases, such as: arterial hypertension, dyslipidemia, insulin resistance, type 2 and metabolic syndrome, pathologies that trigger the development of cardiovascular diseases [18]. In order to reduce the incidence and prevalence of obesity and its metabolic disorders, many treatments are proposed. The literature has aroused interest in investigating the use of medicinal plants with active components that reduce inflammatory markers and oxidative stress, as well as prevent hypercholesterolemia and hypertriglyceridemia [19]. In this sense, the leaves of G. gardneriana present a chemical profile with the presence of a wide variety of phenolic compounds, especially flavonoids, biflavonoids (GB-2a, Fukugentin and Fukugiside), catechins, xanthones, in addition to benzophenones (7-epiclusanone) [11,20], that demonstrate properties associated with pharmacological effects, such as anti-inflammatory, antinociceptive, antibacterial and antiparasitic action. They have promising components for the prevention and treatment of several diseases [11] and have stimulated the development of the study described here, involving an experimental model where a high-fat diet was consumed [21,22]. To date, there are no studies that show the effect of such properties; moreover, there is no evidence of the possible beneficial effect of Garcinia gardneriana (Planchon and Triana) Zappi. ( Clusiaceae) [11] against obesity and its metabolic disorders [23,24]. Thus, the objective of this research was to evaluate the therapeutic effects of ethanolic and aqueous extracts of G. gardneriana in animals receiving a high-fat diet. ## 2.1. Leaf Collection The leaves of G. gardneriana were obtained in an urban area of Campo Grande (latitude 20.533720 and longitude 54.6751460), State of Mato Grosso do Sul, Brazil. It was registered as number A26D547 in the National System for the Administration of Genetic Heritage and Associated Traditional Knowledge (Sisgen). After collection, the leaves were placed in an air ventilation oven at 40 °C in the laboratory of the Food Science Unit (Unical-UFMS-Campo Grande-MS-Brazil) of the Faculty of Pharmaceutical Sciences, Food and Nutrition (Facfan UFMS-Campo Grande-MS-Brazil) of the Federal University of Mato Grosso do Sul (UFMS), then ground and homogenized in a Turrax™ mixer. It was labelled and conserved in dark packages until the preparation of the extracts [24]. ## 2.2. Extract Preparation To obtain the ethanolic extract, the leaves of G. gardneriana were macerated. For each 1 kg of powder, 10 L of ethanol were added and left to rest for 7 days, after which they were filtered. The filtrate was re-extracted with ethanol five more times. For the preparation of the aqueous extract, the leaves were also macerated. For every 1 kg of powdered G. gardneriana leaves 10 L of distilled water was added, kept at rest for 1 day, and then filtered. Both were concentrated under reduced pressure at 37 °C and lyophilized [25]. ## 2.3. Animals The experimental protocol was approved by the Ethics Committee for Animal Use (Protocol no $\frac{1050}{2019}$), according to the International Guiding Principles for Bio-medical Research Involving Animals (CIOMS), Geneva, 1985; the Universal Declaration of Animal Rights (UNESCO), Brussels, Belgium, 1978; and National Institutes of Health guidelines on the use and care of laboratory animals. 130 male Swiss mice of the Mus musculus lineage, adults with 60 days of age, were used. The mice were kept in collective cages (30 × 20 × 13) (GC100) (four to five animals per box) in the animal experimentation room of the Biotherium of the Federal University of Mato Grosso do Sul, under controlled temperature conditions at 22 ± 2 °C. C, relative air humidity of 50–$60\%$ and light/dark cycle of $\frac{12}{12}$ h [26]. ## 2.4. Experimental Design Swiss mice (male and adult) underwent 7 days of adaptation to the new environment, and were then divided into experimental groups, as shown in Figure 1. On the first day of the experimental design, the ration was changed simultaneously with the supplementation, which was performed by gavage, in which saline solution (1 mL/kg of animal weight) was administered to the control groups and the aqueous extract to the experimental groups (200 or 400 mg/kg) or ethanolic extract (200 or 400 mg/kg) of G. gardneriana leaves (Figure 1). The experiment lasted 8 consecutive weeks [27,28,29]. The doses were defined based on a study that used Garcinia cambogia, given, to our knowledge, the absence of in vivo studies with the G. gardneriana species [30,31]. Each group had ad libitum access to water and food during the experimental period; the high-fat diet used in this study was based on that of Lenquiste et al., 2015 [32] and according to experiences of our research group [33] (Figure 2). Food consumption was monitored weekly, considering the difference in grams between the amount offered and leftovers (per animal). The animals’ body weights were evaluated weekly on a semi-analytical scale (Bel® São Paulo-Brazil) [34]. After 8 weeks of treatment and 8-h fasting, the animals were anesthetized with Isofluorane® BioChimico®-Brazil and euthanized by exsanguination through the inferior vena cava. Blood samples were centrifuged at 3000 rpm for 5 min, and the serum was separated and stored at −18 °C in a biofreezer for further analysis [35]. Adipose tissue was also removed (epididymal, retroperitoneal, perirenal, mesenteric and omental) to determine the animal’s fat content (percentage of adipose tissue at each site in relation to body weight) [35]. ## 2.5. Metabolic Changes in Serum The blood of all animals was collected at the end of the experimental period for serum analysis, and serum samples were used to determine the following parameters: fasting glucose, triglycerides, total cholesterol and fractions High Density Lipoprotein (HDL-c), Low Density Lipoproteins (LDL-c) and Very Low Density Lipoproteins (VLDL-c), evaluated by colorimetric kits (Labtest Diagnostics SA™, Lagoa Santa, MG, Brazil). The oral glucose tolerance test (OGTT) was also performed, which occurred 4 days before the end of the experiment, for which the animals were weighed after 12 h of fasting, and then the fasting glycemia was checked via caudal (time 0), using a glucometer. Then, the animals received glucose via gavage at a concentration of 2 g/kg of body weight. The glycemia was determined at 15, 30, 60 and 120 min after the administration of glucose [36]. For the insulin sensitivity test (IST), which was performed 2 days before the end of the experiment, the animals were weighed and blood glucose was checked in the fed state (time 0). Then, 1.5 U/kg of insulin (NovoRapid® -São Paulo, SP, Brazil) was applied intraperitoneally, and blood glucose was evaluated at times 0, 15, 30 and 60 min [35]. For both OGTT and IST, blood glucose values were recorded and the area under the curve (AUC) was calculated [36,37]. ## 2.6. Concentration of Adipokines: IL-10 and MCP-1 The collected serum was vortexed for 30 s and placed in a centrifuge (5000 rpm for 10 min). Afterwards, 10 µL of serum from each animal, 10 µL of assay buffer and 25 µL of solution containing the adipokines IL-10 and MCP-1 were distributed in a 96-well plate, following the instructions of the commercial kit MAD-KMAG-71K® by Merck-Sigma Aldrich® São Paulo-Brazil, reading the plate on the Luminex® by Merck-Sigma Aldrich® São Paulo-Brazil using the MAGPIX® software by Merck-Sigma Aldrich® São Paulo-Brazil, and the concentration values were obtained in µg/mL. ## 2.7. Statistical Analysis Statistical analysis was performed using the software Jandel Sigma Stat, version 3.5 (Systat software, Incs., San Jose, CA, USA), and Sigma Plot, version 12.5 (Systat Software Inc., San Jose, CA, USA) and presented as mean ± standard deviation (SD). The groups were compared using one-way ANOVA followed by Tukey’s post test. Differences were considered significant when $p \leq 0.05.$ ## 3.1. Food Intake, Weigh Again, Body Fat Percentage and Adipocyte Area During the 8 weeks of supplementation and being fed with high-fat diets, it was observed that the intake of food was significantly lower in all groups of animals supplemented with aqueous or ethanolic extracts independently of the dose compared with the control (CTL) Nuvital, CTL AIN93 and High Fat (HF) groups ($p \leq 0.001$). However, weight gain was not prevented for the HF AQ 400, HF ET 200 and HF ET 400 groups that received the 200 mg/kg dose. The HFAQ200 group gained less weight than the other groups under the hyperlipidic diet and showed values close to the CTL AIN93 and CTL Nuvital groups (Figure 3). Thus, all evaluated extracts had a reduction of food intake; however, they had no impact on weight gain, with the exception of HF AQ 200. In addition, they did not impact the reduction in adipose tissue accumulation (Figure 4). ## 3.2.1. Triglycerides and Cholesterol (Total and Fractions) in Serum The ethanol extract at a dose of 200 mg/kg significantly reduced total cholesterol values ($p \leq 0.001$), while the other experimental groups showed higher values with a statistical difference compared with the CTL Nuvital, CTL AIN 93 and HF ET 200 groups (Figure 5). In the HDL-c fraction, it was noted that all groups receiving supplementation with aqueous or ethanolic extracts of G. gardneriana, regardless of dose, obtained higher values with a statistical difference compared with the CTL Nuvital and CTL AIN 93 groups, while the HF AQ 200 group showed higher values than all the others ($p \leq 0.001$). There was no difference among the groups for the non-HDL fraction or triglycerides (Figure 5). Thus, these results show that the ethanol extract at a dose of 200 mg/kg improved the HDL-cholesterol values even under hyperlipidic diet conditions. ## 3.2.2. Glycemic Profile: Fasting Blood Glucose, Oral Glucose Tolerance and Insulin Sensitivity Tests When evaluating the glycemic profile, it was observed that fasting glucose worsened; that is, there was a significant increase in the HF AQ 400, HF ET 200 and HF ET 400 groups compared with the CTL Nuvital, CTL AIN 93, HF and HF AQ 200 groups ($p \leq 0.05$) (Figure 6A). In contrast, there was a reduction in the fasting blood glucose values in the HF AQ 200 group compared with the other groups ($p \leq 0.05$) (Figure 6A). However, there was no impact on the results obtained in the evaluation of the area under the curve of the oral glucose tolerance test or the insulin sensitivity test (Figure 6B,C). ## 3.2.3. Adipokine Concentration: Cytokines IL-10 and MCP-1 In the quantification of the cytokine interleukin 10 (IL-10), it was observed that the CTL AIN 93, HF AQ 200, HF AQ 400 and HF ET 400 groups presented lower values with a statistical difference compared to the CTL Nuvital, HF and HF ET 200 groups ($p \leq 0.001$). This is in contrast to the MCP-1 quantification, in which all groups supplemented with G. gardneriana presented much higher values with a statistical difference compared with the control groups ($p \leq 0.001$) (Figure 7). Therefore, this shows that the HF AQ 200, HF AQ 400 and HF ET 400 groups had reduced IL-10 values, but there was no effect on MCP-1 concentrations. ## 4. Discussion The development of research that investigates the phytochemical composition and therapeutic properties of medicinal plants enables innovation for the production of medicines and herbal isolates, whose nutritional composition of micronutrients and secondary metabolites determines the nutraceutical effects and their medicinal functions [38,39]. They can be promising candidates for the treatment of obesity when compounds are present that manifest effects in the prevention and treatment of obesity and the possible metabolic alterations, such as through reduction of body fat and/or improvement of the serum lipid profile, which can protect against metabolic alterations [40,41]. In this context, numerous phytochemical and biological studies on Garcinia species have been carried out to date, validating their traditional functions under a modern scientific perspective and developing their new pharmacological activities. The extracts of this genus are rich in polyprenylated polycyclic acylfloroglucinols (PPAPs), xanthones, polyphenols and flavonoids [11,12], being described in the literature as healing agents with anti-inflammatory, antioxidant, antitumor, antifungal, anticancer, antihistamine, antiulcerogenic, antimicrobial, antiviral, vasodilator, hypolipidemic, hepatoprotective, nephroprotective and cardioprotective properties [41]. Garcinia species are widely studied for their possible effects on weight loss, due to the presence of compounds that favor fat burning and satiety suppression [21,22]. The leaves of G. gardneriana present sitosterol and stigmasterol, α-copaene, α-muurolene, γ-cadinene and cadinene, which are phytosterols and sesquiterpenes, which have already been identified as potent anti-inflammatory and anticancer agents [42]. G. gardneriana also contains xanthones, steroids, triterpenes and flavonoids, secondary metabolites that have been associated with anti-inflammatory, antinociceptive, antibacterial and antiparasitic activities [10,11,12,14,20]; however, the present study is the first to investigate the effects of G. gardneriana on an experimental model with high-fat diets. Therefore, in this study, after 8 weeks of supplementation of a high-fat diet with aqueous extract or ethanolic extract of G. gardneriana leaves (doses of 200 or 400 mg/kg), there was a significant reduction in food consumption; however, only the aqueous extract in the 200 mg/kg dose reduced weight gain without influencing adiposity. This finding is contrary to those in the study by Lim et al. [ 2020] [43], in which, after 9 weeks of treatment, obese rats treated with methanolic extract of Garcinia atroviridis pulp at doses of 100, 200 and 400 mg/kg had a lower food intake and consequently lower weight gain, manifesting a slimming effect. The same condition was observed in the study by Muhamad Adyab et al. [ 2019] [44], who investigated the potential of aqueous extract of Garcinia mangostana pulp on metabolic and structural changes in obese rats induced by a hyperlipidic diet (diet providing 414.0 kcal/100 g of energy with $43\%$ carbohydrate, $17\%$ protein and $40\%$ fat), supplemented for 7 weeks at different doses (200, 400 and 600 mg/kg); a significant reduction in food intake, body weight and adiposity was observed. Our data, therefore, provide us with the fact that supplementation with aqueous extract or ethanolic extract of G. gardneriana in mice fed a hyperlipidic diet reduced the amount of food consumed and subsequently suppressed excessive body weight gain. These observations support the hypothesis that G. gardneriana has weight-reducing properties. Chae et al. [ 2016] [45], who investigated the effects of Garcinia mangostana on metabolic syndrome in mice fed with a high-fat diet and the underlying mechanisms related to adipogenesis, also observed a lower food intake and body weight, as well as suppressed adiposity, in the groups supplemented with ethanolic extract of Garcinia mangostana bark at 50 or 200 mg/kg doses. Such results are attributed to the fact that the species Garcinia mangostana and Garcinia atroviridis contain the main compound hydroxycitric acid, which contributes to antioxidant activity and is believed to induce weight loss by reducing the lipogenesis process and by appetite suppression [46]; furthermore, low values of hydroxycitric acid lactone are found in G. gardneriana [11]. These studies also pointed to a possible effect on sensitive protein kinases for the regulation of intracellular energy (active protein kinase—AMPK), thus influencing the intracellular energy balance, and consequently impacting the energy metabolism of the whole organism; this effect could play a protective role against metabolic diseases such as obesity [47], as well as being an important regulator of lipid and glycemic metabolism [48]. In this sense, in the present study, a significant reduction in total cholesterol values was observed in the group supplemented with ethanolic extract of Garcinia mangostana bark at doses of 50 or 200 mg/kg (ethanolic extract), along with an increase in HDL-c values in all groups supplemented with either aqueous or ethanolic extract of G. gardneriana independent of dose, but with increased concentrations of the non-HDL fraction and triglycerides, results that are in agreement with other studies [43,44,45]. This finding can be attributed to evidence already published in other studies, such as Patil [2015] [49] and Demenciano et al. [ 2020] [11], who identified the presence of xanthones, flavonoids and catechins, which have antioxidant properties similar to that of vitamin C (ascorbic acid) that help to inhibit the action of free radicals and are related to lipid peroxidation, thus regulating the serum lipid profile. In addition, xanthones have been shown in other studies to play a role in the normalization of metabolic abnormalities and exert good pharmacological effects in animal models of metabolic syndromes, diabetes and obesity, having cardioprotective, antioxidant, anti-inflammatory and anti-obesity agents [44]. The consumption of high-fat diets has been shown to contribute to the development of hyperlipidemia and glucose intolerance [50]. In the present study, hyperglycemia was demonstrated in the groups supplemented with ethanolic or aqueous extract of G. gardneriana, regardless of dose. The results of the HF AQ 200 group indicated reduced fasting blood glucose values compared with the other groups; the results obtained for the oral glucose tolerance test and insulin sensitivity test indicated an increase in the area under the curve values in the same groups, while the HF AQ 200 group failed to maintain the protection demonstrated in the fasting glucose test. Evidence in the literature confirms that high-fat diets result in disturbances in glucose metabolism and glucose intolerance [49], thus causing insulin sensitivity, a condition that is probably associated with reduced expression of transcription factors belonging to the nuclear receptor family, such as peroxisome proliferator-activated receptors (PPARs) and their target genes, which regulate glucose homeostasis, lipid metabolism and inflammation [51,52]. However, both the aqueous and ethanolic extracts, regardless of dose, were unable to favor glucose metabolism in the animals fed a high-fat diet, thus promoting hyperglycemia and decreased beta cell functional activity, which is associated with an intense effect under oxidative stress [53]. Furthermore, a high-fat diet can modify oxygen metabolism because fatty acid molecules with double bonds are vulnerable to oxidative reactions that can lead to lipid peroxidation and, consequently, to oxidative stress [54]. Another fact, related to changes in glycemic metabolism and insulin resistance, is the accumulation of adipose tissue, which influences the expression of several proteins, cytokines and other molecules that are involved in several physiological or pathological processes [55]. In addition, the accumulation of adipose tissue favors an increase in the expression of tumor necrosis-alpha (TNF-α), monocyte chemotactic protein (MCP-1/CCL-2) and interleukin-6 (IL-6) by monocytes and macrophages [55]. These have a pro-inflammatory effect, and are directly related to the development of insulin resistance (IR) [18,56]. In the present study, the groups supplemented with G. gardneriana showed high levels of MCP-1, a pro-inflammatory cytokine, a condition that would explain the results in relation to the lipid and glycemic profile found above. In contrast, interleukin 10 (IL-10) is a cytokine that plays a critical role, has potent anti-inflammatory properties and is produced by M2 macrophages in adipose tissue, with its main functions being to regulate the immune system and significantly inhibit the expression/synthesis of pro-inflammatory cytokines or adipokines via negative counter-regulation [57]. In the present study, a significant reduction in this cytokine was observed, supporting the hypothesis of the potential pro-inflammatory effect of MCP-1. In studies that induced obesity in rodents, a reduction of plasmatic glutathione dismutase and superoxide dismutase, which are markers of antioxidant enzymes, was observed, associated with high levels of plasmatic TNF-α and IL-6 as pro-inflammatory markers. Therefore, it is noted that in the model of this work, when providing a hyperlipidic diet, the metabolic and structural abnormalities mimicked human obesity [44,58]. Similarly, insulin resistance generated in adipose tissue causes lipolysis to occur, increasing the release of free fatty acids into the circulation, and consequently elevates very low density lipoprotein (VLDL) concentrations and triglyceride synthesis in the adipose tissue. The accumulation of fat in the liver causes a decrease in liver function [59]. In addition, these conditions also contribute to the appearance of alterations in the serum lipid profile, such as high triglycerides, a decrease in high-density lipoprotein (HDL) and an increase in low-density lipoprotein (LDL), favoring the onset of dyslipidemia [60]. In this sense, the study of medicinal plants in the treatment of non-communicable chronic diseases has aroused the interest of researchers, with a view to studying the benefits of medicinal plants in the discovery of drugs for the treatment of diseases, based on different isolated bioactive compounds [61]. As the molecular control of the components found in medicinal plants is understood, it is possible to observe potential benefits in the prevention and treatment of current diseases [62]. Medicinal plants and their constituents may represent promising candidates for the treatment of obesity. Several medicinal plants and their active constituents show beneficial anti-obesity effects in vivo. Of all drugs available in therapy, around 25–$30\%$ are produced from natural products (plants, microorganisms, and animals) or are derived from these products [63]. On the other hand, the use of plants to counteract and/or prevent obesity is still poorly studied [64]. ## 5. Conclusions In the study, it was possible to verify that the aqueous extract of G. gardneriana at a dose of 200 mg/kg had a positive impact on food intake and HDL-c concentrations. The other groups, and even the HF AQ 200 group, did not show antioxidant or anti-inflammatory effects, and did not prevent weight gain, adiposity or changes in the lipid or glycemic profile. In conclusion, under the experimental conditions, G. gardneriana did not prove to be a potential resource for the prevention of obesity and metabolic alterations; thus, more research is required to investigate the possible effects using different models, doses and time of investigation to determine the relationship between the phytochemical properties already elucidated in the literature and their medicinal potentials. A different behavior was obtained from that described in the literature with regard to the medicinal potential of Garcinia species. ## References 1. Almeida L.S.B., Murata R.M., Yatsuda R., Dos Santos M.H., Nagem T.J., Alencar S.M., Koo H., Rosalen P.L.. Antimicrobial activity of. Phytomed (2008) 15 886-891. DOI: 10.1016/j.phymed.2007.12.003 2. Panthong A., Norkaew P., Kanjanapothi D., Taesotikul T., Anantachoke N., Reutakul V.. Anti-inflammatory, analgesic, and antipyretic activies of the extract of gamboge from. J. Ethnophamacol. (2007) 111 335-340. 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--- title: Estimation of Free Sugars in the Filipino Food Composition Table and Evaluation of Population-Level Intake authors: - Fabio Mainardi - Vanessa Caroline Campos - Richard Gaston Côté - Nele Kristin Silber - Roko Plestina - Imelda Angeles-Agdeppa journal: Nutrients year: 2023 pmcid: PMC10051834 doi: 10.3390/nu15061343 license: CC BY 4.0 --- # Estimation of Free Sugars in the Filipino Food Composition Table and Evaluation of Population-Level Intake ## Abstract Recommendations to reduce intake of free sugars are included in some national dietary guidelines. However, as the content of free sugars is absent from most of the food composition tables, the adherence to such recommendations is hard to monitor. We developed a novel method to estimate the free sugar content in the Philippines food composition table, based on a data-driven algorithm that enabled automated annotation. We then used these estimates to analyze the free sugar intake of 66,016 Filipinos aged 4 years and over. The average free sugar consumption was 19 g/day, accounting for an average of $3\%$ of the total caloric intake. Snacks and breakfast were the meals with the highest content of free sugars. Intake of free sugars, in grams per day and as % of energy, was positively associated with wealth status. The same pattern was observed for the consumption of sugar-sweetened beverages. ## 1. Introduction There is increasing concern that intake of dietary sugars—particularly in the form of sugar-sweetened beverages–increases overall energy intake and may reduce the intake of foods containing more nutritionally adequate calories, leading to weight gain [1], dental caries [2] and cardiovascular disease [3]. It has been traditionally recommended to decrease the intake of added sugar [4,5], defined as sugars added to foods during processing or preparation. More recently, several health organizations have moved the focus towards monitoring the amount of free sugars instead of added sugars in the diet [6,7,8]. The main difference between added and free sugars is that fruit juices are included within the definition of free sugars. Due to these recently developed recommendations, most food composition tables do not include information on free sugar content, and labels on pre-packaged foods lack such descriptive information. One notable exception is the United States, where added sugars are mandatory on the food labels, and are included in the US Department of Agriculture (USDA) Food Pattern Equivalent Database (FPED), allowing the estimate of their intakes in the US population, based on the National Health and Nutrition Survey (NHANES) data [9]. There is no standardized method to estimate the content of free sugars in foods, and free sugars cannot be distinguished from naturally occurring sugars with chemical analyses. Therefore, the estimates must rely on one of the following facts, or a combination thereof: (a) available categorization of foods in the database, usually available as assignment to food groups; (b) knowledge of the ingredients in a typical recipe; (c) information about the content of other nutrients, mainly total sugars and fiber. Our multi-step approach applies several imputation rules based on food groups, for which it is known a priori that they either contain no naturally occurring sugars (e.g., fish) or that they do not contain any free sugars (mainly whole fruits). In addition, and especially for mixed dishes, a predictive model is applied, based on the nutrient content of the foods. A previously published paper developed a common-sense rule to estimate free sugars from added sugars using a food composition database from commercially available products [10]. However, this method was not validated against other databases. In Louie et al. [ 6], a methodology to estimate the content of added sugars was developed and applied to the Australian Food Composition Table (FCT) and can be easily extended to free sugars. This 10-step procedure can, in principle, be applied to any FCT, but some of the steps require manual, time-consuming annotation and are very subjective. In fact, the reliability of the method was evaluated by comparing the estimates made by two researchers: for $20\%$ of food items. The two researchers did not use the same steps, and for certain steps, agreement was below $50\%$. Although the authors concluded that this 10-step methodology can estimate added sugars content of foods with good reliability, it suggested that development of additional objective steps might rather improve the reliability of the method. There is a knowledge gap around the consumption of free sugars in south-eastern Asian countries, due to the lack of appropriate food databases. The Philippines have adopted the WHO recommendations on free sugars in 2018 [11] and conduct a well-developed national nutrition survey to monitor the adherence of the Filipino population to the local dietary guidelines [12]. However, the information about free sugars is lacking in the FCT. In this study, we propose an alternative method to estimate the content of added and free sugars in a FCT, requiring a minimal number of manual annotations and subjective steps. The method relies on availability of data on total sugars, food groups and nutrients readily available in FCTs (protein, carbohydrates, fiber, total fat, saturated fat and sodium). We applied our method to provide estimates of the intake of free sugars in the adult Filipino population based on the 2018 National Nutrition Survey (NNS). We then analyzed the association of these estimated intakes with wealth status and BMI. ## 2.1. Definition of Free Sugars According to the European Food Safety Authority (EFSA), added sugars comprise all sugars which are added to food by the manufacturer, cook or consumer, such as glucose, fructose, sucrose, starch hydrolysates and other isolated sugar preparations [8]. Free sugars are defined, according to the WHO and the EFSA, as added sugars plus sugars naturally present in honey, syrups, fruit juices and fruit juice concentrates [4]. Both added and free sugars exclude the sugars that naturally occur in dairy products and intact fruit and vegetables. Refer to Figure 1. ## 2.2. Development of a Database of Free Sugars for the Philippines Estimates of free sugar content were added to the electronic data files from the Philippines food composition database (PhilFCT) by adapting the method proposed by Louie et al. [ 6] Our method applies steps 1 to 3 of the 10-step methodology developed by Louie et al. [ 6] and replaces the remaining steps with an automatic data-driven estimation. The first three steps are based on objective criteria leaving less space for inter-researcher guesses. All the steps rely on availability of data for total sugars (see Table 1). Steps 2 and 3 additionally rely on a categorization of the food items, that is usually available in FCTs in the form of food groups and subgroups (see Table 2). In the Philippines’ FCT, a 3-level categorization was available. For example, the item “Biscuit, wholemeal crackers” is categorized as Cereals and cereal products/Other cereal products/Cookies-biscuits. Finally, step 4 relies also on availability of nutrients usually available in FCTs (protein, carbohydrates, fiber, total fat, saturated fat and sodium). The steps 1 to 4 used in our methodology are summarized in Figure 2 and described in what follows. Step 1. Assign 0 g free sugar to foods with 0 g total sugars. Step 2. Assign 0 g free sugar to foods in the following food groups: all spices, herbs, fats and oils; all plain cereal grains, pastas, rice and flours; eggs and egg products (except egg-based desserts); raw, fresh, dried, cooked foods (e.g., fruit, vegetables, legumes, meat, seafood) without addition of sugars; mixed dishes with no added sugar (decided based on ingredient information, e.g., recipe); non-sweetened beverages (e.g., coffees, tea, milks, alcoholic beverages); non-sugar-sweetened dairy products; nuts, coconut and seeds (except sweetened varieties and nut bars); plain breads and pastries without fillings (e.g., vanilla cream, chocolate). These food groups were selected because they are either unprocessed or minimally processed with no added sugar. Step 3. Assign $100\%$ of total sugars as free sugar for foods in the following food groups: All non-dairy confectionery; breakfast cereals and cereal bars without fruits, chocolate, dairy or milk solids; coffee and beverage base with no milk solids, dry or made up with water; crumbed/battered meat and seafood; processed meats; sweetened beverages (e.g., soft drinks, sport drinks, flavored water); savory/sweet biscuits, cakes, donut and batter-based products without fruits, chocolate, or dairy products (decided based on ingredient information, e.g., recipe); soy beverages and soy yoghurt without added fruits; Sugar and syrups. These food groups were selected as they do not contain sugars naturally, therefore, all the sugars present are likely to be free sugars. Step 4. Apply predictive modeling to the remaining foods. We developed a stacked regression model [13], where each algorithm was tuned by 10-fold cross-validation. Stacking regressions is a method for forming linear combinations of different predictors to give improved prediction accuracy. We combined the predictions from:Support vector regression [14],Random forest [15],Extreme gradient boosted regression [16], andRule fit regression [17]. Our strategy to train, test and validate the regression model was as follows. To fit the model, we used:FNDDS 2013–2014 (US, 7618 foods)AUSNUT (Australia, 5740 foods)The model was then validated on a list of completely independent datasets:The Norwegian food composition table (1123 foods),The Danish food composition table (613 foods),3082 recipes from the Internet, with complete information on the nutrients listed in Table 1, and on free sugars,2 weekly menu plans, designed according to US dietary guidelines [18]. The reason to choose those countries was the availability of added or free sugars in their databases. Internet recipes were licensed from a commercial recipe database provider (Edamam LLC, New York, NY, USA) and contained additional ingredient mappings either to USDA SR28 or to the provider’s proprietary food composition table, for items that are not available in the USDA FCT, to provide detailed nutrition composition. ## 2.3. Estimating the Intake of Free Sugars The Philippine National Nutrition Survey (NNS) is the official nationwide survey on nutritional status, diet and other lifestyle-related risk factors for noncommunicable diseases [12]. A 2-day, non-consecutive, 24 h food recall interview is conducted to estimate food intake. We used the first day of recall to estimate the intake of free sugars. We provide descriptive statistics of the intakes for the adult population, stratified by several socio-demographic factors (gender, age groups, BMI status, wealth status). BMI was adjusted for age for the group 4–18 years. Wealth status is a proxy measure of the long-term living standard of the household and was calculated by aggregating several components: household members’ educational backgrounds and occupations, type and tenure of housing unit, ownership of household assets, toilet facilities and garbage disposal systems, and source of drinking water, among others [19]. We analyzed the intake of free sugars as grams per day, and as percentage of daily caloric intake. ## 2.4. Statistical Analysis We report the descriptive statistics of free sugar content (grams per 100 g) in the PhilFCT, overall and by food group. We investigated the association of free sugar intakes with wealth status and with BMI status using a Kruskal–Wallis test followed by a post hoc Dunn test for pairwise comparison, with Benjamini–Hochberg correction for multiple testing. For subjects of age less than 19, the BMI status was adjusted for age. Calculation of means, medians and standard error of continuous variables at daily level are weighted, using the survey weights (function svymean from the R package survey). Weighted general linear models were used to test for increasing trends between a continuous and an ordinal variable. All calculations and analyses were performed in R, version 4.0.2. ## 3.1. Development of a Database of Free Sugars Although Louie et al. [ 6] consider step 1 to 6 as objectives, we decided to not apply their further steps, because the reliability decreases considerably from step 4. For this reason, aiming to decrease the number of manual annotations and possible inter-researcher errors, we used a different approach, and the remaining foods had their free sugars content estimated based on a regression model in which the information on nutrients is used. More precisely, we developed a regression model taking as input seven nutrients: carbohydrate, fiber, protein, saturated fat, sodium, total fat, total sugar. These nutrients are usually well covered in most food databases (some examples are reported in Table 1). A total of 1437 distinct foods were reported in the NNS, from a total of 1547 foods present in the database. There were 302 foods containing no sugars at all (Table 2), and 421 were imputed applying the data-driven model (Table 3). The remaining foods were imputed according to a-priori rules (steps 2 and 3), based on the food group. The highest concentrations of free sugars were found in the syrups, cereals, and misc groups (Table 4); the group named “misc” includes the sugar-sweetened beverages as a subgroup. ## 3.2. Intakes A total of 66,016 respondents had reported at least one day of intake, mostly in the age range 19–59 ($49\%$, Table 5). A total of 756,843 meals were reported in total, the most common ones being breakfast ($29.7\%$), lunch ($28.4\%$) and supper ($27.1\%$). The mean daily intake of total sugars as reported was 28 (0.2) g/day (mean (SE)). Snack and breakfast were the meals with the highest content of free sugars. The daily intake of free sugars was estimated at 19 (0.1) g/day (mean (SE)). Measured as % of daily energy intake, this gave an overall average of $5\%$ (0.03), with higher values for children (Table 6). Snacks and breakfast were the meals with the highest content of free sugars (Table 7). BMI status was available for respondents aged 19 y or more ($$n = 40$$,099). Subjects in the obese and overweight groups had higher intakes of free sugars than subjects in the normal group (Dunn test, p-values < 0.01). When measured as % of energy, intakes were not significantly different between the groups. See Table 8. BMI adjusted for age z-scores (BAZ) were used for age below 19 y (Table 9). The difference between BAZ groups was not significant (Kruskal–Wallis, $$p \leq 0.87$$). Wealth status was available for 65,678 respondents. The daily intake of free sugars was positively associated with wealth status, both when considered as amounts in grams per day, and as percentage of energy intake (Figure 3, Table 10 and Table 11). We also observed an increasing consumption of sugar-sweetened beverages with wealth status (Table 12); all p-values were significant (not shown). ## 4. Discussion As free sugars have become a nutrient of public health concern, several diets and food quality indices/scores have free or added sugars as one of their components [17,18,19]. We developed a method to estimate the content of free sugars in food composition tables and applied it to the estimation of free sugar intakes in the Philippines. About $19.5\%$ of the food had no sugars at all, $53.7\%$ were imputed according to their assignment to specific food groups, and the remaining $26.8\%$ were imputed using a data-driven approach, based on the content of carbohydrate, fiber, protein, saturated fat, sodium, total fat, total sugar. The data-driven method was applied to more than $60\%$ of the cereal products and milk products, where total sugars can be partially coming from natural sources (e.g., milk or oats) and partially be added to the recipe. Correlations between predicted values and original values on the test datasets were very high, ranging from 0.89 to 0.96 (Table S1 Supplementary materials). The mean absolute error of the predictions ranged from 0.9 to 1.3 g/100 g (Table S1). We also evaluated the errors in g/day on 2 weekly menu plans, giving an estimate of how the errors combine when a multiplicity of foods is consumed in usual serving sizes (Table S1). It is useful to compare our estimates with the intakes reported in other countries. In the US in 2017–2018, the average intake of added sugars was 17 teaspoons (71.4 g) for adults aged 20 and older [20], and 76 g for children 4–13 years old [21]. Intakes of free sugars, although not reported, should be expected to be comparable or higher. Our estimate for free sugars in the Philippines is much lower (19 g across all ages); however, this is true already for the intakes of total sugars, which were reported and not estimated (on average 28 g in the Philippines, against 107 g in the US) [22]. The 2009 Food Consumption Survey of Thai Population showed median intake of total sugar and sweeteners for all age groups ranging from 2.0 to 20.0 g per day among males and from 2.0 to 15.7 g per day among females, which is quite close to the average values observed for the Filipino population. In general, it is known that consumption of sugar-sweetened beverages in the Asia-Pacific region is the lowest in the world [23]. Although estimated intakes were higher for overweight and obese, compared to normal BMI, these differences disappeared when intakes were converted to percent of caloric intake, similar to what was observed in the US population [20,21]. This is likely a result of selective under-reporting by overweight and obese individuals, namely of sugar-rich foods [20,22]. A strong association has been found between the preference for fat and energy-dense foods and obesity worldwide [22,23,24]. However, other studies showed no correlation between the preference for specific foods and the BMI status, whereas a recent study found evidence for energy-dense dietary pattern high in free sugars and saturated fatty acids (SFA) and low fiber and the obesity risk in Australian adults [25]. Estimated intakes of free sugars were positively associated with wealth status when measured in grams or as % of calories. This is opposite to what is observed in Western countries such as the US [24], where added sugars and foods with lower nutrient density are associated with lower socio-economic status. In January 2018, the Philippines began imposing a tax of 6 Philippine pesos per liter (around $13\%$ of the cost of the product) on sweetened beverages to curb the obesity burden [25]. Conjecturally, this might induce poorest people to limit their consumption of such drinks, which is indeed what we observed in the data (Table 10, Figure 2). It has been reported that one month after implementation of the tax on 1 January 2018, prices of taxable sweetened beverages had increased by 16.6 to $20.6\%$ and sales in sari-sari (convenience) stores declined by $8.7\%$. ## 5. Limitations We acknowledge some limitations and areas of improvement in this work. We used a single 24 h recall, so our estimates may not be reflective of usual intakes. Our machine learning model was developed on Western data, and its applicability to Asian data might be not guaranteed. However, our database of internet recipes was multi-cultural, including many recipes from Asian countries. In addition, only less than $24\%$ of the foods were fed into the model, the rest was processed during step 1 ($11.6\%$), step 2 ($53.4\%$), step 3 ($11\%$). In addition, our model was not tailored for packaged products, in contrast with the work by Davies et al. Models for packaged products can exploit additional information from the label, particularly the list of ingredients, compensating for the fact that the relationships between nutrients can be altered in ultra-processed food. ## 6. Conclusions We developed a method to estimate the content of free sugars in food composition tables, consisting of four objective steps and. Applied them to the estimation of free sugar intakes in the Philippines. A total of $19.5\%$ of the foods had no sugars at all, $53.7\%$ were imputed according to their assignment to specific food groups, and the remaining $26.8\%$ were imputed using a data-driven approach, based on their nutritional content. The approach was validated on five independent datasets. Correlations between predicted values and original values on the test datasets were very high, ranging from 0.89 to 0.96 while the mean absolute error of the predictions ranged from 0.9 to 1.3 g/100 g. The daily intake of free sugars was estimated at 19.0 ± 0.1 g/day, corresponding to roughly $5\%$ of daily energy intake. As expected, snacks and breakfast were the meals with the highest content of free sugars. Subjects in the obese and overweight groups had higher intakes of free sugars than subjects in the normal group. When measured as % of energy, intakes were not significantly different between the groups. 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--- title: Gut Microbiome-Host Metabolome Homeostasis upon Exposure to PFOS and GenX in Male Mice authors: - Faizan Rashid - Veronika Dubinkina - Saeed Ahmad - Sergei Maslov - Joseph Maria Kumar Irudayaraj journal: Toxics year: 2023 pmcid: PMC10051855 doi: 10.3390/toxics11030281 license: CC BY 4.0 --- # Gut Microbiome-Host Metabolome Homeostasis upon Exposure to PFOS and GenX in Male Mice ## Abstract Alterations of the normal gut microbiota can cause various human health concerns. Environmental chemicals are one of the drivers of such disturbances. The aim of our study was to examine the effects of exposure to perfluoroalkyl and polyfluoroalkyl substances (PFAS)—specifically, perfluorooctane sulfonate (PFOS) and 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy) propanoic acid (GenX)—on the microbiome of the small intestine and colon, as well as on liver metabolism. Male CD-1 mice were exposed to PFOS and GenX in different concentrations and compared to controls. GenX and PFOS were found to have different effects on the bacterial community in both the small intestine and colon based on 16S rRNA profiles. High GenX doses predominantly led to increases in the abundance of Clostridium sensu stricto, Alistipes, and Ruminococcus, while PFOS generally altered Lactobacillus, Limosilactobacillus, Parabacteroides, Staphylococcus, and Ligilactobacillus. These treatments were associated with alterations in several important microbial metabolic pathways in both the small intestine and colon. Untargeted LC-MS/MS metabolomic analysis of the liver, small intestine, and colon yielded a set of compounds significantly altered by PFOS and GenX. In the liver, these metabolites were associated with the important host metabolic pathways implicated in the synthesis of lipids, steroidogenesis, and in the metabolism of amino acids, nitrogen, and bile acids. Collectively, our results suggest that PFOS and GenX exposure can cause major perturbations in the gastrointestinal tract, aggravating microbiome toxicity, hepatotoxicity, and metabolic disorders. ## 1. Introduction In comparison to the human genome, the gut microbiota accounts for unique genes that number approximately 100 times those of the human genome [1]. These genes encode a variety of enzymes that help metabolize environmental chemicals driving a number of remarkable metabolic activities in the gastrointestinal microenvironment, some of which are crucial for host health [2,3,4]. Thus, disruption of the normal gut microbiota due to chemical toxicity can impact human health [5,6,7,8]. In addition, gut microbiota can significantly alter the host response to environmental pollutants, further highlighting the importance of the microbiome when determining the potential toxicity mechanisms of environmental chemicals [7]. These microbial–chemical interactions can be divided into toxicant modulation of the microbiome (TMM) and microbiome modulation of toxicity (MMT) [9]. TMM can include many effects, such as regulation of microbial genes and inhibition of specific enzymes, leading to alterations in the diversity and abundance of microbes in the community. MMT can alter the toxicity of a compound through the microbial enzymatic mechanisms of absorption, metabolism, disposition, and excretion [9,10]. These alterations affect enzyme families, mainly β-glucuronidases, azoreductases, and nitroreductases, that are involved in essential chemical processes in organisms [11,12,13]. In a recent database, around 529 gut microbes were reported to affect more than 1369 xenobiotic compounds through biocatalytic reactions [14]. Specific taxa have been associated with various health outcomes; e.g., susceptibility or resistance to toxic chemicals or drugs, the capability to recover from injury induced by a chemical agent, the presence of phenotypes associated with the disease, and the integrity of immune function [9]. Since the 1950s, perfluoroalkyl and polyfluoroalkyl substances (PFAS) have been some of the most commonly used compounds for both domestic and industrial purposes [15,16]. The most prominent chemical contaminants in this group of synthetic chemicals include perfluorooctanesulfonic acid (PFOS), 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy) propanoic acid (GenX), and perfluorooctanoic acid (PFOA), which have been previously associated with various toxicities [17,18,19,20,21]. Among them, PFOS has been widely used as a surfactant [22] and reported to be present in human populations, leading to concern [23,24]. The half-life of PFOS in human serum is 3.4–5.4 years; thus, it has high potential to impact health [16,25,26], primarily by causing hypercholesterolemia, hyperuricemia, hypertension, hyperlipidemia, hyperglycemia, hepatotoxicity, neurotoxicity, and developmental toxicity [27,28,29,30,31,32]. GenX is a PFAS compound launched as an alternative to PFOA in 2009 and thought to be less toxic [33]. GenX has been found to have a shorter half-life of approximately 5 h [34]. Research in rats revealed a role for GenX in PPARα activation in fetal and maternal hepatic tissues. Further, reductions in the levels of lipids and thyroid hormones in the serum of the maternal rat were noted [35]. Recently, GenX was linked with hepatomegaly and developmental toxicity due to abnormal metabolism of glucose and amino acids, which may be associated with low birth weight and neonatal mortalities [36,37]. It is believed that the shorter-chain GenX is less deleterious to human health owing to its short half-life and low bioaccumulation [33]. Despite that, in vitro [18,38] and in vivo [35] studies indicate otherwise. Considering the possible mechanisms through which the gut bacterial community can influence the toxicity and distribution of chemicals [5,6], it is intriguing to study gut microbiota changes in response to toxic chemical exposures. The association between various metabolic (mainly liver) disorders and PFOS and GenX exposure emphasizes the need to evaluate the effects of PFOS and GenX on gut microbiota and the associated metabolome. However, there is a significant gap in the literature on the impact of PFOS and GenX on different parts of the gastrointestinal system. In this study, we used a combination of analysis tools—i.e., 16S rRNA sequencing and untargeted metabolite profiling using LC-MS/MS analysis—to reveal the effect of PFOS and GenX exposure on the small intestine and colon microbiome and metabolome, as well as on the liver metabolome, in mice. We investigated the key changes induced by low, mild, and high dietary exposure to PFOS and GenX in the gut–liver axis to elucidate their potential role in the development of various host metabolic disorders. We detected noticeable perturbations in bacterial composition and metabolite profiles across the gut and liver, some of which were dose-dependent. A number of differential changes observed when comparing PFOS and GenX treatments suggested differences in their toxicity and metabolism. Our findings contribute to the understanding of the effects of PFOS and GenX on the gut microbiome and liver homeostasis. ## 2.1. Chemicals and Dosing Concentrations PFOS and GenX ($97\%$ purity) were purchased from Synquest laboratories, and Tween 20 was purchased from Sigma-Aldrich (St. Louis, MO, USA). PFOS and GenX stock solutions were prepared in $0.5\%$ Tween-20 and deionized water. Three doses of both PFOS—i.e., 5, 10, and 20 mg/kg/day—and GenX—i.e., 10, 20, and 100 mg/kg/day—were created by diluting stock solutions. A vehicle control was prepared for the dosing of mice in which no PFOS or GenX was added. These dosing concentrations were selected based on previous studies in populations exposed to PFAS compounds through both the environment and occupation. The concentration of PFOS in the human body can reach up to 0.1 µg/g of body weight [39]. Studies with fish samples in the environment have noted concentrations of up to 9 µg/g [40]. According to the previous studies of GenX in mice (CD-1), the no observed adverse effect level (NOAEL) was found to be 5 mg/kg/day [41]. Another study in rats revealed abnormal LDL levels at 125 mg/kg/day and abnormal T3 hormone levels at 30 mg/kg/day doses [35]. Considering the results of the above studies, we selected three dosing concentrations for PFOS—i.e., 5 mg/kg, 10 mg/kg, and 20 mg/kg; three dosing concentrations for GenX—i.e., 10 mg/kg, 20 mg/kg, and 100 mg/kg; and two vehicle control groups for PFOS and GenX each. ## 2.2. Animals, Dosing, and Tissue Harvesting Adult CD-1 male mice were purchased from Charles River, USA. The animal experiments were conducted according to a protocol approved by the University of Illinois Urbana-Champaign (UIUC) Institutional Animal Care and Use Committee (IACUC). We chose to include only male animals to avoid possible variations due to diestrus cycles in females. A total of $$n = 44$$ male mice were randomly divided into eight groups ($$n = 6$$ biological replicates for PFOS and $$n = 5$$ for GenX in each group; three different concentration groups for each chemical and control group). Two to three animals were housed in ventilated polysulfone cages (changed once a week) at 25 °C with 12 h light and dark cycles. Mice were given water filtered via reverse osmosis in polysulfone bottles ad libitum and fed with Harlan Teklad Rodent Diet 8604. After 2 weeks of acclimatization for the PFOS group and 11 days for the GenX treatment group, the 60 day old mice were dosed orally once per day using pipette tips with either PFOS or GenX in various doses or the vehicle control dissolved in deionized water and Tween 20 for 14 consecutive days. Each animal was given a certain volume of the compound solution according to its weight (see Supplementary Table S1 for animal weights). After dosing for 14 days, CO2 asphyxiation was used to euthanize the mice. Intestinal content was immediately collected for microbiome analysis in sterile Eppendorf tubes from the small intestine and colon regions after euthanasia under aseptic conditions. Similarly, liver organs were harvested for metabolome analysis and kept in sterile tubes. All tubes were snap-frozen in liquid nitrogen and stored in a −80 °C freezer until further use. ## 2.3.1. DNA Extraction, Library Preparation, and Sequencing The DNA from the 200 mg gut microbiota samples of mice small intestine and colon were extracted separately from each mouse with a QIAamp PowerFecal Pro DNA kit (Qiagen, Hilden, Germany) per the manufacturer’s instructions. The DNA extracted from all samples was submitted to the DNA Services Facility at the Roy J. Carver Biotechnology Center (UIUC) for library preparation and sequencing per their standard protocol [42]. DNA used in PCR amplification was approximately 1 ng. PCR amplification of the V4 (515F–806R) region was accomplished with primers 5′-GTGYCAGCMGCCGCGGTAA and 5′-GGACTACNVGGGTWTCTAAT using the Fluidigm protocol (Fluidigm Corp., San Francisco, CA, USA). bcl2fastq 2.20 (Illumina, San Diego, CA, USA) was used to convert raw fastq files into demultiplexed compressed fastq files. ## 2.3.2. Bioinformatic Analysis We used trimmomatic v0.38 to remove 20 nt barcodes from the start of the reads. Raw sequences for the colon and small intestine were then processed using QIIME v2-2020.8 and the reads were denoised using DADA2 [43]. To avoid biases generated by differences in sequencing depth, the amplicon sequence variant (ASV) table was rarefied to 10,000 sequences per sample. ASV taxonomy was determined using the RDP v18 naive Bayes classifier with $80\%$ confidence cut-off [44]. Ultimately, we estimated coverage for ASV characterization as 70 ± $17\%$. Due to the limitations of the resolution for taxonomical classification using the 16S gene sequencing technique, all analyses were restricted to the genus level. We used the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) 2.3.0 pipeline to estimate the genomic repertoire of the detected ASVs to predict the functional capabilities of microbial communities [45]. ## Sample Preparation and LC-MS/MS Analysis Liver tissues and fecal samples (from the small intestine and colon) were processed for metabolomic analysis. The wet weight of fecal samples was measured for use in normalization later. The samples were dissolved in 1 mL of the solvent—i.e., chloroform: methanol (2:1 v/v)—and homogenized using Omni Digital Tissue Homogenizer Thq. After homogenization, the final liquid, along with the homogenized samples inside, was delivered in O-ring-sealed, screwed vials in dry ice to the Metabolomics Facility at the Roy J. Carver Biotechnology Center (UIUC) for LC-MS/MS analysis. The analysis was performed by the Metabolomics Facility using their standard protocol [46]. Thermo Compound Discoverer v.3.2 was used for further analysis of the LC-MS/MS data to align the chromatogram and identify/quantitate the compounds. The Untargeted Metabolomics with Statistics to Detect Unknowns with ID Using Online Databases and mzlogic workflow was used. The Spectra settings used were: min. precursor mass = 0 Da, max. precursor mass = 5000 Da, and polarity mode = 1. The data were first analyzed in the (+) mode and then in the (−) mode. Align Retention Time settings were set as: max. Shift = 2 min and Mass tolerance = 5 ppm. Detect Compounds settings were set as: Intensity tolerance = $30\%$, Mass tolerance = 5 ppm, and minimum peak intensity = 1,000,000. Compound Discoverer software was used with four different data sources (mzCloud, Metabolika, ChemSpider, and Predicted Compositions) to assign compound annotations (chemical names and structures). In ChemSpider, five different databases (BioCyc [47], Human Metabolome Database (HMDB) [47], Kyoto Encyclopedia of Genes and Genomes (KEGG) database [48], Massbank, and the National Institute of Health (NIH) clinical collection) were used to search for and annotate the detected metabolites based on their molecular weight. ## 2.5. Statistical Analysis Downstream analysis of taxonomic and metabolomic data was performed in R v4.0.2. ASV counts and transformations into relative abundance, Shannon diversity, and Bray–Curtis dissimilarity were calculated using the vegan package. We used the Bray–Curtis dissimilarity measure and principal coordinate analysis (PCoA) to visualize the differences in the microbial diversity between the various treatment groups. Linear regression analysis was used to test for associations between taxa and the concentrations of toxic compounds. Before testing for taxa differences, all taxa below $0.5\%$ summary abundance across all samples were removed. For the metabolomic data, the peaks that had ∆Rt < 0.2 and ∆M < 0.01 were considered duplicates and were removed from further analysis. The peak areas were normalized according to the weights of samples. The area peak counts were log-transformed and z-score-normalized to stabilize the variance in the data. We used MetaboAnalyst v5.0 to perform statistical and enrichment analyses of the metabolomic data [49] and principal component analysis (PCA) was used to visualize the differences in the metabolic diversity between the various treatment groups and control groups. Prior to statistical analysis, $40\%$ of the metabolites were filtered using the interquartile range (IQR) to remove metabolites with low variability. Identification of important metabolites separating the various treatments in the PFOS/GenX group was undertaken using one-way ANOVA with FDR correction or a linear regression test. Metabolites elevated/lowered in PFOS and GenX diets were selected as per the sign from the linear regression and the p-value of the fit. The set of elevated/lowered metabolites was used to perform pathway enrichment analysis against the KEGG [48] and Small Molecule Pathway (SMPDB) [50] databases. ## 3. Results The experimental design and an overview of the collected data are shown in Figure 1a. Adult male mice were subjected to a diet containing PFOS or GenX in three different concentrations, as well as a vehicle control (control, 5 mg/kg, 10 mg/kg, and 20 mg/kg for PFOS and control, 10 mg/kg, 20 mg/kg, and 100 mg/kg for GenX). After two weeks on a diet, samples were collected from three animal replicates for 16S rRNA sequencing of the mice colon and small intestine and untargeted LC-MS/MS metabolome profiling of liver tissue. The backup samples from the remaining replicates were kept in reserve to be used for untargeted metabolome profiling of the colon and small intestine microbiome. Overall, we detected 818 representative ASVs that were assigned to 73 unique genera in the 16S rRNA samples (Tables S2 and S3). Totals of 5251, 3644, and 4392 unique metabolite features were detected in the colon, small intestine, and liver, respectively. Among them, 1185 (colon), 734 (small intestine), and 1098 (liver) had putative structures assigned (Tables S4–S6). We analyzed these multi-omics data to elucidate the impact of toxic compounds on different segments of the gastrointestinal tract. ## 3.1. PFOS and GenX Exposure Impacts Microbial and Metabolome Diversity The beta diversity analysis of both the colon and small intestine microbiomes revealed differential effects for the various concentrations of PFOS and GenX on the mice microbiomes (Figure S1a,b; PERMANOVA test for Bray–Curtis dissimilarity: small intestine: $F = 1.67$, $R = 0.42$, p-value < 0.05; colon: $F = 1.60$, $R = 0.41$, p-value < 0.01). Samples from the mice on GenX diets were separated from those exposed to PFOS (Figure S1a,b and Figure 1b—green group of dissimilarities). Moreover, GenX had a relatively stronger effect on the beta diversity compared to PFOS, with a relatively more significant effect in the small intestine in comparison to the colon (Figure 1b, blue vs. yellow groups of dissimilarities), as the corresponding samples were spread apart on the PCoA plot (Figure S1b), which may have signified taxonomic changes driven by its toxicity. There were no effects on the alpha diversity for either GenX or PFOS (p-value of linear regression for Shannon index > 0.05, Figure S1c), which is supported by a previous study on PFOS [51]. Initially, we created two separate control groups for PFOS and GenX diets with 0 mg/kg concentrations of the target compounds. We confirmed using taxonomic analyses that these samples were similar to each other (Kolmogorov–Smirnov p-value < 0.01 for comparisons of Bray–Curtis dissimilarities within the control group and for the control group versus others). Thus, in the subsequent metabolomic analyses, we decided to use one group of control samples (marked as PFOS control in Figure S1a,b and Figure 2a). Similar patterns of sample variation were observed for untargeted LC-MS/MS metabolome features (see Figure S1d–f; PERMANOVA test for normalized correlation distance: liver $F = 1.64$, $R = 0.41$, p-value < 0.05; small intestine: $F = 2.07$, $R = 0.53$, p-value < 0.05; colon: $F = 2.08$, $R = 0.47$, p-value < 0.05). There was a much more pronounced effect from the toxicity of the compounds and clearer separation of GenX and PFOS samples for the liver and small intestine compared to microbiome features (Figure 1b,c). Metabolome characteristics also resulted in a more consistent triplicate grouping than taxonomic features (Figure 1c and Figure S1d–f). Interestingly, the colon metabolome was much less affected by toxic compounds than the small intestine, while the effect on the colon microbiome was still significant (Figure 1b). ## 3.2. PFOS and GenX Ingestion Causes Gut Microbial Alterations Changes in taxonomic abundance at the phylum, family, and genus levels were observed in microbiota collected from both small intestines and colons exposed to PFOS and GenX. At the family level, we observed that families with high prevalence of pathogens such as Enterobacteriaceae, Streptococcaceae, and Pseudomonadaceae were associated with higher toxicity (Figure S2). The variation patterns observed in the PCoA plots (Figure S1a,b) were also evident in a heatmap of taxonomic compositions (Figure 2a). In general, replicates tended to cluster together, and samples treated with high concentrations of GenX tended to cluster separately from the PFOS-exposed samples. This separation was mostly driven by the increase in the abundances of the following genera: Turicibacter, Streptococcus, Staphylococcus, and Clostridium sensu stricto. We further assessed whether any of these genera were significantly associated with increases in GenX and PFOS concentrations (Figure 2b,c and Figures S3–S6). With an increasing concentration of PFOS in the small intestine, we observed a significant increase in the abundance of the genus Ralstonia, and a significant reduction for the abundance of Limosilactobacillus (p-value of linear regression model < 0.01, Figure 2b). The abundances of several other bacterial genera were also found to vary (e.g., increase for Staphylococcus and Akkermansia and decrease for Lactobacillus) with increasing concentrations of PFOS (p-value of linear regression model < 0.05). In the colon, PFOS was found to significantly elevate the abundance of the genus Escherichia/Shigella and reduce that of Limosilactobacillus (p-value of linear regression model < 0.01, Figure 2c). Further, the abundances of several other bacteria increased (i.e., Bilophila and Parabacteroides) and decreased (i.e., Neglecta, Ligilactobacillus, Ihubacter, Parasutterella, and Lactobacillus) (p-value of linear regression model < 0.05). Similarly, with the increasing concentration of GenX in the small intestine, we noticed an increase in the abundances of Clostridium sensu stricto, Alistipes, and Flinibacter (p-value of linear regression model < 0.01, Figure 2b). There was also a qualitative increase in the abundance of Kineothrix. With increasing concentrations of GenX in the colon, the abundance of Clostridium sensu stricto increased and that of Limosilactobacillus decreased significantly (p-value of linear regression model < 0.01, Figure 2c). In addition to the alterations in the levels of the abovementioned bacteria, the abundances of several other bacteria were altered qualitatively in both the small intestine and colon in specific treatment groups. At higher concentrations of PFOS, slight decreases in Firmicutes abundance in the small intestine and colon, as well as a slight increase in Bacteroidetes abundance in the small intestine, were found in mice exposed to 5 and 10 mg/kg of PFOS. However, abundances of Bacteroidetes and Firmicutes in the small intestine and colon of GenX-exposed mice and the B/F ratio remained relatively constant (Figure S7). ## 3.3. Microbial Metabolic Pathways Are Altered in PFOS- and GenX-Exposed Mice We used PICRUSt reconstruction of the functional repertoire in 16S rRNA samples to identify pathways potentially enriched with PFOS and GenX diets (Figure 2d,e and Figures S10 and S11). In the small intestine, we detected 60 pathways that were significantly elevated and 5 that were significantly lowered with increases in the concentration of GenX (p-value of linear regression model < 0.01, fold change > 2). These included glutamate and glutamine biosynthesis, purine nucleotide degradation, tetrapyrrole and cobalamin (Vitamin B12) biosynthesis, and the super-pathways of BCAA and AAA biosynthesis (see Figure 2d). In contrast, only 21 microbial pathways were elevated with the PFOS diet (p-value of linear regression model < 0.01, fold change > 2), most of them being amino acid biosynthesis pathways (Figure S10): aromatic amino acid (AAA) biosynthesis, branched-chain amino acid (BCAA) biosynthesis, and pathways involved in the biosynthesis of L-arginine and L-lysine. In contrast to the small intestine, in the colon, the majority of enriched/lowered pathways were associated with the PFOS diet (see Figure 2e). We found 15 significantly elevated and 5 significantly lowered pathways (p-value of linear regression model < 0.01, fold change > 2) for PFOS and only 4 significantly elevated ones for GenX (Figure S11). In the colon, PFOS enriched several microbial pathways, mainly those involved in pyruvate fermentation for butanoate and acetone, L-lysine fermentation for butanoate and acetate, TCA cycle VII (acetate producers), the super-pathways of D-glucarate and D-galactarate degradation, and the pathways of polymyxin resistance. In general, pathways enriched with the PFOS diet were related to various fermentation and oxidation reactions and could reflect the level of oxidative stress of this compound. ## 3.4. PFOS and GenX Ingestion Alters the Small Intestine Metabolome in Mice We identified 383 ($11\%$) metabolite variables that significantly differed between groups (FDR-adjusted one-way ANOVA p-value < 0.01) in the small intestine metabolome. Among the most distinctive (FDR-adjusted one-way ANOVA p-value < 0.0001), 38 had structures assigned to them (Figure S8). There were two main clusters of metabolites: metabolites highly elevated with GenX-containing diets (Figure S8d) and metabolites that were underrepresented in GenX samples (Figure S8e). There was also a small set of metabolites that were characteristic of the PFOS diet: panobinostat, norethisterone enanthate, 3-oxocholic acid, and quinbolone. Based on the linear regression analysis, we identified 73 lowered and 29 elevated metabolites (p-value of linear regression model < 0.05) for PFOS diets (Table S7) and 77 lowered metabolites and 1 elevated metabolite (p-value of linear regression model < 0.05) for GenX diets (Table S9). PFOS exposure resulted in alterations to several metabolites (e.g., cortisol, histidine, methyl testosterone, 2′-deoxyadenosine, protoporphyrin IX, etc.), along with changes in microbiota that were associated with disturbances in various important bacterial metabolic pathways, such as steroidogenesis, purine metabolism, and porphyrin metabolism (Figure S8, Table S7). GenX exposure affected the levels of other microbial metabolites (lyso PE, AAAs, citric acid, serine, theophylline, 2′-deoxycytidine, histidine, etc.) linked to changes in such bacterial metabolic pathways as phospholipid biosynthesis, the urea cycle, the citric acid cycle, AAA metabolism, oxidation of branched-chain and long-chain fatty acids, serine metabolism, purine metabolism, and pyrimidine metabolism (Figure S8, Table S9). ## 3.5. PFOS and GenX Ingestion Alters Mice Colon Metabolome We identified 137 ($3\%$) metabolite variables that significantly differed between groups (FDR-adjusted one-way ANOVA p-value < 0.01) in the colon metabolome, indicating that lower parts of the digestive system are likely to be shielded from PFOS and GenX toxicity (Figure S9). Using linear regression analyses, we identified 33 lowered and 77 elevated metabolites (p-value of linear regression model < 0.05) for PFOS diets and 109 lowered and 22 elevated metabolites (p-value of linear regression model < 0.05) for GenX diets (Tables S7 and S9). Among the metabolites elevated in the PFOS group, we found several glucocorticoid-like molecules, such as cortisone, 11-ketoprogesterone, 3,17-dihydroxy-16-methyl-5,6-epoxypregnan-20-one, etc. Lowered metabolites included lyso PE, AAAs, citric acid, serine, theophylline, 2′-deoxycytidine, and histidine, and they led to disturbances in the metabolism of porphyrin, sphingolipid, arachidonic acid, and linolenic acid (Figure S9, Table S8). In the colon, GenX affected the levels of phytosphingosine, citric acid, arachidonic acid, AAAs, BCAs, and guanine. These metabolites are linked to the metabolism of sphingolipid, arachidonic acid, linolenic acid, tyrosine, purine, and phenylalanine, as well as the citric acid cycle (Figure S9, Table S10). There was also a set of 25 metabolites that were affected with both PFOS and GenX diets (Figure S9c); however, almost half of them showed different effects between the diets (note that the metabolites had a positive regression slope for PFOS diets and negative for GenX). ## 3.6. PFOS and GenX Ingestion Alters Liver Metabolome Untargeted metabolomic analysis using LC-MS/MS was undertaken to observe the general metabolomic alterations due to PFOS and GenX exposure. We used one-way ANOVA to identify metabolite features that differed between groups of replicates and noted 491 metabolites ($11\%$) that were significant (FDR-adjusted p-value < 0.01) (Figure S12). Further, a subset of the most distinctive variables (p-value < 10−4) for which we were able to assign chemical structures (61 metabolites in total) were selected, as shown in Figure 3a. We further classified metabolites into three groups: metabolites that systematically increased with the concentration of toxic compounds (see Figure 3b for examples), metabolites that systemically decreased (Figure 3c), and metabolites that showed nonlinear responses to the concentration of toxic compounds (Figure 3d). The first group predominantly contained cortisol- and carnitine-containing compounds, which increased with increasing concentrations of PFOS and GenX. The second group consisted of various amino acids and dipeptides, such as L-theanine, L-[-]-threonine, alanine-glutamate, and glycine-threonine. There was also a cluster of amine-containing compounds that were elevated with intermediate concentrations of toxic compounds (Figure 3d). We further analyzed the liver metabolome for PFOS- and GenX-containing diets separately to identify metabolites that were specifically enriched/decreased with increasing concentrations of a particular compound (Tables S10 and S11). For PFOS, we identified 147 underrepresented metabolites and 61 overrepresented ones (p-value of linear regression model < 0.05). Among the overrepresented metabolites were various fluorine-containing compounds (e.g., (2,3-difluorophenyl)acetic acid, 2,2,2-trifluoro-N-pentylacetamide, 2,6-difluoro-N-(tetrahydro-2-furanylmethyl)benzamide, hexyl trifluoroacetate, 9-hydrazono-2,7-bis-[2-(diethylamino)-ethoxy]-fluorene, etc.), which were probably products of PFOS degradation. The rest of the enriched metabolites were mostly organic acids, nucleic acids, fatty acyls, and carbohydrates, which were associated with lipid biosynthesis (glycerolipids, cardiolipins, phospholipid biosynthesis, etc.) and steroidogenesis pathways in the liver (Figure 4 and Table S8). In contrast, the underrepresented group primarily consisted of various amides and amino-acid compounds. A further reduced prostaglandin F2 level was found with an increase in PFOS concentration. For GenX, we identified only 18 underrepresented compounds and 49 overrepresented ones (p-value of linear regression model < 0.05), as it is considerably less toxic and has a milder effect on the liver (Table S7). Most of the compounds that decreased in concentration with increases in GenX were organic acids and fatty acyls, as well as amine-containing compounds. For PFOS, among the enriched metabolites, we further detected fluorine-containing compounds (e.g., 9-hydrazono-2,7-bis-[2-(diethylamino)-ethoxy]-fluorene), various organic acids, fatty acyls, and benzenoids and sterol lipids, which are associated with lipid metabolism (see Figure 4). Further, the presence of high concentrations of GenX was associated with increased levels of protoporphyrine and bile acids (taurochenodesoxycholic acid; taurocholic acid; and lithocholic acid, 2TMS derivative) in the liver. ## 4. Discussion In this study, we determined that PFOS and GenX exposure leads to significant perturbations in the gut microbiota and liver metabolome. Our results support previous studies demonstrating the roles of PFOS and GenX in metabolic disorders, endocrine toxicity, hepatotoxicity, developmental toxicity, altered metabolism, and several other kinds of toxicity [18,27,28,29,30,31,35,36,37]. We found that GenX had a relatively greater effect on the microbial beta diversity compared to PFOS and a much greater effect on the microbial diversity of the small intestine compared to colon (Figure 1b,c). Variation patterns similar to the gut microbiome were also observed in the metabolome features. Interestingly, colon and liver samples treated with higher concentrations of both PFOS and GenX had similar effects, while, for the small intestine, we observed different effects for GenX and PFOS. This may suggest that the colon and liver metabolome reflect a general toxicity level, while the small intestine is probably sensitive to a particular compound. Different taxa were found to be affected by PFOS and GenX, with PFOS affecting more species than GenX in both parts of the gut. We further noted that fold changes in relative abundance were much higher for PFOS than for GenX in the range of concentrations studied. In general, exposure to toxic compounds suppressed populations of beneficial taxa, such as Lactobacillus, Limosilactobacillus, and Ligilactobacillus, and led to increases in opportunistic pathogenic clades, such as Streptococcus and Turicibacter. These findings are corroborated by recently published studies that have also revealed the direct effect of PFOS (after 17 and 21 days of exposure) on the cecal content of the mice gut microbiome [10,39,51]. However, there are several discrepancies between the findings (e.g., these studies reported an increase in Clostridium cluster XIVa, while our results showed a reduction in its levels for both chemicals; the previous studies reported depletion of Alistipes, while we observed a qualitative increase in the PFOS treatment group), which might have been due to the collection of gut microbiota from different parts of the intestine in these two studies. The pathway analysis of the gut microbiome revealed that, in the small intestinal community, both PFOS and GenX enriched microbial pathways involved in amino acid biosynthesis; specifically, AAA, BCAA, arginine, and lysine (Figure 2d). Elevated levels of AAA and BCAAs have been reported to be linked to metabolic liver disease (MLD), increased risk of obesity [52], insulin resistance, type 2 diabetes mellitus (T2D) [53], and heart failure [54]. Further, changes in the metabolism of arginine and lysine in the intestinal microbiota were found to disturb host physiology [55,56], while increases in arginine metabolism were linked to coronary heart disease [57]. In addition, for GenX exposure, there were many more enriched pathways, including glutamate and glutamine biosynthesis, purine nucleotide degradation, and cobalamin (Vitamin B12) and tetrapyrrole biosynthesis. Amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease have been linked with perturbed levels of glutamine and glutamate [58,59], suggesting a possible association between GenX exposure and these diseases. Similarly, the enrichment of purine degradation pathways can alter the degradation of purine into uric acid (hyperuricemia), which may influence the development of gout [60,61]. Cobalamin is known to be involved in antioxidative stress response [62], as is glutamine [63], and affects the survival of gut bacteria during severe oxidative stress [62]. Therefore, GenX may have roles in several diseases through the modulation of microbial pathways. Moreover, there is some evidence that various tetrapyrroles, including B12, can be involved in PFAS degradation [64,65], highlighting the intriguing possibility that microbiome modulation due to GenX toxicity occurs as a response to environmental pollutants. This emphasizes the need for further mechanistic studies to provide insight into the mechanisms through which microbiome perturbations resulting from these chemicals may contribute to metabolic health disorders. In contrast to the small intestine, in the colon, most enriched/lowered pathways were associated with the PFOS diet (Figure 2e). Elevated levels of acetate are associated with obesity since acetate participates as a substrate in adipocyte and hepatic lipogenesis [66], as well as promoting secretion of ghrelin and insulin, leading to an increase in fat storage [67]. Secondly, D-glucarate has been found to inhibit various cancers, and its degradation may lead to an increased risk of developing several cancers [68,69]. Further, the enrichment of the polymyxin resistance pathway in gut microbiota may affect antibiotic resistance against polymyxin in bacterial infections due to the presence of transferable genetic elements in the microbiota contributing to polymyxin resistance [70]. In agreement with the fact that a few taxa were altered in colon microbiota in GenX-treated mice, our analysis demonstrated enrichment of very few pathways (Figure S10). The most important ones included cob(II)urinate a c-diamide biosynthesis—i.e., an anaerobic pathway for the synthesis of vitamin B12 [71]—and the super-pathway of thiamin diphosphate (vitamin B1) biosynthesis. Vitamin B1 is involved in nucleic acid ribose metabolism, which may enhance resistance to chemotherapy and tumor survival, thus suggesting a possible role for GenX in promoting the tendency of tumors to grow and spread in the body [72]. PFOS has been found to alter the host metabolism in previous studies [10,51] and various metabolic disorders are associated with exposure to PFAS compounds [35,73]. Therefore, we performed untargeted metabolomic analysis using LC-MS/MS to observe the general metabolomic alterations resulting from PFOS and GenX dietary exposure. Cortisol- and carnitine-containing compounds were found to be increased in the liver metabolome upon exposure to PFOS and GenX. These metabolites are well-known for causing oxidative stress in host species [74,75], and the findings may suggest possible roles for PFOS and GenX in the causation of oxidative stress. The levels of various amino acids and dipeptides, such as L-theanine, L-[-]-threonine, alanine-glutamate, and glycine-threonine, were also reduced as PFOS and GenX concentrations increased, possibly indicating that amino acid biosynthesis pathways were disrupted, as shown in Figure 4. PFAS compound exposure has previously been linked to the disruption of amino acid metabolism, which supports our findings [76]. For PFOS, the other metabolites found to be enriched were mostly organic acids, nucleic acids, fatty acyls, and carbohydrates associated with lipid biosynthesis (glycerolipids, cardiolipins, phospholipid biosynthesis, etc.) and steroidogenesis pathways in the liver (Figure 4 and Table S8). This might suggest a possible mechanistic role for liver metabolite disruption due to PFOS exposure in non-alcoholic fatty liver disease [77]. In contrast, various amides and amino-acid compounds were downregulated, which led to downregulation of multiple pathways, including glycine, serine, alanine, valine, leucine, histidine, and aspartate metabolism; ammonia recycling; and the urea cycle, thus indicating that PFOS induced inhibition of nitrogen metabolism in mice livers (Figure 4). We further detected that the prostaglandin F2 level was reduced with increases in PFOS concentration, and decreased levels of prostaglandin F2 might be associated with severe disruption of endocrine regulation, along with elevated cortisol levels [78], thus suggesting a possible role for PFOS in endocrine disruption. For GenX, limited numbers of compounds were found to be altered compared to PFOS, since GenX is considerably less toxic and has a milder effect on the liver (Table S7). The downregulated compounds were mainly organic acids and fatty acyls, as well as amine-containing compounds. Protoporphyrine was found to be elevated with increasing concentrations of GenX, which might have been associated with the degradation of GenX [64] and protection of the liver from the potential toxic damage posed by GenX. This finding was in agreement with the enriched biosynthetic pathways in the small intestine bacteria. Interestingly, unlike PFOS, the presence of high concentrations of GenX was associated with increased bile acid levels in the liver (taurochenodesoxycholic acid; taurocholic acid; and lithocholic acid, 2TMS derivative). This could potentially explain why microbial communities in the small intestine were so different in diets containing GenX compared to PFOS (Figure 1b,c), as bile acids can modulate bacterial communities in the upper intestine [79]. Overall, our findings demonstrate a differential, dose-dependent effect for PFOS and GenX on the gut microbiota and gut microbial metabolite secretion leading to alterations in the abundances of specific bacteria and metabolites. These changes may be linked to liver metabolome disruption through the gut–liver axis, which needs to be experimentally evaluated. Further, PFOS was found to have relatively greater impact on colon bacteria than GenX, perhaps due to the high potency of PFOS. ## 5. Conclusions In the present study, PFOS and GenX exposure was found to alter the gut microbiota and potentially disrupt the microbial functional pathways and the liver metabolome, as delineated in Figure 5. Our findings indicated that PFOS exhibited a stronger impact on colon microbiota and liver metabolome compared to GenX. Moreover, exposure to toxic compounds suppressed the beneficial taxa populations and increased the abundances of opportunistic pathogenic clades. While the specific alterations were somewhat different for these compounds, our experiments indicated that both PFOS and GenX can affect several host–microbiome pathways involved in many essential metabolic pathways, among which steroidogenesis and metabolism (of carbohydrates, lipids, amino acids, bile acids, purines, and pyrimidines) are of high clinical significance. The direct impact of these compounds on the gut bacterial community and the mechanistic associations between these microbiome perturbations and liver metabolome changes suggest that their toxicity for liver metabolism could perhaps be regulated by the gut microbiome. Hence, both PFOS and GenX can significantly compromise host–microbiome homeostasis, resulting in metabolic disturbances in the host. While the number of biological replicates in our study was limited, we used a combination of analysis tools and multi-omics data to ascertain the effects of toxicity on both the microbial community and the host. Evaluating several concentrations allowed us to strengthen the power of our analysis beyond qualitative determinations of significant changes across the gastrointestinal system. However, further studies with more replicates are needed to reinforce the results and distinguish real effects from natural sample variation. Studies with gnotobiotic animals evaluating changes in the effects of specific microbes and microbial metabolite alterations on host metabolome, transcriptome, and physiology due to PFAS exposure might provide exciting insights into the potency of these effects. Further, research on the impact of chronic PFAS exposure on gut microbiota and host metabolic homeostasis would be valuable in determining the impacts of these compounds on organisms exposed for prolonged duration. ## References 1. Ley R.E., Peterson D.A., Gordon J.I.. Ecological and Evolutionary Forces Shaping Microbial Diversity in the Human Intestine. Cell (2006.0) 124 837-848. 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--- title: 'Exploring the Potential of Phytocompounds for Targeting Epigenetic Mechanisms in Rheumatoid Arthritis: An In Silico Study Using Similarity Indexing' authors: - Sanjay H. Deshpande - Zabin K. Bagewadi - T. M. Yunus Khan - Mater H. Mahnashi - Ibrahim Ahmed Shaikh - Sultan Alshehery - Aejaz A. Khan - Vishal S. Patil - Subarna Roy journal: Molecules year: 2023 pmcid: PMC10051859 doi: 10.3390/molecules28062430 license: CC BY 4.0 --- # Exploring the Potential of Phytocompounds for Targeting Epigenetic Mechanisms in Rheumatoid Arthritis: An In Silico Study Using Similarity Indexing ## Abstract Finding structurally similar compounds in compound databases is highly efficient and is widely used in present-day drug discovery methodology. The most-trusted and -followed similarity indexing method is Tanimoto similarity indexing. Epigenetic proteins like histone deacetylases (HDACs) inhibitors are traditionally used to target cancer, but have only been investigated very recently for their possible effectiveness against rheumatoid arthritis (RA). The synthetic drugs that have been identified and used for the inhibition of HDACs include SAHA, which is being used to inhibit the activity of HDACs of different classes. SAHA was chosen as a compound of high importance as it is reported to inhibit the activity of many HDAC types. Similarity searching using the UNPD database as a reference identified aglaithioduline from the Aglaia leptantha compound as having a ~$70\%$ similarity of molecular fingerprints with SAHA, based on the Tanimoto indexing method using ChemmineR. Aglaithioduline is abundantly present in the shell and fruits of A. leptantha. In silico studies with aglaithioduline were carried out against the HDAC8 protein target and showed a binding affinity of −8.5 kcal mol. The complex was further subjected to molecular dynamics simulation using Gromacs. The RMSD, RMSF, compactness and SASA plots of the target with aglaithioduline, in comparison with the co-crystallized ligand (SAHA) system, showed a very stable configuration. The results of the study are supportive of the usage of A. leptantha and A. edulis in Indian traditional medicine for the treatment of pain-related ailments similar to RA. Our study therefore calls for further investigation of A. leptantha and A. edulis for their potential use against RA by targeting epigenetic changes, using in vivo and in vitro studies. ## 1. Introduction Rheumatoid arthritis (RA) is an autoimmune disease characterized as a chronic inflammatory disease, which affects around about $1\%$ of the population. It is mainly caused by genetic dispositions and environmental conditions, but may also occur because of abnormal activation of the immune system. The divergent activation of innate as well as adapted immune systems plays an important role in the pathogenesis of RA. Elevated levels of inflammatory cytokines produced from B cells and T cells play a very significant role in the development of the disease. The increase in levels of cytokines creates an abnormal environment around the cartilage and bone cells, leading to their destruction, which creates a disturbance in the moment of peripheral joints. The main instances that define RA in its active state are swelling and joint pain, resulting in disability and the destruction of joints, which finally leads to dysfunction of the joints. The anomalies that are characteristic of RA include the erosion of joints immediately after the symptoms appear, synovial infiltration in the clinically unaffected joints and the presentation of autoantibodies before the beginning of the disease, suggesting that the development of the disease occurs significantly earlier than the clinically significant symptoms start to appear [1]. Technological developments have led to clearer identification of the pathogenesis of RA. In recent years, the contribution of resident synovial fibroblasts (SF) has emerged as a key component in the pathogenesis and development of RA leading to the destruction of joints. RASF (rheumatoid arthritis synovial fibroblasts) are the most common cell types at the site of the invasion [2]. In recent years, aberrant epigenetic changes are characterized in connection with RASF that can help in solving intrinsic activation during the destruction of joints. This connection can help in providing the missing link between RA, risk factors and different therapy response [3]. Epigenetic modifications can be defined as the alteration of gene expression or phenotypes at the cellular level caused by mechanisms other than those of changes occurring in the DNA sequence where these modifications can be induced by environmental changes that are short-lived and reversible alterations [4]. Epigenetic modifications include DNA methylation and a network of post-translational modifications on histone tails like acetylation, phosphorylation, methylation, ubiquitination or sumoylation [5]. The target HDAC8 (histone deacetylase 8) is involved in the reaction that catalyzes the deacetylation of lysine residues present on the N-terminal region of the core histones [6,7,8]. The deacetylation functionality of the HDAC (histone deacetylase) enzymes plays a key role in epigenetic repression, which directly affects the transcriptional regulation and cell cycle development [6,7,9]. The key structural configuration of HDAC8 consists of a specific domain (region) ranging from 14–324 amino acids, which defines it as histone deacetylase enzyme [10], with an active site in 143rd position, and two types of binding sites: a divalent metal cation binding site in 178th, 180th and 267th position [11]; and substrate binding site in 101st, 151st and 306th position, as shown in Figure S1. Furthermore, disease-modifying antirheumatic drugs (DMARDs) are used specifically for the treatment of RA. Drugs like Methotrexate, Hydroxychloroquine, Sulfasalazine and gold salts are the most commonly used DMARDs, but due to their high number of side effects, which include damage to bone marrow and the nervous system, there is a need for alternative therapeutic procedures for the treatment of RA [12]. The mechanism of epigenetic modification in RA has gained growing research interest in recent times. The application of epigenetically modified methods is an important field in the research of RA pathogenesis. SAHA (Suberanilohydroxamic acid) is one of the known inhibitors of HDAC that has been applied in the treatment of RA and is known to be effective [13]. In this study, the compound aglaithioduline was selected based on the similarity indexing approach following most of the parameters considered. The information on plants that are being used for the treatment of rheumatoid arthritis was obtained from multiple sources like Indian traditional knowledge, Ayurveda practitioners and some published material available globally. Table S1 provides a list of published plants given in sources like “Indian Medicinal Plants, An Illustrated Dictionary”, C.P. Khare, 2007, Springer-Verlag New York [14] and “WHO Monographs on Selected Medicinal Plants”—Volume 1, 2, 3, 4. Chemistry is a field of study where structural analogy plays a very important role, and understanding the analogy and its functional impact becomes very important. Medicinal chemistry would have been very difficult to study, understand and apply if the structural similarity principle did not exist. The similar property principle states that structurally similar molecules tend to have similar properties, making this method a rule of thumb for application where there is an absence of detailed knowledge of chemicals. Similarity indexing mainly focuses on chemical similarity, which has also increased interest in the field of biological similarity. Similarity measurement techniques have always been looked at as foreign techniques, and people still are apprehensive about their efficiency and credibility. A single measure cannot therefore be stated as a perfect measure of similarity [15]. Molecular descriptors are the numerical values that have been assigned to a chemical structure, and the level of dimensional properties is defined by these descriptors, as shown in Table S2. The similarity coefficient is a quantitative measure of similarity between two sets of molecular descriptors. The similarity coefficient can be measured by various methods like the Tanimoto coefficient/fingerprint method, the cosine coefficient method, the Euclidean distance method and the Tversky index. The Tanimoto fingerprint method is the standard method for measuring the similarity coefficient, which is accepted globally, as given in Formula [1]. The Tanimoto coefficient for two molecules, A and B, can be given as:[1]SIMAB=ca+b−c where the c bits are set in common in the two fingerprints, and the a and b bits are set in the fingerprints for A and B respectively [16,17]. The need to validate the application of traditionally used herbs in a medicinal system with modern techniques is a very important step for the acceptance of these herbs globally. The gap between the usage and validation of traditional medicines can be closed only by initiating preliminary studies. In the current study, one such method of similarity indexing, in combination with widely used in silico techniques like molecular docking and molecular dynamics (MD), has been carried out [18,19]. Along with MD, MM/PBSA analysis and principal component analysis were carried out to understand the ligand–protein complex mechanisms in a system [20]. The main objective of this study is to understand the similarity correlation between the compounds from traditionally used herbs and standard drugs in the treatment of rheumatoid arthritis. ## 2.1. Similarity Indexing Similarity searching using the R programming method and the Tanimoto coefficient method resulted in similarity indices of phytocompounds in comparison to SAHA based on fingerprint values. The similarity indexing was carried out using the Shiny application called “Similarity indexing”, hosted and available for public usage on GitHub (https://github.com/sandes89/Similarityindexing, accessed on 30 September 2022). The application was used to identify highly similar compounds. Aglaithioduline showed ~$70\%$ of similarity in comparison to SAHA, the standard drug, and the co-crystallized compound with HDAC8 (PDB id: 1T69). The molecular properties of the compounds SAHA and aglaithioduline were compared, and it was seen that both compounds showed very similar chemical properties, as shown in Table 1. The pharmacokinetics properties of both compounds were also compared, and it was seen that both the compounds had very similar activities and properties predicted. Both the compounds, i.e., the standard drug (SAHA) and the compound obtained from similarity indexing (aglaithioduline), were subjected to preADMET checks using a pKcsm server [21], and complete details are given in Supplementary Table S1. From the preADMET studies, it was observed that the water solubility of both compounds showed very similar values, whereas the caco2 permeability of aglaithioduline was higher in comparison with that of SAHA. The total clearance rate, which includes both hepatic and renal clearance, was very high for aglaithioduline, making it more effective in terms of excretion from the body. ## 2.2. Binding Site Assignment The binding site for docking studies was assigned using the binding sites of the co-crystallized structure, P2RANK and a review of the literature. It was also based on curated sites from UniProt KB (Q9BY41). The assigned sites and the site coordinates are given in Table 2. ## 2.3. Protein–Ligand Interactions The molecular docking with the shortlisted compound based on the similarity indexing calculation and HDAC8 showed very promising results. The binding score and the interaction of compounds with the amino acid sites of the protein are tabulated in Table 3. Aglaithioduline showed a binding affinity with −8.4 kcal/mol and the interaction diagram is shown in Figure 1. Moreover, to confirm the correctness of the docking, the target HDAC8 and SAHA from the crystallized structure (PDB id: 1T69) were docked using the same configuration. The docking result clearly indicated that the compound stayed in the same binding pocket, thereby confirming the appropriateness and correctness of the docking procedure. The docked and the crystallized structure were superimposed and is shown in Figure 2. The results of docking showed that the binding affinity value of SAHA (standard inhibitor) with the target was found to be highest, and the aglaithioduline binding affinity value was very near to that of SAHA. Aglaithioduline, having ~$70\%$ structural similarity with SAHA, showed very promising results. Based on the binding affinity and the interactions, the HDAC8–aglaithioduline complex was further taken for molecular dynamics and simulation studies. ## 2.4. Molecular Dynamics and Simulation The molecular dynamics trajectory analysis for all three systems, namely APO (protein only), LIG (protein in complex with standard drug SAHA) and AG (protein in complex with aglaithioduline), was carried out. The RMSD of the backbone, RMSF of the residues, solvent-accessible surface area (SASA) and radius of gyration were plotted, and the number of hydrogen bonds between the compound and protein was also plotted for 100 ns (100,000 ps) of simulation duration. ## 2.5. Trajectory Analysis of APO, LIG and AG Systems RMSD analysis of the trajectories was carried out and it was observed that the APO system was stable after 20 ns. The RMSD plot of the LIG system and AG system was plotted and it was seen that the RMSD of aglaithioduline was higher than the APO system but stayed stable after the 20ns, and the RMSD was seen to be in the range of 0.3–0.38 nm. The trajectory of the AG system followed the pattern of the APO system (0.2–0.28 nm), whereas the trajectory of the standard drug (LIG system) showed high variability, which showed an increasing trend Figure 3a. The RMSF of APO, AG and LIG was plotted and it was clearly seen that the APO and AG system showed lower fluctuations than the LIG system. The stable residues indicate the stable configuration of the system in the APO and LIG systems, as shown in Figure 3b. The Rg, which is a measure of the overall size of a protein, is calculated as the root-mean-square distance of a group of atoms from their shared center of mass. The Rg plot of APO, AG and LIG in Figure 3c displays significant variation and fluctuation during simulation time, which suggests that the native conformation of the protein is flexible and subject to change throughout the simulation period. Therefore, this analysis provides valuable insights into the dimensions and dynamics of the protein structure. In addition, the solvent-accessible surface of the target protein was calculated and the volume against the time was plotted (Figure 3d). It was seen that the volume of the APO and AG systems stayed similar but the volume of the LIG system varied during the simulation duration. ## 2.6. Hydrogen Bond Counts for LIG and AG Systems Hydrogen bond analysis of the LIG and AG systems was carried out using the “hbonds” module of Gromacs. The analysis clearly showed that the LIG and AG systems had hydrogen bonds in the system throughout the simulation duration. The presence of hydrogen bonds during simulation indicates the stability of the protein in the system, which is a very important aspect in understanding the protein–ligand interactions (Figure 4). ## 2.7. MM/PBSA and Residual Decomposition Energy The estimated relative binding energy of the complex AG was −53.405 ± 44.255 kJ/mol and the Van der Waals, electrostatic, polar solvation and SASA energy was −45.480 ± 73.158, −5.641 ± 9.017, 2.539 ± 61.749, and −4.823 ± 7.161 kJ/mol, respectively. Furthermore, the AG system residue decomposition energy was calculated to infer the individual residue contributing most to the binding energy (Figure 5). The residues Pro35, Trp141, Phe152, Asp176 and Tyr306 favored stable complex formation by exhibiting the lowest contribution energy of −1.319, −1.552, −1.449, −0.727, and −1.44kJ/mol, respectively. However, the Arg37 residue did not favor the interactions (5.032 kJ/mol). The estimated relative binding energy of the complex LIG was 4.996 ± 16.014 kJ/mol and the Van der Waals, electrostatic, polar solvation and SASA energy was −112.149 ± 16.106, −96.119 ± 12.946, 226.486 ± 17.539, and −13.222 ± 0.869 kJ/mol, respectively. Furthermore, the LIG system residue decomposition energy was calculated to infer the individual residue contributing most to the binding energy (Figure 6). The residues Asp267, Asp272, Asp178, His180 and Phe208 favored stable complex formation by exhibiting the lowest contribution energy of −27.08, −3.76, −30.19, −6.77 and −6.97 kJ/mol, respectively. ## 2.8. Principal Component Analysis We performed principal component analysis to explore the conformational flexibility and diversity of conformations that emerged from the stable trajectory obtained from 100ns MD simulation. The maximum collective motion is captured by the first 50 eigenvectors/principal components. Therefore, we precisely studied the first two eigenvectors/PCs (principal components) in detail. Figure 7 represents the 2D projection of the first two eigenvectors. It is observed that the Apo form shows a lower diversity of conformation during the simulations (−3 to 4). However, the ligand–protein complex shows higher diversity of conformations during simulation (−7 to 3). This reveals that the ligand with protein is well equilibrated and stabilized during the simulation. ## 3. Discussion Many types of similarity indexing methods that utilize 2D fingerprints are available, and each has its own advantages and disadvantages. In this study, the Tanimoto coefficient (TC) is used to quantify and compare the similarity of the drug. The output from the TC is in the range between 0 (maximum dissimilarity) and 1 (maximum similarity) [22]. The TC is considered to be one of the best indices in similarity indexing, and is most efficient in cases that have compounds with moderate molecular weight [22]. The similarity indexing of SAHA and natural compounds resulted in aglaithioduline with a coefficient of ~0.7 ($70\%$ similarity). Aglaithioduline has a molecular weight of less than 300 which is the best-fit compound for the Tanimoto indexing method. The molecular docking studies result in the best-fit pose of aglaithioduline in complex with HDAC8 with a binding energy of −8.5 kcal/mol. The best-fit complex further underwent molecular dynamics analysis. The RMSD plot clearly showed that the LIG system of SAHA was unstable in comparison with the aglaithioduline (AG) system. RMSD stability indicates the stability of the protein–ligand binding and the RMSF calculations also showed stability in the AG system [23]. The MM/PBSA and residual decomposition energy analysis indicated stability and showed low energy, which is highly favorable in nature for the protein–ligand complex. Aglaithioduline, which is present in Aglaia leptantha and Aglaia edulis, has been traditionally used in Indian traditional medicine for the treatment of cancer, inflammatory conditions, fungal infections, tuberculosis and viruses [24,25]. Moreover, specific plants from Aglaia have been known to inhibit the translation process that is directly related to the epigenetic activity of the body [26]. Aglaithioduline and SAHA are both histone deacetylase inhibitors (HDACi) regularly used in cancer treatments. Both of these drugs have proven to be effective in treating various diseases which involve HDACs (histone deacetylases), but there are some key differences between them. Aglaithioduline is an orally administered HDACi that has been shown to have a high level of anti-inflammatory activity and that can inhibit the growth of tumor cells in a variety of cancer types. Studies have demonstrated that aglaithioduline has a higher selectivity for HDAC enzymes and a lower toxicity profile than other HDACi drugs. Aglaithioduline has also been shown to be effective in combination with other drugs and to have synergistic effects when combined with chemotherapy [27]. SAHA, on the other hand, is an intravenously administered HDACi. It has been used to treat a variety of cancers, including leukaemia and RA [28]. In summary, both aglaithioduline and SAHA are effective HDACi drugs used in various pathological conditions, including cancer and RA. All the known activities of the compound and the herb clearly show that the compound aglaithioduline is a compound of interest and that herbs can also be studied further for the elucidation of synergetic activities of other compounds of potential use in the treatment of RA. ## 4.1. Similarity Searching To begin the process of similarity searching, 2,231,213 compounds from the UNPD database were downloaded in sdf format with their corresponding metadata. The reference compound to be searched for similarity is appended at the beginning of the multi-compound sdf file and the merged sdf file is further imported into R [29]. Similarity searching was carried out based on the fingerprints of compounds that are stored in the database in matrix form [30]. The fingerprint set of compounds acts as a searchable database that consists of compounds’ fingerprints [31]. The fingerprints of the compounds are supported by the atom pair database [32]. Similarity searching is further carried out using the Tanimoto similarity search index [33]. The output is given in the form of index values in decreasing order: the higher the value, the more similar the compound is to the reference compound. Using the existing algorithms and library, an R-based Shiny application was developed, which was used to carry out similarity indexing. ## 4.2. Docking Studies Molecular docking of the highly similar phytocompounds in comparison with the structure of target protein HDAC8 (PDB id: 1T69) [34] was carried out using Autodock vina [35,36] with help of POAP implementation [37]. The POAP tool is a powerful program designed to facilitate protein–ligand docking. This tool is used to optimize the binding parameters of protein–ligand complexes by using the methods of free energy calculation, electrostatics and molecular dynamics. The binding site of the target protein was assigned based on the interaction of the co-crystallized structure with the ligand SAHA and also, based on the literature, showing the active sites and binding sites on the target protein. In addition, the target protein was subjected to P2RANK [38] analysis, which provides detailed information on binding sites and their ranking. P2RANK binding site assignment is a computational method for predicting and ranking the potential binding sites of a target protein. The method is based on several physicochemical parameters that measure the strength of the interactions between a target protein and its ligands. These parameters include the electrostatic, hydrophobic, Van der Waals and steric interactions between the two molecules. To rank the binding sites, the P2RANK method calculates a score for each potential binding site, based on these parameters. The compounds selected from the similarity indexing were listed and the chemical structures in sdf format were converted to pdbqt format using POAP, with energy minimization conducted using the steepest descent method [39]. The energy-minimized structures were used for docking studies with an exhaustiveness of 100 [40]. The top complex based on the binding energy was further considered for MD studies based on the interactions with the active site of the co-crystallized structure of HDAC8. The preADMET properties of the test compound and the standard drug were predicted using the pkCSM server. The prediction of ADMET properties is very important in understanding the drug-likeness and toxicity profile [41]. ## 4.3. Molecular Dynamics Studies The simulation systems in the study considered were the apoprotein, the target in complex with the standard drug and the target in complex with the compound obtained from similarity indexing. Simulations were carried out on Gromacs version 2019.4 [42]. The system for the simulations was subjected to 50,000 steps of steepest descent energy minimization to nullify the steric overlap. Furthermore, all the systems were applied to a two-step equilibration phase, namely NVT (constant number of particles, volume and temperature) and NPT (constant number of particles, pressure and temperature). NVT equilibration was run for 500 picoseconds (ps) to stabilize the temperature of the system, and NPT was run for 500 ps to stabilize the pressure of the system to be subjected to dynamics, in order to relax the system and maintain restraint on the protein. The temperature coupling [42,43] method was applied for the NVT ensemble, along with the constant coupling of 1 ps with 303.15 K. For NPT, Nosé–Hoover pressure coupling [44,45] was applied with the constant coupling of 1ps with 303.15 K under conditions of position restraints (h-bonds) by the selection of random seed. The calculation of electrostatic forces for NVT and NPT were carried out using the particle mesh Ewald method [46]. All the systems were subjected to a complete 100 nanosecond (ns) simulation under no restraint conditions, with an integration time step of 0.002 ps and an xtc collection interval of 5000 steps for 100 ps. The analysis of the Gromacs trajectory files was carried out using Gromacs utilities. The trajectory’s root-mean-square deviation (RMSD) was calculated using “gmx rmsd” and root-mean-square fluctuation (RMSF) analysis was carried out using “gmx rmsf”. The radius of gyration was calculated using “gmx gyrate” to determine whether the system reached convergence over the 100 ns simulation. The solvent-accessible surface area (SASA) was calculated using the “gmx sasa” command to determine the area accessible by water in the protein, in which the ligand can move around bound with the target protein. The hydrogen bond counts for the protein–ligand complex in both the target in complex with standard drug and the target in complex with the compound resulted from similarity indexing [47]. ## 4.4. MM/PBSA and Residual Decomposition Energy The molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) is a computational method used to study the thermodynamic properties of protein–ligand complexes. This approach calculates the free energy of a protein–ligand system by breaking it down into separate contributions from various energy terms, such as molecular mechanics, Poisson–Boltzmann electrostatics and solvation-free energies. The MM/PBSA method has been widely used in drug discovery and design, as it provides insights into the molecular interactions between a ligand and a protein target. This information can be used to design and optimize drug candidates for further development. In the current study, the relative binding energy and its contribution to individual residues were calculated using the MM/PBSA method by utilizing the “g_mmpbsa” tool. The parameters from past research were taken into account while calculating the binding energy. Using 50 representative snapshots, the binding energy was determined throughout the steady trajectory observed between 50 and 100 ns [48,49]. The MM/PBSA result summary comprises Van der Waals energy, electrostatic energy, polar solvation energy and total binding energy. Based on the low binding energy of the system the stability of the system can be determined. ## 4.5. Principal Component Analysis The molecule’s rotational and translational motion using the “least square fit” to the reference structure was examined using MD trajectories. The eigenvalue related to each eigenvector indicates the energy contribution of that part to the motion. The projection of the trajectory on a specific eigenvector illustrates the “time-dependent movements” that the components perform in a specific vibrational mode [50,51]. The projection’s time average reveals the contribution of atomic vibration components to this mode of coordinated motion. The eigenvectors and eigenvalues of the trajectory were generated using the Gromacs in-built utilities “g_covar” by calculating and diagonalizing the covariance matrix. The “g_anaeig” tool was also used to analyze and illustrate the eigenvectors. ## 5. Conclusions The similarity indexing approach of identifying compounds having activity similar to that of the existing standard is a highly efficient and accurate method. In this study, the standard drug used in patients with rheumatoid arthritis, SAHA, was taken as a reference molecule against the database of natural compounds to find similarity indexes. The similarity indexing method resulted in the identification of aglaithioduline as a compound with ~$70\%$ similarity, and further in silico studies with HDAC8 clearly showed a high stability in the system in comparison with the standard drug. The system was also found to be very compact based on the radius of gyration around the axis. Hydrogen bond contact analysis also revealed the high binding affinity of aglaithioduline with HDAC8. Based on the results obtained, Aglaia leptantha and Aglaia edulis, in which aglaithioduline is present abundantly, can be taken further for in vivo and in vitro studies as anti–arthritic treatments specifically. ## References 1. Smolen J., Aletaha D.. The Burden of Rheumatoid Arthritis and Access to Treatment: A Medical Overview. Eur. J. Health Econ. (2008.0) 8 39-47. 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--- title: The Impact of a Low-Carbohydrate Diet on Micronutrient Intake and Status in Adolescents with Type 1 Diabetes authors: - Neriya Levran - Noah Levek - Bruria Sher - Noah Gruber - Arnon Afek - Efrat Monsonego-Ornan - Orit Pinhas-Hamiel journal: Nutrients year: 2023 pmcid: PMC10051868 doi: 10.3390/nu15061418 license: CC BY 4.0 --- # The Impact of a Low-Carbohydrate Diet on Micronutrient Intake and Status in Adolescents with Type 1 Diabetes ## Abstract Objective: The aim of this study was to evaluate the macronutrient and micronutrient intake and status in youth with type 1 diabetes mellitus (T1DM) following the consumption of a low-carbohydrate diet (LCD). Research Methods and Procedures: In a prospective intervention clinical trial, adolescents with T1DM using a continuous glucose monitoring device were enrolled. Following a cooking workshop, each participant received a personalized diet regime based on LCD (50–80 g carbohydrate/day). A Food Frequency Questionnaire was administered, and laboratory tests were taken before and 6 months following the intervention. Twenty participants were enrolled. Results: The median age was 17 years (15; 19), and the median diabetes duration was 10 years (8; 12). During the six-months intervention, carbohydrate intake decreased from 266 g (204; 316) to 87 g (68; 95) ($$p \leq 0.004$$). Energy intake, the energy percent from ultra-processed food, and fiber intake decreased ($$p \leq 0.001$$, $$p \leq 0.024$$, and $p \leq 0.0001$, respectively). These changes were accompanied by declines in BMI z-score ($$p \leq 0.019$$) and waist-circumference percentile ($$p \leq 0.007$$). Improvement was observed in the median HbA1c from $8.1\%$ (7.5; 9.4) to $7.7\%$ (6.9; 8.2) ($$p \leq 0.021$$). Significant declines below the DRI were shown in median intake levels of iron, calcium, vitamin B1, and folate. Conclusions: The LCD lowered ultra-processed food consumption, BMI z-scores and the indices of central obesity. However, LCDs require close nutritional monitoring due to the possibility of nutrient deficiencies. ## 1. Introduction Type 1 diabetes mellitus (T1DM) is one of the most common endocrine and metabolic conditions in childhood and is often characterized by poor glycemic control [1]. Integral to the management of T1DM, dietary therapy aims to provide healthy eating principles, improve diabetes outcomes, and reduce cardiovascular risk [2]. A Mediterranean diet in conjunction with carbohydrate counting is frequently used in the clinical management of T1DM [2]. Notwithstanding the pharmaceutical, technological, and nutritional advancements in the past decades, glycemic parameters remain suboptimal, with an average HbA1c of $9.3\%$ between the ages of 15 and 18 years [3]. Carbohydrates are the primary macronutrient that affects the postprandial glycemic response. The international guidelines published by the International Society of Pediatric and Adolescent Diabetes include 40–$50\%$ of total energy consumption from carbohydrates, and achievement of optimal postprandial glycemic control with appropriately matched insulin to carbohydrate ratios and insulin delivery [2]. The evidence in the literature is currently insufficient to support the use of low-carbohydrate diets (LCD) as an adjunctive treatment for T1DM. However, given the difficulty of matching carbohydrate intake with insulin dose, reducing dietary carbohydrate consumption among people with diabetes has become a common dietary pattern [4,5]. The lower consumption of carbohydrates essentially lowers the glycemic response and the insulin requirement. Although LCD has a promising effect on glycemic control, endorsing the regime may lead to harmful dietary consequences. This is due to the complete or partial avoidance of healthy sources of carbohydrate foods such as whole grain bread, cereals, legumes, fruit, and vegetables. In individuals with T1DM, adverse health risks such as diabetic ketoacidosis, hypoglycemia, dyslipidemia, glycogen depletion, and growth impairment remain clinical concerns. In an illustrative case series of children with T1DM who were on LCD, some experienced growth delay and fatigue [6]. In addition, adherence to restricted diets is challenging and can impact social normality. Parents or people with T1DM who choose LCD usually do so without proper medical guidance and may put their child or themselves at risk of nutritional depletion of essential nutrients and minerals. Studies examining glycemic outcomes from LCD have largely been cross-sectional and without validated dietary data [7]. In the current study, we aimed to investigate the effect of an LCD intervention on macronutrient and micronutrient intake and status in youth with T1DM. ## 2.1. Participants and Study Design This report documents a prospective intervention clinical trial conducted in the Pediatric Endocrinology and Diabetes Unit at the Sheba Medical Center. Eligibility criteria were a diagnosis of T1DM according to the American Diabetes Association criteria [1] for at least one year, age 12–22 years, and the usage of a continuous glucose monitoring device (Dexcom, San Diego, CA, USA, Medtronic, Northridge, CA, USA, Libre, Alameda, CA, USA). Exclusion criteria included a medical history of eating disorders in participants or their first-degree family members (there is a clear link between dieting and developing an eating disorder. We were concerned that a restrictive carbohydrate diet could result in, or aggravate, overeating and binge-eating behaviors in those at risk for eating disorders) or any other mental illness. Eligible trial participants were enrolled after they were contacted during their visits to the pediatric diabetic clinic. Written informed consent was obtained from participants aged 18 years or older and from parents or legal guardians of those under age 18 years. Ethics approval was obtained from the Helsinki Committee in the Sheba Medical Center. ## 2.2. Diet Intervention At baseline, each participant underwent a cooking workshop and received a personalized diet regime based on the LCD. For participants younger than 18 years, nutrition education was provided to both the participants and their parents. Participants met individually with a dietitian for diet instructions and support at weeks 1, 2, 4, 7, 10, 12, and 24, for a total of seven frontal meetings. Twice during the first 12 weeks, the dietician conducted 10–15-min motivational telephone calls with each participant. During the entire course of the study, every participant had the option of consulting with the study’s dietitian (Supplementary File S1). ## 2.3. Low-Carbohydrate Diet The LCD aimed to provide 50–80 g/day of carbohydrates. There was no caloric restriction, but each patient received a weekly plan with main meals and snacks. The planned macronutrient composition of the diet (percentage of total calories) was: $20\%$ carbohydrate, $25\%$ protein, and $55\%$ fat. All the dietary details were stated in the protocol and approved by the IRB. ## 2.4. Assessment of Nutritional Composition The habitual food consumption of the participants was evaluated using the Food Frequency Questionnaire (FFQ), which was taken at baseline and after six months of intervention. The FFQ included 116 food items commonly eaten in Israel, standard portion sizes, and a frequency response section. It is based on a validated FFQ used for determining the dietary intake of Israeli multiethnic populations [8]. Using the Tzameret software, Israeli food and nutrient database, total energy intake (Kcal) and both macronutrients and micronutrients were calculated [9]. The distributions of macronutrients and micronutrients as percentages of daily energy consumption were also estimated and compared to dietary recommended intake (DRI) values [10]. ## 2.5. Medical History and Anthropometric Measurements Age of diabetes onset, diabetes duration, and other medical diagnoses data were retrieved from medical records. Height, weight, and waist circumference were measured at each visit according to standardized protocol by trained and certified staff. Body mass index (BMI) was calculated as weight (kg)/height squared (m2). BMI z-score norms were calculated for ages 2–20 years. For participants older than 20 years on the day of enrollment, we extrapolated the BMI z-score from the calculated BMI at age 20 [11]. ## 2.6. Biochemical Parameters Blood samples including HbA1c, total cholesterol, LDL cholesterol, and HDL cholesterol were collected under metabolic stability conditions. The latter were defined as no episode of diabetic ketoacidosis within 1 month before the visit and after ≥12 h of fasting. Laboratory results of serum C-reactive protein (CRP), blood urea nitrogen (BUN), creatinine, sodium, magnesium, calcium, zinc, phosphorous, vitamin B1, vitamin C, and folic acid were recorded. All fasting blood samples were taken at baseline and at 24 weeks, from a forearm vein and then processed by ELISA (Enzyme-Linked Immunosorbent Assay) at the Sheba Medical Center laboratories. ## 2.7. Trial Outcomes Our primary endpoint was nutritional vitamins and mineral status after 24 weeks of an LCD. Secondary outcomes were body weight and waist circumference at this time point. ## 2.8. Statistical Analysis Categorical variables were described using frequencies and percentages. Continuous variables were expressed as medians and interquartile ranges (IQR, 25th; 75th percentiles). The Wilcoxon test was used to compare continuous variables before and after the 6-month period. Spearman’s correlation coefficient test was used to study associations between continuous variables; >0.36 was considered as a moderate correlation, while r > 0.67 was considered as a high correlation. All statistical tests were two-sided, and all p values were adjusted by the false discovery rate. The statistical analyses were performed by SPSS software (IBM SPSS STATISTIC version 28, IBM Corp., Armonk, NY, USA, 2021). ## 3.1. Study Group Characteristics Twenty adolescents with T1DM (14 females) were enrolled in the study at median (IQR) age of 17 years (15; 19). The median diabetes duration was 10 years (8; 12). Eighteen participants were treated with an insulin pump and two were treated with multiple daily injections. The median BMI z-score was 1.3 (0.65; 1.50); nine participants were categorized as having normal weight, seven were categorized as having overweight, and four were categorized as having obesity. The median waist circumference was 85.7 cm (80.0; 91.8), and the median percentile was $76.5\%$ (55.2; 83.5). One female participant withdrew after 3 months as she found it challenging to manage the LCD (Figure 1—A flow chart of the study). ## 3.2. FQQ The median baseline percent from calories of carbohydrates was $44\%$ (37; 47); from protein, $18\%$ (16.5; 20); and from fat, $35\%$ (30; 37). Baseline median percentages of micronutrients were calculated according to DRI values as follows: fiber $115\%$ (97.5; 145.5), iron $101\%$ (85; 138), magnesium $145\%$ (118; 180), calcium $116\%$ (82; 140.7), zinc $135\%$ (111.2; 166.2), copper $158\%$ (144; 182), vitamin B1 $152\%$ (136; 189), vitamin B2 $229\%$ (188; 264), vitamin B6 $252\%$ (199; 288), folate (vitamin B9) $123\%$ (108; 143), vitamin B12 $225\%$ (200; 309), and vitamin C $359\%$ (200; 471). After 6 months of the LCD intervention, the median intakes of several macronutrients and micronutrients were significantly different than at baseline (Table 1). The median percentage of calories from carbohydrate was $20\%$ (18; 25); from protein, $25\%$ (22; 25); and from fat, $51\%$ (48–52). Median energy consumption decreased from 2537 kcal (1954; 2773) to 1533 kcal (1256; 1758 kcal) ($$p \leq 0.001$$), and the percent of calories from ultra-processed food decreased from $16.6\%$ (9.4; 23.0) to $11.0\%$ (8.3; 15.9) ($$p \leq 0.047$$). The reported carbohydrate intake decreased by $67\%$, from 265.0 g (204; 315) at baseline to 86.6 g (68.1; 95) ($p \leq 0.001$). Accordingly, this decline was seen in fibers, total sugars, and fructose. While the median protein intake decreased significantly, it remained within the DRI for all the participants. Fat intake, on the other hand, did not change significantly. Significant decreases were observed in the median intakes of several minerals and vitamins. Median intakes lower than recommended values were noted in iron, calcium, vitamin B1, and folate. Moderate decreases were observed in median intakes of fat-soluble vitamins (A, E, K) and in vitamin C, but these changes were not statistically significant (Table 1). According to the DRI, higher proportions of participants were deficient after than before the intervention, in: fiber, $75\%$ vs. $35\%$; calcium, $50\%$ vs. $45\%$; magnesium, $20\%$ vs. $10\%$; copper $5\%$ vs. $0\%$; vitamin B1, $65\%$ vs. $15\%$; and folate, $50\%$ vs. $20\%$. ## 3.3. Weight Loss and Waist Circumference The LCD was associated with significant reductions in median BMI z-scores ($$p \leq 0.042$$) and waist circumference percentiles ($$p \leq 0.021$$) (Table 2). ## 3.4. Blood Laboratory Measurements The median (interquartile range) HbA1c level declined after LCD, from $8.1\%$ (7.5; 9.4) to $7.7\%$ (6.9; 8.2), $$p \leq 0.021.$$ Parameters of the lipid profile did not change significantly. CRP declined from 3.5 mg/L (1.1; 7.1) to 2.5 mg/L (1.0; 4.9) ($$p \leq 0.042$$). The median serum level of magnesium did not change; however, three participants had low levels (<1.8 mg/dL) at the end of the study. The median serum levels of folic acid and vitamin C did not change; however, one participant had borderline levels of folic acid deficiency (2–4 ng/mL), and another developed marginal vitamin C level (<6 mg/L). The median serum zinc level decreased from 130.5 mcg/dL (104.7; 150.0) to 98.0 mcg/dL (82.5; 119.0) ($$p \leq 0.042$$), but all participants were in the normal range of 50–150 mcg/dL. The medians of vitamin B1, calcium and phosphorous did not change significantly (Table 2). ## 3.5. Correlations Delta body weight was not correlated with any of the parameters examined. The delta of calories from ultra-processed food did not correlate with any of the macronutrients or micronutrients examined. Table 3 shows correlations of decreased carbohydrate intake and of decreased protein intake, with changes in the consumption of selected macronutrients and micronutrients, as reported in the FFQ. A decreased intake of carbohydrates was associated with a significant decreased intake of fibers, iron, copper, potassium, magnesium, vitamin B1, vitamin B6, vitamin B2, and vitamin C. Decreased protein intake was significantly correlated with a decreased intake of fat, iron, calcium, potassium, sodium, zinc, vitamin B1, and vitamin B2; no correlations were observed between reported FFQ intakes and blood levels of calcium, magnesium, thiamine, and vitamin C. ## 4. Discussion In this novel study of youth with TIDM who followed LCD for six months, decreases were found in median intakes of several macronutrients and micronutrients. Median blood levels of several nutrients decreased. These changes were in parallel to an improved median HbA1c level and lower median values of CRP, BMI z-score, and waist circumference. The proportion of calories from ultra-processed food decreased during the intervention, because adherence to the LCD required more frequent cooking and less consumption of prepared food. Our findings are in concordance with a randomized trial among adults without diabetes [12]. The decrease by $70\%$ in carbohydrate intake shows good compliance of our participants throughout the study period. We believe that the workshops with food preparation and imparting knowledge, together with the careful supervision and frequent in-person meetings and phone calls contributed to the good adherence and compliance in our study. The decrease in carbohydrate intake was associated with reduced intakes of fibers and fructose. Low fiber intake was consistently demonstrated in several studies that investigated LCD [6,13,14]. Appropriate fiber intake has been positively linked with a potential increase in lifespan [15]. Decreased carbohydrate intake requires the substitution of another macronutrient, hence the fear that increased fat consumption could impair the lipid profile. However, among our participants, the fat intake did not change significantly after conversion to LCD due to calories decrease. Lipid profiles were not significantly elevated; these findings are in line with a 12-week crossover randomized study comparing high-carbohydrate diet versus LCD in 14 participants with T1DM [16]. Daily protein intake, on the other hand, decreased but was still higher than or as high as the DRI. The reported FFQ showed significantly lower median intakes at the end of the intervention compared to baseline, according to percentages of recommended daily allowance of several minerals and vitamins (iron, calcium, phosphorus, vitamin B1). These findings are in agreement with a systematic review that showed deficient intakes of magnesium, calcium, iron, iodine, thiamine, and folate in healthy adults who followed a carbohydrate-restricted diet [17]. Only one case series examined micronutrient intake among adolescents and children with T1DM who consumed LCD [6]. Among five participants, deficient intakes were detected in at least one of the following; calcium, magnesium, phosphorus, thiamine, and folate [6]. These data suggest that some high-carbohydrate foods are good sources of vitamins and minerals, which are present naturally or added to fortify foods. At the end of the 6-month intervention, decreases by about $30\%$ were reported in the median intakes of water-soluble vitamins, namely, vitamin B1 and folate. Our findings of unchanged median blood levels, despite decreases in median intakes, corroborate a prospective study that measured the nutrient intake of children and adolescents on 4-month treatment with a ketogenic diet [18]. We demonstrated that the decreases in mineral and vitamin intake were associated with decreased intake of carbohydrates and not secondary to the decrease in total energy. Indeed, the vitamins whose intake decreased are mainly found in whole grains, which are not part of an LCD; and in pork and seafood, which are not regular components of the Israeli diet. B vitamins are critical cofactors for axonal transport, the synthesis of neurotransmitters, and many cellular metabolic pathways. Thus, guidelines for nutritional replacement should be given to those who consume LCD [19]. Importantly, mean intakes of fat-soluble vitamins (A, E, K) did not change during our intervention. This might be due to the composition and types of food consumed in the LCD, such as eggs, fish, meat, and nuts. Median intake levels of the trace elements iron and calcium were lower after the LCD than at baseline. Notably, a systematic review and case series described a lower intake of iron after conversion to LCD [6,17]. In the present study, median serum zinc values were within the normal range both at baseline and at the end of the intervention in spite of a downward trend. Data on the effect of dietary zinc intake on its serum level remain inconclusive. This decrease in daily consumption may be due to the lack of legumes and grains in LCD. Zinc is an essential trace element found in food, playing a role in many antioxidative defense and metabolic processes, such as insulin processing, storage, secretion and action [20,21]. Studies have shown that serum zinc concentrations of Polish children with T1DM were significantly lower than those of a control group [22]. One review estimated a dose–response relation of zinc intake with serum zinc concentrations in children aged 1–17 years [23], while another more recent study showed that serum zinc concentrations were not related to dietary or supplemental zinc but to an individual’s sex and age as well as the time of blood draw [24]. Homeostatic regulatory mechanisms were also observed to result in decreased dietary zinc absorption as intake increased [23], emphasizing the importance of monitoring zinc intake rather than relying solely on zinc levels in plasma. Data indicated a decrease in copper intake. Copper is a vital mineral that aids in the production of neurotransmitters, connective tissue, neuropeptides, and energy [25]. Amounts of the mineral in food vary based on the season, soil quality, and water sources [26]. A case study found copper deficiency-induced anemia and neutropenia in a child who changed from a liquid to solid ketogenic diet [27]. According to the FFQ, magnesium intake was significantly lower in our participants after the LCD; four participants had deficient magnesium plasma levels. Magnesium is an essential cation that is found in legumes, nuts, and vegetables. Of note, magnesium deficiency is the most prevalent trace element deficiency in individuals with T1DM [22] and is associated with cardiac arrhythmias, hypertension, and intima-media thickness (an early marker of atherosclerosis) [28]. Therefore, individuals with T1DM who follow an LCD are in particular need of guidance for nutritional enrichment or supplements of magnesium. A $30\%$ decrease in selenium intake was observed in our cohort despite instructed supplementation with Brazil nuts. Selenium is an essential trace element known to influence various physiological processes, including energy homeostasis, through its redox functions. It is used to synthesize selenoproteins, which is a family of proteins with mainly antioxidant roles [29]. A study on children with intractable epilepsy on a ketogenic diet showed $20\%$ selenium deficiency [30] and suggested screening for selenium deficiency when intake is lower than $75\%$. Thus, an appropriate selenium level should be obtained through the diet, and the consumption of selenium-rich foods, such as seafood, organ meats, and Brazil nuts, should be recommended. Our data demonstrated improved parameters of the metabolic syndrome such as weight, BMI z-score, waist circumference, and CRP, as well as improved glycemic control, among adolescents with T1DM following a 6-month LCD intervention. The high CRP levels observed at baseline corroborate a study of children with T1DM who had higher levels of CRP than a control group; elevated CRP has been linked to coronary events [31]. Furthermore, the incidence of the metabolic syndrome among TIDM is growing, and it is a major problem, further increasing risks of morbidity and mortality [31]. Therefore, the impact of LCD on improving these parameters is of high importance. For people with T1DM who follow LCD, we advise long-term and periodic monitoring of the nutrients whose intakes and blood levels decreased during the six months of our intervention. Nutritional deficiencies after LCD emphasize the need to provide nutritional substitutes that could fill the nutritional gaps [32]. Our study has some limitations. As with all dietary recall studies, FFQ interviews are subject to recall bias. However, this recall method is considered more reliable than a single-day recall [33]. Despite its strong research foundation, the FFQ probably contains omissions regarding precise amounts of nutrients. Another limitation is that in Israel as elsewhere, a large market of ketogenic/low-carb products has emerged as a result of the popularity of LCD in the general public. As some producers are local, the quantities of the dietary components may not always have been precise. This could result in underestimation and overestimation of the total caloric intake. In addition, our cohort comprised only 19 participants and does not inform the development of nutritional deficiencies following long-term adherence to LCD. Although physical activity is a major aspect of lifestyle change, the participants did not receive explicit instructions regarding their physical activity. Moreover, as the aim was nutritional intake and not weight change, physical activity was not assessed. The strengths of the study are its prospective follow-up. It is the first study to perform a 6-month intervention, intensive dietary surveillance for LCD, and assessment of a variety of micronutrients. ## 5. Conclusions Medical nutrition therapy remains a cornerstone of diabetes care [2]. LCD has the potential of significantly improving glycemic control, preventing and treating overweight and obesity, and improving parameters of the metabolic syndrome such as central obesity. Nonetheless, LCD may result in nutritional deficiencies, as decreased carbohydrate consumption was positively correlated with decreases in vitamin and mineral intake that were not due to calorie reduction. Thus, these decreases resulted from the LCD content rather than from reduction in calories. As LCD may be accompanied by nutritional deficiencies, in individuals with type 1 diabetes who have opted to switch to LCD, we recommend an assessment of the contents of vitamins and minerals from the beginning. The dietician should plan a diet enriched with foods containing soluble vitamins (in particular folate and thiamin), selenium, magnesium, calcium, and iron. Furthermore, we recommend supplementation in a specific quantity, such as yeast extract, Brazil nuts, and Wolffia globose daily. Finally, we advise checking vitamin and mineral blood levels every six months and, if necessary, supplementing daily intake with vitamins and minerals. ## References 1. 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--- title: Albumin–Globulin Score Combined with Skeletal Muscle Index as a Novel Prognostic Marker for Hepatocellular Carcinoma Patients Undergoing Liver Transplantation authors: - Yang Huang - Ning Wang - Liangliang Xu - Youwei Wu - Hui Li - Li Jiang - Mingqing Xu journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051871 doi: 10.3390/jcm12062237 license: CC BY 4.0 --- # Albumin–Globulin Score Combined with Skeletal Muscle Index as a Novel Prognostic Marker for Hepatocellular Carcinoma Patients Undergoing Liver Transplantation ## Abstract Background: Sarcopenia was recently identified as a poor prognostic factor in patients with malignant tumors. The present study investigated the effect of the preoperative albumin–globulin score (AGS), skeletal muscle index (SMI), and combination of AGS and SMI (CAS) on short- and long-term survival outcomes following deceased donor liver transplantation (DDLT) for hepatocellular carcinoma (HCC) and aimed to identify prognostic factors. Methods: A total of 221 consecutive patients who underwent DDLT for HCC were enrolled in this retrospective study between January 2015 and December 2019. The skeletal muscle cross-sectional area was measured by CT (computed tomography). Clinical cutoffs of albumin (ALB), globulin (GLB), and sarcopenia were defined by receiver operating curve (ROC). The effects of the AGS, SMI, and CAS grade on the preoperative characteristics and long-term outcomes of the included patients were analyzed. Results: Patients who had low AGS and high SMI were associated with better overall survival (OS) and recurrence-free survival (RFS), shorter intensive care unit (ICU) stay, and fewer postoperative complications (grade ≥ 3, Clavien–Dindo classification). Stratified by CAS grade, 46 ($20.8\%$) patients in grade 1 were associated with the best postoperative prognosis, whereas 79 ($35.7\%$) patients in grade 3 were linked to the worst OS and RFS. The CAS grade showed promising accuracy in predicting the OS and RFS of HCC patients [areas under the curve (AUCs) were 0.710 and 0.700, respectively]. Male recipient, Child–Pugh C, model for end-stage liver disease (MELD) score > 20, and elevated CAS grade were identified as independent risk factors for OS and RFS of HCC patients after DDLT. Conclusion: CAS grade, a novel prognostic index combining preoperative AGS and SMI, was closely related to postoperative short-term and long-term outcomes for HCC patients who underwent DDLT. Graft allocation and clinical decision making may be referred to CAS grade evaluation. ## 1. Introduction HCC is the third leading cause of cancer death worldwide and primarily develops in patients with cirrhosis, especially in eastern and southeastern Asia [1]. At present, prognosis in HCC patients is still a complex challenge, as the majority of them may die due to tumor recurrence or progression. Moreover, liver failure or complications of cirrhosis will seriously threaten their lives [2,3]. Comparing treatment modalities for HCC, liver transplantation (LT) is the best option because it can not only simultaneously remove the tumors and underlying cirrhosis but also eliminate complications, such as liver failure and portal hypertension [4]. Due to strict living donating criteria and complex ethical issues, most HCC patients choose deceased donor livers in China. However, with an increase in the gap between graft supply and demand, to maximize utilization of the available donor pool, comprehensive risk stratification and optimal donor–recipient matching will benefit more from limited resources [5]. Chronic infections with hepatitis B virus and/or hepatitis C virus are the strongest risk factors for HCC. Especially in China, approximately $80\%$ of HCC cases are associated with chronic hepatitis [6]. Increasing evidence has shown that chronic inflammation plays crucial roles in tumor progression, metastasis, and recurrence by altering the tumor microenvironment and destroying immunologic function [7,8,9]. Recently, an increasing number of inflammation-based models have been used to evaluate the prognosis of patients with HCC, such as the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) [9,10,11]. In addition, ALB and GLB, the two major constituents of serum proteins, are considered to play pivotal roles in the inflammatory process. ALB is not only used to monitor nutritional status but also correlated with the systemic inflammatory response by suppressing the activation of cytokines [12,13]. Conversely, GLB participates in immunity and inflammation through the regulation of inflammatory cytokines [14]. Previous studies have shown that the albumin-to-globulin ratio (AGR) is an independent prognostic factor in digestive system cancers, such as colorectal cancer, gastric cancer, and cholangiocarcinoma [15,16]. Similarly, AGS is a novel predictor that reflects the cumulative effect of both ALB and GLB on esophageal squamous cell carcinoma and non-small-cell lung cancer [17,18]. However, no report has clarified the relationship between these indicators and the outcome in patients with HCC after DDLT. The MELD score is the most frequently used method to prioritize patients with end-stage liver disease for liver transplantation, and it can also predict prognosis [19]. Despite its strong predictive value, the MELD score underestimates disease severity in approximately 15–$20\%$ of patients with cirrhosis [20,21]. To compensate for the imperfection of the MELD score, the MELDNa and five-variable MELD score were proposed on the basis of the original MELD score [22,23]. Nevertheless, we still ignored the patient’s physical and nutritional status in concurrent cirrhosis and HCC. Indeed, sarcopenia, characterized by progressive and generalized loss of skeletal muscle mass and strength with increasing age [24], is a common but underappreciated complication of cirrhosis and cancer [25]. Sarcopenia has recently been found to predict waiting list mortality and mortality following liver transplantation [26,27,28] and is associated with posttransplant severe infections or sepsis [29], longer ICU stays, and postoperative hospital stays [30]. Therefore, our study aimed to assess the effects of AGS and SMI on the prognosis of HCC patients after DDLT. Meanwhile, CAS, a novel index from the combination of AGS and SMI, was characterized to evaluate the nutritional and inflammatory status of HCC patients and was analyzed to investigate the influence on long-term outcome in HCC patients who underwent DDLT. ## 2.1. Study Population This study included 221 adult patients who received DDLT from January 2015 to December 2019 at the Liver Surgery and Liver Transplantation Center, West China Hospital (no prisoner’s organs were used for transplantation after 2015 in our center). All subjects over 18 years were pathologically diagnosed with HCC and conformed to the University of California at San Francisco (UCSF) criteria (a solitary lesion no more than 6.5 cm or multiple lesions no more than 3 in number, none of which were larger than 4.5 cm and total tumor size no more than 8 cm in the absence of macrovascular invasion and metastasis). Patients who had liver transplantation for acute liver failure, reduced-sized liver transplantation, or combined multivisceral transplantation were excluded. Patients with allograft nonfunction within hours after revascularization with no discernible cause and leading to retransplantation or death were excluded. Patients who had no complete CT images or medical records were excluded. This study was approved by the ethics committee of the West China Hospital, in accordance with the guidelines of the 1975 Declaration of Helsinki. Informed consent was obtained from patients. ## 2.2. Preoperative Evaluation The demographic evaluation of recipients included age, sex, body mass index (BMI) [weight (kg)/height squared (m2)], and etiology of cirrhosis. Since the US instituted the MELD system in 2002 and soon thereafter, MELD-based liver allocation has been adopted throughout the world. To date, the MELD score is the basis of liver allocation policy in our center. All patients had a laboratory examination including blood tests, liver biochemistries, coagulation function, serum creatinine, serum albumin, and tumor markers, and these examinations were performed every month to update the MELD score and Child–Pugh score. Head, chest, and abdomen CT scans were performed 1 week before LT to assess the tumor characteristics, including the tumor size, tumor number, presence of macrovascular invasion, and distant metastasis. Concerning the protocol of DDLT for HCC patients, two principles were considered: [1] UCSF criteria were adopted for patient selection; [2] if the tumor burden met the Milan criteria (single nodule ≤ 5 cm or 2–3 nodules, each ≤3 cm in diameter without vascular invasion or extrahepatic metastases), the patient could enjoy the MELD score adding policy up to 22 points. The functional status of recipients can be measured by the Karnofsky performance status (KPS), a simple, 11-class scale expressed as a percentage of physical function ranging from $100\%$ (normal, no complaints, no evidence of disease) to $0\%$ (dead) [31], combined with characteristic complications of cirrhosis, ascites, and hepatic encephalopathy. The KPS was classified into three categories according to the patient’s self-care ability. KPS A (scoring 80–$100\%$) could carry out normal activity and work, KPS B (scoring 50–$70\%$) could not work but could live at home and care for personal needs, and KPS C (scoring 0–$40\%$) could not provide self-care. Quality assessment of donor allografts included donor age, sex, steatosis, serum sodium concentration, cold ischemic time (CIT), and warm ischemic time (WIT), which were used to calculate the donor risk index (DRI), a summary metric to quantify liver allograft quality [32]. ## 2.3. Diagnostic Criteria and Definitions The preoperative diagnosis of HCC was based on the criteria defined by the American Association for the Study of Liver Diseases. The diagnosis of HCC was considered reliable when the tumor characteristics were concordant with two imaging techniques, while tumor biopsy was confined to doubtful cases. All surgical complications observed during the first 90 days after DDLT were recorded according to the Clavien–Dindo classification [33] and quantified using the comprehensive complication index [34]. Postoperative infections were diagnosed by positive results from the sampling site. OS was defined as the interval between the date of DDLT and the date of death or the last follow-up until December 2021. RFS was defined as the interval between the date of DDLT and the date of recurrence in transplanted liver or extrahepatic organs when medical tests confirmed. ## 2.4. Nutritional and Inflammation Assessment ALB and GLB are two major components of total proteins in human serum. They are routinely measured in biochemical examination. The AGR was calculated by dividing the ALB level by the GLB level. The optimal cutoff values for ALB, GLB, and AGR were identified using ROC curve analyses. On the basis of a previous study, we defined AGS as follows: patients with both hypoalbuminemia (≤ALB cutoff value) and an elevated GLB level (>GLB cutoff value) were assigned an AGS of 2, whereas those with only one of the two abnormalities were assigned an AGS of 1, and those with normal values for both parameters were assigned an AGS of 0 [17]. An AGS of 1 or 2 was defined as high AGS, while 0 was defined as low AGS. All patients were routinely examined by CT prior to liver transplantation to assess the tumor staging and anatomy of hepatic vessels and biliary ducts. The area of skeletal mass was determined by cross-sectional CT images at the level of the third lumbar vertebra (L3) using Mimics (version 21.0, Materialise NV, Leuven, Belgium). Muscles in the L3 region include the psoas, erector spinae, quadratus lumborum, transversus abdominis, external and internal obliques, and rectus abdominis (Figure 1). SMI was calculated as follows: cross-sectional area of skeletal muscle (cm2)/height squared (m2). It was divided into two groups of low SMI (Figure 1a) and high SMI (Figure 1b) according to the cutoff value of male and female. Then, the CAS grade was defined as follows: patients with both low AGS [0] and high SMI were assigned a CAS of 1, those with both high AGS ($\frac{1}{2}$) and low SMI were assigned a CAS of 3, and the others were assigned a CAS of 2. ## 2.5. Follow-Up Following their discharge, patients visited our outpatient clinic every week for the first 3 months, then every two weeks for 3 to 6 months, and thereafter once a month regularly. The content of rechecking included blood tests, liver and renal biochemistries, tumor markers (alpha-fetoprotein and abnormal prothrombin), blood concentration of tacrolimus (FK506), and transplantation ultrasound. CT and magnetic resonance imaging (MRI), if necessary, were performed. Once tumor recurrence, liver function abnormalities, or other emergencies occurred, patients were readmitted to the hospital for subsequent therapies. ## 2.6. Statistical Analysis All data were collected retrospectively from the institutional electronic database and clinical correspondence. The statistical analyses were performed using SPSS (version 22.0, Chicago, IL, USA), MedCalc (version 15.2.2.0, Ostend, Belgien), and GraphPad Prism (version 8.0, San Diego, CA, USA) software. Continuous variables are presented as the mean ± standard error or median (range), and categorical variables are presented as percentages. Student’s t-test or the Mann–Whitney U test was used to determine the difference in continuous variables between groups, and the chi-squared test or Fisher’s exact test was used for categorical variables, as appropriate. Among CAS groups, we performed the Kruskal–Wallis H test and chi-squared test for continuous variables and categorical variables, followed by the SNK-q test and Bonferroni multiple comparisons test, respectively. The 5 year OS was chosen as the primary endpoint for the survival analyses, and the 5 year RFS was used as the secondary endpoint. ROC curves were applied to determine the optimal cutoff value, as the Youden index attained the maximum value with 2 year survival as the end point. The AUCs were compared between AGS, SMI, and CAS. Survival curves were generated by the Kaplan–Meier method and compared with the log-rank test. Univariate Cox proportional hazard regression was used to identify potentially related factors. Hazard ratios (HR) and $95\%$ confidence intervals (CI) were estimated. The multivariate analysis included all values with $p \leq 0.1$ in the univariable analyses. A two-tailed p-value less than 0.05 was considered statistically significant. ## 3.1. Patient Baseline Characteristics As shown in Table 1, a total of 221 eligible patients were enrolled in the study consecutively and were divided into two groups according to sex. We summarized the demographic characteristics of recipients and donors, laboratory parameters, intraoperative parameters, histological and gross features of tumors, and prognostic outcomes. A total of 187 patients were males ($84.6\%$), the median age was 50 years (range 18–69 years), and the median BMI was 22.7 kg/m2 (range 13.9–33.6 years). Their general status was estimated by KPS on admission, and the median value was $80\%$ (10–$100\%$). Thirty-four patients were females ($15.4\%$), the median age was 50 years (range 21–69 years), and the median BMI was 22.4 kg/m2 (range 15.2–30.9 years). The median KPS was $70\%$ (range 10–$90\%$). The etiologies of liver disease were hepatitis B ($86.6\%$ in males, $76.5\%$ in females), hepatitis C ($4.8\%$ in males, $11.8\%$ in females), alcohol ($5.9\%$ in males, $2.9\%$ in females), and nonalcoholic steatohepatitis ($1.1\%$ in males, $5.9\%$ in females). Among males, 30 patients ($16.0\%$) and 51 patients ($27.3\%$) had concomitant encephalopathy and ascites, respectively. Similarly, five patients ($14.7\%$) and seven patients ($20.6\%$) had concomitant encephalopathy and ascites, respectively, in females. ## 3.2. Clinical Characteristics Related to ALB, GLB and AGR Figure 2 shows the distribution of preoperative ALB, GLB, and AGR levels for patients divided by survival status. A high ALB level was significantly correlated with a benefitted survival outcome ($p \leq 0.001$, Figure 2a). The GLB level had no significant correlation with survival outcome; nevertheless ($p \leq 0.05$, Figure 2b), elevated AGR had a better survival outcome ($p \leq 0.05$, Figure 2c). The optimal cutoff values for ALB, GLB, and AGR were identified to be 39.8 g/L, 28.6 g/L, and 1.47, respectively. Survival curves showed that patients with an AGR >1.47 ($$n = 87$$, $39.4\%$) were associated with greater OS (1, 3, and 5 year OS: $97.7\%$, $88.5\%$, and $76.8\%$ vs. $94\%$, $79.8\%$, and $64.6\%$, $$p \leq 0.034$$, Figure 3a) and RFS (1, 3, and 5- year RFS: $92.7\%$, $83.8\%$ and $80.8\%$ vs. $84.6\%$, $71.5\%$ and $64.1\%$, $$p \leq 0.035$$, Figure 3d) than patients with AGR ≤ 1.47. ## 3.3. Outcome Analyses according to AGS As shown in Table 2, we defined AGS 0 as low AGS and AGS ($\frac{1}{2}$) as high AGS; 60 patients ($27.1\%$) were classified as low AGS, and 161 patients ($72.1\%$) were classified as high AGS. The low AGS group had a higher KPS score ($$p \leq 0.039$$) and lower Child–Pugh score ($$p \leq 0.002$$) and MELD score ($$p \leq 0.037$$) than the high AGS group. Moreover, a decreased rate of encephalopathy, ascites, and serum AFP ≥ 400 ng/mL were observed in patients with low AGS ($$p \leq 0.023$$; $$p \leq 0.048$$; $$p \leq 0.011$$, respectively). The other characteristics, such as recipients’ demographic characteristics, tumor number, total tumor size, differentiation of HCC, and status of microvascular invasion, were comparable between the low and high AGS groups. In addition, the low AGS patients had a lower incidence rate of postoperative infection ($$p \leq 0.011$$) and shorter duration of ICU stay ($$p \leq 0.039$$); considering all complication profiles, the low AGS group’s 90 day comprehensive complication index (CCI) was significantly lower than the high AGS group ($p \leq 0.001$). In addition, patients in the low AGS group had significantly longer OS (1, 3, and 5 year OS: $96.6\%$, $89.8\%$, and $80.2\%$ vs. $95.7\%$, $81.3\%$, and $65.4\%$, $$p \leq 0.024$$, Figure 3b) and RFS (1, 3, and 5 year RFS: $96.6\%$, $88.1\%$, and $84.2\%$ vs. $84.4\%$, $71.7\%$, and $65.9\%$, $$p \leq 0.011$$, Figure 3e). ## 3.4. Outcome Analyses according to SMI According to the optimal cutoff values for SMI in males (43.1 cm2/m2) and females (32.9 cm2/m2). A total of 128 patients ($57.9\%$) were grouped into high SMI, and 93 patients ($42.1\%$) were grouped into low SMI, as shown in Table 2. In the high SMI group, male recipients accounted for a smaller proportion than in the low SMI group ($$p \leq 0.045$$), and BMI was significantly higher than that in the low SMI group ($$p \leq 0.011$$). The high SMI group had higher KPS scores ($p \leq 0.001$), lower serum ammonia levels ($$p \leq 0.044$$), and lower Child–Pugh scores ($p \leq 0.001$) and MELD scores ($$p \leq 0.015$$) than the low SMI group. A significantly decreased rate of encephalopathy and ascites was observed in patients with high SMI ($p \leq 0.001$ and $p \leq 0.001$). The other characteristics were comparable between the two populations. The high SMI group had an overwhelming advantage in short-term outcomes, such as a lower incidence of postoperative infection ($$p \leq 0.001$$), a lower 90 day CCI ($p \leq 0.001$), and a shorter duration of ICU stay ($$p \leq 0.003$$). Meanwhile, the high SMI group had a higher OS (1, 3, and 5 year OS: $97.7\%$, $87.5\%$, and $79.4\%$ vs. $92.4\%$, $77\%$, and $55.4\%$, $$p \leq 0.001$$, Figure 3c) and RFS (1, 3, and 5 year RFS: $95.3\%$, $83.8\%$, and $76.2\%$ vs. $76.5\%$, $64.7\%$, and $61.7\%$, $$p \leq 0.001$$, Figure 3f) than the low SMI group. ## 3.5. Outcome Analyses according to CAS Grade After stratification by CAS grade, 46 patients ($20.8\%$) were classified into CAS grade 1, 96 patients ($43.4\%$) were classified into CAS grade 2, and 79 patients ($35.7\%$) were classified into grade 3 (Table 3). Patients in CAS grade 1 were associated with the significantly lowest percentage of male recipients, encephalopathy, and ascites, the highest KPS score, and the lowest Child–Pugh score and MELD score. Moreover, there was a relatively significant relationship among patients in CAS 1, 2 and 3, with increasing CAS grade, an ascending trend toward postoperative infection, 90 day CCI, and duration of ICU stay. Moreover, after post hoc analysis, we found that the ALB level and 90 day CCI were statistically significant between every two groups. Patients with CAS grade 1 were associated with the greatest OS and RFS, whereas patients with CAS grade 3 had contrary outcomes (1, 3, and 5 year OS for CAS grades 1, 2, and 3: $97.8\%$, $93.4\%$, and $87.9\%$ vs. $96.9\%$, $83.3\%$, and $73.5\%$ vs. $92.3\%$, $76.7\%$, and $53.5\%$, $p \leq 0.001$, Figure 4a) and (1, 3, and 5 year RFS for CAS grades 1, 2, and 3: $95.7\%$, $86.9\%$, and $82.5\%$ vs. $93.6\%$, $82.2\%$, and $70.8\%$ vs. $73.7\%$, $59.6\%$, and $57.9\%$, $$p \leq 0.001$$, Figure 4b). ## 3.6. ROC Curve Analysis and risk Factor Analysis Figure 5 indicates that the CAS had a more accurate identification ability for OS than AGS and SMI (AUC: 0.710 vs. 0.618 and 0.646, respectively) (Figure 5a). Similarly, the AUC of CAS grade (0.700) was greater than that of AGS (0.620) and SMI (0.612) for RFS (Figure 5b). Lastly, our univariable Cox proportional hazards regression model showed a significant relevance of male recipient, NLR > 2.6, Child–Pugh C, MELD score > 20, microvascular invasion and elevated CAS grade with OS (Table 4). The multivariable analysis identified male recipient (HR: 1.824, $95\%$ CI: 1.349–2.502, $$p \leq 0.017$$), Child–Pugh C (HR: 2.045, $95\%$ CI: 1.028–4.426, $$p \leq 0.011$$), MELD score > 20 (HR: 1.984, $95\%$ CI: 1.113–3.026, $$p \leq 0.025$$), CAS grade 2 (HR: 3.045, $95\%$ CI: 1.382–6.896, $$p \leq 0.001$$), and CAS grade 3 (HR: 4.412, $95\%$ CI: 2.117–9.480, $p \leq 0.001$) as independent factors associated with impaired OS. ## 4. Discussion This study comprehensively explored the association of malnutrition with short- and long-term post-DDLT patient survival outcomes by evaluating the CAS grade, which is a novel prognostic marker combined with AGS and SMI. Interestingly, on the basis of our data, the prognostic value of CAS was proven to be more accentuated than that of either alone. The CAS grade reflected the nutritional and inflammatory status of HCC patients simultaneously. As an independent prognostic risk factor for OS and RFS in HCC patients, CAS grade had higher accuracy in predicting OS and RFS than AGS and SMI. Chronic inflammation is a critical contributor to tumor development, proliferation, and metastasis and is also related to the risk of death and recurrence among malignant patients after surgery [7,8,9]. Serum ALB, produced by the liver, reflects nutritional status and participates in the body’s natural defense activities. Furthermore, low serum ALB levels were also reported to be related to chronic inflammation, which is not only associated with a reduction in circulating albumin concentrations but also probably through increased degradation, especially in patients with viral hepatitis cirrhosis [35]. GLB, produced by immune organs, is a major component of systemic inflammation and comprises numerous proinflammatory proteins. High levels of GLB resulting from immunoglobulins and acute-phase protein aggregation may be associated with the malignant microenvironment [36]. Zhang et al. found that a high GLB level was significantly related to high AFP, cirrhosis, major tumor size, and poor Edmondson grade of the tumor [37]. Although ALB and GLB are important predictive factors in many malignant tumors, their serum levels are affected by many factors, such as stress response, liver insufficiency, and alteration of body fluid volume. Therefore, their clinical value for predicting cancer patient prognosis is limited. Then, the AGR, defined as ALB (g/L)/GLB (g/L), proved to be an independent prognostic factor in digestive system cancers, upper-tract urothelial carcinoma, and oral squamous cell carcinoma [7,15,38]. Consistent with our results, patients with an AGR > 1.47 had a better survival outcome than those with an AGR ≤ 1.47 (Figure 3a,d). Meanwhile, on the basis of ALB, GLB, and AGR, the AGS has been proposed as another novel model to predict the prognosis of cancer. Li et al. compared the prognostic value of AGR and AGS in a cohort study of 458 esophageal squamous cell carcinoma (ESCC) patients and concluded that AGS outperformed AGR as a prognostic factor in ESCC [18]. Later, it was also shown that AGS could reflect the OS and RFS of non-small-cell lung cancer and cholangiocarcinoma patents, and that the predictive performance was better than that of AGR [16,17]. Similarly, our study initially confirmed this perspective in HCC patients who underwent DDLT, and the AGS was significantly related to preoperative general status, serum AFP level, Child–Pugh score, and MELD score. Additionally, the AGS showed a great capacity for predicting the long-term survival outcome for HCC patients. Malnutrition is a common comorbidity in patients with liver cirrhosis. In our study population, $81\%$ of patients had liver cirrhosis, which makes most HCC patients have no chance of achieving anatomical resection. Sarcopenia, a complex syndrome characterized by progressive decreases in skeletal muscle mass and function, has now been integrated into the definition of malnutrition. To date, Chinese diagnostic criteria for sarcopenia based on the L3-SMI have not been established [39]. Because the etiology of HCC and the characteristics of cirrhotic patients are markedly different in China than in other districts, we set up the cutoff value of SMI in a Chinese cohort with HCC after DDLT (male: 43.1 cm2/m2, female: 32.9 cm2/m2). The cutoff values were smaller than those determined by a North American expert (male: 50 cm2/m2, female: 39 cm2/m2) [40]. Some scholars showed that sarcopenia has a negative effect on long-term prognosis following liver transplantation [26,27,28]. However, others argued that sarcopenia was not associated with impaired survival after liver transplantation [30]. Our study showed that low SMI was a poor prognostic indicator in terms of both OS and RFS. The controversy may be attributed to differences in ethnicity, selection bias of the study populations, and the inconsistent definition of sarcopenia. Currently, cross-sectional imaging studies are the gold standard for quantitating skeletal muscle. These measurements are not influenced by the presence of ascites or edema, especially in our study populations [21]. L3-SMI, as the optimal parameter to assess sarcopenia, has been shown to be the best correlation with whole-body muscle mass [30]. Interestingly, in our study, there was no apparent relationship in BMI between low SMI and high SMI. Similarly, Judith et al. deemed that sarcopenia is not exclusively present in patients with a low BMI and may be present as an occult condition in HCC patients with any BMI [25]. Therefore, a surgeon’s decision is fraught with the subjectivity of health status, which some clinicians call “the eyeball test” [26]. Loss of muscle mass can be precipitated by a superimposed pathological condition, such as cancer or chronic diseases [41]. The pathogenesis of sarcopenia includes systemic inflammation, myostatin signaling, and insulin resistance [16,41]. In addition, several mechanisms related to cirrhosis likely contribute to muscle alterations, such as hypoalbuminemia, hepatocyte dysfunction, and hyperammonemia [41]. Muscle acts as a metabolic partner for the liver; in turn, decreased muscle mass worsens hyperammonemia. Ammonia-lowering therapies have been shown to reverse skeletal muscle alterations in hyperammonemic rodent models [42]. Therefore, lowering ammonia prior to surgery may be beneficial for a better prognosis. To comprehensively evaluate the impact of nutritional status and inflammatory environment on the prognosis of DDLT in HCC patients, given the prognostic value of AGS and SMI, a novel index (CAS grade) was introduced. It exhibits greater correlations with OS and RFS than each alone. Male recipient, a dependent risk factor for poor survival outcome, occupied an increasing percentage with CAS grade elevation. One explanation is that there is a clear sex predisposition for sarcopenia in cirrhosis, being more prevalent in males than in female patients. Fluctuations in hormone levels lead to more and faster loss of skeletal muscle [27]. The other explanation is that males have significantly more visceral fat, whereas females have more subcutaneous fat. Subcutaneous adipose tissue is the major producer of leptin, the hormone that regulates insulin sensitivity, glucose and lipid metabolism, and the immune response [43]. KPS scoring, as an assessment of the overall performance status of patients, is significantly related to CAS grade. Despite its subjectivity, Paul et al. believed that the KPS is perhaps a reflection of the overall physical and mental status of patients with end-stage liver disease that could not be quantified by objective parameters [44]. However, the KPS score may lack reliability in this study, where the large difference in the presence of encephalopathy and ascites between different CAS grades could influence the KPS score assessment. The MELD score and Child–Pugh score are the most widely used for evaluating donor allocation and liver function, respectively. Specifically, they play important roles in predicting prognosis for HCC patients and are dependent risk factors for poor outcome. Despite the irrefutable benefits of the MELD score, the limitations of MELD score have been recognized, and there are ongoing attempts to improve it [21,30]. One of the major limitations of the MELD score is the lack of evaluation of the nutritional and functional status of patients on the waiting list. Furthermore, the present data suggest that the relationship between low muscle mass and poor outcome is independent of the MELD score [15,41]. This result is consistent with our findings. Tandon et al. showed that sarcopenic patients with a low MELD score had a similar outcome compared with patients with a high MELD score with or without sarcopenia [45]. In addition, a Japanese study also included measures of skeletal muscle in the MELD score (Muscle-MELD score) to predict mortality after living donor liver transplantation (LDLT) [46]. Therefore, enrolling the CAS grade in the MELD score may be used to more accurately select patients in the waiting list and allocate organs in the future. In other words, HCC patients who conformed to the UCSF criteria concurrent with CAS grade 0 had priority to receive the graft in terms of utilization value. The identification of patients listed for LT who are susceptible to increased postoperative morbidity and mortality is pivotal. We comprehensively analyzed the impact of CAS on postoperative complications by 90-day CCI, finding that CAS grade 3 is significantly associated with poorer short-term outcomes, especially in the occurrence of infection episodes. Infectious complications are significant sources of mortality for liver transplant recipients. Krell et al. claimed that increased vulnerability to infection was associated with sarcopenia, but the potential influence of sarcopenia on infection-related outcomes deserves further investigation [29]. Certainly, this work must be considered within the context of its limitations. Firstly, we reported on a retrospective study with a cohort of patients from a single center. Future prospective studies should include a wider ethnicity and multiple institutions so as to set the optimized cutoffs for male and female in the larger population. Secondly, selection bias for patient inclusion was present in the study group. Patients with allograft nonfunction and no discernible cause leading to retransplantation or death were excluded. Thirdly, ALB and GLB were the latest laboratory tests prior to the surgical procedure, and they might not reflect the actual situation due to albumin infusion. Fourthly, we need to consider whether our cutoff values for ALB, GLB, and SMI were adequate to define the CAS grade in a slightly insufficient population and the deficiency for using alone CAS as a prognostic parameter in HCC patients who underwent DDLT. Lastly, we had no comprehensive data about the patients’ mobility after surgery; hence, we could not objectively evaluate their self-care ability. Until now, there has been no multicenter prospective study of a Chinese cohort to provide a definition of CAS grade. Notwithstanding the aforementioned limitations. To the best of our knowledge, this was the first study to integrate preoperative ALB, GLB, and skeletal muscle mass to predict short- and long-term outcomes of HCC patients who underwent DDLT. Assessing CAS grade in possible LT candidates can help to predict posttransplant outcomes. Therefore, CAS grade can be supplemented in the process of recipient selection and organ allocation. ## 5. Conclusions The present study provided a novel prognostic index combining preoperative AGS and SMI that was closely related to postoperative short-term and long-term outcomes for HCC patients who underwent DDLT. Performing CAS grade evaluation may be used for clinical decision making. 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--- title: A Literature Review of Simulation-Based Nursing Education in Korea authors: - Sumee Oh - Jungmin Park journal: Nursing Reports year: 2023 pmcid: PMC10051872 doi: 10.3390/nursrep13010046 license: CC BY 4.0 --- # A Literature Review of Simulation-Based Nursing Education in Korea ## Abstract This study reviewed the papers that studied the effect of simulation nursing education in the nursing field and examined the trend of simulation nursing education for nursing college students in Korea. Background: Simulation-based education started receiving attention as a pedagogical method in order to provide medical service of high quality in an ethical and safe environment. This has been of great importance during the coronavirus disease 2019 global pandemic. This literature review was conducted to suggest a direction for simulation-based nursing education in Korea. Methods: For literature searches, the authors used the following search terms in the Web of Science, CINAHL, Scopus, PubMed—‘utilization’, ‘simulation,’ ‘nursing student’, ‘nursing education’. A final search was conducted on 6 January 2021. The materials for this study were collected through literature searches according to the PRISMA guidelines. Results: 25 papers were selected as the final literature for analysis. The study was conducted for 48 percent of senior students in nursing college students in Korea ($$n = 12$$). High fidelity (HF) as the simulation type was 44 percent ($$n = 11$$). The simulation education subjects were composed of 52 percent adult health nursing ($$n = 13$$). According to educational goals described by Benzamine Bloom [1956], $90\%$ in the psychomotor domain is considered a positive learning achievement. Conclusions: Effectiveness in the psychomotor domain through simulation-based training is correlated with expert nursing. It is essential to develop a systematic debriefing model and methods to evaluate performance and learning in the short- and long-term to expand the effectiveness of simulation-based education in nursing. ## 1. Introduction Both the increasing severity of a patient’s condition and the complicated and changing medical environment require high-quality medical services to ensure the best patient outcomes [1]. There is a growing need for good-quality educational courses in nursing colleges to educate nursing experts who are equipped with proper certifications. Such nurses who receive an advanced nursing education can help reduce the delays in recovery and damaging side effects for patients, thereby preventing failure during treatment. By reducing mortality rates, nurses will be able to play a vital role in treatment and even patient satisfaction by helping patients and their families avoid unnecessary medical costs. It is difficult even for well-educated nurses to be fully prepared for nursing [2]. With the recent increase in the awareness of patients’ rights and professional ethics of healthcare professionals, there are limited opportunities for gaining practical experience in real-world clinical settings [3]. Therefore, changes are needed in nursing education to enable students to acquire the necessary knowledge and skills [4]. Owing to the limitations of clinical practice, simulation-based education has become a promising alternative, enabling nursing professionals and students to gain and develop skills without facing patients directly. Efforts have been made to ensure that simulation-based education provides good-quality and effective education [5]. The outbreak of coronavirus disease 2019 (COVID-19) caused enormous damage to learning opportunities for students in the medical environment. Isolation, social distancing, and society’s need for prepared clinical nurses created major challenges for nursing education [6]. The appearance of new infective diseases, such as COVID-19 and Middle East respiratory syndrome, has created the requirement for new pedagogical methods for nurses instead of the traditional methods in practice [7,8]. Simulation-based education applies a patient care scenario in a safe educational environment, which will likely reappear in clinical settings, to help nurses gain skills and experience managing the situation, thereby reducing error in real-world clinical situations [9]. Nursing students enjoy the simulations based on feedback to increase their self-confidence and satisfaction [10]. In domestic nursing education, learning methods that use standardized patients (SPs) as a teaching method have been adopted since 2001 [11]. Simulation-based education started in 2006 and has increased rapidly since then [12]. The Korea Accreditation Board of Nursing Education established a requirement for 1000 h of simulation-based practical experience per year for training expert nurses as part of the nursing education accreditation evaluation [13]. Literature reviews were conducted to determine how simulation-based education has been used in Korea for nurses and nursing students from 2014 to 2020 [12,14]. With the increase in simulation-based practical education in the curriculum of nursing colleges, it is essential to review the effectiveness and the direction of simulation-based education in nursing. Hence, this study will suggest directions for simulation-based nursing education in Korea after understanding trends and the effect of this type of education on the field. ## 2.1. Aim This study examines reviews conducted on simulation-based education as a subject in the national curriculum for nursing students in Korea for trends and outcomes. ## 2.2. Design A literature review was conducted to suggest directions for simulation-based nursing education in Korea. ## 2.3. Search Methods The materials for this work were collected according to the PRISMA guidelines [15]. This work reviewed the effect of simulation nursing education on the nursing field and identified the trend of simulation nursing education for nursing college students in Korea. For the literature searches, the following search terms were entered in the Web of Science, CINAHL, Scopus, PubMed—‘utilization’, ‘simulation’, ‘nursing student’, ‘nursing education’. A final search was conducted on 6 January 2021. Based on the standard for certification from the Korean Accreditation Board of Nursing Education in 2014, practical simulation experience accounts for $10\%$ of the total number of clinical practice hours for the graduation. These reviewed papers were limited to those published between 2014 and January 2021 and included a total of 5549 papers. Of these, 124 were excluded because they were dissertations, and 2723 were excluded because they were duplicated papers. Other bases for exclusion were papers that excluded clinic nurses or included overseas nursing college students, research conducted with the other students, simulation theory development studies, simulation education program evaluation, and simulation conception analyses. Finally, 25 papers were selected as the final literature for analysis (Figure 1). ## 2.4. Material Analysis Method General features related to simulation, measured variables, and results in the selected twenty-five papers as study objects were analysed. The publication year of the study, the study subject, and study design type were analysed as general features. Other features were the simulation type and subject, as well as measured variables and the effects of the research. The selected papers were noted for acquiring high study quality and were reviewed in academic journals. The study collection and data extraction process was reviewed and finally agreed upon by two researchers through several meetings; there were no disagreements. ## 3.1. Literature Selection The goals and design, measured variables, mediation, and results of the selected simulation studies for Korean nursing college students appear in Table 1. ## 3.2. Study Design of Simulation-Based Education Studies General features of simulation-based studies conducted since 2014 on Korean nursing students as subjects appear in Table 2. Simulation-based nursing education studies in Korea were confirmed to comprise seven studies ($28\%$) from 2014 to 2015, eight studies ($32\%$) from 2016 to 2017, six studies ($24\%$) from 2018 to 2019, and four studies ($16\%$) in 2020. There have been no studies conducted on the curriculum for first year students of nursing colleges. The curriculum for simulation-based nursing education for students ranging from sophomores to junior year students was confirmed to include 13 studies ($52\%$) and 12 studies ($48\%$) for senior year students. Random-contrast experimental studies were part of 6 papers ($24\%$), while those featuring a single group comprised 8 studies ($32\%$); 11 studies featured similar control groups ($44\%$). The analysis results for simulation relational variables appear in Table 3. The simulation type was high fidelity (HF) in 11 cases ($44\%$), standardized patient in 2 cases ($8\%$), role-play (RP) in 5 cases ($20\%$), low fidelity (LF) in 3 cases ($12\%$), HF and SP in 1 case ($4\%$), LF and SP in 1 case ($4\%$), virtual reality (VR) and HF in 1 case ($4\%$), and a Web-based study of HF in 1 case ($4\%$). The analysis results categorized by the simulation subject courses of the papers appear in Table 4. Adult health nursing was analysed in 13 studies ($52\%$), pediatric nursing was examined in 6 studies ($24\%$), maternity nursing in 2 studies ($8\%$), mental health nursing in 1 study ($4\%$), emergency nursing in 2 studies ($8\%$), and other research in 1 section ($4\%$). ## 3.3. A Related Measurement Variable and Results of Simulation-Based Education Research According to educational goals described by Benzamine–Bloom [1956], the education goal classification areas were divided into cognitive, affective, and psychomotor domains (Table 5) [41,42]. The measurement variables of the cognitive domain were apprehension (one case), clinical judgment (three cases), communication ability (two cases), communication clarity (three cases), critical thinking skills (seven cases), knowledge (nine cases), learning effect (one case), metacognition (two cases), and problem-solving ability (three cases). The measurement variables of the affective domain were attitude (8 cases), collective (team) efficacy (2 cases), interest (1 case), perception (2 cases), satisfaction (10 cases), self-assertiveness (1 case), self-confidence (6 cases), self-efficacy (3 cases), self-leadership (1 case), difficulty (1 case), and stress (3 cases). The psychomotor domain consisted of skill performance (three cases), critical performance (three cases), confidence in performance (one case), clinical competency skill (one case), and practice (one case). ## 4. Discussion Simulation provides a safe learning environment for the learner to develop the skills and behaviours necessary for effective nursing practice [43]. In addition, it improves clinical skills, reinforces learning through practiced actions,and increases self-confidence [44]. Thus, after 2014 when a certification evaluation standard of the Korea Accreditation Board of nursing education had been implemented, research on the effectiveness of simulation-based education has been continuously progressing. However, the significance of simulation-based education has eluded national nursing education. An examination of the simulation-based curriculum revealed that while simulation-based subjects were included in the curriculum for sophomores and juniors, they carried more weight for seniors. One of the goals of simulation-based education is to equip nurses with the capacity to handle various situations in clinical settings [45,46]. Additionally, simulation-based education has been a crucial alternative to supplement clinical field practice during the pandemic. A study of a similar experiment by a contrast group revealed the most important weight in eleven elements ($44\%$). Sample size justification was checked for all except four elements in 21 research projects. Except for one element, 24 elements appeared in instrument validation, demonstrating that verified invalidity changed the results. However, as the method used by Kim et al. is not valid, the results must be interpreted carefully. In a study containing 11 elements ($44\%$), HF was the most common type of simulation. High-fidelity simulation (HFS) simulates potentially far deeper cognition by having the learner participate in the learning. In addition, HFS, by providing the experience of high concentration, has been recognized as an effective learning method for medicine. Another study mixed more than two types of simulations. Combining more than two types of methods helps understand complicated clinical fields. For effective simulation-based education, of student learning was assessed through structured self-examination and feedback [47]. Due to the increasing importance of debriefing, a simulation course was implemented by including debriefing in 19 research studies ($76\%$). However, we lack a standardized debriefing model; one must be developed and applied for more effective simulation-based education. One study to compare with this study notes that simulation-based education has been expanding in other areas, such as pediatric, maternity, and emergency nursing [48]. However, this study can verify that adult health nursing comprises 13 studies ($52\%$), accounting for the most weight [49,50]. The frequency of measuring knowledge was the highest, with a positive result of $70\%$ in the evaluation area, which is related to the cognitive domain [42]. In the affective domain, the frequency of evaluating satisfaction was the highest and showed a positive result of $70\%$ [42]. Simulation training in most nursing courses covers pediatric, adult, mental health, and maternal nursing [51]. Simulation-based education satisfies the criteria of a cognitive domain similar to a traditional learning method and meets the learning needs of students in the affective domain. Nonetheless, the evaluation method of the cognitive and affective domains is the most important assessment, which can take place through a survey using self-reporting forms. To achieve effective learning goals, it is important to implement various methods of evaluation. A positive learning achievement of $90\%$ in the psychomotor domain implied that the lessons learned from simulation could be re-enacted in the clinical field. Additionally, through repeated education with increasing skill levels, the psychomotor domain showed the best correspondence to the goals of simulation-based education as a learning strategy for increasing clinical competency [52,53,54]. An area evaluation of education goal classification by Bloom showed a similar tendency in an HF precedence study, which likewise showed the outcome of qualified increase with higher levels of thinking [42]. Simulation-based education is a positive learning method for clinical judgment training and critical thinking, offering a safe environment for improving nursing knowledge and competency. Moreover, it is effective in removing the anxiety of the learner and encouraging teamwork [9,55,56]. Therefore, it is essential to develop simulation-based education that uses various themes. It is also crucial to develop methods to estimate the effectiveness of simulation-based education in the short- and long-term. Simulation-based nursing education should expand from the existing nursing college curriculum and work to reach more nursing students and professionals. Finally, a change in instruction methods can play an important role in nursing education. ## 5. Conclusions Due to an increase in the severity of disease, the significance of simulation-based nursing education is expanding gradually with the increasing need for skilled expert nurses. Simulation-based education has been continuously progressing in recent years. However, simulation-based nursing education has been restricted to senior students. The simulations have concentrated on adult health nursing. In addition, there is either no mention of debriefing in simulation-based nursing education, or the debriefing is deficient. Further, effectiveness in the psychomotor domain was identified as the highest expert nursing skill that can be developed through simulation-based education. To improve the educational effectiveness in the psychomotor domain through simulation learning, we suggest that the learning participants should be expanded from seniors to juniors. 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--- title: Oral Administration of Chaetoceros gracilis—A Marine Microalga—Alleviates Hepatic Lipid Accumulation in Rats Fed a High-Sucrose and Cholesterol-Containing Diet authors: - Bungo Shirouchi - Yuri Kawahara - Yuka Kutsuna - Mina Higuchi - Mai Okumura - Sarasa Mitsuta - Norio Nagao - Kazunari Tanaka journal: Metabolites year: 2023 pmcid: PMC10051878 doi: 10.3390/metabo13030436 license: CC BY 4.0 --- # Oral Administration of Chaetoceros gracilis—A Marine Microalga—Alleviates Hepatic Lipid Accumulation in Rats Fed a High-Sucrose and Cholesterol-Containing Diet ## Abstract Microalgae are attracting attention as a next-generation alternative source of protein and essential fatty acids that do not consume large amounts of water or land. Chaetoceros gracilis (C. gracilis)—a marine microalga—is rich in proteins, fucoxanthin, and eicosapentaenoic acid (EPA). Growing evidence indicates that dietary fucoxanthin and EPA have beneficial effects in humans. However, none of these studies have shown that dietary C. gracilis has beneficial effects in mammals. In this study, we investigated the effects of dietary C. gracilis on lipid abnormalities in Sprague-Dawley rats fed a high-sucrose cholesterol-containing diet. Dried C. gracilis was added to the control diet at a final dose of 2 or $5\%$ (w/w). After four weeks, the soleus muscle weights were found to be dose-responsive to C. gracilis and showed a tendency to increase. The hepatic triglyceride and total cholesterol levels were significantly reduced by C. gracilis feeding compared to those in the control group. The activities of FAS and G6PDH, which are related to fatty acid de novo synthesis, were found to be dose-responsive to C. gracilis and tended to decrease. The hepatic glycerol content was also significantly decreased by C. gracilis feeding, and the serum HDL cholesterol levels were significantly increased, whereas the serum levels of cholesterol absorption markers (i.e., campesterol and β-sitosterol) and the hepatic mRNA levels of Scarb1 were significantly decreased. Water-soluble metabolite analysis showed that the muscular contents of several amino acids, including leucine, were significantly increased by C. gracilis feeding. The tendency toward an increase in the weight of the soleus muscle as a result of C. gracilis feeding may be due to the enhancement of muscle protein synthesis centered on leucine. Collectively, these results show that the oral administration of C. gracilis alleviates hepatic lipid accumulation in rats fed a high-sucrose and cholesterol-containing diet, indicating the potential use of C. gracilis as a food resource. ## 1. Introduction Numerous algae species are found worldwide and are classified into two groups—macroalgae (also known as seaweeds) and microalgae—depending on the complexity of their biological organization [1]. Microalgae are microscopic, unicellular, and photosynthetic organisms distributed in both freshwater and marine ecosystems [1,2]. They have attracted attention as promising candidates for the industrial exploitation of food and biofuels due to their high productivity per unit area compared to agricultural crops, their high adaptability to various cultivation conditions, and their capacity to grow rapidly [1,2]. From the perspective of sustainable food supply and security, microalgae are also attracting attention as next-generation alternative sources of protein and essential fatty acids that do not require the consumption of large amounts of water or land [2]. Currently, the majority of microalgae dominating the global market are freshwater species that are inexpensive and easy to grow, such as Spirulina and Chlorella, which can be produced in open ponds with little risk of contamination [3]. On the other hand, marine microalgae species are known to be efficient producers of bioactive compounds, such as carotenoids and n-3 polyunsaturated fatty acids [4]. Compared to fish oils, marine microalgae oils have several advantages, such as no unpleasant smell, less contamination with heavy metals, and no variations in fatty acid composition under controlled cultivation [5]. In Commission Implementing Regulation (EU) $\frac{2018}{1023}$, the European Union’s list of novel foods was established to include several microalgae, including dried biomass and extracted oils [6]. Among the marine microalgae, Chaetoceros gracilis (C. gracilis) is classified as a diatom and is characterized by high protein, fucoxanthin, and eicosapentaenoic acid (EPA) contents, in addition to photosynthetic pigments such as chlorophyll a, c1, and c2 [4,7,8]. Fucoxanthin is a non-provitamin-A carotenoid that belongs to the xanthophyll family and has an allene structure. Fucoxanthin has been reported to have anti-proliferative and apoptosis-inducing effects on cancer cells [9,10], an anti-obesity effect [11], and an anti-diabetic effect [12,13], suggesting that the allene structure is involved in the expression of physiological functions. EPA is an essential fatty acid that humans are unable to produce and has both a lipid-lowering effect and an anti-inflammatory effect, leading to a lower risk of cardiovascular diseases [14,15]. Although C. gracilis is not currently included in the European Union’s list of novel foods, the intake of C. gracilis—which is rich in these bioactive compounds—is expected to have these beneficial effects. To the best of our knowledge, no studies have reported the effects of C. gracilis as a dietary supplement against lipid abnormalities. Therefore, to explore the potential use of C. gracilis as a food resource, the present study examines the effects of dietary C. gracilis on lipid abnormalities in rats fed a high-sucrose, cholesterol-containing diet. ## 2.1. Materials C. gracilis was cultured, as described previously [7], at Blue Scientific Shinkamigoto Co., Ltd. (Nagasaki, Japan). Cultured C. gracilis was centrifuged at 7000 rpm at 25 °C at a flow rate of 0.8 L/min using a continuous high-speed centrifuge (H-660 type; KOKUSAN Co., Ltd., Saitama, Japan). Separated C. gracilis was freeze-dried for 3 days using a freeze dryer (EYELA FDU-1110; Tokyo Rikakikai Co., Ltd., Tokyo, Japan) and then stored at −20 °C until use. The nutritional composition of C. gracilis was analyzed by the Institute of Food Hygiene, the Nagasaki Food Hygiene Association, and the Food and Environment Research Center (Nagasaki, Japan) (Table 1). The compositions of amino acids [16] and fatty acids [17] in C. gracilis were also analyzed by the aforementioned institute. Their compositions are shown in Table S1 and Table S2, respectively. The pigments in C. gracilis were analyzed using a liquid chromatography mass spectrometer (LCMS), as previously described [7], and determined to be as follows (per g dry weight): 15.2 mg chlorophyll a, 5.73 mg chlorophyll c1, 0.868 mg chlorophyll c2, 11.8 mg fucoxanthin, 0.650 mg diadinoxanthin, and 0.455 mg diatoxanthin. ## 2.2. Animals and Diets All animal experiments were conducted in accordance with the Guidelines for Animal Experiments of University of Nagasaki, Siebold, and Law no. 105 and Notification no. 6 of the government of Japan. The animal protocol used in this study was approved by the Institutional Review Board of University of Nagasaki, Siebold (authorization no. R02-12). Five-week-old male Sprague-Dawley rats (Jcl:SD) were purchased from CLEA Japan Inc. (Osaka, Japan). The rats were housed individually in metal cages in an air-conditioned room at 22 ± 1 °C and 55 ± $5\%$ humidity under a 12 h light-dark cycle. After a one-week adaptation period on a powder chow diet (CE-2; CLEA Japan, Inc.), 19 rats were assigned to one of three groups ($$n = 6$$–7/group). The experimental diets were prepared according to the AIN-76 formula [18] with several modifications. Dried C. gracilis was added to the control diet at a final dose of 2 or $5\%$ (w/w). The protein, fat, and other components (i.e., carbohydrate, ash, moisture, and sodium) in the diets containing C. gracilis were adjusted with casein, corn oil, and sucrose, respectively, to match the control diet. Diets containing high sucrose and cholesterol levels were used to induce lipid abnormalities. Further details regarding the composition of the experimental diets can be found in Table 2. The rats were provided free access to food and water for four weeks. Then, their feces were collected over a period of 48 h at the end of the experiment. At the end of the four-week feeding period and after a six-hour starvation period, the rats were euthanized by decapitation. To obtain serum, blood was incubated at room temperature for 30 min and then centrifuged at 1200× g for 15 min at 4 °C. The liver, soleus muscle, and abdominal (epididymal, perirenal, and mesenteric) white adipose tissue (WAT) and brown adipose tissue were excised immediately and weighed within 4 h. The collected samples were stored at −80 °C until further analysis. ## 2.3. Measurement of Serum Biochemical Parameters The serum levels of triglycerides (TG), total cholesterol, phospholipids (PL), non-esterified fatty acids (NEFAs), glucose, and alanine aminotransferase (ALT) were measured using commercial enzyme assay kits (TG E-test Wako, Cholesterol E-test Wako, Phospholipid C-test Wako, NEFA C-test Wako, Glucose CII-test Wako, and Transaminase CII-test Wako; FUJIFILM Wako Pure Chemical Co., Osaka, Japan). Serum high-density lipoprotein (HDL) fractions were separated as described previously [19]. The serum cholesterol levels in the HDL fraction were measured using a commercial kit (Cholesterol E-test; Wako). The serum non-HDL cholesterol levels were calculated as the difference between the total cholesterol and HDL cholesterol levels. The serum levels of C-peptide, insulin, and adiponectin were measured using commercial rat ELISA kits (LBIS rat C-peptide ELISA kit and LBIS rat insulin ELISA kit; Shibayagi, Gunma, Japan; mouse/rat adiponectin ELISA kit; Otsuka Pharmaceutical, Tokyo, Japan). ## 2.4. Measurement of Triglycerides, Cholesterol, Phospholipids, and Glycogen Contents in the Liver Total lipids from the liver were extracted using the Bligh and Dyer method, with some modifications, as described previously [20]. The extracted lipids were then dissolved in 2-propanol. The hepatic TG and total cholesterol contents were measured using commercial kits (TG E-test Wako and Cholesterol E-test Wako) [21]. The hepatic phospholipid content was measured according to the method described by Rouser et al. [ 22]. The hepatic glycogen content was measured according to the method described by Lo et al. [ 23]. ## 2.5. Assays for Hepatic Enzyme Activities The activities of fatty acid synthase (FAS), malic enzyme (ME), and glucose-6-phosphate dehydrogenase (G6PDH) in the cytosolic fraction, along with that of carnitine palmitoyltransferase (CPT) in the mitochondrial fraction, were determined as previously described [24]. The protein concentration of each fraction was determined according to the method described by Lowry et al. [ 25], using bovine serum albumin as the standard. ## 2.6. Measurement of Serum Steroid Levels Biomarkers related to cholesterol metabolism—such as lathosterol, campesterol, and β-sitosterol [26,27]—in serum were measured by a gas chromatography-mass spectrometry (GC-MS) system using the Shimadzu GCMS-QP2010 Ultra (Shimadzu Corporation, Kyoto, Japan) equipped with an InertCap 5MS/NP capillary column (30 m × 0.25 mm i.d., 0.25 µm thickness, GL Sciences Inc., Tokyo, Japan) and using 5α-cholestane (Cayman Chemical Company, MI, USA) as an internal standard. Briefly, 250 µL of serum was added to 25 µg of 5α-cholestane. Then, the samples were saponified with ethanolic KOH and the steroids were extracted. The extracted steroids were converted to trimethylsilyl (TMS) ethers using the TMS derivatization reagent (N,O-Bis(trimethylsilyl)trifluoroacetamide (BSTFA)-trimethylchlorosilane (TMCS), (99:1); Tokyo Chemical Industry Co., Ltd., Tokyo, Japan) before injection into the GC-MS system. The following program was applied using helium as a carrier gas at a flow rate of 1.08 mL/min: 180 °C for 1 min, from 180 °C to 250 °C (20 °C/min), from 250 °C to 290 °C (5 °C/min), and 290 °C for 17.5 min. The total run time was 30 min. The injector was operated at a split ratio of 1:30 and was maintained at 300 °C. The interface temperature was 250 °C. The ion source temperature was 290 °C. The mass spectrometer was operated in the electron impact (EI) mode (70 eV). The mass scan range was 35–700 m/z. ## 2.7. Analysis of Hepatic mRNA Levels Total RNA was extracted from frozen liver tissue using RNAzol® RT reagent (Molecular Research Center, Inc., Cincinnati, OH, USA) with 4-bromoanisole (Molecular Research Center, Inc.) and converted to cDNA using PrimeScript™ RT Master Mix (Perfect Real Time) (Takara Bio Inc., Shiga, Japan), according to the manufacturer’s instructions. Polymerase chain reaction (PCR) amplification was performed in a final volume of 20 µL, which contained SYBR Green (THUNDERBIRD® SYBR® qPCR Mix; Toyobo Co., Ltd., Osaka, Japan), 0.3 µM of each primer (Fasmac Co., Ltd., Kanagawa, Japan), and 20 ng of cDNA, using a real-time PCR system (LightCycler®96; Nippon Genetics Co., Ltd., Tokyo, Japan). The reaction conditions were as follows: hot start at 95 °C for 60 s, followed by 45 cycles of denaturation at 95 °C for 15 s, and annealing/extension at 60 °C for 45 s. The relative mRNA levels were determined using the ΔΔCT method [28] using ribosomal protein L4 (Rpl4) as the housekeeping gene. The sequences of the primers used in this study are listed in Table S3. ## 2.8. Analysis of Water-Soluble Metabolites in the Liver and Soleus Muscle (Non-Target Metabolome Analysis) Water-soluble metabolites in the liver and soleus muscle of rats in the two groups (control group and $5\%$Chaeto group) were analyzed according to the protocol described by Tsugawa et al. [ 29], with some modifications. Prior to metabolomic analysis, frozen liver (20 mg) or soleus muscle (50 mg) was homogenized using a ShakeMan 6 (Bio Medical Science, Tokyo, Japan) with zirconia beads. Homogenized samples were mixed with 250 µL of mixed solvent (methanol–H2O–chloroform = 5:2:2) and 10 µL of an internal standard solution (0.5 mg/mL) (2-isopropylmalic acid; Sigma-Aldrich Co., MO, USA). After vortexing, the samples were shaken using a shaking apparatus at 37 °C for 30 min. After centrifugation at 16,000× g and 4 °C for 3 min, the supernatants (180 µL) were collected, placed in new microtubes with 200 µL of H2O, and mixed using a vortex. The tubes were centrifuged at 16,000× g at 4 °C for 3 min. The resulting supernatants (250 µL) were collected into new microtubes for analysis. To prepare quality control (QC) samples, 50 µL of each sample was mixed and dispensed into new tubes (200 µL/microtube). The analysis and QC samples were condensed using a centrifugal evaporator (EYELA CVE-2200; Tokyo Rikakikai Co., Ltd.) with a cold trap (EYELA UT-1010; Tokyo Rikakikai Co., Ltd.) at room temperature until the solvent evaporated. Methoxyamine hydrochloride (Sigma-Aldrich Co.) in anhydrous pyridine (20 mg/mL) was added to each tube, mixed using a vortex, and sonicated in an ice-cold water bath for 20 min with an ultrasonic cleaner. The mixture was shaken using a shaking apparatus for 90 min at 30 °C for oxidation. Next, 30 µL of N-methyl-N-trimethylsilyltrifluoroacetamine (MSTFA; GL Sciences Inc., Tokyo, Japan) was added to each tube and shaken with a shaking apparatus for 30 min at 37 °C to prepare the trimethylsilyl (TMS) derivatives. After centrifugation (16,000× g, room temperature, 5 min), the supernatant (80 µL) was collected into a 100 µL spitz attached to a 1.5 mL vial, which was sealed with a septum and a screw cap. The derivatized samples were analyzed with a GC-MS system (GCMS-QP2010 Ultra; Shimadzu) equipped with an InertCap 5MS/NP capillary column. The following program was applied using helium as a carrier gas at a flow rate of 1.12 mL/min: 80 °C for 2 min, from 80 °C to 330 °C (5 °C/min), and 330 °C for 6 min. The total run time was 58 min. The injector was operated at a split ratio of 1:20 and was maintained at 230 °C. The interface temperature was maintained at 250 °C. The ion-source temperature was maintained at 200 °C. The mass spectrometer was operated in EI mode (70 eV). The mass scan range was 85–500 m/z. The obtained MS data (qgd-format) were converted to netCDF format. The data (netCDF format) were converted to the analysis base file (ABF) format by using an ABF converter (https://www.reifycs.com/AbfConverter/, accessed on 11 March 2023). Data processing was performed using MS-DIAL (version 4.92) [30,31]. Peak identification and prediction were also performed using MS-DIAL. The relative quantity of each metabolite was calculated using the peak area of each metabolite relative to that of an internal standard (2-isopropylmalic acid). ## 2.9. Statistical Analysis All values are expressed as the mean ± standard error of the mean (SEM). All data were analyzed using Bartlett’s test (among three groups) or the F-test (between two groups) for equality of variance. When the data were recognized as unequal variances, they were normalized by logarithmic transformation and then re-analyzed using Bartlett’s test or the F-test. Parametric tests were used for further statistical analysis to confirm the homogeneity of all data. Comparisons among three groups (control, $2\%$Chaeto, and $5\%$Chaeto groups) were performed using one-way analysis of variance (ANOVA), followed by Dunnett’s multiple comparison post hoc test. The dose dependency of the Chaeto groups ($2\%$ and $5\%$) was examined using the Jonckheere–Terpstra trend test. Comparisons between two groups (control and $5\%$Chaeto groups) were performed using Student’s t-test for data with equal variances or Welch’s t-test for data with unequal variances. Results with $p \leq 0.05$ were considered statistically significant, and 0.05 ≤ $p \leq 0.1$ was considered a tendency. Statistical analysis was performed using EZR, which is a graphical user interface for R (version 4.0.4) (The R Foundation for Statistical Computing, Vienna, Austria) [32], as well as MetaboAnalyst 5.0—a free web-based software platform [33]. Metabolites significantly affected by the $5\%$Chaeto diet compared to the control diet were subjected to pathway and enrichment analyses using MetaboAnalyst 5.0. ## 3.1. Effects of C. gracilis Feeding on Morphometric Variables in SD Rats At the time of autopsy, the color of white adipose tissues of rats fed C. gracilis was found to turn “orange-like” (Figure 1). Table 3 summarizes the morphometric variables of SD rats after a four-week feeding period. Furthermore, no significant differences were observed in the final body weight, food intake, food efficiency, and organ or tissue weights—including the liver, several white adipose tissues, and brown adipose tissue—among the three groups. In contrast, dose dependency was observed in the weight of soleus muscle in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). The soleus muscle weight tended to be higher in rats fed the $5\%$Chaeto diet than in those fed the control diet ($$p \leq 0.0916$$). Similarly, dose dependency was observed in the fecal weights in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). Furthermore, a significant difference in fecal weight was observed between the control group and the $5\%$Chaeto group ($p \leq 0.05$, Dunnett’s multiple comparison test). ## 3.2. Effects of C. gracilis Feeding on Hepatic Lipid and Glycogen Contents and Serum Biochemical Parameters in SD Rats Table 4 summarizes the hepatic lipid and glycogen contents and serum biochemical parameters in SD rats after a four-week feeding period. A dose dependency was observed in the hepatic TG contents in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). The hepatic TG contents were significantly lower in the $2\%$ and $5\%$Chaeto groups than in the control group. Dose dependency was also observed in the hepatic total cholesterol contents in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). The hepatic total cholesterol content was significantly lower in the $5\%$Chaeto group than in the control group. However, no significant differences in hepatic PL and glycogen contents were observed among the three groups. Dose dependencies were observed in the serum total cholesterol and HDL cholesterol levels in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). The serum levels of total and HDL cholesterol were significantly higher in the $2\%$ and $5\%$Chaeto groups than in the control group. In contrast, no significant differences were observed in the serum levels of TG, PL, NEFAs, glucose, C-peptide, insulin, adiponectin, or ALT among the three groups. ## 3.3. Effects of C. gracilis Feeding on Activities of Hepatic Enzymes and mRNA Levels Related to Fatty Acid Metabolism in SD Rats Enzymatic activities related to hepatic fatty acid de novo synthesis and fatty acid β-oxidation in rats are summarized in Table 5. Dose dependencies were observed for the FAS and G6PDH activities in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). FAS activity tended to be lower in rats fed the $5\%$Chaeto diet than in those fed the control diet ($$p \leq 0.0865$$). G6PDH activity was significantly lower in the $5\%$Chaeto group than in the control group. However, no significant differences were observed in the ME and CPT activities among the three groups. The hepatic mRNA levels of Fasn and G6pd did not differ significantly among the three groups (Table 5). ## 3.4. Effects of C. gracilis Feeding on Serum Levels of Steroids and Relative Levels of Hepatic mRNA Related to Cholesterol Metabolism in SD Rats The serum steroid levels and relative levels of hepatic mRNA related to cholesterol metabolism in rats are summarized in Table 5. A dose dependency was observed in the serum levels of cholesterol absorption markers, such as campesterol and β-sitosterol in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). The serum levels of campesterol and β-sitosterol were significantly lower in the $2\%$ and $5\%$Chaeto groups than in the control group. In contrast, the serum levels of lathosterol—a cholesterol synthesis marker—did not significantly differ among the three groups. In addition, dose dependency was observed in the hepatic mRNA levels of Scarb1, known as the HDL receptor, in the $2\%$ and $5\%$Chaeto groups ($p \leq 0.05$, Jonckheere–Terpstra trend test). The Scarb1 mRNA levels were significantly lower in the $5\%$Chaeto group than in the control group. In contrast, the hepatic mRNA levels of Hmgcr, Soat1, and Abca1 did not significantly differ among the three groups. ## 3.5. Effects of C. gracilis Feeding on Water-Soluble Metabolites in the Liver of SD Rats Among the 66 metabolites identified and semi-quantified in the liver (Table S4), the levels of three metabolites (glycerol, hypotaurine, and inositol) were significantly reduced in the $5\%$Chaeto group compared to those in the control group (Table 6). ## 3.6. Effects of C. gracilis Feeding on Water-Soluble Metabolites in the Soleus Muscle of SD Rats Among the 50 metabolites identified and semi-quantified in the soleus muscle (Table S5), the levels of 19 metabolites (2-aminoethanol, 3-hydroxypyruvate, β-alanine, cadaverine, creatine, glycerol, glycine, hypoxanthine, iminodiacetate, isoleucine, leucine, lysine, nicotinamide, O-phosphoethanolamine, phenylalanine, serine, threonine, uracil, and valine) were significantly increased, whereas the levels of one metabolite (oxalate) were significantly reduced in the $5\%$Chaeto group compared with those in the control group (Table 6). These 20 significant metabolites were subjected to pathway and enrichment analyses using MetaboAnalyst 5.0. The associated metabolic pathways are shown in Figure 2a, wherein nine pathways were found to be significantly related to C. gracilis feeding: “aminoacyl-tRNA biosynthesis,” “valine, leucine and isoleucine biosynthesis”, “pantothenate and CoA biosynthesis”, “glycine, serine and threonine metabolism,” “valine, leucine and isoleucine degradation”, “β-alanine metabolism”, “glutathione metabolism”, “phenylalanine, tyrosine and tryptophan biosynthesis,” and “glyoxylate and dicarboxylate metabolism”. Similarly, the enrichment ratio and p-values suggested that these nine pathways were significantly enriched (Figure 2b). ## 4. Discussion To explore the potential use of C. gracilis as a food resource, the effects of dietary C. gracilis on lipid abnormalities were investigated in rats fed the high-sucrose and cholesterol-containing diet. In a previous study that evaluated the safety of long-term administration of high-dose fucoxanthin (500 mg and 1000 mg/kg of body weight) in mice, increases in the levels of cholesterol and phospholipids in the blood, as well as in the weight of the liver were observed [34]. In the present study, the fucoxanthin intake calculated from its content in C. gracilis was approximately 40 mg/kg of body weight, and no findings other than increased serum total and HDL cholesterol levels were observed (Table 4). Although EPA has a TG-lowering effect [14], the intake of 2–$5\%$Chaeto (including EPA) did not affect the serum TG levels (Table 4). In addition, the color of the white adipose tissues of rats fed C. gracilis was observed to turn “orange-like” (Figure 1). This was consistent with previous studies in which fucoxanthin was administered alone [34]. Hashimoto et al. showed that, in mice, dietary fucoxanthin undergoes metabolic conversion to amarouciaxanthin A in the liver via fucoxanthinol and preferentially accumulates as amarouciaxanthin A in the adipose tissue [35], suggesting that amarouciaxanthin A is involved in the orange coloration of the adipose tissue. Taken together, we believe that the fucoxanthin contained in C. gracilis contributed greatly to the outcomes of this study. In the present study, the soleus muscle weights were found to be dose-responsive to C. gracilis and showed a tendency to increase (Table 3). Dietary intake of protein is known to be a prerequisite for the day-to-day maintenance of skeletal muscle mass, which stimulates an increase in muscle protein synthesis and attenuates muscle protein breakdown [36]. In a previous study, dietary fucoxanthin was found to protect against dexamethasone-induced muscle atrophy in mice [37]. Therefore, the intake of C. gracilis, which is rich in protein and fucoxanthin, may be effective in maintaining muscle mass. As shown in Table 4, the hepatic TG content was significantly reduced in the $2\%$ and $5\%$Chaeto groups compared with that in the control group. To understand the mechanisms underlying the hepatic TG-lowering action of C. gracilis, the activities of hepatic enzymes related to fatty acid metabolism were analyzed. Although the activities of CPT responsible for fatty acid β-oxidation in the mitochondria did not differ among the three groups, the activities of FAS and G6PDH—which are related to fatty acid de novo synthesis in the cytosol—were found to be dose-responsive to C. gracilis and showed a tendency to decrease (Table 5). The decreased activities of FAS and G6PDH were consistent with the results of a previous study in which mice were fed high-fat diets with fucoxanthin ($0.05\%$ and $0.2\%$) [38]. The hepatic mRNA levels of Fasn and G6pd did not differ among the three groups (Table 5), suggesting that the changes in FAS and G6PDH activities resulting from C. gracilis feeding represent post-translational regulation, but not transcriptional regulation. According to the results of metabolomic analysis in the liver, the glycerol content was significantly reduced in the $5\%$Chaeto group compared to that in the control group (Table 6). These results suggest that the reduction in hepatic TG content by C. gracilis feeding was attributable to the reduction in both fatty acids and glycerol, which are the substrates of TG. As shown in Table 4, compared with the control group, the hepatic total cholesterol content was significantly reduced in the $5\%$Chaeto group. To gain insights into the effects of C. gracilis feeding on cholesterol metabolism, we analyzed the serum levels of cholesterol, biomarkers, and hepatic mRNA levels related to cholesterol metabolism. Lathosterol is a precursor of de novo cholesterol synthesis, and its serum levels can be used as an index of cholesterol synthesis in the body [26,27]. In addition, plant sterols—such as campesterol and β-sitosterol—are sterol isomers that cannot be synthesized in animal bodies, and their serum levels are positively correlated with cholesterol absorption rates [26,27]. Although the serum levels of lathosterol and the hepatic mRNA levels of Hmgcr did not differ among the three groups, the serum levels of campesterol and β-sitosterol were found to be dose-responsive to C. gracilis and showed a significant decrease (Table 4 and Table 5). Additionally, as shown in Table 4, the serum total cholesterol levels were significantly higher in the $2\%$ and $5\%$Chaeto groups than in the control group. Higher total cholesterol levels were associated with significantly increased HDL cholesterol levels. A previous study showed that high-fat diets with fucoxanthin ($0.05\%$ and $0.2\%$) reduced the hepatic cholesterol content and HMG-CoA reductase activities and increased the plasma HDL cholesterol levels and fecal cholesterol contents in mice [38]. This behavior, except for cholesterol synthesis in the previous study, was consistent with the results of our study. This difference in cholesterol synthesis was thought to be due to the differences in animal species (rats in the present study versus mice in the previous study), dietary fat ($10\%$ fat based on corn oil in the present study versus $10\%$ lard + $10\%$ corn oil in the previous study), and cholesterol content. Unfortunately, the quality of the lard used in the diet of the previous study was unknown, and the cholesterol contents in the diets of the present and previous studies could not be accurately compared. In the present study, no significant difference in the serum non-HDL cholesterol levels was observed (Table 4), indicating that C. gracilis supplementation did not affect the secretion of cholesterol from the liver into the bloodstream. Beppu et al. reported that fucoxanthin intake increases the serum HDL cholesterol levels by decreasing the protein expression of SR-B1—a receptor of HDL—in the livers of mice [39]. As shown in Table 5, the hepatic Scarb1 mRNA levels were significantly decreased in the $5\%$Chaeto group, supporting the results of a previous study. Taken together, these data suggest that the decreases in intestinal cholesterol absorption and HDL uptake from the bloodstream into the liver caused by C. gracilis feeding contribute to the reduction in hepatic total cholesterol content in rats. From the perspective of the utilization and safety of C. gracilis rich in fucoxanthin as a food resource, further studies using LDL animals—such as hamsters, which have a lipoprotein metabolism similar to that of humans—are needed to evaluate whether the increase in the total and HDL blood cholesterol levels is specific to HDL animals, such as rats and mice. The health benefits of n-3 PUFAs such as EPA and DHA on lipid metabolism are well known [14,15]. A systematic review of the differential effects of dietary EPA and DHA on cardiometabolic risk factors indicates that dietary DHA—but not EPA—increases blood HDL-cholesterol levels [40]. Thus, we consider that fucoxanthin (but not EPA) contained in C. gracilis contributes greatly to the changes in lipid metabolism observed in this study. Since C. gracilis feeding tended to increase the soleus muscle weight of rats, water-soluble metabolite analysis in the soleus muscle was performed. As a result, compared to the water-soluble metabolite analysis in the liver, many metabolites in the muscle were significantly changed between the two groups (Table 6). The muscular contents of several amino acids, including branched-chain amino acids (BCAAs), were significantly increased in the $5\%$Chaeto group (Table 6). The magnitude of the muscle protein synthesis response to an ingested protein source is regulated at multiple levels, including dietary protein digestion and amino acid absorption, splanchnic amino acid retention, postprandial insulin release, transport, and uptake of amino acids into skeletal muscles [41]. The experimental diets used in this study were adjusted to ensure equal protein contents (Table 2). In terms of the amino acid contents of the $5\%$Chaeto diet, the contents of aspartic acid, glycine, alanine, arginine, and cystine were slightly higher and the contents of other amino acids were slightly lower compared to the control diet (Table S6). As the increase in the amino acid contents of muscles after C. gracilis feeding did not match the contents in the diet, this increase may be attributed to increases in protein digestion in C. gracilis and amino acid absorption, as well as amino acid uptake by the muscle. Leucine has been shown to upregulate the muscle protein synthesis machinery by activating the mechanistic target of the rapamycin complex 1 (mTORC1) signaling pathway [42]. Pathway and enrichment analyses associated with the significantly altered metabolites revealed that nine metabolic pathways were potentially affected by C. gracilis feeding. “ Aminoacyl-tRNA biosynthesis” was one of the pathways found in the analysis (Figure 2a,b). Aminoacyl-tRNA synthetases are a family of essential enzymes used for protein synthesis that play pivotal roles in the ligation of tRNA with their cognate amino acids [43]. Therefore, these results suggest that the tendency toward an increase in the weight of the soleus muscle after C. gracilis feeding may be due to the enhancement of muscle protein synthesis centered on leucine. As several pathways that may be affected by C. gracilis feeding were identified in the present study, future studies should seek to focus on these pathways. In conclusion, this study is the first to report that the oral administration of the marine microalga C. gracilis alleviates hepatic lipid accumulation in rats fed a high-sucrose and cholesterol-containing diet, indicating its potential use as a food resource. Through further comparative research with other marine microalgae containing bioactive compounds similar to those of C. gracilis, determining whether or not C. gracilis intake has a unique beneficial effect would be interesting. 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--- title: High-Resolution Taxonomic Characterization Reveals Novel Human Microbial Strains with Potential as Risk Factors and Probiotics for Prediabetes and Type 2 Diabetes authors: - Sarah A. Hendricks - Chantal A. Vella - Daniel D. New - Afiya Aunjum - Maximilian Antush - Rayme Geidl - Kimberly R. Andrews - Onesmo B. Balemba journal: Microorganisms year: 2023 pmcid: PMC10051885 doi: 10.3390/microorganisms11030758 license: CC BY 4.0 --- # High-Resolution Taxonomic Characterization Reveals Novel Human Microbial Strains with Potential as Risk Factors and Probiotics for Prediabetes and Type 2 Diabetes ## Abstract Alterations in the composition of the gut microbiota is thought to play a key role in causing type 2 diabetes, yet is not fully understood, especially at the strain level. Here, we used long-read DNA sequencing technology of 16S-ITS-23S rRNA genes for high-resolution characterization of gut microbiota in the development of type 2 diabetes. Gut microbiota composition was characterized from fecal DNA from 47 participants divided into 4 cohorts based on glycemic control: normal glycemic control (healthy; $$n = 21$$), reversed prediabetes (prediabetes/healthy; $$n = 8$$), prediabetes ($$n = 8$$), or type 2 diabetes ($$n = 10$$). A total of 46 taxa were found to be possibly related to progression from healthy state to type 2 diabetes. Bacteroides coprophilus DSM 18228, Bifidobacterium pseudocatenulatum DSM 20438, and Bifidobacterium adolescentis ATCC 15703 could confer resistance to glucose intolerance. On the other hand, Odoribacter laneus YIT 12061 may be pathogenic as it was found to be more abundant in type 2 diabetes participants than other cohorts. This research increases our understanding of the structural modulation of gut microbiota in the pathogenesis of type 2 diabetes and highlights gut microbiota strains, with the potential for targeted opportunistic pathogen control or consideration for probiotic prophylaxis and treatment. ## 1. Introduction Gut bacterial populations are prone to perturbations driven by intrinsic host factors (e.g., genetics and lifecycle stage) and environmental factors (e.g., pollutants, diet, lifestyle, pharmaceutical use) that can alter host physiology and health status [1]. Alterations in the gut microbiota composition (dysbiosis) have been associated with the progression of insulin resistance (IR) and type 2 diabetes [2]. Among consistently reported findings, the signatures of dysbiosis associated with type 2 diabetes include, but are not limited to, a decrease in the genera of Bifidobacterium, Bacteroides, Faecalibacterium, Akkermansia, and Roseburia; and an increase in the genera of Ruminococcus, Fusobacterium, and Blautia [3]. Several studies have found a correlation between type 2 diabetes and gut microbiota alpha (α)-diversity, as well as Firmicutes/Bacteroidetes (F/B) ratios; however, other studies have found no correlation [3]. Other commonly found gut microbiome shifts include the depletion of butyrate-producing bacteria [4] and a reduction in probiotics [5]. For example, several bacterial species, such as Lactobacillus fermentum, L. plantarum and L. casei, Roseburia intestinalis, Akkermansia muciniphila, and Bacteroides fragilis, have been shown to decrease the risk of diabetes development through maintaining intestinal barrier integrity, improving glucose metabolism and insulin sensitivity, and suppressing proinflammatory cytokines [6]. While these protective species may be candidates for probiotics, it is essential that they be carefully characterized and assigned to a given strain, and not to the entire genus or species [7]. To date, strain level data have been limited in studies identifying bacterial changes accompanying metabolic disease. Fei and Zhao [2013] found that a single strain, Enterobacter cloacae B29, in combination with a high-fat diet, induced fully developed obesity phenotypes, including endotoxin-induced inflammation, adiposity, and IR in gnotobiotic mice [8]. Aside from this case, most strain level microbiome research related to metabolic disease is focused on probiotics. For example, a comparison between Bifidobacterium animalis ssp. lactis GCL2505 (BlaG) and B. longum ssp. longum JCM1217T found that BlaG reduced visceral fat accumulation and improved glucose tolerance in a mouse model [9]. Without high resolution taxonomic information, these studies would not have been able to identify strains for development of effective probiotics. Further strain-level information regarding type 2 diabetes progression could be useful for targeted opportunistic pathogen control or probiotic prophylaxis and treatment. In this study, we aimed to identify novel strains associated with type 2 diabetes. We investigated the fecal microbiota in humans with prediabetes and type 2 diabetes, as well as those without diabetes. Using long-read DNA sequencing technology, a high-resolution ~2500-bp genetic marker (including the entire 16S gene and two additional genes), and a recently published reference database [10], we estimated microbial abundance and diversity, assessed microbiota associated with health status, and report new stains associated with type 2 diabetes progression. ## 2.1. Consent and IRB A convenience sample of 48 adults (mean ± SD age 51.0 ± 15.9 years, $60\%$ women) with and without type 2 diabetes, aged 18 years and older, were recruited from a university and the surrounding community to participate in this study that included two visits to the laboratory for each patient. Eligibility for the study was determined by a pre-screening questionnaire that was completed over the phone by a trained researcher. Study exclusion criteria included a history of gastric bypass surgery, inflammatory bowel disease (i.e., irritable bowel syndrome, Crohn’s or colitis), colon cancer, celiac disease, multiple sclerosis, Parkinson’s disease, Alzheimer’s disease, or current pregnancy. The University of Idaho Institutional Review Board approved the study (protocol 20-098) and all participants provided verbal and written informed consent to participate in the study. All experiments were conducted in accordance with the Declaration of Helsinki. ## 2.2. HbA1c Measurement A small sample of blood (~1 µL) was obtained from the middle or ring finger of the non-dominant hand and analyzed for HbA1c under strict standardized operating procedures using the DCA Vantage analyzer (Siemens Healthcare Diagnostics, Tarrytown, NY, USA). In brief, the finger was cleaned with alcohol prior to measurement. A disposable safety lancet (SurgiLance, MediPurpose, Duluth, GA, USA) was used to puncture the skin and the first drop of blood was wiped clean. The sample was drawn into the capillary tube, inserted into the reagent cartridge, and analyzed immediately. Participants were divided into four groups, based on measured hemoglobin A1c (HbA1c) during the first study visit: healthy ($$n = 21$$, HbA1c < $5.7\%$), healthy range but previously diagnosed with prediabetes by a registered physician (prediabetes/healthy (reversed prediabetes), $$n = 9$$; HbA1c < $5.7\%$), prediabetes ($$n = 8$$, HbA1c 5.7–$6.4\%$), and type 2 diabetes ($$n = 10$$, HbA1c ≥ $6.5\%$). ## 2.3. Stool Collection After collection of the blood sample, participants were provided a stool sample kit and detailed instructions to collect and store the sample. All samples were stored on ice in a Styrofoam cooler, brought to the laboratory within 24 h of collection, and frozen at −80 °C prior to extraction. The average number of days between the blood sample collection and fecal sample collection was 4.8 ± 2.1 days (range 1–8 days). ## 2.4. DNA Isolation, Sequencing, and Taxonomic Identification Total genomic DNA from 250 mg of human fecal samples was extracted using the QIAamp PowerFecal Pro DNA kits (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. The DNA concentration and purity were monitored on $1.5\%$ agarose gels. The Intus Biosciences Wave StrainID Kits (Farmington, CT, USA), SetA and SetZ, were then used to produce amplicons that span the full-length 16S, ITS, and partial 23S rRNA genes. Sequencing libraries were generated from these amplicons using PacBio SMRTbell Express Template Prep Kit v.3.0 (Pacific Biosciences, Menlo Park, CA 94025, USA) according to the manufacturer’s instructions. We included two negative controls (elution buffer and DNA extraction with water). The library was sequenced on 1 SMRT Cell 8M on a PacBio Sequel II System using the circular consensus sequencing (CCS) mode at the University of Idaho Institute for Interdisciplinary Data Sciences Genomics and Bioinformatics Resources Core. The CCS reads were determined with a minimum predicted accuracy of 0.9 and the minimum number of passes set to three in the SMRT Link software package v.10.2.1.143962 (Pacific Biosciences). SBanalyzer v.3.0 (Intus Biosciences) was used to demultiplex and assign taxonomic identification to all reads by mapping to the Athena database [10]. In this analysis, sequences are clustered by similarity with a threshold of $97\%$ and put into bins called ‘Operational Taxonomic Units’ (OTUs). Setting the sequence similarity threshold to $97\%$ to delineate species is only a rough approximation and, in some cases, may not be biologically accurate to distinguish between some taxa [11]. A single sequence is selected as a representative sequence for each of the OTU bins. If a read does not match any strains or if it matches equally to multiple strains in the database, the taxonomic classification will be reported at the highest level where an unambiguous call can be made, resulting in an “unclassified” taxon. The output reports abundance for each OTU for each patient. Patients with less than 500 reads were removed from all subsequent analyses. Potential reagent contaminants were identified using the decontam package v.1.14.0 with a threshold frequency of 0.5 of the OTU in the negative control [12,13]. The decontam package has been shown to remove upward of $90\%$ of contaminants even when the source of contamination was not well defined [14]. To determine whether sequencing depth was sufficient to capture a nearly complete microbiome profile for samples, rarefaction curves were plotted using the R-package vegan (v.2.6.2; [15]). ## 2.5. Alpha and Beta Diversity Analyses Subsequent analysis of the filtered OTU table was conducted in R [16] using the phyloseq package v.1.16.2 [17]. To calculate and plot α-diversity indices (Shannon diversity, Simpson index, and Chao1 index) of the microbiome communities, we used phyloseq. To analyze whether the α-diversity was significantly different between the four health status groups (healthy, prediabetes/healthy, prediabetes, diabetes), we first tested for normal distribution of each of the α-diversity indices using the Shapiro–Wilk test of normality. For nonparametric data, we tested for significant differences using the Kruskal–Wallis test. For normally distributed data, we used an ANOVA test and subsequent Tukey’s honest significance test of the ANOVA to test for statistical differences. We calculated beta (β) diversity using non-metric multidimensional scaling (NMDS) from Bray-Curtis dissimilarity in phyloseq. To test whether microbial communities differ by donor health status, we used the adonis2 function in R-package vegan (v 2.6.2) to run a permutational multivariate analysis of variance (PERMANOVA) after testing for multivariate homogeneity of group dispersion (beta dispersion). ## 2.6. Identification of Differentially Abundant Taxonomic Groups Community composition barplots were generated using the fantaxtic v.0.2.0 package in R. To identify taxa that were significantly different between health status groups, we used the DESeq2 package as described for microbiome applications [18,19]. After controlling for donor sex in the design matrix, DESeq2 was run under the Wald significance tests and parametric fitting of dispersions to the mean intensity settings, and false discovery rate adjusted p-values were calculated with the Benjamini-Hochberg procedure using a significance threshold of $p \leq 0.05.$ Differentially abundant (or “discriminatory”) taxa were assessed at the phylum, genus, and strain levels. To further investigate the level of differentiation across groups for discriminatory strains, we generated NMDS plots using Bray–Curtis dissimilarity for strain-level OTUs that were differentially abundant for one or more pairwise comparisons. ## 3.1. DNA Isolation, Sequencing, and Taxonomic Identification After removing one individual due to a low number of sequencing reads (SG11), the number of fecal microbial DNA samples sequenced was 21 healthy, 8 prediabetes/healthy, 8 prediabetes, and 10 type 2 diabetes individuals (Supplementary Table S1). The mean number of CCS reads per sample was 15,836.76. After all filtering steps, 641,305 reads were successfully classified with a mean of 13,644.79 (±5311.93) per sample. Before removing contaminants, 884 OTUs were identified. Eight OTUs were removed at a prevalence threshold of 0.5. After removing contaminants, ten phyla were identified, including Actinobacteria, Bacteroidetes, Cyanobacteria, Elusimicrobia, Firmicutes, Fusobacteria, Proteobacteria, Synergistetes, Tenericutes (Mycoplasmatota), and Verrucomicrobia. Four phyla, namely Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria were the most abundant across all samples (Figure 1), with a mean percent total reads across samples for these phyla of $58.80\%$ (±16.85), $23.13\%$ (±15.90), $10.72\%$ (±10.37), and $5.15\%$ (±5.76), respectively (Supplementary Table S2). These phyla were represented by 29 classes, 62 orders, 114 families, 312 genera, 602 species, and 876 strains. Of the 876 strains, 314 were known, previously published strains and 562 were unclassified (de novo) strains (Supplementary Table S3). ## 3.2. Alpha and Beta Diversity Rarefaction curves of the gut microbiomes of all individuals approached, but did not reach, a plateau, indicating that our dataset likely captured the dominant patterns of the microbial communities; however, that increased sequencing depth may have captured additional information regarding low-frequency taxa (Supplementary Figure S1). We used the Chao1 index as an indicator of microbial community richness, and Shannon and Simpson indexes as indicators of diversity (Figure 2a). These alpha diversity indices were not significantly different between the bacterial gut microbiomes of individuals from any health status comparisons. The Shapiro–Wilk normality test indicated that the Shannon and Simpson diversity values were not normally distributed (Shannon: $W = 0.92$, $$p \leq 0.003$$; Simpson: $W = 0.79$, $$p \leq 1.13$$ × 10−6), and the Kruskal–Wallis test showed no evidence of differences between groups (Shannon: chi-squared = 2.65, df = 3, $$p \leq 0.45$$; Simpson: chi-squared = 2.02, df = 3, $$p \leq 0.57$$). Chao1 richness was normally distributed ($W = 0.99$, $$p \leq 0.91$$) and was not significantly different between groups ($$p \leq 0.31$$). When testing for β-diversity, the NMDS plot did not indicate distinct clustering between health status cohorts, as evidenced by overlapping ellipses (Figure 2b). However, the PERMANOVA test did identify significant differences ($p \leq 0.05$) between health status categories ($F = 1.72$; R2 = 0.11; $$p \leq 0.02$$). ## 3.3. Differentially Abundant Taxa Some taxa exhibited significant differences ($p \leq 0.05$) in abundance between health status cohorts. At the phylum level, two phyla were less abundant in the type 2 diabetes cohort than other cohorts (Supplementary Table S4). In particular, Tenericutes was less abundant in type 2 diabetes participants compared to all other cohorts, and Firmicutes was less abundant in type 2 diabetes participants compared to healthy and prediabetes/healthy participants. Proteobacteria were more abundant in healthy and prediabetes/healthy participants (Supplementary Table S4). No phyla exhibited abundance differences for the remaining cohort comparisons (prediabetes to healthy, prediabetes/healthy to healthy, and prediabetes/healthy to prediabetes). F/B ratios were significantly higher for type 2 diabetes than for any of the three other cohorts (healthy controls: $$p \leq 0.01$$; prediabetes/healthy: $p \leq 0.001$; prediabetes: $$p \leq 0.01$$; Supplementary Table S1). There were no significant differences in F/B ratios in any other comparisons (prediabetes to healthy: $$p \leq 0.35$$, prediabetes/healthy to healthy: $$p \leq 0.06$$, and prediabetes/healthy to prediabetes: $$p \leq 0.57$$). At the genus level, several genera were significantly more abundant for the healthy cohort than for participants in type 2 diabetes (5 genera) and prediabetes (3 genera) cohorts ($p \leq 0.05$, Supplementary Table S5). In contrast, Streptococcus and (Bacteroides) genera were significantly less abundant in healthy individuals than in prediabetes/healthy and prediabetes participants, respectively. We also observed that one genus (Lactococcus) was less abundant and two (Selenomonas and Megasphaera) were more abundant in prediabetes/healthy participants compared to prediabetes participants. Prediabetes participants had five genera more abundant than in type 2 diabetes participants, while type 2 diabetes participants had four genera more abundant than prediabetes participants (Supplementary Table S5). There were three genera more abundant in type 2 diabetes as compared to prediabetes/healthy and four genera less abundant between the two cohorts (Supplementary Table S5). At the OTU level, 55 distinct taxa were found to differ in abundance across cohorts, with 39 of those taxa found to be significantly different in more than one comparison, and 16 taxa unique to a single comparison. Of these 55 OTUs, $60\%$ were identified to species level ($$n = 15$$) or strain level ($$n = 18$$). The number of differentially abundant OTUs ranged between 10 and 33 for the six pairwise comparisons of treatment cohorts (Figure 3, Supplementary Table S6, and description in Supplementary Materials). When calculating β-diversity using only strains that were differentially abundant across one or more pairwise comparisons, NMDS primarily distinguished healthy from diabetic participants (Supplementary Figure S2b). ## 4. Discussion In the present study, the fecal microbiota of healthy, prediabetes/healthy, prediabetes, and type 2 diabetes individuals were explored using long-read technology to sequence 16S-ITS-23S amplicons, and taxonomic classification was performed using a recently published reference database. The gut microbiota structure of all individuals was found to be mainly composed of Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. To our knowledge, we identified more strain-level microbial differences associated with type 2 diabetes progression than previous studies were able to find due to methodical limitations resulting in a lack of species- and strain-level resolution. As with many previous studies, we noted bacteria that may act as opportunistic pathogens as they are more abundant in the diabetic group than the glucose tolerant groups. Further, our study revealed that some taxa are significantly correlated with healthy individuals and likely infer a protective or probiotic role within the host, which corroborates findings from other studies that show the importance of these microbial markers to health. ## 4.1. Probiotic Taxa We identified several taxa that were positively associated with healthy status and that could be candidates for probiotic development. Bifidobacterium pseudocatenulatum (unclassified and strain DSM 20438) was higher in abundance with healthy status and, similarly, B. adolescentis ATCC 15703 shifts to a greater abundance in the healthy group as compared to prediabetes/healthy. There is strong support for Bifidobacterium’s protective role in type 2 diabetes in previous studies. Many papers report a negative association between this genus and type 2 diabetes (see [3]), with only one paper reporting conflicting results [20]. Certain species, such as B. adolescentis, B. bifidum, B. pseudocatenulatum, B. longum, and B. dentium, have been found to have a negative association with type 2 diabetes patients treated with the antihyperglycaemic agent metformin [21]. In animal studies testing for probiotic effects, several species/strains from this genus (B. bifidum, B. longum, B. infantis, B. animalis, B. pseudocatenulatum CECT 7765, and B. breve) showed improvement of glucose tolerance [9,22,23,24,25], with some species (B. adolescentis) being superior in alleviating type 2 diabetes symptoms compared to other species (B. bifidum; [26]). Our results support the notion that Bifidobacterium naturally inhabiting the human gut may play a protective role in type 2 diabetes and indicate that two strains, B. pseudocatenulatum DSM 20438 and B. adolescentis ATCC 15703, have the potential for new probiotic agents. We also found Prevotella copri DSM 18205 to be more abundant as health increases. However, there have been contradictory results regarding the pathophysiological role of P. copri. This species is correlated with IR in humans and in fat-fed mice [27], and has been found to be elevated in type 2 diabetes [28]. Direct inoculation of rats with P. copri showed an improved glucose homeostasis [29]. This inconsistent pattern may be due to the existence of several P. copri clades or host diet-dependent effects [30]. Given that these microbes were more abundant in glucose tolerant groups, they may be possible candidates for probiotic use in type 2 diabetes prevention and treatment. However, risk, efficacy, and dosage for each strain should be fully explored through science-based clinical studies on targeted populations and pre-market approvals should be established [31]. We found that Romboutsia, a butyrate producing bacteria genus, and R. timonensis also increased in healthy and prediabetes individuals as compared to the type 2 diabetes group. Similarly, other studies found Romboutsia to be inversely associated with IR, type 2 diabetes, and gestational diabetes mellitus [32,33,34]. Additionally, studies have shown that Romboutsia is negatively correlated with fasting glucose, insulin, and high-density lipoprotein cholesterol; and positively correlated with indicators of obesity [35]. Contrary to these findings, one study found a significantly lower relative abundance of R. timonensis in type 2 diabetes participants as compared to healthy controls [36]. Further, Hu et al. [ 2019] reported that Romboutsia was reduced in the diabetic rats [37]. Therefore, Romboutsia may be a candidate genus for predicting and treating obesity and related metabolic disorders; however, more species and strain-specific knowledge is required to define utilities of these microbes in humans. ## 4.2. Pathogenic Taxa In this study, we found several taxa that increased in abundance with progression from prediabetes to type 2 diabetes, indicating a possible pathogenic effect. Odoribacter laneus YIT 12061 was found to be significantly more abundant in prediabetes/healthy, prediabetes, and type 2 diabetes than in healthy controls. This species is a succinate-consuming bacterium and has been associated with a number of diseases, including colitis in a mouse model [38]. Odoribacter has been found to be negatively associated with the expression of intestinal epithelial tight junction proteins, suggesting a link with impairing mucosal barrier function in rats [39]. However, Huber-Ruano et al. [ 2022] showed that one strain of O. laneus, DSM 22474 A, has beneficial anti-inflammatory and metabolic properties in obese mice [40]. Collectively, our results strongly suggest that the effects of this species may be strain-specific and indicate the need of comprehensive evaluation before pursuing Odoribacter strains for treating type 2 diabetes in humans. Another genus and species that increased in abundance and could be involved in the development of type 2 diabetes were Flavonifractor plautii and an unclassified Flavonifractor species, which were more abundant in type 2 diabetes participants than prediabetes/healthy participants. This pattern supports previous findings showing that the genus Flavonifractor decreased in prediabetes and increased in type 2 diabetes [41], and was associated with a lower insulin sensitivity and higher prevalence of dysglycemia [42]. F. plautii, specifically, was lower in patients with prediabetes and higher in patients with diabetes [41,43]. One possible mechanism underlying the association of Flavonifractor with type 2 diabetes progression is that this genus may increase oxidative stress and trigger inflammatory cytokines in plasma [44,45]. These cytokines are associated with type 2 diabetes by impairing insulin signal transduction and triggering IR [46]. To support this, possible treatments such as the oral administration of Sanghuangporous vaninii SVE have been shown to improve body weight, glycolipid metabolism, and inflammation-related parameters through modulating gut microbiota including decreasing Flavonifractor [47]. ## 4.3. Species- and Strain-Dependent Associations We identified stain-dependent type 2 diabetes associations within the Escherichia genus. Escherichia coli O128:H27 were more enriched in healthy and prediabetes/healthy than in prediabetes and type 2 diabetes. In contrast, E. coli O25b:H4 and E. coli O25b:H4-ST131 were more abundant in type 2 diabetes and prediabetes than in prediabetes/healthy; however, both were more abundant in healthy than prediabetes/healthy. Following a similar pattern, E. coli O1:H42 was more abundant in type 2 diabetes than prediabetes and healthy, but also more abundant in healthy as compared to prediabetes. We discovered an unclassified strain of E. coli was more abundant in type 2 diabetes than in prediabetes/healthy. Previous studies have positively associated Escherichia increasing in abundance with progression from normal glucose tolerance to type 2 diabetes [48,49,50] and with effects of metformin therapy [21,51]. Our results support the findings that E. coli may play a role in the pathogenesis of type 2 diabetes as well as metformin mechanisms of action. However, our work illuminates the essence of E. coli strain specificity when considering their functional use as antidiabetic targets for humans. Within the genus Bacteroides, B. coprophilus DSM 18228 = JCM 13818, and B. stercoris ATCC 43183 were more abundant as health increases; however, B. vulgatus (unclassified strain and strain ATCC 8482) were higher in type 2 diabetes participants. Moreover, (Bacteroides) pectinophilus ATCC 43243 was unique to prediabetes and B. coprocola DSM 17136 to prediabetes/healthy individuals. According to Gurung et al. [ 2020], many previous studies have found Bacteroides to be either negatively or positively associated with type 2 diabetes [3]. Our study suggests that these inconsistencies could be driven by species and strain-specific effects, which would not have been distinguished in previous studies due to limitations of taxonomic classification below the genus level with traditional partial-16S sequencing. Alternatively, other confounding variables could be involved. For example, the studies that found positive associations with disease noted that participants had taken antidiabetic treatments, such as metformin, which have been shown to result in functional microbial shifts [51,52]. This could account for the apparent inconsistency in this study as well as previous studies. There could be several other confounding variables resulting in these inconsistencies, such as underlying host genetics, diet, physical activity level, medication use, and sequencing techniques. Nonetheless, our study indicates that species specificity of Bacteroides is important when considering the utility of antidiabetic properties and as a beneficial role on glucose metabolism in humans. We identified three Lactobacillus species that were differentially abundant in our association analysis. Lactobacillus animalis and L. murinus are more abundant in both the two extreme phenotypes, healthy and type 2 diabetes, as compared to the prediabetes/healthy and prediabetes participants, whereas L. johnsonii was associated with type 2 diabetes. Although L. animalis and L. murinus were found to be highly abundant in healthy individuals, they both were also highly abundant in type 2 diabetes, so are not likely candidates for probiotics. The highly diverse Lactobacillus genus, which is frequently detected and reported in type 2 diabetes association studies, has the highest number of taxa with probiotic potential found in the human gut to date [3]. The effects of this genus on type 2 diabetes seem to be species-specific. For example, three species, L. acidophilus [53], L. gasseri [54], L. salivarius [54], were significantly more abundant in type 2 diabetes participants, while L. amylovorus [51] was decreased in type 2 diabetes participants. These previous results, as well as the results of our study suggests that species and strain specificity from this genus impact the functionality of host metabolism. Collectively, these differences in association patterns across species and strains reported herein highlight the significance of using high-resolution taxonomic methods to identify specific species and strain linking the microbiome with type 2 diabetes and other illnesses. ## 4.4. Microbial Diversity Our study found mean richness and diversity measures were lower in participants with type 2 diabetes than all other participants, but higher in prediabetes/healthy and prediabetes than in healthy individuals. However, these differences were non-significant across comparisons, which may be due to limited sample size. Although α-diversity has been proposed as a biomarker in general health and disease, there is currently controversy regarding the association between diversity and type 2 diabetes due to inconsistent findings. For example, a systematic review of 13 studies investigating associations of gut microbiota α-diversity and type 2 diabetes found that an equal number of studies identified a negative correlation ($$n = 2$$) and a positive correlation ($$n = 2$$), and 9 found no correlation [3]. The lack of significant association for α-diversity with type 2 diabetes in our study supports the idea that gut microbiota richness and diversity may not necessarily decline with the progression of illness. However, many of the study participants classified as prediabetes/healthy and prediabetes were taking antihyperglycaemic agents, such as metformin. These agents have been found to increase the α-diversity of gut microbiota, as well as the reduction of HbA1c and fasting blood glucose concentrations [21,55]. These effects could have increased diversity in prediabetes/healthy and prediabetes participants relative to healthy participants in our study. It has also been noted that colonic transit time [56] and stool consistency [57] may interfere with the ability to use α-diversity as a biomarker in disease status. Beta diversity, a measure of the similarity or dissimilarity of two communities, was found to statistically differ between healthy, prediabetes/healthy, prediabetes, or type 2 diabetes. According to Gurung et al. [ 2020], of 8 studies reporting β-diversity, 7 did not find any significant association between microbial β-diversity and type 2 diabetes [3]. Taxa may not have clustered distinctly on a community level as shown in the NMDS plot (Figure 2b) due to host participants living in relatively homogeneous environments [58] including similar host subsistence strategies, geographic location, and ethnicity [59]. ## 4.5. F/B Ratios The progression of type 2 diabetes may, in part, be due to the transformation of dominant bacteria, and, thus, F/B ratios are often measured to investigate associations between the microbiome and type 2 diabetes. The systematic review by Gurung et al. [ 2020] found that the B/F ratio did not show consistent associations with type 2 diabetes with six publications that found no association, three with a positive association, and four with a negative association [3]. Our findings showed that F/B ratios are highest in the type 2 diabetes group and significantly different than each of the three other categories. F/B ratios were not significantly different between healthy, prediabetes/healthy, and prediabetes cohorts likely due to the effect of antihyperglycaemic drugs as highlighted above. ## 4.6. Limitations and Future Directions This study had several potential limitations. First, sample sizes were relatively small. Second, not all OTUs were resolved to the strain level, indicating that additional strain-level associations may exist in our dataset that could not be detected in our analyses. Thus, further development of the reference database could lead to even greater taxonomic resolution in future studies. Third, most prediabetes and type 2 diabetes participants in this study had taken antihyperglycaemic or anti-hypertensive drugs, and/or probiotics/prebiotics, which may have influenced the bacterial communities. Fourth, we could not control for every possible lifestyle factor or duration of disease in the study design, which leaves the possibility of residual confounding factors. Finally, our cross-sectional study cannot draw a direct link between bacterial taxa and particular metabolites involved in type 2 diabetes. Functional studies will be required to determine whether relevant bioactive metabolites were produced by the bacteria that were determined to be differentially abundant between diabetes participants and healthy participants, and if these metabolites were indeed causal for the disease phenotype. Future studies that integrate metagenomic and metabolomic approaches would greatly contribute to treatment discovery. Furthermore, a complete genome sequence and annotation, especially of genes associated with causal metabolites, is necessary for the registration of new probiotic strains. ## 5. Conclusions To our knowledge, we identified more strain-level microbial differences associated with type 2 diabetes progression than previous studies were able to find due to methodical limitations resulting in a lack of species- and strain-level resolution. 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--- title: A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity authors: - Tiankuo Luan - Daqiang Song - Jiazhou Liu - Yuxian Wei - Rui Feng - Xiaoyu Wang - Lin Gan - Jingyuan Wan - Huiying Fang - Hongzhong Li - Xia Gong journal: Medicina year: 2023 pmcid: PMC10051894 doi: 10.3390/medicina59030424 license: CC BY 4.0 --- # A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity ## Abstract Background and Objectives. The prognostic role of adjacent nontumor tissue in patients with breast cancer (BC) is still unclear. The activity changes in immunologic and hallmark gene sets in normal tissues adjacent to BC may play a crucial role in predicting the prognosis of BC patients. The aim of this study was to identify BC subtypes and ribosome-associated prognostic genes based on activity changes of immunologic and hallmark gene sets in tumor and adjacent nontumor tissues to improve patient prognosis. Materials and Methods. Gene set variation analysis (GSVA) was applied to assess immunoreactivity changes in the overall sample and three immune-related BC subtypes were identified by non-negative matrix factorization (NMF). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses were after determining the prognostic gene set using the least absolute shrinkage and selection operator (LASSO) method. Ribosome-related genes were identified by PPI (protein-protein interaction) analysis, and finally a prognostic risk model was constructed based on the expression of five ribosomal genes (RPS18, RPL11, PRLP1, RPL27A, and RPL38). Results. A comprehensive analysis of immune and marker genomic activity changes in normal breast tissue and BC tissue identified three immune-related BC subtypes. BC subtype 1 has the best prognosis, and subtype 3 has the worst overall survival rate. We identified a prognostic gene set in nontumor tissue by the least absolute shrinkage and selection operator (LASSO) method. We found that the results of both KEGG and GO analyses were indistinguishable from those of ribosome-associated genes. Finally, we determined that genes associated with ribosomes exhibit potential as a reliable predictor of overall survival in breast cancer patients. Conclusions. Our research provides an important guidance for the treatment of BC. After a mastectomy, the changes in gene set activity of both BC tissues and the nontumor tissues adjacent to it should be thoroughly evaluated, with special attention to changes in ribosome-related genes in the nontumor tissues. ## 1. Introduction BC (breast cancer) is one of the most common cancers for women in the world. Moreover, the incidence rate of BC accounts for $30\%$ of all cancers in women, and the mortality rate is as high as $15\%$ [1]. Metastasis in BC patients is the major reason for death. The five-year survival rate is only $25\%$ for patients with metastatic BC [2]. Unfortunately, even after treatment, patients with primary breast cancer still have a 20–$30\%$ probability of metastasis [3]. Mastectomy is the main method for early treatment of BC, but BC will still recur after treatment [4]. Despite surgical intervention, there remains a risk of recurrence. Moreover, BC has a high degree of heterogeneity, which leads to the invasion and metastasis of breast cancer to a large extent, making the treatment of BC more difficult [5]. Most previous studies on BC subtypes have focused on pyroptosis-related genes [6], subtypes based on multi-omics and transcriptional patterns [7], and subtypes based on biological and immune components [8]. These studies all provide important clinical implications for the treatment of BC. Nevertheless, few studies have identified BC subtypes by systematically analyzing nontumor tissues adjacent to BC and BC samples for changes in the activity of immunological and signature gene sets. In this study, we established three different BC subtypes by systematic immunological and marker gene set activity change analysis based on normal breast samples and BC samples. Three clinical subtypes of BC were used to identify a set of prognostic genes in non-tumor samples. Immune cell abundance, immune score, stromal score, estimate score, and tumor purity were evaluated for the three clinical subtypes. KEGG and GO analysis and PPI co-expression network results showed that they were intimately associated with ribosome. Therefore, based on the above results, we further analyzed the specific ribosomal molecular characteristics in BC subtypes, and constructed a risk model according to ribosome-correlated genes to evaluate the survival rate of BC patients. Our study offers a novel approach for categorizing subtypes of BC and crucial support for BC treatment. It highlights the need to closely monitor the alteration of ribosome-related gene activity in non-tumor tissues surrounding mastectomy sites in BC patients. ## 2.1. Data Collection RNA-seq data from 1222 BC samples, including 1109 tumor samples and 113 normal samples, and their clinical information were downloaded from the TCGA database (https://portal.gdc.cancer.gov/ (accessed on 24 November 2021)). Gene expression profiling data and associated clinical information for BC were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/ (accessed on 24 November 2021)), including (GSE20685, $$n = 327$$), (GSE88770, $$n = 116$$). Gene set enrichment analysis (GSEA) (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp (accessed on 24 November 2021)) software was used to download the 50 hallmark genes sets and 4872 ImmuneSigDB gene sets of C7 [9,10]. ## 2.2. Gene Set Variation Analysis (GSVA) R Package GSVA was utilized to enrich gene sets of TCGA and GEO BC patients’ gene expression profiling data and further observe the changes of gene set activity [11]. ## 2.3. Heatmaps and Nonnegative Matrix Factorization (NMF) The R package “pheatmap” was used to draw heatmaps [12]. TCGA and GEO gene expression profiling data of BC were analyzed using the NMF package [13]. ## 2.4. Classification of BC Samples TCGA and GEO gene expression profiling data of BC were analyzed using the “Cancer subtypes” package [14]. ## 2.5. ESTIMATE and ssGSEA Analysis of BC Subtypes The analysis of 29 immune pathways in a single ssGSEA sample from three subtypes of BC was conducted. ESTIMATE was used to analyze immune cells (immune score), stromal cells (stromal score), tumor purity, and ESTIMATE score for three subtypes of BC [15]. Finally, it is presented with a violin plot. ## 2.6. Construction and Validation of Potential Prognostic Gene Sets Models The potential prognostic gene sets were identified by the least absolute shrinkage and selection operator (LASSO) method [16]. The prognostic model’s accuracy and OS analysis in BC patients were analyzed using the ROC and Kaplan–Meier algorithms. ## 2.7. Estimation of Tumor-Infiltrating Immune Cells (TICs) We calculated the proportion of 23 kinds of immune cells in BC patients with the ssGSEA algorithm. ## 2.8. Gene Set Enrichment Analysis (GSEA) GSEA was performed between high and low group of risk score. Risk score = −0.088 × (RPS18 expression) + −0.155 × (RPL11 expression) + −0.024 × (RPLP1 expression) + −0.153 × (RPL27A expression) + −0.047 × (RPL38 expression). The number of random sample permutations was set at 1000, and NOM $p \leq 0.05$, FDR q < 0.05, and \|NES\| > 1 were set as the significance thresholds. ## 2.9. Functional Analysis of GO and KEGG Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of genes in prognosis-associated gene sets were used to clarify their mechanism in prognosis. ## 2.10. String and Protein-Protein Interaction Analysis Constructing a prognostic gene set protein relationship network through the string data base (https://cn.string-db.org/ (accessed on 24 December 2021)) [17]. The MCODE (Molecular Complex Detection) plug-in Cytoscape_v3.9.0 (San Diego, CA, USA) was used to filter out hub genes [18]. ## 2.11. Statistical Analysis All statistical analyses in this article were performed with R software (Auckland, New Zealand, version 4.1.2, https://www.r-project.org/ (accessed on 24 November 2021)). Statistical differences between two or three groups were compared using the Wilcoxon test. $p \leq 0.05$ = “”, $p \leq 0.01$ = “”, and $p \leq 0.001$ = “*”. p values < 0.05 would be statistically significant. ## 3.1. Three BC Subtypes Based on Changes in Activity of Immune and Hallmark Gene Sets Gene set variation analysis (GSVA) can be used to detect changes in the activity expression of gene sets in different pathways [11]. To get a comprehensive view of the changes in immune and hallmark sets in breast cancer tissue and nontumor tissue adjacent to BC, we downloaded 50 hallmark gene sets and 4872 ImmuneSigDB gene sets of C7 from gene set enrichment analysis (GSEA) (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp (accessed on 1 October 2021)). After performing GSVA enrichment analysis on TCGA data samples, we found some differences among BC tumor tissues and BC normal tissues (Figure 1). A Cox regression algorithm was developed using the cancer subtypes package for expression level and clinical data to screen 41 clinically related gene sets from 4922 gene sets. The factoextra package was used to screen the optimal K value, which was 3 (Figure 2A,B). The NbClust package was used to classify breast cancer patients for subtypes, and finally three different subtypes were obtained (Figure 2C). The average silhouette width was 0.85 (Figure 2D), indicating the rationality of our BC subtype classification. Patients with BC subtype 2 had the best survival rate, followed by subtype 1 patients and subtype 3 patients (Figure 2E). We used the same method to combine the GSE20685 and GSE88770 data and removed batch effects for the analysis. This result was consistent with TCGA data analysis, that patients with BC subtype 2 had the best survival rate, followed by subtype 1 patients, and subtype 3 patients had the worst survival rate (Figure S1A–E). Detailed clinical information on the three subtypes is presented in Supplementary Table S1. Recent studies have shown that the tumor microenvironment influences the incidence and development of tumors [19,20], and immune cells and stromal cells interact to play an important role [21]. Therefore, we studied three BC subtypes using the estimate score algorithm. In the TCGA BC patients cohort, the results of three subtypes for the correlation with tumor microenvironment are presented with a violin plot (Figure 3A–C). The results showed that the BC subtype 2 had the highest immune score, stromal score, and estimate score, followed by those of subtype C1, and subtype C3 had the lowest scores. Furthermore, BC subtype C2 had the lowest tumor purity, and subtype C3 had the highest tumor purity (Figure 3D). In the GEO cohort, the BC subtype C2 also had a significantly higher immune score, stromal score, and estimate score than those of the other two subtypes (Figure S2A–C). Additionally, BC subtype C2 had much lowest tumor purity than subtype C1 and subtype C3 (Figure S2D). We adopted the ssGSEA method to score 23 kinds of immune cells for the three BC subtypes, and the scores reflected the relational degree of 23 kinds of immune cells for the three BC subtypes. The results showed that subtype C2 had higher scores of immune-related pathways than subtype C1 and subtype C3 in both TCGA (Figure 3E) and GEO (Figure S2E) datasets, and subtype C3 had the lowest scores. The scoring results of both the estimate score algorithm and ssGSEA method (23 kinds of immune cells) remained consistent with our initial survival results obtained for the three BC subtypes. subtype C2 had the best survival, followed by subtype C1 patients, and subtype C3 patients had the worst survival rate, further justifying our BC subtypes classification and illustrating the positive correlation between high immunologic activity and survival. ## 3.2. Analysis on BC Subtypes and Clinical Correlation Next, we analyzed the clinical characteristics of BC subtypes. The results also revealed that patients with BC subtype 2 had the best survival rate, followed by subtype 1 patients, and subtype 3 patients had the worst survival rate in both the TCGA cohort and GEO cohort (Figure 2E and Supplementary Figure S1E). To identify the gene sets that differ among the three subtypes, we first compared the GSVA enrichment scores of normal tissue and tumor tissue to obtain the differential gene sets (adj p value < 0.05). logFC > 0 was defined as the T gene set, while logFC < 0 was defined as the N gene set. The differential expression analysis was then performed between each two subtypes, and 211 gene sets that differed between any two subtypes (with the same constraints as above) were obtained. Figure 4A shows 211 representative differential gene sets, and the differential gene sets and clinical correlation are demonstrated with a heatmap (Figure 4B). The heatmap showed that BC subtype C2 had the highest expression level in the differential gene sets, subtype C3 had the lowest expression level, and the three subtypes was highly correlated with age. To further identify the gene sets most related to the prognosis of BC subtypes, we applied the LASSO regression model to finally identify a gene set N_GSE42088 (Figure 5A,B), Risk Score = Coefficients value (−7.63584585568389) × expression of N_GSE42088_UNINF_VS_LEISHMANIA_INF_DC_4H_DN. In Figure 5C, the area under the curve is (AUC) 0.665, proving the reliability of the risk score. The* gene set expression level of N_GSE42088_UNINF_VS_LEISHMANIA_INF_DC_4H_DN correlated with the overall survival (OS) of BC patients in TCGA cohort ($$p \leq 0.001$$), and patients had a better survival rate when this gene set had a high expression level (Figure 5D). ## 3.3. Functional and Pathway Enrichment Evaluation We obtained all the genes in this prognostic gene set and performed KEGG and GO enrichment analysis to reveal the mechanism of its prognosis. The CC (cellular component) of this nontumor gene set was mainly associated with cytoplasmic translation. MF (molecular function) was concerned with ribosome, ribosomal subunit, and cytosolic ribosome. BP (biological process) was connected with structural component of ribosome (Figure 6A). KEGG analysis results were enriched in ribosome and coronavirus disease COVID-19 (Figure 6B). By using protein–protein interaction network analysis, we retained scores greater than 0.9 for subsequent analysis (Figure S3). Intriguingly, the 34 hub genes with the highest degree score in cluster 1 were all associated with ribosomes (Figure 7A), cluster 2 was EIF3E, EIF3F, EIF3H and EIF3L (Figure 7B), cluster 3 was HLA-DRA, HLA-DQB2, HLA-DPB1 and CD74 (Figure 7C), and cluster 4 was IFITM3, GBP2, and OASL (Figure 7D). ## 3.4. Identification of Ribosome-Associated Clusters and Assessment of Immune Cell Infiltration To explore the role of ribosome related genes in BC, we further used the NMF algorithm to analyze 34 ribosome-related hub genes. In this way, the BC cohort of TCGA was divided into two subtypes with different molecular characteristics and clinical features, including ribosome related subtype C1 and C2 (Figure 8A–C). We found that C1 patients had a notable higher survival rate than C2 (Figure 8D). We used multiple algorithms, including CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER and XCELL, to analyze the two subtypes of immunocyte infiltration. The heatmap showed that the proportion of CD8+ T cells in C1 subtype was higher than that in C2, while the proportion of Macrophage M2 in C1 subtype was lower than that in C2 (Figure 8E). ## 3.5. Development and Validation of a Ribosome-Related Prognostic Risk Model To nail down the role of these two subtypes in the clinical treatment of BC, and calculate the risk score for BC patients, we performed univariate COX regression analysis of 34 ribosome-related genes previously obtained, and 18 ribosome related genes were $p \leq 0.05$ in the TCGA cohort (Figure 9A). The LASSO regression algorithm finally confirmed five ribosome-related genes in Figure 9B,C (RPS18, RPL11, RPLR1, RPL27A, and RPL38), named ribosome risk score signature (RRS), which will be used for the construction of ribosome signature. Risk score = −0.088 × (RPS18 expression) + −0.155 × (RPL11 expression) + −0.024 × (RPLP1 expression) + −0.153 × (RPL27A expression) + −0.047 × (RPL38 expression). After analyzing the prognostic survival of risk score and TCGA BC patients by using the Kaplan–Meier curve, we found the survival rate of the high-risk group was significantly lower than that of the low-risk group (Figure 9D). The same results were obtained by using the GSE20785 data set to verify (Figure 9E). The results of T-SNE and PCA analysis proved the rationality of the RRS model in the division of both high-risk and low-risk groups in TCGA (Figure S4A,C) and GEO cohort (Figure S4B,D). The risk curve analysis showed that the mortality rate of the low-risk group was lower and the survival time was longer (as shown in the left side of the imaginary line in the graph), while the number and mortality of the high-risk group were positively correlated with the risk score (Figure S4E–H). The 3-year AUCs curve in the TCGA breast cancer patient cohort was 0.568, and the 5-year AUCs curve was 0.587. ( Figure S4I). The AUCs curves for 3 and 5 years in the GSE20785 cohort were 0.554 and 0.583, respectively (Figure S4J). ## 3.6. Clinicopathological Characteristics, Immune Activity, and Functional Enrichment Analysis Based on the RRS Model The following was a comprehensive analysis of TCGA BC cohort. The results of the heatmap reveal that the RRS model risk score was significantly correlated with age (Figure S5A). The results of univariate and multivariate cox algorithms demonstrate that RRS has an important role in the prognostic assessment of breast cancer patients (Figure S5B,C). XCELL, QUANTISEQ, MCPCOUNTER, CIBERSORT, and CIBERSORT-ABS algorithm results identify that the high-risk group displayed a positive correlation with macrophage M2, while low-risk group showed a favorable correlation with CD8+ T cells (Figure 10A). Details of immune cell infiltration in the high- and low-risk groups are shown in Supplementary Table S2. This result is similar to previous results of immune infiltration based on 34 ribosome-associated hub genotypes. For this reason, we compared and analyzed the enrichment fraction of 16 immune cells and the activity of 13 immune-related pathways between the high-risk group and the low-risk group in the RRS model. The infiltration of aDCs, B cells, CD8+ T cells, dendritic cells (DCs), induced dendritic cells (iDCs), and plasmacytoid tumor-infiltrating lymphocytes (TILs) in the low-risk group was higher than that in the high-risk group (Figure 11B). However, macrophages and neutrophils showed higher infiltration in the high-risk group than in the low-risk group (Figure 10B). APC co-stimulation, chemokine receptor (CCR), immune checkpoint, cytolytic activity, human leukocyte antigen (HLA), inflammation promotion, and Type1-IFN response activity in low-risk group were well above the high-risk one (Figure 10C). The GSEA algorithm explores the function of KEGG and GO for high- and low-risk groups. The results of KEGG enrichment analysis showed that the main enriched pathways in the high-risk group were ABC transporters, ECM–receptor interaction, inositol phosphate metabolism, steroid hormone biosynthesis, and systemic lupus erythematosus (Figure 11A). The low-risk group pathways were enriched in ribosome, Huntington’s disease, oxidative phosphorylation, Parkinson’s disease, and primary immunodeficiency (Figure 11B). In addition, GO enrichment results in the high-risk group were focused on ribosome assembly, ribosome organization, DNA packaging complexes, and protein DNA complexes. ( Figure 11C). Results of the low-risk group revealed a significant correlation with cytosolic ribosome, structural constituents of ribosome, nuclear transcribed mRNA catabolic process nonsense mediated decay, establishment of protein localization to endoplasmic reticulum, and cotranslational protein targeting to membrane (Figure 11D). ## 4. Discussion Our study conducted a thorough and multi-layered analysis on the alterations in the activity of immunological markers and gene sets in both BC tissue and adjacent tissue, offering new insight into the significance of adjacent tissue in the prognosis of BC instead of solely focusing on changes within BC tissue. Previous studies on BC subtypes and prognosis were still limited to BC itself, and the changes between BC and adjacent tissues were not analyzed as a whole. For example, classification of breast cancer into different subtypes have been based on pyroptosis-related genes, metabolic characteristics, and multi-omics features [5,6,7]. These studies have important significance in the prognosis diagnosis and targeted treatment of BC. However, the adjacent breast tissue cannot be ignored in the process of BC. Therefore, we divided BC patients into three survival-related subtypes with an NMF algorithm after analyzing the immunological and marker gene set activities of BC tissues and adjacent sample tissues. In summary, subtype 2 had the better prognosis compared with subtype 1 and subtype 3, and subtype 3 had the worst prognosis. Additionally, the proportion of immune cells, stromal cells, and enrichment of immune-related pathways in subtype 2 were also higher than those in subtype 1 and subtype 3. Previous research had revealed that the activation of immune cells and immunity pathways in tumor tissues has an essential roles in the prognosis of cancer patients [22,23]. Using the LASSO Cox algorithm, we found a gene set of prognostic genes in BC adjacent tissues, and the results of KEGG and GO enrichment algorithms suggested that the gene set was associated with ribosome and cytoplasmic translation and constitutive of ribosome. Interestingly, through the PPI algorithm and MCODE algorithm, we found that 34 hub genes were also highly correlated with ribosome. The changes in the number and modification of ribosomes can affect the growth and proliferation of tumor cells, suggesting that ribosomes were intensively associated with tumor cells [24]. Our study further confirms our research results and demonstrated the important function of ribosome-associated genes in the process of BC. Next, according to the expression levels of 34 ribosome associated genes, two ribosome associated subtypes were identified. The survival rate of BC patients in C1 was better than that in C2. CD8+ T cells in C1 were also higher than that in C2, and CD8+ T cells have a strong tumor-killing effect [25]. The ribosome signature of five ribosome-related genes (RPS18, RPL11, RPLP1, RPL27A, and RPL38) was determined by using single factor Cox analysis and LASSO analysis, and its accuracy and reliability were verified by the GEO dataset. In the risk model constructed with these five ribosome-related genes, we found that the number of macrophages and neutrophil infiltrates was significantly higher in the high-risk group. The malignant potential of breast cancer may directly influence the infiltration of neutrophils, and the more aggressive triple negative breast cancer (TNBC) is able to attract more neutrophils. They may promote cancer development and metastasis by creating a pro-inflammatory microenvironment [26]. Tumor-associated macrophages have the ability to influence the progression of TNBC by regulating the activity of hepatic leukemia factor (HLF) through secretion of transforming growth factor-beta1 (TGF-β1). This leads to an increase in the proliferation, metastasis, and resistance of TNBC cells [27]. However, the activity of immune checkpoint-related pathways was higher in the low-risk group than in the high-risk group. The level of immune checkpoint activity may not consistently align with the level of breast cancer risk, suggesting the presence of other influencing factors. The main KEGG results in the high-risk group were focused on inositol phosphate metabolism and ECM–receptor interaction. Detection of changes in the activity of the inositol phosphate metabolic pathway in patients with early-stage breast cancer has important clinical implications [28]. The ECM–receptor interaction signaling pathway was also identified as a potential contributor to the development of breast cancer [29]. RPS18 is a reference parameter in the demonstration of multiplex nucleic acid sequence-based amplification (NASBA) on microarray analysis for breast cancer diagnostics [30]. Previous research has demonstrated a correlation between high levels of expression of RPL11 and improved overall survival rates in breast cancer patients. This association has been considered a positive prognostic indicator, and is consistent with our results [31]. RPLP1 can indeed lead to the accumulation of reactive oxygen, which activates the MAPK1/ERK2 signaling pathway and enhances the growth of breast cancer cells [32]. tRNA-derived fragment-19-W4PU732S can target to inhibit RPL27A to accelerate the malignant activity of breast cancer cells [33]. RPL38 can be used as a potential target for immunotherapy of BC [34]. Our research still has some limitations. Firstly, the verification group has less samples. Since there were few arrays containing paired tumor and non-tumor samples of expression and clinical information, we have to choose gene expression profiles that combine multiple different array platforms to further validate our classification. Second, the prognostic gene sets identified in our study has not been validated in our clinical samples. In the future, we will devote more energy to evaluate the prediction effect of the above gene sets multicenter samples and explore their clinical application value. Therefore, further studies will be needed to confirm our results. Our study provides significant assistance to patients after mastectomy, who should be more concerned about changes in ribosome-related gene activity in nontumor tissues adjacent to BC. ## 5. Conclusions To sum up, three BC immune-related clinical subtypes were established based on changes in immune-related pathway activity in tumor and non-tumor tissues. The biological functions performed by ribosome-related genes in the three subtypes may determine the prognosis of BC patients. RRS can be a biological marker of prognosis for BC patients that might be of some benefit in BC treatment. Changes to ribosome-related genes in non-tumor tissues adjacent to BC samples should be focused upon further during the treatment of BC. ## References 1. 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--- title: 'Pirimicarb Induction of Behavioral Disorders and of Neurological and Reproductive Toxicities in Male Rats: Euphoric and Preventive Effects of Ephedra alata Monjauzeana' authors: - Latifa Khattabi - Aziez Chettoum - Houari Hemida - Walid Boussebaa - Maria Atanassova - Mohammed Messaoudi journal: Pharmaceuticals year: 2023 pmcid: PMC10051897 doi: 10.3390/ph16030402 license: CC BY 4.0 --- # Pirimicarb Induction of Behavioral Disorders and of Neurological and Reproductive Toxicities in Male Rats: Euphoric and Preventive Effects of Ephedra alata Monjauzeana ## Abstract Carbamate pesticides are a risk to human well-being, and pirimicarb is the most widely employed carbamate insecticide. This ongoing investigation aimed to reveal its toxicity on neurobehavioral and reproductive function. The study was carried out on male Wistar rats by assessment of behavioral changes via experiments, such as the forced swim test and the elevated plus maze; determination of oxidative stress (checking parameters such as catalase activity, etc.); measurement of cortisol and testosterone serum titers, and IL-1β levels in the plasma and brain; and evaluation of histopathological lesions that induced pirimicarb after 28 days of gavage, specifically in the brain and testis. Traces of pirimicarb were analyzed in tissue extracts using LCMS/MS. At the same time, the beneficial and protective effect of EamCE (Ephedra alata monjauzeana Crude Extract) were tested. The outcomes showed considerable anxiety and depressive status, with an evident increase in cortisol and IL-1β titers and an important decrease in oxidative enzymes and testosterone. Significant histological lesions were also recorded. In addition, the LCMS/MS analysis affirmed the accumulation of pirimicarb in organ tissue from rats force-fed with pirimicarb. Conversely, EamCE demonstrated outstanding potential as a preventive treatment, restoring cognitive and physical performance, boosting fertility, enhancing antioxidant and anti-inflammatory activities and preserving tissue integrity. We concluded that pirimicarb has critical deleterious impacts on health, affecting the neuroimmune-endocrine axis, and EamCE has a general euphoric and preventive effect. ## 1. Introduction Exposure to pesticides is expected for workers in their production and application; however, the public population can also be exposed from contaminated water and food. Pesticides have been extremely overused, and mostly uncontrolled in several developing countries. This may result in high exposure in large number of people and lead to more severe and widespread health effects [1]. Pesticide contamination comes from the circulation of the chemical through the target-treated part of the plants, resulting in environmental pollution. Such chemical residues impact human health via environmental and food contamination [2]. There are four common ways that pesticides can enter the human body: Dermal, oral, eye, and respiratory pathways. The toxicity of pesticides can vary depending on the type of exposure. As would be generally expected, the danger of pesticide contamination usually increases depending its concentration and its toxicity rate [3]. Highly hazardous pesticides are a risk to human well-being and the environment through enzymatic inhibition and the induction of oxidative stress [4]. Carbamate pesticides have been identified as disruptive agents of endocrine function, neuro-behavioral influencers, and having a role in increasing the risk of dementia [5]. Pirimicarb is a widely employed carbamate insecticide in apple orchards and in general, is considered to be a selective aphidicide [6]. Despite photodegradation and microbial degradation of pirimicarb, it has been proven [7] that pirimicarb still persists in some environmental matrices as a residue, notably in food [8,9,10]. Therefore, for this compound, food and water contamination present as the main ways to affect humans; however a video imaging technique has revealed vast deposition of pirimicarb on the bodies of greenhouse chrysanthemum workers [11], which is considered as direct exposure to pesticide nuisance. Furthermore, mammalian metabolism of pirimicarb involves hydrolysis of its moiety with subsequent demethylation at the dimethylamino group, resulting in the following metabolites that were detected in the urine samples of seven farmers who applied pirimicarb to their crops: 2-dimethylamino-5, 6-dimethyl-4-hydroxypyrimidine (DDHP), 2-methylamino-5,6-dimethyl-4-hydroxypyrimidine (MDHP), and 2-amino-5,6-dimethyl-4-hydroxypyrimidine (ADHP) [12]. There are few studies published concerning human toxicity of pirimicarb. These include a comparative study which was carried out to estimate the toxicity of nine pesticides, including pirimicarb, on three human cell lines (HepG2, HEK293, and JEG3) [13]. In addition, human volunteer investigations have been performed involving oral co-administration of pirimicarb (0.02 mg/kg/day) and chlorpyrifos-methyl at an acceptable daily intake, which is a very low (tolerable) concentration. Effectively, the results indicated no significant toxicokinetic interactions occurring between pirimicarb and chlorpyrifos-methyl when they were administrated together [14]. Otherwise, the majority of scientific surveys that were previously carried out on rodents and other laboratory animal models concerning the toxicity of pirimicarb only involved the compound in combination with other pesticide molecules, and not pirimicarb alone [15,16,17,18]. Due to the lack of data and the need for a better understanding of the toxicological effects of pirimicarb, we agreed the purpose of our study should be to elucidate the deleterious effects of pirimicarb on the brain, behavior, and reproductive system of male albino rats. We deliberately chose to investigate the preventive effects of Ephedra alata monjauzeana, as we were aware from our previous investigations [19] that this plant has many beneficial biological properties, namely antioxidant, anti-inflammatory, and others. More importantly, we consider this plant as a candidate for preventive effect due its ephedrine content [20,21]. Ephedrine has known neuroprotective effects against neuro-depression, ischemia injury and neurotoxicity [22,23,24,25]. In Algeria, Ephedra alata is used traditionally as a herbal tea to reduce stress, to enhance mood and to attenuate insomnia. ## 2.1.1. Forced Swim Test (FST) In the FST, animals in G3 spent the majority of their time immobile (more than $69\%$ of time) compared with control groups (G1 and G2) and G4 (treated with EamCE), in which a moderate amount of time was spent in swimming. Only 24.167 s was spent in escalation attempts; however, animals in the healthy groups spent the most time trying to climb (236.833 s (G1) and 226.500 s (G2)), as shown in Figure 1. ## 2.1.2. Open Field Test (OFT) Statistical analysis of OFT parameters showed that there were highly significant variations ($p \leq 0.001$). The total distance traveled by animals in the healthy control, EamCE control, and pirimicarb + EamCE groups was higher compared with the pesticide group (501.167 ± 3.656, 460.833 ± 3.817, 204.500 ± 3.271) vs. (94.000 ± 4.382) (Figure 2). Conversely, locomotor activity was significantly reduced in the group treated with pirimicarb, compared with the other control groups, and animals treated with the pirimicarb + EamCE complex. ## 2.1.3. Elevated Plus Maze (EPM) The locomotor activity of healthy controls animals (G1 and G2) was higher than that of animals treated with pirimicarb; this was evidenced by the total number of visits (11.167 ± 0.983 vs. 3.333 ± 0.816), (7.500 ± 1.049 vs. 3.333 ± 0.816). The same result was noted in the animals treated with pirimicarb + EamCE, which showed high locomotor activity compared with the animals treated with pirimicarb only. ( 11.667 ± 0.816 vs. 5.167 ± 1.472). Finally, we noted that the healthy control and EamCE-treated animals, and the animals treated pirimicarb + EamCE complex, spent the majority of time in the open arms of the device; this was well illustrated by the percentage of the time spent in the open fields (OF) of the device, as shown in Figure 3 (83.665 ± 0.731, 90.757 ± 1.244, 90.757 ± 1.244). At the same time, animals in the pirimicarb group spent the majority of their time (a percentage of 98.28 (±0.509)) in the closed fields (CF) of the device and a percentage of only 1.720 (±0.491) in the open parts (Figure 3). ## 2.1.4. Elevated Zero Maze (EZM) The latency of entering the open section for animals in the healthy control groups (G1 and G2) was lower than that of animals treated with pirimicarb (51.50 ± 1. 36 vs. 256.167 ± 0.983); (35.16 ± 1.47 vs. 102.333 ± 4.32). Conversely, the time spent in the open section was very high for healthy controls compared with animals treated with pirimicarb. In addition, the number of entries into the open section (EOS) and the number of head dips (HD) were most notable in the healthy groups, G1 (EOS): 8.16 ± 0.4, G2 (EOS): 5.5 ± 0.83, G1 (HD): 31.83 ± 1.32, G 22 (HD): 45.16± 0.40 and moderate in G4 animals treated with (pirimicarb + EamCE) complex, EOS: 3.5 ± 0.83, HD: 19.16± 1.32. But, both parameters were limited in the pirimicarb group, EOS (1.66 ± 0.81), HD (3.5 ± 0.83) (Figure 4). ## 2.2. Cortisol and Testosterone Titers The serum dosage of cortisol showed a noticeable elevation in cortisol titer for the pirimicarb group compared with the other groups (G3: 2.070 ± 0.118 > G4: 1.353 ± 0.053 > G2: 0.977 ± 0.038 > G1: 0.996 ± 0.006), as illustrated in Figure 5. In contrast, the testosterone titer (Figure 5) was lowest in the pirimicarb group and was at its highest level in the G2 animals treated with EamCE (G1: 4.908 ± 0.898, G2: 7.850 ± 0.388, G3: 0.809 ± 0.334, G4: 2.681 ± 0.166). *** $p \leq 0.001$ = very highly significant, and those with the same subscripts were not significantly different ($p \leq 0.05$). ## 2.3. Oxidative Stress Parameters Similarly, the tissue homogenates of the different organs studied had highly significant differences in the variation of protein concentrations ($p \leq 0.001$) (Table 1). MDA concentration was increased in G3, its value gradually decreasing from G4, to G2, to G1. Concentrations of GSH and catalase differed among the groups, being high in G1 and G2, moderately elevated in G4, and decreased in G3. The total findings are summarized in Figure 6. ## 2.4. IL-β Quantification The quantification of IL-1β in brain homogenate and plasma samples showed a significant increase in animals in the G3 treated with pirimicarb (478.66 ± 1.43 pg/mL and 504.66 ± 0.22 pg/mL, respectively), compared with basic levels of IL-1β registered in samples from healthy animals (G1: 150 ± 0.68 pg/mL in brain homogenate and 155 ± 0.51 pg/mL in plasma). Concerning animals in G2 and G4, the levels of IL-1β were nearer to the basic values in G1 and were significantly reduced compared with the levels recorded in G4 (Figure 7). ## 2.5. Photomicrographs of Histologic Sections Figure 8 demonstrates photomicrographs of the cerebral cortex of rats in different groups. Figure 9 shows photomicrographs of histological changes in the testis of animals in different groups. ## 2.6. UPLC-ESI-MS-MS Analysis of Brain and Testis The LCMS/MS analysis of extracts from brain and testis determined the presence of pirimicarb in all the tested extracts, the peaks for pirimicarb and its ion products (Table 2) are well represented in the chromatograms in Figure 10A–D corresponding to brain and testis extracts from rats in G3 and brain and testis extracts from rats in G4. Ion products structure is described in Figure 11. ## 3. Discussion Behavioral trials in rodents are utilized to estimate neurological traits and events, such as locomotor activity, depression-like behavior, socialization, memory, and other traits [26].The EPM and the OFT are some of the most widely employed procedures to investigate anxiety-like behavior in rats [27]. Moreover, the EZM has been proposed and validated as an apparatus for measuring anxiety status; however, the OFT has long been used for evaluating anxiety/fearfulness as well as locomotor/exploratory activity [28]. Likewise, the FST is also one of the most commonly used tests to assess depressive-like behavior in animal models [29]. The results obtained in the current study revealed the negative impact of pirimicarb on the behavior status of rats. In fact, in animals fed with pesticide (G3), the reduced total traveled distance, the minimized number of visits to the central area, and the increased duration of stay in the periphery zone and device corners indicated significantly decreased locomotor activity compared with control groups, and we noticed in G4 animals that the action of EamCE was clearly ameliorative. In addition, induced anxiety in the rats of G3 was significantly linked to reduced time spent in the open fields; increased time spent in the closed fields; fewer total number of entries into the open section; reduced frequency of head dipping; and extended latency to enter into the open section. Further, the climbing ability in FST was very feeble in affected rats of G3; they spent the majority of their time immobile. These deficiencies reveal clearly the diminution of the cognitive and locomotor competencies that would be sufficient to confirm the depressive effect of pirimicarb. Various negative effects on neuro-behavior have been previously recorded subsequent to exposure to a combination of different pesticides, even with safe doses (NOAEL) [30]. In the current study, this depressive effect was thoroughly reduced by the protective activity of EamCE in all the recorded behavioral parameters, with an obvious tendency to approach the values registered in the control groups. In point of fact, physical and cognitive performance in an anterior study was experimentally enhanced by the action of the major component ephedrine that was isolated from Ephedra alata plant, additionally to its many other potent pharmacological effects, notably for treating narcolepsy and depression [31]. Depressive and anxiety-like behaviors trigger the secretion of glucocorticoids [32,33]. Upon exposure to persistent or repetitive stress, this leads to already sensitive stress pathways become markedly hyperactive and, consequently, increases in cortisol secretion persist, which may cause alterations in glucocorticoid receptors and therefore contribute to the pathogenesis of mood and anxiety disorders [34]. Our findings appear to endorse the latter point because plasma titers of cortisol were high in anxious and depressive rats in the group treated with pirimicarb as a chemical stressor agent. The brain has long been considered a privileged organ, from an immunological point of view, since the blood–brain barrier and its tight junctions prevent the transmigration of systemic immune cells [35]. Cytokines are chemical messengers that stimulate the hypothalamus pituitary adrenal axis (HPA) axis when the organism is under stress or an infection, acting as endocrine factors to regulate hormone secretion and feedback control of the HPA axis. They transmit information from the immune compartments to the central nervous system as immunotransmitters and function in immunomodulatory neuroendocrine circuits [36]. Systemic immunological stressors elicit extended activation of the HPA axis, mainly due to the release of pro-inflammatory cytokines (IL-1, IL-6 and TNF-α) from stimulated peripheral immune cells [37]. There is ample evidence to support the association between increased cortisol and pro-inflammatory cytokines (IL-1β, IL-6, IL-8, TNF-α) in negative mood conditions, stress levels, anxiety, and depression [38]. IL1-β stimulates the production of mesencephalic astrocyte-derived neurotrophic factor (MANF), through its specific receptor type 1 (IL-1 R1) [39]. Astrocytes are usually described as maintenance cells that participate indirectly in nerve transmission. They are now known to participate in the inflammatory response in acute brain injury by modifying their morphological and functional phenotype; by expressing the major histocompatibility complex (MHC), cytokines, and chemokines; and by producing NO via over-expression of inducible NO synthase (iNOS) [40]. More than that, IL-1 aggravates brain damage and its pharmacological blockade or transgenic mutation of the IL-1 receptor reduces the size of the lesion and the behavioral dysfunction [41]. Given the above, we assume that the finding of high levels of IL-1β in both plasma and, notably, in brain homogenate of the pirimicarb-exposed animals had a direct and/or indirect action on the activation of HPA axis, the elevated titer of cortisol, the neurobehavioral disturbances and observed neurodegeneration. Vice versa, we strongly assert that cortisol enhanced the production of IL-1β from peripheral immune cells; this correlation has previously been proven [42]. Regarding the role of EamCE and the reduced release of IL-1β, we do associate this with the anti-inflammatory effect of the plant [19,43]. Importantly, Ephedra alata Decne has already shown the ability to reduce the production of pro-inflammatory cytokines [44]. The outcomes of oxidative stress assessment in our study illustrated the genesis of a substantial profile of oxidative stress, affecting both tissues of interest—the brain and testis. Indubitably, we refer to the samples from the pirimicarb-treated group of rats. Lipids are susceptible to oxidation, and lipid peroxidation products are potential biomarkers for oxidative stress status and its related diseases in vivo. Lipid peroxidation products in biological samples have been widely assessed; aldehydes such as MDA have been considered as a marker of lipid peroxidation in vivo [45]. Undoubtedly, the concentration of MDA as an oxidative stress indicator was increased in G3 rats exposed to pesticide, compared with the reduced concentration in G4, G2 and G1. A review work has reported that disturbances of MDA, GSH and SOD were associated with recurrent depressive disorder and lowered levels have been found in depressed patients compared with healthy volunteers [46]. Several investigations have been performed to evaluate the toxic effect of various types of pesticide and prove their ability to induce oxidative stress, as prominently indicated by low titers of antioxidant factors such as GSH, SOD, and catalase, and high concentrations of MDA [47,48] in brain tissue [49,50,51] and the male reproductive system [52,53,54], in the context of provoking neuro and reproductive male toxicities. Reactive oxygen species (ROS) are released as a result of normal cellular metabolism at low-to-moderate rates; they react normally in physiological cell processes, but higher amounts produce detrimental changes in cell elements, such as lipids, proteins, and DNA. The alteration of the oxidant/antioxidant balance in favor of oxidants is called “oxidative stress”. It may contribute to several health issues, including cancer, neurological disorders, hypertension, ischemia, diabetes, acute respiratory distress syndrome, etc. [ 55]. We suggest that pirimicarb exerted an inhibitory effect towards the antioxidant enzymes such as SOD and catalase, which may have resulted in an increase in ROS amounts (resulting even from pirimicarb metabolism) that in turn caused the elevation of MDA, the decrease in GSH, and the promotion of toxicological manifestations. A previous study noted changes in human red blood cell antioxidant enzymes in subjects with long-term exposure to pesticides. The most important finding was the reduction in SOD and catalase activities, with significant lower levels compared with controls in both the long and the short duration of pesticide exposure [56]. Nevertheless, the authors strongly presume that, EamCE enhanced the antioxidant potential of rats fed with the extract and protected them from damage caused by pirimicarb, notably the oxidative stress engendered in G4 rats. Ephedra alata has been widely exploited in different biological investigations. Unquestionably, the in vitro and in vivo antioxidant, anti-inflammatory, analgesic, antipyretic, antidiabetic, antihypolipidemic, antihemolytic, and antithrombotic activities of Ephedra alata extracts were efficiently performed, being rich in terms of polyphenol and flavonoid content [43,57,58,59,60,61,62]. Antioxidant phytochemicals, such as polyphenols and flavonoids, induce the high expression and activation of antioxidant enzymes, namely, catalase, SOD, glutathione peroxidase, and glutathione reductase. These plant components have electrophilic activity and can favor antioxidant enzymes via the Kelch-like ECH-associated protein 1-NF-E2-related factor-2 pathway and antioxidant responsive elements [63]. Histological examination of rats in control groups G1 and G2 showed brain sections with normal histological architecture with no lesions (Figure 8a,b). In the brain sections of pirimicarb-treated rats, the parenchymatous cells of the cerebral cortex showed degeneration and liquefactive necrosis, characterized by partial or complete dissolution of dead tissue and transformed into a liquid, viscous mass [64]. Prominent vacuolization was also identified; this was previously considered a side effect of the action of cytotoxic factors and its accumulation an important initiating event, causing metabolic alterations or stress responses that lead to cell death [65]. In addition, some glial cells showed pyknotic nuclei and numerous congested blood vessels (Figure 8d–f); these deleterious aspects have been determined in numerous neurotoxicity studies induced by pesticides or other toxic chemicals [66,67,68]. In contrast, the brain sections of G4 rats showed almost normal morphological appearance of nerve cells with less fine vacuolization. No pathological changes were observed in testicular sections of untreated control animals. Indeed, microscopic examination of testicular tissue of rats in the control group showed normal histological architecture with normal seminiferous tubules showing all cell layers of germinal cells and a spermatozoa-filled lumen (Figure 9, G1). However, EamCE (200 mg/kg) treated rats (G2) showed an increase in the number of spermatozoa and round spermatids (Figure 9, G2). Testes of rats treated with 147 mg/kg of pirimicarb (G3) showed marked histological changes characterized by reduced diameter; a markedly reduced number of spermatozoa; seminiferous tubules showing a disrupted germinal epithelium with various degree of atrophy; degeneration and necrosis with a prominent increase in interstitial space; and a reduced number of Leydig cells (Figure 9, G3). Rats receiving pirimicarb with EamCE (G4) showed a tendency towards a return to normal testicular histology indicated by a markedly developed germinal epithelium, and with almost a normal number of Sertoli cells and Leydig cells (Figure 9, G4). Moreover, the presence of spermatozoa was observed in the lumen of seminiferous tubules. The ongoing hispathological manifestations were accompanied by a raised level of cortisol and a decline mainly in the testosterone hormone. Previously, researchers have found that long-term exposure to deltamethrin (pesticide) caused alteration of reproductive hormones, including serious dysfunction of testicular tissue in which cortisol and testosterone levels were inversely proportional [69]. An earlier study that corroborates our findings on the potential role of carbamate pesticides interference on the natural hormones of the hypothalamic–pituitary–thyroid that result in disturbances of the male reproductive system. It reported that there is evidence that exposure to carbamates leads to lower levels of gonadotropin-releasing hormone (GnRH), luteinizing hormone (LH) and/or follicle-stimulating hormone (FSH), thus compromising steroid genesis and spermatogenesis. Furthermore, various histologic alterations have been demonstrated in the testis along with deficiency of male reproductive capacity [70]. The protective effect of EamCE regarding testicular tissue integrity and boosting fertility via enhancing spermatogenesis and increasing testosterone level, could probably be explained by the effect of saponins [71,72] and ephedrine alkaloids [73,74] that are contained in the plant crude extract. In effect, saponins have been known as substances responsible for, and enhancers of, an aphrodisiac effect due to their ability to increase androgen hormones [75,76]. In addition, we also observed, from a few days after starting the experiment, and frequently until the day of sacrifice, some sexual behaviors in the G2 (EamCE control) fed rats, such as mounting and intermission, that strongly explain the presumed fertilizing and aphrodisiac effects of EamCE. Contrary to organophosphate poisoning, carbamate poisoning normally starts to diminish within a few hours and disappears after 24 h, usually without any permanent sequelae. Carbamates commonly do not traverse the blood–brain barrier as easily as organophosphates; as such, brain injuries with carbamates occur with a lower frequency and are less severe than with organophosphates [72]. In another study, it was reported that central nervous system symptoms are not particularly noticeable in carbamate poisoning due to the poor permeability of these compounds across the blood–brain barrier [73]. A molecule can be totally ($100\%$) absorbed from a given formulation; however, it may have low bioavailability before being broken down after absorption [74]. Pesticides are generally distributed in the organism due to their ability to bind with plasma proteins, blood cells, and lipids in various organs and peripheral tissues. The binding potential is determined by the lipophilicity, which increases the pesticide’s successive bioaccumulation. Thus, the lipophilicity of compounds can truly alter their bioavailability [75]. According to the Swiss ADME prediction online platform [76], pirimicarb has a lipophilicity with a log Po/w of 3.39 and with a score of bioavailability equal to 0.55, which are sufficient values for a molecule to accumulate and engender its different modes of action. LCMS/MS-MRM analysis in the current study has effectively allowed us to confirm simulation data and find pirimicarb in brain and testis tissues from animals orally administered pirimicarb (rats in G3 and G4). The revelation of pirimicarb in brain and testis disclose that this molecule is resistant to different mechanisms of biotransformation and metabolism in the rat organism; in this case, pirimicarb bioavailability increased and the molecule was able to infiltrate many types of tissue. Renal excretion of unchanged drug has only a modest role in the complete elimination of many chemicals as long as lipophilic compounds filtered through the glomerulus are mostly reabsorbed into the systemic circulation during passage through the renal tubules [77]. Finally, we have summarized the impact of pirimicarb in the current study, and the proposed mechanism of action of EamCE with candidate metabolites at each level of interaction is Figure 12. ## 4.1. Chemicals and Reagents Pirimor 50 DG was obtained from Syngenta; sodium chloride (NaCl), Bradford reagent, bovine serum albumin (BSA), Trizma (tris), TCA (trichloroacetic acid), thiobarbituric acid (TBA), hydrogen chloride (HCl), 5,5-dithio-bis-(2-nitrobenzoic acid (DTNB), ethylenediaminetetraacetic acid (EDTA), pyrogallol, hydrogen peroxide (H2O2) $30\%$, monosodium phosphate (NaH2PO4,2H2O), disodium phosphate disodium phosphate (Na2HPO4,2H2O), potassium phosphate monobasic (KH2PO4), acetonitrile ≥ $99.8\%$, formic acid 98–$100\%$, magnesium sulfate (MgSO4), and activated charcoal were all obtained from Sigma Aldrich; ethanol $96\%$ xylene and formaldehyde 37–$38\%$ were obtained from PanReac AppliChem; Certistain was obtained from Merck, Mayer’ hematoxylin was obtained from Specilab, and neoxylene was obtained from Eukitt. ## 4.2. Animals Twenty-four albino Wistar male rats were purchased from Algiers Pasteur Institute (IPA), weighting 190 g–230 g and underwent an acclimatization period of 15 days before beginning the experiment. The rats were kept at 22 ± 2 °C and 50–$60\%$ humidity under a light/dark cycle of 12 h and had free access to standard commercial pelleted feed (supplied by ‘‘ONAB” Guelma, Algeria) and clean tap water ad libitum at the animal laboratory of CRBt. ## 4.3. Experimental Design In order to induce subacute toxicity, we followed different protocols [49,77,78,79] to constitute our own. The animals were divided in four groups (6 rats/each) that received different treatments by oral gavage: G1, deionized water; G2, 200 mg/kg of EamCE [19]; G3, 14.5 mg/kg ($\frac{1}{10}$ of LD 50 (145 mg/kg)) of pirimicarb [12,15,80,81]; and G4, 14.5 mg/kg ($\frac{1}{10}$ of LD 50 (145 mg/kg)) of pirimicarb + 200 mg/kg of EamCE (the EamCE was administrated 1h before administrating pirimicarb). These daily repeated doses were given for a period of 28 days. Thereafter, the animals were subject to three successive days of behavioral examination (Figure 13). Subsequently, animals were euthanized by cervical dislocation; blood tissue and some organs (brain, liver, spleen, kidney and testicles) were collected for carrying out further investigations. All procedures were accomplished in accordance with laboratory guidelines for animal care, Algerian Executive Directive (18 March 2004, N◦ 10–90 JORA) and Law No.88-08 of 26 January 1988 relating to veterinary medicine activities and the protection of animal health (N◦ JORA: 004 of 27-01-198). ## 4.4.1. Forced Swim Test (FST) The FST in rats is a preclinical behavioral model that has good predictive validity and is widely used to determine the efficacy of antidepressant drugs (ADS) [82]. For the current study, our purpose was to check the eventual depressant effect of pirimicarb. Therefore, we executed the FST [83] with some modifications. We eliminated the first step (pre-test) that consisted of inducing a stressful situation in rats, because the rats were supposed to be already depressed under the effect of pirimicarb. Therefore, the animals were directly immersed in an aquarium (54 cm high by (34 × 60 cm) base area; these dimensions ensure that the rat cannot escape by clinging to the edges of the device) for five minutes. The behavior of the animal in the device was filmed using a video camera. The aquarium was filled with warm water (26 °C) up to a height of 40 cm, in order to ensure that the rat would not use its lower limbs to stay on the surface and therefore be forced to swim. We then proceeded to analyze the sequences and measure the time spent in immobility, swimming and climbing (escalation). ## 4.4.2. Open Field Test (OFT) The locomotor activity of rats was measured using a device consisting of a rectangular wooden enclosure 1 m in diameter and 50 cm high, divided into 7 parts each of the same area: a central part and six peripheral parts. The central part serves as a starting point for the animals in each test. The animals are placed in the device for 10 min. Locomotion in the OFT was evaluated by noting the total distance traveled, the number of entries in the central part and the number of redress. These cumulative indices gave us the total locomotion index for rats in the device [84]. ## 4.4.3. Elevated Plus Maze (EPM) The EPM device was in a form of a cross raised to a height of 40–60 cm from the ground. It consisted of a central part (10 × 10 cm), and two open protected arms without walls (50 × 10 × 50 cm) which oppose two other arms with closed walls, which are perpendicular to the open protected arms. The test lasts 5 min and begins when the rat is placed in the center of the maze, facing an open arm. An animal that explored within the open arms was described as being “slightly anxious” and an animal that remained confined in the closed arms of the device was described as being “anxious”. Two types of variables were identified: classic variables [85,86] and more ethological variables taken from the defensive behavioral repertoire of rodents [87]. ## 4.4.4. Elevated Zero Maze (EZM) The EZM was an elevated annular runway with alternating open and enclosed quadrants (105 cm diameter, 10 cm width) 65 cm above from the ground level, divided equally into four areas; this updated device helped to remove any uncertainty of interpretation regarding the time lost on the central square of the traditional design and allowed uninterrupted exploration [88]. Latency to enter into an open section, time spent in the open sections, number of entries in the open sections and number of head-dips were measured for 5 min [28]. ## 4.5. Cortisol and Testosterone Titers Serum titers of cortisol and testosterone were quantified using Abbott Alinity automaton with their respective specific kits (Alinity 08P3320, Alinity 07P6821). ## 4.6.1. Tissue Homogenate The organs were immediately collected, washed using $0.9\%$ NaCl solution and weighed; 1 g of each organ was put in 2 mL of TBS (Tris-buffered saline): Tris 50 mM, NaCl 150 mM, adjusted to pH = 7.4 with HCl 1 M. The mix was homogenized using a “SONICS, Vibra-Cell VX 130” sonificator, under ice-cold conditions. Homogenates were centrifuged at 3000× g for 30 min at 4 °C. The supernatants were then aliquoted and stored at −20 °C. ## 4.6.2. Protein Titration Proteins from tissue homogenates were quantified spectrophotometrically at 595 nm according to the modified method of Bradford [89], using bovine serum albumin as standard. ## 4.6.3. Malondialdehyde (MDA) The evaluation of lipid peroxidation levels was accomplished by detecting the value of MDA in organ homogenates. MDA reacts with thiobarbituric acid as a reactive substance to generate a red-colored complex. The procedure involved combining 500 µL of tissue homogenate with 1 mL of TCA-TBA-HCI ($15\%$, $0.375\%$, 0.25 N) and mixing thoroughly. The mixture was heated in a boiling water bath for 15 min. Then, the flocculent precipitate was removed by centrifuging at 1000× g for 10 min and the absorbance was measured at 535 nm [90]. ## 4.6.4. Reduced Glutathione (GSH) GSH levels of organ homogenates were measured by employing a colorimetric technique based on the oxidation of GSH by DTNB, which generates a yellow color according to the Elman method [91]. Tissue homogenate (400 µL) was added to 100 uL of sulfosalicylic acid ($0.25\%$) and left for 15 min in an ice bath. After centrifugation at 1000 rpm for 15 min, 250 µL of supernatant was collected and added to 500 µL mL of Tris-EDTA buffer (0.4 M HCl, 0.02 M EDTA, pH 9.6) and 12.5 µL of DTNB (0.01 M). After shaking and incubation for 5 min, the absorbance was recorded at 412 nm. ## 4.6.5. Superoxide Dismutase (SOD) The SOD activity was estimated according to the Marklund and Nandy procedures [92,93] with slight changes. The method was based on inhibition of the auto-oxidation of pyrogallol by SOD. An 850 µL quantity of Tris HCL buffer (50 mM, pH = 8.2) was added, followed by 100 µL of EDTA (10 mM). Then, the reaction was started by the addition of 50 µL of pyrogallol (2.5 mM in 10 mM HCL). The absorbance reading was taken at 420 nm every minute for 3 min in the presence or absence of 20 µL of tissue homogenate sample. SOD activity was expressed as U/mg protein. One unit of SOD activity (U) was determined as the amount of enzyme required to inhibit $50\%$ of pyrogallol autoxidation. ## 4.6.6. Catalase (CAT) CAT activity was evaluated following the procedure of Aebi [94]. In brief, 983.5 μL of H2O2 (10 mM, prepared in 50 mM phosphate buffer (KH2PO4, Na2HPO4), pH = 7.2) was added to 16.5 μL of tissue homogenate. The reaction was based on the disappearance of hydrogen peroxide, and the decrease in absorbance was monitored for 30 s at 240 nm. ## 4.7. IL1-β Titration and Quantification in Brain and Plasma The level of Il-1β was quantified from brain homogenates and plasma samples, using Rat IL-1β ELISA Kit, E-EL-R0012 (Elabscience Biotechnology Inc.: Houston, TX, USA). The generation of a standard curve and quantification steps were executed according to the manufacturer’s handbook. ## 4.8. Histopathological Examination No treatment-related deaths were evident. Sacrificed rats were subjected to a full necropsy examination. Organs were then removed and examined for any gross lesion after being rinsed with NaCl ($0.9\%$) solution thoroughly and properly. Then, they were immediately fixed in formaldehyde solution ($10\%$). Tissue samples were routinely processed through an automatic tissue processor. After that, the tissues were embedded in paraffin, sectioned, and stained with hematoxylin and eosin (H&E) according to the technique described by [95]. Photomicrographs of selected lesions were taken using an optical microscope with an integrated camera (BioBlue Euromex (EU 2131898)) and treated by Image Focus plus V2. ## 4.9.1. Pirimicarb Extraction A 0.33 g tissue fragment from each animal target organ (brain and testis) was mixed and stirred vigorously with 10 mL of distilled water, 10 mL of acetonitrile, 4 G of MgSO4 and 4 G of NaCl. After that, it was centrifuged at 4500 rpm, 15 °C for 5 min. The supernatants were collected, and 2 g of MgSO4 and 25 mg of activated charcoal were added. The newly constituted mixture was centrifuged under the same previous conditions, and the supernatants were recovered, filtered through a 0.22 µM filter and evaporated. Next, the extract was dissolved with a small quantity of acetonitrile and stored at 20 °C before analysis [96]. ## 4.9.2. UPLC-ESI-MS-MS Analysis The tissue extracts were analyzed using the LC-MS/MS method in multiple reaction monitoring (MRM) mode. The analysis was performed using UPLC-ESI-MS-MS Shimadzu 8040 Ultra-High sensitivity with UFMS technology and equipped with binary bump Nexera XR LC-20AD. The ESI conditions were as follows: CID gas, 230 KPa; conversion dynode, −6.00 Kv; interface temperature, 350 °C; DL temperature, 250 °C; nebulizing gas flow, 3.00 L/min; heat block, 400 °C; and drying gas flow, 15.00 L/min. The MRM transition was accessed from Shimadzu Pesticide MRM Library Support for LC/MS/MS. The pump mode was isocratic, and the mobile phase contained: $15\%$ A water, $0.1\%$ formic acid, and $85\%$ B Acetonitril. The flow rate was: 0.2 mL/min and the injected volume of extracts was 5 µL, using a Restek column of force C18 1.8 µm 50 × 2.1 mm. ## 4.10. Statistical Study The outcomes of our experiments were expressed as means and standard deviations related to six values for each group and each studied parameter. Variance analysis was conducted on XLSTAT Version 2016.02.28451 using ANOVA, the significance of differences was checked using Tukey’s HSD test. Values with different subscripts (a, b, c, d, e) in the same parameter were significantly different compared with the healthy group G1 (* $p \leq 0.001$ = very highly significant, $p \leq 0.01$ = highly significant, * $p \leq 0.05$ = significant), and those with the same subscripts were not significantly different ($p \leq 0.05$). ## 5. Conclusions Pesticides are recognized as producing toxicological effects with various modes of action. Indeed, the outcomes of the prevailing research gave us sufficient insight about pirimicarb toxicity on neurobehavior and reproductive system. The proven accumulation of pirimicarb in the brain and testis explained perturbations of behavior and mood, induction of oxidative stress, and inflammation status with serious lesions in brain tissue and testis. These manifestations are characteristic of traumatic disorders such as dementia and infertility. In the long term, they may lead to more severe consequences, such as cancer malignancies and death. EamCE from Ephedra alata monjauzeana offered significant protection from pirimicarb damage due to its antioxidant, anti-inflammatory, fertilizing and euphoric potential. 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--- title: Impact of Postharvest Putrescine Treatments on Phenolic Compounds, Antioxidant Capacity, Organic Acid Contents and Some Quality Characteristics of Fresh Fig Fruits during Cold Storage authors: - Emine Kucuker - Erdal Aglar - Mustafa Sakaldaş - Fatih Şen - Muttalip Gundogdu journal: Plants year: 2023 pmcid: PMC10051898 doi: 10.3390/plants12061291 license: CC BY 4.0 --- # Impact of Postharvest Putrescine Treatments on Phenolic Compounds, Antioxidant Capacity, Organic Acid Contents and Some Quality Characteristics of Fresh Fig Fruits during Cold Storage ## Abstract The storage and shelf life of the fig, which has a sensitive fruit structure, is short, and this results in excessive economic losses. In a study carried out to contribute to the solution of this problem, the effect of postharvest putrescine application at different doses (0, 0.5, 1.0, 2.0, and 4.0 mM) on fruit quality characteristics and biochemical content during cold storage in figs was determined. At the end of the cold storage, the decay rate and weight loss in the fruit were in the ranges of 1.0–$1.6\%$ and 1.0–5.0 %, respectively. The decay rate and weight loss were lower in putrescine-applied fruit during cold storage. Putrescine application had a positive effect on the changes in fruit flesh firmness values. The SSC rate of fruit varied between 14 and $20\%$, while significant differences in the SSC rate occurred depending on storage time and putrescine application dose. With putrescine application, the decrease in the acidity rate of the fig fruit during cold storage was smaller. At the end of the cold storage, the acidity rate was between 1.5–$2.5\%$ and 1.0–5.0. Putrescine treatments affected total antioxidant activity values and changes occurred in total antioxidant activity depending on the application dose. In the study, it was observed that the amount of phenolic acid in fig fruit decreased during storage and putrescine doses prevented this decrease. Putrescine treatment affected the changes in the quantity of organic acids during cold storage, and this effect varied depending on the type of organic acid and the length of the cold storage period. As a result, it was revealed that putrescine treatments can be used as an effective method to maintain postharvest fruit quality in figs. ## 1. Introduction The interest in the fig, which is a symbol of a healthy and long life and is seen as being sacred, is increasing day by day because the fig is rich in fiber, amino acids, vitamins, carotenoids, minerals, antioxidants, sugars, organic acids, and sodium, because it is fat- and cholesterol-free, and due to its different evaluations [1]. Although the consumer preference for figs is fresh consumption, the fig’s postharvest life is short due to the sensitive structure of the fresh fig fruit, and therefore dry consumption of figs is greater than fresh consumption. The short storage and shelf life causes significant economic losses during marketing processes [2] and limits fig cultivation. Fig is a climacteric fruit species, and when fruit for fresh consumption are harvested at eating maturity, their ripening continues after harvest [2]. For this reason, the fig’s fruit sensory quality characteristics are quickly lost. In order to contribute to the solution of this problem, applications of Aloe vera [2], calcium chloride [3], chlorine dioxide [4], modified atmosphere packaging, a nanomist humidifier [5], and sodium hydrosulfide have been used to maintain the fruit quality of figs for a longer postharvest period. However, no study has been conducted about the application to figs of polyamines [6], which are claimed to prolong shelf life in fruit. Polyamines such as putrescine, spermidine, and spermine, which have basic functions in living organisms, play a role in many biological processes, including cell division, cell elongation, embryogenesis, root formation, floral initiation and development, fruit development and ripening, and pollen tube growth and senescence, and in response to biotic and abiotic stress in plants [7,8,9,10,11]. Polyamines, which play a role in growth and development processes in plants, can delay ripening by slowing the respiration rate and ethylene production in fruit, reducing postharvest softening and chilling damage, and increasing resistance to diseases [12]. Previous studies have examined postharvest polyamine applications such as melatonin, putrescine, and spermidine. It has been reported that postharvest melatonin application delays senescence, increases resistance to chilling damage, and protects fruit quality by increasing resistance to diseases in fruit species such as litchi [13], mango [14], orange [15], peach [16], banana [17], sweet cherry [18], pear [19], pomegranate [20], plum [21], and kiwifruit [22] during postharvest storage. Putrescine maintains membrane integrity and delays the removal of epicuticular waxes, which play an important role in water exchange through the skin. Therefore, putrescine may be used to prolong storability and increase shelf life in fruit during cold storage. The aim of this study, which we planned based on the potential of putrescine, was to determine the effect of putrescine applied in different doses after harvest on fruit quality characteristics and biochemical content of figs during cold storage. ## 2.1. Weight Loss, Decay Ratio, and Fruit Firmness Weight loss, which increased proportionally with the cold storage period, was higher in the fruit of the control treatment (Figure 1). Supporting the study result, Candir et al. [ 23], Rasouli et al. [ 24], Byeon and Lee [25], and Ozturk et al. [ 26] reported that the weight loss resulting from the evaporation of water in the fruit by transpiration [27], and causing significant economic damage [28], increased proportionally with the storage time. Polyamines, which delay aging in fruits, decrease as maturity progresses, and this negatively affects the textural properties and storage time of fruit [29]. However, weight loss during storage can be reduced by the use of polyamines such as melatonin and putrescine, which delay cell wall degradation [30,31] and cause low respiration in fruit [32,33]. Indeed, Fawole et al. [ 34] suggested that putrescine treatment may reduce weight loss in fruit by consolidating the permeability of tissues and cell integrity. Considering this issue, in our study aimed at prolonging postharvest life, it was found that putrescine treatment reduced weight loss during cold storage, but the application dose was not effective (Figure 1). Similarly, Kibar et al. [ 35] reported that the application of putrescine to peach reduced weight loss during cold storage, due to the lower respiration rate in putrescine-applied fruit. Significant changes in the decay rate occurred during cold storage. The decay rate increased with all applications in the first 7 days of cold storage. There were significant differences between the treatments in the measurements made during this period, where the lowest decay rate was recorded in fruit with applied doses of 1 and 4 mM of putrescine, and the highest values were recorded with the control application. The decay rate increased continuously with the control application during the cold storage period; the decay rate of the putrescine-applied fruit decreased on the 14th day of cold storage and significant differences occurred depending on the application concentration. At the end of cold storage, the highest decay rate was recorded with control and 1 mM putrescine applications, while the lowest decay rate was in 0.5 and 4 mM putrescine-applied fruit (Figure 2). Polyamines such as putrescine and spermidine, which have anti-pathogenic properties, significantly reduce rot and chilling damage in fruit during postharvest storage [36]. Previous studies have shown that polyamine applications decrease rot and chilling damage and maintain fruit quality during cold storage in peach [35,37], pomegranate [38], apricot [39], and papaya [36]. Fruit flesh firmness, which decreases as fruit maturity progresses as a result of the degradation of the cell wall components, such as pectin substances, hemicellulose, and cellulose, and the decrease in turgor pressure in the cell [40], is an important quality parameter that determines the storage potential of the fruit [41,42]. Fruit flesh firmness, which has an important effect on marketing and postharvest processes in fruit, decreases with the progress of the ripening. Previous studies have reported that the softening in the fruit flesh firmness occurred in fruit species such as jujube [43], [26], orange [24], pomegranate [23], sweet cherry [44], cherry laurel [45], and fig [46,47,48]. After harvest, the fruit flesh firmness values increased until the 7th day of cold storage, followed by a decrease, and the lowest values were obtained at the end of cold storage. The putrescine application affected the changes in the fruit flesh firmness values, with the lowest values recorded in the 2 mM putrescine-applied fruit and control applications during cold storage. At the end of cold storage, it was observed that the fruit flesh firmness was higher in the fruit treated with 0.5 mM putrescine (Figure 3). Polyamines, which delay ripening by changing the stability of the cell wall in fruit, contribute to the maintenance of fruit flesh firmness after harvest. In previous studies, it has been reported that putrescine application maintained fruit flesh firmness in fruit species such as plum [49,50], peach [35,51], and papaya [36]. ## 2.2. Soluble Solids Content and Titratable Acidity Soluble solid content and titratable acidity, which are effective in determining the quality of the fruit and its acceptability by the consumer, are important fruit characteristics that affect the postharvest storage period. As the maturity of the fruit progresses, the amount of SSC increases while the acidity rate decreases [52]. Consistent with this explanation, there was no significant change in the amount of SSC with control treatment during cold storage in the study. However, a lower SSC rate was measured in putrescine-treated fruit during cold storage compared to harvest. The significant differences in the SSC rate occurred depending on the cold storage time and putrescine application dose. For example, with applications of 0.5 and 2 mM, the SSC rate during cold storage decreased steadily. It was determined that there was a decrease in the SSC rate in the first week of storage in 1 mM putrescine-applied fruit, no change during the 2nd week, and an increase during the 3rd week. At the end of the cold storage, the lowest SSC ratio was measured in 2 mM treated fruit while the highest value was recorded in control fruit (Figure 4). As ripening progresses, the acidity rate decreases. In the study, it was observed that there was a decrease in the titratable acidity rate in all applications during the first week of storage. At the end of cold storage (day 21), the highest titratable acidity was recorded in control fruits, and the lowest acidity was recorded in fruits treated with 1 mM putrescine. As a result, it was determined that the effect of putrescine application dose on the acidity rate of the fig fruit during storage is important (Figure 5). Putrescine, which delays ripening by reducing ethylene production in fruit, also reduces the changes in SSC and TA ratios after harvest [50]. In previous studies, it was suggested that the changes in the SSC and TA ratios were lower with putrescine application in species such as plum [50], peach [35,51,53], and papaya [36]. ## 2.3. Total Phenolics and Total Antioxidant Activity Phenolic compounds, which are the most important antioxidant components in fruit and can change depending on genetic factors, temperature, and environmental conditions during postharvest storage [54], decompose and gradually decrease with the prolongation in the storage period [55]. Putrescine application affected the total phenolic content, which generally decreased during storage, but inconsistencies occurred in this effect. The highest total phenolic value was obtained in 0.5 mM putrescine-applied fruit in the first week of cold storage, and it was determined that there was no difference between other applications. Significant differences occurred between all applications during the second week of cold storage. At the end of cold storage, the highest values were recorded with putrescine applications of 2 and 4 mM, and the lowest values were recorded in fruit treated with 1 mM of putrescine (Figure 6). Putrescine application affected the total antioxidant activity values, which varied depending on the storage period and the applications. However, the changes in total antioxidant activity occurred depending on the putrescine application dose. At the end of cold storage, there was no difference between the total antioxidant activity values of fruit treated with 2 or 4 mM of putrescine, while the lowest values were recorded in fruit treated with 1 mM of putrescine, and the highest values were recorded in fruit of the control application (Figure 7). Indeed, Davarynejad et al. [ 56] reported that putrescine application was found to affect the total phenolic content and antioxidant activity of plum fruit during cold storage, with the effect varying depending on the application dose, and the most effective application dose being 4 mM. Furthermore, Kibar et al. [ 35] suggested that the change in total phenolic and antioxidant activity after harvest in peach was lower with putrescine application, and putrescine application of 1.6 mM was more effective. ## 2.4. Specific Phenolic Compounds Polyphenolics are secondary metabolites that increase the quality and antioxidant properties of fruits and vegetables, such as firmness, flavor, bitterness, and color, and contribute to the defense mechanism of the plant [57]. Polyamines including melatonin, spermidine, and putrescine, which remove reactive oxygen species (ROS) and induce the gene expression of antioxidant enzymes in plants [13,58], are also used to improve fruit quality by increasing the level of some beneficial compounds, such as sucrose, natural antioxidants, phenolics, aroma components, polyphenolics, and soluble solids in fruit [19,59,60]. Polyamine application may cause an increase in the content of compounds such as amino acids, anthocyanins, phenols, and flavonoids in fruit after harvest [13,60,61]. In this study, protocatechuic acid was the individual phenolic having the highest quantity in figs, followed by chlorogenic acid, gallic acid, ferulic acid, syringic acid, and p-coumaric acid, in order. The quantity of these individual phenolic compounds decreased with prolonged storage time. The decrease in the quantity of phenolic acids both during and at the end of cold storage was lower in putrescine-treated fruit. It was determined that putrescine application concentration was effective in the maintenance of phenolic acids after harvest (Table 1). Rutin and catechin concentrations decreased proportionally with the storage time, while epicatechin and hydrocinnamic acid concentrations increased. It was observed that putrescine application had an effect on flavonoid compounds during cold storage, but this effect varied depending on the application concentration and flavonoid compound. Considering the measurements taken at the end of the cold storage, it was observed that putrescine application was effective in maintaining rutin and epicatechin concentrations, but had no effect on hydrocinnamic acid concentration (Table 2). Kibar et al. [ 35] reported that the individual phenolic contents of peach decreased during cold storage, and the putrescine application prevented the loss of these compounds, with the effect varying depending on the concentration. Putrescine application delays the biochemical changes that occur by preventing ethylene synthesis in the fruit [53]. ## 2.5. Organic Acids Organic acids are important fruit quality parameters. Their rate of change decreases with the progress of maturity in fruit and their concentration may vary depending on fruit species [62]. Fig fruit contain many organic acids, including citric acid, malic acid, fumaric acid, acetic acid, and shikimic acid, and organic acid levels vary significantly with fig cultivars, growth stages, and harvest seasons [63,64]. In this study, the highest amount of citric acid was found in figs, followed by tartaric, fumaric, and succinic acid. The changes occurred in the quantity of organic acids during cold storage (Table 3). However, Celikel and Karacali [65] reported that there was no change in the citric acid content of the fig fruit during cold storage. Putrescine application affected the changes in the quantity of organic acids during cold storage, and this effect varied depending on the type of organic acid and the length of the storage period. It can be said that putrescine application slows down the decrease in the concentration of organic acids during cold storage (Table 3). In similar studies [14,66] it was revealed that the organic acid content of the fruit was significantly maintained during storage with polyamine applications. ## 2.6. Correlation between Postharvest Putrescine Treatments and Quality Characteristics of Fruits, Organic Acids, and Phenolic Compounds by PCA Statistical evaluation is of significant importance for the scientific evaluation of the findings obtained in research and for the correct interpretation of the results. Principal component analysis (PCA) is an important statistical method that scientifically reveals the relationship between the results of research and the effect of the applied method on the findings [18,67,68]. In this study, the effect of putrescine applications at different doses after harvest on the quality and biochemical properties of fig fruits was revealed by PCA. In the PCA performed to measure the reaction of some quality parameters of fig fruits to putrescine applications during storage, the correlation was $63.1\%$ (PCA 1 + PCA 2) (Figure 8). In this study, it was determined that there was a positive correlation between total phenolic and total antioxidant, but there was a negative correlation between degradation rate and these biochemicals. It was observed that there was an inverse relationship between weight loss and acidity values and fruit firmness. Examination of the PCA plane shows that TA, TP, and pH were found in the first plane. On the PCA plane, acidity and weight loss were in the second region, fruit firmness was in the third region, and SSC and DR were in the fourth region. Examination of the correlation between putrescine application doses and the control group showed that the results from increasing doses of putrescine differed from those of the control group. On the PCA plane, 0.5 and 2 mM were located in the first region, 1 and 4 mM were in the third region, and the control group was grouped in the fourth region. Statistical evaluations of the storage period showed that the 7th day group formed a large intersection area with the 14th day group. It was determined that there was no clear distinction between the three storage periods (7th day, 14th day, and 21st day) and there were common intersection areas. In the PCA analysis performed to evaluate the statistical relationship between the phenolic compound contents of fig fruits and the postharvest putrescine application doses, it was found that the correlation was $54.6\%$ (PCA 1 + PCA 2). It was determined that there were no phenolic compounds in the first and third regions of the PCA plane. Catechin, rutin, ferulic, and protocatechuic acids were located in the second region in the PCA plane, and other phenolic compounds were located in the fourth region (Figure 9). A positive correlation between catechin, rutin, ferulic, and protocatechuic values, and a parallelism, were determined. A significantly negative correlation was observed between o-coumaric and catechin. Significant differences were determined between the putrescine doses and the control group. In this study, on the PCA plane, the control group was located in the second region, 0.5 and 1 mM in the first region, 2 mM in the second region, and 4 mM in the fourth region. Examination of the correlation between storage times showed that there was a large difference between the 7th day storage and the 21st day storage, and the intersection ratio was very low. Therefore, it was determined that as the storage time increased, the change in the phenolic compound content of the fig fruits was higher and there was a negative relationship between storage time and phenolic compounds. In this study, it was observed that the organic acid content of fig fruits generally decreased during storage. According to PCA analysis, the correlation between organic acids was $88\%$ (PCA 1 + PCA 2). This ratio largely revealed the correlation between organic acids by two main factors of principal component analysis (Figure 10). In this study, it was observed that malic acid differed from other organic acids and was located in the second region in the PCA plane. Tartaric, succinic, fumaric, and citric acid were located in the fourth region in the PCA plane. When the correlation between the control group and putrescine doses was examined, it was observed that the 0.5 mM putrescine dose was grouped in the third region and the other doses were grouped in the fourth region together with the control group. It was determined that the change in organic acids emerged clearly during the storage period and the rate of decrease in these compounds was high. It was determined that there were significant differences between the 7th day and 21st day findings in storage and that there was a low level of intersection between these two groups in the cluster analysis. ## 3. Materials and Methods Fruit harvested in an orchard established using the “Bursa Siyahı” cultivar at a planting distance of 5 m × 5 m in Siirt in 2012 were placed in plastic boxes (Plastas, Turkey) with a capacity of 5 kg and immediately transferred to Laboratory of Horticulture Department of Siirt University (Siirt, Turkey), within 1 h using a refrigerated vehicle (12 ± 1.0 °C and 75 ± $5.0\%$ RH). The fruits were harvested when the SSC ratio was $19\%$. The maturity index was added to the “Materials and Methods” section of the manuscript as shown below. The fruits were harvested when the SSC rate was $19\%$. Twenty fruit were used for harvest period analysis and measurements. The remaining 300 fruit were grouped into groups of 60 fruit for 5 treatments (control, 0.5 mM, 1 mM, 2 mM, 4 mM putrescine). One group was selected as the control group, and fruit of the other four groups were immersed in putrescine solution prepared at different concentrations for 15 min. According to previous research, one of the main effects of postharvest polyamines is preservation of fruit firmness. Flesh firmness augmentation and fruit softness reduction have been reported in most horticultural crops, such as strawberries [69], peach [70], and plum [50]. For each application, the fruit were put into 3 plastic containers of 1 kg to be used in analyses and measurements conducted at different periods after harvest and stored at 0 ± 0.5 °C and 90 ± $5\%$ RH for 7, 14, and 21 days. Fruit were analyzed at the end of each storage period. ## 3.1. Weight Loss At the beginning of cold storage, initial weights (Wi) of the fruit were determined by a digital scale with a precision of 0.01 g (Radwag, Poland). Then, on days 7, 14, and 21 of the storage, final weights (Wf) were determined. The weight loss that occurred in fruit was based on the weight at the beginning of each measurement period and determined as a percentage through the equation given below (Equation [1]):[1]WL=Wi−WfWi×100 ## 3.2. Decay Rate Before the cold storage, the fruit (about 0.5 kg of fruit) were counted in each replication and the total number of fruit (TF) was determined. Then, during each measurement period, the decayed fruit (DF) in each replication were determined. If the development of mycelium on the shell occurred, the fruit were considered rotten. Finally, with the following equation (Equation [2]), the decay rate (DR, %) was detected:[2]DR=TF−DFTF×100 ## 3.3. Fruit Firmness Five fruit from each replication were used to determine firmness. The fruit skin was cut at two different points (on the cheeks) along the equatorial part of the fruit and the firmness was determined using a penetrometer (FT–327; McCormick, WA, USA) with a 7.9 mm penetrating tip. Firmness was stated in Newtons (N). ## 3.4. Soluble Solids Content, Titratable Acidity Soluble solids content (SSC) was determined with a digital refractometer (Atago PAL-1, Washington, USA) and recorded as a percentage (%). For titratable acidity (TA) measurement, 10 mL of distilled water was added to 10 mL of juice. Then, 0.1 N sodium hydroxide (NaOH) was added until the solution’s pH reached 8.2. Based on the amount of NaOH consumed in titration, titratable acidity was determined and stated as g malic acid/kg [34]. ## 3.5. Total Phenolics and Antioxidant Capacity During each measurement period, five fruit taken from each replication were first washed with distilled water. The fruit were homogenized by a blender (Promix HR2653 Philips, Turkey). About 30 mL of homogenate was taken and placed into a 50 mL falcon tube. The prepared tubes were kept at −20 °C until the time of analysis. Before the analyses, the frozen samples were dissolved at room temperature (21 °C). Pulp and juice were separated from each other by a centrifuge at 12,000× g at 4 °C for 35 min. The resultant filtrate was used to determine the content of total phenolics and antioxidant capacity. Spectrophotometric measurements for total phenolics and antioxidant capacity were performed using a UV-Vis spectrophotometer (Shimadzu, Kyoto, Japan) [71,72]. ## 3.6. Specific Phenolic Compounds Specific phenolic compounds were analyzed as follows. One gram of homogeneously selected fresh fruit samples was weighed and extracted with methyl alcohol (5 mL) in a test tube for 6 h. The extract was analyzed by high pressure liquid chromatography (HPLC) (Perkin-Elmer series 200, Norwalk, CT, USA). The HPLC system was equipped with a DAD detector (Agilent, USA) and quaternary solvent dispensing system (Series 200, analytical pump) and used at 280 nm. Analyses were separated by a chromatographic separation performed with a 250 × 4.6 mm, 4 µm ODS column (HiChrom, Bergenfield, NJ, USA). The column temperature was adjusted to 26 °C in the automatic temperature regulation system in the HPLC device. Solvent A (methanol/acetic acid/water; 10:2:28) and solvent B (methanol/acetic acid/water; 90:2:8) were used as the mobile phase (Table 4). The mobile phase flow rate was maintained at 1 mL per minute and 20 μL of the sample was injected, and in the light of the results of the obtained peak areas, the contents of phenolic compounds were expressed as mg/100 g FW [73]. ## 3.7. Organic Acids Extraction of organic acids in fresh and dried samples was carried out with a modification of the method reported by Bevilacqua and Califano [74]. A quantity of 10 g of sample was placed in centrifuge tubes and then 10 mL of 0.009 N sulfuric acid was added to the samples and homogenized. The samples were mixed for 1 h and centrifuged at 14,000 rpm for 15 min. The liquid (supernatant) remaining at the top of the centrifuge tube was filtered through filter paper, then passed through a 0.45 μm membrane filter (Millipore Millex-HV Hydrophilic PVDF, Millipore, USA) and finally through a SEP-PAK C18 cartridge. It was injected into the HPLC (Agilent HPLC 1100 series G 1322 A, Germany) device and the separations were performed on the appropriate column (Aminex HPX—87 H, 300 mm × 7.8 mm). Organic acids were determined at wavelengths of 214 and 280 nm. A quantity of 0.009 N H2SO4 solution was used as mobile phase [74]. ## 3.8. Statistical Analysis One-way ANOVA was used to analyze the effect of postharvest putrescine applications on the investigated properties of fig fruits. Differences among means were evaluated by the Tukey HSD test and the significance was accepted at the $p \leq 0.05$ level. The ANOVA analyses were performed using JMP 16 (SAS Institute Inc., Cary, NC, USA). Principal component analysis (PCA) was performed using the JMP 16 (SAS Institute Inc., Cary, NC, USA) program to determine the relationship between postharvest applications of fig fruits, and their physicochemical properties and storage times. ## 4. Conclusions Putrescine application reduced the weight loss and decay rate in storage while it delayed the softening of the fruit. Significant differences in SSC rate occurred depending on storage time and putrescine application dose. At the end of the cold storage, the lowest SSC ratio was measured in 2 mM treated fruit, while the highest value was recorded in control fruit. With putrescine application, the decrease in the acidity rate of the fig fruit during storage was smaller. Putrescine application affected the total phenolic content, which generally decreased during storage, but there were inconsistencies in this effect. Putrescine application affected the total antioxidant activity values and changes occurred in total antioxidant activity depending on the application dose. The decrease in the quantity of phenolic acids both during and at the end of the cold storage was smaller in putrescine-treated fruit. It was observed that putrescine application had an effect on flavonoid compounds during cold storage, but this effect varied depending on the application concentration and flavonoid compound. Putrescine application affected the changes in the quantity of organic acids during cold storage, and this effect varied depending on the type of organic acid and storage time. As a result, it was revealed that putrescine application can be used as an effective method to preserve fruit quality after harvest in figs. ## References 1. 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--- title: 'Maternal Gestational Diabetes Is Associated with High Risk of Childhood Overweight and Obesity: A Cross-Sectional Study in Pre-School Children Aged 2–5 Years' authors: - Maria Mantzorou - Dimitrios Papandreou - Eleni Pavlidou - Sousana K. Papadopoulou - Maria Tolia - Maria Mentzelou - Antigoni Poutsidi - Georgios Antasouras - Georgios K. Vasios - Constantinos Giaginis journal: Medicina year: 2023 pmcid: PMC10051905 doi: 10.3390/medicina59030455 license: CC BY 4.0 --- # Maternal Gestational Diabetes Is Associated with High Risk of Childhood Overweight and Obesity: A Cross-Sectional Study in Pre-School Children Aged 2–5 Years ## Abstract Background and Objectives: Childhood obesity is a global public health concern with long-term and serious health implications. An important factor for childhood obesity is maternal gestational diabetes mellitus (GDM), which in turn impacts maternal and offspring long-term health. This study aimed to investigate the associations between maternal GDM and childhood weight status and multiple anthropometric and sociodemographic factors and perinatal outcomes. Materials and Methods: A total of 5348 children aged 2–5 years old and their paired mothers took part in the study. Questionnaires were utilized to evaluate the sociodemographic factors and perinatal outcomes as well as smoking habits, educational level, economic status, age, and parity status. Children’s anthropometric parameters were measured, and maternal medical history, preterm birth records, and anthropometric measures during pregnancy were retrieved by their medical records. Results: Overall, $16.4\%$ of the children aged at 2–5 years were overweight, and $8.2\%$ of them were affected by obesity, leading to a total $24.6\%$ of children with overweight/obesity. Further, $5.5\%$ of the enrolled mothers were diagnosed with gestational diabetes mellitus. GDM doubles the probability of childhood overweight/obesity at ages 2–5 years old independently of multiple confounding factors. Pre-pregnancy overweight and obesity, older maternal age, and smoking are risk factors for GDM, while GDM additionally increases the risk of preterm birth. Children of mothers that developed GDM were at greater risk of overweight or obesity, with the association between GDM and offspring’s weight status being independent of confounding factors. Conclusions: GDM is a severe public health issue with prolonged complications for both the mother and their children. Public health approaches and programs need to promote the negative role of pre-pregnancy weight and smoking status as well as the significance of a good glycemic control throughout gestation in women of childbearing age. ## 1. Introduction Childhood obesity constitutes a severe public health issue worldwide, with long-term and serious health complications. The risk of childhood obesity begins in utero [1], influenced by genetic, epigenetic, and environmental factors [2,3,4]. Childhood overweight and obesity levels in European countries are high [5], while the data in pre-school stages of life remain scarce [6]. In pre-school children up to 5 years old, the incidence of overweight and obesity ranges between $1\%$ and $28.6\%$ [7]. In Greece, the prevalence of risk of overweight and obesity in pre-school children up to 5 years old has been estimated at $21.3\%$ based on the International Obesity Task Force (IOTF) method of estimation [8]. Due to the physical and mental health implications of obesity as well as its economic burden, timely preventive and management strategies are strongly needed. An important factor for childhood obesity appears to be maternal gestational diabetes mellitus (GDM). GDM affects about one in six pregnant women in the world [9] and impacts both maternal and offspring health outcomes in the short and long term. In the short term, GDM can lead to hypertension and pre-eclampsia [9] and dystocia [10,11]. In the long term, GDM enhances the likelihood of cardiometabolic, liver, and kidney diseases [9]. Women with GDM show elevated probability to be diagnosed with insulin-independent diabetes at the next stage of their life [9,11], especially those who needed insulin, had high BMI, had multiparous pregnancy, had offspring with macrosomia, and those who gained weight between their pregnancies [12]. A new meta-analysis demonstrated that advanced maternal age, family history of diabetes, Black and non-Hispanic White ethnicities, and living in Europe and Southeast Asia are associated with increased probability of diabetes after being diagnosed with GDM [13]. In fact, almost half of mothers with a history of GDM will exhibit type II diabetes at the next decade of their life [14]. Among the most important risk factors, weight status before gestation and gestational weight gain (GWG) are strongly associated with several perinatal complications for both the mothers and their fetuses, including GDM [15,16,17]. Notably, meta-analysis studies supported evidence for the presence of a dose–response association between BMI before gestation and GDM, highlighting the need for robust public health interferences for the management of maternal BMI before gestation as well as for the control of the maternal body weight gain throughout gestation [16,17]. Moreover, GDM has considerably been related with elevated childbirth weight and a high probability of large for gestational age and macrosomia [18]. Regarding fetal health, maternal GDM can lead to increased fetal adiposity [19] and macrosomia [20], which can increase the risk of difficulties and trauma during birth as well as preterm birth [10,20]. Furthermore, due to the change on glucose supply and offspring’s hyperinsulinemia, neonatal hypoglycemia may be present [21]. Apart from short-term complications, maternal GDM may cause prolonged health implications for their children, including metabolic syndrome and type II diabetes, obesity and abdominal obesity, hypertension and dyslipidemia [9,22,23,24,25], as well as cardiovascular diseases [26]. Notably, the impact of GDM on children’s glucose and insulin resistance is not solely dependent on either mother or child’s BMI status or familial history of diabetes mellitus [25], as epigenetic modifications in utero can influence long-term health outcomes [27]. However, there are not enough data concerning the potential effect of GDM on the probability of exhibiting childhood overweight and obesity in pre-school age and especially in the Greek population. In view of the above considerations, the purpose of the present cross-sectional study was to explore whether maternal GDM may affect childhood weight status at the first stages of life while taking into account multiple anthropometric and socio-demographic factors and perinatal outcomes as confounders. ## 2.1. Subjects In the current survey, 7122 Caucasian mothers and their matched children at the age of 2–5 years old were initially, voluntarily enrolled from nine diverse Greek areas, namely Athens, Thessaloniki, Larisa, Patra, Alexandroupolis, Kalamata, Ioannina, Crete, and the North Aegean from community and especially from nursery schools and playgrounds. Enrollment to the survey took place from May 2016 to September 2020. Beyond the enrolled 7122 Caucasian mothers, another 87 mothers were selected to participate to the study; however, they refused to take part. In multiparous Caucasian mothers, merely the most recent gestation was considered for analysis. The participating mothers and their children had no disease during the postpartum period. All recorded data were confidential. The participating mothers were informed about the objectives of the survey and signed a permission form in which they approved that their personal data may be published. Sample size estimation was established using the PS: Power and Sample Size calculator program based on achieving adequate power for hypothesis testing. Among the 7122 firstly enrolled women and paired children, 972 of them ($13.6\%$) were excluded from the survey because of lost or inadequate data. Among the remaining 6150 women and paired children, 802 ($13.0\%$) of them were omitted from the survey because of a history of disease such as diabetes mellitus type 1 or 2, hyperlipidemia, hypertension, anemia, thyroid disorders, cardiovascular diseases, osteoporosis, multiple sclerosis, polycystic ovary syndrome, inflammatory gastrointestinal diseases, gallstones, autoimmune liver disease, celiac disease, pelvic floor dysfunction, and cancer, leading to a final response rate of $75.1\%$. History of disease was self-reported by the participating women via the provided questionnaires. The only inclusion criterion regarding disease was gestational diabetes or pregnancy-induced hypertension that had been treated effectively. A total of 5348 women and their paired children were finally included. A flow chart of study enrolment is presented in Figure 1. The survey was certified by the Ethical Board of the University of the Aegean (ethical authorization protocol: No. $\frac{12}{14.5.2016}$) and was in agreement with the World Health Organization (52nd WMA General Assembly, Edinburgh, Scotland, 2000). ## 2.2. Study Design At the time of study, 2–5 years postpartum, certified semi-quantitative questionnaires were utilized to evaluate the sociodemographic parameters and perinatal outcomes of the survey population [28,29]. Children’s anthropometric characteristics (weight and height) at the age of 2–5 years old (2–5 years postpartum) were determined by qualified nutritionists as per protocol [28,29,30,31]. Children’s weight was determined utilizing the same electronic scale, and height was determined utilizing a portable stadiometer. IOTF method was applied to classify overweight and obesity in participating children [32]. In fact, children with BMI between 85th and 95th percentiles of IOFT growth curves were categorized as overweight, and those with BMI ≥ 95th percentile of IOFT growth curves were categorized as obese [32]. Mothers’ GDM status was retrieved by their medical records. All mothers were screened for GDM by applying a universal oral glucose tolerance test (OGTT) during pregnancy [33]. In fact, a fasting OGTT after 75 g glucose with a cut-off plasma glucose of ≥140 mg/dL after 2 h for the first and subsequent trimester at 24–28 weeks of pregnancy was performed for all participating mothers [33]. Mothers’ weight and height was derived from their records with measurements during the first weeks of gestation and immediately prior to childbirth during their visit to their personal gynecologists and/or the health care units that they visited. Mothers’ pre-pregnancy body mass index (BMI) was determined according to the weight and height that was stated in their medical records. Gestational weight gain (GWG) of participating mothers was also retrieved by their medical files. In addition, participating women were questioned regarding whether they followed breastfeeding practices at all and whether they followed exclusive breastfeeding for a minimum period of four months. To avoid recall bias, the women were questioned regarding whether they exclusively breastfed for a minimum period of four months since at this moment they were counselled to slowly incorporate pulp foods to the feeding practices of their children, and thus, they memorized more accurately this time point, making their responses more consistent. On the contrary, women who followed breastfeeding practices for smaller duration were not capable of responding with certainty about the precise interval of breastfeeding. Participating women additionally reported whether they gave a preterm birth (<37th week), and their responses were additionally cross-checked by their medical files so as to have more accurate records regarding the precise week of gestation that preterm birth took place. Nevertheless, we detected that several data were lost regarding the precise week of preterm birth in the medical records, and several of them did not come to an agreement with the women’s responses, and thus, preterm birth was categorized as binary outcome, with childbirth either earlier than or after the 37th week of gestation. Measured childbirth weight data were collected by their mother’s gynecologists’ or hospitals’ medical files. Childbirth weight of was categorized as low (<2500 g), normal (2500–4000 g), and high (>4000 g). Maternal smoking habits, educational level, economic status, age, and parity status were recovered by the given questionnaires according to mothers’ memory recall. Specifically, educational level was estimated based on the total years of education, and financial level was categorized based on the yearly family income as: 0, <5000; 1, 5000–10,000; 2, 10,000–15,000; 3, 15,000–20,000; 4, 20,000–25,000; and 5, >25,000 in euros. Financial level was additionally categorized as low for family annual income ≤ 10,000, medium for annual income ˃10,000 and ≤20,000, and high for annual income ˃ 20,000, all in euros. The explaining guidelines were provided to the participating mothers by qualified dietitians and nutritionists concerning the accomplishment of questionnaires, and a thorough demonstration of the questions to support precise responses was made. ## 2.3. Statistical Analysis Statistical analysis was accomplished by Student’s t-test for continuous variables followed normal distribution based on Kolmogorov–Smirnov test. All continuous variables followed normal distributions. Chi-square test was applied for categorical variables. The normally distributed quantitative variables are given as mean value ± standard deviation (SD), and the qualitative variables as absolute or relative frequencies. Multivariate logistic regression analysis was applied for assessing whether maternal GDM status is independently associated with sociodemographic and anthropometric characteristics and perinatal outcomes by adjusting for potential confounding factors. Differences were classified as significant at $p \leq 0.05$ and $95\%$ confidence interval. The statistical analysis of the study data was accomplished by Statistica 10.0 software, Europe (Informer Technologies, Inc., Hamburg, Germany). ## 3.1. Sociodemographic and Anthropometric Parameters and Perinatal Outcomes of the Study Population The current survey included 5348 pre-school children at the age of 2–5 years old and their matched mothers, enrolled 2–5 years after delivery. Table 1 presents the descriptive statistics of the survey population. The mean age of the mothers was 33.7 ± 4.7 years (range: 22–46 years) at the time of pregnancy, and the mean age of their children was 4.06 ± 1.06 years (range: 2.0–5.5 years) at the time of study. Concerning children’s gender, $49.3\%$ were males, and the remaining $50.7\%$ were females. Regarding children’s BMI at age 2–5 years old, $16.4\%$ of them were classified as overweight, $8.2\%$ of them were classified as obese, and in total, $24.6\%$ of the children were affected by overweight or obesity at the age of 2–5 years old. The BMI of the participating women prior to gestation was 22.7 ± 3.7 Kg/m2 (range: 15.9–37.6 Kg/m2). In fact, $17.5\%$ of the women were affected by overweight, and $4.9\%$ were affected by obesity prior to gestation based on BMI classification, and overall, an incidence of $22.4\%$ regarding maternal overweight/obesity prior to gestation was recorded. The mean years of maternal education were 14.6 ± 2.8 years (range: 0–17 years). Concerning economic status, $45.8\%$ of mothers had low family annual income, $45.6\%$ had medium family annual income, and $8.6\%$ of them had high family annual income. In total, $25.5\%$ of the mothers were smokers before pregnancy, and the remaining $74.5\%$ of the mothers were never smokers. Further, $59.7\%$ of the participants had no child since this was the first childbirth, and $40.3\%$ of mothers had more than one child except for the childbirth included in this study. Moreover, $5.5\%$ of the mothers were diagnosed with GDM, and $4.1\%$ of the mothers were diagnosed with gestational hypertension. The mean maternal GWG was 13.8 ± 6.1 (range: 0–45 Kg). Preterm birth (<37th week) was noted in $30.1\%$ of the participating mothers. Half of participating women ($49.8\%$) followed exclusive breastfeeding for a minimum period of 4 months (mean duration: 4.5 ± 1.9 months), and $50.2\%$ of them did not follow exclusive breastfeeding for a minimum period of 4 months or did not breastfeed at all. Classifying children according to their birth weight, $8.2\%$ of them were categorized as low newborn weight (< 500 g), $85.3\%$ of them had normal newborn weight (2500–4000 g), and $6.5\%$ of them had high newborn weight (>4000 g). ## 3.2. Maternal Gestational Diabetes Mellitus in Relation to Sociodemographic and Anthropometric Parameters and Perinatal Outcomes of the Study Population Older women were at higher risk of developing GDM than younger women (Table 2, $p \leq 0.0001$). A significantly higher prevalence of delivering a female child was observed in women who developed GDM (Table 2, $$p \leq 0.0012$$). Childhood overweight and obesity at the age of 2–5 years old was considerably more often observed in the offspring of mothers who developed GDM than in the children of mothers without history of GDM (Table 2, $p \leq 0.0001$). Mothers who developed GDM were also more frequently affected by overweight or obesity pre-pregnancy compared to those that were not diagnosed with GDM (Table 2, $$p \leq 0.0155$$). Low family annual income was considerably related with a higher incidence of maternal GDM (Table 2, $$p \leq 0.0065$$). Mothers who smoked were also more likely to be diagnosed with GDM than those who never smoked (Table 2, $$p \leq 0.0049$$). Multiparity was borderline-correlated with a greater GDM incidence (Table 2, $$p \leq 0.0552$$). Women who developed GDM showed a marginally lower prevalence of exclusive breastfeeding than those who were not diagnosed with GDM (Table 2, $$p \leq 0.0656$$). Maternal educational level and pregnancy-induced hypertension as well as childbirth weight were not associated GDM (Table 2, p ˃ 0.05). ## 3.3. Multivariate Regression Analysis for Gestational Diabetes Mellitus Status In the multivariate logistic regression analysis, mothers developed GDM exhibited a 2-fold greater prevalence of delivering children that had overweight/obese BMI at the age of 2–5 years, independently of multiple confounders (Table 3, $$p \leq 0.0006$$). Mothers diagnosed with GDM showed a $27\%$ greater incidence of delivering female children than male ones (Table 3, $$p \leq 0.0050$$). Older women also showed a $29\%$ greater risk of being diagnosed with GDM than younger ones (Table 3, $$p \leq 0.0027$$). Mothers affected by overweight or obesity before pregnancy exhibited more than a $30\%$ greater likelihood of developing GDM (Table 3, $$p \leq 0.0326$$). Smokers also showed a $54\%$ higher probability of developing GDM than non-smokers (Table 3, $$p \leq 0.0204$$). Mothers diagnosed with GDM showed a $77\%$ greater prevalence of preterm birth compared to those without a history of GDM (Table 3, $$p \leq 0.0135$$). Family economic status, parity, educational level, gestational weight gain, breastfeeding practices, and childbirth weight were not considerably related to the probability of developing GDM in multivariate analysis (Table 3, p ˃ 0.05). ## 4. Discussion In the current survey, $24.6\%$ of the children aged 2–5 years old were either affected by overweight or obesity. Childhood obesity levels in Greece are high, and according to the COSI study data, Greece leads the way in Europe for severe obesity in children [34]. In pre-school aged children, the rate of overweight and obesity is 21–$22\%$ [8,35]. Children of mothers that developed GDM exhibited greater probability of overweight or obesity, with the relationship between GDM and offspring’s weight status being independent of confounding factors. In Europe, the incidence of GDM has been estimated to be $5.4\%$ (range: 3.8–$7.8\%$), which is in line with our results [36]. Moreover, the recently published study by Gao et al. [ 37] found that even maternal insulin resistance, assessed via elevated HOMA-IR, was related to an enhanced likelihood for the children to be overweight during the first two years of life [37]. The HAPO survey [38,39] findings, with data from 10 countries and 4832 children, are also in line with our findings. In utero glucose levels lead to higher adiposity in childhood and increased waist circumference. Furthermore, a novel survey by Choi et al. [ 40] is in line with our findings, as the authors observed that maternal obesity before gestation and GDM further raise the probability of childhood obesity at 5 years [40]. Another recent retrospective study by Ardic et al. [ 41] also found that GDM increases the probability for childhood obesity at the ages of 2 and 3 years old. The proposed mechanisms behind this association are the exposure to higher glucose levels in utero [38,39], reduced insulin sensitivity due to maternal hyperleptinemia [42], epigenetic programming [43], as well as the altered maternal gut microbiome due to GDM [44]. It should be noted that maternal BMI before gestation is another important factor that incorporates both genetic predisposition and shared obesogenic environment [45]. It is of great concern that childhood obesity increases the probability of obesity through the different stages of life [46]. More to the point, $55\%$ of children affected by obesity become adolescents with obesity, and $80\%$ of these adolescents will still be affected by obesity in adulthood [47]. Additionally, childhood obesity can increase the risk of cardiometabolic diseases and cancer in adulthood [48,49]. In our analysis, mothers affected by overweight or obesity before gestation were at $30\%$ higher risk of developing GDM than those with normal weight. Indeed, it is very well established in the literature that higher BMI status raises the probability of glucose intolerance and GDM [15,16,17]. In fact, a dose–response association between BMI and the probability of GDM development was discerned, with the risk increasing by $4\%$ for every unit of increase on BMI [16], while the probability of GDM in women affected by overweight or obesity tends to $23\%$ [17]. Accordingly, in a meta-analysis of 39 cohorts from Europe, North America, and Oceania, women affected by obesity with high GWG exhibited the greatest likelihood of gestational complications such as pregnancy-induced hypertensive disorders, GDM, and large for gestational age at childbirth [50]. In accordance with the above, we demonstrated that mothers diagnosed with GDM exhibited greater GWG; nevertheless, this relationship was considerably attenuated after adjusting for potential confounding factors. Several studies also suggested that GDM may increase the likelihood of increased childbirth weight and large for gestational age and macrosomia [18]. Recently, a prospective, hospital-based cohort study showed that GDM increased the odds of preterm birth, higher birthweight, and large for gestational age [51]. Although we recorded an elevated probability of preterm birth in mothers diagnosed with GDM, there was no relationship between GDM and childbirth weight, which may be ascribed to the rather modest prevalence of GDM in our survey population. Interestingly, in our study, women who developed GDM exhibited a $27\%$ greater incidence of delivering female children than male ones. Recent findings have demonstrated that fetal sex may exert a role on maternal insulin sensitivity [52]. In GDM, the placenta is affected, and different gene expression takes place, with fetal sex playing an important role [53,54]. Moreover, a lipotoxic placenta environment has been established in obese mothers, with enhanced inflammatory and oxidation stress. The above conditions may change mitochondrial function, producing reactive oxygen species, which may result in placenta dysfunction and diminished gestation outcomes [55]. In addition, placenta metabolome analysis of pregnant women affected by obesity revealed differences in metabolites implicated in antioxidant defense systems, nucleotide production, as well as lipid biosynthesis and energy production, supporting a shift to greater placenta metabolism [56]. These metabolic signatures in the placentas of women affected by obesity could indicate alterations occurring in the intrauterine metabolic environment, which could affect the risk of several diseases during adulthood [56]. Regarding GDM and fetal sex, Hooks et al. [ 57] found that in women with GDM, having a male fetus raises the probability of preterm birth [55], while Seghieri et al. [ 58] found that having a male fetus raises the likelihood of GDM, and in pregnancies with a female fetus, maternal obesity before gestation increases the probability of GDM. Another recent study found that having a male fetus is associated with higher insulin sensitivity [52]. Moreover, Mando et al. explored the potential effect of GWG on fetal/placental ratio in overweight with different fetal gender and found different placenta adaptation depending on fetal sex, with substantial alterations merely in female fetuses [59]. The above could be part of a female-specific approach intending to guarantee survival if another adverse outcome appears [59]. Regarding preterm birth, mothers diagnosed with GDM had a $77\%$ higher probability of preterm birth compared to mothers who did not develop GDM. Several studies have shown that GDM increases the risk for preterm birth by 30–$42\%$ [60,61]. The difference in the risk might be ascribed to the fact that our survey sample is quite smaller that the above studies. Women’s age is considered a risk factor for developing GDM [62], and our study confirms that older mothers had a $29\%$ greater likelihood of developing GDM compared to younger ones. Smokers also showed a $54\%$ higher probability of developing GDM than non-smokers. and although earlier meta-analyses showed no association between smoking and GDM [63], more recent studies have revealed a relationship with smoking [64,65] and even passive smoking [66]. Breastfeeding also exerts beneficial effects on mothers’ post-natal weight loss [67], being related with decreased probability of childhood obesity by $22\%$ [68,69] in a dose-response manner [70]. In addition, in spite of the advantages of breastfeeding for both children’s and mothers’ health and body weight, women affected by obesity are less prone to apply breastfeeding practices to their children [71,72]. Moreover, the incidence of breastfeeding among GDM mothers is far less than optimal. Based on the WHO, only over one-third ($34.8\%$) of GDM mothers apply breastfeeding practices for their children, and the proportion is even lower in developing countries [73]. However, we found only a marginal association between breastfeeding and GDM incidence, which was further attenuated after adjustment for confounders that may be ascribed to the rather low prevalence of GDM in our survey population. It should be mentioned that there are some limitations in our survey. BMI is considered a crucial indicator to classify mothers as overweight or obese. However, direct techniques evaluating body fat quantity and distribution are needed to expand and confirm the present findings. Moreover, memory bias was essential in our survey because some probable risk factors were self-reported by the participating women. Hence, no conclusive evidence concerning causality can be derived because of the cross-sectional design of the present study in spite of its nationally representative nature. Another limitation of our study deals with the fact that it did recorded neither feeding practices of mothers during their pregnancy nor eating habits of their children beyond the breastfeeding period. In this aspect, specific nutritional approaches such as the Mediterranean diet have been related to a significant decrease of certain gestational complications, such as GDM, overweight or obesity, sleep quality, childbirth difficulties, urinary tract infections, and alterations in fetal growth as well as perinatal problems including childbirth weight, prematurity, gastroschisis, and other childhood complications [74]. There is also substantial evidence that healthy dietary patterns such as the Mediterranean diet can decrease the risk of developing overweight and obesity through childhood up to adolescence [75]. Furthermore, despite a thorough effort adjust confounding factors, we acknowledge the likelihood of immeasurable confounding factors. Nevertheless, our survey advantage is the comparatively high and representative survey population given that it comprised women and their paired children from nine geographically different regions of Greece, including urban, rural, and island areas. The survey sample was adequately high and consisted of a Caucasian population, and thus, its representativeness may be judged as quite sufficient. Hence, the present findings may well be extrapolated away from the Greek population to other Caucasian peoples of other ethnicities. Nevertheless, further studies need to be conducted on other ethnic groups that could exhibit various differences regarding genetic background, sociodemographic, and lifestyle factors. ## 5. Conclusions GDM is a serious public health issue worldwide, with prolonged complications for both the mother and its child. The present study supported evidence at a Caucasian population-based level that GDM raises the risk for childhood overweight/obesity in the early years of the offspring’s life, which further may raise the risk for adolescent and adulthood obesity. The strong relationship between mothers’ GDM and childhood overweight/obesity is independent of multiple confounding factors. The risk of GDM is greater in women with higher weight status and those who smoke; hence, public health approaches and policies need to promote the important role of pre-pregnancy weight, GWG, and smoking status as well as the importance of a good glycemic control throughout pregnancy. Future studies are recommended to explore whether healthy dietary patterns during pregnancy may reduce GDM risk, also highlighting the need to improve eating habits at the early years of children’s life to decrease the risk of overweight and obesity and the related complications at the next stages of life. ## References 1. 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--- title: Heart Rate Variability in Subjects with Severe Allergic Background Undergoing COVID-19 Vaccination authors: - Maria Bernadette Cilona - Filippo D’Amico - Chiara Asperti - Giuseppe Alvise Ramirez - Stefano Turi - Giovanni Benanti - Shai Marc Bohane - Serena Nannipieri - Rosa Labanca - Matteo Gervasini - Federica Russetti - Naomi Viapiana - Martina Lezzi - Giovanni Landoni - Lorenzo Dagna - Mona-Rita Yacoub journal: Vaccines year: 2023 pmcid: PMC10051914 doi: 10.3390/vaccines11030567 license: CC BY 4.0 --- # Heart Rate Variability in Subjects with Severe Allergic Background Undergoing COVID-19 Vaccination ## Abstract Anti-Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) vaccination is the world’s most important strategy for stopping the pandemic. Vaccination challenges the body’s immune response and can be complicated by hypersensitivity reactions. The autonomic nervous system can modulate the inflammatory immune response, therefore constituting a potential marker to characterize individuals at high risk of hypersensitivity reactions. Autonomic nervous system functionality was assessed through measurement of the heart rate variability (HRV) in subjects with a history of severe allergic reactions and 12 control subjects. HRV parameters included the mean electrocardiograph RR interval and the standard deviation of all normal R–R intervals (SDNN). All measurements were performed immediately before the anti-SARS-CoV-2 vaccination. The median RR variability was lower in the study than in the control group: 687 ms (645–759) vs. 821 ms (759–902); $$p \leq 0.02.$$ The SDNN was lower in the study group than in the control group: 32 ms (23–36) vs. 50 ms (43–55); $p \leq 0.01.$ No correlation was found between age and the SDNN. Autonomic nervous system activity is unbalanced in people with a severe allergy background. ## 1. Introduction Coronavirus disease 2019 (COVID-19) is a highly transmissible respiratory infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is characterized by a respiratory syndrome and a heterogeneous hyperinflammatory response [1]. Global healthcare systems have faced an unprecedented challenge. Despite improvements in the medical management of COVID-19, vaccination against the viral pathogen SARS-CoV-2 represents the most important global strategy in controlling the pandemic. Indeed, vaccination campaigns rapidly advanced, especially in developed countries, and are associated with a clear reduction in the number of SARS-CoV-2 infections, decrease in viral RNA load, reduction in illness duration and attenuation of symptoms among those with breakthrough infections despite vaccination [2]. However, vaccination campaigns encountered some hurdles. People’s adherence to large-scale vaccination was limited in part due to their fear of any adverse reactions to vaccination [3]. The side effects of vaccination were amplified by the media, increasing vaccine hesitancy from the beginning of the vaccination campaign, and governments introduced measures to undermine misinformation and encourage vaccination. Scientific research has currently been focused on hypersensitivity reactions and the characteristics of subjects who may develop them [4,5]. Hypersensitivity reactions are an exaggerated and inappropriate immunological response to an allergen typically characterized by skin, respiratory, and/or cardiovascular involvement [6]. Individuals who have experienced a suspected hypersensitivity reaction to the vaccine or to its excipient usually undergo a preventive allergy workup to safely receive another dose of the vaccine, which includes allergy tests with vaccine excipients (polyethylene glycol and polysorbates) in selected cases, as suggested by national and international guidelines [7]. The pathophysiological mechanisms underlying hypersensitivity reactions involve mast cells’ degranulation, Th2 response, and alteration of the neuroendocrine–immune axis [8]. Notably, the autonomic nervous system plays a key role in all those mechanisms involved in the activation of inflammatory immune responses [8,9]. Indeed, allergic reactions can occur at different levels of organ involvement (e.g., respiratory, gastrointestinal, cutaneous) and may have an impact on hemodynamic stability. In acute conditions such as anaphylactic reactions, a sudden drop in blood pressure is caused by vasodilation induced by mast cells [10]. Gastrointestinal manifestations are characterized by increased peristalsis, mucus production, and diarrhea [11]. Typically, atopic dermatitis is characterized by a chronic itch caused by increased histamine production and inflammatory skin lesions [12]. Chronic conditions such as allergic rhinitis and asthma are mediated by mucus production and bronchial overactivity which result in bronchoconstriction [13]. The nervous system is involved in regulating all these pathophysiological mechanisms. Furthermore, due to the deep innervation of visceral organs, neurons share proximity with immune cells, leading to a peculiar crosstalk mediating the inflammatory immune response. In particular, the sympathetic nervous system leads to dysregulated cytokine production and unbalanced Th1/Th2 responses, stimulates mast cell degranulation, and activates inflammatory mediators and hormones directly involved in inflammation (e.g., cortisol, histamine, vasoactive intestinal peptide) [14]. Indeed, the finding of a sympathetic nervous system activation could represent a marker of the degree of inflammatory response and a possible therapeutic target of allergic conditions [15]; however, a useful marker of the sympathetic nervous system activity is heart rate variability (HRV). The HRV describes the oscillation of the intervals between consecutive heartbeats (the time elapsed between two successive R waves of the QRS signal (R–R intervals)) and reflects cardiac autonomic modulation [16]. In physiologic conditions, heart rate and rhythm are regulated by the intrinsic cardiac system of specialized pace-maker cells and modulated by the autonomic nervous system. The activation of the sympathetic nervous system tends to synchronize the RR interval to decrease the HRV. A widely used measure is the standard deviation of all normal RR intervals (SDNN) [17]. The HRV can be used in clinical practice to assess the physiologic status of autonomic activity, and HRV measurement is routinely used in cardiovascular medicine and sports medicine [18,19]. The HRV is often used for professional athletes to monitor cardiac activity. Athletes use these parameters to measure their psychophysical balance and response to physical stress [20]. Despite HRV being applied in clinical practice for a wide spectrum of diseases, consensus was only reached to use HRV parameters to predict the risk of arrhythmic events after acute myocardial infarction and function as a clinical marker for progression of diabetic neuropathy [21]. In all the other medical fields, there are insufficient clinical data on the practical utility of HRV. Indeed, further studies are needed to confirm its potential utility in clinical practice in other areas. In the field of allergology, the HRV was used to characterize subjects with chronic immunological disease [22,23]. The role of the autonomic nervous system has never been studied in acute conditions such as hypersensitivity reactions. This study aims to compare the HRV in subjects with a severe allergic background undergoing anti-SARS-CoV-2 vaccination with the HRV of subjects from a control group. ## 2.1. Study Design We conducted an observational 2:1 case–control study comparing individuals with history of severe allergic reactions undergoing anti-SARS-CoV-2 vaccination in a dedicated prompt-response setting with individuals vaccinated in a standard environment. Participants were previously identified by an allergist not involved in study data collection and defined as people with a history of multiple or severe anaphylaxis, severe controlled asthma, chronic spontaneous urticaria with a recent flare, mast cells disorders, or previous hypersensitivity reactions to SARS-CoV-2 vaccines. All participants were enrolled between February and March 2022, and vaccination sessions were conducted in IRCCS San Raffaele Hospital, Milan. The primary endpoint was the difference in the SDNN between the study and control groups. The secondary endpoints were correlations between age and SDNN and the difference in RR values between the study and control groups. ## 2.2. Enrollment Participants were enrolled, upon signing a specific informed consent form, in the Panimmuno research protocol approved by the Institutional Review Board (reference code 22/INT/2018). Subjects undergoing vaccination and older than 18 years were eligible for the study. Patients with cardiac arrhythmias, taking rate/rhythm control drugs, or who did not provide written informed consent to participate in the study were excluded. Subjects with a severe allergic background were previously identified by an allergist independently from the study. Those individuals considered to have a high risk of hypersensitivity reactions were referred to exclusive vaccination sessions. Subjects with a history of severe hypersensitivity reactions were identified by anamnestic data through the administration of a questionnaire assessing their history of atopy, antiallergic medication, previous allergic reactions to drugs and/or food, or reactions to previous doses of an COVID-19 vaccine. The control group was selected according to the expected standards for this type of study. Indeed, the control group was defined as a group of subjects undergoing COVID-19 vaccination with a low risk of developing hypersensitivity reactions to vaccination. The low risk of developing hypersensitivity reactions to vaccination was defined by the allergist based on the subject’s clinical history. Due to the limited number of subjects undergoing vaccination in the later stages of vaccination campaign, subjects were sequentially selected; therefore, we decided to select the first 24 subjects of the study group and the first 12 subjects of the control group meeting the inclusion criteria for their enrolment in the study. ## 2.3. Sample Size Available data in the literature have suggested a normal value of the SDNN of 50 ± 10 ms [16]. The SDNN < 50 ms is associated with an overactivity of the sympathetic nervous system. In the latest meta-analysis on the association of inflammation and the HRV, they found the SNDD was the strongest value negatively correlated with markers of inflammation [24]. Previous studies have reported values close to 40 ms are associated with clinical manifestations that typically result from an overactivation of the sympathetic nervous system [25,26,27,28]. Therefore, we identified a reduction in the SDNN to 40 ms for the present study to be significantly relevant. A sample size calculation based on Pearson’s Chi-square test with a two-sided alpha error of 0.05 and $80\%$ power with an enrolled ratio of 2 suggested a sample size of 24 participants in the study group and 12 participants in the control group using the continuity correction, resulting in a total study population of 36 patients. ## 2.4. Outcome Measurement On the day of injection, participants were monitored for 5 min in an isolated room before vaccine administration, and their mean RR variability and SDNN were evaluated. Data were analyzed and elaborated with the previously validated Kubios HRV software (version 3.5; University of Kuopio, Kuopio, Finland) [29], according to the guidelines recommended by the Taskforce of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology [16]. An example of data extraction is reported in Supplemental S1 (Supplementary Materials). As a secondary analysis, we correlated the age of individuals in the study group with SDNN values. All patients were also screened by means of an allergy questionnaire reported in Supplemental S2. The assessed characteristics included the following: history of vaccination, hypersensitivity reactions to vaccination, allergic drug reactions, positivity to allergy tests for common aeroallergens, other allergic comorbidities, and antiallergic drugs consumed. Demographic data, clinical history, and medications were also collected on the day of vaccination. ## 2.5. Statistical Analysis Demographic and baseline disease characteristics were summarized with the use of descriptive statistics. Categorical variables were reported as absolute numbers and percentages. Unadjusted univariate analyses to compare the two treatment groups were based on Fisher’s exact test. Continuous variables were reported as median, interquartile range (IQR). Normality was evaluated using the Shapiro–Wilk test. Between-group differences were evaluated using the t-test or Wilcoxon signed-rank test in accordance with normality of the distribution [30]. We considered significant a p-value < 0.05. Correlation was calculated using a Pearson correlation test, considering an inconsistent correlation for R < 0.1, weak correlation for R < 0.5, and strong correlation for R > 0.5 [31]. Subjects of the study group had peculiar characteristics related to their allergic history (e.g., antiallergic medications, positivity to allergic test); therefore, it was not possible to match individuals of the study group with those of the control group. Considering the small sample size and the limitations in enrolling more subjects, we decided not to adjust the baseline characteristics between the groups to avoid errors in the data interpretation [32]. ## 3.1. Study Population Of the 50 screened subjects, 36 were eligible for the study, and the main reason for exclusion was based on medications able to influence a subject’s heart rate (Figure 1). As planned, we enrolled 24 patients in the study group and 12 in the control group. Individuals in the study group were younger (48 years (34–53) vs. 60 years (53–67); $p \leq 0.01$), and more frequently female ($96\%$ vs. $75\%$, $$p \leq 0.02$$) than those in the control group (Table 1). Individuals in the study group also more frequently had a history of hypersensitivity reactions to drugs (14 ($58\%$) vs. 2 ($17\%$); $$p \leq 0.01$$), hypersensitivity reactions to food (11 ($46\%$) vs. 0 ($0\%$); $p \leq 0.01$), and a history of previous positive allergic tests ($67\%$ vs. $0\%$; $p \leq 0.001$) than those in the control group (Table 1). No difference was found in the overall allergic comorbidity (14 ($58\%$) vs. 4 ($33\%$); $$p \leq 0.15$$). Anti-histaminic drugs were used by a higher number of subjects in the study group ($$p \leq 0.005$$), whereas no difference was observed for other antiallergic medications. Among the 24 subjects in the study group, 1 subject ($4\%$) reported a previous suspected hypersensitivity reactions to a previous dose of a COVID-19 vaccine, and 12 subjects ($50\%$) were taking antiallergic medications. No difference was found in non-allergic comorbidities between the two groups. None of the participants developed hypersensitivity reactions after vaccine administration. Baseline characteristics of participants are reported in Table 1. ## 3.2. Outcomes The mean RR variability was lower in patients from the study than those in the control group: 687 ms (645–759) vs. 821 ms (759–902); $$p \leq 0.02$$, respectively. SDNN was lower in the study group than in the control group 32 ms (23–36) vs. 50 ms (43–54); $p \leq 0.01$, respectively. There was no correlation between the age of subjects in the study group and the SDNN values (R2 = 0.002). Results of HRV time-domain and frequency-domain measurements are reported in Table 2. ## 4. Discussion The main finding of our study is that subjects with a severe allergic background have low SDNN and RR values; therefore, individuals with a history of severe allergic reactions seem to have a predominant sympathetic nervous system activation that synchronizes beat-to-beat intervals. We reported a significant prevalence of females in the study group. Additionally, subjects of the study group were significantly younger, and no correlation was found between age and SDNN. To the best of our knowledge, this is the first study that intended to evaluate the HRV parameters in subjects with a severe allergic background undergoing COVID-19 vaccination. Alhumaid et al. reported that risk factors for the development of anaphylactic and non-anaphylactic reactions were being female and having a history of atopy [33]. This finding is consistent with our observation; however, Alhumaid et al. found only anamnestic data to detect the risk of allergic reaction to vaccination. Previously, we reported that people with a history of severe allergic reactions undergoing COVID-19 vaccination have a higher level of anxiety compared to individuals with a history of mild allergic reactions [34]. Interestingly, a reduced HRV was historically associated with anxiety disorders [35]. Previous studies evaluated HRV in allergic diseases. Yokusoglu M et al. observed that SDNN was increased in patients with allergic rhinitis [36]. Furthermore, several studies reported the same finding in asthmatic patients [37,38,39], which suggests there is likely a prevalent activation of vagal tone driving pathophysiological pathways. Although the precise pathogenesis of asthma is still debated, one of the proposed underlying mechanisms is an imbalance in the autonomic nervous system [40]. Parasympathetic activity, enhanced cholinergic activation, and vagal tone stimulate bronchoconstriction. Conversely, we reported an increase in sympathetic component activation. This inconsistency may be explained in part by the different natural courses of the analyzed conditions; indeed, the autonomic nervous system enhances excitatory pathways (cholinergic, α-adrenergic, and excitatory non-adrenergic, non-cholinergic-NANC mechanisms) or reduces inhibitory pathways (β-adrenergic and inhibitory NANC mechanisms) [41]. Specifically, norepinephrine inhibits IL-2, interferon, and IL-12 through adrenoceptors and stimulates IL-6 and IL-10 production [42]. Above all, norepinephrine enhances IL-4 production and stimulates IgE production. Furthermore, mast cells have anatomic proximity with postganglionic sympathetic nerve fibers that release norepinephrine [43]. These may all be potential mechanisms underlying hypersensitivity reactions’ development. There is only one study that reported data on the assessment of HRV parameters in allergic subjects. Consistent with our data, Kazuma et al. reported a reduction in HRV in subjects with a history of hypersensitivity reactions [44]; this suggests that those individuals who experienced hypersensitivity IgE-mediated reactions may have a reduction in HRV, a component of the overactivity of the sympathetic nervous system. Individuals who experienced non-IgE-mediated reactions may be characterized by an overactivity of the parasympathetic system. We did not find a correlation between the SDNN and the age of participants. The SDNN has been found to be independent from gender and inversely correlated to age [45]. These results suggest that the differences in baseline characteristics did not influence our results. In the study group, participants were taking antiallergic medications (antihistaminic drugs, corticosteroids, anti-leukotrienes drugs) due to their chronic history of allergy. Interactions between the use of antiallergic medications and the HRV parameters were never reported, and no correlation was found between the administration of antiallergic drugs and the HRV measurement [44,46]. The present study has several theoretical and practical implications. First, results from our study suggest the autonomic nervous system might play a key role in allergic conditions. Second, health care professionals and allergists should consider the risk of hypersensitivity reactions could have clinically relevant implications. Indeed, studies have described how a low HRV is associated to a high risk of sudden cardiac death, cardiac arrhythmias, and heart failure [21]; thus, these conditions should be considered especially in a circumstance as stressful as receiving a vaccination. The need to characterize subjects with a severe allergic background is still debated. Indeed, an objective complementary tool to help in stratification of these subjects is not yet available. The association between low HRV with a severe allergic background could create a way to find a complementary diagnostic tool. In particular, for those subjects who may experience immune and non-immune-mediated adverse events while undergoing vaccination, this may allow safer, large-scale administrations of vaccines and reduce the risk of misdiagnosis. Conditions considered possible risk factors for hypersensitivity reactions to vaccines are a history of uncontrolled asthma or chronic spontaneous urticaria, anaphylaxis, and mast cell disorders with increased tryptase levels [47]. Subjects with a clinical history of previous suspected hypersensitivity reactions to vaccine excipients (such as polyethylene glycol or polysorbate) should undergo an allergy test with these agents before receiving vaccination to exclude potential sensitization and receive vaccination safely. At the end of the allergy workup, subjects considered at a higher risk of hypersensitivity reactions should be referred to exclusive vaccination sessions where they would be supervised by health care personnel trained to address potential moderate to severe allergic reactions [48]. Since a reliable diagnostic tool is not yet available for subjects suspected of being at risk of hypersensitivity reactions, decisions are taken on the basis on anamnestic data only, thus leading to a potential risk of patient mis-stratification. Consequently, some patients may be mistakenly advised to not to be vaccinated, giving them a high risk of contracting severe forms of COVID-19 in case of infection. In addition, further allergic investigations performed on this population may result in unnecessary costs for the health care system. On the other hand, underestimated risks of developing hypersensitivity reactions may lead to unexpected allergic reactions during vaccination. Although the number of patients included in the present study was small, the results are encouraging in supporting a potential future use of HRV as an additional tool to characterize subjects with a relevant history of severe allergic reactions when undergoing vaccination. Although our findings should be interpreted with caution, this study has several strengths. We had the possibility of studying a population (those with a relevant past history of severe allergic reactions undergoing vaccination) that is usually difficult to identify; indeed, this was made feasible because of the magnitude of the global pandemic and the Italian strategy to render COVID-19 vaccination mandatory to identify the populations at high risk before vaccination. Second, as opposed to previous studies, we included a control group in our study. However, we acknowledge some limitations: first, our study population was comprised of individuals deemed to be at high risk of hypersensitivity reactions to vaccination by traditional risk factors and not those who had developed allergic reactions after a previous vaccine administration. Indeed, none of the participants developed hypersensitivity reactions after vaccination. Second, it is still not clear if sympathetic hyperactivity can increase the severity of systemic hypersensitivity reactions or if an allergic status causes a dysregulation of the autonomic nervous system by itself. Finally, a limited number of subjects underwent vaccination in the later stages of vaccination campaign (up until 1 February 2022, 46.1 million citizens were fully vaccinated in Italy. On 31 January 2023, 47.9 million citizens were fully vaccinated); therefore, less than $2\%$ of citizens in Italy underwent vaccination in the last year. In our single-center study, we enrolled subjects undergoing vaccination during the study period in our center. Considering this limitation, we decided not to perform a baseline-matched case–control analysis. As a result, some baseline characteristics were significantly different between the individuals of the study and the control group (e.g., age, sex). We cannot exclude that baseline differences between the study group and the control group may have influenced our results. Individuals in the study group were younger and more frequently female. Notably, being female is a known risk factor for the development of anaphylactic and non-anaphylactic reactions, which could explain the higher number of female subjects in the study group than in the control group of the present study; however, in previous studies, people who were female and of a younger age were associated with high HRV in contrast to our findings [45]. It is possible to hypothesize that these baseline characteristics did not influence our results, but we cannot completely exclude them. In addition, HRV values in the study group were also low when compared with the expected values in the general population. Furthermore, the control group had HRV values consistent with those expected in the general population. Another source of uncertainty is that other factors may have had an influence on HRV measurements. For instance, subjects of the study group used antiallergic medications more frequently than the control group. Thus far, there are no available data suggesting a possible interaction between antiallergic drugs with HRV parameters [44,46]; however, the number of studies in this field is so limited that any conclusion is currently impossible. In addition, it was not possible to perform subgroup analyses due to the present study’s small sample size. Further studies should be performed to investigate the potential influencing role of the general comorbidities or the type of allergy (e.g., food, drug, respiratory) on the HRV. The autonomic nervous system activity is specific to each allergic phenotype, so further research is required to characterize the sympathetic and parasympathetic system activation profiles in different subpopulations of allergic subjects. Future larger cohort studies with a propensity score matched to the current topic are, therefore, recommended. Furthermore, the present results should be validated in a different setting. Further studies are also needed to increase the knowledge about the role of the autonomic nervous system in allergic conditions. 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--- title: Associations between Adipokines and Metabolic Dysfunction-Associated Fatty Liver Disease Using Three Different Diagnostic Criteria authors: - Jie Pan - Yijie Ding - Yan Sun - Qiuyan Li - Tianyi Wei - Yingying Gu - Yujia Zhou - Nengzhi Pang - Lei Pei - Sixi Ma - Mengqi Gao - Ying Xiao - De Hu - Feilong Wu - Lili Yang journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051925 doi: 10.3390/jcm12062126 license: CC BY 4.0 --- # Associations between Adipokines and Metabolic Dysfunction-Associated Fatty Liver Disease Using Three Different Diagnostic Criteria ## Abstract Background: A panel of experts proposed a new definition of metabolic dysfunction-associated fatty liver disease (MAFLD) in 2020. To date, the associations between adipokines, such as adiponectin, adipsin, and visfatin and MAFLD remain unclear. Therefore, we aimed to evaluate the associations between each of these three adipokines and MAFLD using different diagnostic criteria. Methods: In total, 221 participants were included in our study based on medical examination. Detailed questionnaire information, physical examination, abdominal ultrasound, and blood-biochemical-test indexes were collected. The levels of adipokines were tested by using an enzyme immunoassay. Logistic regression models were used to assess the associations of the adipokines with MAFLD. Results: In total, 122 of the participants were diagnosed with MAFLD. Higher levels of adipsin and lower levels of adiponectin were found in the MAFLD group than in the non-MAFLD group (all $p \leq 0.05$). According to the logistic regression analysis, the ORs were 0.11 ($95\%$ CI: 0.05–0.23) for adiponectin, 4.46 ($95\%$ CI: 2.19–9.12) for adipsin, and 0.51 ($95\%$ CI: 0.27–0.99) for visfatin when comparing the highest tertile with the lowest tertile (all p-trend < 0.05). The inverse association between adiponectin and MAFLD was strongest when T2DM was used as the diagnostic criterion alone, and the positive association between adipsin and MAFLD was strongest when BMI was used as the diagnostic criterion alone. There was no significant association between visfatin and MAFLD, regardless of whether each of BMI, T2DM, or metabolic dysregulation (MD) was used as the diagnostic criterion for MAFLD alone. Conclusion: Adipsin levels were positively associated with MAFLD and adiponectin levels were inversely associated with MAFLD. The strength of these associations varied according to the different diagnostic criteria for MAFLD. ## 1. Introduction The term “nonalcoholic fatty-liver disease” (NAFLD) was first coined by Ludwig et al. in 1980 to describe the disease of fatty liver without significant alcohol consumption [1]. In general, NAFLD is defined as steatosis in more than $5\%$ of hepatocytes without significant alcohol consumption and other known causes of liver disease [2,3,4,5]. Nonalcoholic fatty-liver disease is related to metabolic comorbidities [6,7], and the role of metabolic risk factors in the progression of NAFLD should not be ignored. The pathogenesis of NAFLD is complex. Genetic susceptibility, environment, and metabolic risk factors interact with each other, which promote the development of NAFLD and increase the risk of disease progression [8]. The nomenclature and diagnostic criteria of NAFLD were not revisited until 2020. A panel of international experts proposed a new definition of metabolic dysfunction-associated fatty liver disease (MAFLD) in 2020 [9]. Metabolic dysfunction-associated fatty liver disease is a hepatic manifestation of systemic metabolic dysfunction [8]. It is diagnosed based on hepatic steatosis and one of three other criteria: overweight/obesity, type 2 diabetes mellitus, or metabolic dysregulation [9]. The overall prevalence of MAFLD was $38.77\%$ ($95\%$ CI: 32.94–$44.95\%$) according to a meta-analysis [10], notably exceeding previous estimates of the global prevalence of NAFLD [11,12,13]. The factors secreted by adipose tissue are collectively referred to as adipokines [14]. Adipokines signal key organs to maintain metabolic homeostasis, and their dysfunction has been implicated in a vast range of metabolic disorders [15]. Adiponectin is the most abundant peptide secreted by adipocytes [16] and has anti-inflammatory properties in the liver [17]. The adiponectin levels were low in patients with fatty-liver disease [18]. The addition of adiponectin in mice can significantly improve hepatomegaly and steatosis [19]. Adipsin (also known as complement factor D) was identified as the first adipokine to be highly expressed in adipocytes [20,21]. It plays a key role in glycolipid metabolism, energy balance, and maintaining islet beta cell function [22,23,24]. Visfatin is an adipokine produced and secreted primarily by visceral white adipose tissue [25]. According to a literature review, controversy remains in current studies on the role of visfatin in insulin resistance, hepatic steatosis, and hepatic fibrosis [26]. Associations between MAFLD and the three adipokines, adiponectin, adipsin, and visfatin, have not been reported until now. In this study, we aimed to investigate the associations of adiponectin, adipsin, and visfatin with MAFLD by using different diagnostic criteria. We also analyzed the differences in adipokine levels between participants with and without metabolic dysregulation. ## 2.1. Study Population In total, 221 participants were included in our study based on medical examination at the Physical Examination Center of the Third Affiliated Hospital of Sun Yat-sen University from April 2016 to September 2016. The grouping characteristics of the participants are presented in Figure 1. This study was conducted according to the Declaration of Helsinki and was approved by the Ethics Committee of the School of Public Health at Sun Yat-sen University. Written informed consent was obtained from all participants. ## 2.2. Clinical- and Laboratory-Data Collection Participants were interviewed face-to-face by trained investigators using structured questionnaires to collect information concerning demographic sociological characteristics, behavior, and lifestyle. A vertical ruler and digital scale were used to measure participants’ heights and weights, while an anthropometric tape was used to gauge waist circumference and hip circumference. Participants’ blood pressure was measured with an electronic sphygmomanometer on their left arm. Note that all the above measurements were conducted twice and the values were averaged. Body mass index (BMI) was calculated as weight (kg)/[height (m)]2. The imaging of a normal liver can be identified by similarity in sonogram echoes between the kidney or spleen and liver. The following characteristics were used to detect fatty liver by ultrasonography: liver parenchyma appeared more echogenic than renal cortex, posterior-beam attenuation was present, vessels were less visible, and diaphragmatic appearance appeared abnormal [27,28]. A 10-milliliter fasting blood sample was obtained from each participant in the morning after overnight fasting (free of food intake for more than 8 h before blood drawing). The serum was separated into several aliquots and stored at −80 °C within 2 h. Blood biochemistry was examined and routine blood tests were performed in the clinical laboratory of the hospital. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), total cholesterol (TC), triglycerides (TG), low-density-lipoprotein cholesterol (LDL-C), high-density-lipoprotein cholesterol (HDL-C), uric acid (UA), and fasting glucose were measured by an automatic biochemical analyzer (Hitachi 7600, Tokyo, Japan). A quantitative sandwich enzyme-linked immunosorbent assay was used to test adiponectin and adipsin levels (R&D Systems, Minneapolis, MN, USA). A competitive enzyme immunoassay (RayBiotech, Norcross, GA, USA) was used to test visfatin levels. ## 2.3. Working Definitions Hepatic steatosis can be diagnosed with abdominal ultrasound diagnosis or by fatty-liver index (FLI) greater than 60 [29] or hepatic-steatosis index (HSI) greater than 36 [30]. Metabolic-dysfunction-associated fatty-liver disease is diagnosed by hepatic steatosis (detected by imaging techniques, blood biomarkers/scores, or liver histology) combined with any one of the following three criteria: overweight/obesity, type 2 diabetes mellitus, or metabolic dysregulation. [ 9]. Overweight/obesity is defined as BMI ≥ 23 kg/m2 in Asians. An individual diagnosed with metabolic dysregulation (MD) has at least two metabolic risk abnormalities: (i) waist circumference ≥ $\frac{90}{80}$ cm in Asian men and women; (ii) blood pressure ≥ $\frac{130}{85}$ mmHg or specific drug treatment; (iii) plasma triglycerides (TG) ≥ 1.70 mmol/L or specific drug treatment; (iv) plasma HDL-C < 1.0 mmol/L for men and <1.3 mmol/L for women or specific drug treatment; (v) prediabetes (fasting glucose levels 5.6 to 6.9 mmol/L); (vi) homeostasis model assessment of insulin-resistance (HOMA-IR) score ≥ 2.5; and (vii) plasma high-sensitivity C-reactive protein (hs-CRP) level > 2 mg/L [9]. Hypertension was diagnosed by systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥ 90 mmHg. Type 2 diabetes mellitus (T2DM) was defined by having fasting glucose ≥ 7.0 mmol/L or a history of T2DM. The definition of dyslipidemia was as follows: TC ≥ 6.2 mmol/L or TG ≥ 2.3 mmol/L or HDL-C < 1.0 mmol/L or LDL-C ≥ 4.1 mmol/L [31]. For the current study, smoking was defined as more than one cigarette per day for six months and alcohol drinking was defined as drinking at least one time per week for six months. The FLI was calculated using the following formula [29]:FLI = (e 0.953 × loge (triglycerides) + 0.139 × BMI + 0.718 × loge (ggt) + 0.053 × waist circumference − 15.745)/(1 + e 0.953 × loge (triglycerides) + 0.139 × BMI + 0.718 × loge (ggt) + 0.053 × waist circumference − 15.745) × 100 Triglycerides, mg/dL (1 mg/dL = 0.0113 mmol/L); BMI, kg/m2; GGT, U/L; waist circumference, cm. The HSI was calculated using the following formula [30]:HSI = 8 × ALT/AST ratio + BMI (+2, if DM; +2, if female) ## 2.4. Statistical Analysis Continuous variables were presented as means ± standard deviation or median (interquartile range), depending on whether the data were normally distributed. Categorical variables were described as frequency (percentage). Independent-samples t-test, Mann–Whitney U-test, and Pearson chi-square test were used for comparison between two groups. Kruskal–Wallis test was used to compare multiple groups. The logistic regression model was used to examine the associations of adipokines with MAFLD. The lowest tertile of adipokine levels served as the reference group. Tests for trends across the tertile of adipokines levels were evaluated by using a median value within each tertile as a continuous value. One participant had an AST level of 419 U/L and an ALT level of 780 U/L, which were considered as extreme outliers; he was therefore excluded. Eventually, 221 participants were included in the analysis. All statistical analyses were performed using SPSS 25.0 software (SPSS Inc., Chicago, IL, USA) and R version 4.2.0. The significance threshold was 0.05, and all tests were 2-sided. ## 3.1. Comparison of Adipokines between the Non-MAFLD and MAFLD Group (Three Diagnostic Criteria) As shown in Figure 2, higher levels of adipsin and lower levels of adiponectin were found in the MAFLD groups (regardless of whether the diagnostic criteria were BMI, MD, or T2DM) than in the non-MAFLD group (all $p \leq 0.05$). However, no statistical significance was found in the difference in visfatin levels between the non-MAFLD group and the MAFLD group (regardless of whether the diagnostic criteria were BMI, MD, or T2DM). ## 3.2. Comparison between the Non-MAFLD Group and the MAFLD Group All the participants were divided into two groups (the non-MAFLD group and the MAFLD group) based on whether they had MAFLD. Through univariate comparisons between the two groups, the WC, WHR, BMI, SBP, DBP, TC, TG, LDL-C, fasting glucose, ALT, AST, GGT, UA, PLT, FLI score, and HSI score were found to be higher in the MAFLD group than in the non-MAFLD group. In addition, the MAFLD group contained a higher proportion of subjects who also had T2DM, hypertension, and dyslipidemia. It was noteworthy that the adipsin levels were significantly higher in the MAFLD group compared to those in the non-MAFLD group (889.06 (528.99–1379.60) ng/mL vs. 632.63 (379.32–908.19) ng/mL, $p \leq 0.001$). Conversely, those in the MAFLD group had lower levels of adiponectin in comparison with those in the non-MAFLD group, with levels of 2.17 (1.56–2.98) µg/mL and 3.60 (2.41–4.96) µg/mL, respectively ($p \leq 0.001$). The visfatin levels were similar between the two groups, with levels of 27.12 (23.49–33.33) ng/mL and 30.31 (25.08–37.46) ng/mL in the MAFLD and non-MAFLD groups, respectively ($$p \leq 0.052$$; Table 1). ## 3.3. Differences in the Distribution of Adipokine Tertile Levels between the MAFLD and Non-MAFLD Groups Figure 3 shows the differences in the distribution of the adiponectin, adipsin, and visfatin tertile levels between the MAFLD and non-MAFLD groups. The highest tertile level (T3) of adiponectin accounted for more than $50\%$ in the non-MAFLD group but less than $20\%$ in the MAFLD group ($p \leq 0.001$). Conversely, the highest tertile (T3) of adipsin was $45.9\%$ in the MAFLD group, but less than $20\%$ in the non-MAFLD group ($p \leq 0.001$). The distribution of the visfatin levels did not differ significantly between the two groups ($$p \leq 0.103$$). ## 3.4. Associations of Adiponectin, Adipsin, and Visfatin with MAFLD The ORs for the associations of MAFLD with adiponectin, adipsin, and visfatin are shown in Table 2. In model 1, the ORs of MAFLD were 0.11 ($95\%$ CI: 0.05–0.23; p-trend < 0.001) for adiponectin, 4.46 ($95\%$ CI: 2.19–9.12; p-trend < 0.001) for adipsin, and 0.51 ($95\%$ CI: 0.27–0.99; p-trend = 0.037) for visfatin in the highest tertile compared with those in the lowest tertile. In model 2, after adjusting for age, gender, smoking, drinking, physical activity, AST, and ALT, the ORs of MAFLD were 0.12 ($95\%$ CI: 0.05–0.30; p-trend < 0.001) for adiponectin, 6.90 ($95\%$ CI: 2.71–17.61; p-trend < 0.001) for adipsin, and 0.54 ($95\%$ CI: 0.24–1.20; p-trend = 0.122) for visfatin in the highest tertile compared with those in the lowest tertile. The inverse association between adiponectin and MAFLD (the highest tertile vs. the lowest tertile) was the strongest when T2DM was used as the diagnostic criterion alone (Figure 4A), and the positive association between adipsin and MAFLD (the highest tertile vs. the lowest tertile) was the strongest when BMI was used as the diagnostic criterion alone (Figure 4B). In addition, there were no significant associations between visfatin and MAFLD, regardless of whether each of BMI, MD, or T2DM was used as the diagnostic criterion alone for MAFLD (Figure 4C). After adjusting for multiple potential confounders, there were no significant changes in the associations between the three adipokines and MAFLD under the three diagnostic criteria (Figure 5). ## 3.5. Differences in Adipokine Levels in the Presence or Absence of Metabolic Dysregulation Compared with the group without MD, the group with MD had lower adiponectin levels ($p \leq 0.001$). Conversely, the MD group had higher adipsin levels than the non-MD group ($$p \leq 0.017$$). However, the visfatin levels did not differ significantly between the two groups and were similarly distributed ($$p \leq 0.414$$; Figure 6). ## 4. Discussion According to the analysis of the 221 participants, we found higher levels of adipsin and lower levels of adiponectin in the MAFLD group than in the non-MAFLD group. The inverse association between adiponectin and MAFLD was at its strongest when T2DM was used as the diagnostic criterion alone, and the positive association between adipsin and MAFLD was the strongest when BMI was used as the diagnostic criterion alone. There was no significant association between visfatin and MAFLD, regardless of whether BMI, MD, or T2DM was used as the diagnostic criterion alone for MAFLD. Adiponectin ameliorated hepatomegaly and steatosis and decreased the levels of liver enzymes in mice [19]. In a model of rhesus monkeys that spontaneously developed obesity and subsequently developed type 2 diabetes, the plasma adiponectin levels were also decreased [32]. A systematic review and meta-analysis also reported that higher adiponectin levels were consistently associated with a lower risk of type 2 diabetes in prospective studies of diverse populations [33]. Chow et al. reported an independent association between hypoadiponectinemia and hypertension [34]. Additionally, several studies reported lower adiponectin levels in patients with hepatic steatosis than in controls [35,36,37]. The research results regarding adiponectin in animals and humans are consistent: it appears to have a protective effect on metabolism-related diseases. Similarly, in our study, we found that the participants without MAFLD or MD had higher adiponectin levels compared with the controls and that adiponectin levels were inversely associated with MAFLD. This association was at its strongest when T2DM was used as the diagnostic criterion alone. After adjusting for potential confounding factors, the degree of this association was retained. This may have been due to the close association between adiponectin and T2DM. Currently, adiponectin is among the strongest and most consistent biochemical predictors of T2DM [38]. Adipsin increases lipid accumulation and adipocyte differentiation [39]. According to previous reports, in human studies of metabolism-related diseases (such as obesity, diabetes, and metabolic syndrome), adipsin levels were higher compared to controls [40,41,42,43]. Since the definition of MAFLD involves hepatic steatosis, overweight/obesity, metabolic dysregulation, and diabetes, it may be reasonable to speculate that increased circulating levels of adipsin are associated with MAFLD. In our study, we found that the people with MAFLD or MD had higher levels of adipsin than the controls and that adipsin levels were positively associated with MAFLD. This association was at its strongest when BMI was used as the diagnostic criterion alone, and this phenomenon persisted after adjusting for several potential confounding factors. On one hand, adipsin may be more strongly associated with BMI than T2DM or MD. On the other, the association may have arisen because the sample size of MAFLD diagnosed by BMI alone was the largest. With respect to visfatin, it has been reported that the serum visfatin concentration was significantly higher in obese women compared to non-obese women [44]. A systematic review and meta-analysis found that plasma visfatin was significantly increased in subjects diagnosed with overweight/obesity, T2DM, and metabolic syndrome [45]. However, another review indicated that visfatin levels were not associated with NAFLD, the presence or severity of hepatic steatosis, NASH, or gender [46]. Ismaiel et al. reported that no significant difference in serum visfatin levels in MAFLD patients compared with controls was found [16]. Currently, the findings regarding the association of visfatin with metabolism-related diseases or liver diseases are still controversial. In this study, we found no difference in visfatin levels between the MAFLD and non-MAFLD groups and the distribution of visfatin levels was similar between the MD and non-MD groups. In addition, no association was observed between visfatin and MAFLD, regardless of whether each of BMI, MD, or T2DM was used as the diagnostic criterion alone. There are three possible explanations for the results of this study: [1] the association between visfatin itself and metabolism-related diseases is relatively weak; [2] different population sources and study designs can influence results; and [3] the sample size of this study was not sufficiently large. The new definition of MAFLD may reduce patients’ confusion about the true cause of fatty-liver disease, which, in turn, could lead to better communication between doctors and patients. Using “positive” features to diagnose MAFLD can better stratify the risks of patients, and, subsequently, help to take targeted prevention and treatment measures to improve clinical efficacy. This is difficult to accomplish with NAFLD, which is defined by using certain conditions as the exclusion criteria. Unlike cases of NAFLD only, the MAFLD criteria can help identify a meaningful group of people with more comorbidities and worse prognoses [47]. Lin et al. reported that the MAFLD definition is more practical for identifying patients with fatty-liver disease with a high risk of disease progression [48]. This change in terminology will affect drug development and biomarker discovery. The use of different diagnostic criteria may influence the potential biomarkers of MAFLD. Although epidemiologic associations between adipokines and metabolism-related diseases have been established, the causal relationship and the exact molecular mechanisms are still unclear. Large-sample prospective-study designs are needed to further validate whether these adipokines can act as potential biomarkers of MAFLD under different diagnostic conditions. Ultrasound is less sensitive for detecting hepatic steatosis in individuals with steatosis of less than $20\%$ or with a BMI greater than 40 [9]. Therefore, in our study, we diagnosed hepatic steatosis by ultrasound or fatty-liver index or hepatic-steatosis index, which is a more reliable approach than using ultrasound alone. In addition, FLI and HSI have higher cut-off values for diagnosing hepatic steatosis (60 and 36, respectively), so there is less misclassification bias. Nevertheless, there are some limitations in our study. First, this is a descriptive study, which can only draw epidemiological associations, not causal inferences, although it can provide clues for further mechanistic studies. Second, the effect of HOMA-IR and hs-CRP on MAFLD could not be investigated due to the lack of data on their levels. Third, the participants in this study were mainly men, so the conclusions drawn from the study should be extended to women with caution. 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--- title: Regulation of Aqueous Humor Secretion by Melatonin in Porcine Ciliary Epithelium authors: - Ka-Lok Li - Sze-Wan Shan - Fang-Yu Lin - Choi-Ying Ling - Nga-Wai Wong - Hoi-Lam Li - Wei Han - Chi-Ho To - Chi-Wai Do journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051954 doi: 10.3390/ijms24065789 license: CC BY 4.0 --- # Regulation of Aqueous Humor Secretion by Melatonin in Porcine Ciliary Epithelium ## Abstract Secretion of melatonin, a natural hormone whose receptors are present in the ciliary epithelium, displays diurnal variation in the aqueous humor (AH), potentially contributing to the regulation of intraocular pressure. This study aimed to determine the effects of melatonin on AH secretion in porcine ciliary epithelium. The addition of 100 µM melatonin to both sides of the epithelium significantly increased the short-circuit current (Isc) by ~$40\%$. Stromal administration alone had no effect on the Isc, but aqueous application triggered a $40\%$ increase in Isc, similar to that of bilateral application without additive effect. Pre-treatment with niflumic acid abolished melatonin-induced Isc stimulation. More importantly, melatonin stimulated the fluid secretion across the intact ciliary epithelium by ~$80\%$ and elicited a sustained increase (~50–$60\%$) in gap junctional permeability between pigmented ciliary epithelial (PE) cells and non-pigmented ciliary epithelial (NPE) cells. The expression of MT3 receptor was found to be >10-fold higher than that of MT1 and MT2 in porcine ciliary epithelium. Aqueous pre-treatment with MT1/MT2 antagonist luzindole failed to inhibit the melatonin-induced Isc response, while MT3 antagonist prazosin pre-treatment abolished the Isc stimulation. We conclude that melatonin facilitates Cl− and fluid movement from PE to NPE cells, thereby stimulating AH secretion via NPE-cell MT3 receptors. ## 1. Introduction Glaucoma is a sight-threatening disease characterized by a gradual and permanent loss of retinal ganglion cells, resulting in progressive loss of vision. Although the pathogenesis of glaucoma is not fully understood, elevated intraocular pressure (IOP) remains as the only modifiable risk factor identified thus far. IOP is dictated by the rates of aqueous humor (AH) secretion and drainage. The ciliary epithelium, which is composed of pigmented ciliary epithelium (PE) and non-pigmented ciliary epithelium (NPE) layers, actively secretes AH. After that, AH exits the eye primarily through the conventional pressure-dependent trabecular meshwork (TM) outflow pathway. Active Cl− transport across the ciliary epithelium has been shown to be the major driving force for AH secretion [1,2]. The intercellular gap junctions at the apical surfaces of PE and NPE cells link these two cell layers to work in a coordinated manner as a syncytium [3,4,5]. In addition, swelling-activated Cl− channels located at the basolateral membrane of NPE cells are thought to likely play important roles in regulating AH secretion rates via Cl− release [3,6,7]. Melatonin, a natural hormone potentially regulating AH dynamics, is an indole-derived compound primarily secreted by the pineal gland of the brain [8,9]. It can also be synthesized by ocular tissues, including the ciliary body and the retina [8,10]. Melatonin is involved in maintaining circadian rhythms and synchronizing various body functions, including maintenance of tissue metabolism, core body temperature, immune response, hormonal homeostasis, and blood pressure [10,11]. Two melatonin receptors, MT1 and MT2, and a putative MT3 receptor have been identified [12]. MT1 and MT2 are G protein-coupled receptors, while MT3, a detoxification cytosolic enzyme, has been suggested to belong to the reductase group, quinone reductase 2 (NQO2) [13]. The melatonin-binding site of MT3, purified from Syrian hamster kidney has been identified as the hamster homolog of the human NQO2 [14]. Melatonin receptors have been shown to express in the ciliary body of various species [9]. For example, MT1 receptor is present in rabbits, while MT2 receptor has been found in both rabbits and humans [15,16]. MT3 receptor has been demonstrated in African clawed frogs (Xenopus laevis) [17]. Physiologically, melatonin levels in the AH display diurnal variation [12,18], supporting its potential significance in regulating the circadian rhythm of AH dynamics and thereby IOP. While several studies have shown that administration of melatonin or its analogues lowers IOP in both humans [19,20,21] and animals [22,23,24,25], others have not observed this melatonin-induced IOP-lowering effect [26,27]. Recently, higher levels of melatonin in the AH were detected in patients with higher IOPs [28]. This controversy hinders the understanding of the precise functional significance of melatonin in regulating AH dynamics. This study aimed to determine the direct effects of melatonin on AH secretion across porcine ciliary epithelium, which is considered as a good animal model to mimic human conditions [29]. This was achieved by evaluating the cellular effects of melatonin on transepithelial Cl− and fluid secretion, as well as gap junction permeability. The effects of various melatonin receptor antagonists on transepithelial Cl− transport were also investigated. ## 2.1. Melatonin Increases Short-Circuit Current (Isc) across Porcine Ciliary Epithelium The effects of melatonin at different concentrations (1, 10, and 100 μM) on Isc across porcine ciliary epithelium were determined using a modified Ussing chamber. When administered bilaterally (i.e., applied to both stromal and aqueous sides), melatonin had no effect on Isc at 1 and 10 μM (Figure 1). However, at 100 μM, it significantly stimulated the Isc by 38 ± $6\%$. Addition of melatonin only to the aqueous side triggered a similar concentration-dependent Isc stimulation (Figure 2A). The melatonin-induced Isc stimulation was only observed at 100 μM (40 ± $9\%$), but not at 1 or 10 μM. In contrast, no significant effect was observed at all concentrations tested when melatonin was added to the stromal side alone (Figure 2B). The latency period after the administration of melatonin between the bilateral (42 ± 8 min) and aqueous (52 ± 9 min) applications were similar ($p \leq 0.05$, Student’s t-test). In addition, the melatonin-induced Isc stimulation observed in both aqueous and bilateral application was abolished by the addition of 1 mM niflumic acid (NFA), a non-selective Cl− channel blocker. These results strongly suggested that melatonin stimulated Cl− secretion across the porcine ciliary epithelium by enhancing Cl− release from NPE cells into the posterior chamber. ## 2.2. Melatonin Stimulates Transepithelial Fluid Flow and Electrical Measurements To confirm whether melatonin exerts any direct effect on fluid secretion, both Isc and transepithelial fluid movement were monitored simultaneously with a fluid flow chamber. The changes in Isc and fluid flow are summarized in Figure 3. Addition of melatonin (100 µM) to the aqueous side elicited a concomitant stimulation of Isc and fluid movement in the stromal-to-aqueous direction. A sustained increase in fluid flow was observed from the baseline value of 1.22 ± 0.14 µL/h to a maximum of 2.27 ± 0.29 µL/h after 90 min of melatonin treatment (Figure 3A). ## 2.3. Melatonin Enhances Gap Junction Permeability between PE and NPE Cells As melatonin has been reported to modulate gap junction permeability [30,31], the effect of pre-treatment with heptanol, a non-selective gap junction blocker on Isc was investigated (Figure 4). Bilateral addition of heptanol (3.5 mM) abolished the baseline Isc and completely inhibited the subsequent melatonin-induced Isc stimulation across the porcine ciliary epithelium, suggesting that melatonin might increase Cl− secretion by enhancing gap junction permeability. The lucifer yellow (LY) dye transfer technique was employed to confirm whether melatonin has a direct effect on gap junction permeability. The diffusion of LY dye from PE to NPE cell couplet is shown in Figure 5. The relative fluorescence intensities (F ratios) of melatonin-treated and control groups were monitored for 30 min. The results showed that melatonin (100 μM) significantly enhanced the gap junction permeability across isolated PE-NPE cell couplets. At 15 min, the F ratios of the melatonin and the control groups were 2.64 ± 0.38 and 1.68 ± 0.15, respectively, indicating a $60\%$ increase in gap junction permeability compared with the control. Similarly, pre-treatment with 100 μM melatonin for 45 min triggered a sustained increase in gap junction permeability. At 15 min, the F ratios of the melatonin-pretreated and the control groups were 3.06 ± 0.44 and 1.68 ± 0.15, respectively. The F ratios between the melatonin-pretreated and melatonin groups was not statistically significant at all time points (Figure 5). ## 2.4. Melatonin Stimulates Cl− Secretion via MT3 Receptor The gene expression level of melatonin receptors MT1, MT2, and MT3 was quantified in porcine NPE cells using RT-qPCR. The results demonstrated that MT3 was the most abundant isoform compared with MT1 and MT2 receptors (Figure 6). In addition, effects of two melatonin antagonists, luzindole (an MT1/MT2 receptor antagonist) and prazosin (a putative MT3 receptor antagonist) were investigated. Both antagonists were pre-treated at the aqueous side of the ciliary epithelium prior to aqueous administration of melatonin (100 μM). The results indicated that luzindole (10 μM) did not affect the baseline Isc (Figure 7). Interestingly, luzindole enhanced the melatonin-induced Isc stimulation compared with application of melatonin alone ($p \leq 0.05$, Student’s t-test). The subsequent addition of 1 mM NFA significantly inhibited the melatonin-induced Isc stimulation, in either the presence or absence of luzindole pre-treatment. The effects of prazosin (1.5 μM and 10 μM) on Isc are summarized in Figure 8. At 1.5 μM, prazosin had no significant effects on either baseline Isc or the subsequent melatonin-induced Isc stimulation. At 10 μM, prazosin pre-treatment did not affect the baseline Isc, but significantly inhibited the subsequent melatonin-induced Isc stimulation. Similar to luzindole, the subsequent addition of 1 mM NFA abolished Isc stimulation after prazosin pre-treatment ($$n = 5$$, $p \leq 0.001$, Student’s t-test). ## 3. Discussion The results of this study suggest that melatonin, when administered to the aqueous side, elicits a concomitant stimulation of transepithelial Cl− and fluid secretion across the isolated porcine ciliary epithelium, potentially increasing the rate of AH secretion. This finding was supported by the melatonin-induced facilitation of transcellular fluid movement from the PE to NPE in isolated cell couplets. The melatonin-induced stimulation of Cl− secretion was mediated through MT3 receptors. Similar to IOP, the level of melatonin in the AH displays a diurnal variation [12,18]. The concentration of melatonin in the AH has been shown to increase by 2–3 fold at night in rabbits [32] and humans [33,34], suggesting its potential contribution to the regulation of AH dynamics and IOP. Studies have shown that topical administration of melatonin or its analogues reduces IOP in rabbits and monkeys [22,25,35]. Human studies have also demonstrated that oral intake of melatonin or its analogues lowers IOP [19,20,21]. This is also supported by a study reporting that urinary melatonin levels in high-tension glaucoma patients were lower compared to those of control subjects [36]. Despite these reports, there has been no consensus on the pathway for melatonin to achieve IOP reduction. Based on a study using MT1 knock-out mice, it has been postulated that the MT1 receptor is primarily responsible for the ocular hypotensive effect [37]. Other studies have demonstrated that selective MT2 antagonists block the IOP-lowering effects of melatonin and its analogues [24]. In contrast, MT3 receptors have been proposed to trigger melatonin-induced IOP reduction [22,25]. To date, the precise cellular effects of melatonin in modulating AH secretion are still unconfirmed. The results of the current study showed that low concentrations of melatonin (1 or 10 μM) had no effect on Isc, when added to both stromal and aqueous sides, whereas a significant increase in Isc was observed at 100 μM. The increase in Isc may reflect a stimulation of net transepithelial Cl− secretion across the ciliary epithelium [38]. Melatonin is highly lipophilic and can penetrate and/or diffuse across plasma membrane influencing both PE and NPE cells. However, administration of melatonin to the stromal side had a subtle effect on Isc (Figure 2B). On the contrary, melatonin, when applied to the aqueous side alone, produced similar responses to that of bilateral administration of melatonin with no additive effect (Figure 2A). This result strongly suggest that the effect of melatonin is primarily mediated in NPE cells [39]. This notion was further supported by the evidence that Isc stimulation by melatonin was completely blocked by either heptanol or NFA, indicating that solute uptake in PE cells was not rate limiting [38,40]. To confirm whether melatonin directly acts on active Cl− and fluid secretion, the effect of melatonin on the transepithelial ion and fluid secretion across the intact porcine ciliary epithelium was determined. In agreement with the results obtained from electrical parameter measurements, we showed that melatonin, when applied to the aqueous side, triggered a ~$80\%$ increase in fluid secretion across the porcine ciliary epithelium. To the best of our knowledge, this is the first report of melatonin-stimulated fluid secretion concomitant with an increase in Isc. The melatonin-stimulated fluid secretion was further substantiated by the results demonstrating that melatonin [1] failed to stimulate Isc after heptanol pre-treatment and [2] enhanced transcellular fluid transfer from PE and NPE cells, as revealed by a sustained increase in LY dye transfer across isolated PE-NPE cell couplets. These results are in line with previous studies that melatonin plays a pivotal role in regulating gap junction permeability in various cell types [30,31,41,42,43]. Our finding suggests that melatonin may increase Cl− secretion by enhancing gap junction permeability. This finding differs from a recent study in which melatonin and its analogue 5-MCA-NAT were shown to inhibit Cl− efflux by rabbit NPE cells [39]. The exact reason for this discrepancy is not clear but could, at least in part, be explained by species differences [44]. It has been suggested that integrated transport mechanism of ions across the ciliary epithelium displays species variation [44]. In rabbits, AH secretion is primarily driven by HCO3− transport, and to a lesser extent by Cl− secretion [45,46,47]. The inhibition of Cl− efflux in NPE cells may not necessarily lead to a suppression of AH production [48]. In contrast, Cl− secretion has been shown to be the major driving force for AH secretion in animal species, including pigs, oxen, and humans [38,45,46,49]. It has been suggested that pig eye serves as a good animal model for studying human AH dynamics [5,29], partly because of their similarities to humans regarding anatomical structures, AH’s electrolyte composition, and responses to drugs [50,51,52,53]. Our current results were also in good agreement with a previous study, which demonstrated that melatonin stimulated Isc and Cl− secretion in human colonic T84 cells [54]. It Is noted that the physiological concentration of melatonin in the AH was reported to be in the range of 4–48 pg/mL [32,33] to 0.5–46.7 ng/mL [28,55], depending on the experimental conditions and methodology adopted. The reported values were lower than the concentrations of melatonin used in the current study, although the chosen concentrations still fell within the working range used in the previous studies [39,41,54,56] with no cytotoxicity reported [57]. The discrepancy could also be attributed to the compartmentalization of melatonin in the ciliary epithelial cells [28] and the differences in metabolism, such as endogenous synthesis, secretion, and degradation of melatonin between physiological and experimental conditions. In general, the functional significance of MT3 receptor is less well documented and characterized compared with MT1 and MT2 receptors [58]. Our results also provided the first evidence that melatonin potentially increases Cl− secretion and AH secretion rate through MT3 receptors. We demonstrated that pre-treatment with 10 μM luzindole, a non-selective MT1/MT2 receptor antagonist, did not inhibit melatonin-induced Isc stimulation. This lack of inhibition exerted by luzindole suggested that the melatonin-induced response was not mediated through MT1/MT2 receptors. This finding was in parallel with a recent study in which melatonin-induced effect was enhanced, rather than prevented, by MT1/MT2 receptor antagonists [39]. In contrast, although pre-treatment with 1.5 μM prazosin, an MT3 receptor antagonist, had no effect on melatonin-induced Isc stimulation, at a higher concentration (10 μM), it abolished Isc stimulation by melatonin. It has been reported that prazosin (at 1.5 μM) was sufficient to inhibit the melatonin-induced response [39], but in the current study the inhibitory effect of prazosin was only observed at higher concentration. This difference may be explained by: [1] species difference in affinity to prazosin at the binding sites [59,60,61] and [2] difference in sample preparations as immortalized cultured NPE cells were used in the earlier study [39], whereas excised ciliary epithelium was used in the current study. The freshly isolated ciliary epithelium preparation may have vitreous humor attached to the ciliary epithelium, potentially hindering the access of melatonin to the target site(s), such as NPE cells [29]. Little is known about the presence of MT3 receptors in human ciliary epithelium. We found that the MT3 receptor was the most abundant isoform among all melatonin receptors in porcine ciliary epithelium, an animal model compared favorably with humans [29,62]. Additional work is warranted to determine the precise expression of melatonin receptors in human ciliary epithelium in the future. Physiologically, melatonin has been demonstrated to trigger cellular effects via various signaling cascades, including cAMP, cGMP, PI3K/AKT, calmodulin, and phospholipase C [63,64,65,66,67,68]. In addition to intercellular gap junctions linking PE and NPE cells, it is likely that melatonin may affect Cl− channels at the basolateral membrane of NPE cells. Although the identities of Cl− channels are not fully understood [69], Cl− efflux by NPE cells is a crucial step for AH secretion [6,7]. In our study, the melatonin-induced Isc stimulation was abolished by NFA administered to the aqueous side, suggesting that Cl− channels might be a potential target for the observed response. Further studies are required to investigate the mechanistic actions of melatonin and its antagonists on the regulation of NPE-cell Cl− channels. This study’s in vitro findings suggest that melatonin may potentially stimulate Cl− and, thereby, AH secretion, possibly through putative MT3 receptors (Figure 9). This result was in good agreement with a recent study that there was a good correlation between IOP and melatonin concentration in the AH [28]. Patients with ocular hypertension had a three-fold increase in melatonin concentration (46.63 ng/mL for IOP > 21 mmHg versus 14.62 ng/mL for IOP < 21 mmHg) [28]. Similarly, glaucomatous DBA/2J mice displayed a higher concentration of melatonin in the AH as compared to the control C57BL/6J mice [28]. Nevertheless, our finding differed from other reports of melatonin-induced IOP reduction in both experimental animals and humans [22,24]. As isolated porcine ciliary epithelium was used in this study, extraneous factors, including hydrostatic pressure, hormonal, and vascular influences, were excluded. In living animals, however, melatonin and its analogues may affect both AH secretion and drainage pathways concomitantly. This difference could reflect compensatory changes in outflow facility. For example, melatonin was found to stimulate voltage dependent Na+ current in human TM cells [70], potentially influencing the outflow facility and IOP. In addition, oxidative stress was reported to increase AH outflow resistance and IOP by affecting the integrity of TM cells [71,72,73]. As melatonin is a potent free radical scavenger, it is likely that melatonin may serve as an anti-oxidant by protecting TM cells against oxidative stress. Further studies are required to determine the precise functional significance of melatonin on the modulation of AH outflow resistance. ## 4.1. Transepithelial Electrical Measurements with Modified Ussing Chamber Freshly enucleated porcine eyes were obtained from a local abattoir. For Ussing chamber experiments, a sector of the ciliary body epithelium was excised [38,74]. Similar to our previous study [29], the ciliary body was mounted onto the Ussing chamber with an exposed area of 0.10 cm2. Both hemi-chambers (i.e., stromal side facing the PE and aqueous side facing the NPE) of the Ussing chamber were filled with Ringer’s solution and then bubbled with a mixture of $95\%$ O2 and $5\%$ CO2 throughout the experiment. Drugs, including melatonin, niflumic acid (NFA), luzindole, and prazosin, were added either bilaterally or to the aqueous/stromal side only, as appropriate. As melatonin is sensitive to light [75], the experiment was conducted under dim light conditions. Transepithelial electrical parameters including the Isc were monitored with a dual voltage current clamp unit (World Precision Instruments, Sarasota, FL, USA). ## 4.2. Simultaneous Electrical and Fluid Flow Measurements with Custom-Built Chamber Similar to Ussing chamber experiments, an intact annulus ring of porcine ciliary epithelium with iris attached was isolated for fluid flow measurements [29,76]. The whole ciliary body preparation was mounted between two hemi-chambers with an exposed area of 0.78 cm2. One hemi-chamber was connected to a bubbling reservoir to facilitate drug administration, while the other was connected to a 25 µL graduated capillary tube. Both sides of the chamber were filled with Ringer’s solution and bubbled with $95\%$ O2 and $5\%$ CO2 throughout the experiment. The spontaneous fluid flow was monitored every 15 min for 2–3 h by determining the changes in height of the water column in the capillary tube. ## 4.3. Measurement of Gap Junction Permeability with Lucifer Yellow (LY) Dye Transfer As reported in our previous studies, LY dye diffusion was determined across freshly isolated porcine PE-NPE cell couplets [5,77]. For each PE-NPE cell couplet, a tight seal was formed between the micropipette and the plasma membrane of the PE cell (chosen as the donor cell). Melatonin was added to the bathing solution either 45 min before (i.e., melatonin pre-treatment) or at the time of membrane rupture. After membrane rupture, the rate of LY dye diffusion from the PE (donor) cell to the NPE (recipient) cell were determined. Images were captured every 30 s for 30 min by an inverted fluorescence microscope (Nikon Corp, Tokyo, Japan). F ratio (fluorescence intensity in NPE cell compared to that of the PE cell) was used for fluid flow analysis. ## 4.4. Reverse Transcription-Real Time Polymerase Chain Reaction (RT-qPCR) As summarized previously [5], total RNA was extracted from the porcine ciliary epithelium by Qiagen RNeasy Micro Kit (Qiagen Co, Dusseldorf, Germany), quantified, and reverse transcribed to cDNA using a High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Waltham, MA, USA). Real time-qPCR was conducted using the LightCycler 480 SYBR Green I Master (Roche Applied Science, Penzberg, Germany) with primers specific for the target gene MT1 (forward primer: 5′-CTCGCGCTCATCCTCATCTT-3′; reverse primer: 5′-TTCCTGCGTTCCTCAGCTTC-3′), MT2 (forward primer: 5′-GAGCATGTTCGTGGTGTTCG-3′; reverse primer: 5′-CCTGCGGAAGTTCTGGTTCA-3′), MT3 (forward primer: 5′-TCAGGAGGCTGATCTGGTGA-3′; reverse primer: 5′-GACGGCCAGTTTACCCTTGA-3′), and the internal reference gene GAPDH. qPCR was performed in 96-well plates on the ROCHE LightCycler 480 (Roche Applied Science). A total reaction volume of 10 μL qPCR mixture containing 5 μL of 2 × Taq PCR Master Mix, 1 μL of sterile water, 2 μL of cDNA template, and 1 μL of 10 μM primers (forward and reverse primers, respectively) was used. The thermal cycling conditions were: 95 °C for 5 min, followed by 40 cycles of 95 °C for 30 s, 61 °C for 30 s and 72 °C for 30 s. A melting-curve analysis was performed to rule out primer–dimer formation and non-specific product amplification. Data were analyzed using Light LC480 software. ## 4.5. Solutions and Pharmacological Agents All chemicals were purchased from Sigma-Aldrich. HEPES-buffered Ringer’s solution, composed of (in mM) 113.0 NaCl, 21.0 NaHCO3, 10.0 HEPES, 7.5 D-Glucose, 4.56 KCl, 1.4 CaCl2, 1.0 L-Glutathione (reduced), 1.0 Na2HPO4, and 0.6 MgSO4 was used as the bathing solution for all experiments. The pH and osmolarity of the solution were adjusted to 7.4 and 300 mOsm/kg, respectively. For LY dye diffusion, the pipette solution contained 120 mM N-Methyl-D-glucamine (NMDG), 110 mM L-aspartic acid, 25 mM NaCl, 0.38 mM CaCl2, and 12 mM HEPES with 1 mg/mL LY CH, lithium salt (Invitrogen, Waltham, MA, USA). All drugs used in the study, including melatonin, luzindole, prazosin, and NFA (except heptanol), were dissolved in dimethyl sulfoxide (DMSO). The final concentration of DMSO was adjusted to <$0.1\%$ in the bathing solution. ## 4.6. Statistical Analysis All data were presented as mean ± SEM. One-way repeated measures ANOVA or Student’s t-test were used to analyze the data. $p \leq 0.05$ was considered statistically significant. ## 5. Conclusions Currently, lowering IOP is the only available clinical intervention known to delay the onset and progression of glaucomatous blindness. The results of this study indicate that melatonin increases gap junction permeability between PE and NPE cells, facilitating Cl− and fluid secretion across the porcine ciliary epithelium via MT3 receptors. Whether or not melatonin contributes to the regulation of both AH secretion and drainage, and their relationship to IOP, awaits further investigation. ## References 1. To C.H., Kong C.W., Chan C.Y., Shahidullah M., Do C.W.. The mechanism of aqueous humour formation. Clin. Exp. Optom. (2002) 85 335-349. PMID: 12452784 2. 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--- title: 'Exploring Probenecid Derived 1,3,4-Oxadiazole-Phthalimide Hybrid as α-Amylase Inhibitor: Synthesis, Structural Investigation, and Molecular Modeling' authors: - Bilal Ahmad Khan - Syeda Shamila Hamdani - Muhammad Khalid - Muhammad Ashfaq - Khurram Shahzad Munawar - Muhammad Nawaz Tahir - Ataualpa A. C. Braga - Ahmed M. Shawky - Alaa M. Alqahtani - Mohammed A. S. Abourehab - Gamal A. Gabr - Mahmoud A. A. Ibrahim - Peter A. Sidhom journal: Pharmaceuticals year: 2023 pmcid: PMC10051969 doi: 10.3390/ph16030424 license: CC BY 4.0 --- # Exploring Probenecid Derived 1,3,4-Oxadiazole-Phthalimide Hybrid as α-Amylase Inhibitor: Synthesis, Structural Investigation, and Molecular Modeling ## Abstract 1,3,4-Oxadiazole moiety is a crucial pharmacophore in many biologically active compounds. In a typical synthesis, probenecid was subjected to a sequence of reactions to obtain a 1,3,4-oxadiazole–phthalimide hybrid (PESMP) in high yields. The NMR (1H and 13C) spectroscopic analysis initially confirmed the structure of PESMP. Further spectral aspects were validated based on a single-crystal XRD analysis. Experimental findings were confirmed afterwards by executing a Hirshfeld surface (HS) analysis and quantum mechanical computations. The HS analysis showed the role of the π⋯π stacking interactions in PESMP. PESMP was found to have a high stability and lower reactivity in terms of global reactivity parameters. α-Amylase inhibition studies revealed that the PESMP was a good inhibitor of α-amylase with an s value of 10.60 ± 0.16 μg/mL compared with that of standard acarbose (IC50 = 8.80 ± 0.21 μg/mL). Molecular docking was also utilized to reveal the binding pose and features of PESMP against the α-amylase enzyme. Via docking computations, the high potency of PESMP and acarbose towards the α-amylase enzyme was unveiled and confirmed by docking scores of −7.4 and −9.4 kcal/mol, respectively. These findings shine a new light on the potential of PESMP compounds as α-amylase inhibitors. ## 1. Introduction Diabetes mellitus is a chronic disease aroused by the inability of the body to consume blood sugar, which leads to high blood sugar levels and the malfunction of the vascular system, vision, urinary system, and nerves. According to a WHO report, about 422 million people all around the globe are suffering from diabetes mellitus and 1.5 million/year deaths are caused by it; an ascending trend in these numbers has been continuously observed [1,2]. α-Amylase is released by the salivary glands and pancreas and catalyzes the breakdown of starch and polysaccharides to produce sugars as end-products. The excessive production of this enzyme causes an accelerated degradation of polysaccharides, resulting in an extreme sugar concentration in the blood. One way to control diabetes mellitus is to control the release of α-amylase in the blood, thus producing a restricted amount of sugars [3]. 1,3,4-Oxadiazole, a five-membered heterocycle moiety with two nitrogen atoms and one oxygen atom in the cycle, has been recognized to have a decreased aromatic and improved diene character [4]. Compounds relevant to this category of heterocycles have expressed a versatile therapeutic potential as antimicrobial [5], antiepileptic [6], anticancer [7,8], hypoglycemic [9,10], antiviral [11], and anti-inflammatory agents (Figure 1) [12]. Many commercially available drugs bear the 1,3,4-oxadiazole moiety in their core structure as a pharmacophore (Figure 1) [13]. Among those drugs, raltegravir is used to treat HIV [14], furamizole treats microbial infections [15], nesapidil is prescribed as a vasodilator [16], and zibotentan is an anticancer drug [17]. The developments in the synthesis of 1,3,4-oxadiazole scaffolds and their biological activities have been reviewed [18,19]. Probenecid, a sulfonamide containing benzoic acid, is a commercially available drug used to manage hyperuricemia [20]. Probenecid-derived amide linkage-containing structures have been successfully synthesized and analyzed for their carbonic anhydrase inhibition [21]. A little less attention has been devoted to the conversion of probenecid into its oxadiazole derivatives and investigations of their biological activities. However, probenecid-derived 1,3,4-oxadiazole–phthalimide hybrids have been investigated for their dengue virus NS2B/NS3 protease inhibition [10]. Moreover, phthalimide-based 1,3,4-oxadiazoles have been found to be anticonvulsant [22], cytotoxic [23], and peripheral analgesic [24] agents. In the context of our previous research [10,25], we envisioned that a combination of probenecid, 1,3,4-oxadiazole, and phthalimide moieties to access a hybrid molecule might result in enhancing enzyme inhibitions. Thus, a synthesis of enzyme inhibitors was undertaken, along with a single-crystal analysis, DFT exploration, and α-amylase inhibition studies of probenecid-derived 1,3,4-oxadiazole–phthalimide hybrids. Docking predictions were carried out to unveil the docking pose and score of PESMP against the α-amylase enzyme. These findings shine new light on the potential of PESMP as an α-amylase inhibitor. ## 2.1. Chemistry The PESMP compound was synthesized by a multi-step synthetic path, as depicted in Scheme 1. The purity of PESMP was confirmed based on thin-layer chromatography. The pure compound had a melting point of 154–155 °C. In the 1H NMR spectrum of PESMP (Figure S1), a triplet at δ 0.89 ppm (coupling constant = 7.35 Hz) was designated for six protons. A multiplet for four protons of two methylene groups (CH3CH2CH2) was observed at δ 1.49–1.66 ppm. Another multiplet for four protons of two methylene groups (N-CH2) attached to the N-atom was present at δ 3.00–3.22 ppm. A singlet for two protons at δ 5.41 ppm represented SCH2N. The aromatic protons were detected between δ 7.71 and 8.25 ppm. Similarly, the 13C-NMR spectrum also established the synthesis of the desired PESMP (Figure S2). The methyl carbons were observed at δ 11.56, and the methylene carbons attached to the methyl group were found at δ 22.34 ppm. The methylene carbons attached to the nitrogen atom were found at δ 40.14 ppm, and a methylene carbon sandwiched between sulfur and nitrogen was present at δ 50.32 ppm. Aromatic carbons were found in the range of δ 124–143 ppm. The carbon atoms of 1,3,4-Oxadiazole ring were found at 165.86 and 166.81 ppm, whereas the carbonyl carbons of the phthalimide ring were found at 168.2 ppm. ## 2.2. Single-Crystal Analysis In PESMP (Figure 2, Table 1), the 2-methylisoindoline-1,3-dione moiety A (C1-C9/N1/O1/O2), 2,5-dihydro-1,3,4-oxadiazole-2-thiol group B (C10/C11/N2/N3/O3/S1), and hydrosulfonylbenzene ring C (C12-C17/S2) are planar with root mean square (RMS) deviations of 0.0344, 0.0137, and 0.0069 Å, respectively. The dihedral angles A/B and B/C are 25.76[4] ° and 15.03[6] °, respectively. The root mean square plane of group B (C10/C11/N2/N3/O3/S1) is oriented at the dihedral angles of 25.76[4] ° and 15.03[6] ° with respect to moiety A (C1-C9/N1/O1/O2) and ring C (C12-C17/S2), respectively. The geometry around the S2-atom is a distorted tetrahedron as the bond angles containing the S2-atom as a central atom range from 106.87[6] ° to 107.66[6] ° and the bond lengths range from 1.4337 [10] to 1.7732 [14] Å (Table S1). Two dipropylamine groups named group D (C18-C20/N4) and group E (N4-C21-C23) containing N4 as a common atom are directed at the dihedral angles of 39.8[8] ° and 42.8[9] °, respectively. The structure of PESMP is stabilized by intramolecular C-H⋯O bonding (Table 2 and Figure 3). Symmetry codes: (i) −x, −y + 2, −z + 1; (ii) −x + 1, −y + 1, −z; (iii) −x + 1, −y + 1, −z + 1; (iv) 1 + x, y, z; (v) 1 − x, 2 − y, 1 − z. Cg1, Cg2, and Cg3 are the centroids of the (C12/C17), (C10/C11/N2/N3/O3), and (C1/C2/C7/C8/N1) rings, respectively. The molecules are further connected via C-H···O bonding to form R22[10] hydrogen-bonded loops (Figure 4). The R22[10] H-bonded loops are connected through C-H⋯O and C-H⋯N bonding. As a result, R22[8] H-bonded loops are formed. The weak intra-molecular π⋯π stacking interactions are unveiled via crystal packing. The five-membered ring of group A is involved in an intra-molecular π⋯π stacking interaction with the five-membered ring of group B with an inter-centroid separation value of 4.08 Å (Figure 4). The dihedral angle between the rings is 26.27[8] °. The inter-centroid separation of the intermolecular offset π⋯π stacking interactions is observed in the range of 3.33–3.72 Å, forming a chain of molecules along the [110] direction. The similar five-membered rings of the symmetry-related molecules are involved in inter-molecular offset π⋯π stacking interactions with the ring offset, or slippage ranges from 1.396 to 1.994 Å. The CH from one of the propyl groups participates in the C-H⋯π interaction with the aromatic ring of the symmetry-related molecules (1 + x, y, z), which forms an infinite chain of molecules that goes along the a-axis (Figure 5a, Table 2). An intra-molecular C-O⋯π interaction is found in PESMP with an O⋯π distance of 3.2430[12] ° and a C-O⋯π angle of 90.74[9] ° [26]. In crystal packing, the inter-molecular C-O⋯π interaction shows an O⋯π distance of 3.2417 [12] Å and a C-O⋯π angle of 80.93[8] °, which interlink the molecules in the form of dimers (Figure 5b, Table 2). ## 2.3. Hirshfeld Surface Analysis and Interaction Energy Calculation A Hirshfeld surface (HS) analysis is an informative technique to elaborate and recognize non-covalent interactions in single crystals. It was developed to divide crystal densities into molecular fragments [27,28,29,30,31,32,33]. The hydrogen bonding interactions can be elucidated using HS plots over the normalized distance (dnorm) property. The red- and blue-colored regions on surface stand for short and long contacts, respectively. Meanwhile, the spots on the white region indicate that the contacts have distances between their atoms equal to the sum of the van der Waals radii summation. Figure 6a,b show the HS surfaces over normalized distances (dnorm) and shape index, respectively. The red spots around one of the O-atoms of the carbonyl and sulfonyl groups as well as the one N-atom of the 2,5-dihydro-1,3,4-oxadiazole confirm the contributions of the H-bonding interactions (Figure 6a). The interactions of π⋯π stacking can be recognized by extracting the HS over the shape index property. The occurrence of successive blue and red triangular patches on the HS around the aromatic ring shows π⋯π stacking interactions [34]. These areas are noted on the HS plots relevant to the shape index property for PESMP (Figure 6b), which confirms the existence of π⋯π stacking interactionsin PESMP. The contribution of the interatomic contacts in defining the overall packing of the crystal is determined by a 2D fingerprint plot analysis [25,35,36,37,38,39]. 2D fingerprints of all the interactions are generated (Figure 7). The reciprocal contacts are also included while forming the 2D plots. Overall interaction is displayed in Figure 7a. The most significant contributor to crystal packing is announced to be the H⋯H contact, with $35.3\%$ (Figure 7b). The other important contacts are O⋯H, C⋯H, N⋯H, and S⋯H, with contributions of $35.3\%$, $28.1\%$, $14\%$, $6.6\%$, and $6.1\%$, respectively (Figure 7c–f). The C⋯C and C⋯N contacts show lower contributions to the crystal packing as compared to the contacts, as shown in Figure 7, although these contacts are involved in π⋯π stacking interactions. The contacts that have comparatively smaller percentage contributions to the crystal packing are shown in Figure S3. The enrichment ratio provides the actual contacts for a given single crystal [40,41]. The enrichment ratio is determined as a result of the division of the actual contact value obtained directly from CrystalExplorer by the ratio of the random contact determined theoretically. The enrichment ratio values for the pair of chemical species are summarized in Table 3. According to the compiled data in Table 3, C⋯C was the most favorable contact with an enrichment ratio of 3.31. The second most favorable contact was O⋯H, with an enrichment ratio of 1.39. The H⋯H and C⋯C contacts became less favorable by decreasing the enrichment ratio to less than one. A possible reason for the higher enrichment ratio of the C⋯N contact as compared to that of the C⋯C contact is that the intermolecular offset π⋯π stacking and C-O⋯π interaction interactions involve π-rings containing one or more nitrogen atoms. In crystal packing, various features of the single crystals, especially their mechanical properties, depending on the voids. For a single crystal to have good mechanical properties, the voids should be small. The voids were assessed by means of the Hartree–Fock theory, and the electronic densities of all the atoms were added up by supposing the spherical nature of the atoms [42,43,44,45,46]. Figure S4 is the graphical view of the voids in PESMP. The volume of voids was 148.35 Å3, which indicated that only $12.6\%$ of the total volume was taken up by voids. The void research addressed the tight packing of molecules along with the lack of significant cavities in the crystal packing of the PESMP compound. The CrystalExplorer software was employed for the calculation of the interaction energy within the molecular pairs. The calculation was carried out on a series of molecules located within 3.8 Å3 of the reference molecule using the B3LYP/6-31G(d,p) computational level. The symmetry-related molecules are displayed in Figure 8a. The obtained findings of the interaction energies among the molecular pairs are shown in Table S2. Table S3 collects the utilized atomic coordinates in the interaction energy calculations. As summarized in Table S2, the highest attractive total energy was for the pair of molecules with an intermolecular distance of 8.14 Å. The highest energy value of −92.7 kJ/mol reflected attractive forces, indicating that the molecules were connected by inversion symmetry. The lowest attractive total energy with a value of −7.1 kJ/mol was found for the molecular pair with a distance of 19.10 Å between molecular centroids. For only one molecular pair, the total interaction energy was repulsive, with a value of 0.2 kJ/mol. Electrostatic energy was attractive for most of the molecular pairs except for the molecular pair $R = 12.91$ Å. Figure 8b–d show the energy framework for coulomb, dispersion and total energy, respectively. The molecular centers were attached by the cylinders, and the thickness of the cylinder was directly related to the interaction strength. For the electrostatic coulomb energy, the thickness of the cylinders (Figure 8b) was smaller than that for the dispersion energy (Figure 8c), indicating that the dispersion energy was dominant over the coulomb energy. ## 2.4.1. Frontier Molecular Orbitals Analysis Frontier molecular orbitals (FMOs) theory is employed as a dependable tool for estimating the electronic properties along with the chemical stability of a system [47,48]. In the context of FMOs, the electron density distribution in molecular orbitals is elucidated. FMOs also interpret the chemical affinity and relation of the examined molecule with other moieties. Furthermore, FMOs support our understanding of the reactive sites in any π-electron system [49]. FMOs investigate two principal orbitals. The first one is the highest occupied molecular orbital (HOMO), which holds and donates electrons as an electron donor. The second one is the lowest unoccupied molecular orbital (LUMO), which has a vacant orbital and tends to receive electrons [50]. Via EHOMO and ELUMO values, the FMO’s band gap (ΔE) is computed to elucidate the reactivity, electron transference properties, hardness, and softness of a molecule. The compounds possessing a greater energy difference between HOMO and LUMO are considered to be harder, kinetically more stable, and less reactive in their nature and vice versa [51]. For the PESMP compound, FMO calculations were carried out, and the results of HOMO, HOMO − 1, HOMO − 2, LUMO, LUMO + 1, and LUMO + 2, along with their corresponding band gaps, are collected in Table 4. The molecular orbital sketch of the PESMP compound is shown in Figure 9. As shown in Table 4, the energies of HOMO, HOMO − 1, and HOMO − 2 of the PESMP compound are −0.2678, −0.2808, and −0.2898 a.u. Furthermore, the energies of LUMO, LUMO + 1, and LUMO + 2 of the PESMP compound were −0.0946, −0.0822, and −0.0562 a.u., respectively. The energy gaps of HOMO and LUMO, HOMO − 1 and LUMO + 1, and HOMO − 2 and LUMO + 2 were 0.1732, 0.1987, and 0.2335 a.u., respectively. In the PESMP compound, the charge density for HOMO was found over the oxadiazole and benzenesulfonamide moieties (Figure 9). The charge density for LUMO was situated on the phthalimide moiety, predicting an excellent charge transference from oxadiazole and benzenesulfonamide toward the phthalimide moiety. ## 2.4.2. Global Reactivity Parameters (GRPs) Global reactivity parameters (GRPs) are beneficial for calculating the stability and chemical reactivity of chemical systems [52]. For the PESMP compound, numerous GRPs, comprising ionization potential (IP), chemical potential (μ), electron affinity (EA), hardness (η), electronegativity (X), global softness (σ), and electrophilicity index (ω), were assessed by Koopman’s theorem as illustrated in the Section 3.2 [53]. The chemical hardness (η) of a molecule is related to the energy gap (ΔE) value. The overall softness and reactivity of the PESMP compound demonstrated an inverse relationship. η showed a value of 0.0866 a.u., revealing the high stability and lower reactivity of the considered compound. The ionization potential (IP) and electron affinity (EA) values were 0.2678 and 0.0946 a.u., respectively. Moreover, the values of μ, ω, and σ were 0.1812, 0.1896, and 5.7737 a.u., respectively. ## 2.4.3. Molecular Electrostatic Potential (MEP) One way of determining the electrostatic potential values over the iso-electronic density map is to investigate a three-dimensional (3D) layout of the molecular electrostatic potential (MEP) surface. The MEP is conducted for the estimation of electrophilic and nucleophilic attacks on chemical systems [54]. The MEP diagram shows a variety of colors, red, blue, yellow, green, light blue, and blue, which represent significantly electron-rich, slightly electron-rich, neutral, slightly electron-deficient, and significantly electron-deficient regions, respectively [55]. The morphology, molecular size, and electrostatic potential amplitude of the PESMP compound are all clearly shown in Figure 10. In the MEP map of the PESMP compound displayed in Figure 10, a red-colored zone is noted around the oxygen atoms. The likelihood of an electrophilic attack is therefore related to this area, which represents the electron-rich zone. On the hydrogen and certain carbon atoms, green and blue zones are seen, signifying electron-deficient zones, which point to a nucleophilic attack on these potential sites. ## 2.5. α-Amylase Inhibition Activity The inhibitory potential of a probenecid-derived 1,3,4-oxadiazole–phthalimide hybrid (PESMP) against α-amylase was investigated at concentration levels ranging from 10 to 200 μg/mL, with PESMP inhibiting α-amylase by $81.06\%$ at 200 μg/mL (Table 5). Acarbose, a commercially used standard α-amylase inhibitor, demonstrated inhibitory activity with an IC50 value of 8.80 ± 0.21 μg/mL. ## 2.6. Molecular Docking The efficiency of the AutoDock4.2.6 package in anticipating the correct inhibitor-α-amylase binding pose was validated. For validation purposes, the co-crystallized acarbose ligand was re-docked in the α-amylase enzyme’s active site, and the anticipated docking pose was compared to the experimental binding mode (PDB ID: 1ose [56]) (Figure S5). From Figure S5, the predicted docking pose was similar to the binding mode of the native structure of the acarbose inhibitor with an RMSD value of 0.23 Å, exhibiting several hydrogen bonds with the key amino acid residues of the α-amylase enzyme [25]. The docking score and pose of PESMP against the α-amylase enzyme were predicted and compared to that of acarbose with the aid of AutoDock4.2.6. The anticipated docking score and pose are presented in Figure 11. As depicted in Figure 11, PESMP demonstrated a −7.4 kcal/mol docking score. The potency of PESMP as an α-amylase inhibitor may be relevant to its ability to form a hydrogen bond with HIS305 (2.07 Å). Moreover, PESMP exhibited π⋯π T-shaped and π⋯π stacked interactions with the TYR62 residue and a π-anion interaction with the ASP197 residue. Moreover, PESMP demonstrated a carbon–hydrogen bond with the TRP59, TYR151, and GLY306 residues, a π-alkyl interaction with the VAL163 and ALA198 residues, and alkyl interactions with the LYS200, HIS201, and ILE235 residues (Figure 11). A pan-assay interference compound (PAINS) prediction for PESMP was also performed using the SmartsFilter web server (http://pasilla.health.unm.edu/tomcat/biocomp/smartsfilter, accessed on 1 December 2022). According to the predicted SmartsFilter results, PESMP passed the PAINS filter. ## 3.1. Experimental Details The current work was supported by the use of easily available laboratory-grade chemicals and reagents. The utilized solvents were of analytical grade and were employed without drying or distillation. The melting point was measured in an open capillary using a Gallenkamp melting point device (MP-D). Thin-layer chromatography was used to monitor all reactions using Merck pre-coated plates (silica gel 60 F254, 0.25 mm). Using UV rays (254 nm), fluorescence quenching was adopted to view the results. A Bruker AV-300 (300 MHz) spectrometer was employed to record the 1H and 13C NMR spectra. Single-crystal X-ray diffraction data were collected for PESMP compound on Bruker Kappa APEX-II CCD diffractometer with molybdenum X-ray source, which generated kα radiations with a wavelength value of 0.71073 Å. The structure was solved and refined by SHELXT-2014 [57] and SHELXL-$\frac{2019}{2}$ [58], respectively. Mercury version 4.0 software [59] and PLATON [60] were employed for graphically illustrating single-crystal X-ray diffraction results. ## 3.1.1. Synthetic Procedure for the Preparation of 4-(5-((1,3-Dioxoisoindolin-2-yl)methylthio)-1,3,4-oxadiazol-2-yl)-N,N-dipropylbenzene-sulfonamide (PESMP) A modified multistep synthetic procedure was followed to access PESMP. Step I: In a typical experimental procedure, probenecid (PE) (30 mmol) was esterified in 20 mL of methanol using catalytic amounts of sulfuric acid (0.5 mL) at reflux temperature for 4 h. The mixture was extracted thrice with 30 mL of ethyl acetate after being neutralized with 50 mL of saturated sodium bicarbonate solution. The organic layer was dried over anhydrous sodium sulphate and filtered, and then the solvent was removed to obtain crude methyl ester of probenecid in a quantitative yield. Step II: Methyl ester of probenecid (MPE) (with 25 mmol) was dissolved in 30 mL of methanol, and NH2NH2.H2O ($80\%$, 0.06 mol) was added dropwise. After refluxing for 8 h, the reaction mixture was cooled to 25 °C and then dispensed into ice-cold water. Probenecid hydrazide (PEH) was precipitated, filtered, dried, and finally recrystallized from MeOH. Step III: A solution of probenecid hydrazide (PEH) (20 mmol) in 10 mL of methanol and 3 equivalents of KOH dissolved methanol (30 mL) were added. After 10 min, carbon disulfide (30 mmol) was slowly added. Afterwards, the reaction mixture was refluxed for about 12 h. The reaction mixture was cooled down to 25 °C, concentrated, and poured into ice-cold water. The solution was acidified (pH = 2) with dilute hydrochloric acid. The precipitated probenecid oxadiazole (PEO) was washed with warm water and purified by recrystallization with the help of MeOH. Step IV: Probenecid oxadiazole (PEO) (10 mmol) was dissolved in acetone and 12 mmol of potassium carbonate was added. After stirring for 10 min at 25 °C, 12 mmol of N-(bromomethyl)phthalimide was added, and the reaction mixture was stirred for another 6 h. The solvent was removed, and the crude was recrystallized from methanol to obtain pure PESMP (Scheme 1). ## 3.1.2. Methyl 4-(dipropylsulfamoyl)benzoate (MPE) Colorless solid; M.P.: 65–66 °C; yield: $87\%$; 1HNMR (300MHz, Chloroform-D) ppm: 8.16 (m, 2H), 7.88 (m, 2H), 3.97 (s, 3H), 3.11 (m, 4H), 1.54 (m, 4H), and 0.88 (t, $J = 15$ Hz, 6H); 13C NMR (75 MHz, Chloroform-D) ppm: 165.76, 144.27, 133.41, 130.22, 127.00, 52.61, 49.89, 21.91, and 11.15; FT-IR (cm−1): 3100, 3051 (C-H, Aromatic), 2935, 2873(C-H, Aliphatic), 1726 (Carbonyl), 1341(asym), and 1156(sym)(O=S=O). ## 3.1.3. 4-(Dipropylsulfamoyl)benzoic acid hydrazide (PEH) Colorless solid; M.P.: 116–118 °C; yield: $73\%$; 1HNMR (300MHz, DMSO-d6) ppm: 10.00 (s, 1H), 7.98 (d, $J = 9$ Hz, 2H), 7.86 (d, $J = 9$ Hz, 2H), 4.59 (s, 2H), 3.04 (t, $J = 15$ Hz, 4H), 1.46 (m, 4H), 0.80 (t, $J = 15$ Hz, 6H), and 13C NMR (75MHz, DMSO-d6); 164.94, 142.06, 137.31, 128.42, 127.29, 50.09, 22.09, and 11.42; FT-IR (cm−1): 3297, 3211 (NH2), 3086 (N-H), 3036, (C-H, Aromatic), 2964, 2873 (C-H, Aliphatic), 1658 (Carbonyl), 1328 (asym.), and 1155(sym.) O=S=O. ## 3.1.4. N,N-dipropyl-4-(5-thioxo-4,5-dihydro-1,3,4-oxadiazol-2-yl)benzene sulfonamide (PEO) Colorless solid; M.P.: 177–180 °C; yield: $77\%$; 1HNMR (300MHz, DMSO-d6) (ppm): 14.92 (s, 1H), 8.06 (d, $J = 9$ Hz, 2H), 7.97 (d, $J = 9$ Hz, 2H), 3.06 (t, $J = 15$ Hz, 4H), 1.46 (pnt, $J = 15$ Hz, 4H), and 0.80 (t, $J = 15$ Hz, 6H); 13C-NMR (75 MHz, DMSO-d6) ppm: 178.12, 159.79, 142.78, 128.24, 127.49, and 126.44; FT-IR (cm−1): 3068 (C-H, Aromatic), 2968 (C-H, Aliphatic), 1612, 1592 (C=N), 1340 (C-S), and 1158 (O=S=O). ## 3.1.5. 2-((5-Phenyl-2-thioxo-1,3,4-oxadiazol-3(2H)-yl)methyl)isoindoline-1,3-dione (PESMP) Colorless solid; M.P.: 154–155 °C; yield: $81\%$; 1H NMR (300 MHz, Chloroform-D) δ ppm: 0.89 (t, $J = 7.35$ Hz, 6 H, CH3), 1.49–1.66 (m, 4 H, CH3CH2), 3.00–3.22 (m, 4 H, NCH2), 5.41 (s, 2 H, SCH2N), 7.717.83 (m, 2 H, Aromatic), 7.85–7.91 (m, 2 H, Aromatic), 7.92–7.97 (m, 2 H, Aromatic), and 8.15–8.25 (m, 2 H, Aromatic); 13C NMR (75 MHz, Chloroform-D) δ ppm: 11.56 (Methyl-C), 22.34 (Methylene-C), 40.14 (N-mehtylene-C), 50.32 S-methylene-C), 77.42, 77.84, 124.32, 127.12, 127.85, 128.10, 132.06, 135.10, 143.64, 165.87 (Oxadiazole-C), 166.81 (Oxadiazole-C), and 168.2 (Carbonyl-C); FT-IR υ(cm−1): 3025 (Aromatic CH), 2960 (Methylene CH2), 1723 (Amide carbonyl), 1606, 1568 (Oxadiazole C=N), 1327, and 1154 (Sulfonamide SO2); anal. calcd for C23H24N4O5S2: C, 55.18; H, 4.83; N, 11.19; O, 15.98; and S, 12.81; found: C, 55.90; H, 4.88; N, 11.24; O, 16.01; and S, 12.84 (Figures S1 and S2). ## 3.2.1. Hirshfeld Surface (HS) Analysis Hirshfeld surface (HS) was analyzed for PESMP compound using CrystalExplorer version 21.5 [61] to further elucidate features of non-covalent interactions within a single crystal. In that spirit, the surface of normalized contact distance (dnorm) was extracted using a color range from −0.2450 to 1.5592 a.u. Moreover, a map of the shape index property was generated with a color scope ranging from −1.0 a.u. ( concave) to 1.0 au (convex). Two-dimensional fingerprints were created to unveil the contribution of interatomic contact to the overall crystal packing. To investigate the crystal packing environment widely, the enrichment ratio was evaluated by dividing the actual contact by the random contact theoretical proportion. Voids were also divulged using the Hartree–Fock theory to understand the properties of the single crystal from a mechanical point of view. Energy framework computations were performed to illustrate the energy framework and interaction energies of PESMP compound. Interaction energy calculations were carried out on a cluster of molecules located within 3.8 Å3 of the reference molecule using the B3LYP method with a 6-31G(d,p) basis set. ## 3.2.2. Density Functional Theory (DFT) Analysis DFT-based computations were performed with the Gaussian 09 program package [62] in conjugation with M$\frac{06}{6}$-311G(d,p) function for the quantum chemical investigations of synthesized PESMP compound. The input files were developed by using the GaussView 6.0 program [63]. To demonstrate the contributions of the electron density surrounding the molecular orbitals, FMOs theory was invoked. The distributions of HOMO and LUMO were generated. Using FMOs, energies of HOMO (EHOMO) and LUMO (ELUMO) were computed for the PESMP compound. Band gaps were accordingly assessed as the difference between the energies of LUMO and HOMO levels, as shown in the following Equation [1]:[1]ΔE= ELUMO−EHOMO Several global reactivity parameters (GRPs) were calculated for the PESMP compound as per Equations [2]–[8]:IP = −EHOMO[2] EA = −ELUMO[3] [4]X=IP−EA2 [5]η=IP−EA2 [6]μ=EHOMO+ELUMO2 [7]σ=12η [8]ω=μ22η MEP plot was generated for pictorially addressing the chemical nature of the PESMP compound. In MEP map, blue, green, yellow, orange, and red represented regions with decreasing order of positive electrostatic potential magnitudes. ## 3.3. Enzyme Inhibition Activity α-Amylase inhibition potential of probenecid-derived 1,3,4-oxadiazole–phthalimide hybrid (PESMP) was investigated employing the 3,5-dinitro-2-hydroxybenzoic acid (DNS) method [64]. PESMP (1 mg) and DNS (1 mg) were separately solvated in 1 mL of DMSO. A solution of PESMP and α-amylase (200 μL, pH 7.0) was maintained at 30 °C for 10 min. An aqueous starch solution ($1\%$) was poured and the same temperature was regulated for another 3 min. The reaction was stopped by adding a DNS reagent (200 μL). The tube was immersed in boiling water. After 10 min, the tube was cooled down to 25 °C, and distilled water (5 mL) was added. The absorbance was obtained at 540 nm. Acarbose (10–250 μg/mL) was utilized as a standard inhibitor for the comparison of the inhibitory potential of PESMP in triplicate experiments, whereas $2\%$ DMSO was used for the control incubation, which represents maximal enzyme activity. Percentage inhibition was calculated by using a formula (Equation [9]), and then IC50 values were calculated. [ 9]% α amylase inhibition=Ao−AiAo×100 ## 3.4. Molecular Docking The employed docking calculations are detailedly described elsewhere [65,66,67]. Briefly, the α-amylase crystal structure (PDB access code: 1ose [56]) complexed with acarbose was retrieved and employed as a template for docking predictions. For the purpose of preparation, all ions, heteroatoms, and crystallographic water molecules were eliminated. The protonation states of the α-amylase enzyme were scrutinized with the assistance of the H++ website [68]. In addition, all missing hydrogens were added. The structure of PESMP was manually built, and then energetically minimized using MMFF94S force field within SZYBKI software [69,70]. The Gasteiger method was utilized to assign the atomic charges of PESMP and acarbose compound [71]. In this work, docking computation was conducted utilizing AutoDock4.2.6 software [72]. The genetic algorithm number (GA) was adjusted to 250. The maximum number of energy evaluations (eval) was set to 25,000,000. Other docking parameters were set to default values. The grid box was tailored to involve the binding pocket of the α-amylase enzyme, with a grid size of 60 Å × 60 Å × 60 Å. The coordinates of the grid center were $x = 32.644$, $y = 38.464$, and z = −3.166. The AutoGrid program was employed to extract the grid maps with a spacing of 0.375 Å. All molecular interactions were represented using BIOVIA Materials Studio [73]. ## 4. Conclusions An efficient, multistep synthetic approach was followed to synthesize good yields of 4-(5-((1,3-dioxoisoindolin-2-yl)methylthio)-1,3,4-oxadiazol-2-yl)-N,N-dipropylbenzene-sulfonamide (PESMP). Its synthesis was confirmed via structural validation using NMR (1H, 13C), FT-IR, and single-crystal X-ray diffraction analyses. The purity of PESMP was established on the basis of thin-layer chromatography. To obtain further insight into the features of the entitled compound, various DFT calculations were executed accordingly. The band gap value of the PESMP compound (0.1732 a.u.) for the HOMO-LUMO orbital was smaller than the band gap values of HOMO-LUMO ±1 and HOMO-LUMO ±2. The testing of PESMP against α-amylase revealed an IC50 = 10.60 ±0.16 μg/mL using acarbose (IC50= 8.80 ±0.21 μg/mL) as a standard drug. Molecular docking revealed the binding mode of the PESMP compound against the active site of α-amylase. PESMP and acarbose showed docking scores of −7.4 and −9.4 kcal/mol against the α-amylase enzyme, respectively. These findings shine new light on the potential of the PESMP compound as an α-amylase inhibitor. ## Figures, Scheme and Tables Figure 1: Schematic representation of the 1,3,4-oxadiazole moiety: (A) in commercial drugs; (B) in pre-clinical trials; (C) as α-amylase inhibitor; (D) in versatile biological activities; and (E) in current work. Scheme 1: Synthetic path to access PESMP compound. Figure 2: ORTEP presentation of PESMP which is visualized at a $50\%$ level of probability. Hydrogen atoms are displayed by small circles with arbitrary radii. Figure 3: Packing diagram of PESMP elucidates the interlinkage of the molecules via C-H⋯O and C-H⋯N bondings. Only selected hydrogen atoms are shown to avoid ambiguity. Figure 4: Graphical representation of intra- as well as inter-molecular offset π⋯π stacking interactions. For the purpose of clarity, hydrogen atoms are skipped. Distances are in Å. Figure 5: Representation for (a) C-H⋯π interactions that form an infinite chain of molecules besides the a-axis, (b) C-O⋯π interactions that interlink molecules through a dimeric form. Distances are in Å. Figure 6: Hirshfeld surface of PESMP mapped over (a) dnorm using scope from −0.2450 to 1.5592 a.u., and (b) shape index using scope from −1 to 1 a.u. Figure 7: 2D fingerprint plot of interactions and important interatomic contacts in PESMP. Figure 8: (a) Graphical representation of the molecules involved in the computations of the interaction energy between molecular pairs. Energy framework for (b) coulomb energy, (c) dispersion energy, and (d) total energy. Figure 9: HOMO and LUMO diagrams of the PESMP compound, along with the band gap (ΔE, in a.u.) energetic values. 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--- title: 'Associations between Dietary Patterns and Physical Activity with Physical Fitness among Adolescents in Shandong Province, China: A Cross-Sectional Study' authors: - Sizhu Wu - Xiaolei Xiu - Qing Qian journal: Nutrients year: 2023 pmcid: PMC10051977 doi: 10.3390/nu15061425 license: CC BY 4.0 --- # Associations between Dietary Patterns and Physical Activity with Physical Fitness among Adolescents in Shandong Province, China: A Cross-Sectional Study ## Abstract Background: The trend of physical fitness (PF) and physical activity (PA) among Chinese adolescents is not optimistic, and unhealthy dietary behaviors are common. PA and dietary patterns (DPs) have been linked to PF in adolescents, but the associations between DPs and PF with PF in Chinese adolescents are rarely discussed. Methods: A total of 8796 adolescents aged 11–18 were enrolled from Shandong Province, China. The CNSPFS battery was applied to assess PF. PA levels and diet quality were determined using the Physical Activity Questionnaire for Adolescents and the modified Chinese Diet Quality Questionnaire, respectively. This study used factor analysis to identify DPs and linear regression models to investigate the association between PF and related factors. Results: The average PF score of the participants was 75.67. Adolescents who were girls, lived in rural areas and were active in PA performed better on the PF test ($p \leq 0.05$). Boys whose fathers were university educated or above had a higher probability of achieving higher PF scores (OR 4.36, $95\%$ CI 1.32–14.36); however, if their mothers were university educated or above, they had a lower probability of achieving higher PF scores (OR 0.22, $95\%$ CI 0.063–0.76). Unhealthy dietary pattern was negatively correlated with cardiorespiratory fitness in boys (OR 0.56, $95\%$ CI 0.31–0.98). The association between unhealthy dietary pattern and girls’ BMI became significant after adjustment for PA ($p \leq 0.05$). Conclusions: Girls performed better in PF than boys. Highly educated fathers could contribute to improve the PF performance in boys. There were four DPs among adolescents in Shandong Province, and different DPs may have different effects on PF in boys and girls. ## 1. Introduction Physical fitness (PF) is a set of health- or skill-related attributes [1]. The components of health-related PF include body composition, muscular endurance, muscular strength, cardiovascular endurance and flexibility, which are widely recognized as markers of health-related outcomes throughout life [2,3]. The adolescence period is a crucial time for PF development. Improving PF in adolescents is of great significance not only to improving their academic performance, quality of life, cognitive ability and mental health but also to improving the quality of national health [4,5,6]. However, the decline of PF in adolescents has become a global public health problem. In recent years, although the PF of Chinese adolescents has generally improved, the trend of PF is still not optimistic. According to the results of the 8th National Survey on Student Physical Fitness and Health released by the Chinese Ministry of Education in 2021, only $17.7\%$ of students aged 13–22 could achieve a “good” or “excellent” rating of PF [7]. Therefore, given the current situation of PF among Chinese adolescents, it is necessary to take effective measures to improve their PF. There are various factors that affect adolescents’ PF, such as genetics, biological characteristics, dietary habits and physical activity (PA) [8,9,10]. Studies have shown that PA and diet are associated with PF in adolescents. Relevant research can be divided into the following three categories. [ 1] Association of PA and diet with weight status: The results of several studies have indicated that intermittent fasting is beneficial for body weight, but diet-induced weight changes are generally short-lived and greater benefits can be gained through vigorous PA [11,12]. Bogataj et al. have demonstrated that just 8 weeks of school-based high-intensity interval training with three sessions a week and nutrition intervention can improve upper body muscle and physical aerobic performance in adolescents and help reduce BMI in overweight girls [13]. Oh et al. identified dietary patterns in Korean children and adolescents, and found that the “fast food and soda pattern” was positively associated with waist circumference, serum insulin and BMI, while the “white rice and kimchi pattern” and “oil and seasoned vegetables pattern” indicated a preventive effect on these parameters [14]. [ 2] Effect of diet and PA on health: Previous studies have found an effect of diet on cardiorespiratory fitness (CRF) and metabolic syndrome (MetS) [15,16]. For example, CRF was positively associated with frequent consumption of fruits, vegetables, bread and dairy products [15,17]. Shahinfar et al. showed that adherence to the mixed dietary pattern was associated with increasing odds of MetS in Iranian adults [18]. Moreover, Wenjie et al. found that adequate calcium intake and the improved CRF were essential for the development of good mental health in adolescents aged 12–13 years [19]. [ 3] Relationship between Mediterranean diet and PA and different parameters of PF: The Mediterranean diet (MD) is postulated as one of the healthiest dietary patterns that exists [20]. The authors concluded that optimal adherence to the MD pattern was associated with higher CRF and PA levels as well as high levels of muscular strength [21,22,23,24]. For an instance, Cristina et al. found that greater adherence to the MD pattern was related with higher CRF and lower limbs muscular strength and speed agility [25]. Pablo et al. also showed that higher levels of CRF in boys and girls were associated with medium and high adherence to the MD [26]. However, some studies indicated the positive correlation between the MD pattern and higher CRF and speed agility only in boys [27,28]. Although several studies have analyzed the associations between dietary patterns and PA with PF among adolescents, there are still several problems. First, the existing studies are controversial about the correlation between parents’ educational level and PF. One study showed that the educational level of German parents was positively correlated with their children’s aerobic fitness [29]. However, a Swiss study found that parents’ educational level affected children differently, with the mother’s education level appearing to have a greater impact on children’s PF [30]. Another study found that those Catalan children whose fathers had higher education had lower waist circumference and BMI [31]. Second, the measurement standards of Chinese and foreign students’ PF are different. For an instance, Spain measures upper body muscular strength of students using a hand dynamometer with adjustable grip, whereas China does not measure girls’ upper body muscle strength and only uses pull-ups to measure the upper body muscular strength of boys [24,32]. Third, most studies on the relationship between dietary patterns and PF have focused on the MD pattern. The MD pattern is characterized by high consumption of fruits and vegetables, nuts, cereals, fish and olive oil and minimal amounts of red meat and dairy products, which is quite different from the grain-based Chinese dietary pattern [25]. Currently, we have not found any reports on the interaction between dietary patterns and PF in Chinese adolescents. Therefore, it is necessary to explore the relationship between dietary patterns, PA and PF among Chinese adolescents based on Chinese physical fitness measurement standards and dietary culture. This study was designed with the following general aims: [1] to comprehensively evaluate the physical fitness status of adolescents (11–18 years old) in Shandong Province; [2] to explore the relationship between diet, physical activity and physical fitness; and [3] to further analyze the differences between boys and girls in the relationships between dietary patterns, physical activity and different parameters of PF. We hope that the findings of this study can provide a valid and specific theoretical basis for improving the physical fitness of Chinese adolescents. ## 2.1. Participants and Study Design This is a cross-sectional study that is part of a special program to investigate the status quo of health and health-related behaviors of Chinese junior and senior high school students. Detailed sampling methods have been published elsewhere [33]. Briefly, the sample for this study was selected using a probability-proportional-to-size sampling method during the 2020–2021 semester. Ultimately, 11,063 adolescents aged 11–18 years were recruited for the study. After excluding illogical samples and those missing information on PF or diet, a total of 8796 participants were finally included for analysis. Teachers, parents and students filled out a consent form prior to enrollment in this survey. The research was approved by the Ethics Committee of Shandong University, China [20180517]. ## 2.2. Data Availability The data used in this study are publicly available in the Population Health Data Archive [34]. ## 2.3.1. Demographic Factors They included gender, age, place of residence (rural/urban), parents’ educational level (junior high school and below, high school, university and above), and family economic status (poor, middle, good). This information was collected through a self-reported questionnaire for participants. ## 2.3.2. Physical Activity Measure PA was evaluated by the Physical Activity Questionnaire for Adolescents (PAQ-A). This scale is a revised version of the Physical Activity Questionnaire for Children (PAQ-C), which is designed to assess the PA level of adolescents [35]. It is on a 5-point scale (1–5), with higher scores indicating higher levels of PA. The results can be divided into two categories: low PA levels (1–1.9 points) and high PA levels (2–5 points) [36]. The validity and reliability of the PAQ-A has been validated among Chinese adolescents [37]. This study also demonstrated that the questionnaire has good internal consistency and structural validity: the Cronbach’s alpha value was 0.82; the Kaiser—Meyer—Olkin (KMO) value was 0.83; and for Bartlett’s test, $p \leq 0.001.$ ## 2.3.3. Dietary Assessment Participants’ dietary status was assessed using the modified Chinese Diet Quality Questionnaire (DQQ), a 5-point scale (1–5) for rapid qualitative and quantitative analysis of participants’ diet quality. The DQQ contains three diet scores: GDR-Healthy score, GDR-Limit score and overall GDR score. The GDR-Healthy score reflects global recommendations for health-protective foods in healthy diets. The GDR-Limit score reflects global recommendations for limiting dietary components. Lower overall GDR score, lower GDR-Healthy score and higher GDR-Limit score indicate poorer diet quality [38]. Studies have shown that the DQQ can be a valid tool for assessing the diet quality of Chinese children and adolescents aged 7–18 [39]. The DQQ includes 29 food groups. Considering the dietary habits of people in Shandong Province and the purpose of this study, we removed cereals and cheese from the DQQ. Additionally, the food items were combined into 17 groups in this study to facilitate adolescents filling out the questionnaire. Each participant was required to answer the question (How often have you eaten this type of food in the past week?), and the answers were divided into five levels (1 = “0 times”, 2 = “1–2 times”, 3 = “about once every 2 days”, 4 = “about once a day”, or 5 = “more than once a day”). In this study, the Cronbach’s alpha was 0.87, and the questionnaire was demonstrated to have good construct validity (KMO 0.91, Bartlett’s test $p \leq 0.001$). ## 2.3.4. Physical Fitness Trained physical education teachers administered all PF tests according to standard operating procedures The training was conducted through workshops and the specific procedures for data collection have been described in a previous paper [33]. PF was assessed by the Chinese National Student Physical Fitness Standard (CNSPFS) battery published by the Ministry of Education of the People’s Republic of China, which is a reliable and valid instrument for assessing PF in adolescents [40]. The total score of the participants’ PF test is 100 points, and the percentage of the score for each item and the test method are shown in Table 1. ## 2.4. Statistical Analysis All data were analyzed by IBM SPSS Statistics Version 26.0 (IBM Corporation, Armonk, NY, USA). Continuous variables were expressed as mean (M) and standard deviation (SD), and numbers (N) and percentages (%) were reported for categorical variables. Independent samples 2-tailed t-test, one-way analysis of variance (ANOVA) test or Chi-square test were used to compare the differences between groups of categorical variables, as appropriate. Furthermore, we performed multiple comparisons using Bonferroni-corrected p-values to account for inflation of type-I errors due to multiple comparisons made. To investigate the relationship between predictors (diet and PA) and outcomes (PF), we first analyzed their relationship using linear regression. Then, factor analysis was used to analyze the dietary patterns of the participants. As an exploratory analysis, we further investigated the differences in the relationship between PF and dietary patterns in boys and girls. Specifically, each PF was regressed on the dietary patterns after adjusting for basic confounders such as age, place of residence, parents’ educational level and family economic status (Model 1). Other analyses adjusted for high PA levels (Model 2). Odds ratios and their $95\%$ confidence intervals obtained from the model were reported. A p-value <0.05 was considered to be statistically significant. ## 3.1. Sociodemographic Characteristics of the Participants In total, 8796 students (4332 ($49.2\%$) boys; 4464 ($50.8\%$) girls) were included in the final statistical analysis of this study. The demographic characteristics of the participants are summarized in Table 2. The mean age of the participants was 14.32 years and mean PF score was 75.67. The results showed significant differences in PA, diet, and PF between boys and girls. A significantly higher percentage of boys than girls were active in PA ($58.1\%$ vs. $46.5\%$). However, the proportion of boys with a BMI above normal was significantly higher than that of girls ($27.4\%$ vs. $21.3\%$). Girls had a significantly higher mean overall GDR score (7.53 vs. 7.45) and mean PF score than boys (77.34 vs. 73.94). The mean PF scores of adolescents varied widely among cities in Shandong province, ranging from 70.58 in Liaocheng to 81.2 in Linyi (Figure 1). In terms of boys’ PF, boys in Heze had the highest mean PF score of 80.54, while boys in Dongying had the lowest mean PF score of 68.32. Girls in Linyi had the highest mean PF score of 83. ## 3.2. Physical Fitness Status of Adolescents in Shandong Province Table 3 shows the means and deviations of the PF tests by age and gender, and the variation of boys’ and girls’ performance on the various PF tests with age is shown in Figure 2. It can be observed that girls had higher PF scores than boys in all age groups. In particular, girls performed significantly better than boys on the CRF test. Boys performed better than girls on the motor test. However, boys had poorer upper body muscular strength and only the 17-year-old boys passed the pull-ups test with an average score (70.07). ## 3.3. Relationship between Physical Fitness and Other Variables In this study, the PF score was used as the dependent variable, and the relationship between PF and various factors was analyzed by multiple linear regression (Table 4). The results showed that girls’ PF performance was 26.38 times (OR 26.38, $95\%$ CI 16.97–41.01) higher than that of boys. Adolescents living in rural areas had significantly higher PF scores than those living in urban areas, and this phenomenon was more pronounced among boys (OR 8.00, $95\%$ CI 3.89–16.45). Furthermore, we found that participants’ PF scores became higher as participants aged. The PF scores of boys whose fathers had a university or above level of education were 4.36 times (OR 4.36, $95\%$ CI 1.32–14.36) higher than those whose fathers had a junior high school or below level of education. Compared to boys whose mothers had a junior high school or below level of education, boys whose mothers had a university or above level of education had $78\%$ lower (OR 0.22, $95\%$ CI 0.063–0.76) PF scores. A statistically significant positive correlation was found between PF scores and PA levels ($p \leq 0.01$). ## 3.4. Dietary Patterns of Adolescents Aged 11–18 The study conducted factor analysis (based on principal component analysis) to investigate participants’ dietary patterns (DPs) based on the percentage energy intake of 17 food groups. To determine the number of DPs, we considered eigenvalues greater than 0.4 and scree plots. Finally, four mutually exclusive DPs were identified, as shown in Figure 3. The DP was named according to salient food characteristics. DP1 was named the “unhealthy food pattern”, and was characterized by high factor loading from sugar-sweetened beverages, packaged ultra-processed salty snacks, deep-fried foods, Western fast-food, instant noodles and processed meats. Similarly, the other three DPs were named DP2—tuber and legume pattern (white root/tubers, potato, legumes, red and orange vegetables), DP3—protein and seafood pattern (eggs, milk, unprocessed red meat, fish and seafood), DP4—vegetable and fruit pattern (green leafy vegetables, other vegetables and fruit). These four DPs could explain $22.67\%$, $15.29\%$, $13.89\%$ and $12.47\%$ of the variance, respectively. Food variables with higher factor loadings in the DP indicated higher intake. Each participant had four DP scores, with the largest DP score indicating their preference for that DP. As shown in Figure 4 and Figure 5, $50.6\%$ of the participants tended to be DP4, and $55.90\%$ of them were girls; $15.8\%$ of participants preferred DP1, of which $54.1\%$ were boys. ## 3.5. Associations between Dietary Patterns and Physical Fitness Table 5 showed the results of the linear regression analysis of the predictor (DPs) for different parameters of PF after adjusting for the basic confounders (age, place of residence, parents’ educational level and family economic status; model 1) and additional adjustment for PA confounders (model 2). DP1 was negatively correlated with CRF in boys (OR 0.56, $95\%$ CI 0.31–0.98, $p \leq 0.05$). DP2 was negatively correlated with BMI in girls (OR 0.84, $95\%$ CI 0.72–0.97, $p \leq 0.05$) and positively correlated with flexibility fitness in boys (OR 3.03, $95\%$ CI 1.36–6.77, $p \leq 0.01$). DP3 was positively associated with girls’ motor fitness (OR 2.37, $95\%$ CI 1.14–4.95, $p \leq 0.05$) and boys’ upper body muscular strength (OR 1.15, $95\%$ CI 1.04–1.27, $p \leq 0.01$). When analyzed with additional adjustment for PA (model 2), all results remained statistically significant (all $p \leq 0.05$). Moreover, the relationship between DP1 and girls’ BMI became significant (OR 1.12, $95\%$ CI 1.001–1.26, $p \leq 0.05$) after adjusting for age, place of residence, parents’ educational level, family economic status and PA. ## 4. Discussion The purpose of this study was to examine the associations between PA levels, DP and PF among Chinese adolescents, taking into account demographic factors such as gender, age, place of residence, parents’ educational level and family economic status. We had several important findings. ## 4.1. Physical Fitness The average PF score of the participants was 75.67, and $39.4\%$ of participants could achieve a “good” or “excellent” rating from PF. Compared with 2016, the PF performance of adolescents in Shandong Province has been greatly improved. Specifically, their muscular endurance and muscular strength improved. For example, the 1000 m/800 m run was shortened by 8.1 s and 5.5 s for boys and girls, respectively, and the standing long jump was improved by 7.51 cm and 3.00 cm, respectively. Additionally, the average number of pull-ups for boys also increased by 1.18 [41]. However, $55.8\%$ of the boys still failed the pull-ups test, and even $31\%$ scored 0. The boy’s upper body muscular strength is worrying and it is necessary to carry out targeted exercises for boy’s upper body muscles. Secondly, we found statistical differences in PF by gender, place of residence and PA. We observed that girls had better PF performance than boys, especially in CRF. Adolescents living in rural areas had higher PF scores than those living in urban areas; active PA could significantly improve adolescents’ PF performance, and PF performance improved with age. These findings are consistent with previous studies [42,43,44]. However, the PF scores of 18-year-old boys in this study were significantly lower than those of 17-year-old boys. This result may be due to the small sample size of 357 ($4.1\%$) for 18-year-old boys. The specific reasons for this will be explored in detail in the future by further expanding the sample size. It is noteworthy that parents’ educational level was only associated with boys’ PF in this study. Boys whose fathers had a university or above level of education performed significantly better in PF than those whose fathers had a junior high school or below level of education. However, boys whose mothers had a university or above level of education performed worse in PF than those whose mothers had a junior high school or below level of education. These findings are inconsistent with the findings of previous studies [29,30]. These discrepancies may be partly attributable to the different division of parenthood in Chinese families. Chinese fathers play a key role in their children’s PA choices and behaviors [45]. Adolescents whose fathers were highly educated engaged in significantly more PA per week than those whose fathers were less educated, and PA levels were positively associated with adolescents’ PF performance [46,47]. However, Chinese mothers, especially those from better-off and better educated families, invest more in their children’s education and are more willing to enroll their children in cram schools, which greatly reduces their children’s PA time [48]. ## 4.2. Dietary Patterns Four DPs were identified in this study, including the unhealthy food pattern, tuber and legume pattern, protein and seafood pattern and vegetable and fruit pattern. It can be found that the DPs derived from this study are significantly different from the Korean DP and MD patterns [14,25]. According to the recommendations of the “Dietary Guidelines for Chinese School-aged Children [2022]”, school-age children should drink milk every day and not drink sugary drinks. However, we found that $15.8\%$ of the participants preferred the “unhealthy food pattern”, and only about half of them ($58.8\%$) drank milk on a daily basis. It is evident that the milk consumption among Chinese adolescents is relatively low, and the promotion of scientific consumption concepts of dairy products should be strengthened to raise the correct awareness of dairy products among adolescents and their parents. Additionally, $24.3\%$ of participants in this study were overweight, which is higher than the findings in 2017 [49]. Studies have shown that the prevalence of overweight among Chinese adolescents continues to increase [50]. Furthermore, we found that GDR scores were associated with BMI in Chinese adolescents, with higher GDR-limit scores associated with higher odds of obesity and higher overall GDR scores associated with lower odds of obesity [38]. However, the overweight participants in this study consumed more unhealthy foods than those who were obese. This may be due to misperceptions about their weight among overweight individuals. Some studies have reported that adolescents who perceive themselves to be heavier have more restrictions on their diets [51]. Therefore, in order to effectively curb the epidemic of overweight and obesity among Chinese adolescents and to promote their healthy growth, it is necessary to enhance the dissemination of nutritional health knowledge among Chinese adolescents, especially boys, and guide them to develop the correct view of health. ## 4.3. Physical Activity, Dietary Patterns and Physical Fitness Further analysis of different PF tests revealed that DPs had different effects on the PF of boys and girls. Energy-dense and low-nutrient junk food is a major component of DP1. Excessive consumption of junk food can lead to excessive accumulation of energy, obesity and other metabolic diseases [43]. Another investigation reported that excessive consumption of junk food in obese school children is associated with derangement of sympathetic cardiovascular functions and reduced pulmonary functions [52]. Our findings have showed that DP1 was negatively correlated with CRF in boys. This may be due to the higher prevalence of obesity among boys in this sample. Whether there are gender differences in the effect of junk food on CRF among Chinese adolescents needs to be further explored. DP2 (tuber and legume pattern) is rich in white root/tubers, potato, legumes, red and orange vegetables and low in seafood. It is a major food source of isoflavones, phytosterols, lecithin, chlorophyll, lutein, lycopene, anthocyanins, polyunsaturated fatty acids and dietary fiber [53,54]. Previous studies have shown that there was a negative association between DP2 and abdominal obesity among adolescents [16]. However, in the present study, DP2 was only negatively associated with BMI in girls but not significantly associated with BMI in boys. In addition, moderate intake of high-quality protein has been shown to help improve muscular strength and speed-agility in adolescents [55]. However, we found that DP3 (protein and seafood pattern) had different effects on PF in boys and girls. For girls, DP3 was positively associated with motor fitness, while for boys, DP3 was positively correlated with upper body muscular strength. To examine the role of PA on the relationship between DPs and PF, we further adjusted the analysis for active PA. The results showed that the relationship between DP1 and girls’ BMI became significant after adjustment for active PA. One explanation is that physically active individuals make healthier and more beneficial food choices in order to perform better [56]. However, we did not find a significant change in the relationship between DP1 and boys’ BMI due to adjustment for active PA. In the future, more investigations are needed to explore this cause. ## 4.4. Study Limitations and Future Research Some limitations in this study must be explained. First, this study was based on participants’ self-reports, which may be subject to self-report bias. Second, although gender, age, place of residence, parents’ educational level and family economic status were accounted for in our analyses, residual confounding factors such as sedentary behavior and pubertal development status cannot be excluded. Third, it must be noted that this research is a cross-sectional study, so it cannot reflect the development and changes of PF in adolescents. Given the above limitations, longitudinal studies with more diverse sample sources and more comprehensive designs are needed in the future to better understand the influencing factors of Chinese adolescents’ PF and formulate corresponding countermeasures. ## 5. Conclusions This paper elucidates for the first time the impact of DPs and PA on the PF through the factor analysis of adolescents aged 11–18 years in Shandong Province from 2020–2021, and further analyzes the differences between boys and girls. We have found that: [1] Overweight, unhealthy food patterns and poor upper body muscular strength were more common in boys than in girls. [ 2] Highly educated fathers contributed to improve PF in boys, but highly educated mothers did not. [ 3] Four DPs were obtained, and different DPs may have different effects on PF in boys and girls. Specifically, the unhealthy food pattern was negatively associated with CRF in boys. After adjusting for active PA, the relationship between unhealthy food pattern and girls’ BMI became significant. The tuber and legume pattern was negatively associated with BMI in girls, yet positively associated with flexibility fitness in boys. The protein and seafood pattern was positively associated with girls’ motor fitness and boys’ upper body muscular strength. Therefore, in order to effectively improve PF in adolescents, strategy developers should take into account the differences in diet and PF between boys and girls as well as the different effects of DPs and PA on PF in boys and girls so as to maximize the effectiveness of interventions. Our findings could have benefits in formulate a theoretical basis for the development of PF in Chinese adolescents. Future larger prospective studies are needed to explore the relationship between DPs, PA and PF and other health-related parameters in the Chinese adolescents. ## References 1. Caspersen C.J., Powell K.E., Christenson G.M.. Physical activity, exercise, and physical fitness: Definitions and distinctions for health-related research. Public Health Rep. (1985.0) 100. PMID: 3920711 2. Ganley K.J., Paterno M.V., Miles C., Stout J., Brawner L., Girolami G., Warren M.. Health-related fitness in children and adolescents. Pediatr. Phys. Ther. (2011.0) 23 208-220. DOI: 10.1097/PEP.0b013e318227b3fc 3. 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--- title: 'Urinary Continence Resolution after Bariatric Surgery: Long-Term Results after Six-Year Follow-Up' authors: - Thibaut Waeckel - Khelifa Ait Said - Benjamin Menahem - Anais Briant - Arnaud Doerfler - Arnaud Alves - Xavier Tillou journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051985 doi: 10.3390/jcm12062109 license: CC BY 4.0 --- # Urinary Continence Resolution after Bariatric Surgery: Long-Term Results after Six-Year Follow-Up ## Abstract Background: Bariatric surgery is known to improve stress urinary incontinence (SUI) and overactive bladder disorders (OAB). However, there is little long-term follow-up in the literature. Objective: To determine the long-term effect of bariatric procedures on SUI and OAB and their impact on quality of life, we applied the ICIQ and USP questionnaires. Setting: The research was conducted at a French university hospital with expertise in bariatric surgery. Methods: We performed an updated follow-up at 6 years of a prospective cohort of 83 women who underwent a bariatric procedure between September 2013 and September 2014. The women completed the USP and ICIQ questionnaires before surgery, 1 year and 6 years after the surgery. Results: Of the 83 patients, 67 responded ($80.7\%$) in full. SUI remained improved at 6 years: the USP score decreased from 3 [1; 7] before surgery to 0 [0; 1] ($$p \leq 0.0010$$) at 1 year after surgery and remained at 0 [0; 0] ($$p \leq 0.0253$$) at 6 years. The decrease in the OAB symptom score remained statistically significant: 3 [1; 7] before the surgery vs. 2 [0; 5] at 6 years ($$p \leq 0.0150$$). However, this improvement was significantly less pronounced than at 1 year: 0 [0; 1] ($$p \leq 0.002$$). Conclusions: Bariatric surgery seems to be effective at treating SUI and OAB with a long-lasting effects, still noted at 6 years. ## 1. Introduction Obesity is a worldwide public health problem affecting $13\%$ of the population [1]. The Obepi 2 study [2] published in 2020 shows that overweight affects almost half of the population in France. Bariatric surgery can be considered for patients with a body mass index (BMI) ≥ 40 kg/m2, or ≥35 kg/m2 when associated with another comorbidity condition (after of 6 to 12 months of medical treatment) [3]. Urinary incontinence is defined according to the terminology of the International Continence Society as “involuntary loss of urine through the urethra”, constituting a social or hygiene problem that can be objectively demonstrated [4]. There are three main types of urinary incontinence: stress urinary incontinence (SUI); overactive bladder (OAB) and mixed incontinence. It is a major public health problem; in France, approximately three million women are affected by urinary incontinence [5]. After failure of medical treatment, sub-urethral slings can be proposed to treat SUI in women. For women with a BMI ≥ 35 kg/m2, the results of sub-urethral slings are poor: only $81\%$ achieve continence vs. $96\%$ in the general population [6]. Weight loss for obese women who suffer from urinary incontinence is recommended too by the European Association of Urology (EAU) [7]. We established previously, with a one-year follow-up, that weight loss after bariatric surgery improved stress urinary incontinence (SUI), OAB (overactive bladder), dysuria and quality of life (QoL). These results were especially convincing in women [8]. The aim of this study was to determine the impact of bariatric surgery on female urinary incontinence at 6 years. ## 2.1. Endpoints The primary endpoint was the evolution of urinary incontinence at 6 years, as evaluated by the USP questionnaire. The secondary endpoints were the evolution of urinary incontinence and associated quality of life between 1 and 6 years. ## 2.2. Patients Between September 2013 and September 2014, in a French University hospital with expertise in bariatric surgery, 83 women underwent bariatric procedures. The surgical technique chosen (Roux-en-Y gastric bypass (LRYGB) or sleeve gastrectomy (LSG)) was discussed for each patient during a multidisciplinary meeting. All patients were included in an observational prospective cohort [8]. They completed two urinary questionnaires: the Urinary Symptom Profile (USP) and the International Consultation on Incontinence Questionnaire (ICIQ). ## 2.3. Questionnaires The USP (Supplementary Materials) was developed by the French Association of Urology in 2005. The 13 questions explore all urinary symptoms: stress urinary incontinence (SUI), overactive bladder (OAB) and obstructive symptoms. The ICIQ (Supplementary Materials) focuses on SUI, urge incontinence, mixed incontinence and their impact on quality of life (QoL) [9]. The ICIQ is validated in French. These questionnaires are complementary: the USP does not assess QoL, while the ICIQ does not assess OAB symptoms. The higher the score, the more severe the symptoms. The endpoint of this study was based on these questionnaires. The questionnaires were completed in the hospital preoperatively, by mail at one year and by phone at six years. ## 2.4. Weight Loss Evaluation Weight loss was expressed as the change in body mass index (BMI), the percentage of excess weight loss (%EWL) and the percentage of total weight lost (%TWL). The %EWL is based on an ideal body weight equivalent to a BMI of 25kg/m2. The %TWL is based on the maximum weight reached by the patient. ## 2.5. Statistical Analysis Baseline characteristics were described by numbers (percentages) for qualitative variables and the median (and interquartile range (IQR)) for quantitative variables. The normal distribution of quantitative variables was tested using the Shapiro–Wilk test. The primary endpoint and secondary endpoints were analyzed using Friedman’s non-parametric test to compare repeated measures. Wilcoxon’s rank test was used to compare the %EWL at one and six years. Spearman’s correlations were generated to assess the association between the evolution of SUI and evolution of %EWL and %TWL. Post hoc analysis was performed with Dunn’s multiple comparisons. Some secondary endpoints (BMI, ICIQ, %EWL, %TWL) had missing data; at most, there were 3 missing data ($4\%$) for each of the 67 patients. We handled missing data using multiple imputations through the fully-conditional specification method, based on the age and values of the secondary endpoints at baseline, with the generation of one dataset. Subgroup analyses were performed for each surgical modality (LSG and LRYGB). We compared the evolution before surgery vs. at six years of IMC, % TWL and USP and ICIQ scores using the Mann–Whitney U test. GraphPad Prism version 9.3.1 (GraphPad Software, San Diego, CA, USA, https://www.graphpad.com accessed on 3 January 2023) and SAS software version 9.4 (SAS institute, NC, Cary, USA) were used for statistical analyses and a p-value < 0.05 was considered to denote statistical significance. ## 2.6. Ethics The study was conducted according to the guidelines of the Declaration of Helsinki. Data collection followed French legislation concerning prospective non-interventional studies to evaluate routine care (Article Art. L1121-1-2 of French Public Health Code). Data were collected from a prospectively maintained database of patients who underwent laparoscopic bariatric surgery at the University Hospital of Caen, a French specialized and accredited bariatric center, after January 2012 (CNIL 2204611v0). The study did not require submission to a consultative committee for persons’ protection in biomedical research. ## 3.1. Characteristics of the Population The median age of the women operated on was 46.0 [36.0; 54.0] years. The preoperative BMI was 42.5 [39.4; 46.0] kg/m2. These women were suffering from sleep apnea (29–$43.3\%$), gastric reflux (7–$11.4\%$), arthrosis (13–$19.4\%$), diabetes (14–$20.9\%$), arterial hypertension (22–$32.8\%$) and dyslipidemia (10–$13.9\%$) (Table 1). ## 3.2. Follow-Up Questionnaires Both questionnaires were completed by 83 women (19 LSG–64 LRYGB) at one year and by 67 ($80.7\%$) women at six years (14 LSG–53 LRYGB). Two women died ($2.4\%$) and 14 were lost to follow-up ($16.9\%$). After 6 years of follow-up, 22 patients still attended regular in-office follow-up ($26.5\%$). The mean age was 45.7 ± 11.6 years old. A flow chart of the follow-up is shown in Figure 1. ## 3.3. Weight Loss Weight loss at 6 years remained significant despite weight regain between the first and sixth years: %EWL increased from 73.0 [59.0; 94.0] to 61.0 [45.0; 80.0] ($p \leq 0.0001$); %TWL increased from 36.1 [31.6; 44.4] to 29.9 [23.9; 39.2] ($p \leq 0.0001$). BMI changed from 42.5 [39.4; 46.0] kg/m2 before the surgery to 29.1 [26.0; 33.3] kg/m2 one year after the surgery, then to 30.8 [28.1; 36.4] kg/m2 six years after the surgery ($p \leq 0.0001$). No significant difference in evolution was found between pre-surgery and six years post-surgery according to the type of surgery (LSG or LRYGB) for BMI ($$p \leq 0.57$$) or %TWL ($$p \leq 0.51$$) ## 3.4. Stress Urinary Incontinence SUI remained improved at 6 years: the USP score decreased from 1 [0; 3] before surgery to 0 [0; 0] ($$p \leq 0.001$$) at 1 year after surgery and 0 [0; 0] ($$p \leq 0.0253$$) at 6 years. There was no deterioration of the USP score between one and six years ($p \leq 0.9999$). There was no correlation between the evolution of SUI and the evolution of %EWL (r = −0.20; 95 CI [−0.42; 0.05]; $$p \leq 0.10$$) or %TWL (r= −0.10; $95\%$ CI [−0.34; 0.15]; $$p \leq 0.40$$). The type of surgery (LSG or LRYGB) did not influence the evolution between the results before surgery and at six years ($$p \leq 0.72$$). ## 3.5. Overactive Bladder The decrease in the OAB symptom score remained statistically significant: 3 [1; 7] before the surgery vs. 2 [0; 5] at six years ($$p \leq 0.0150$$). However, this improvement was significantly less pronounced than at one year: 0 [0; 1] ($$p \leq 0.002$$). There was no correlation between the evolution of OAB and the evolution of %EWL (r = −0.05; $95\%$ CI [−0.30; 0.20]; $$p \leq 0.67$$) or %TWL (r = −0.05; $95\%$ CI [−0.29; 0.20]; $$p \leq 0.69$$). The variation of the score before surgery vs. at six years was not influenced by the type of surgery ($$p \leq 0.12$$). ## 3.6. Dysuria Despite weight loss, dysuria was not improved at one and six years. The score was 0 [0; 0] before the surgery and was still 0 [0; 0] at one year ($$p \leq 0.8997$$) and 0 [0; 0] at six years ($$p \leq 0.7306$$). ## 3.7. Quality of Life Related to Urinary Symptoms The improvement in QoL related to urinary symptoms at one year (0 [0; 0] vs. 3 [0; 9] ($$p \leq 0.0001$$)) was not found at six years: 0 [0; 7] ($$p \leq 0.3918$$). There was a significant deterioration of the ICIQ ($$p \leq 0.0325$$). The results before surgery vs. at six years did not differ significantly depending on the type of surgery ($$p \leq 0.39$$). The questionnaire results and evolution of dimensions are show in Table 2. ## 4. Discussion To our knowledge, with 66 months of follow-up, this study offers data with the longest follow-up in the literature. Recent meta-analyses on this topic reported follow-ups of approximately 1–2 years [10,11,12]. Follow-up of bariatric surgery patients is difficult due to moderate compliance with care. In the SOS study, the rate of follow up at 10 years was $42\%$ [13]. The follow-up of patients in this study appeared to be consistent with those reported in the literature. Weight loss after bariatric surgery was shown to improve SUI [14]. Our study confirmed this effect in the long term despite a partial weight gain. SUI in obese patients is due to abdominal pressure exceeding the strength of the urinary sphincter. Reducing intra-abdominal weight may be sufficient to improve SUI. Despite an improvement in the OAB at one year, our study demonstrated a deterioration at six years. This degradation did not seem to be related to %EWL or %TWL. The production of leptin by the adipose tissue leads to stimulation of the noradrenergic sympathetic nerves [15]. Perivesical fat accumulation is also associated with local inflammation leading to OAB [16]. Furthermore, researchers assert that the distribution of fat in women could explain this phenomenon, although it is recognized that weight gain is more often localized in the hips than in the perivesical area. The EPICONT [17] study, a large Norwegian prospective study, showed a dose effect of weight in urinary incontinence without distinguishing the type of surgery. This effect seems to be cumulative because we did not find any correlation with %TWL. Rapid weight loss could provide a better improvement in urinary incontinence [18]. This hypothesis tends to give an advantage to LRYGB; however, in this cohort, the type of surgery (LSG or LRYGB) did not seem to influence the outcome at six years. This can probably be explained by a lack of power. Indeed, only 14 women were treated with LSG. The strengths of our study were its prospective nature and the number of patients included, with a long follow-up associated with a good response rate of completed questionnaires at one year. The questionnaire at one year was administered by email and had a self-administrated design, which may have supported the good response rate. In addition, weight was measured at a one-year follow-up clinical consultation. This study also had some limitations. To simplify and optimize data collection and minimize the number of people lost to follow-up, the collection of weight measurements and the answers to the questionnaires at six years were carried out by phone. The declared weight was, therefore, subject to social desirability bias [19]. This bias could have minimized the reported weight gain at six years. Furthermore, USP and ICIQ are validated, self-administered questionnaires [20,21], but phone responses to them may have biased the results. However, considering the number of patients lost to long-term follow-up, this method allowed us to increase the amount of data. Additional points to note are that since 2012, the Caen University Hospital has been recognized as a Specialized Obesity Center (CSO); there was thus a risk of selection bias given the center’s expertise. Finally, this was a retrospective study on a prospective cohort; there were, therefore, biases inherent in the study’s design. ## 5. Conclusions Obesity is a fast-growing public health issue around the world, and related urinary and fecal disorders are underestimated. These results support a long-term effect of bariatric surgery (LSG or LRYGB) on urinary incontinence in women. This effect seems to diminish in the long term compared to at one year but is still notable. 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--- title: Exploration of the Antioxidant Effect of Spermidine on the Ovary and Screening and Identification of Differentially Expressed Proteins authors: - Dongmei Jiang - Yongni Guo - Chunyang Niu - Shiyun Long - Yilong Jiang - Zelong Wang - Xin Wang - Qian Sun - Weikang Ling - Xiaoguang An - Chengweng Ji - Hua Zhao - Bo Kang journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10051986 doi: 10.3390/ijms24065793 license: CC BY 4.0 --- # Exploration of the Antioxidant Effect of Spermidine on the Ovary and Screening and Identification of Differentially Expressed Proteins ## Abstract Spermidine is a naturally occurring polyamine compound that has many biological functions, such as inducing autophagy and anti-inflammatory and anti-aging effects. Spermidine can affect follicular development and thus protect ovarian function. In this study, ICR mice were fed exogenous spermidine drinking water for three months to explore the regulation of ovarian function by spermidine. The results showed that the number of atretic follicles in the ovaries of spermidine-treated mice was significantly lower than that in the control group. Antioxidant enzyme activities (SOD, CAT, T-AOC) significantly increased, and MDA levels significantly decreased. The expression of autophagy protein (Beclin 1 and microtubule-associated protein 1 light chain 3 LC3 II/I) significantly increased, and the expression of the polyubiquitin-binding protein p62/SQSTM 1 significantly decreased. Moreover, we found 424 differentially expressed proteins (DEPs) were upregulated, and 257 were downregulated using proteomic sequencing. Gene Ontology and KEGG analyses showed that these DEPs were mainly involved in lipid metabolism, oxidative metabolism and hormone production pathways. In conclusion, spermidine protects ovarian function by reducing the number of atresia follicles and regulating the level of autophagy protein, antioxidant enzyme activity, and polyamine metabolism in mice. ## 1. Introduction Mammalian ovaries consist of follicles as basic functional units. The reproductive life span of the organism mainly depends on follicular development that maintains the primordial follicle pool in the cohort of follicles within the ovary [1]. The total number of ovarian follicles is determined early in life, and the depletion of the follicle pool leads to reproductive senescence [2]. Follicular atresia occurs in approximately $99\%$ of the follicles in the mammalian ovary at various stages [3]. The total count of primordial follicles decreases with age due to ovulation and follicular atresia. Follicular atresia, a process of ovarian follicle degradation, mainly occurs via apoptosis, but recent studies also favor autophagy existence [1]. Generally, the proliferation and differentiation of granulosa cells lead to follicular maturation and ovulation, whereas apoptosis and degeneration of granulosa cells result in follicular atresia [4]. Ovarian granulosa cells are the only somatic cells that interact closely with oocytes and are extensively involved in primordial follicle recruitment, dominant follicle selection, steroid hormone secretion, and follicular atresia, and serve major roles in follicular development [5,6]. Polyamines are a class of polycationic fatty amines widely existing in the biological world, mainly including putrescine, spermidine and spermine. Natural polyamines themselves, especially spermidine and spermine, can act as reactive oxygen species (ROS) scavengers, thereby protecting cells from oxidative damage mediated by free radicals [7,8]. In recent years, a great quantity of in vitro and in vivo experimental studies have shown that polyamine depletion induces ROS accumulation and leads to cell damage, which in turn inhibits cell growth [9,10,11]. Exogenous spermidine can play antioxidative stress [12,13,14] and antiaging [15] roles by activating the autophagy pathway. Therefore, maintaining the stability of polyamine levels in the body is instrumental in maintaining the homeostasis of cellular redox. Spermidine is a polyamine widely present in animals, plants and microorganisms and can participate in the regulation of animal reproduction by mediating spermatogenesis in male animals, as well as follicle development, oogenesis and ovulation in female animals [16]. Apoptosis of granulosa cells is the initiating factor of follicular atresia, which is not conducive to the improvement of animal productivity and is also associated with premature ovarian failure [5]. It has been proved that oxidative stress can induce apoptosis. Spermidine is an antioxidant [17] that is closely related to ovarian function. In addition, studies in recent years have shown that spermidine can reduce ROS levels and delay cell aging in humans and other models, such as yeast, Drosophila and nematode models [18]. Adding spermidine or feeding spermidine-rich food can significantly improve the lifespan of rats [15]. Spermidine and spermine themselves protect E. coli and mammalian cells from oxidative damage caused by H2O2 [10,19]. Using microarrays to compare yeast (spermine-deficient) mutants containing lower levels of spermidine with yeast mutants supplemented with spermidine, spermidine altered the expression of 500 genes by more than 2-fold, including several genes involved in the oxidative stress response (HSP12, GAD1, GPX2, etc.) [ 20], suggesting that spermidine can regulate a variety of antioxidant enzymes at the transcriptional level. Studies have found that spermidine can activate the Keap1-Nrf2-ARE antioxidant signaling pathway and then mediate heme oxygenase-1 (HO-1) and reduce coenzyme (NAD(P)H quinone oxidoreductase 1. Endogenous antioxidant enzymes such as NQO 1 and catalase (CAT) are involved in regulating the body’s antioxidant function [21,22]. In addition, a recent study showed that spermidine could manifest an antioxidative stress role by increasing the level of glutathione (GSH) and reducing the content of malondialdehyde (MDA) in rat brain tissue, reducing lipid peroxidation [23]. Spermidine can also participate in free radical scavenging activities, reducing age-related oxidative protein damage and ROS overproduction [24,25]. To date, the research on spermidine’s antioxidative stress has mainly focused on neural tissue, while research on spermidine’s involvement in regulating the antioxidant function of the female ovary and further affecting its reproductive and production performance is relatively rare, and the corresponding mechanisms remain unclear. Under normal physiological conditions, autophagy maintains the physiological activities of cells by specifically degrading damaged or redundant organelles, so autophagy is an important cytoprotective mechanism. However, excessive autophagy is detrimental. Studies have shown that nonapoptotic forms of programmed cell death (PCD), such as autophagy, may also be involved in the process of follicular atresia [26,27,28]. More autophagosomes can be detected in the granulosa cell layer of atretic follicles [29], and ROS, as a byproduct of aerobic metabolism in the body, can induce oxidative stress and cell damage when accumulated in large amounts [30]. Animal reproductive activities often require large amounts of energy and nutrients, which also lead to the production and enrichment of ROS [31]. Numerous studies have shown that spermidine can enhance cellular function by activating autophagy. Spermidine lost the ability to scavenge ROS after the knockout of the autophagic protein Beclin 1 [18]. It is suggested that spermidine can induce autophagy and inhibit follicular atresia in mice. In recent years, proteomics technology has provided technical support for ovarian-related research. For example, comparing the differences in serum protein expression levels between patients with polycystic ovary syndrome (PCOS) and non-PCOS patients is helpful for finding potential serum markers [32]. Additionally, integrative metabolomics and proteomics were used to highlight altered polyamine pathways in lung adenocarcinomas [33]. Combined single-nucleus sequencing (snRNA-seq) and proteomic analysis revealed a direct anti-inflammatory effect of spermidine on glial cells in a mouse model in an autophagy-dependent manner [34]. In this study, mice were fed with exogenous spermidine for a period of time. We investigated the effect of spermidine on the antioxidation of ovarian function by detecting the histological changes of the ovary, the expression level of autophagy protein and follicular development-related protein, the activity of antioxidant enzymes, the content of polyamines and the expression of polyamine metabolism genes. Further, the differential proteins related to antioxidation and autophagy of spermine were mined by using the LFQ proteomics technology, and the protein expression profile of spermine on ovarian function was screened and analyzed, providing clues for further research. ## 2.1. Effects of Spermidine on Water Intake, Body Weight and Ovarian Index in Mice After feeding female ICR mice with 3 mmol L−1 spermidine for 3 months, it was found that the weight of the mice increased steadily but did not differ significantly between the two groups (Figure 1A). This shows that spermidine has no harmful effect on mice. The daily food intake increased significantly but did not lead to significant differences in daily weight gain or water intake (Figure 1B,D,E), and spermidine had no effect on the ovarian index of mice (Figure 1C). ## 2.2. Effects of Spermidine on Ovarian Histomorphology and Follicular Development in Mice We found that the boundary between the mouse ovarian cortex and medulla was clear: round or oval follicles with different sizes were visible, the number of oocytes did not increase significantly, there was no obvious interstitial hyperplasia in the medulla, and the shape and number of primordial follicles, growing follicles and mature follicles in the cortex were not significantly different from the control group (Figure 2A). The number of atresia follicles and the extent of corpus luteum in the spermidine treatment group decreased significantly (Figure 2B). To verify the effect of spermidine on mouse follicular development, we quantified proteases related to ovarian steroid hormone synthesis. Many studies have demonstrated that steroid hormones play important roles in regulating follicular growth and atresia. Cytochrome P45017A1 (CYP17A1), 3 β-hydroxysteroid dehydrogenase (3β-HSD), and 17 β-hydroxysteroid dehydrogenase (17β-HSD) and other enzymes are expressed in growing follicles, and the corpus luteum, and their main function is to convert estrogen into E2, thereby affecting follicular development. The results showed that the protein expression of CYP17A1 and HSD3B2 in mouse ovaries treated with spermidine was significantly increased (Figure 2C,D) ## 2.3. Effects of Spermidine on Polyamine Content and Expression of Key Metabolic Genes in Mouse Ovaries The spermine content in the treatment group was significantly higher than that in the control group, which was approximately 1.2 times that of the control group. There was no significant effect of putrescine and spermidine content in ovaries (Figure 3A). The relative expression of the polyamine oxidase (APAO) gene was significantly upregulated in the treatment group. The relative expression of the spermidine synthase (SPDS), spermine synthase (SPMS) and spermine oxidase (SMO) genes was significantly lower than in the control group. The relative expression of the ornithine decarboxylase (ODC) and N’-spermidine/spermine acetyltransferase (SSAT) genes was not significantly different (Figure 3B). ## 2.4. Spermidine Activates Antioxidant Enzyme Activity to Protect the Ovary Further exploration of the antioxidant function of spermidine on the mouse ovary showed that the total antioxidant capacity of the mouse ovary was significantly increased to approximately 1.62 times that of the control group (Figure 4B). Both SOD and CAT enzyme activities were significantly higher than those of the control group, and they were 2.50 times and 1.67 times those DEPs of the control group, respectively (Figure 4A,C). The ovarian MDA level of the spermidine-treated group was significantly lower than that of the control group, which was 0.47 times that of the control group (Figure 4E). Feeding spermidine had no significant effect on the enzymatic activity of mouse ovary GSH-px (Figure 4D). ## 2.5. Spermidine Induces Ovarian Autophagy in Mice SPD antioxidant effect is achieved through the rescue of autophagic flux, but there is a lack of research in the context of the ovary. Therefore, we determined the expression and localization of autophagy proteins in ovaries after spermidine treatment. The positive products of the autophagy marker proteins LC3 and p62 were mainly distributed in the cytoplasm and mainly concentrated in the granulosa cell layer of antral follicles. After feeding with spermidine, the LC3 protein expression signal in mouse ovarian tissue was enhanced, while the p62 protein expression signal was weakened (Figure 5A). The protein expression levels of Beclin 1 and LC3II/I in the ovaries of the treated mice were significantly increased and were 1.93 times and 1.83 times those of the control group, respectively. Compared with the control group, the expression of p62 protein was significantly decreased to 0.53 times that of the control group (Figure 5B,C). ## 2.6. Protein Sample Consistency Test and Protein Identification Next, with the purpose of investigating the potential mechanisms of spermidine action against ovarian oxidative stress and induced autophagy, we conducted non-label-free proteomic sequencing to screen and identify the key proteins that confer protective effects on the mouse ovary. Sample quality and repeatability are important for protein sequencing. The results of the protein quantitative principal component analysis showed that the quantitative repeatability of the aggregation degree between repeated samples was good, the difference between the two groups was large (Figure 6A), the RSD box axis was relatively centered (Figure 6B), and the Pearson correlation coefficient between samples was close to one. The samples were shown to be reproducible (Figure 6C), and the samples were available. The distribution of peptide lengths (7–20 amino acids) identified by mass spectrometry met the quality control requirements (Figure 6D). A negative correlation between the molecular weight of the protein and the coverage was observed. To achieve equal coverage, more peptides must be identified for a large protein (Figure 6E). ## 2.7. Screening of Differentially Expressed Proteins Next, we screened 6545 DEPs by nonstandard quantitative proteomic sequencing, of which 5498 proteins could be quantified (Figure 7A). Compared with the control group, the 3 mmol·L−1 spermidine-treated group had 681 differentially expressed proteins and 424 upregulated proteins, including tumor protein p53 (P53), nuclear receptor subfamily 5 group A member 1 (Nr5a1), BCL2-related ovarian killer (Bok), and BH3 domain apoptosis-inducing protein (Bid). There were 257 downregulated proteins, including xanthine dehydrogenase (XDH) and thioredoxin-interacting protein (TXNIP) (Figure 7B and Table 1). These proteins are mainly involved in functions such as “steroid synthesis, apoptosis, autophagy and oxidative stress”. ## 2.8. Functional Classification, Subcellular Structure Localization Classification, and COG/KOG Functional Classification of Differentially Expressed Proteins Most of the DEPs have transporter, transducer, binding and catalytic activities and participate in cellular biological processes (Figure 8A). We classified the proteins identified in this study according to their cellular components based on GO analysis. The DEPs were mainly distributed in the nucleus, cytoplasm, extracellular space, mitochondria and plasma membrane of the mouse ovary. ( Figure 8B). Signal transduction mechanisms (enrich 76 proteins); lipid transport and metabolism (enrich 45 proteins); replication, recombination and repair (enrich 21 proteins) (Figure 8C). ## 2.9. Functional Enrichment Analysis of Differentially Expressed Proteins In terms of biological processes, DEPs are involved in steroid biosynthesis, cholesterol metabolism, lipid homeostasis and transport, and cellular hormone metabolism (Figure 9A). In terms of cellular components, the DEPs mainly play roles in protein extracellular matrix, nuclear chromosome parts and telomeric regions, extracellular matrix component, and chromosomal regions (Figure 9B). In terms of biological functions, the main functions of DEPs, including sterol transporter activity, copper ion binding, cholesterol transporter activity, and especially steroid dehydrogenase activity, were more obvious (Figure 9C). KEGG analysis revealed that DEPs were enriched in signaling pathways such as DNA replication, ovarian steroidogenesis, steroid biosynthesis, and glycerol lipid metabolism (Figure 9D). ## 2.10. Protein Domain Enrichment In order to study the physiological functions of proteins, we enriched protein domains. Protein domains were mainly enriched in the MCM domain, MCM OB domain, MCM N-terminal domain; EGF-like domain, extracellular; START domain; alkaline phosphatase-like, core domain; AMP-dependent synthase/ligase, etc. ( Figure 10). ## 2.11. Analysis of Protein Interaction Network A total of six DEPs were screened, namely, XDH, TXNIP, p53, Nr5a1, Bok and Bid. XDH is an enzyme that catalyzes purine metabolism, which may be related to oxidative stress. TXNIP is also related to oxidative stress, and there seems to be some connection to excessive autophagy. p53 is a cell cycle factor that participates in the cell block. Nr5a1 is a transcription factor for steroidogenesis. Bid and Bok are both proapoptotic proteins and are involved in inducing apoptosis (Figure 11). ## 3. Discussion Putrescine, spermidine and spermine are interconverted through the polyamine metabolic system to maintain the stability of the body’s polyamine pool, and this process requires the participation of a variety of polyamine metabolizing enzymes [35]. In our experiments, after feeding with 3 mmol·L−1 spermidine for 3 months, the expression of the ODC gene in the ovary of mice was statistically insignificant, and the level of putrescine in the ovary did not change, indicating that 3 mmol·L−1 spermidine did not affect the synthesis of putrescine in the ovary of mice. Furthermore, the expression of the SPDS, SPMS and SMO genes in the ovaries of mice in the spermidine group was significantly decreased. APAO had the opposite effect (the levels of spermidine and putrescine were unchanged, and the level of spermine was significantly increased). It is speculated that a portion of the ingested spermidine is converted into spermine for storage, and part of the ingested spermidine forms N 1-acetyl-spermidine under the action of SSAT to maintain spermidine in the ovary. In addition, the decreased expression of SMO is also one of the reasons for the increased spermine level in the ovary. Natural polyamines themselves can bind to negatively charged biological macromolecules such as nucleic acids, proteins, and biofilms, thereby exerting the functions of antioxidative stress and scavenging ROS. However, excess polyamines are catabolized by various amine oxidase enzymes, which produce many reactive aldehydes (such as acrolein) and H2O2, which are toxic and detrimental to proteins, DNA in mammalian cells, and other cellular components that are susceptible to oxidative damage [21,36]. Therefore, how to effectively utilize the antioxidant capacity of polyamine while avoiding oxidative stress caused by polyamine metabolism has become a major problem in the study of polyamine functions. In addition, both spermidine and spermine can be degraded by acetylpolyamine oxidase, and spermine oxidase can directly degrade spermine. While both pathways can produce toxic products, including H2O2, oxidation by spermine oxidase is more likely to cause damage because spermine oxidase is present in the nucleus and cytoplasm, while acetylpolyamine oxidase is a peroxidant. The bioenzyme itself has a protective effect on cells [37]. In this experiment, the expression of SMO in the ovary decreased significantly after spermidine feeding. Our experimental results are consistent with previous results [38]. We speculate that exogenous spermidine can regulate polyamine catabolism by inhibiting the expression of SMO at the transcriptional level and avoiding oxidative damage. Therefore, spermidine can maintain the stability of the polyamine pool by regulating the genes encoding polyamine-metabolizing enzymes. Studies have shown that many pathological phenomena in the body are closely related to lipid peroxidation caused by free radicals [30,39]. In recent years, oxidative stress has taken an important part in maintaining the normal physiological function of the female reproductive system and the pathogenesis of reproductive diseases such as polycystic ovary syndrome [40]. CAT is an important enzyme in the body’s enzymatic antioxidant system that scavenges H2O2 and indirectly inhibits lipid peroxidation and membrane damage. The activity of CAT can indirectly reflect antioxidant capacity [41]. GSH-Px is a known antioxidant enzyme that can convert peroxides and hydroxyl radicals into nontoxic forms [42]. MDA is not only an important product of lipid peroxidation but can also cause intramolecular and intermolecular cross-linking of proteins by reacting with free amino acids of proteins, resulting in cell damage [43]. As a secondary product of lipid peroxidation, MDA reflects the occurrence of ROS and can be used as an indicator of membrane damage [44,45]. Oxidative damage is usually accompanied by decreased activities of CAT, SOD and GSH-px enzymes and an increase in the level of MDA [46,47]. Jantaro et al. [ 48] indicated that the exogenous addition of spermidine could significantly alleviate the increase in ROS levels and lipid peroxidation caused by ultraviolet irradiation in algal cells and had a protective effect on the enzyme activities of SOD and CAT in cells. Recent studies have shown that during cisplatin-induced nephrotoxicity, spermine supplementation can effectively inhibit oxidative stress and nitric acid stress and reduce DNA damage and lipid peroxidation, thereby preventing cisplatin-induced renal tubular necrosis [49]. During follicle development, spermidine is crucial in the regulation of ovarian granulosa cells. External stress may cause apoptosis of ovarian granulosa cells, resulting in follicular atresia and affecting the reproduction of female animals. Our results are consistent with previous findings [50,51] that feeding with 3 mmol·L−1 spermidine significantly increased the T-AOC/SOD and CAT enzyme activities of mouse ovarian tissue without affecting the daily weight gain and ovarian organ index of mice. It significantly reduced the MDA content and decreased the level of ovarian lipid peroxidation. It also significantly reduced the number of atretic follicles in mice. Moreover, the protein expression of CYP17A1 and HSD3B2 in ovarian tissue was increased, thereby promoting follicle development. In conclusion, adding spermidine to drinking water can significantly reduce the atresia rate of follicles in mice and significantly improve the antioxidant capacity of mouse ovaries by increasing the activities of various antioxidant enzymes and reducing lipid peroxidation. It was found that autophagy levels were significantly increased in various tissues (heart, liver and muscle) from 4 h to 24 h by acute intraperitoneal injection of spermidine in mice supplemented with spermidine in drinking water. Changes in mitochondrial structure and function are an initial factor in cellular senescence [52,53], and studies have shown that spermidine can promote cell-dependent selective degradation (mitophagy) in human fibroblasts and mouse neuroblastoma (N2a) cells. This contributes to mitochondrial health and function, which in turn has anti-aging effects [39,54]. Recent studies have shown that spermidine can also inhibit the degeneration of the intervertebral disc by inducing autophagy and then reducing the apoptosis of nuclear myeloid cells [55]. In the field of reproduction, the regulation of autophagy and antiaging effects of spermidine have rarely been reported. Consistent with existing results, we found that spermidine also induces autophagy in mouse ovaries, but the exact mechanism remains unclear. Feeding spermidine significantly increased the expression of the key autophagy proteins Beclin 1 and LC3II in the ovary; at the same time, the expression of p62 protein was significantly decreased, indicating that 3 mmol·L−1 spermidine feeding can induce autophagy. At the same time, the immunohistochemistry results showed that the positive products of the autophagy marker proteins LC3 and p62 were mainly distributed in the cytoplasm and concentrated in the granulosa cell layer of antral follicles. Phagocytosis marker proteins were specifically distributed in the ovary, mainly in granulosa cells. Properly increasing the level of autophagy can help to improve oxidative stress and alleviate neural deafness due to aging or drugs [56]. The above studies show that autophagy has a positive impact on improving the antioxidant capacity of the mouse ovary. The specific mechanism by which spermidine induces autophagy in mouse ovaries to protect against oxidative stress is unclear. Therefore, our research group used proteomic sequencing to screen differentially expressed proteins and provide theoretical support for subsequent experiments. In this study, proteomic methods revealed 681 DEPs in the ovarian tissue of spermidine drinking water-fed mice, including 424 upregulated proteins and 257 downregulated proteins, including p53, Nr5a1, Bok, Bid, XDH and TXNIP, etc. These proteins are mainly involved in functions such as “cell cycle, steroid synthesis, apoptosis, autophagy and oxidative stress”. The expression of several ribosomal proteins and histones was increased, and the upregulated proteins are known to be involved in apoptosis and other processes, indicating that spermidine can promote protein synthesis and apoptosis in ovarian tissue. At the same time, the expression levels of several ribosomal proteins and molecules related to oxidative metabolism were downregulated, and the downregulated proteins are known to be involved in energy metabolism, signal transduction, RNA processing and modification, transcription, lipid transport and metabolism, and other processes. The treatment has an inhibitory effect on some functions of ovarian tissue. GO annotation and functional enrichment analysis showed that the functions of most of the DEPs were related to cell binding, enzyme catalytic ability and molecular function regulation, indicating that spermidine acts on ovarian granulosa cells and through the regulation of related molecular functions, it can change the interactions among ovarian granulosa cells. In our research, protein domains were mainly enriched in the MCM domain, MCM OB domain, MCM N-terminal domain; EGF-like domain, extracellular; START domain; alkaline phosphatase-like, core domain; AMP-dependent synthase/ligase, etc. The MCM protein family is an important part of the DNA prereplication complex and plays an important role in the DNA replication initiation process and DNA damage repair. EGF may regulate reproductive function by controlling the secretion of transferrin; aging can affect the transcription of EGF and EGFR. START and AMP-dependent enzymes are closely related to ovarian steroidogenesis. The KEGG pathway enrichment results showed that the DEPs were involved in multiple cell signaling pathways, including the p-ERK, JNK, p53, TNF, TXNIP and DR signaling pathways. Some research has shown that the p53 [57] signaling pathway is involved in the regulation of ovarian granulosa cell cycle arrest and apoptosis caused by oxidative stress, and these signaling pathways play important roles in regulating ovarian granulosa cell function and follicle development. An appropriate level of autophagy in the body is a prerequisite for the body to maintain normal physiological functions. Insufficient or excessive autophagy can lead to cell death. TXNIP is a widely expressed protein that is induced by various cellular stresses, including oxidative stress and apoptosis [58]. TXNIP is a pro-oxidative protein that negatively regulates thioredoxin activity and its antioxidant function [59]. Gao et al. found that TXNIP significantly reduced the expression of LC3 and p62 proteins during myocardial ischemia/reperfusion (I/R), indicating that TXNIP is an autophagy regulator [60]. Several studies have shown that regulation of developmental and DNA damage response 1 (REDD1) can be bound and stabilized by TXNIP. TXNIP increases autophagosome formation during I\/R by upregulating REDD1 and inhibits autophagosome clearance in vivo by ROS induction [58,61]. TXNIP-REDD1 plays a role in excessive myocardial autophagy, which is a new way to regulate autophagy [62]. Previous studies found that TXNIP can regulate the autophagy of Mueller cells [63] and tubular cells [64] by inhibiting the activation of mTOR. Consistent with this, in Caco-2 cells, the bidirectional effect of TXNIP on autophagic flux may also regulate the change in SQSTM1/p62 protein [65]. In our research, we found by proteomics that spermidine downregulated the protein expression of TXNIP in mouse ovaries. In addition to its role in mediating oxidative stress, TXNIP is also a factor closely related to the reproductive system. Oxidative stress induces excessive secretion of androgens, which in turn induces IR in PCOS [66]. Localized IR in the ovary may lead to abnormal follicular development, ovulatory disorders and hyperandrogenism, resulting in reproductive disorders. The levels of testosterone (T), Luteinizing hormone (LH), Estradiol (E2), and the mRNA levels of TXNIP and insulin-like growth factors (IGF-1) in ovarian tissue decreased after TXNIP was knocked down, and the level of FSH increased. This result indicated that inhibiting the expression of TXNIP could reduce the expression of ovarian function-related hormones. The results of Illumina sequencing and qRT-PCR showed that the CYP19A1 and TXNIP genes might take part in promoting the development of bovine follicles and ultimately cause follicle ovulation [67]. TXNIP is highly expressed in bovine cumulus cells [68], porcine oocytes [69] and porcine oviduct epithelial cells [70]. This gene is also important in the maturation of mouse oocytes [71]. These results provide a potential reference for the study of mammalian follicular mechanisms and provide a possible new genetic marker for the study of the pig granulosa cell cycle [72]. These data suggest that future research directions will involve the exploration of the specific functions of TNXIP in the ovary. Studies have shown that excessive oxidative stress can lead to ovarian granulosa cell damage [73], which in turn induces granulosa cell apoptosis, leading to follicular atresia [74]. Spermidine has been reported to inhibit reactive oxygen species and may act as an endogenous reactive oxygen species scavenger [10]. This result suggests that spermidine may play an antioxidant role by downregulating the expression of TXNIP in ovarian granulosa cells to regulate autophagy. These results provide new insights into the future exploration of spermidine-induced autophagy to exert anti-oxidation and thus protect mammalian ovarian function. However, the specific mechanism of the screened key functional proteins needs further verification. ## 4. Conclusions Our current findings suggest that spermidine regulates the activity of antioxidant enzymes and the expression level of autophagy proteins, and autophagy activated by spermidine plays an antioxidant role in preventing follicular atresia. Using proteomics, we found that it is mainly involved in steroid hormone production, oxidative stress, lipid metabolism, autophagy and apoptosis, and the main proteins are Nr5a1, XDH, P53, LDLR, TXNIP, Bok and Bid. In summary, spermidine protects ovarian function by reducing the number of atresia follicles and regulating the level of autophagy protein, antioxidant enzyme activity, and polyamine metabolism in mice. ## 5.1. Experimental Animals and Sample Collection Seven-week-old healthy female ICR mice (SPF-grade experimental mice purchased from Chengdu Da Shuo Laboratory Animal Co., Ltd., Chengdu, China) were selected and kept in separate cages, and the mice were fed ad libitum. The mice were randomly divided into a control group (normal drinking water) and a spermidine group (3 mmol ·L−1 spermidine solution instead of drinking water), with 20 mice in each group. During the feeding process, the water intake, cleaning of the drinking water bottle, and replacement of the drinking water were recorded every three days, and the animals were weighed and recorded every 15 days. After 3 months, the reproductive cycle was identified by the vaginal smear method, and mice in oestrus were selected. The mice were killed by cervical dislocation, and the bilateral ovaries were quickly collected, washed with $0.9\%$ normal saline, dried with filter paper, and placed on an electronic balance. Some of the ovarian tissue samples were fixed with $4\%$ paraformaldehyde for HE staining, some were sequenced by proteomics, and the rest were stored in a −80 °C freezer for later use. This experiment was completed in the College of Animal Science and Technology, Sichuan Agricultural University. All feeding and killing requirements were in line with the animal operation code of Sichuan Agricultural University and approved by the Welfare Administration Committee (DKY-B2019202011). ## 5.2. Main Reagents and Kits Putrescine standard, spermidine standard, spermine standard and 1,6-hexanediamine were purchased from Sigma (St. Louis, MO, USA); Protein Maker, ECL chromogenic solution and PVDF membrane were purchased from BIO-RAD Biological Company; PBS, PMSF, RIPA, primary antibody diluent and secondary antibody diluent were purchased from Beyotime Co., Ltd. (Haimen, China); chromatographic methanol was purchased from Bio-Rad Yu (Fisher Scientific, Waltham, MA, USA); SYBR Green Supermix was purchased from TaKaRa (Kusatsu, Japan); PMSG was purchased from Ningbo Sunshine Biological (Wuxi, China); perchloric acid, sodium hydroxide, concentrated hydrochloric acid, benzoyl chloride, anhydrous ethanol and all other reagents were analytically pure and purchased from Ruijinte (Chengdu, China). ## 5.3. Analysis Software The proteins obtained by liquid chromatography-mass spectrometry were analyzed by means of bioinformatics. The tools and websites used for the analysis are shown in Table 2. ## 5.4. Morphological Detection of Ovarian Tissue The ovarian tissue was fixed in $4\%$ paraformaldehyde for 24 h, after which the tissue was removed, dehydrated in a series of alcohols with different concentrations, embedded in paraffin, and sectioned. Next, hematoxylin-eosin staining was performed. The slides were sealed with neutral gum and dried in an oven at 37 °C. The changes in the tissue morphology of the ovary, the size of the follicles, and the granulosa layer of the follicles were observed under an optical microscope, and the follicles of different grades were counted. ## 5.5. Immunohistochemical Detection of Autophagy-Related Proteins in Ovarian Tissue First, the tissue was embedded and sectioned, the sections were dewaxed and then stained, and the sections were infiltrated with $3\%$ methanol and hydrogen peroxide for 9 min, washed three times with PBS, and immersed in 0.01 mol/L citrate buffer (PH 6.0). After heating for 5 min, the slices were allowed to cool completely, and then the slices were washed 2–3 times with PBS. At room temperature, goat serum blocking solution was used to block the slices for 20 min. The primary antibody was diluted according to the antibody instructions, added dropwise to the slice, and incubated at 4 °C overnight. The secondary antibody was incubated at 37 °C for 30 min. The slices were washed three times with PBS for 4 min each time. After DAB color development at room temperature, the slices were placed under a microscope, and the reaction was observed and rinsed with distilled water after approximately 2–3 min. Counterstain was performed, followed by dehydration and xylene clearing. Finally, the sections were mounted with neutral gum. The sections were observed microscopically, and images were acquired for subsequent analysis. ## 5.6. Antioxidant Index and Lipid Peroxidation Levels Detection An appropriate amount of ovarian tissue sample was added to prepare the solution. Then, a hand-held electric homogenizer was used to homogenize the samples on ice, and the supernatant was collected as the sample to be tested. The protein concentration was determined with a BCA protein concentration kit for quality control for subsequent detection. The working solution was prepared according to the instructions of the kit, the sample was diluted, the 96-well plate was gently shaken to fully mix the solution, the plate was incubated in an incubator at 37 °C, and the absorbance of the sample was detected at 450 nm. The enzyme activity was calculated according to the instructions of the kit {CAT (Beyotime, S0082, Shanghai, China), SOD (Beyotime, S0101S, Shanghai, China), GSH-Px (Beyotime, S0056, Shanghai, China), total antioxidant capacity (T-Ait isOC, Beyotime, S0119, Shanghai, China) and MDA (Beyotime, S0131S, Shanghai, China)}. ## 5.7. Determination of Polyamine Content in Mouse Ovarian Tissue by High-Performance Liquid Chromatography Approximately 0.1 g of mice ovary tissue was added to an internal standard and 1 mL $5\%$ HClO4 grinding sample and placed on ice for subsequent detection. Vortex vibration and ultrasonic crushing were performed for 10 min, followed by centrifugation and supernatant extraction, which was repeated 1–2 times. Aliquots of 2 mL 2.5 mol/L NaOH and 7 μL benzoyl chloride were added to the above homogenate solution, vortexed and mixed, then derivation was performed in a water bath without light, with the derivatization solution adjusted to pH 7.0 with 6 mol/L HCl. The samples were activated with chromatographic methanol and ultrapure water in advance, and the polyamines were completely filtered and separated, washed with 15 mL double distilled water and 15 mL $15\%$ chromatographic methanol, and dried. Then, 0.5 mL chromatographic methanol was used to elute the components to be tested. A 0.22 μm filter was used to filter the prepared sample solution, and the filtered sample solution was detected by HPLC. The detection conditions were as follows: the mobile phase was methanol: water (62:38, v/v), the detection wavelength of the UV detector was 229 nm, and the column temperature was 25 °C. The peak time and peak area of three polyamines and internal standard in each sample were obtained by liquid chromatography, and the concentration of each polyamine was calculated according to the standard curve. ## 5.8. Real-Time Fluorescence Quantitative PCR Detection After grinding the ovarian tissue with liquid nitrogen, total RNA was extracted according to the instructions of the RNAiso Plus kit (TaKaRa, 9109, Dalian, China), according to the instructions of the reverse transcription kit (TaKaRa, RR047A), and the total RNA sample was reverse transcribed into a cDNA template. Primer information is as follows (Table 3. The mixed system {TB Green Premix EX Taq II(TaKaRa, RR820A, Dalian, China) 5.0 μL; PCR upstream primer, 0.2 μL; PCR downstream primer, 0.2 μL; cDNA 0.5 μL; dd H2O, 4.1 μL}. The reaction conditions were as follows: pre-denaturation at 95 °C for 3 min; 39 cycles of denaturation at 95 °C for 10 s, annealing at 57–63 °C for 30 s, and extension at 72 °C for 30 s (fluorescence collection); holding at 95 °C for 10 s. The β-actin gene was used as an internal reference gene. Three repetitions were performed for each sample, and 2−ΔΔ was used to calculate the relative expression of mRNA by the Ct method. ## 5.9. Western Blot Detection of Protein Expression After the ovarian tissue was ground with liquid nitrogen, $0.1\%$ protease inhibitor (PMSF) and protein lysis buffer (PIPA) were added and centrifuged at 4 °C at 12,000 r/min for 10 min, and the protein of the sample was detected according to the BCA protein concentration detection kit (Beyotime, P0009) after concentration and denaturation. After preliminary separation by SDS-PAGE, the proteins were transferred to PVDF membranes for sealing, followed by 4 °C, overnight incubation of primary antibody {1:1000, rabbit polyclonal antibody CYP17A1 (Abcam, ab125022, Cambridge, UK), HSD3B2 (Abcam, ab191515, UK), p62/SQSTM1 (CST, 23214S, US), LC3B (Sigma, L7543-100UL, US), rabbit monoclonal antibody Beclin 1 (Abcam, ab207612, UK), mouse monoclonal antibody GAPDH (Trans Gen Bio, HC301, Beijing, China) and rabbit monoclonal antibody β- Tubulin (ABclonal, A12289, Wuhan, China)}. The membrane was incubated with secondary antibody {1:1000, goat anti-rabbit secondary antibody (Beyotime, A0208), goat anti-mouse secondary antibody (Beyotime, A0216)} for 60 min at 37 °C. An ECL reagent kit was used for color development, exposed with an AI 600 imager, and analyzed with image analysis software (ImageJ 1.8.0.112, Bethesda, MD, USA). ## 5.10. Protein Extraction and Consistency Test of Repeated Samples After the mice were fed with 3 mmol·L−1 spermidine drinking water for three months, ovarian tissue was collected. The samples were ground in liquid nitrogen, lysis buffer (inhibitor) was added, each group of samples was lysed by ultrasonication, and the supernatant was collected after centrifugation. SDS-PAGE was used for quality control. The Pearson correlation coefficient (Pearson) was used to measure the degree of linear correlation between the two groups of data; the relative standard deviation (RSD) was used to calculate the ratio of the standard deviation to the arithmetic mean of the measurement results, which reflected the degree of dispersion of the data; the principal component analysis (PCA) method extracts the key components in the sample data to effectively distinguish the samples, intuitively reflects the relationship between the samples, and assesses the consistency and repeatability of samples. ## 5.11. Liquid Chromatography-Mass Spectrometry (LC-MS) Analysis After dissolution with liquid chromatography mobile phase A ((v/v) formic acid in water), the Nano Elute ultrahigh-performance liquid system was used for separation. The peptides were separated by an ultrahigh-performance liquid phase system, injected into the capillary ion source for ionization, and then analyzed by a tims-TOF Pro mass spectrometer. ## 5.12. Database Search and Bioinformatics Analysis MS/MS data were retrieved using Max Quant (v. 1.6.6.0). The nonstandard quantitative calculation method was used to calculate the nonlabeled quantitative intensity of protein in each sample, and the relative quantitative value of each sample was obtained. The average value was obtained, and the final differential expression amount was calculated. Differential proteins were screened based on the p-value and differential expression of the original data, and GO annotation was used to classify the differential proteins according to cellular components, molecular functions or physiological processes. At the same time, the protein pathways were annotated using the KEGG annotation tool KASS, and the KEGG mapper matched the differentially expressed proteins to the corresponding KEGG pathways in the database. ## 5.13. Differential Protein Screening The relative quantitative value of each sample was taken as log 2 (to make the data conform to the normal distribution), and the p-value was calculated by t-test. When p ≤ 0.05, a fold change (FC) change >1.2 was used as the threshold for significant upregulation. FC < 0.67 was taken as the threshold for significant downregulation. Fisher’s exact paired-end test was used to detect the enrichment of DEPs for all identified proteins, and p ≤ 0.05 was considered statistically significant. 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--- title: Measurement of Complex Permittivity for Rapid Detection of Liquid Concentration Using a Reusable Octagon-Shaped Resonator Sensor authors: - Chun-He Quan - Xiao-Yu Zhang - Jong-Chul Lee journal: Micromachines year: 2023 pmcid: PMC10051991 doi: 10.3390/mi14030542 license: CC BY 4.0 --- # Measurement of Complex Permittivity for Rapid Detection of Liquid Concentration Using a Reusable Octagon-Shaped Resonator Sensor ## Abstract Substrate-integrated waveguides (SIWs) are widely used in microwave systems owing to their low cost and ease of integration. In this study, an SIW-based resonator that reacts to the complex permittivity variation of solutions with dimensions of 79.2 mm × 59.8 mm is introduced. This octagon-shaped sensor can be installed on a preliminary monitoring system to test water quality by observing the parameter variations caused by external factors. The resonant structure was used to test different concentrations of ethanol–water and acetone–water mixtures for verification. The resonant frequency and quality factor (Q-factor) were found to vary with the relative complex permittivity of the liquid in the S-band, and the electric field distribution varied when liquid droplets were placed in the center of the substrate. The designed sensor operates at 2.45 GHz in the air, and the observed minimum resonant frequency shift with liquid was 15 MHz. The measurement error was approximately $3.1\%$, and the results reveal a relationship between the resonant frequency and temperature as well. Considering the observed sources of error, the measured relative permittivity is consistent with the actual values. The proposed sensor is economically convenient and suitable for various test environments. ## 1. Introduction A sensor is a subsystem, machine, or module used to identify targets or detect changes in environmental variables. With advances in their small size and simple operation, sensors are extensively being applied in electronic and electrical devices. Among the multiple types of sensors available, permittivity sensors are among the most widely used. As a function of state, which depends on the magnitude, frequency, temperature, and many other factors, the permittivity of a material must be accurately measured because it plays a key role in technological fields, including chemistry, physics, and biomedicine. For example, strong buildings can withstand unexpected natural disasters, but an incorrect mixing ratio of compounds may cause a building to collapse. In addition, the robustness of structures can be judged by measuring the relative permittivity of building material samples to ensure quality. In automobiles, long-term non-destructive monitoring of engines helps extend their service life [1,2,3,4]. In microwave applications, permittivity is considered a basic parameter that carries critical information, such as the robustness and electrical energy capacity of a material. Several traditional methods have been used to determine the permittivity of materials. The open-ended coaxial probe method is practical for determining permittivity when a target is difficult to reach in its natural environment. The free-space method is realized by simultaneously measuring the phase and amplitude of the transmission wave while changing the length of the material under test (MUT) to calculate its permittivity. Moreover, many other enhanced methods of testing permittivity exist, such as the two-port transmission line method and the phase sensing method [5,6,7,8,9]. Measuring devices are preferred for testing MUTs because they are portable and provide high-precision measurements. Traditional testing waveguides or transmission lines are generally bulky and expensive; therefore, the feasibility of an enhanced chipless radio frequency identification permittivity sensor that works within the industrial scientific medical (ISM) band was suggested [10]. Time-domain reflectometry is applied as the operating method, with several antennas connected to the reader and tag. However, most sensors are specifically designed to measure gases or solids. Moreover, measurement is difficult because of the complicated sensor structure. As a result, substrate-integrated waveguide (SIW) technology has been applied in filter and sensor designs in recent years to check water quality. The resonator must be immersed in a large amount of liquid or filled with samples using a micro-capillary to characterize a material accurately [11]. Microfluidic technology has recently emerged as a solution to the wastefulness of specimens [12]. However, this type of sensor is difficult to apply in industrial production. An octagon-shaped sensor, which has a simple design and is easy to fabricate, was proposed in this study to address these issues. The eight sides of the octagon constituting the sensor are close to the center slot, enabling variable changes to be observed clearly due to its compact size. An SIW-based structure was introduced to measure the relative complex permittivity of a liquid. The characteristics of the resonant frequency and quality factor (Q-factor) are influenced by the MUT through a rectangular slot on the top metal plane. The operating frequency was set between 2.40–2.49 GHz. Various concentrations of mixtures were prepared, with the sensor tested three times at room temperature for accuracy. This sensor can be installed in various home devices owing to its simple structure and compact size. The rest of this article is organized as follows: Section 2 presents the design of the SIW sensor and the process of planning an experiment to test the relative complex permittivity of liquids. Section 3 describes the measurement results of binary mixtures of ethanol–water and acetone–water. Finally, discussions and conclusions are given in Section 4 and Section 5. ## 2. Materials and Methods As key devices in radiofrequency (RF) technology research, waveguides are used to guide waves and reduce losses during propagation. Various structures with easy fabrication and high performance have been used in microwave engineering. An SIW structure prototype was first proposed in the late 20th century. After years of improvement, the SIW is considered a new standard type of waveguide with low radiation loss. The structure is composed of arrayed metallic holes connecting the upper and lower metal layers on a low-loss dielectric substrate that can be connected to circuits and various active and passive microwave devices on the same dielectric substrate. As a result, SIWs are widely used in RF systems and antenna arrays owing to their advantages of low cost and ease of integration. SIWs can be fabricated using printed circuit boards, low-temperature co-fired ceramics, and other manufacturing processes [13]. An SIW resonator with a planar structure was used to measure liquid permittivity. The sidewalls of classical waveguides are composed of metal as an ideal electrical wall, although the gap between vias in an SIW leads to slight radiation loss. However, impedance matching can be improved when the gap between the conductor and ground is sufficiently small for a certain feed length. The transmission characteristics of SIWs are identical to those of classical waveguides. As essential parameters of the waveguide, the lengths of the wide and narrow sides directly affect the working frequency and cut-off frequency of the waveguide. An effective width ae can be derived by applying waveguide theory to an SIW. The cut-off frequency of the SIW is associated with the width of the waveguide and the distance between the two via rows. The radiation loss of the SIW can be reasonably small if s/d < 2.5, with s/$d = 2$ recommended for the design, where d is the diameter of a via and s is the distance between two successive vias. Additionally, a relatively high mechanical strength was obtained using the SIW structure with relatively easy fabrication [14]. As shown in Figure 1, a SIW resonator with propagating modes of TE101 and TE102 was proposed, with a coplanar waveguide (CPW) slot inserted between the vias of the SIW working as the feedline. Coupling effects occurred between the TE mode propagating in the SIW and the TEM mode propagating in the CPW when power was transmitted in the resonator cavity. Various types of cavities with surrounding fences can be designed using the SIW structure, with electric and magnetic field distributions identical to those in a rectangular waveguide. However, only the TEm0p mode can exist in the SIW resonator as the electrical current cannot propagate between vias, unlike in the classical waveguide resonator. The resonant frequency f of the TEm0p mode, primarily affected by the length a and width w of the SIW cavity, can be derived as follows [11]: where ae and we denote the equivalent length and width of the SIW cavity, respectively; m and p denote the mode numbers; εr denotes the substrate relative permittivity; and c denotes the speed of light in free space. The resonator is used in various RF devices, such as filters, oscillators, and amplifiers. The principle of microwave resonators is identical to that of resonators with an equivalent model comprising an RLC parallel resonant circuit. The value of the Q-factor may be affected by the losses in the SIW, including dielectric loss in the substrate, ohmic loss in the metal, the radiation loss caused by the slot, and the internal resistance of external measuring devices such as a network analyzer. The Q-factor, as a dimensionless parameter, describes the underdamping of a resonator or oscillator. The Q-factor is proportional to the sum of the average electric and magnetic energies stored in the resonator and inversely proportional to the cavity loss. The unloaded Q-factor Qu can be calculated using [4]Qu=ε”ε’+1Qc−1 where Qc is the Q-factor of the resonator with a lossless dielectric and ε’ and ε” denote the real and imaginary parts of the substrate, respectively [16]. [ 5]Qc=(kaw)3bηo2π2Rm12p2a3b+2bw3+p2a3w+aw3 [6]Rm=πfμ0/σ Generally, the thickness of a rectangular waveguide cavity resonator is much larger than that of an SIW resonator. Qc decreases with decreasing thickness of the resonator. Qc of the TE10p mode can be determined by [5] when the surface resistance Rm of the metal wall is defined by [6], where k denotes the wave number, σ denotes the conductivity, and η0 = μ0/ε0 = 377 Ω denotes the impedance of free space [15]. The proposed transition structure of the CPW line was introduced between the feed line and the SIW cavity. As the characteristics of the central part of the SIW sensor varied most prominently, a compact octagon-shaped structure was used to keep all sensor parts close to the center and make the feed line and slot lie in a straight line. The resonant frequency and Q-factor of the SIW resonator were primarily determined by the relative permittivity of the substrate. A Taconic TLX-8 series board with a dielectric constant, loss tangent, and thickness of 2.55, 0.0018, and 1.016 mm, respectively, was used for fabrication. The substrate was composed of multilayer glass fibers [17]. The dimensions of the designed SIW resonator were optimized by the simulation tool ANSYS High-Frequency Structure Simulator (HFSS) 2021 R1 using radiation boundary condition with the number of mesh more than 100 thousand as shown in Figure 2a, which significantly reduced the cavity volume. The eigenmode solver was also employed to calculate the resonance mode at the S-band to suppress unwanted modes in the waveguide. The dimensions were Sc = 2 mm, Dc = 0.8 mm, W1 = 59.8 mm, L1 = 79.2 mm, Sd = 1.2 mm, Wf = 3 mm, Lf = 25 mm, and Sf = 1 mm. The electric field distribution of the designed feedline at the resonant frequency was calculated using a three-dimensional model drawn from the HFSS, as depicted in Figure 2b. The designed feeding structure could excite the TE101 mode without affecting the proximity of the original cavity. Generally, a deviation of 0.1 in the real part of the relative permittivity of the substrate results in a 50–150 MHz resonance frequency shift. An Agilent 8719ES network analyzer, with a step of 10 kHz and a frequency range between 50 MHz–13.5 GHz, was used to measure the SIW resonator. Qu and the resonant frequencies of the SIW resonators f0 were derived from the measured S-parameter. As depicted in Figure 3, the measured and simulated results show a good agreement with a resonant frequency of approximately 2.45 GHz. The fractional bandwidth of $1.1\%$ with the return loss better than −10 dB in the ISM band was obtained. According to the cavity perturbation theory, either a small deformation of the cavity or the introduction of foreign objects will affect cavity performance. Generally, electromagnetic wave attenuation occurs in a planar resonance cavity when a high-loss dielectric material and sensor are in direct contact. The sensor can be partially immersed in a liquid; however, the amount of liquid used for each measurement will vary. Therefore, a quarter-wavelength slot was created at the top plane, where the distribution of the electric field changes rapidly [18]. The performance of this model was stable because only a small area of the sensor with an open structure was in contact with the liquid. As depicted in Figure 4, a narrow slot with a length of 11.8 mm and width of 2.9 mm was fabricated on the sensor. The slot was surrounded by a short plastic hollow tube to prevent liquid spills when conducting the experiments. The solutions were completed with a measuring cylinder and beaker, and a clean pipette tube was used to transfer equal amounts of liquids. The S-parameters tested by the network analyzer vary with the concentration of the mixture because the equivalent complex permittivity of the resonant cavity was affected by the liquid in the slot [19]. A reference temperature of 25 °C was selected and kept constant, considering that the temperature affected the test results. The resonant characteristics of the SIW resonator with deionized water at 30, 25, and 20 °C are listed in Table 1, which shows that fo and Qu vary slightly with temperature. An effective method of reducing errors in volume and measurement results involves multiple measurements of the average values. A binary mixed solution of ethanol and water was first selected as the test sample because of its low cost and non-toxicity. The structural and diffusion properties of the mixed solutions have been studied for industrial applications. The mixed solution forms hydrogen bonds, resulting in variations in the physical and chemical properties with different ratios of solutions; therefore, further study on the properties of mixed solutions is necessary. A total of 21 test samples were prepared with a mole fraction of ethanol between 0–$100\%$. The volumes of the mixture constituents are expressed in moles because the volume of the solution may change after mixing due to intermolecular spaces. Water (H2O) and ethanol (CH3CH2OH) were used to prepare the mixture proportioning in $5\%$ intervals after purification and distillation [20]. The capacities of the measuring cylinder, beaker, and pipette tube should not be too large, considering that the liquid used in a single test is generally no more than 1 mL. Every piece of equipment was cleaned after being used to test a sample, and the response time for each sample did not exceed 15 s. A model that reflects the relationship between the sensor parameters and the permittivity can be used to obtain the exact value of the complex permittivity of a liquid. An approximate machine-learning model that reflects the relationship between the SIW sensor parameters and relative permittivity was built using Python because it integrates well with open-source libraries. The Python Data Analysis Library was used as an accurate and flexible data manipulation tool to first analyze the data. Next, a decision-tree-based method—extreme gradient boosting—was adopted [21]. This method was selected to deal with distributed problems, microwave theoretical analysis, and calculations owing to its advantages of high-speed dynamic response and memory ability. The learning procedure started by inputting a set of tabulating data consisting of fo and Qu extracted from the simulated results, and stopped when the relationship between the calculated relative permittivity and the simulated values of the resonant frequency and Q-factor was mapped [13]. The real and imaginary parts of the relative complex permittivity could be computed by entering the values of the measured fo and Qu after establishing a two-input, two-output model. ## 3. Results The test results for Qu and fo with different mole fractions of ethanol are shown in Figure 5. The solid and dashed lines represent measured and actual values, respectively. The values vary significantly when the ethanol concentration is over $80\%$; the value of Qu decreases, whereas that of fo increases with increasing ethanol concentration. The ethanol concentration can be estimated using [7], which can be employed for predictive analysis when sophisticated instruments are not available and the difference between the predicted and actual concentrations is no more than $10\%$ [22]. The average percentage error between the theoretical and measured data can be calculated using [8]. [ 7]Ethanol concentration=(−3.4×Qu+304)% [8]Δ=∑$i = 1$mεM−εAεAm×$100\%$ where εM and εA denote the measured and actual values of the relative complex permittivity, respectively, and m denotes the number of solution samples [23]. The percent error of the real part is $2.4\%$ and that of the imaginary part is $2.5\%$ when compared to the values in [24,25]. Figure 6 depicts the results of another test performed on an acetone–water mixture using the same method to verify the accuracy and sensitivity of the sensor. These values vary more minimally than those in the previous experiment because the permittivities of ethanol and acetone are different. The green line represents the variation in acetone concentration with respect to Qu or f0, and the red and blue colors represent the real and imaginary parts of the relative complex permittivity with respect to Qu and f0. The relative error of the real part is $2.5\%$ and that of the imaginary part is $3.1\%$ when compared with the values in [26]. Qu changes by approximately 0.1 for every $1\%$ change in the concentration of the acetone. The desired results were achieved for ethanol and acetone detection with a relatively stable measurement error. The measured results indicate that the designed SIW sensor can respond quickly to the permittivity variation of the mixed solutions, indicating that the complex permittivity of a liquid with complex components can be measured. The designed sensor can be used to measure unknown liquids using the relationship between Qu and fo of the SIW resonator and the relative complex permittivity. ## 4. Discussion The principles of measuring complex permittivity based on the SIW sensor are described in this article. As shown in Figure 7, the basic characteristics of the SIW were analyzed first in this study before introducing the working principle and Q-factor of the resonant cavity. The simulation results were used to optimize the dimensions. Finally, two different kinds of mixed solutions were tested, with the complex permittivities of the liquid mixtures derived using HFSS and Python. The SIW sensor was tested in air and liquid, with the corresponding calculations performed in a stepwise manner. As the relative permittivity of the gases is approximately 1, the influence of air is negligible. As a reusable and washable sensor, the designed SIW sensor can sensitively detect the output values and identify the liquid concentration. A relationship was derived to convert the measured data into the relative complex permittivity of the MUT. The sensor was validated based on an unloaded test to remove incorrect values, with the tests repeated thrice to determine average values [27,28]. Ethanol–water and acetone–water mixtures were selected to observe the changes in permittivity. Compared with other sensors used for sensing liquids in Table 2, the designed sensor in this work achieves good performance as well as a compact physical size of 79.2 mm × 59.8 mm, equivalent to the electrical size of 0.65λ0 × 0.49λ0, where λ0 denotes the wavelength in the free space at the operating frequency, with a planar SIW structure. The designed SIW resonator could work well in S-band with a sharp band edge. Measurement errors are primarily caused by the manufacturing process and test environment [29]. Additionally, a permittivity sensor can be used to measure the liquid permittivity in the L- or C-band by changing the size of the sensor [30,31]. ## 5. Conclusions With advances in efficiency and intelligent control, sensor applications have expanded beyond the traditional fields of pressure, temperature, and humidity. Scientists have developed a few real-time sensors to check the state of devices or areas of concern [36]. Considering the distribution of the electric field and temperature frequently change in the center slot of the substrate where the liquid is placed, an octagon-shaped sensor was designed in this study to measure the permittivity and observe its variation. The selected working frequency of the sensor is easy to control because it consists of only a one-port component [37,38]. The measured results show the relationships between the permittivity and parameters of the SIW sensor (tested at 25 °C). The influence of air humidity can be ignored because the sensor is partly immersed in the liquid, with the relative permittivity and permeability of the gas close to 1. SIW sensor performance was tested, and its applicability to liquids was verified. As non-invasive and contactless sensors, liquids can be tested efficiently and safely. Technological progress has enabled more accurate sensors to be manufactured and applied more conveniently with more features. The use of sensing devices, including smart home sensors, increased rapidly with the advent of the global “trillion sensor” era [39]. Refrigerators, boilers, air conditioners, and laundry machines constitute a large percentage of the home appliance market share. The Coronavirus Disease 2019 (COVID-19) outbreak is currently restraining activities in the electrical industry due to supply chain disruption, and a decline in purchasing power and the adoption of smart home appliances and electric vehicles among consumers will further hinder global market growth. 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--- title: Malnutrition and Insulin Resistance May Interact with Metabolic Syndrome in Prevalent Hemodialysis Patients authors: - Shuzo Kobayashi - Yasuhiro Mochida - Kunihiro Ishioka - Machiko Oka - Kyoko Maesato - Hidekazu Moriya - Sumi Hidaka - Takayasu Ohtake journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10051997 doi: 10.3390/jcm12062239 license: CC BY 4.0 --- # Malnutrition and Insulin Resistance May Interact with Metabolic Syndrome in Prevalent Hemodialysis Patients ## Abstract Background: We sought to determine the prevalence of metabolic syndrome (Mets) and whether 100 cm2 of visceral fatty area (VFA) measured by computed tomography (CT) validates the criteria of waist circumference (WC) in hemodialysis (HD) patients. Methods: The study comprised 141 HD patients. Mets was defined according to the criteria of Adult Treatment Panel III (ATP III) and the modified criteria of National Cholesterol Education Program (NCEP) that defines abdominal obesity as a WC of >=85 cm in men and >=90 cm in women. Results: The prevalence of Mets was $31.9\%$ in men and $13.6\%$ in women. However, the prevalence of patients with a body mass index over 25 in all HD patients was only $11.2\%$. The visceral fatty area (VFA) measured by CT showed a strong positive correlation with WC. The patients with Mets, comparing with those without Mets, have significantly shorter duration of HD, higher high-sensitive C-reactive protein, and higher Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). In the patients with Mets, there was a significant negative correlation between HOMA-IR and serum albumin levels. Multivariate logistic regression analysis showed that HOMA-IR and short duration of HD were chosen as independent risk factors for Mets. Conclusions: Mets is more prevalent in HD patients. In Japanese HD patients, 100 cm2 of VFA corresponded to a WC of 85 cm in men and 90 cm in women, thus confirming the validity of the modified criteria. HOMA-IR and serum albumin were significantly correlated in HD patients with Mets. ## 1. Introduction In patients on hemodialysis (HD), malnutrition and its related inflammation are known to cause atherosclerosis (malnutrition, inflammation, atherosclerotic syndrome; MIA syndrome) [1], thus leading to cardiovascular disease (CVD). Likewise, metabolic syndrome (Mets), characterized by abdominal obesity, hypertriglyceridemia, low high-density lipoprotein (HDL) cholesterol level, high blood pressure, and high fasting glucose level [2], is also known to be a major leading cause of CVD in the general population [3]. Mets has been associated with an increased risk for diabetes mellitus and CVD, as well as increased CVD and all-cause mortality [3,4,5]. Chen et al. reported that Mets is prevalent and might be an important factor in the cause of chronic kidney disease (CKD) [6]. In Japan, Mets is a significant determinant of CKD in men under 60 years of age [7]. Besides the fact that Mets is one of the risk factors in CKD, it is important to note that we need to know the prevalence of Mets and its associated factors in maintenance HD patients because malnutrition develops with longer HD duration. In this regard, little information is available, although at the initiation of renal replacement therapy (RRT), there is a report showing that Mets is highly prevalent in incident dialysis patients [8]. Unfortunately, body mass index (BMI) is used instead of the criteria of waist circumferences (WC), and no data on fasting blood are available in that report. Moreover, information on associated factors is not provided. The pathogenesis of Mets and the relationship between Mets and CVD lie in insulin resistance [9]. Insulin resistance is known to develop at an early stage of non-diabetic CKD [10]. We reported a similar result using a hyperinsulinemic euglycemic glucose clamp method and also showed that acidemia and dyslipidemia are independently associated with insulin resistance in CKD [11]. Although RRT improves insulin resistance [12], insulin resistance is still occasionally found in maintenance HD patients [13]. However, it remains unknown concerning the relationship between Mets and insulin resistance in hemodialysis patients. Therefore, in the present study using fasting blood samples, we first assessed the prevalence of Mets in maintenance HD patients according to the criteria of the Adult Treatment Panel III (ATP III) [2] using modified criteria of WC. We studied the associated factors including insulin resistance expressed by the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) [14]. Finally, using computer tomography (CT) [15], we confirmed whether or not visceral fat area (VFA) greater than 100 cm2 corresponds to a WC of 85 cm in men and 90 cm in women, respectively. ## 2.1. Study Design and the Subjects The present study was cross-sectional observational study conducted in our hospital. The protocol was approved by the Tokushukai Group Institutional Review Board (TGE1897-024) and adhered to the tenets of Declaration of Helsinki. The potential subjects comprised 162 patients who were on maintenance HD therapy in dialysis center in our hospital in December 2005. The end date of patient recruitment was 31 December 2005. Patients aged 20 years old or more were enrolled, and there was no upper restriction in age for study entry. Patients with insulin treatment were essentially excluded in this study. Data were collected from maintenance HD patients in December 2005 unless they had acute illness (9 patients) or post-operative conditions (4 patients) within 3 months prior to this study. The patients within 3 months of the initiation of HD (8 patients) were also excluded. The patients visited to our hospital for a 1-day annual check of complications. The study comprised 141 HD patients (97 men, 44 women). These patients recruited in the present study corresponded to $90\%$ ($\frac{141}{162}$ patients) of all patients in our hospital and had been treated by regular dialysis for more than 3 months. ## 2.2. Blood Sampling, WC, and VFA Blood was drawn in the morning after an overnight fast of at least 12 h on non-dialysis day in the middle of week. EDTA-plasma was used for glucose, insulin, and lipids, and serum for other biochemical assays. Glucose was measured by a glucose oxidase method. Insulin was measured by radioimmunoassay (Insulin RIA-BEAD II: Dinabot Co., Tokyo, Japan). Total cholesterol (TC) and triglycerides (TG) were measured enzymatically. HDL cholesterol was measured after precipitating apolipoprotein B-containing lipoproteins with dextran sulfate and magnesium chloride. High-sensitive C-reactive protein (hsCRP) was measured using a nephelometric immunoassay. WCs of the patients were also measured at a standing position. Finally, 92 patients in men and 20 patients in women who agreed to undergo CT examination received CT examination for measuring VFA, respectively. ## 2.3. Assessment of Insulin Resistance Using HOMA-IR Insulin resistance was assessed using HOMA-IR originally described by Mathew et al. [ 14]. HOMA-IR was calculated using the following formula: HOMA-IR = fasting glucose (mmol/L) × fasting insulin (μU/mL)/22.5. ## 2.4. BMI and Measurement of VFA Using CT BMI was calculated as the weight in kilograms divided by the height in meters squared. The amount of abdominal and visceral fat deposition was assessed by CT. The area of the subcutaneous fat and visceral fat was measured in a single cross-sectional scan at the level of the umbilicus. An image histogram was computed for the subcutaneous fat layers in order to determine the range of CT numbers for the fat tissue. The total fat area was then calculated by counting the pixels that had intensities within the selected range of CT numbers. The intraperitoneal space was defined by tracing its contour on the scan image. The total area with the same CT numbers was considered to represent VFA [15]. ## 2.5. Mets Criteria The ATP III [2] report defines Mets as a constellation of risk factors of metabolic origin including increased abdominal obesity, high triglyceride, low HDL cholesterol, elevated blood pressure, and elevated fasting blood glucose. Elevated blood pressure was defined as systolic or diastolic blood pressure of $\frac{130}{85}$ mmHg or higher; low HDL cholesterol level was defined as less than 40 mg/dL; high serum TG levels were defined as 150 mg/dL or more; and elevated fasting glucose level was defined as 110 mg/dL or more. Finally, WC of 85 cm or more in men and 90 cm or more in women was defined as abdominal obesity in Japan as modified NCEP criteria [7]. ## 2.6. Measurement of Blood Pressure Blood pressure (BP) was measured with a standard mercury sphygmomanometer and cuffs adapted to arm circumferences after the patients had rested in the supine position for at least 5 min prior to HD on the first HD session of a week. Hypertension was also defined as the use of one or more antihypertensive drugs. ## 2.7. Statistical Analysis Continuous variables were expressed as mean ± standard deviation (SD) when normally distributed or as median (interquartile range [IQR]) when non-normally distributed. Skewed variables underwent log transformation before statistical analysis. The prevalence of Mets and its individual components (elevated BP level, high plasma glucose level, high triglyceride level, low HDL cholesterol level, and abdominal obesity), as well as the number of Mets components (0, 1, 2, 3, 4, or 5), was determined for the overall study sample. Univariate or multivariate logistic regression analysis was also applied for the determinants of Mets. A p-value of less than 0.05 was considered statistically significant. These were analyzed using statistical software (StatView 5; SAS Institute Inc., Carry, NC, USA) for Windows personal computer. ## 3. Results The mean age was 67 years, with a range of 34–89 years. Table 1 summarizes the baseline characteristics of the subjects. Body weight, body height, rate of current smoker, rate of diabetes mellitus, TC, and HDL-C were significantly different between men and women, as shown in Table 1. The prevalence of Mets was $31.9\%$ in men, $13.6\%$ in women, and $26.2\%$ in total according to the modified criteria of NCEP using a definition of a WC of 85 cm or more in men and 90 cm or more in women. The prevalence of HD patients with each Mets component in men and women was shown in Table 2. The prevalence of a WC of 85 cm or more in men and 90 cm or more in women was $53.6\%$ and $25\%$, respectively. The number of Mets components present in men was $3.8\%$ with no Mets risk factors, $36.5\%$ with one, $44.2\%$ with two, $7.7\%$ with three, and $7.7\%$ with four. The number of Mets components present in women was $0\%$ in no Mets risk factors, $45.4\%$ with one, $54.5\%$ with two, and $0\%$ with three and/or four. The VFA measured by CT showed a strong positive correlation with WC in both men (R2 = 0.390, $p \leq 0.0001$) and women (R2 = 0.472, $p \leq 0.0001$) as shown in Figure 1. In Japanese HD patients, 100 cm2 of VFA corresponded to a WC of 85 cm in men and 90 cm in women, thus confirming the validity of the modified criteria. HOMA-IR showed a skewed distribution with a median of 0.922, and $20\%$ of the patients had the value greater than 2.0 of HOMA-IR. The patients with Mets, comparing with those without Mets, had significantly greater WC, shorter duration of HD, greater BMI, higher hsCRP, higher HOMA-IR, higher FBS, and higher TG, as shown in Table 3. In patients undergoing HD for more than 10 years, the prevalence of Mets became $10\%$ (3 patients/30 patients) (data not shown). In all patients, a significant negative correlation between serum albumin and hsCRP (R2 = 0.101, $p \leq 0.001$), and a negative weak correlation between the duration of HD and HOMA-IR (R2 = 0.032, $p \leq 0.05$) were found [Figure 2]. On the contrary, the prevalence of serum albumin levels less than 3.7 g/dL was $45.2\%$ in men and $70.5\%$ in women, respectively. The prevalence of the patients with BMI less than 18.5 was $17.5\%$ in men, and $27.3\%$ in women, respectively. The prevalence of patients with a BMI greater than 25 in all HD patients was only $11.2\%$. Regarding the correlation between HOMA-IR and serum albumin levels, there was a significant negative correlation only in patients with Mets (R2 = 0.349, $p \leq 0.001$), while in patients without Mets, there was no significant correlation (R2 < 0.001, $$p \leq 0.957$$) (Figure 3). In a study of univariate regression analysis associated with HOMA-IR, only serum albumin level was chosen as a significant determinant [Table 4] in patients with Mets, while other parameters, including age, HD duration, WC, BMI, hsCRP, TC, TG, and HDL cholesterol, did not show any significant correlation. The results of multivariate logistic regression analysis on the determinants of Mets, when factors other than the modified NCEP criteria were entered, demonstrated that HOMA-IR, as well as short duration of HD, BMI, and sex (men vs. women), were chosen as independent risk factors [Table 5]. ## 4. Discussions Mets is known as a cause of end-stage renal disease (ESRD) and CVD. It is reasonable to find high prevalence of Mets in HD patients [16,17]. However, the results are of interest due to the potentially conflicting nature of malnutrition and Mets in dialysis patients. In HD patients, whether Mets-related risk factors depend on visceral adiposity or uremia per se remains unknown. Although the present study does not provide a clear answer for this, we demonstrated that Mets was more prevalent in HD patients as well as in non-dialysis general populations, despite the prevalence of patients with a BMI over than 25 being only $11.2\%$. Mets tends to become less prevalent with the duration of HD. In patients with Mets, however, the higher the degree of malnutrition developing, the greater the proportion of patients who have insulin resistance with inflammation. Therefore, abdominal obesity may also play an important role in atherosclerosis as well as malnutrition in HD patients. In contrast to the general population, obesity is associated with improved survival [18] and decreased hospitalization rate [18] among patients with ESRD. In addition, the association between obesity and improved prognosis remained significant even after adjustment for serum albumin [18]. It may be hypothesized that a higher level of adiposity may provide a survival advantage for patients with ESRD. Regarding the report on the prevalence of Mets in HD patients, Young et al. showed that Mets is highly prevalent in incident dialysis [8]. However, the patients were studied at the initiation of dialysis therapy in contrast to our report dealing with maintenance HD patients. Moreover, fasting blood samples were not used for evaluating each metabolic component and BMI was used instead of WC. In this regard, our study is the first report showing the precise prevalence of Mets in maintenance HD patients. There are accumulating data that (visceral) abdominal obesity and attendant risk factors are associated with increased risk for CVD [16,19]. In a prospective study (Quebec Cardiovascular Study) in which more than 2000 middle-aged men were followed over 5 years, two clinical characteristics associated with visceral obesity were the strongest independent risk factors for ischemic heart disease: fasting hyperinsulinemia and increased apolipoprotein B concentrations [20]. Abdominal obesity is often accompanied by insulin resistance and hyperinsulinemia [9]. This hyperinsulinemia may, in turn, contribute to increased CVD and stroke. Insulin resistance in HD patients has been reported to be an independent predictor of CVD and mortality [13]. In the present study, the distribution of HOMA-IR was similar to that report [13], which means that insulin resistance still remains after the initiation of RRT. However, it appears that the prevalence of insulin resistance becomes less with the duration of HD. Serum albumin level itself was not a determinant of Mets in HD patients. However, there was a significant correlation between serum albumin levels and insulin resistance in patients with Mets, whereas the association was not seen in patients without Mets. Therefore, the significance of serum albumin is thought not to be a determinant of Mets, but rather an important component in the pathophysiology of Mets in HD patients. In the patients with Mets, hypoalbuminemia is associated with increased HOMA-IR. Comparing patients without Mets, the patients with Mets have significantly higher hsCRP levels. Therefore, in prevalent HD patients, insulin resistance may play an important role for atherosclerosis through the interaction between malnutrition and inflammation. In patients with Mets, the higher the degree of malnutrition developing, the greater the proportion of patients who have insulin resistance with inflammation. In this regard, it is reported that TNF-α could play a role in the development of insulin resistance in humans, both in muscle and in vascular tissue [21]. Sustained low-grade inflammation could be one factor that explains why CKD and CVD often develop simultaneously. It is well known that insulin resistance is associated with endothelial dysfunction [22], which underlies atherosclerotic CVD. HOMA-IR showed a negative correlation with HD duration in our study. However, because it was a weak correlation, the result should be interpreted with caution. Further study might be necessary to confirm the relationship between HOMA-IR and HD duration. Mets has been exposed to vigorous critique [23], while others are arguing that Mets is of great value [24]. Moreover, a role of Mets remains unclear in maintenance HD patients. Our study may provide a clue to consider Mets as well as malnutrition and its related atherosclerosis through insulin resistance. There are several limitations to the current study. The present study is a cross-sectional and observational study in a single hospital. However, we do not want to obtain any causality between Mets and cardiovascular events. Second, we evaluated Mets according to the modified NCEP criteria, because in Japan these criteria were authorized by the Japanese Society of Internal Medicine in 2005 by changing the definition of WC. Tanaka and Iseki et al. have already reported the relationship between the Mets and CKD [7] using these modified criteria. The relationship between NCEP criteria and modified criteria is well documented in their report. Indeed, the prevalence of Mets was $12.4\%$ when NCEP criteria was used, while the prevalence increased up to $21.2\%$ when modified criteria was used with a similar rate reported in the USA [6]. The discrepancy might be related to the difference in the prevalence and degree of obesity between the two countries [25]. Evaluation of nutritional status including prealbumin, muscle consumption, upper arm muscle circumference, and comprehensive score was not evaluated in this study. Therefore, full assessment of nutritional status was not performed. However, the objective of the present study was to reveal a relationship between malnutrition and atherosclerosis in terms of metabolic syndrome, which is known to be an independent risk factor for cardiovascular disorders. In order to discuss this issue, we focused on serum albumin levels being an important nutritional factor. It is no doubt that serum albumin, although affected by inflammation, plays an important role as one of many nutritional markers. Future study is necessary to clarify the association between nutritional status by precise nutritional assessment and Mets in patients undergoing HD. Finally, regarding a difference between % of males versus females in the present study, in an overview of regular dialysis treatment in Japan as of 31 December 2009 reported by the Japanese Society for Dialysis Therapy, there are, in Japan, 173,391 men versus 106,722 women in regular dialysis treatment, a ratio (Men/Women) of 1.72, which clearly shows a predominance of men over women, with a similarity to our study (men 97/women 44). Despite the limitations described above, we believe that the data obtained from this study provide evidence of an important issue considering nutritional status and abdominal obesity in maintenance HD patients. 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--- title: Apocynin Ameliorates Monosodium Glutamate Induced Testis Damage by Impaired Blood-Testis Barrier and Oxidative Stress Parameters authors: - Merve Acikel-Elmas - Salva Asma Algilani - Begum Sahin - Ozlem Bingol Ozakpinar - Mert Gecim - Kutay Koroglu - Serap Arbak journal: Life year: 2023 pmcid: PMC10052003 doi: 10.3390/life13030822 license: CC BY 4.0 --- # Apocynin Ameliorates Monosodium Glutamate Induced Testis Damage by Impaired Blood-Testis Barrier and Oxidative Stress Parameters ## Abstract Background: the aim of this study was to investigate the effects of apocynin (APO) on hormone levels, the blood-testis barrier, and oxidative biomarkers in monosodium glutamate (MSG) induced testicular degeneration. Methods: Sprague Dawley male rats (150–200 g; $$n = 32$$) were randomly distributed into four groups: control, APO, MSG, and MSG + APO. MSG and MSG + APO groups were administered MSG (120 mg/kg) for 28 days. Moreover, the APO and MSG + APO groups received APO (25 mg/kg) during the last five days of the experiment. All administrations were via oral gavage. Finally, biochemical analyses were performed based on the determination of testosterone, follicle-stimulating hormone (FSH), luteinizing hormone (LH), malondialdehyde (MDA), glutathione (GSH), and superoxide dismutase (SOD), as well as light and transmission electron microscopic examinations, assessment of sperm parameters, ZO-1, occludin, NOX-2, and TUNEL immunohistochemistry were evaluated. Results: MSG increased both the oxidative stress level and apoptosis, decreased cell proliferation, and caused degeneration in testis morphology including in the blood-testis barrier. Administration of apocynin reversed all the deteriorated morphological and biochemical parameters in the MSG + APO group. Conclusions: apocynin is considered to prevent testicular degeneration by maintaining the integrity of the blood-testis barrier with balanced hormone and oxidant/antioxidant levels. ## 1. Introduction The widely used L-glutamic acid, as an additive, occurs naturally in a variety of foods and is the source of the flavor enhancer, monosodium glutamate (MSG) [1]. Many processed foods contain MSG as an additive, with an average daily intake in European industrialized nations as 0.3 to 1.0 g. [2]. Even though MSG consumption is considered safe by food safety organizations, it is still questioned in several preclinical and clinical studies, especially its long-term exposure. Among the physiological functions of glutamate is its neurotransmitter property in the central nervous system, as a precursor of metabolites such as glutathione [1]. Long-term consumption of MSG has been shown to have negative effects on the male reproductive system. Studies have shown that long-term consumption of MSG decreases sperm count in males and affects the morphological structure of sperm and the testes [3]. The majority of the research cited previously focused primarily on the toxicity of MSG in rats at doses of 2000–8000 mg/kg body weight, which is extremely unlikely for humans at this level [4]. Allometric conversion by Shin et al. [ 5] showed this dose to be equivalent to 120 mg/kg body weight in rats. There are a significant number of glutamate receptors in the reproductive organs and sperm, making them susceptible to excitation damage from excess glutamate in the body. This makes the reproductive system a frequent target for glutamate-induced damage. In addition, glutamate toxicity is known to directly damage the hypothalamic–pituitary–gonadal axis, leading to a homeostatic imbalance in reproduction [6]. MSG has resulted in oxidative damage (increased lipid peroxidation and decreased antioxidant enzyme activities) and spermatogenic changes manifested by low sperm count and morphological abnormalities [3]. Therefore, we studied the effects of oral consumption of MSG on rats when they ingested a moderate dose extrapolated directly from the daily intake in humans. This MSG dose effect on rat testicular morphology was also observed in experimental studies [3,7]. The overproduction of reactive oxygen species (ROS) triggers oxidative stress and apoptosis. Due to their reactive structures, free radicals can interact with lipids, nucleic acids, and proteins and have harmful effects on the body [8]. Oxidative stress, induced by ROS, is known to play an important role in male infertility [9]. Studies have shown that NADPH oxidase (NOX) is one of the main sources of ROS [10]. Excessive ROS and oxidative stress in the male reproductive system cause negative changes in sperm concentration, motility, and morphology. Degenerated sperm and impaired semen parameters lead to infertility [11]. ROS causes male infertility due to DNA damage in the sperm [12]. Oxidative stress compromises the integrity of the plasma membrane of sperm and induces early capacitation. As a result, the fertilizing ability of sperm decreases and infertility occurs [13]. Apocynin (APO), extracted from the roots of the plant Apocynum cannabinum, is known to be effective as an inhibitor of NOX [14]. The anti-inflammatory effect of APO has been demonstrated in many experimental studies [15]. NOX activation occurs through the migration of cytosolic components to the cell membrane [16,17]. APO acts as a selective inhibitor of ROS production by acting on NOX activity in active human neutrophils. However, APO does not affect phagocytosis or other mechanisms of intracellular death [18,19]. NOX isoforms are expressed in various cells and have different physiological functions. NOX-2 is an isoform of NOX, which is present in eosinophils, macrophages, and neutrophils [20]. The spermatogenic cells are connected to each other and the Sertoli cells. This dynamic relationship is regulated by tight junctions and gap junctions [21]. The tight junctions between the Sertoli cells are important for the formation and function of the blood-testis barrier (BTB). The structure of the BTB includes tight junctions, desmosomes, basal ectoplasmic specializations, and gap junctions. Tight junctions of epithelial origin are multimolecular membrane specializations that contain multiple integral membrane proteins such as zonula occludens-1 (ZO-1) and occludin [21]. Occludins are one of the molecules contributing to the formation of tight junctions. Zonula occludens proteins such as zonula occludens-1 (ZO-1), ZO-2, and ZO-3 are important proteins involved in this structure. Occludin, ZO-1, and ZO-3 interact with the actin cytoskeleton. The protein ZO-3 is associated with the cytoplasmic domains of ZO-1 and occludin [22]. Oxidative stress occurs when there are not enough antioxidants against free radicals. A decrease in the activity of antioxidant enzymes such as superoxide dismutase (SOD) and glutathione (GSH) levels leads to an increase in oxidative damage [23]. Malondialdehyde (MDA), a parameter of cell membrane damage, indicates the density of oxygen radical attack in reactive cells and free radical metabolism in vivo. Decreased SOD and increased MDA trigger oxidative stress and cause cell damage, resulting in cell death [24]. Studies indicated NOX-2 as the source of ROS [20,25]. APO, a potent NOX-2 inhibitor [26], could be effective in the inhibition of NOX-2 to prevent tissue damage due to the oxidative stress. The administration of APO could have a curative effect on oxidative stress parameters and histopathological damage. The aim of this study was to evaluate the effects of MSG on testicular tissue damage, cell proliferation, apoptosis, and oxidative stress indicated by the expression of NOX-2 and on the blood-testicular barrier. In addition, the study aimed to investigate whether apocynin can improve the effects on all these parameters. ## 2.1. Experimental Design This experimental study was approved by the Ethics Committee of Acibadem Mehmet Ali Aydinlar University Experimental Animals (ACU-HADYEK, Approval number: HDK-$\frac{2020}{39}$). In this study, 8-week-old Sprague Dawley male albino rats ($$n = 32$$) were kept in cages with a temperature of 22 ± 2 °C and a standard light/dark (12:12 h) cycle. Rats were fed with standard animal food ad libitum for the 28 days of the experimental period. This research was conducted in accordance with the guidelines and regulations of ARRIVE (Animal Research: Reporting of In Vivo Experiments). In this study, Sprague Dawley male rats ($$n = 8$$ in each group) were randomly divided into 4 groups as control, APO, MSG, and MSG + APO. Distilled water (1 mL) was given to the control group of rats by oral gavage for 28 days. The MSG and MSG + APO groups were administered 120 mg/kg MSG by oral gavage for 28 consecutive days [4]. The APO and the MSG + APO groups were administered 25 mg/kg APO by oral gavage on the last 5 days of the experiment [27]. The weights of the rats in the experimental groups were analyzed weekly. After isoflurane anesthesia, the rats were sacrificed. Blood samples, as well as testicular and epididymis tissue samples, were used for biochemical and microscopical evaluations. ## 2.2. Measurement of Serum Testosterone, FSH, and LH Concentrations Serum testosterone, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) concentrations were measured by using enzyme-linked immunosorbent assay (ELISA) kits. Rat testosterone (Catalog no: EA0023Ra, ELISA kit Bioassay Technology Laboratory), Rat FSH (Catalog no: EA0015Ra, Bioassay Technology Laboratory, Shanghai, China), and Rat LH ELISA (Catalog no: EA0013Ra, Bioassay Technology Laboratory) kits were used for hormone levels analysis according to the kit procedure. Testosterone results were given as nmol/L and FSH and LH were given as mIU/L. ## 2.3. Measurement of Testicular MDA, GSH, and SOD Levels MDA levels were determined using a commercial kit (E-BC-K025-M, Elabscience, Houston, TX, USA). MDA, one of the degradation products of lipid peroxidation, reacts with Thiobarbituric acid (TBA) to form a pink complex with an absorption maximum of 532 nm. The MDA levels in the tissue were calculated in nmol/g. GSH analysis in testicular tissue was performed according to the Beutler method [28]. The principle of the method is based on the fact that GSH in the analysis tube reacts with 5,5′-dithiobis-2-nitrobenzoic acid (DTNB) to give a yellowish color. The light intensity of this color was read in the spectrophotometer at a wavelength of 410 nm. The tissue homogenates were centrifuged, and a $10\%$ TCA solution was added to the obtained supernatant, mixed, and centrifuged again to precipitate the proteins. The brightly colored supernatants were used for GSH analysis. The intensity of the color formed in the samples kept at room temperature for 5 min was read at 410 nm in the spectrophotometer, and the GSH levels in µmol/g in the tissue were determined using the glutathione standard curve. SOD activity was determined using the Sigma SOD Determination Kit (E-BC-K019-M, Elabscience, Houston, TX, USA). Absorbance values were read at 450 nm after incubating SOD activity with an enzyme-working solution. The SOD levels in the tissue were calculated in IU/g. ## 2.4. Sperm Count, Motility, and Morphology Epididymal tissue samples from rats were placed in an Earle’s Balanced Salts solution with a Hepes buffer solution and processed for analysis of sperm count, motility, and morphology based on a previous study [27]. Briefly, epididymis tissue samples of rats were transferred into an Earle’s Balanced Salts solution with Hepes buffer solution added to them following dissection. A routine density gradient method was used to evaluate the spermatozoa. The supernatant was removed, and the pellet was diluted with a spermatozoa washing medium (SAGE, Newcastle upon Tyne, UK) and centrifuged. Then the pellet was diluted with a sperm preparation medium (SAGE, UK). The 10 μm pellet was used to count spermatozoa in a Macler counting chamber (Sefi cut out Medical Instruments, Haifa, Israel) with a photomicroscope to count them. For morphological evaluation, smears were prepared and then stained using the Diff-Quick kit (Medion Diagnostics, Grafelfing, Munich, Germany). In each slide, 100 spermatozoa were examined at 100× magnification with a photomicroscope (Zeiss A1 Axio Scope, Oberkochen, Germany) to evaluate the sperm morphology. ## 2.5. Tissue Processing for Light Microscopy Testicular tissues were fixed with the Bouin solution for routine histological examinations. For immunohistochemical examinations, testicular tissues were fixed with a $4\%$ paraformaldehyde (PFA) solution. Following fixation, the tissues underwent routine a paraffin embedding procedure [29]. Haematoxylin and eosin (H&E) stain was applied to the sections for routine histological evaluation. Periodic acid-Schiff (PAS) reaction was applied to reveal the structure of the basal membranes of seminiferous tubules. Seminiferous tubules in H&E-stained testicular sections were scored on the basis of modified Johnsen’s histopathological scoring parameters [30,31]. In addition, the epithelial thicknesses of 100 seminiferous tubules were measured in all sections using Image J (Image J software, National Institutes of Health) program. ## 2.6. Terminal Deoxynucleotidyl Transferase dUTP Nick End Labelling (TUNEL) Immunochemistry The terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) method was applied to testicular tissue sections according to the kit‘s instruction manual given by the manufacturer (ApopTag Plus, In Situ Apoptosis Detection Kit, S7101, Merck Millipore, Darmstadt, Germany). In brief, after deparaffinization and rehydration, the sections were washed in PBS and then heated in a microwave oven in citrate buffer. After cooling, proteinase K (20 μg/mL) was dripped onto the tissue sections. The sections were washed in distilled water and soaked in a $3\%$ hydrogen peroxide-prepared solution. After washing in PBS, a 10 μL stabilizing tampon was placed on the sections for 30 min at room temperature. Then, 10 μL Tdt enzyme was dripped, and sections were incubated for 1 h at 37 °C. The stop-wash buffer was dripped for 10 min at room temperature. After washing with PBS, 13 μL of anti-digoxigenin was dripped onto the sections. After incubating at room temperature for 30 min, sections were washed 4 times for 2 min in PBS. Then, 13 μL 3,3’-Diaminobenzidine (DAB) solution was dripped. Then, the sections were shaken with distilled water. For contrast staining, the sections were soaked in Mayer hematoxylene solution (J.T Baker, Center Valley, PA, USA). After washing in distilled water sections were mounted with entallan. Sections were imaged with a light microscope (Zeiss A1 Axio Scope, Oberkochen, Germany). The apoptotic index was estimated by dividing the total number of testicular tubules by the number of seminiferous tubules with 3 or more TUNEL-positive cells [32]. ## 2.7. Proliferating Cell Nuclear Antigen (PCNA) Immunohistochemistry Sections were subjected to PCNA immunohistochemistry to determine the number of proliferative cells and the proliferation index. After deparaffinization and rehydration, the sections were processed for PCNA immunohistochemistry as described in a previous study [32]. In brief, the sections were stored in a $3\%$ hydrogen peroxide solution (Sigma-Aldrich, St. Louis, MO, USA) for 20 min. The sections were heated in a microwave oven at 200 W in ethylenediaminetetraacetic acid (EDTA) buffer (Sigma-Aldrich, USA) for 20 min. After washing with PBS 3 times, the sections were soaked in a $5\%$ goat serum-blocking solution (Invitrogen, Waltham, MA, USA) for 10 min. Then, the primary rabbit anti-PCNA antibody (Catalog no: SY12-07, Novus Biologicals, Littleton, CO, USA) (1:50) was applied. Sections were kept in a humidified chamber at 4 °C overnight and washed 3 times with PBS for 5 min each time. Biotin-labelled goat anti-rabbit secondary antibody (Catalog no: A16100, Invitrogen, Waltham, MA, USA) (1:500) was dropped onto the sections and kept at 37 °C for 30 min. Streptavidin peroxidase (Invitrogen, Waltham, MA, USA) was instilled into the sections and left for 10 min. After washing 3 times with PBS, the sections were soaked in 3,3′-diaminobenzidine (DAB) chromogen (1 mL DAB substrate + 30 μL DAB chromogen) for 5 min. After washing with distilled water, the sections were stained with Mayer’s hematoxylin solution for contrast staining. The sections were then mounted with Kaiser’s glycerol gelatin (Catalog no: 1.09242, Sigma-Aldrich, Darmstadt, Germany). The sections were examined under a light microscope (A1 Axio Scope, Oberkochen, Zeiss, Germany). To determine the proliferation index, the number of PCNA-positive cells in 20 tubules in each section was divided by the total number of cells [32]. ## 2.8. Immunohistochemistry of ZO-1 and Occludin The $4\%$ PFA-fixed tissue sections were deparaffinized and rehydrated with alcohol solutions. Sections were then soaked in a $3\%$ hydrogen peroxide solution (Sigma-Aldrich, St. Louis, MO, USA) for 20 min to block endogenous enzymes. After washing with PBS, the sections were heated in a microwave at 200 W in an EDTA buffer (Sigma-Aldrich, St. Louis, MO, USA). The sections were cooled for 30 min at room temperature and stored 3 times for 5 min each in PBS followed by 10 min in $10\%$ buffered goat serum (Invitrogen, USA). The sections were treated with rabbit anti-ZO-1 (Catalog no: 61-7300, Invitrogen, Waltham, MA, USA) and rabbit antioccludin (1:100) (Catalog no: 71-1500, Invitrogen, Waltham, MA, USA) antibodies (overnight, at +4 °C). After washing 3 times in PBS for 5 min, a biotin-labelled antirabbit secondary antibody (Catalog no: 65-6140, Invitrogen, Waltham, MA, USA) (1:1000) was dropped onto the sections. After soaking in PBS 3 times and 5 min, streptavidin-peroxidase (Invitrogen, Waltham, MA, USA) was applied to the sections. After washing in PBS, AEC Single/Plus Chromogen (Abcam, Cambridge, UK) was dropped on, and sections were shaken with distilled water and mounted with Kaiser’s glycerol gelatin (Catalog no: 1.09242, Sigma-Aldrich, Darmstadt, Germany). Sections were imaged using a light microscope (A1 Axio Scope, Oberkochen, Zeiss, Germany). The intensity of immunoreactivity of both ZO-1 and occludin was calculated using the Image J program (1.44 software, National Institutes of Health). ## 2.9. ZO-1, Occludin and NOX-2 Immunofluorescence Analysis The sections were kept in $3\%$ hydrogen peroxide and washed with PBS. Then, sections were incubated with rabbit anti-ZO-1(1:100) ZO-1(Catalog no: 61-7300, Invitrogen, Waltham, MA, USA), rabbit antioccludin (1:100) (Catalog no: 71-1500, Invitrogen, USA), and rabbit anti-NOX-2 primary antibodies (1:100) (Catalog no: NBP2-41291, Novus, Bio-Techne, Minnesota, USA). Slides were washed with PBS and then incubated with AF 488 (Catalog no: ab150077, Abcam, USA) labeled goat antirabbit secondary antibody (1:1000). After the sections were washed with PBS for the last time, they were mounted with a 4′6-diamino-2-phenylidol (DAPI) solution (Catalog No: ab104139, Abcam, Boston, MA, USA). The sections were imaged with a fluorescence microscope (Zeiss Axio Scope. A1 microscope with fluorescence attachment Zeiss AxioCam MRc 5 camera). The fluorescence intensity in the photographed sections was calculated using Image J (Image J software, National Institutes of Health) program. ## 2.10. Tissue Processing for Transmission Electron Microscopy Testis tissue samples were fixed with buffered $2.5\%$ glutaraldehyde solution (in 0.1 M PBS, pH 7.2) and processed for routine transmission electron microscopical preparation according to the previously published protocol [32]. Sections were analyzed under transmission electron microscope (TALOS L 120 C, Thermo Scientific Fisher, Eindhoven, The Netherlands). ## 2.11. Statistical Analysis Data were analysed with one-way ANOVA and Tukey’s multiple comparison tests with $p \leq 0.05$ considered significant. Statistical analysis was performed using Graph Pad Prism 8.0 (San Diego, CA, USA). ## 3.1. Serum Testosterone, FSH, and LH Levels Testosterone levels in the MSG group were lower compared to the control group. Although the MSG + APO group showed an increase in testosterone levels compared to the MSG group, this increase was not statistically significant (Figure 1A). The FSH level was higher in the MSG group compared to the control group. The FSH level in the MSG + APO group was decreased compared to the MSG group (Figure 1B). Decreased levels of LH in the MSG group and increased levels of LH in the MSG + APO group were not statistically significant compared to the experimental groups (Figure 1C). ## 3.2. Testicular MDA, GSH, and SOD Levels The tissue MDA level was increased in the MSG group compared to the control group. On the other hand, when comparing the MSG + APO group with the MSG group, a significant decrease in MDA was observed (Figure 1D). GSH and SOD levels were decreased significantly in the MSG group when compared with the control and APO groups, respectively. A significant increase in GSH and SOD levels was revealed in the MSG + APO group compared with the MSG group (Figure 1E,F). ## 3.3. Sperm Count, Motility, and Morphology Normal morphology was observed in sperm samples in the control group and APO groups (Figure 2A,B). A large number of spermatozoa with morphological abnormalities were observed in the MSG group (Figure 2C). In the MSG + APO group, few abnormal sperm were detected, as a majority of sperms were of normal morphology (Figure 2D). The sperm count and motility were lower in the MSG group compared to the control and APO groups. Those parameters were increased significantly in the MSG + APO group compared to the MSG group (Figure 2E,F). ## 3.4. Testicular Weight/Body Weight Ratio Although the testicular weight/body weight ratio of the MSG group was observed to be lower compared to the other experimental groups, this decrease was not statistically significant. There was no statistical difference in the testicular weight/body weight ratio between the experimental groups (Figure 3E). ## 3.5. Histopathological Results Light microscopical examination of testicular tissue by H&E staining revealed normal morphology of the seminiferous tubules in the control group. ( Figure 3(A1)). Intact testicular morphology was observed in the APO group (Figure 3(B1)). In the MSG group, the germinal epithelia of the seminiferous tubules were disorganized. Vacuoles indicating prominent tissue damage were detected in the basal compartment of the seminiferous tubules (Figure 3(C1)). Those morphological disturbances were reflected in a significantly high histopathological score for this group. In the MSG + APO group, the majority of seminiferous tubules reflected the normal morphology, with a limited number of degenerated seminiferous tubules (Figure 3(D1)). Compared with the MSG group, the histopathological score was significantly low in the control and APO groups. The histopathological score significantly increased in the MSG group and was significantly decreased in the MSG + APO group, compared to the MSG group (Figure 3F). In addition, the thickness of the seminiferous tubules in the MSG group was low compared to the other experimental groups. In the MSG + APO group, there was a significant increase in tubule thickness compared to the MSG group (Figure 3G). The control and APO groups presented a strong PAS-positivity (Figure 3(A2,B2)) for the basement membranes of seminiferous tubules with regular morphology. Deteriorated basement membranes of seminiferous tubules of MSG resulted in a decreased PAS-positivity of sections. ( Figure 3(C2)). PAS-positivity of the MSG + APO group was nearly equivalent to the control group, with a small number of disturbed seminiferous tubules presenting detached basement membranes (Figure 3(D2)). The morphologies of testicular tubules and tunica albuginea were normal in the control group (Figure 3(A3)), APO group (Figure 3(B3)), and MSG + APO group (Figure 3(D3)). However, in the MSG group (Figure 3(C3)), fat tissue was observed in the tunica albuginea, and the morphology of the tubular stroma was also normal. ## 3.6. Results for PCNA A large number of PCNA-positive cells in the seminiferous epithelium, as dark brown, were observed in the control and APO groups (Figure 4(A1,B1)). In the MSG group, a decrease in the number of PCNA-positive cells of the seminiferous epithelium was noticed (Figure 4(C1)). Also, PCNA-positive spermatogenic cells in the lumen of seminiferous tubules are seen in the MSG group. The proliferation index, lowest in the MSG group, was increased in the MSG + APO group compared to the MSG group (Figure 4E). The MSG + APO group also showed an increase in PCNA-positive cells in the seminiferous epithelium (Figure 4(D1)). ## 3.7. Results for TUNEL Immunocytochemistry In the control and APO groups, TUNEL-positive cells were low (Figure 4(A2,B2)). The number of TUNEL-positive cells was higher in the MSG group than in the other experimental groups (Figure 4(C2)). TUNEL-positive cells were fewer in the MSG + APO group than in the MSG group (Figure 4(D2)). The apoptotic index was higher in the MSG group than in the other experimental groups. There was a comparative decrease in this index in the MSG + APO group (Figure 4F). ## 3.8. Results for NOX-2 Immunofluorescence Weak NOX-2 immunopositivity was observed in the control (Figure 5A–C) and APO groups (Figure 5D–F). The highest immunoreactivity was observed in the MSG group (Figure 5G–I), whereas a decrease was detected in the MSG + APO group (Figure 5J–L). Negative controls of the NOX-2 immunofluorescence analysis were shown in Figure S1 ## 3.9. Results for ZO-1 and Occludin Immunohistochemistry ZO-1 and occludin positivities were detected as a dark red color in the basolateral cytoplasm of Sertoli cells located in the seminiferous tubule of the germinal epithelium. While the intensities of ZO-1 and occludin immunoreactivity were highest in the control group (Figure 6A–C, Figure 7A–C, Figure 8(A1,A2) and Figure 9A,B) and APO group (Figure 6D–F, Figure 7D–F and Figure 8(B1,B2)) and a decrease in the distribution of immunoreactivities was observed in the MSG group (Figure 6G–I, Figure 7G–I and Figure 8(C1,C2)). Increases in ZO-1 and occludin positivities were observed in the MSG+APO group, compared to the MSG group (Figure 6J–L, Figure 7J–L and Figure 8(D1,D2)). ## 3.10. Transmission Electron Microscopical Results In the control and APO groups, normal ultrastructure of seminiferous tubular germinal epithelium presenting numerous spermatozoa, and Sertoli cells interconnected with tight junctions were observed (Figure 10A). The APO group had a similar ultrastructure as with the control group (Figure 10B). In the MSG group, vacuolization and lipid droplets in the germinal epithelial cells of the seminiferous tubule, separations between the Sertoli–Sertoli cell junctions and deteriorated basal lamina of the seminiferous tubules were observed (Figure 10C). The ultrastructure of the MSG + APO group reflected the normal organization of seminiferous tubules with few lipid droplets in the cytoplasm (Figure 10D). ## 4. Discussion In this study, the healing effect of APO on MSG-induced testicular damage has been evaluated by biochemical, microscopical, and immunohistochemical parameters. Testosterone and LH levels decreased and FSH levels increased, oxidative stress parameters such as MDA level increased, while GSH and SOD levels decreased in the MSG group. In MSG-induced testicular injury, the histopathological score and the number of damaged seminiferous tubules and spermatozoa were increased. The proliferative index was low and the apoptotic index was higher in the MSG group. The germinal epithelium of the seminiferous tubules was decreased in thickness. Those degenerative changes have been reversed by the administration of APO. The MSG group depicted a decrease in the distribution of ZO-1 and occluding as tight junction proteins of the blood-testis barrier. MSG affected the oxidative stress markers. In this group, there was an increase in the distribution of the protein NOX-2, which was involved in the synthesis of ROS. Ultrastructure examinations of the MSG group indicated prominent damage in the cytoplasm of seminiferous tubule germinal epithelial cells of the seminiferous tubules with separated tight junctions. Biochemical, histological, immunohistochemical, and ultrastructural analyses showed that these parameters improved with APO treatment in the MSG + APO group. Experimental studies have shown that oral ingestion of MSG can be toxic to reproduction; however, due to the high doses used in the studies, the toxic effects on the reproductive system due to consumption of MSG were unlikely to translate to human consumption [33,34] The human ingested daily dose of MSG is thought to be between 1200 and 3000 mg/kg [35]. In this study, the dose of 120 mg/kg body weight of MSG was used for experimental design, based on an allometric extrapolation of the average daily intake of this substance in humans [5]. The hypothalamic–pituitary–gonadal (HPG) axis plays a key role in processes related to the development and maturation of the male reproductive system. FSH is a factor in the maintenance of intragonadal testosterone synthesis and spermatogenesis. LH plays a role in the development of the male genital system and the process of sex determination by stimulating Leydig cells [36]. The stimulation causes Leydig cells to secrete the necessary levels of testosterone. The proper testosterone level is controlled by GnRH activity through a negative feedback mechanism [36]. With this mechanism, the HPG axis functions in a controlled manner [37,38]. In some population-based studies, sex hormones have been shown to affect sperm morphology, concentration, and motility. In a study of subfertile couples, an inverse relationship was found between LH and sperm motility and morphology [39]. In clinical studies, FSH levels were found to correlate negatively with sperm concentration [40]. In other experimental studies, following the administration of MSG, a decrease in sperm motility, concentration, and LH hormone levels was revealed. Studies have also shown that MSG causes a decrease in testosterone hormone levels and sperm concentrations [34,41]. In our present study, FSH, LH, and testosterone levels in the APO group were similar to the control group. A statistically significant decrease in testosterone hormone was observed in the MSG group. A significant increase in FSH hormone levels was observed in the MSG group. In the MSG + APO group, the FSH level was lower than in the group MSG. Although a decrease in LH hormone was observed in the MSG group, there was no statistical difference in LH hormone between the experimental groups. MSG could do damage to Leydig cells for testosterone secretion. Decreased testosterone and LH levels are also associated with sperm count. Thus, low testosterone and LH levels could be related to decreased sperm count and abnormal sperm morphology [42]. In contrast, an elevated FSH level indicates that there is a disturbance in spermatogenesis causing altered FSH signaling. MSG has been shown that it may cause a disturbance in hormonal pathways in the hypothalamus [4]. As a result of our study, it was observed that administration of MSG interfered with the HPG axis by affecting FSH, LH, and testosterone levels, as well as testicular and sperm morphology, sperm concentration, and motility. Administration of apocynin reduced the impaired testosterone, FSH, and LH levels to near normal levels and this improvement in hormone levels also affected the morphological parameters. SOD is an important enzyme that protects cells from damage caused by internal and external superoxide ions [43]. MDA is an aldehyde formed by free radicals during lipid peroxidation and is an indicator of both cell membrane damage and the severity of the effect of oxygen radicals on reactive cells. A decrease in SOD and an increase in MDA can trigger oxidative stress, leading to cell damage and cell death [24]. GSH is involved in the reduction of ROS such as hydrogen peroxide in the cell [44]. NOX is a source of ROS and apocynin is known as a NOX inhibitor [45]. In studies of MSG-induced testicular injury, MDA levels in testicular tissue increased and SOD levels decreased when MSG was administered [4,46]. In another study, ingestion of MSG was also shown to decrease GSH levels in testicular tissue [4]. In a study in which apocynin was used as a healing agent, it was shown that apocynin reduced MDA levels, which were increased due to tissue damage and caused an increase in GSH and SOD levels in the testicular damage group [27]. In another experimental study of the hypoxia-induced testicular degeneration model, NOX-2 activation and MDA levels were increased and GSH levels were decreased due to the effect of hypoxia. However, testicular tissue damage was shown to be reduced by the application of APO [47]. Our present study concluded an increase in MDA levels with a decrease in GSH and SOD levels in the MSG group. We could suggest that APO improved these parameters in the MSG + APO group through NOX-2 inhibition. Some preclinical studies have revealed the toxic effects of MSG on many organ systems, such as the liver, kidneys, and reproductive system [3]. An experimental study states that MSG can cause infertility due to its harmful effect on the ovaries and oocytes [48]. The toxic effect of MSG on the testes with an imbalance of sex hormones has been noted [34]. In a similar study, the levels of oxidative stress markers were increased in the testicular tissues of rats administered MSG, and testicular morphology and sperm morphology were also negatively affected by MSG [41]. It has been observed that MSG leads to a degeneration in testicular morphology with a negative effect on testosterone [4,49]. In testicular injury models, a decrease in the thickness of the seminiferous tubule germinal epithelium was demonstrated [50,51]. In an MSG-induced testicular injury model the thickness of the seminiferous tubule epithelium was decreased [52]. In our study, the thickness of the seminiferous tubular germinal epithelium of the MSG group was decreased compared to the other experimental groups. There was an increase in the germinal epithelial thickness of the MSG + APO group compared to the MSG group. MSG is stated to lead to obesity, as an appetizer [53]. There are question marks about whether MSG consumption can be a risk factor in the rapid increase in epidemic obesity. In an open-cohort study among Chinese adults, it was shown that those who used MSG had a higher body mass index compared with those who did not use MSG [54]. In other experimental studies, it has been observed that the weight of MSG-given rats increased and made them prone to obesity [55,56]. However, in our study, there was no statistically significant difference in body weight between the experimental groups, weighted every week during the experiment. In a related study where MSG has been administrated to rats, a decrease was observed in testicular weights in the MSG group compared to the control group [4,52]. However, testicular weight/body-weight ratios of our current study, indicated a decrease in the MSG group compared to other experimental groups, as statistically insignificant. In studies examining the effects of MSG on sperm concentrations, MSG was found to cause a decrease in sperm viability [4,49,52]. In another testicular damage model, the curative effect of apocynin on sperm parameters was examined, and an increase in sperm concentration was observed in the apocynin healing group compared to the damage group [27]. In our study, when comparing sperm counts between experimental groups, it was found that the sperm count was lowest in the MSG group, while the sperm count in the MSG + APO group was statistically higher than in the MSG group. It is stated that the use of apocynin is safe in animal studies. In addition, APO has potent antioxidant and anti-inflammatory effects in many experimental models [57]. Experimental testicular injury models reported the effect of apocynin on the reduction of oxidative stress [58,59]. In chemotherapy-based experimental studies, the healing effect of apocynin was also highlighted on testes tissue. In these studies, it was observed that apocynin leads to a decrease in the number of apoptotic cells and an increase in testosterone levels [27,60]. As one of the factors of male infertility, oxidative stress leads to sperm dysfunction. Oxidative stress-induced spermatozoon damage affects 30–$80\%$ of infertile men [61]. Enzymes in the NOX family are responsible for cellular ROS synthesis, and apocynin is a NOX inhibitor [45]. In an experimental model of testicular injury in which apocynin was used as a healing agent, the highest NOX-2 immunoreactivity was observed in the testicular injury group. APO treatment concluded in a decrease in the number of NOX-2 immunopositive cells [27]. Literature data revealed a limited number of experimental testicular damage studies evaluating the amount and distribution of NOX-2. In our study, NOX-2 immunoreactivity was highest in the MSG group, with a decreased immunoreactivity in the MSG + APO group compared to the MSG group. There was no significant difference between the APO group and the control group, presenting the lowest NOX-2 immunoreactivity. Apoptosis is the programmed cell death, which is essential for tissue homeostasis [62]. Regulation of apoptosis is a critical factor in the development, differentiation, and function of germ cells [61]. Exposure to factors that lead to oxidative stress negatively affects spermatogenesis by negatively affecting the structure of chromatin in spermatozoa [63]. Infertile men have been found to have higher oxidative stress and apoptotic cells in their seminal fluid compared to fertile men. In experimental models of testicular damage, the increased number of apoptotic cells in damaged testis tissue was reversed by the administration of APO as a curative substance [23,51]. In an experimental study of testicular injury, apocynin was shown to have a healing effect on DNA damage caused by NOX -induced oxidative stress [64]. Similarly, in our study, the proliferation index was decreased in the MSG group, with an increase in the apoptotic index. In the MSG + APO group, a decrease in the apoptotic index and an increase in the proliferative index were evaluated. The blood-testis barrier protects the developing germ cells against the external environment and provides support for the germ cells to divide and develop, which is very important for fertility [65]. Sertoli cells, which are specialized epithelial cells found in the seminiferous tubules, form the basis of the blood-testis barrier with tight junctions. Occludin, ZO-1, ZO-2, and ZO-3 are molecules found in the tight junctions of the blood-testis barrier. ZO proteins are involved in binding the occludin proteins to the actin in the cytoskeleton [66,67]. It was observed that spermatogenesis was negatively affected, and atrophic seminiferous tubules formed in the occludin knockout mouse model. Our study revealed the highest immunoreactivities of ZO-1 and occludin in the control group and APO group, whereas the MSG group had significantly lower immunoreactivity. ZO-1 and occludin immunoreactivities were higher in the MSG + APO group, compared to the MSG group. Transmission electron microscopic examinations of experimental studies depicted degenerated testicular germinal epithelial cells and lipid droplets [41,54] with deteriorated tight junctions in the blood-testis barrier [68]. In our study, transmission electron microscopic examinations revealed normal testicular seminiferous tubule ultrastructure in the control and APO groups. Vacuolization, lipid droplets, and degenerations in the tight junctions of the blood-testis barrier were evident in the MSG group. In the MSG + APO group, apocynin was found to have a healing effect at the level of ultrastructural damage. ## 5. Conclusions Our study concluded with a regulating role of APO, for the formation of reactive oxygen derivatives and the HPG axis in rat testicular injury induced by MSG. APO maintained the balance between the proliferative and apoptotic indexes, preserved the integrity of the blood-testis barrier, and contributed to the healing of testicular tissue damage caused by oxidative damage. It is also thought that apocynin administration may have a healing effect on infertility by reversing the harmful effects of MSG both on sperm motility and number. ## References 1. Zanfirescu A., Ungurianu A., Tsatsakis A.M., Nițulescu G.M., Kouretas D., Veskoukis A., Tsoukalas D., Engin A.B., Aschner M., Margină D.. 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--- title: Early Intervention of Elateriospermum tapos Yoghurt in Obese Dams Mitigates Intergenerational Cognitive Deficits and Thigmotactic Behaviour in Male Offspring via the Modulation of Metabolic Profile authors: - Ruth Naomi - Rusydatul Nabila Mahmad Rusli - Teoh Soo Huat - Hashim Embong - Hasnah Bahari - Mohd Amir Kamaruzzaman journal: Nutrients year: 2023 pmcid: PMC10052004 doi: 10.3390/nu15061523 license: CC BY 4.0 --- # Early Intervention of Elateriospermum tapos Yoghurt in Obese Dams Mitigates Intergenerational Cognitive Deficits and Thigmotactic Behaviour in Male Offspring via the Modulation of Metabolic Profile ## Abstract Maternal obesity is an intergenerational vicious cycle and one of the primary causes of cognitive deficits and high anxiety levels in offspring, which often manifest independently of sex. It is proven that curbing the intergenerational inheritance of obesity through early intervention during the gestation period has a positive outcome on the body composition, cognitive function, and anxiety level of the offspring. A recent discovery shows that the consumption of Elateriospermum tapos (E. tapos) seed extract modulates body mass and ameliorates stress hormones in obese dams, while a probiotic bacterial strain can cross the placenta and boost a child’s memory. Thus, we speculate that probiotics are the best medium to integrate plant extract (E. tapos extract) to access the effect on the child’s cognition. Thus, this study aimed to investigate the early intervention of E. tapos yoghurt in obese dams in the cognition and anxiety levels of male offspring. In this study, 40 female rats were fed with a high-fat diet (HFD) to induce obesity before pregnancy, while another 8 rats were fed with standard rat pellets for 16 weeks. Upon successful copulation, treatment was initiated for the obese dams up to the postnatal day (PND) 21. The groups included normal chow and saline (NS), HFD and saline (HS), HFD and yoghurt (HY), HFD and 5 mg/kg E. tapos yoghurt (HYT5), HFD and 50 mg/kg E. tapos yoghurt (HYT50), and HFD and 500 mg/kg E. tapos yoghurt (HYT500). All rats were euthanised on PND 21, and the body mass index (BMI), Lee index, and waist circumference were measured for the male offspring. Hippocampal-dependent memory tests and open field tests were conducted to access for cognition and anxiety status. Fasting blood glucose (FBG), total fat (%), insulin, leptin, lipid profile, and antioxidant parameter on serum and hypothalamus (FRAP and GSH) were accessed on PND 21. The result shows male offspring of 50 mg/kg-supplemented obese dams have comparable total fat (%), lipid profile, insulin level, FBG level, plasma insulin level, recognition index, low anxiety level, and improved hypothalamic FRAP and GSH levels to the normal group. In conclusion, this study highlights that the effect of early intervention of our novel formulation of E. tapos yoghurt in obese dams alleviates cognitive deficits and anxiety in male offspring by modulating metabolic profiles at the dose of 50 mg/kg. ## 1. Introduction Excessive gestational weight gain is often linked to a neurodevelopmental delay in the offspring [1]. Maternal obesity is an intergenerational vicious cycle, and the obesogenic can be passed to the next generation [2]. Maternal overnutrition in the foetus can induce leptin resistance in the hypothalamus, thereby stimulating the overexpression of appetite-regulating peptides. As such, there is a positive correlation between overnutrition and the foetus’s BMI, waist circumference, length, and adiposity [3]. Prolonged consumption of a high-fat diet (HFD) is one of the causes of prepregnancy weight gain, and the persistent intake of an HFD is directly linked to poor memory in the offspring [4]. One of the reasons for this scenario could be due to neuroinflammation in the hippocampus. Numerous in vivo studies show that the consumption of an HFD could activate glial cells, leading to neuroinflammation and eventually cognitive dysfunction. This proves that there is a strong association between lipid profile dysregulation and memory decline [5]. Aside from this, the prolonged consumption of an HFD can negatively affect peripheral organs and neuronal plasticity [6]. One possible mechanism for this is that a HFD alters the function of the mitochondria in the brain, which are responsible for providing energy to support synaptic plasticity and controlling the production of reactive oxygen species (ROS). Because synaptic areas have particularly high energy demands, the negative effects of an HFD on mitochondrial function may be more pronounced in these areas. When mitochondria in the brain become dysfunctional due to inflammation and oxidative stress, they can no longer provide enough energy to support synaptic plasticity, leading to impaired neuronal function and neurodegeneration [6,7]. Along with this, the intake of an HFD induces oxidative stress in the hypothalamus. This is evident based on the drastic reduction of enzymatic antioxidant activity, such as glutathione (GSH) [8] and nonenzymatic antioxidants, such as ferric reducing ability of plasma (FRAP) in the plasma [9]. There is growing evidence suggesting that the consumption of an HFD may have negative effects on cognitive function, both in mothers and their offspring. In animal studies, maternal consumption of an HFD during pregnancy and lactation has been shown to impair cognitive function in offspring. These offspring exhibit deficits in learning and memory tasks, as well as increased anxiety-like behaviour [10]. Various mechanisms have been identified to cause cognitive decline in the offspring of maternal subjects that consume an HFD during pregnancy and lactation. Some of them are inflammation, impaired blood–brain barrier (BBB), epigenetic modifications, and alterations in the gut microbiome. One possible explanation is chronic low-grade inflammation induced by an HFD, which can cause cellular damage and negatively affect cognitive function. Inflammatory molecules may cross the placenta and impact fetal brain development [11]. Another mechanism is the impairment of the BBB in offspring, allowing harmful substances to enter the brain and disrupt normal cognitive function [12]. Maternal HFD consumption can also induce epigenetic modifications in the offspring’s DNA, altering the expression of genes involved in brain development and function, leading to cognitive impairments [13]. In addition, maternal HFD consumption can also alter the composition of the gut microbiome in both the mother and offspring, which has been associated with cognitive impairments [14]. However, HFD-induced cognitive deficits are often exhibited in a sex-dependent manner as male offspring are more prone to develop poor memory compared to female offspring. The male offspring of obese dams often display an anxiety-like behaviour and prefer to exhibit thigmotactic behaviour [15]. So, males are more vulnerable to develop schizophrenia [16], vascular dementia [17], and attention deficit hyperactivity disorder (ADHD) [18]. Hence, there is an urgent need to curb maternal obesity-induced cognitive dysfunction and anxiety in the offspring to prevent long-term neurodevelopmental complications. The currently available treatments, such as Orlistat, is linked with adverse effects, such as acute kidney injury [19], while prolonged intake of Sibutramine can result in asthenia, amnesia, and obstipation [20]. Thusly, natural products are said to be the best and most effective option to curb obesity and its complications. In this context, our preliminary study shows that a local tropical plant known as Elateriospermum tapos (E. tapos) comprises a variety of polyphenol and bioactive molecules that can exhibit an antiobesity effect in obese dams by suppressing the activity of lipoprotein lipase [21]. Studies performed by Abidin et al., [ 2020] show that E. tapos extract can modulate stress hormones [22]. E. tapos is a semideciduous plant that can be found in the deep forest of Southeast Asian countries, such as Borneo, Thailand, Peninsular Malaysia, and Indonesia. The seed of the E. tapos plant contains high levels of proteins, unsaturated fatty acids, white oleic acids, a-linolenic acid [23], omega-3 essential fatty acids, and amygdalin, which have potential therapeutic benefits to health [24]. The seed of the plant can either be eaten raw or cooked prior to eating. Yet, the excessive consumption of E. tapos seed can cause dizziness [24]. On the other hand, probiotic consumption favours the body’s metabolism [25]. This is because certain probiotic strains can cross the placental barrier and exhibit beneficial effects on the foetus [26]. The safety efficacy study on E. tapos seed shows that it is safe for consumption up to 2000 mg/kg [27]. Thus, through a related literature search, it has been speculated that probiotics are the most effective medium to supplement the plant extract to the growing foetus [28,29,30]. Hence, this study was designed to investigate the effect of early intervention of E. tapos yoghurt in the male offspring of obese dams focusing on intergenerational cognitive deficits and anxiety levels. ## 2.1. Collection and Confirmation of E. tapos Seed The E. tapos seed was obtained from the Forest Research Institute of Malaysia (FRIM) and was sent for identification and confirmation to Herbarium Biodiversity Unit, University Putra Malaysia (UPM) under the approval code of UPM SK $\frac{3154}{17.}$ ## 2.2. Ethanol Extraction of E. tapos Seed Upon confirmation, about 500 g of E. tapos seed was soaked in 2 litre of $95\%$ ethanol for 7 days. On the 7th day, we collected the filtrate and evaporated it using a rotary evaporator, and maltodextrin powder was added to the filtrate at a ratio of 1:1 [31] and was dried overnight in the oven at 45 °C [32]. The following day, the powder form of E. tapos was collected and stored in the freezer until further usage. ## 2.3. Formulation of E. tapos Yoghurt The yoghurt was prepared by boiling 100 mL of full cream milk (Dutch Lady Purefarm UHT) at 70 °C for 20–30 min. Then, the milk was allowed to cool down at room temperature, and a starter culture consisting of live bacterial culture of Streptococcus thermophilus APC151 and Lactobacillus delbrueckii subsp. Bulgaricus ATCC 11842 was added. The mixture was then incubated in the yoghurt maker (Pensonic PYM-700) for a maximum of 8 h and refrigerated at 4 °C overnight. The following day, the preprepared E. tapos powder was added to the yoghurt at the ratio of 2 g per 100 mL yoghurt and stirred well [33]. ## 2.4. High-Fat Diet Preparation The preparation of a high-fat diet (HFD) was adapted from elsewhere. A total of $68\%$ standard chow pellet (Gold Coin Feedmills (M) Sdn Bhd, Selangor, Malaysia), $6\%$ corn oil (Vecorn, Yee Lee Corporation Berhad, Kuala Lumpur, Malaysia), $6\%$ ghee (Crispo, Crispo-Tato (M) Sdn Bhd, Kuala Lumpur, Malaysia), and $20\%$ milk powder (Dutch lady, Dutch Lady Milk Industries Berhad, Selangor, Malaysia) were mixed and baked at 100 °C for 1–2 h before being refrigerated overnight at 4 °C [34]. ## 2.5. Experimental Animals All animal procedures were conducted based on the guideline provided by the Institutional Animal Care and Use Committee (IACUC), UPM under the approval code of UPM/IACUC/AUP-R$\frac{025}{2022.}$ In this study, 48 female Sprague–Dawley (SD) rats weighing from 150 to 200 g were used. All rats were acclimatised for one week at $\frac{12}{12}$ light/dark cycles in a temperature-controlled room (23–24 °C). During the acclimatisation period, all rats were supplemented with standard chow pellet (Gold Coin Feedmills (M) Sdn Bhd, Selangor, Malaysia) containing $23.4\%$ protein, $4.5\%$ fat, and $72.1\%$ carbohydrates with free access to water (bottle feeding) [35]. ## 2.6. Obesity Induction Female SD rats ($$n = 40$$) were supplemented with HFD pellets for 16 weeks, while the control group ($$n = 8$$) received standard chow pellets. Obesity was confirmed in HFD-supplemented group upon confirming a $13\%$ mean body weight increase compared to control groups [36]. ## 2.7. Mating, Gestation, and Weaning Upon successful obesity induction, both the control group ($$n = 8$$) and obese rats ($$n = 40$$) proceeded with mating by placing one male rat per 2 female rats in a cage. The next morning, all female rats were subjected to manual palpation, and vaginal smears were collected and observed under a microscope for the presence of sperm. The first day for detection of sperm was recorded as postcoital day 0 [37], and treatment with different concentrations of E. tapos yoghurt was initiated in the obese dams. The treatment groups were as follows: normal chow and saline (NS), HFD and saline (HS), HFD and yoghurt (HY), HFD and 5 mg/kg E. tapos yoghurt (HYT5), HFD and 50 mg/kg E. tapos yoghurt (HYT50), and HFD and 500 mg/kg E. tapos yoghurt (HYT500). The treatment was given through oral gavage until postnatal (PND) 21 for the obese dams. No direct treatments were administered to the offspring. ## 2.8. Anthropometrical Determinations On PND 21, all male offspring were sacrificed using carbon dioxide overdose. Body mass index (BMI), Lee index, and waist circumference were determined on the male offspring on PND 21. The waist circumference of the rats was measured in a ventral posture using a flexible tape at the greatest portion of their stomach [38]. To measure the length, the rat was positioned on a flat surface with its head and tail aligned, and then the distance between the tip of the nose and the base of the tail was measured using a ruler. To measure nose-to-anus length in rats, the same technique as measuring total length was used, but with the tail excluded. The distance was measured from the tip of the nose to the anus [39]. The length, nose-to-anus length, and waist circumference were measured 3 consecutive times (repeated measurements) to ensure intraobserver variability. From the recorded measurement, BMI and Lee index were calculated using the formula below: (a)BMI = weight (g)/(length (cm))2;Obesity threshold: BMI > 0.687 g/cm2 [40].(b)Lee index = (weight (g)/length (cm))^($\frac{1}{3}$);Obesity threshold: Lee index > 310 g [41]. ## 2.9. Anxiety Test The thigmotactic behaviour in male offspring was determined through an open-field test (OFT) on PND 21. In this test, a grey PVC box (Muromachi Kikai Co., Tokyo, Japan) measuring 80 cm in width, 80 cm in length, and 50 cm in height was used. The test was conducted during the light illumination cycle. During the test, the rats were placed in one corner of the box, and the time spent close to the wall (thigmotaxis), time spent at the central region, and total distance travelled were recorded using ANY-maze™ Video Tracking System (Stoelting Co., Wood Dale, IL, USA) [42]. ## 2.10. Novel Object Recognition Test (NORT) and Place Recognition Test (PRT) The hippocampal-dependent memory tests known as NORT and PRT were performed on all male offspring on PND 21. For both these tests, all male offspring were allowed to acclimatise in a grey PVC box (Muromachi Kikai Co., Tokyo, Japan) measuring 80 cm in width, 80 cm in length, and 50 cm in height for 5 min on the first two days. On the 3rd day, for NORT, the rats were allowed to tour around an identical object (1.25-litre plastic bottle) for 5 min (trial phase) followed by a 5 min retention phase. During the testing phase, a novel object was added (mug) to the PVC box, and the rats were placed into the box. The total time spent on the novel object was recorded using ANY-maze™ Video Tracking System (Stoelting Co., Wood Dale, IL, USA). For PRT, both the objects used were identical during the trial phase. However, during the testing phase, one of the objects was transferred to a new location in the PVC box. Thus, the time the rats spent at the new location was recorded using ANY-maze™ Video Tracking System (Stoelting Co., Wood Dale, IL, USA). All data obtained from NORT and PRT were expressed as recognition index (%) [43]. ## 2.11. Fasting Blood Glucose Level All rats were fasted for 12 h overnight with free access to water on PND 21 before fasting blood glucose (FBG) analysis. The following morning, the tails of all male offspring were pricked, and blood was sucked using a glucose strip. The FBG levels were recorded using a glucometer (Glucocard™ 01-mini, Arkray Factory, Inc., Kyoto, Japan) [44]. ## 2.12. Postmortem Fat Percentage (%) Analysis Upon sacrificing the rats on PND 21, the body fat (brown adipose tissue, retroperitoneal fat, visceral fat, and gonadal fat) was extracted from the rats, and their weights were measured. The weights were determined based on 100 g of body weight [45]. ## 2.13. Insulin Level Upon sacrificing the rats on PND 21, blood samples (4–5 mL) were collected using a heparin tube, while the hypothalamus was harvested and stored at −80 °C for further analysis. The blood samples were then subjected to centrifugation at 3500 rpm for 15 min to obtain the plasma. The plasma insulin level was then measured using commercial rat insulin ELISA kit (Shibayagi Co., Ltd., Gunma, Japan) [46]. ## 2.14. Lipid Profile The level of low-density lipoprotein (LDH), high-density lipoprotein (HDL), triglycerides, and total cholesterol in blood were measured using a diagnostic reagent test kit (Roche, Germany) using Hitachi Automatic Analyzer 902 (Tokyo, Japan) [47]. ## 2.15. Antioxidant Parameter The hypothalamus was defrosted at room temperature, minced into small pieces, and diluted with 1:15 w:v of phosphate buffer saline (PBS). The samples were then homogenised (Omni TH, Omni International, Kennesaw, GA, USA) together with protease inhibitor and butylated hydroxytoluene followed by sonication three times, each lasting about 20 s using ultrasonic cell disrupter (UP 400S, Hielscher, Teltow, Germany). The final homogenates were then subjected to centrifugation at 5000× g for 20 min [48]. The supernatant was then collected, and the concentrations of ferric reducing ability of plasma (FRAP) in the hypothalamus and plasma were analysed using double-antibody sandwich enzyme-linked immunosorbent assay ELISA kits (Cayman Chemical Company, Ann Arbor, MI, USA) [49]. A similar protocol was adapted to measure the hypothalamus and plasma concentrations of glutathione (GSH) using glutathione ELISA assay kits (Cayman Chemical Company, Ann Arbor, MI, USA). ## 2.16. Statistical Analysis Data were analysed using SPSS version 27.0. Normality tests were performed on all obtained data to ensure normal distribution of the results. All data were expressed as mean ± standard error of the mean (SEM). To test for significant differences among the six groups, a one-way ANOVA was conducted. If the resulting p-value was less than 0.05, a Bonferroni correction test was employed to adjust the significance level and account for the increased risk of false positives associated with multiple comparisons. Because there were six groups, the adjusted significance level was set to $p \leq 0.0083$ (0.05 divided by 6) to maintain an overall family-wise error rate of 0.05. This allowed for a more accurate determination of statistically significant differences among the groups. Different letters in the figures and tables indicate a significant difference. ## 3.1. Body Mass Index (BMI), Lee Index, and Abdominal Circumference of Male Offspring on PND 21 Figure 1A shows the BMI of male offspring on PND 21. The data show that the BMI of male offspring in HS, HY, and HYT5 is significantly higher compared to NS. There is no significant difference in the BMI of HYT50 and HYT500 compared to NS. As shown in Figure 1B, the Lee index of male offspring in HS, HY, and HYT5 is significantly higher compared to NS with a value of more than 310 g. There is no significant difference in the Lee index of HYT50 and HYT500 compared to NS. As shown in Figure 1C, the waist circumference of male offspring in HS, HY, and HYT5 is significantly higher compared to NS, while there is no significant difference in the waist circumference of HYT5, HYT50, and HYT500 compared to NS. ## 3.2. Fasting Blood Glucose in Male Offspring on PND 21 Figure 2 shows the FBG level of male offspring on PND 21. The data show that the FBG level of male offspring in HS, HY, and HYT5 is significantly higher compared to NS, while there is no significant difference in the plasma FBG level of HYT5, HYT50, and HYT500 compared to NS. ## 3.3. Anxiety Test in Male Offspring on PND 21 Figure 3A shows the time spent by male offspring in the central zone of the open field test (OFT). The data show that the male offspring in HS spend a significantly low duration of time compared to NS in the central zone. There is no significant difference in the duration of time spent by HY and HYT5 in the central zone compared to NS and HS. However, the time spent by HYT50 and HYT500 is similar to NS in the OFT. As shown in Figure 3B, the male offspring in HS and HY spend a significantly high duration of time compared to NS in the thigmotaxis. There is no significant difference in the duration of time spent by HYT5, HYT50, and HYT500 at the thigmotaxis compared to NS. Figure 3C shows the total distance travelled by male offspring in the central zone of the OFT. The data show that the total distance travelled by male offspring in HS is significantly lower compared to NS, whereas there is no significant difference in the total distance travelled by HY, HYT5, HYT50, and HYT500 in the central zone compared to NS. ## 3.4. Novel Object Recognition Test (NORT) and Place Recognition Test (PRT) in Male Offspring on PND 21 Figure 4A,B show the recognition index (%) of male offspring in NORT and PRT on PND 21. As shown in Figure 4A, the recognition index of male offspring in HS, HY, and HYT5 is significantly lower compared to NS, whereas there is no significant difference in the recognition index of HYT50 and HYT500 compared to NS in NORT. The data in Figure 4B show that the recognition index of male offspring in HS and HY is significantly lower compared to NS, whereas there is no significant difference in the recognition index of HYT5, HYT50, and HYT500 compared to NS in PRT. ## 3.5. Fat Percentage (%) in Male Offspring on PND 21 Table 1 shows the fat percentage in male offspring on PND 21. The percentage of brown adipose tissue (BAT) and retroperitoneal white adipose tissue (RpWAT) and visceral and gonadal fat in male offspring of HS is significantly higher compared to NS. In male offspring of HY, the percentage of BAT shows no significant difference compared to HS. The fat percentage of RpWAT and visceral and gonadal fat in male offspring of HY is significantly lower compared to HS while significantly higher compared to NS. There is no significant difference in HYT5, HYT50, and HYT500 for BAT and RpWAT and visceral and gonadal fat compared to NS. The fat percentage of visceral and gonadal fat of male offspring in HYT50 and HYT500 shows no significant difference compared to HY. The RpWAT in male offspring of HYT50 shows no significant difference compared to HY. ## 3.6. Lipid Profile of Male Offspring on PND 21 Figure 5A–D show the lipid profile of male offspring on PND 21. The data show that the serum cholesterol levels of male offspring in the HY and HS groups are significantly higher compared to NS. There is no significant difference in the serum cholesterol levels of HYT5, HYT50, and HYT500 compared to NS. As shown in Figure 5B, the serum triglyceride level of male offspring in HS is significantly higher compared to NS. There is no significant difference in the serum triglyceride of HY, HYT5, HYT50, and HYT500 compared to NS. Meanwhile, the plasma HDL levels in the male offspring in HY and HS are significantly lower compared to NS. There is no significant difference in the plasma HDL levels of HYT5, HYT50, and HYT500 compared to NS. The data shown in Figure 5D indicate that the plasma LDL levels in the male offspring of HY and HS are significantly higher compared to NS. There is no significant difference in the plasma HDL levels of HYT5, HYT50, and HYT500 compared to NS. ## 3.7. Insulin Level in Male Offspring on PND 21 Figure 6 shows the plasma insulin levels of male offspring on PND 21. The plasma insulin level of male offspring in HS is significantly higher compared to NS, whereas there is no significant difference in the plasma insulin levels of HY, HYT5, HYT50, and HYT500 compared to NS. ## 3.8. Antioxidants Level in Serum and Hypothalamus of Male Offspring on PND 21 Figure 7A–D show the antioxidant levels in the serum and hypothalamus of male offspring on PND 21. As shown in Figure 7A, the serum FRAP level is significantly lower in HS compared to NS. There is no significant difference in the serum FRAP levels of HY, HYT5, and HYT50 compared to NS. However, the serum FRAP level of HYT500 is significantly higher compared to NS, HS, HYT5, and HYT50, while there is no significant difference in the serum FRAP level of HYT50 compared to HYT500. As shown in Figure 7B, the FRAP levels in the hypothalamus are significantly low in HS and HYT5 compared to NS. There is no significant difference in the FRAP levels in the hypothalamus of HYT5, HYT50, and HYT500 compared to NS. The data in Figure 7C show the serum GSH levels. As shown in Figure 7C, the serum GSH levels are significantly lower in HS and HY compared to NS. Meanwhile, the serum GSH levels of HYT5 and HYT500 are significantly lower compared to HS, HY, and NS. However, the serum GSH level in HYT50 is significantly higher compared to HS, HY, HYT5, HYT500, and NS. The data in Figure 7D show the GSH level in the male offspring’s hypothalamus. As shown in Figure 7D, there is no significant difference among NS, HS, HY, HYT5, HYT50, and HYT500 in the hypothalamic GSH levels. However, the GSH level in the hypothalamus of male offspring in HYT50 shows a similar mean value to NS. ## 4. Discussion Maternal obesity greatly affects the growth and behaviour of the child. Preliminary studies show that male offspring are more prone to glucose tolerance and increased levels of adiposity compared to female offspring due to overnutrition during the gestational period [50]. Similarly, offspring born to HFD-supplemented obese dams exhibited a high level of triglycerides, insulin, and expression of lipid genes [51]. Recent evidence claims that the offspring of obese mums possess $60\%$ higher chances of developing ADHD and autism spectrum disorder (ASD) [52] and are more vulnerable to develop psychosocial difficulty [53]. Emerging evidence proves that nutritional intake during the gestational period greatly influences the behavioural changes of the offspring, particularly in hippocampal-dependent memory [54]. Thus, this study investigates the effects of early intervention of Elateriospermum tapos yoghurt in obese dams to mitigate intergenerational cognitive deficits and thigmotactic behaviour in male offspring, focusing on metabolic parameters and antioxidant changes in the hypothalamus. The key findings from this study show that the male offspring born to the HFD-supplemented group without any treatment (HS group) have a high BMI, Lee index, and waist circumference. They do possess a low level of recognition index in NORT and PRT as well as an increased level of thigmotactic behaviour with a reduced antioxidant profile in the hypothalamus. Their fat percentage in BAT and RpWAT and visceral, and gonadal fat is significantly high with an altered metabolic profile on PND 21. This outcome in this study proves the successful establishment of the intergenerational obese model in male offspring with a poor neurodevelopment condition. This result is similar to the study conducted by O’Reilly et al., 2013 [55], who noticed that an increase in BMI has a positive correlation with body fat content. Our result is in line with Oken et al., 2021, who demonstrated that maternal obesity influences poor memory, learning ability, and fetal brain development [56]. On the contrary, the male offspring of the yoghurt-supplemented obese dams (HY) show a slight reduction in body composition and metabolic profile and a slight improvement in memory compared to the HS group. Our result is similar to the study performed by Wiciński et al., 2020, as the child’s obese mum supplemented with probiotics shows normal body mass, metabolic profile, and inflammatory markers just as the negative control group [57], and the probiotic-containing Lactobacillus strain is able to restore cognitive decline in the offspring of HFD-supplemented dams [58]. This is because probiotics, such as yoghurt consumption during pregnancy, modulate gut microbiome composition and prevent gut dysbiosis in the foetus, thereby limiting the inheritance of the obesogenic gene in the child [59]. Similarly, the presence of proteins, iodine, and zinc in yoghurt enhances the memory function of the growing foetus [60]. However, the changes observed in the male offspring of dams administered with plain yoghurt (HY) are not as prominent as the male offspring of dams supplemented with E. tapos-integrated yoghurt (HY5, HY50, and HY500) in this study. This is because medicinal plant-integrated yoghurt exhibits more beneficial effects similar to the NS in the study. The outcome in HY50 and HY500 is almost similar to the NS group; however, male offspring HY50 exhibit a similar mean value as NS in all of the parameters accessed in this study. Intriguingly, our data are similar to the previous study performed by Balan et al., 2021, who noticed that E. tapos extract was proven to inhibit the transgenerational inheritance of obesity in the female offspring [61] and ameliorate cognitive dysfunction in the F1 generation [62]. This is because E. tapos extract contains numerous bioactive compounds that have a molecular weight of ≤600 daltons [24] that could cross the placenta and blood–brain barrier to exhibit beneficial effects. In this context, E. tapos seed contains a high concentration of phenolic and flavonoids, which possess inhibitory activity on α-amylase, α-glucosidase, and pancreatic lipase [63]. The ability to inhibit pancreatic lipase by E. tapos prevents lipid absorption, thereby manifesting in a decreased level of fat content [64]. Meanwhile, the inhibitory activity of α-amylase prevents the absorption of carbohydrates and hydrolyses glucose into polysaccharides [65]. Resultantly, these changes may be evinced as decreased levels of cholesterol and glucose in the bloodstream. Similarly, the inhibition of α-glucosidase may reduce triglycerides and hyperinsulinaemic conditions [66]. Proportionately, such changes in the metabolic profile could be the underlying mechanism of male offspring belonging to HYT5. HYT50 and HYT500 show a gradual reduction in the BMI, Lee index, and waist circumference compared to the HY group in this study. In the bargain, the presence of flavonoids, such as kaempferol and amentoflavone in E. tapos extract [67], is one of the reasons for the increased levels of GSH in the male offspring of HYT5, HY50, and HYT500 in the hypothalamus compared to the plain yoghurt-supplemented group (HY) and HS. This is because those flavonoids are strong antioxidants that exhibit protective effects against oxidative stress or inflammation via various signalling pathways [68,69]. Comparatively, a similar phenomenon is observed in the FRAP levels in the serum and hypothalamus of the E. tapos yoghurt-treated group, which proves that flavonoids could increase the level of antioxidants. Increased levels of antioxidants (FRAP and GSH) could neutralise free radicals and prevent inflammatory responses [70] that are released by an excessive level of adipose tissue in obesity. Thus, increased levels of GSH and FRAP in the hypothalamus may reverse memory decline and ease anxiety-like behaviour [71]. This is because GSH acts as a protective shield for neurons from stress disturbance [72], while FRAP prevents memory deficits by reversing the deprivation of neurotransmitters [73]. Hence, through the results obtained from this study, the hypothesis has been proven because the early intervention of E. tapos in obese dams prevents cognitive deficits and thigmotactic behaviour in male offspring via the modulation of the metabolic profile. ## 5. Conclusions An HFD intake during pregnancy is one of the factors for maternal obesity, while maternal obesity is positively correlated with metabolic disturbance, cognitive decline, and anxiety-like behaviour in the offspring. The supplementation of E. tapos yoghurt during the gestational period to the HFD-fed obese dams has proven to mitigate intergenerational cognitive deficits and thigmotactic behaviour in male offspring via the modulation of the metabolic profile at the dose of 50 mg/kg/day. ## 6. Limitation One of the limitations of this study could be that the outcomes from this study may not provide a complete understanding of how the intervention impacts female offspring. There could be significant differences in how the intervention affects the metabolic profiles and cognitive functions of male and female offspring. Thus, from the outcomes of this study, it may not be possible to generalise the findings to female offspring. This is because there may be gender-specific differences in response to the intervention or in the manifestation of cognitive deficits and thigmotactic behaviour. 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--- title: Selenium Status and Oxidative Stress in SARS-CoV-2 Patients authors: - Andrejs Šķesters - Anna Lece - Dmitrijs Kustovs - Maksims Zolovs journal: Medicina year: 2023 pmcid: PMC10052009 doi: 10.3390/medicina59030527 license: CC BY 4.0 --- # Selenium Status and Oxidative Stress in SARS-CoV-2 Patients ## Abstract Background and Objectives: Insufficient intake of essential micronutrient selenium (Se) increases the susceptibility to diseases associated with oxidative stress. The study aim was to assess Se status and oxidative stress in COVID-19 patients depending on severity of the disease. Materials and Methods: Blood plasma of 80 post-COVID-19 disease patients and 40 acutely ill patients were investigated. Concentration of Se was detected by a fluorometric method with di-amino-naphthalene using acidic hydrolysis. Selenoprotein P (Sepp1), malondialdehyde (MDA), and 4-hydroxynonenal (4-HNE) and their metabolite adducts were evaluated by spectrophotometric methods using commercial assay kits. Results: Obtained results demonstrated that Se and Sepp1 concentration in acute patients were significantly ($p \leq 0.05$ for Se and $p \leq 0.001$ for Sepp1) decreased compared with post-COVID-19 disease patients. However, in post-COVID-19 disease patients, Se values were close to the low limit of the norm for the European population. 4-HNE adducts concentration as a marker of lipid peroxidation was significantly increased in the acute patients group compared to the recovery group ($p \leq 0.001$). Conclusions: COVID-19 pathology is characterized by the induction of oxidative stress and suppression of antioxidant defenses during the acute phase. Lower levels of Se and Sepp1 and higher levels of reactive oxygen species reflect this imbalance, highlighting the role of oxidative stress in the disease’s pathogenesis. ## 1. Introduction Trace element selenium (Se) has attracted the attention of researchers over the past decades, but its true potential as a biologically active entity is far from clear understanding. Se performs its function via Se containing proteins which mostly contain selenocysteine at their active centre, and up to date, about 25 Se containing proteins have been identified in the cells of various organs and tissues in humans. Selenoproteins play a vital role in several physiological functions, such as thioredoxin reductases and deiodinases that regulate cellular redox homeostasis and thyroid metabolism. The glutathione peroxidase family of enzymes function as reactive oxygen species scavengers, and selenoprotein K contributes to immune cell activation and proliferation. Moreover, selenoprotein P (Sepp1) acts as a selenium transporter and represents the major selenoprotein in plasma, synthesized in the liver, secreted into the plasma, and transported to the target tissues [1]. Thus, Se plays a crucial role in the redox reactions and cell signalling, antioxidant processes, immune system [2], hormone metabolism, cardiovascular system [3], and maintenance of reproductive function [4]. Thus, it is not surprising that several studies have identified an association between Se depletion and diverse pathologies, such as cardiovascular diseases [5], heart failure [6], certain cancers [7], impaired immune function, infertility [8], cognitive decline [9], and increased susceptibility to RNA viral infections. SARS-CoV-2, along with Ebola, human immunodeficiency virus type 1 (HIV-1), coxsackievirus, influenza virus, SARS-CoV, and MERS-CoV, is classified as a single-stranded linear RNA virus [10]. Studies have demonstrated that inadequate levels of Se promote the replication, mutations, and virulence of multiple RNA viruses [11,12,13]. The involvement of Se in both innate (macrophages and neutrophils) and adaptive (T and B cells) immune system components suggests that Se deficiency may impede the non-specific cell-mediated immune response and lead to impairments in T-cell lymphocyte activation, proliferation, and differentiation [2,14]. This, in turn, may enhance the susceptibility to infections, resulting in increased morbidity and mortality [15]. Epidemiological studies performed in various countries, with a primary focus on China, the origin of SARS-CoV-2, have demonstrated a close association between the body’s Se level and the incidence, severity, and prognosis of COVID-19 disease caused by the SARS-CoV-2 virus [16,17,18,19]. A recent comprehensive review by Fakhrolmobasheri et al. has revealed a strong correlation between lower Se and Sepp1 levels and unfavourable outcomes in COVID-19 patients. Additionally, Se concentrations in COVID-19 patients were significantly lower than those in healthy individuals [20]. Variability in the findings reported in the review may be attributed to the lack of consideration given to the initial Se levels in each country’s population and the presence or absence of regional Se deficiency in the soil. Lower Se and Sepp1 levels were reportedly detected in COVID-19 patients across various nations, such as Belgium’s intensive care unit short-stayers (7–11 days), Germany’s deceased cases compared to discharges, India’s male patients, Nigeria’s patients, Russia’s moderate to severe cases, South Korea’s severe cases, and Turkey’s pregnant women with COVID-19 [20]. The content of Se in human plasma can be estimated by determining the concentration of not only elemental Se but also Sepp1. Sepp1 is the major Se transporter in the bloodstream and is responsible for delivering more than $50\%$ of the total Se content in human plasma [21,22]. Recent scientific studies have demonstrated the multifaceted roles of Sepp1 in the body. Sepp1 exhibits enzyme-like activity similar to that of glutathione peroxidase, enabling it to reduce phospholipid hydroperoxide in the presence of glutathione and thereby counteracting the effects of oxidative stress [17]. The current scientific literature suggests that viral infections are accompanied by escalated reactive oxygen species (ROS) generation, which can facilitate viral replication by exacerbating the infection [17]. ROS are highly reactive molecules that are produced by cells during normal metabolism and in response to various stressors, including viral infection. While low levels of ROS can have beneficial effects on the immune system, excessive ROS production can lead to oxidative stress, which can damage cells and contribute to inflammation and disease. The ROS with polyunsaturated fatty acids can lead to lipid peroxidation, which generates a wide variety of oxidation products. Lipid peroxidation is a chain reaction process that can occur in cell membranes, where polyunsaturated fatty acids are abundant. The degree of lipid peroxidation is often used as a reliable biomarker of oxidative stress mediated damage. The concentrations of secondary lipid peroxidation products, such as malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE) and their metabolite adducts in different body fluids such as the whole blood, blood plasma, serum, and in other tissues, are generally used as an indicator of lipid peroxidation and markers of oxidative damage. Higher formation of MDA is associated with various diseases including hypertension, diabetes, and atherosclerosis [23]. 4-HNE acts both as a signalling molecule and as a cytotoxic product of lipid peroxidation causing long-lasting biological consequences. Once formed, 4-HNE can promote cell survival or death. If 4-HNE can be enzymatically metabolized at the physiological level, cells can survive. However, if 4-HNE is at a high or very high level, it induces apoptosis or necrosis-programmed cell death, eventually leading to molecular cell damage which may facilitate development of various pathological states [24]. The objective of this investigation was to evaluate Se status in COVID-19 patients during the acute phase and in recovered patients after 2 months, using Se and Sepp1 concentrations as biomarkers. We also aimed to determine the extent of oxidative stress by measuring MDA and 4-HNE adduct concentrations in plasma, with the intention of uncovering any potential relationship between Se status, disease severity, and oxidative stress. ## 2. Materials and Methods The study was carried out on a cohort of 120 participants, comprising 40 acutely ill COVID-19 patients who were hospitalized in the COVID-19 unit or intensive care unit at Pauls Stradins Clinical University Hospital and 80 individuals who had recovered from COVID-19 and were discharged from the hospital 2 months earlier. The present research was conducted in compliance with the Declaration of Helsinki, Guidance on Good Clinical Practices, and applicable regulatory requirements. This clinical trial was conducted as a component of the Latvia Research Programme, which aims to investigate the clinical, biochemical, and immunogenetic paradigms of COVID-19 infection and their associations with socio-demographic, etiological, pathogenetic, diagnostic, therapeutic, and prognostic factors for inclusion in guidelines. The concentration of Se in blood plasma was evaluated using the fluorometric method with di-amino-naphthalene and acidic hydrolysis. The measurement of Sepp1 was carried out using the previously reported Human Sepp1 ELISA kit [25]. Chemicals were produced by Sigma-Aldrich (Spruce St., Saint Louis, MO, USA). MDA was detected using OxiSelect™ TBARS (MDA Quantitation) Assay kit, Cell Biolabs, Inc, San Diego, CA, USA, according to the manufacturer’s instruction. 4-HNE adducts were detected using OxiSelect™ HNE Adducts Competitive ELISA kit, Cell Biolabs, Inc, San Diego, CA, USA, according to the manufacturer’s instructions. The absorption spectrum was measured using multimodal microplate reader SPARK, TECAN, Austria. Blood samples were collected utilizing BD Vacutainers LH 1701.U Plus Blood Collection tubes, followed by centrifugation at a force of 1500× g and 4 °C for a duration of 10 min. The resulting blood plasma was fractionated into cryogenic tubes and then preserved by freezing at −80 °C prior to analysis. Statistical analysis was performed using RStudio v.2021.09.1 (Boston, MA, USA) statistical software. Data distribution was checked visually (histograms and QQ-plots) and with Shapiro–Wilk test. MDA and 4-HNE adducts were log transformed due to positively skewed distributions. The Levene’s test was used to test if samples have equal variances. Statistical analysis of differences between groups was carried out using analysis of variance (ANOVA) and compared by the Tukey’s HSD test. p-value < 0.05 was set as statistically significant level. Data are presented as mean ± standard deviation and graphically. ## 3. Results The study included 120 patients who met the eligibility criteria for analysis. Blood plasma samples were collected from all patients, and their Se, Sepp1, MDA, and 4-HNE adducts status were assessed. The patients were divided into three groups based on their COVID-19 infection status: infected in the spring–early summer period (March-June; Group 1) and in the autumn period (October; Group 2) both two months post-discharge from the hospital, and acutely ill patients (March-June; Group 3), divided into two subgroups: patients treated in the COVID-19 unit and patients treated in the intensive care unit (20 + 20). A previous study in healthy adults ($$n = 195$$, mean age 49, range 21–59) was utilized to obtain the average concentrations of Se, Sepp1, MDA, and 4-HNE adducts in the population [26]. The results that were obtained are presented in Figure 1 and Figure 2 below. The Se content in the blood plasma of acutely ill patients at the hospital was significantly decreased ($p \leq 0.05$) compared to post-COVID-19 disease patients, as shown in Figure 1a. Furthermore, an even greater decrease in Se concentration was observed when samples from patients treated in intensive care units were analysed separately, with their plasma containing only 59.3 μg/L of Se ($15\%$ lower compared to the whole group) and having an extreme range of limits (min/max) from 75.4 μg/L to 43.2 μg/L. In contrast, the Se content in the blood plasma of post-COVID-19 disease patients was close to the lower limit of the normal range for the European population, with no significant differences observed between the spring–summer (1st group) and summer–autumn (2nd group): 84.6 ± 20.7 μg/L and 88.2 ± 27.2 μg/L, respectively (Figure 1a). The Sepp1 concentration in plasma was measured to be 4.5 ± 2.4 mg/mL in acute patients, 5.5 ± 2.2 mg/mL in the 1st group of post-COVID-19 patients, and 6.8 ± 2.3 mg/mL in the 2nd group. A marked reduction in the concentration was noted in the acute patient group ($p \leq 0.001$) compared to the Se concentration in this group. Interestingly, the summer–autumn recovery group showed a significant increase in Sepp1 concentration compared to each other group, as shown in Figure 1b. The levels of MDA were increased in all groups of patients studied, with concentrations exceeding those observed in healthy individuals: 26.6 ± 10.8 μmol/L, 31.0 ± 18.6 μmol/L, and 26.6 ± 10.8 μmol/L in acute patients, the spring–summer group, and the summer–autumn group, respectively. Analysis of the logarithmic-transformed data showed no statistically significant differences among the groups (refer to Figure 2a). A different pattern emerged when investigating the plasma concentration of 4-HNE adducts. The highest level was detected in acute patients, while the concentration of 4-HNE was significantly ($p \leq 0.001$) lower in the spring–summer group, but without a significant difference in the summer–autumn group: 5.1 ± 2.4 μg/L, 3.4 ± 1.9 μg/L, and 3.9 ± 1.8 μg/L, respectively. A similar trend was evident when examining the logarithmic-transformed data: 1.5 ± 0.5 vs. 1.1 ± 0.5 vs. 1.3 ± 0.4 (see Figure 2b). No correlation between the examined parameters was detected. The study findings indicate significant differences between acute patients and post-COVID-19 recovery groups. The concentrations of Se and Sepp1 were markedly lower in the acute patients, in comparison to healthy individuals. Conversely, the oxidative stress biomarkers, MDA and 4-HNE adducts, were elevated beyond the acceptable range. ## 4. Discussion Se is an essential micronutrient that has antioxidant properties and plays a role in immune function, while Sepp1 participates in regulating Se metabolism and transporting Se throughout the body. Therefore, it has been hypothesized that deficiency of Se and Sepp1 might enhance the susceptibility and severity of COVID-19. Several studies confirmed a decrease in Se and associated components in patients with COVID-19 disease [27,28,29,30]. The results of our study indicate that hospitalized COVID-19 patients had reduced levels of Se in their blood plasma, which were lower than the European healthy adult reference ranges of 70–130 μg/L (median 87 μg/L) for Se concentration, with concentrations below 70 μg/L considered deficient [6]. In addition, the Se concentrations were also lower than the range of 77.4–81.5 µg/L (median 79.5 μg/L) observed in healthy individuals from Central Europe [31] and the reference data from a European cross-sectional analysis of serum Se, with a concentration of 84.4 ± 23.4 µg/L [16]. A similar outcome is seen with Sepp1 concentration in hospitalized patients, which was near the lower limit of adequate level of healthy Europeans (2.56–6.63 mg/L). These results are in line with other investigators who reported significantly lower Se levels in COVID-19 patients compared to healthy controls [16,18,19,20] not depending on the relatively high [32] or low [16,18,19] baseline Se level. A notable association has been shown between low Se level and COVID-19 disease incidence [18,19], severity [33], and outcomes [34], especially in hospitalised patients [16] and patients in intensive care unit, which is in conformity with our results and specify Se deficiency as risk factor for COVID-19 disease. Comparable findings have been elaborated by Majeed et al., where the authors established that viral load could damage critical organs in the body, especially after interacting with enzymes such as angiotensin [35]. Important considerations can now be directed to supportive nutrient therapies such as Se to mitigate the susceptibility and long-term impacts of COVID-19 disease. Se is effective in improving the immune system and controlling inflammation that could result from the spread of the virus [30]. Therefore, the inability to overcome oxidative changes can largely result in negative outcomes such as fatalities. In another study by Tsermpini and colleagues, the researchers demonstrated that SAR-COV-2 is connected to increased oxidation stress, which is an imbalance between the production of antioxidant systems and free radicals [36]. As a result, such impacts can lead to severe conditions of COVID-19 disease because of their participation in the pathogenesis. With the increase in oxidative stress, various mechanisms such as DNA damage, protein inactivation, and lipid peroxidation can occur, which can potentially cause cell dysfunctions or result in an inflammatory response. Interestingly, Muhammad et al. found significant depletion of antioxidant levels in COVID-19 patients, resulting in increased formation of free radicals [27,37]. For instance, the researchers noted that essential elements such as Se, zinc, copper, and manganese were lower among patients with COVID-19 compared to controls. Similarly, plasma-concentrated nutrients such as vitamin A, C, and E were also lower in COVID-19 patients. In another study, to determine the relationship between COVID-19 and oxidative stress (vascular stress and lipid peroxidation), the authors demonstrated that there was a reduction in antioxidant capacity, and thus, the patients were unable to counteract oxidative modifications [37,38]. Moreover, our results are consistent with previous studies indicating that oxidative stress markers are significantly elevated in COVID-19 patients. The significantly higher concentrations of 4-hydroxy-2-nonenal (4-HNE) protein adducts in acutely ill (hospitalized) patients suggest impaired antioxidant defense mechanisms in these individuals. Similarly, Mehri et al. reported increased malondialdehyde (MDA) levels in intensive care unit patients, accompanied by heightened enzymatic antioxidant activity [39]. The reduction in 4-HNE adduct concentrations two months after discharge suggests an improvement in dysregulated antioxidant system response to oxidative stress. Nevertheless, our assessment of lipid peroxidation by MDA measurements indicates consistent increase in MDA levels across all patient groups, including those who have recovered, which is in line with previous studies. Ikonomidis and co-workers reported elevated MDA level compared to controls at 4 months post-infection that remained increased even at 12 months after COVID-19 infection, when disease symptoms almost disappeared [40]. Another research group detected considerably higher MDA levels in COVID-19 patients 4 months after infection not associated with disease severity (mild, moderate, and severe) [41]. Thus, it can be considered that COVID-19 patients have elevated oxidative stress extending over a long post-infection period. Additionally, oxidative stress may play a significant role in the mechanism of disease and complications, especially endothelial and vascular development. Therefore, patients with COVID-19 may benefit from strategies to reduce or prevent oxidative stress. Our results show that Se status among observed COVID-19 patients in Latvia, as assessed by Se and Sepp1 concentration in human plasma, is low among acute patients and patients 2 months following their discharge from the hospital. Therefore, current results are consistent with previous studies showing that Se deficiency is a global problem [15]. The deficiency of Se can result from insufficient dietary intake or increased requirements. The observed patients are affected by both factors, as the soil in Latvia, along with other regions in Eastern Europe, lacks sufficient Se content. This, in turn, affects the Se levels in plants, grain products, and other representatives of the food chain [42]. On the other hand, RNA viral infections can increase the production of ROS, which can lead to oxidative stress and damage to cells and tissues. In response to this, the host antioxidant defence system is activated, and the immune system is also stimulated to fight the infection. Selenoproteins play an important role in both the antioxidant defence system and the immune system [12]. Moreover, COVID-19 infection can lead to inflammatory and hypoxic conditions that may increase the need for Se and exacerbate Se deficiency. Considering all that is mentioned above, there is extraordinary question regarding the use of Se supplementation for COVID-19 patients. In terms of the type of Se compound that is more suitable for supplementation, organic Se compounds such as selenomethionine and selenocysteine are generally considered to be more bioavailable and better absorbed than inorganic forms of Se such as sodium selenite [43]. However, the optimal form and dose of Se for COVID-19 patients has not been established and requires further research. Oral supplementation is the most common form of Se supplementation and may be sufficient for individuals with mild Se deficiency. However, individuals with more severe Se deficiency or those who are unable to tolerate oral supplementation may require intravenous administration. The optimal duration and dose of Se supplementation for COVID-19 patients also requires further investigation. Excessive Se intake can be toxic and lead to adverse health effects; therefore, the dose of Se should be carefully monitored and tailored to individual patient needs [44]. While the role of Se supplementation in the treatment of COVID-19 is an area of active research, there is currently limited evidence to support its routine use in clinical practice. Any decisions regarding the use of Se supplementation should be made in consultation with a healthcare provider and based on individual patient needs. ## Strengths and Weaknesses of the Study This research is critical because it helps to understand the interventions that can be incorporated to reduce adverse outcomes, such as the potential of developing other adverse conditions during high viral load, such as in the case of COVID-19. For instance, Žarković suggested how to respond to patients with SARS-CoV-2 by administering antioxidants such as lipophilic agents that can help to counter the spread of the virus [38]. Furthermore, Chavarría et al. established that antioxidant therapy can help to reduce the severity of conditions such as COVID-19 because it improves the survival rates of critical outcomes such as sequential organ failure assessment (SOFA) [27]. Similarly, the study by Molteni established that antioxidant molecules are effective in reducing the prognosis and symptoms of viral diseases such as COVID-19 [28]. There is no doubt that it is important to ensure redox balance by involving vital molecules to control the adverse effects of the virus. The presence of oxygen and nitrogen radicals should be regulated to prevent high concentration or low concentrations. It is worth noting that imbalances can result in a significant increase in viral load. However, the corrective measures may not be effective when patients have comorbidities such as diabetes, hypertension, and other diseases, which can largely cause oxidative stress [37]. Furthermore, while clinicians decide to use antioxidants in the treatment, it is important to ensure they are regulated and taken in their right dosages to reduce negative outcomes such as increased mortality and toxicity. Therefore, although there has been an elevated decline in critical nutrients such as Se in COVID-19 patients, it is important to understand the application of the research in clinical practice, such as the modifications that can be implemented following an increase of virus and the reduction of nutrients. Conversely, it is worth noting that the present study was conducted using a smaller sample size, and hence the results cannot be applied in other contexts without modification. Despite this limitation, the study can form a rich body of knowledge for researchers developing interventions for COVID-19 disease [30]. For example, paying attention to the trace element (Se) can help in reducing adverse outcomes such as an increase in the spread of infections during crises such as the COVID-19 pandemic. Therefore, clinicians can use the knowledge acquired in this review paper to develop mechanisms for controlling Se deficiency, which is associated with the development of pathogens [35]. This will help in reducing the mortality rate among patients with COVID-19 and other serious viral diseases. For instance, Alshammari et al. suggested the potential of developing Se-based dosages and compositions, such as inhalers and sprays, to control the spread of the COVID-19 pandemic [45]. ## 5. Conclusions Based on our results, it can be concluded that severe COVID-19 patients experience lower Se and Sepp1 concentrations and increased oxidative stress, which indicates heightened reactive oxygen species formation in the body. At two months post-infection, Se status appears to improve, with Se and Sepp1 concentrations reaching average population values for these biomarkers. Despite this, oxidative stress remains high, suggesting ongoing ROS formation and dysfunction of the antioxidant system, which are closely related to selenoproteins. Understandably, decrease in mortality rate among patients with COVID-19 can be controlled by regulating the oxidative stress biomarkers. 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--- title: Novel Synthesis of Dihydroisoxazoles by p-TsOH-Participated 1,3-Dipolar Cycloaddition of Dipolarophiles withα-Nitroketones authors: - Caiyun Yang - Sirou Hu - Xinhui Pan - Ke Yang - Ke Zhang - Qingguang Liu - Xiaobing Xin - Jie Li - Jinhui Wang - Xiaoda Yang journal: Molecules year: 2023 pmcid: PMC10052018 doi: 10.3390/molecules28062565 license: CC BY 4.0 --- # Novel Synthesis of Dihydroisoxazoles by p-TsOH-Participated 1,3-Dipolar Cycloaddition of Dipolarophiles withα-Nitroketones ## Abstract This article reports in detail a method for the synthesis of 3-benzoxoxazoline by the reaction of alkenes (alkynes) and a variety of α-nitroketones in the presence of p-TsOH. The scope of alkenes is broad, including different alkenes and the alkyne. This reaction provides a convenient and efficient synthetic method of 3-benzoylisoxazolines. ## 1. Introduction Heterocycles are important structural elements, which are present in natural products from all classes and in many biologically active synthetic compounds [1]. Heterocyclic compounds perform an important role in chemical industry, e.g., food fragrance and dyes. Amongst these, isoxazole and its derivatives represent a group of five-element heterocyclic compounds containing oxygen and nitrogen atoms of a valuable class [2]. Additionally, they have performed a vital role in the theoretical development of heterocyclic chemistry and are also extensively used in organic synthesis [3]. Isoxazoles have attracted an increasing research interest, and are widely used and studied in the modern drug discoveries as non-classical amide or ester bioisosteres, and potential pharmacophores endowed, and most isoxazoles have strong biological activity [4,5]. Isoxazolines are partially saturated analogs of isoxazoles as important intermediates for synthesis of varieties of fascinating organic molecules applicable to both basic organic synthesis and life sciences [6]. Isoxazolines can be converted into various synthetic units, such as hydroxy ketones [7], amino alcohols [8], β-hydroxynitrile [9], and masked aldols [10], and be used as synthetic equivalent of 1,3-dicarbonyl structure [11]. Isoxazolines can exhibit a variety of bioactivities, such as anti-inflammatory [12], anticancer [13], hypoglycemic [14], antibacterial [15], anti-HIV [16], anti-Alzheimer’s [17], antifungal [18], antimalarial [19], antioxidant [20], anti-tuberculosis [21], and antinociceptive [22] activities (Figure 1). Isoxazolines can also be good herbicides [23] and insecticides [24]. Therefore, the development of new methods for more efficient synthesis has been always an attractive task. Based on the characteristics and wide application of isoxazolines derivatives, the research progress of isoxazolines derivatives have progressed rapidly in recent years, and a large number of synthetic methods for isoxazole derivatives are reported in the literature every year. These approaches can be summarized as the following four major types: [1] 1,3-dipolar cycloaddition between nitrile oxide and unsaturated hydrocarbon [25,26,27,28,29], [2] intramolecular addition cyclization reaction of unsaturated hydroxime [30,31,32,33], [3] condensation reactions of 1,3-dicarbonyl derivatives [34], and [4] cycloisomerization [35]. In the past decades, the 1,3-dipole cycloaddition reaction of alkenes with nitrile oxide is the most direct and extensive method for the construction of isoxazoline skeletons [36]. Nitrile oxides are usually derived from aldoximes and nitro compounds [37,38], but the common use of transition metal catalysts, such as Cu(I), Cu(II), and Ru(II), in the reaction makes the products residual metal and cytotoxic [39,40,41], which limits its application in biology and drug development (Scheme 1). Therefore, the development of practical, simple, and cost-effective new methods for synthesis 2-oxazolines would complement current methods. In the previous study, we first used the alkaline catalyst chloramine-T to catalyze the reaction of α-nitroketone and alkene to synthesize isoxazoline with a yield of $77\%$ [42]. In the present work, we report a novel synthesis of dihydroisoxazoles by p-TsOH (anhydrous)-participated 1,3-dipolar cycloaddition of isoxazoline with α-nitroketones. On one hand, compared with the strong acid (H2SO4)-catalyzed synthesis of isoxazole [43], p-TsOH gives a milder reaction condition that avoids carbonization of organic substance, and it is low in toxicity and is inexpensive. On the other hand, Natarajan Arumugam and co-workers [44] reported a good, facile, and efficient method for the rapid synthesis of fused pyrrolidine and indolizinoindole heterocycles through 1,3-dipolar cycloaddition in the presence of p-TsOH. Additionally, Zhenghui Guan and co-workers [45] also demonstrated a p-TsOH mediated 1,3-dipolar cycloaddition approach of nitroolefins and sodium azide for the synthesis of 4-aryl-NH-1,2,3-triazoles, and a slightly higher yield ($93\%$) was isolated. It is an efficient p-TsOH-mediated 1,3-dipole cycloaddition reaction that can tolerate a wide range of functional groups, and quickly and easily obtain the target product under mild conditions. p-TsOH was discovered as a vital additive in this type of 1,3-dipolar cycloaddition. Herein, isoxazolines, given the importance of preparing biologically active molecules, are chosen for validation of the accessibility, operational simplicity, and atom economy of our method. ## 2.1. Optimization of the Reaction Conditions First, we compared the effects of different acids and solvents. The reaction of benzoylnitromethane 1a with allylbenzene 2a to form isoxazoline 3a was performed and the results were summarized in Table 1. It is noted that the reaction without acid did not proceed. In the presence of various acids, i.e., HCl, HNO3, H2SO4, TFA, H3PO4, fluoroboric acid, MsOH, and p-TsOH, the yield was significantly improved. It appears that oxidative acids produced similar good yield (Table 1, entries 3 and 4), but reagents used there are expensive, toxic, and dangerous. It was found that MsOH in i-PrOH at 80 °C effectively promoted the formation desired isooxazoline. However, the yield of 3a was slightly lower than that of p-TsOH (LD50: 1410 mg/kg) (Table 1, entries 8 and 9), and MsOH (LD50: 200 mg/kg) is highly toxic. Therefore, p-TsOH, which is non-oxidizing, corrosive, and low toxic was selected to participate in the synthesis of isoxazoline with a yield of $67\%$. While among the five tested solvents (ACN, i-PrOH, DMF, DMSO, and H2O), it was found that the yield reduced significantly with the relative polarity of the solvent (Table 1, entries 9–13) and can obviously is the best solvent. The reaction temperature and amount of p-TsOH were further optimized. The results were shown in Figure 2. Then, the optimal condition was regarded acanACN as solvent, 4 equiv of p-TsOH was involved in the reaction at 80 °C for 22 h, in which a good yield of $90\%$ could be obtained. ## 2.2. Substrate Scope Studies With the optimal reaction conditions, we first tested the 1,3-dipolar addition reaction for benzoyl nitromethane and allylbenzene and had a yield of product of $90\%$. Then, to examine the generality and scopes of this methodology, we took a variety of benzoylnitromethane derivatives 1 (Scheme 2) and allylbenzene 2a as substrates and representative results were shown in Scheme 2. These results showed that a variety of electronically varied aromatic α-nitroketones were well compatible with the cycloaddition in all the reactions, and reaction generally obtains in moderate to good yields for the synthesis of isoxazoline derivatives. Moreover, in this reaction, we found a good regioselectivity, which was consistent with the work of Ken-ichi Itoh [45]. At first, it was found that the R1 substituents would affect the cycloaddition efficiency in these reactions. The electron-rich α-nitroketones (1e, 1g, Scheme 2) provided products (3e, 3g, Scheme 2) in slightly better yields in comparison to the electron-deficient ones (1d, 1f, 1i, Scheme 2). Different electron-withdrawing substituents at the same position of phenyl-α-nitroketone resulted in similar yields (3d, 3i, Scheme 2). Additionally, surprisingly, isoxazoline derivative (3f, Scheme 2) were obtained in moderate yields when electron-donating group(-OMe) were used with a yield of $66\%$, which was close to the yield of isoxazoline obtained by electron-deficient α-nitroketone. In the case of electron-deficient α-nitroketone, the corresponding were obtained in good yields (3b–3d, Scheme 2), respectively $73\%$, $70\%$, and $67\%$. The results show that the position of the substituent has no effect on the reaction results. Additionally, aromatic substrate, such as benzene, behaved similar to an electron-withdrawing substituents and gave a yield of $68\%$ for product 3h. However, the reaction rate was slower than that of aliphatic substituted substrates. Next, we also investigated the scope of the alkenes (Table 2). The reaction of 1a with alkenes derivatives 4 was carried out under the optimum reaction conditions whose results are shown in Table 2. All the reactions gave 5a–5f as product, respectively, in good to excellent yield, except 5f. The type of reaction substrate alkenes was modified, and it was found that the reaction proceeded well with both aliphatic alkenes and aromatic alkenes affording isoxazolines in good yields from the same α-nitroketone (entries 1–5, Table 2). In addition, cycloaddition of cyclohexene (4f) with benzoylnitromethane (1a) could also be achieved in fairly good yields, the corresponding isoxazoline 5f was obtained in $69\%$ yield (entry 6, 5f, Table 2). In addition, in order to expand the applicability of the reaction, we further examined the types of reaction materials. Isoxazolines were synthesized using the dipolarophiles 2a (allylbenzene) and alkyl nitroketones 6 (Scheme 3). The results showed that in the presence of p-TsOH, alkyl nitroketones were also able to react with dipolar reagents to obtain isoxazoline derivatives; unfortunately, compared with 3 and 5 phenylisoxazoline, 7a and 7b yields were lower, $23\%$ and $20\%$, respectively. Finally, the alkyen 8 was used for the reaction with α-nitroketone (1a) under the optimized reaction conditions, which obtained in excellent yields Isoxazoles. Under the same conditions, the reaction rate with alkyen was quicker than with alkenes. Nevertheless, 9a and 9b were obtained in $85\%$ and $88\%$ yield, respectively (Scheme 4). ## 2.3. Mechanistic Studies After screening the reaction conditions and studying the application of the products, the reaction mechanism was also studied. On the basis of the reaction mechanism reported by Ken-ichi Itoh et al. [ 46,47]. We proposed the theory of 1,3-dipolar cycloaddition of benzoylnitromethane with allylbenzene was deduced as follows (Scheme 5): In this reaction, α-nitroketones are converted to nitroso cations in the presence of non-aqueous phase protons, then nitrile oxides are formed from nitroso cations. Finally, isoxazolines and their derivatives are obtained by intermolecular the 1,3-dipolar cycloaddition cyclization of dipolarophiles (alkenes or alkynes) and nitrile oxide. ## 3.1. General Experimental Methods The structures of produced compounds were firmly confirmed by 13C NMR and 1HNMR spectra, and supported by HRMS, and IR data (see the Supplementary Materials). 1H NMR (400 MHz) and 13C NMR (101 MHz) were recorded at room temperature on DRX-400 spectrometer (Bruker, Saarbrücken, Saarland, Germany) in CDCl3. The chemical shifts are given in parts per million (ppm) on the delta (δ) scale. The solvent peak was used as a reference value, for 1H NMR: CDCl3 δH 7.26; for 13C NMR: CDCl3 δC 77.16 ppm. IR spectra were recorded using an Avatar 360 FT-IR ESP spectrometer (Nicolet, Madison, Wisconsin, USA) at room temperature. HR-ESI-MS spectra were acquired using an Agilent 6210 ESI/TOF mass spectrometer (Agilent Technologies, Santa Clara, CA, USA). Analytical TLC was conducted on silica gel plates (GF254, Yantai Institute of Chemical Technology, Yantai, China). Spots on the plates were observed under UV light. Column chromatography was performed on silica gel (200~300 mesh and 300~400 mesh; Qingdao Marine Chemical Factory, Qingdao, China). Super-dry solvent i-PrOH, ACN, DMSO and DMF were purchased from Aldrich and used as supplied. The α-nitroketones were synthesized using the same method as reported in the literature [48,49]. ## 3.2. General Procedure for the Cycloaddition of Alkenes and α-Nitroketones p-TsOH (0.500 mmol, 4 equiv) was added to a solution of 1 (0.125 mmol, 1 equiv) or 6 (0.125 mmol, 1 equiv) and 2 (0.625 mmol, 5 equiv) (or 4 (0.625 mmol, 5 equiv) or 8 (0.625 mmol, 5 equiv)) in ACN (0.2 mL). The mixture was then stirred at 80 °C until the starting material disappeared as monitored by TLC. Subsequently, the mixture was directly purified by flash chromatography (with ethyl acetate/petroleum ether as the eluent) to obtain the desired product (3, 5, 7 or 9). ## 4. Conclusions In conclusion, we have developed an efficient cycloaddition of a variety of α-nitroketones with alkenes or alkyne using inexpensive and gentle acid. Among the synthesized compounds, the yield of cycloaddition products of substituted phenylnitroketone is high (66–90 %), while the yield of cycloaddition products of alkyl nitroketones (such as 7a–b) is low (20–23 %). This synthesis is based on cycloaddition 1,3-dipolar in presence of p-TsOH, which is attractive that the low cost, simple synthetic route, and ease of handling of the gentle acid. It is particularly noteworthy that the reaction provides an effective synthesis method for 3-carbonylisoxazolines. The development of other methods for the synthesis of 3-carbonylisoxazoline is currently under investigation and will be disclosed in due course. ## Figures, Schemes and Tables Figure 1: Structures of isooxazolines with bioactivity. Scheme 1: Overview of the 1,3-dipolar cycloaddition of hydrocarbons and α-nitro ketones [36,39]. Figure 2: Optimization of the reaction conditions. (a) The effect of various equivalence of p-TsOH; (b) The effect of various temperature. The amount of p-TsOH was 0.5 mmol. General conditions: 1a (0.125 mmol), 2a (0.625 mmol), ACN (0.2 mL) at 80 °C or indicated temperature for 22 h. Scheme 2: Scopes of the substituted phenylnitroketones. 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--- title: Industrial and Ruminant Trans-Fatty Acids-Enriched Diets Differentially Modulate the Microbiome and Fecal Metabolites in C57BL/6 Mice authors: - Farzad Mohammadi - Miranda Green - Emma Tolsdorf - Karine Greffard - Mickael Leclercq - Jean-François Bilodeau - Arnaud Droit - Jane Foster - Nicolas Bertrand - Iwona Rudkowska journal: Nutrients year: 2023 pmcid: PMC10052023 doi: 10.3390/nu15061433 license: CC BY 4.0 --- # Industrial and Ruminant Trans-Fatty Acids-Enriched Diets Differentially Modulate the Microbiome and Fecal Metabolites in C57BL/6 Mice ## Abstract Industrially originated trans-fatty acids (I-tFAs), such as elaidic acid (EA), and ruminant trans-fatty acids (R-tFAs), such as trans-palmitoleic acid (TPA), may have opposite effects on metabolic health. The objective was to compare the effects of consuming 2–$3\%$ I-tFA or R-tFA on the gut microbiome and fecal metabolite profile in mice after 7 and 28 days. Forty C57BL/6 mice were assigned to one of the four prepared formulations: lecithin nanovesicles, lecithin nanovesicles with EA or TPA, or water. Fecal samples and animals’ weights were collected on days 0, 7, and 28. Fecal samples were used to determine gut microbiome profiles by 16S rRNA sequencing and metabolite concentrations by GC/MS. At 28 days, TPA intake decreased the abundance of Staphylococcus sp55 but increased Staphylococcus sp119. EA intake also increased the abundance of Staphylococcus sp119 but decreased Ruminococcaceae UCG-014, Lachnospiraceae, and Clostridium sensu stricto 1 at 28 days. Fecal short-chain fatty acids were increased after TPA while decreased after EA after 7 and 28 days. This study shows that TPA and EA modify the abundance of specific microbial taxa and fecal metabolite profiles in distinct ways. ## 1. Introduction Trans-fatty acids (tFAs) are known for their adverse physiological effects [1]. Nevertheless, not all tFAs have the same effects on metabolism [2]. Specifically, tFAs include industrial tFAs (I-tFAs) that are made by partial hydrogenation of oil in the industry, such as elaidic acid (EA; trans-18:1n-9) [3], and ruminant tFAs (R-tFAs) produced by bacterial hydrogenation of unsaturated fatty acids, such as trans-palmitoleic acid (TPA, trans-16:1n-7) and trans-vaccenic acid (TVA, trans-18:1n-7) [3]. The global consumption of tFA is reported to represent $1.4\%$ of the total energy intake (0.2–$6.5\%$ range) [4] and is mostly I-tFAs. Indeed, consumption of R-tFAs is estimated at <$0.5\%$ of the total energy intake [5]. Contrary to I-tFAs, recent observational studies showed that circulating TPA may lower insulin resistance, atherogenic dyslipidemia, and the incidence of type 2 diabetes [6]. Nevertheless, the differences in the mechanisms of action between I-tFA and R-tFA are unknown. Modifications in the gut microbiome (GM) may be potential novel mechanisms that may modulate the effects of I-tFA and R-tFA on metabolic pathways. Indeed, quantitative and qualitative compositions of GM have been shown to be related to insulin resistance [7], inflammatory [8], and metabolic syndrome pathways [9]. Microbiota–host interactions influence nutrient uptake and impact host metabolism. Dietary nutrients undergo microbial fermentation, resulting in the production of metabolites, such as short-chain fatty acids (SCFAs). For example, butyrate, one of the major SCFAs, is known for its various physiological functions: serving as fuel for colonic epithelial cells, inducing the proliferation of intestinal cells, and acting as an anti-inflammatory immune modulator [10]. Moreover, bacterial fermentation of branched amino acids, such as valine, leucine, and isoleucine, results in branched SCFAs. Thus, identifying key bacterial taxa that respond to nutrients is important for understanding the impact of dietary factors on host health. In addition, investigation of fecal metabolomics provides functional readouts of the metabolic interplay between the host, diet, and the GM and may complement sequencing-based approaches. Notably, fecal metabolites have been used as biomarkers of metabolic disorders, such as type 2 diabetes and inflammation, in animal and human studies [11,12]. Previously, the respective effects of I-tFA and R-tFA on changes in GM and fecal metabolites have been investigated. First, the intake of EA (I-tFA, diet containing low ($4\%$) or high ($23\%$) levels of partially hydrogenated soybean oil) was shown to increase the abundance of harmful bacteria such as Proteobacteria in C57BL/6 mice for 8 weeks [1]. The same study demonstrated that EA also numerically decreased fecal butyric and valeric acids [1]. In another study, results show that the consumption of a diet rich in Decaisnea insignis seed oil that composed of $55\%$ palmitoleic acid (16:1n-7), $12\%$ palmitic acid (C16:0), and $29\%$ oleic acid (C18:1, $$n = 9$$) of total fat (3–12 g/kg) increased the abundance of beneficial bacteria such as Lactobacillus after 12 weeks in Kunming male mice [13]. Yet, to our knowledge, there is no study that directly compares the effects of I-tFA and R-tFA on GM and fecal metabolites profiles to examine the potential mechanisms of action. Thus, it is hypothesized that the intake of I-tFA and R-tFA will differentially modify GM and fecal metabolites profiles. Specifically, the main objective of the study is to examine differences in GM and fecal metabolites profiles after intakes of 2–$3\%$ of the total energy of EA (I-tFA) or TPA (R-tFA) for 7 and 28 days in C57BL/6 mice. Yet, it is well known that assessment of oral intake of a solid diet needs individual housing of animals, as well as frequent weighing of mangers which makes it difficult to use solid diet [14]. Therefore, delivering fatty acids in the form of solutions has been suggested as an alternative method [15]; however, this strategy does not address the poor solubility of fatty acids in the watery environment of the gastrointestinal tract. Consequently, nanovesicles prepared by hydration of lipid films followed by extrusion through polycarbonate membranes have been proposed to overcome this challenge. Here, we implement these lipid nanovesicles to understand the full impact of lipid delivery on GM and metabolite factors and assess their effectiveness as a nutrient vehicle in vivo. ## 2.1. Materials EA and TPA, which are free fatty acids with a purity of over $99\%$, were obtained from Nu-check Prep, Inc. (Elysian, MN, USA) under product numbers U-47-A, U-49-A, and U-41-A, respectively. Soy lecithin Ultralec® F ($97\%$ purity, CAS# 8030-76-0, product no: 2516, Medisca, Montréal, QC, Canada) was generously donated by Medisca, Inc. The commercial Teklad Global $18\%$ Protein Rodent Diet, which was adjusted for calories, with $58\%$ of calories from carbohydrates, $24\%$ from proteins, and $18\%$ from fats, was purchased from Envigo International Holdings, Inc. (Madison, WI, USA). Further details about the diet can be found online (www.envigo.com (accessed on 11 March 2023)). All remaining reagents and solvents were procured from Sigma-Aldrich (St. Louis, MO, USA) or Fisher Scientific (Waltham, MA, USA). ## 2.2. tFA Preparation Lipid film technique is adapted from common methodologies used to fabricate liposomes [16]. Briefly, soy lecithin and tFA (EA and TPA) were added to chloroform/methanol (8:2 v/v) or methanol to reach a concentration of 40 mg/mL in a round-bottom flask. A mixture of lecithin and tFA solutions for each single fatty acid at a ratio of 86:14 (w/w) was prepared [17]. The solvent was removed on a rotary evaporator, and the lipid film was hydrated with distilled water. The vesicles were extruded on 400, 200, and 100 nm polycarbonate filters, using a Liposofast-50 high-pressure extruder (Avestin, ON, Canada). The composition of fatty acid in vesicle formulations was determined by gas chromatography as previously described by Chotard et al. [ 17]. ## 2.3. Animals and Diets All animal experiments in this study were carried out in accordance with the guidelines of the Canadian Council on Animal Care and approved by Université Laval (Protocol #17-019-3). Seven-week-old healthy male mice were purchased from Charles River (Saint-Constant, QC, Canada) and housed in a facility with a controlled environment (22 °C, 12 h day/night cycle) with ad libitum access to food and water. Forty C57BL/6 mice were divided into four equal groups. Each group was given a normal diet (Teklad Global $18\%$ Protein Rodent Diet, Envigo, Madison, WI, USA) with water, blank nanovesicles (only lecithin) as a negative control group or different formulations of tFA: containing 14 wt% TPA or EA. Animals were followed for 28 days. All vesicle formulations had a phospholipid concentration of 1 wt%. The diet was standardized across all groups, and the only variation was in the solutions provided for the animals to consume. Animal weight was measured every 3 days and fecal samples were collected at days 0, 7, and 28 for further analysis on short- and long-term changes in microbiota and metabolites [18,19,20]. ## 2.4. 16S rRNA Sequencing and Amplicon Sequence Variant (ASV) Processing Bacterial DNA was isolated from cecal and fecal samples utilizing methods that have been previously reported, albeit with some modifications [21]. Briefly, the samples were initially transferred into screw cap tubes that contained 2.8 mm ceramic beads, 0.1 mm glass beads, GES, and sodium phosphate buffer, in agreement with the reported procedures. Following this, the samples were subjected to bead beating and centrifugation, with the supernatant subsequently subjected to further processing through utilization of the MagMAX Express 96-Deep Well Magnetic Particle Processor (Applied Biosystems, Waltham, MA, USA) along with the Multi-Sample kit (Life Technologies #4413022, Carlsbad, CA, USA)). Amplification of the 16S rRNA gene sequences was performed in accordance with published protocols, incorporating modifications that were described by Whelan et al. [ 22,23]. For this process, 50 ng of DNA was used as a template with 1U of Taq polymerase (Thermofisher, Waltham, MA, USA), 1x buffer, 1.5 mM MgCl2, 0.4 mg/mL BSA, 0.2 mM dNTPs, and 5 pmol each of 341F and 806R Illumina adapted primers. The reaction was carried out with an initial step at 94 °C for 5 min, followed by five cycles of 94 °C for 30 s, 47 °C for 30 s, and 72 °C for 40 s. Another 25 cycles were executed at 94 °C for 30 s, 50 °C for 30 s, and 72 °C for 40 s, with a final extension of 72 °C for 10 min. The resulting PCR products were visualized on a $1.5\%$ agarose gel to verify amplicon size. Positive amplicons were normalized using the SequalPrep normalization kit (ThermoFisher #A1051001, Waltham, MA, USA) and sequenced on the Illumina MiSeq platform at the McMaster Genomics Facility (Hamilton, ON, Canada). The raw FASTQ files from Illumina were subsequently processed through DADA2, a Bioconductor package [24,25]. The sequences underwent truncation, removal of PCR primers, and discarding of expected errors. The estimation of the error rates of the sequences was accomplished using the learnErrors function. The filtered sequences were then dereplicated using the derepFastq function, and unique sequences were generated. The generation of amplicon sequence variants (ASVs) from the sequences was accomplished using the dada function. The forward and reverse reads were independently processed. Using the mergePairs function, reverse and forward reads were merged to refine ASVs, in which a count table was then generated. Chimeric sequences were removed using the removeBimeraDenovo function [24,25]. Taxonomic assignments up to the genus level were made using the Ribosomal Database Project (RDP) classifier and Silvia reference database (version 1.3.8). To prepare for further analysis, the ASV table was generated by removing singleton ASVs with the use of the phyloseq package in R. ## 2.5.1. Analysis of SCFA Samples were prepared in a 20 mL headspace screw cap bottle containing 400 mg of sodium chloride, 71 µL of phosphoric acid $85\%$, and 910 µL of water. A volume of 19 µL of an internal standard, 2-ethylbutyric acid (1.11 mg/mL) purchased from Fisher Scientific (Waltham, MA, USA) was added to the sample. Finally, 5 mg of freeze-dried feces sample was added and shacked at low speed for 5 min. Volatile Free Acid Mix from Sigma (Oakville, ON, Canada) containing acetic, propionic, butyric, isobutyric, isovaleric, valeric, isocaproic, caproic, and heptanoic acids was used to build a calibration curve. The standard solutions were prepared similarly to samples by counterbalancing the amount of water added to reach a total volume of 1 mL. Sample analysis by headspace injection was carried out with Pal 3 injection system and performed on an Agilent gas chromatograph (GC) 7890B coupled with a single quadrupole mass spectrometer 5977B (Santa Clara, CA, USA). Headspace stability was reached by a 40-min incubation at 85 °C under agitation. A sample volume of 1 mL was introduced with a split ratio (3:1) into the injector set at 250 °C. The carrier gas (helium) flow rate was fixed at 1.75 mL/min. Chromatographic separation was accomplished with an HP-Innowax column (30 m × 0.25 mm × 0.25 m) from Agilent with the following oven program. The initial temperature of 50 °C was held for 8 min and increased to 260 °C at a rate of 30 °C/min. The oven remained at this final temperature for 5 min. Mass spectra were recorded in scan mode (29–200 amu) with an electron impact ion source set at 70 eV. ## 2.5.2. Analysis of Other Metabolites Analysis of other metabolites was carried out as previously described [19] with few modifications for feces. Briefly, 1 mg of freeze-dried feces was mixed with 20 µL of a xylose solution in water and 20 µL of myristic-d27 and δ-tocopherol solution in ethanol as internal standards, each compound at a concentration of 0.05 mg/mL. To prevent oxidation, 15 µL of butyl-hydroxy-toluene ($1\%$ w/v in ethanol) was also added. A first extraction was performed by adding cold solvents (−20 °C): 150 µL of methanol and 55 µL of ethanol. The sample was subjected to vortexing for 5 min at 4 °C, followed by centrifugation for 2 min at 16,000 rcf. The supernatant was transferred to a new tube and labeled as ‘MeOH/EtOH/H2O extract’. The resulting pellets were rinsed with 150 µL of double distilled water (mean resistivity 18.2 MΩ, Milli-Q, Millipore, Etobicoke, ON, Canada) and vortexed and centrifuged at room temperature at 16,000 rcf. The aqueous supernatant was added to the MeOH/EtOH/H2O extract and stored at 4 °C. A last extraction with 50 µL of isopropanol was carried out on the pellet, after the vertexing and centrifuging at 16,000 rcf steps; the resulting supernatant was transferred to a new tube, labelled as ‘IPA extract’ and dried. Once the alcohol evaporated, the MeOH/EtOH/H2O extract was added to the evaporated IPA extract and vortexed. A final centrifugation was carried out and the resulting supernatant was transferred to a new tube. A volume of 116 µL of the total extract was collected, corresponding to about 0.3 mg of feces of each sample was added to a new tube and the rest of the sample was used to constitute a pool for a spiked calibration curve. The two-stage derivatization process was executed in accordance with the extensive method outlined by Fiehn (Agilent Technologies, Inc., Santa Clara, CA, USA, Manual Part Number: G1676-90001, 2013). Chromatography was conducted employing an Agilent 7890B GC oven that was coupled to an MS 5977B Mass Selective Detector (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer’s instructions (Agilent Technologies, Inc., Manual Part Number: G1676-90001, 2013). Metabolites were detected utilizing the AMDIS software (version 2.71) and characterized based on their mass spectra patterns and retention index matches in the Agilent G1676AA Fiehn GC/MS Metabolomics RTL Library (Agilent Technologies, Santa Clara, CA, USA) and the NIST/EPA/NIH Mass Spectral Library (Version 2.2, 2014) (National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA). To determine quantitative values, standards of the same compound were utilized for quantification. Semiquantitative values were expressed as the ratio of the compound response (area under the curve or peak height) to that of the corresponding internal standard (compounds with the same spectral and retention time). The sole distinction between quantitative and semiquantitative approaches is that no calibration curve slope is employed in the latter. The sample contained 10 bile acids named by number considering similar defragmentation spectrums and retention times too close to allow a differential identification using the library. ## 2.6. Statistical Analyses All statistical analyses for weight change were performed with SPSS software (version 18, SPSS Inc., Chicago, IL, USA), and Shapiro–Wilk test was performed to evaluate the normality of distribution before performing statistical analyses. Continuous variables were considered for normality, and nonnormal variables were log-10 transformed for significance testing. ANOVA followed by Bonferroni post hoc test was performed to compare animal weight at days 0, 7, and 28 between each group: lecithin, EA, TPA, and water. All microbiome analysis analyses were completed within R version 3.4.3. Alpha and beta diversity were calculated using the raw ASV data using the vegan package. Alpha diversity metrics included the Inverse Simpson index and the Shannon index. Differences between strains were assessed using a Skillings–Mack test to account for incomplete block design with a significance cut-off of $p \leq 0.05.$ Pairwise differences were also assessed using a Wilcoxon post-hoc test. Beta diversity between samples was explored using principal coordinate analysis (PCoA) with Jaccard, Bray–Curtis, and Aitchison distance metrics applied to ASV count data. To assess the influence of diet on beta diversity across the supplementation period, a blocked permutational multivariate analysis of variance (PERMANOVA) was conducted using the distance metrics function adonis() from the phyloseq package, stratified such that permutations were restricted to age-matched supplementation groups. Pairwise comparisons were implemented to assess drivers of omnibus group differences significant to $p \leq 0.05.$ Prior to differential abundance analysis, ASV tables were further preprocessed using the retain resolve method, as previously described [26]. In brief, taxa were sequentially filtered and glommed to obtain a final dataset that retains biologically significant taxonomic classifications while removing noise in the form of spurious sequences and highly partitioned subgroups. Differential abundance analysis was executed using a consensus technique, combining models constructed using Linear models for Differential Abundance analysis (LinDA) [27] and a modified limma/voom pipeline [28]. All taxa were assessed for significant changes between each dietary group and the control group (H2O) across sampled timepoints. This was achieved by setting the H2O group as a baseline and testing the marginal effect of each diet (i.e., the interaction between diet and timepoint condition) at each sampling day. To account for compositionality, data were either centered log-ratio or log-ratio transformed prior to mean comparisons. Repeated measures in the LinDA and limma/voom models were accounted for by either integrating a random effect term (animal ID) into the model formula or by using the duplicateCorrelation() function, forcing the magnitude of the random effect to be the same across all taxa, respectively. Criteria for significantly different taxa between groups were set at a Benjamini–Hochberg (BH) corrected p-value < 0.05 and an effect size analog (log-2-fold change or change coefficient) of >1. A final list of consensus taxa was then constructed using the mutually significant taxa between models at each timepoint. Metabolites analyses were performed by the Metaboanalyst platform (online: www.metaboanalyst.ca (accessed on 17 January 2022)). The difference in metabolites level at baseline with day 7 and day 28 was evaluated by paired t-test for each group. p-values ≤ 0.05 were considered as statistically significant. ## 2.7. Machine Learning Analyses Supervised machine learning models were performed using BioDiscML to identify optimal relevant predictive signatures of microbiomes and metabolites. The tool reports various models and signatures with many metrics obtained through multiple evaluation methods (e.g., 10-fold cross-validation, leave-one-out cross-validation, bootstrapping). Different scenarios were conducted to find the optimal model. The scenarios were microbiome data at days 0 and 7; microbiome data at days 0, 7, and 28; metabolite data at days 0 and 7; and metabolite data at days 0, 7, and 28. ## 3.1. Fatty Acid Composition of Vesicles Is Stable Figure 1 shows the combined fatty acid composition of lecithin vesicles and the encapsulated tFA. Control vesicles are mainly composed of linoleic acid, palmitic acid, oleic acid, EA, TPA, alpha-linolenic acid, and stearic acid. tFAs encapsulated are comparable between formulations since encapsulated EA and TPA were $22.9\%$ and $21.4\%$, respectively. Overall, these results demonstrate that the composition of fatty acids in the vesicles was comparable except for EA and TPA in each corresponding vesicle. ## 3.2. Animal Weight Is Similar in All Groups Figure 2 shows animal weight for all groups. Animals had an initial (day 0) weight of 18.2, 17.2, 18.3, and 17.8 g for lecithin, EA, TPA, and water group, respectively. Animals gained 0.64, 0.02, 0.56, and 0.78 g after 7 days and 2.20, 1.60, 1.90, and 2.72 g after 28 days in lecithin, EA, TPA, and water groups, respectively. ANOVA test indicated a significant difference between EA and lecithin groups at day 28 (p-value < 0.05). Moreover, there was no significant difference between EA and TPA groups in weight. ## 3.3. tFA Intake Does Not Impact Alpha Diversity but Modifies Beta Diversity Compositional differences in GM between mice supplemented with water, lecithin vesicle, TPA, and EA were investigated by 16S rRNA gene sequencing. There were no differences in alpha diversity between supplement groups (Skillings–Mack (SM) test, $$p \leq 0.2695$$), although a decrease in alpha diversity was observed in an omnibus comparison between timepoints (SM, $p \leq 0.01$). The further pairwise comparison revealed that this result was driven by differences in the lecithin, TPA, and EA groups from day 0 to day 7 and day 0 to day 28 (Wilcoxon rank-sum test with p-value correction, $p \leq 0.01$), though no differences were observed in animals supplemented with water ($p \leq 0.1$). This is supported by visualization of the data in Figure 3a, wherein there is a notable downwards trend in alpha diversity in all intake groups, including the blank lecithin, while in the water group alpha diversity remains relatively constant over time. Despite a lack of discernable clustering of samples by diet in Bray–Curtis ordination plots (Figure 3b), there was an effect of diet group on beta diversity ($p \leq 0.05$, blocked PERMANOVA). However, Figure 3b also presents a notable shift in microbiome composition across sampling timepoints, which was also significant ($p \leq 0.001$, blocked PERMANOVA). Omnibus differences in diet were driven by only a few group-wise differences, including water vs. lecithin and lecithin vs. TPA at day 7 ($p \leq 0.05$) as well as water vs. lecithin and lecithin vs. EA at day 28 ($p \leq 0.05$). Pairwise comparisons also revealed that longitudinal shifts in composition were present in groups supplemented with EA ($p \leq 0.05$, day 0 to day 7 and day 0 to day 28), lecithin, and TPA (both $p \leq 0.05$ from day 0 to day 7, day 0 to day 28, and day 7 to day 28), but not in the water-supplemented group. Together, these findings suggest that although subtle shifts in the GM may occur with tFA intake, these changes are not significant at the levels of overall intra- and inter-sample microbiome diversity and are not substantially different from changes introduced by supplementing with blank lecithin. ## 3.4. tFA Intake Impacts Abundance of Select ASVs To explore more fine-grained impacts of tFA intake on the microbiome, we conducted a differential abundance (DA) analysis that compared differences in ASV-level microbial abundance between supplement groups and water across sampling timepoints. The results of this analysis are shown in Figure 4. According to consensus analysis (bolded circles), tFA intake impacted the abundance of 9 ASVs at day 7 and 13 ASVs at day 28. However, among these ASVs, only two (Bacteroides sp47 and sp54) were uniquely impacted by either TPA or EA intake compared to the lecithin control at day 7, while only six (including Ruminococcaceae UCG-014 sp134, Bacteroides sp47 and sp54, as well as Clostridium sensu stricto sp51) met these criteria at day 28. On day 7, all three intake groups displayed a marked increase in Staphylococcus sp119, while both TPA and lecithin groups showed an increase in Ruminiclostridium 6 sp122. At day 28, Lachnospiraceae NK4A136 group sp66 displayed a decreased abundance in both the lecithin and TPA groups. Interestingly, some ASVs, such as Bacteroides sp47, were only decreased in the EA group at day 7 and only decreased in the TPA group at day 28. Furthermore, despite showing an increase across all three experimental groups at day 7, Staphylococcus sp119 only persisted at increased levels in tFA intake at day 28 but not in the lecithin group. Together, these results show that while global microbiome features were not strongly impacted by tFA intake, supplementation does alter the longitudinal community structure of specific microbial taxa that may have implications for overall functional output. ( The abundances of all the (consensus) DA taxa across diet groups and timepoints are shown in Figure S4). ## 3.5. tFA Intake Impacts on Fecal Metabolites The changes in fecal metabolites after tFA intake for 7 and 28 days compared to the baseline are presented in Figure 5. ## 3.5.1. Lipids and Fatty Acids After 7 days, TPA intake increased butyric acid. On the other hand, heptanoic acid and isocaproic acid decreased in the water, lecithin, and EA-supplemented groups after 7 days. Furthermore, the lecithin and EA intake also decreased isovaleric acid. Lecithin intake also decreased isobutyric acid and valeric acid on day 7. After 28 days, the TPA intake increased in butyric acid, isobutyric acid, and propionic acid. Oppositely, heptanoic acid and isocaproic acid decreased in the water, lecithin, and EA-supplemented groups after 28 days. Furthermore, lecithin and EA intake decreased caproic acid after 28 days. EA intake also decreased isobutyric acid, isovaleric acid, and valeric acid after 28 days. Other lipids, such as azelaic acid and palmitoleic acid, were increased with lecithin intake after 7 days. Furthermore, water intake increased palmitoleic acid and succinic semialdehyde after 7 days. After 28 days, water intake increased levels of myristic acid, elaidic, acid and methyl succinic acid. Furthermore, TPA intake increased palmitoleic acid on day 28. Finally, methyl ester was increased following EA intake after 28 days. ## 3.5.2. Carbohydrates and Derivatives Fecal glucose levels were increased on day 7 by EA intake; yet on day 28 glucose levels were increased by lecithin and TPA intake. Fructose was increased by water, TPA, and EA intake on days 7 and 28, whereas fructose was increased by lecithin only on day 28. Mannose was increased after 7 days by water intake, after 7 and 28 days by EA and TPA intake, and after 28 days by lecithin intake. Mannitol increased after 7 days by water intake along with 28 days by water and lecithin intake. Even if mannitol decreased after 7 days by EA intake, it increased after 28 days. Sucrose and sorbitol were increased on day 7 after EA intake. Lecithin increased the level of xylitol after 7 days, but water decreased levels of xylitol after 28 days. Furthermore, xylitol was decreased after 7 days by EA intake; yet, after 28 days xylitol was increased. Furthermore, ribitol decreased after 7 days when mice received EA and after 28 days when mice received TPA intake. After 7 days, water and TPA intake increased D-glucose-6-phosphate. Meanwhile, lecithin and EA intake decreased D-glucose-6-phosphate after 7 days. Furthermore, after 28 days, lecithin, TPA, and EA intake increased D-glucose-6-phosphate. Maltose levels increased after 7 days by EA intake as well as after 28 days by lecithin and TPA intake. On the other hand, lactose levels were decreased by water while it was increased by EA intake after 7 and 28 days. Still, lecithin also increased lactose on day 28. ## 3.5.3. Amino Acids and Derivatives Beta-glutaric acid was increased by TPA intake on day 7 and by water on day 28. Creatinine was increased on day 7 by lecithin as well as on day 28 by lecithin and water. However, creatinine was decreased by TPA intake on day 28. Cystathionine was increased by TPA intake on day 7, whereas water increased cystathionine on day 28. Glutamic acid was increased by water after 7 days and TPA intake after 28 days. In addition, N-acetyl-D-glucosamine was increased after water and EA intake only on day 7. Furthermore, EA intake increased N-acetyl-L-aspartic acid after 28 days. Water also increased N-acetyl-L-glutamic acid after both 7 and 28 days; yet TPA intake increased N-acetyl-L-glutamic acid on day 7. Furthermore, ornithine was increased after TPA intake on days 7 and 28. Additionally, lecithin increased phosphoserine on day 7. Likewise, taurine was increased by water, lecithin, and EA intake on day 7. Meanwhile, EA and TPA intake increased taurine on 28 days. Citrulline increased after TPA intake on day 28. Furthermore, 3-aminoisobutyric acid was increased by lecithin on day 28. Finally, TPA intake increased 3-methylpiperazine-2,5-dione after 28 days. ## 3.5.4. Vitamins Ascorbic acid (vitamin C) was increased after 7 days on the water diet and after 28 days on the lecithin diet. On the other hand, dehydroascorbic acid decreased following TPA intake on day 28. Alpha-tocopherol (vitamin E) was increased on the water diet after 28 days. Furthermore, ergocalciferol (vitamin D2) was decreased after lecithin intake on day 7. Nicotinic acid (vitamin B3) was increased after water intake on day 7, lecithin intake on day 28, EA intake on day 28, as well as TPA intake on days 7 and 28. Finally, pantothenic acid (vitamin B5) was decreased after TPA intake for 28 days. ## 3.5.5. Bile Acids The number of bile acids that increased was four, four, and one following water, lecithin, and TPA intake on day 7, respectively. Yet, after 28 days, only four bile acids were increased after the lecithin intake. ## 3.5.6. Purine Compounds On day 7, guanosine was increased after water and TPA intake. Further after 28 days, increased guanosine was observed after lecithin, EA, and TPA intake. Xanthine was increased following water on day 7 and lecithin intake on day 28. Hypoxanthine was increased by TPA intake after 7 and 28 days. Similarly, hypoxanthine was also increased by water on day 7 and lecithin on day 28. Inosine was increased by water and TPA intake after 7 and 28 days as well as EA intake on day 28 only. Interestingly, lecithin intake decreased and increased inosine on days 7 and 28, respectively. Uric acid was decreased after lecithin and TPA intake on day 28. ## 3.5.7. Organic Compounds Alpha-ketoglutaric acid was increased following water and TPA intake on day 7. Even though lecithin decreased the level of alpha-ketoglutaric acid on day 7; fecal alpha-ketoglutaric acid increased on day 28. Benzene acetic acid was increased after water intake on days 7 and 28. Yet, lecithin on day 7 and TPA intake on day 28 also increased benzene acetic acid. Flavin adenine dinucleotide increased after lecithin intake on day 7. Furthermore, water and TPA intake increased glycerol 1-phosphate on day 7 and lecithin increased glycerol 1-phosphate on day 28. Hydrocinnamic acid also increased following lecithin and TPA intake on day 28. Hypotaurine was increased by TPA intake after 7 and 28 days. Myo-inositol increased following lecithin intake after days 7 and 28 as well as EA intake after 28 days. On the other hand, TPA intake decreased myo-inositol and urea on day 7. Pseudo-uridine increased water control on day 7. In addition, pseudo-uridine was increased by lecithin after 28 days, even if pseudo-uridine was decreased by lecithin on day 7. Spermidine was increased by water and TPA intake on day 7 as well as lecithin on day 28. Likewise, uracil was increased after water on day 7 and lecithin on day 28. Urea was decreased by TPA intake on day 7 as well as with lecithin and TPA intake on day 28. Uridine was increased after TPA and water intake after 7 and 28 days, whereas EA increased uridine after 28 days only. Urocanic acid was increased after water on days 7 and 28, after TPA intake on day 7, and after lecithin on day 28. On day 7, lecithin decreased 1-methyl nicotinamide as well as 2-hydroxyglutaric acid even though water increased 2-hydroxyglutaric acid. Additionally, 3-indolepropionic acid was increased after lecithin and TPA intake on day 28. Next, 3-(3-hydroxyphenyl) propionic acid and 5-hydroxy indole-3-acetic acid were decreased by water and TPA intake after 7 days. Furthermore, 6-hydroxynicotinic acid was increased by lecithin on day 28. Yet, lecithin also decreased 3,4-dihydroxyphenylacetic acid after 7 days while EA intake and TPA intake increased 3,4-dihydroxyphenylacetic acid on day 28. Similarly, 4-hydroxybenzeneacetic acid was decreased after lecithin intake on day 7 and oppositely EA intake increased 4-hydroxybenzeneacetic acid on day 28. Finally, 6-hydroxynicotinic acid was increased by water and TPA intake on day 7 and by lecithin on day 28 (Figure 5). ## 3.6. Features Identified from Machine Learning Analysis as Markers of TFA Intake The best machine learning analysis results were obtained with microbiome 0, 7, and 28 days: short signature, average Matthew correlation coefficient (MCC) 0.787 (standard deviation: 0.094). In addition, a long signature was detected with an average MCC of 0.863 (standard deviation: 0.121). The best machine learning analysis results for metabolites 0, 7, and 28 days: average MCC: 0.557 (standard deviation: 0.097) and metabolites 0 and 7 days: average MCC: 0.53 (standard deviation: 0.089). Relevant features from microbiome and metabolites identified from machine learning analyses are presented in Figure 6 and Figure 7. First, Figure 6 shows a change in microbiomes, where Lachnospiraceae Lachnospiraceae NK4A136 group sp40 (day 28), Lachnospiraceae Lachnospiraceae NK4A136 sp21 (day 7), and Lactobacillaceae Lactobacillus sp57 (day 7) predicted a short signature. Figure 6 also shows Bacteroidaceae Bacteroides sp109 (day 0), Staphylococcaceae Staphylococcus sp55 (days 7 and 28), Ruminococcaceae Ruminiclostridium 6 sp122 (day 7), Lactobacillaceae Lactobacillus sp57 (day 7), Lachnospiraceae Lachnospiraceae NK4A136 group sp21 (day 7), Staphylococcaceae Staphylococcus sp55 (day 28), Lactobacillaceae Lactobacillus sp117 (day 28), Ruminococcaceae Ruminococcaceae UCG-014 sp74 (day 28), and Lachnospiraceae Lachnospiraceae NK4A136 sp66 (day 28) predict a long signature. Figure 7 shows changes in alpha-ketoglutaric acid (baseline), glucose (day 7), and arachidonic acid (day 28). Moreover, analyses identified another model in which bile acid #10 (baseline), bile acid #9 (baseline), o-phospho-L-serine (day 7), tyrosine (day 7), phytosphingosine (day 28), 1-monostearin (day 28), and pyruvic acid (day 28) were identified as biomarkers. Specific modifications in microbiomes and metabolites profiles after 7 and 28 days is shown in Figures S1 and S2. ## 4. Discussion Despite the contrasting health effects of I-tFA and R-tFA, little is known about the mechanisms by which these compounds modulate host metabolism. Consequently, this study explored the impacts of I-tFA (EA) and R-tFA (TPA) on the fecal microbiome and metabolome, implementing lipid film nanovesicles to facilitate in vivo tFA delivery. Our results show that TPA appears to have a more beneficial effect on GM compared to EA, as well as an enhanced production of beneficial fecal metabolites. Specifically, both TPA and EA increased the abundance of Staphylococcus sp119 at day 7. However, at 28 days TPA supplementation reduced its relative abundance compared to baseline, whereas abundance was further increased in EA-supplemented animals. TPA also significantly decreased the abundance of Staphylococcus sp55 at day 28 according to compositional test results. Staphylococcus is a major human pathogen and is known for its harmful effects that are related to a variety of diseases [29]. In a study in which mice were fed different types of fat ($60\%$ kcal from fat) for 16 weeks, a diet high in coconut fat increased the abundance of Staphylococcus, whereas extra-virgin olive oil decreased the abundance of Staphylococcus [30]. In another study, a diet high in fat ($58\%$, mainly coconut oil) increased Staphylococcus in 16-week-old male offspring [31]. Furthermore, the abundance of Staphylococcus was positively correlated with plasma glucose levels in humans [32] and inflammatory cytokines such as TNF-α, IL-1β, and IL-6 in BALB/c mice [33]. Overall, TPA might facilitate relative reductions in Staphylococcus with prolonged supplementation compared to EA, which in turn might relate to its anti-inflammatory properties. In addition, tFA supplementation impacted the abundance of multiple ASVs from the Ruminococcaceae family, including ASVs classified in the genus Ruminiclostridium 6 and Ruminiclostridium 9, as well as uncultured genus-level groups (UGCs) −014 and −005. However, the impact on populations of UCG-005 and Ruminiclostridium 9 only reached significance in the lecithin control group, whereas UCG-014 was significantly decreased in the EA group at day 28 and Ruminiclostridium 6 was significantly increased by TPA supplementation at day 7. In general, Ruminococcaceae consists of a group of anaerobic bacteria that exists in the colonic mucosal of healthy individuals and plays an important role in butyrate production [34]. Specifically, Ruminiclostridium is generally considered a beneficial bacterium in the gut, involved in the secretion of SCFAs and positive regulation of proper functionality and morphology of intestinal epithelial cells [35]. A previous study with C57BL/6 mice fed a high-fat diet (45 % fat) for 5 months resulted in lower numbers of Ruminiclostridium 6 [36]. Ruminiclostridium 6 abundance was also negatively correlated with cholesterol and plasma triglycerides in hamsters fed with a high-fat, high-fructose diet ($66\%$ of diet from fat) for 2 weeks [37], suggesting a potentially protective role for this taxon in the context of high-fat feeding. However, Ruminiclostridium 6 has also been shown to alter energy intake due to the positive correlation to ghrelin levels in rats receiving a high-fat diet ($60\%$, mostly from lard) [38]. Furthermore, the abundance of Ruminiclostridium 6 was also positively correlated with inflammatory factors such as TNF-α and IL-6 in SPF male BALB/c mice receiving Saikosaponin-d (a major bioactive triterpene saponin) treatment [39]. Thus, the role of Ruminiclostridium 6 in regulating host lipid metabolism and inflammation may be pleiotropic in nature and context-dependent. It should be noted, however, that the observed increase in the abundance of this genus with TPA supplementation was also observed in lecithin-supplemented controls, thus its mechanistic contribution to the metabolic effects of TPA itself remains unclear. In contrast, decreased levels of Ruminococcaceae UCG-014 have been consistently observed in studies exposing rats to high-fat diets over a prolonged period (10–12 weeks) [40,41], and it is a known beneficial bacterium because of its SCFA-producing capabilities [42]. Furthermore, Ruminococcaceae UCG-014 abundance is also negatively associated with proinflammatory cytokines, such as TNF-α and IL-6 [43]. Thus, the decreased abundance observed only in EA-supplemented animals might contribute to a decrease in SCFA production and potential metabolic perturbation. Considering these results, the diverse impacts of Ruminococcaceae genera in response to dietary lipids, either in the presence or absence of caloric surplus, warrant further exploration as a means of modulating host metabolic health. EA intake also markedly decreased the abundance of Clostridium sensu stricto sp51. Clostridium sensu stricto belongs to the order Clostridiales, which produces butyrate by fermentation, metabolizing carbohydrates and amino acids [44,45,46,47]. However, Clostridium sensu stricto 1 has also been characterized as an opportunistic pathogen and has been linked to intestinal inflammation and the development of necrotic enteritis (NE) [48,49]. Additionally, the abundance of Clostridium sensu stricto was increased in Wistar rats when fed a high-fat diet (containing 40 kcal%) from soybeans and lard for 8 weeks [50]. These existing data appear to conflict with the suppression of this pathogen in the EA-supplemented group, where one might expect I-tFA to promote pathogen outgrowth due to its inflammatory properties. However, this may suggest an interaction between Clostridium sensu stricto and populations of other pathogens, such as the aforementioned Staphylococcus genus, which shows a marked increase with EA supplementation. Indeed, previous experiments implementing side-by-side challenge models have demonstrated that Clostridium sensu stricto is sensitive to the presence of other competing pathogens, and its populations can be suppressed by coinfection with other opportunistic taxa [48]. EA may thus provide a competitive advantage to specific pathogenic strains, subtly disrupting microbiome structure with downstream metabolic effects. In parallel, SCFAs including caproic, heptanoic, isobutyric, isocaproic, isovaleric, and valeric acids decreased after EA intake. Oppositely, TPA intake increased SCFAs, particularly butyric, isobutyric, and propionic acids. Similarly, a study showed that EA (low ($4\%$) or high levels ($23\%$) of partially hydrogenated soybean oil in diet) decreased fecal butyric acid and valeric acid [1]. SCFAs act as signaling molecules on both the gut cells and other tissue cells [51]. Butyrate is an essential fuel source for colonocytes, whereas propionate is mainly taken up by the liver and utilized as a substrate for lipogenesis as well as gluconeogenesis [52]. Beneficial effects of higher SCFAs have been shown on different pathways of host physiology, such as improved weight loss, glycemic control, and improved metabolism [53,54,55]. Overall, the increase in the production of SCFAs might be due to a higher availability of TPA for gut bacteria since GM did not change the abundance of species of bacteria known to influence SCFA production; yet more studies are needed. After 28 days of exposure to lecithin and TPA, an increase in IPA was observed. The IPA is a metabolite derived from the tryptophan metabolism by the gut bacteria [56]. This indole derivative has been shown to decrease gut inflammation, prevent gut barrier dysfunction through aryl hydrocarbon receptor (AhR) activation, and modulate the secretion of glucagon-like peptide-1 (GLP-1) [57]. Therefore, IPA production may be involved in modulating host inflammation and thus contributes to the metabolic effects of tFAs. Results also demonstrate changes in the concentrations of sugar acids and polyols in fecal content in both EA- and TPA-treated groups. Specifically, after 7 days of EA intake, polyols including mannitol, xylitol, ribitol, and sorbitol were decreased which may be due to an increase in the abundance of Clostridia [58]. Similar to GM results changes in sugar acids and polyols concentrations did not persist after 28 days. For TPA intake, only ribitol was decreased after 28 days; yet other sugars were increased. Ribitol is a part of the chemical structure of riboflavin (vitamin B2) which contributes to energy metabolism [59]. Furthermore, myo-inositol levels in feces were increased after EA. Previous work has shown that the depletion of intracellular myo-inositol levels has been associated with glucose homeostasis, insulin resistance, and diabetes complications [60]. Therefore, dietary EA and TPA exposure may modify energy metabolism pathways. Creatinine was increased in EA but decreased after TPA intake. Fecal creatinine excretion is elevated when there is a breakdown product of creatine phosphate from muscle and protein metabolism. The results show that TPA intake also decreased urea and increased citrulline in feces short term. Urea is a byproduct from purines and amino acid degradation and usually produces free ammonia when degraded by bacterial urease [61]. Citrulline, a nonprotein amino acid, is involved in the urea cycle as well as arginine and nitric oxide metabolism. TPA also decreased fecal uric acid and increased hypoxanthine. High blood concentrations of uric acid are associated with diabetes and the formation of ammonium acid urate kidney stones [62]. Hypoxanthine is an important substrate for colon barrier function, mucosal repair ability, and a healthy microbiota [63]. In addition, fecal glutamic acid was increased after 28 days of TPA intake. The higher level of blood glutamic acid is associated with a higher Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), indicating lower insulin sensitivity [64]. An increase in fecal ornithine was observed in the TPA group. One study reported that administration of ornithine to mice resulted in mucin secretion, cell proliferation, and goblet cell production, which overall improved intestinal health [65]. Fecal hypotaurine was also increased in the TPA group. Hypotaurine is a transition product in the taurine biosynthetic pathway and has an antioxidant activity [66]. Overall, the metabolism of TPA differs from the EA-treated group; however, whether the concentrations in fecal metabolites corresponded to the changes in the levels in plasma metabolites and their impact on health remain to be investigated. Results from ML analysis indicate that specific features of the GM, such as the abundance of Lachnospiraceae NK4A136 group sp21, Lactobacillus sp57, and Bacteroides sp109, may predict the various tFA intake. Lachnospiraceae are known for their beneficial effects, particularly through the production of butyrate [67]. In one study, a diet high ($23.60\%$) in I-tFA from partially hydrogenated soybean oil resulted in a decrease in Lachnospiraceae after 8 weeks [1]. Similarly, in another study in which mice received $60\%$ of energy from fat (mainly lard), a lower amount of Lachnospiraceae was observed after 9 weeks [68]. Lachnospiraceae appears to be positively associated with unsaturated fat intake and negatively associated with triglycerides and I-tFA exposure [69,70]. Lactobacillus is a group of probiotic bacteria known for their beneficial effects by improving the bioavailability of nutrients [71]. Studies have previously shown that supplementation with omega-3 polyunsaturated fatty acids (PUFAs) in the form of fish oil for 15 days increased the amount of Lactobacillus [72]. In contrast, in a study in which cells were cultured with EA at concentrations of 100, 200, and 500 mg/L for 24 h, Lactobacillus decreased [73]. Interestingly, the combination of EA and vaccenic acids (a form of R-tFA) was able to improve the growth of Lactobacillus [74]. These results align with the expansion of putative opportunistic pathogens in the EA-supplemented group of the present experiment, which have been shown to concurrently decrement Lactobacillus populations [48]. Similarly, the features of the fecal metabolites may also help to distinguish the effects of different tFAs. Numerous bile acids, which are natural detergents mainly involved in facilitating the absorption of dietary fat, were identified features in the ML signature. Other metabolites in this signature included compounds involved in the metabolism of energy, carbohydrates, proteins, and fats. Arachidonic acid (fatty acids) may also contribute to inflammation by producing mediators [75,76]. Finally, 1-monostearin (also known as 1-stearoyl-rac-glycerol) is formed as a byproduct in the breakdown of fats. Thus, the modification in these fecal metabolites may be related to biomarkers of tFA intake or to changes in metabolism after tFA intake. Further studies should examine if these features may predict the intake of tFA, either EA or TPA. Potential limitations and strengths of the study should be considered. First, a cage-to-cage difference might impact the composition since the GM composition is highly sensitive [77]. However, the other potential environmental factors that affect GM composition such as diets, water, light, temperature, bedding, humidity, cage-changing frequency, and animal handlers were controlled for all groups. Another significant limitation of the study is that the vesicles were prepared using lipid films obtained by the evaporation of organic solvents. With this synthesis method, traces of residual solvents (ppm) can remain in the formulation, despite the most thorough evaporation methods [78]. The effects of residual solvent on GM remain unknown. In addition, DA analysis revealed that many bacterial taxa impacted by tFA were also impacted by supplementation with the lecithin vehicle, further hindering our ability to draw conclusions about the effects of tFA on GM. Finally, large amounts of variation in group-wise baseline measurements (day 0) of specific taxa may have confounded longitudinal DA results and presented further challenges in interpreting compositional changes to the data. The major strength is the physiological dose of the tFA received (2.1–$3.2\%$ of total energy intake) which is equivalent to a realistic consumption. However, it is important to note that 76–$99\%$ of dietary fat is absorbed in the small intestine and does not reach the large intestine [79]. Therefore, tFAs absorbed could further contribute additional effects on health due to other mechanisms. ## 5. Conclusions To conclude, the impact of tFA on GM and fecal metabolites varies depending on the type of tFA ingested. Specifically, the findings indicate that the intake of TPA may lead to improvements in the composition of GM and the production of SCFAs, which can confer health benefits to the host. In contrast, EA intake may decrease beneficial microbiomes and SCFAs. 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--- title: Epigenetic Differences Arise in Endothelial Cells Responding to Cobalt–Chromium authors: - Célio Junior da C. Fernandes - Rodrigo A. Foganholi da Silva - Gerson Santos de Almeida - Marcel Rodrigues Ferreira - Paula Bertin de Morais - Fábio Bezerra - Willian F. Zambuzzi journal: Journal of Functional Biomaterials year: 2023 pmcid: PMC10052026 doi: 10.3390/jfb14030127 license: CC BY 4.0 --- # Epigenetic Differences Arise in Endothelial Cells Responding to Cobalt–Chromium ## Abstract Cobalt–chromium (Co-Cr)-based alloys are emerging with important characteristics for use in dentistry, but the knowledge of epigenetic mechanisms in endothelial cells has barely been achieved. In order to address this issue, we have prepared a previously Co-Cr-enriched medium to further treat endothelial cells (HUVEC) for up to 72 h. Our data show there is important involvement with epigenetic machinery. Based on the data, it is believed that methylation balance in response to Co-Cr is finely modulated by DNMTs (DNA methyltransferases) and TETs (Tet methylcytosine dioxygenases), especially DNMT3B and both TET1 and TET2. Additionally, histone compaction HDAC6 (histone deacetylase 6) seems to develop a significant effect in endothelial cells. The requirement of SIRT1 seems to have a crucial role in this scenario. SIRT1 is associated with a capacity to modulate the expression of HIF-1α in response to hypoxia microenvironments, thus presenting a protective effect. As mentioned previously, cobalt is able to prevent HIF1A degradation and maintain hypoxia-related signaling in eukaryotic cells. Together, our results show, for the first time, a descriptive study reporting the relevance of epigenetic machinery in endothelial cells responding to cobalt–chromium, and it opens new perspectives to better understand their repercussions as prerequisites for driving cell adhesion, cell cycle progression, and angiogenesis surrounding this Co-Cr-based implantable device. ## 1. Introduction Biomaterials play a key role in the success of bone reconstruction, which, for decades, has been widely used in the fields of implantology, dentistry, and regenerative medicine [1]. Overall, a biomaterial can be described as a systematic material and a pharmacologically inert substance designed for implantation within a living system [2] in order to meet the requirements of regenerative procedures for the regeneration of missing tissues and organs. Among biomaterials, autologous biomaterials are considered the gold standard for treating periodontal defects and bone regeneration [3]. However, considering their limited availability, other options have been proposed and are constantly in development [4,5,6,7]. In this sense, studies have been carried out in order to propose biomaterials that can help or replace tissues in their biological functions [8], as well as to propose surface modifications to biomaterials already known, such as titanium alloys or other widely used materials in clinical procedures, such as cobalt–chromium (Co-Cr) and zirconia. It is expected that those modifications will become more bioactive materials, focusing on more appropriate biological responses from the host tissue; this is because the surface directly interacts with the surrounding tissue by promoting reactional tissue during appositional bone growth [9,10,11,12,13]. Among the surface’s modifications, dual acid etching is known to at least promote irregular topography and increase the contact area with host cells, such as osteoblasts and endothelial cells [14,15,16,17]. Over the last few years, we have demonstrated that metallic biomaterials are able to modulate the specific biological responses of surrounding tissues by driving intracellular signaling that is able to modulate gene expression in cells [18,19,20], mainly considering the cellular mechanisms of cell adhesion, proliferation, and differentiation [21,22,23,24]. Among the metallic materials used in clinical trials, Co-Cr alloys have shown that there is no cytotoxic or carcinogenic effect on responsive cells [18], and they display very interesting mechanical resistance; altogether, these characteristics are extremely attractive for alternative biomaterials to be used in humans [18,25,26,27]. Although the literature already extensively discusses these characteristics, it is barely known how the biological mechanisms triggered by these materials work considering the pleiotropy of the cells composing the surrounding tissue during osseointegration mechanisms. In addition, it is also believed that biomaterials develop antimicrobial activity on their metal surfaces, and this opens new perspectives in the development of inherent antibacterial medical devices [28,29,30,31]. Among the biological mechanisms of the challenged cells, using epigenetic marks seem to be an adequate strategy to better understand the effect of the microenvironment promoted by Co-Cr in affecting the phenotype of responsive cells. We have gained some experience on this topic by applying this strategy to other known biomaterials [32], such as titanium and zirconia [33]. Regarding Co-Cr, we have previously described its effect on fibroblasts and pre-osteoblasts, where the activity of mitogen-activated protein kinase (MAPKs) seems to be determinant in drive-cell fates. It is important to mention that cobalt mimics hypoxia, thereby preventing the degradation of hypoxia-inducible factor 1 subunit alpha (HIF1A); this environmental condition deserves more attention, mainly considering the impact of Co-Cr-enriched mediums in modulating the phenotype of endothelial cells, and it is believed to modify the epigenetic machinery. Epigenetic machinery involves the control of DNA methylation with a prominent role in transcriptional regulation, specifically regarding the silencing of a specific gene. Conversely, demethylation, which consists of the removal of a methyl group from a DNA nucleotide, may control imprinted gene expressions; at the same time, the most important carrier of epigenetic information is the post-translational modification of histones, which have emerged as one of the prime constituents of transcription regulatory machinery. Among them is the methylation and acetylation of lysine residues, although lysine ubiquitylation and serine/threonine/tyrosine phosphorylation are the main means of epigenetic control [34]. Taking into consideration the relevance of epigenetic mechanisms during cell responses to Co-Cr, we have investigated it by analyzing the expression of genes and protein content in the classical biomarkers of epigenetic pathways, such as DNA methylation (practiced by DNA methyltransferase-DNMT) and demethylation (controlled by Tet methylcytosine dioxygenase-TET) [35,36,37,38]. Conversely, we have also investigated the action of histone acetyltransferase (HAT) and histone deacetylase (HDAC) enzymes in endothelial cells. In summary, our data are a descriptive set of data highlighting the relevance of epigenetic marks in endothelial cells responding to Co-Cr, and this opens new perspectives to propose functional methodologies to better know their effects on endothelial cell viability and angiogenesis. ## 2. Materials and Methods Materials: Cobalt–chrome (Co-Cr) was obtained from SIN Implants System Company (SIN), São Paulo, Brazil. Antibodies: HDAC1 (10E2) Mouse mAb #5356; HDAC2 (3F3) Mouse mAb #5113; HDAC3 (7G6C5) Mouse mAb #3949; HDAC6 (D2E5) Rabbit mAb #7558; SirT1 (1F3) Mouse mAb #8469; SAPK/JNK antibody (phospho-Thr180/ Tyr182) #4511; GAPDH (D16H11) Rabbit mAb #5174. These were obtained from Cell Signaling (Danvers, MA, USA). DNMT1 antibody (60B1220.1), DNMT3A antibody (64B1446) (Novus Biologicals LLC, Centennial, CO, USA), TET3 antibody, anti-DNMT3B (orb372330), TET1 (orb228563), and TET2 (orb131790) were purchased from BiorByt (San Francisco, CA, USA). Anti-ERK1/ERK2 antibody (ERK-7D8) (ab54230); anti-ERK$\frac{1}{2}$ (phospho-Thr202/ Tyr204) antibody (ab214362); anti-P38 (ab7952); and anti-P38 (phospho-T180 1 Y182]) (ab4822) were obtained from Abcam (Cambridge, MA, USA). Cell culture: Human Umbilical Vein Endothelial Cells–HUVEC (ATCC-CRL-1730) was provided by ATCC and used in agreement with its recommendations. Cells were maintained in Dulbecco’s Modified Eagle’s medium (DMEM; Sigma Chemical Co., San Luis, Missouri, USA) supplemented with $10\%$ fetal calf serum (FCS; Gibco, Grand Island, NY, USA), 100 U/mL of penicillin, and 100 μg/mL of streptomycin at 37 °C in a humidified atmosphere containing $5\%$ CO2. Co-Cr-enriched medium: The conditioned medium was prepared according to ISO10993-12:2016 by incubating discs of Co-Cr in a conic tube containing DMEM without SFB for up to 24 h. Thereafter, the Co-Cr-enriched medium was harvested to further expose HUVECs [18]. Cell exposition and experimental design: The HUVEC cells (3.5 × 104/mL) were seeded in sextuplicate into 96-well plates in DMEM supplemented with $10\%$ FCS. Thereafter, after 72 h of incubation at 37 °C in a humidified atmosphere containing $5\%$ CO2, the cells were exposed to Co-Cr-enriched medium respecting the experimental design as follows: control—the cells were maintained under classical conditions; Co-Cr/Wo—the cells were treated with conditioned medium obtained from Co-Cr without DAE; Co-Cr/W—the cells were treated with conditioned medium obtained from Co-Cr discs subjected to DAE. All the cultures were incubated for 72 h at 37 °C in a humidified atmosphere containing $5\%$ CO2. Western blot: After each treatment, challenged HUVEC cells were properly washed in ice-cold PBS and the protein extracts were obtained using a lysis buffer (50 mM Tris-HCl, pH 7.4, $1\%$ Tween 20, $0.25\%$ sodium deoxycholate, 150 mM NaCl, 1 mM EGTA, 1 mmol/l Na3VO4, 1 mM NaF, and protease inhibitors (1 μg/mL aprotinin, 10 μg/mL leupeptin, and 1 mM 4-(2-aminoethyl) benzenesulfonyl fluoride)) for 2 h on ice, as described earlier [32,39]. Protein extracts were cleared by centrifugation, and the protein concentrates were properly harvested. Thereafter, the protein concentration was determined using the Lowry protein assay [40], and immediately, this sample was combined at equal volume with Laemmli buffer (2X sodium dodecyl sulfate (SDS), 100 mM Tris-HCl (pH 6.8), 200 mM dithiothreitol (DTT), $4\%$ SDS, $0.1\%$ bromophenol blue, and $20\%$ glycerol). The proteins were resolved into SDS–PAGE ($8\%$ or $10\%$) and afterward transferred to PVDF membranes (Millipore, MA, USA), which were properly blocked with $1\%$ bovine serum albumin ($2.5\%$) in Tris-buffered saline (TBS)–Tween-20 ($0.05\%$), and incubated overnight with an appropriate primary antibody at 1:1000 dilutions. After washing in TBS–Tween-20 ($0.05\%$), membranes were incubated with secondary conjugated anti-rabbit, anti-goat, or anti-mouse IgGs antibodies at 1:5000 dilutions (all in immunoblotting assays) in blocking buffer for 1 h. Immunoreactive bands were detected with an enhanced chemiluminescence (ECL) kit (Thermo Scientific, MA, USA). RNA extraction and qPCR analysis: For total mRNA extraction, HUVEC cells previously treated with conditioned medium for up to 72 h were harvested with PBS and immediately homogenized with 0.5 mL of Ambion TRIzol Reagent (Life Sciences-Fisher Scientific Inc., Waltham, MA, USA). The total RNA was extracted using the TRIzol/chloroform protocol. After RNA extraction, the concentration and purity were determined using a microplate reader (SYNERGY-HTX multi-mode reader, Biotek, Tigan St, Winooski, VT, USA). For the gene expression study, first, cDNA synthesis was performed with a high-capacity cDNA reverse transcription kit (Applied Biosystems, Foster City, CA, USA) according to the manufacturer’s instructions after DNase I treatment (Invitrogen, Carlsbad, CA, USA). Posteriorly, qPCR reactions were carried in a QuantStudio®3 Real-Time PCR (Thermo Fisher Scientific, Waltham, MA, USA) in reactions of 10 μL Syber Green Master Mix 2x-5 μL, 0.4 μM of each primer (for primers and conditions, see Table 1), 50 ng of cDNA, and nuclease-free H2O. The GAPDH gene was considered a housekeeping gene. Statistical analysis: Densitometry analysis of the immunoblots bands was performed, and the arbitrary values were represented as mean ± standard deviation (SD). They were verified using Student’s t-test (2-tailed) with $p \leq 0.05$ considered statistically significant and $p \leq 0.001$ considered highly significant. In an experiment where there were >2 groups, we used one-way ANOVA (non-parametric) with a Bonferroni post-test in order to compare all pairs of groups. In this case, the significance level was considered to be reached when α = 0.05 ($95\%$ confidence interval). The software used was GraphPad Prism version 6.0. ## 3.1. Experimental Design To assess the effect of Co-Cr on endothelial cells (HUVEC), an indirect experimental model was explored where cells received a medium previously conditioned by Co-Cr for up to 72 h (Figure 1a–d). First, we investigated the expression of genes and proteins related to enzymes that catalyze the addition (DNMTs) or removal (TETs) of a methyl group in a DNA strand in a process called DNA methylation metabolism (Figure 1e). Furthermore, the mRNA transcription mechanism can be regulated by another epigenetic marker responsible for promoting the acetylation (HATs) or deacetylation (HDACs) of histones (Figure 1g) in lysine residues in the N-terminal branch. Together, these mechanisms make the DNA strand accessible to RNA polymerase, which promotes gene transcription (Figure 1h). ## 3.2. Effect of Co-Cr-Enriched Medium on JNK Phosphorylation Figure 2 reveals the involvement of c-Jun N-terminal kinase (JNK) activation in response to the Co-Cr-enriched medium. Importantly, it seems that JNK Phosphorylation (Thr180/Tyr182) is constitutively required in endothelial cells once it becomes phosphorylated with the culture groups investigated in this study, although a significant decrease has been found in response to Co-Cr-enriched medium. ## 3.3. Effect of Co-Cr-Enriched Medium on the Protein Content of Histone Deacetylase Enzymes Additionally, for the analysis of the involvement of the methylation metabolism in DNA strands, we focused on understanding whether there is involvement with histone acetylation metabolism in endothelial cells responding to Co-Cr and if it is relevant and complimentary to previous findings looking to map the biological effect during angiogenesis. As previously reported here, histone deacetylases (HDACs) are responsible for promoting the lysine breakdown of the N-terminal region of histones and driving gene transcription. Our data show a higher expression (mRNA) of HDAC1 (Figure 3a), which also reflects the protein content (Figure 3(a’,a”)) in response to both Co-Cr_wo and Co-Cr_w, while HDAC2-related expression (Figure 3b) and protein content (Figure 3(b’,b”)) was downregulated in response to the Co-Cr medium. Additionally, both HDAC3 (Figure 4a) and HDAC6 (Figure 4b) behaviors were also investigated in this study in endothelial cells responding to Co-Cr_wo and Co-Cr_w. Our data show both HDACs genes were higher in the Co-Cr-enriched medium (Figure 4a,b), but it was reflected only in the increase in the HDAC6 protein profile (Figure 4b(’,b”)), while the HDAC3 protein content was lower in endothelial cells responding to the Co-Cr medium (Figure 4(a’,a”)). Furthermore, Sirtuin 1 (SIRT1), another protein member of the histone deacetylase family, was also addressed in this study. Our data clearly show that both Co-Cr conditions (Co-Cr_wo and Co-Cr_w) positively modulate the expression of SIRT1 in exposed endothelial cells (Figure 5), fully considering mRNA (Figure 5a) and protein content (Figure 5b,c). ## 3.4. DNA Methylation-Related DNMTs Were Investigated in Response to Co-Cr Alloys The DNA methylation enzyme family mainly consists of DNMT1, DNMT3A, and DNMT3B, and all of them were analyzed in this study. Specifically, we observed that DNMT1 is differentially expressed in response to each condition of the Co-Cr alloy investigated in this study. Regarding DNMT1, the HUVEC cells exposed to both Co-Cr conditions responded differentially; considering the qPCR technology, the expression of this gene was lower than the control in HUVECs responding to Co-Cr_wo and in an opposite way responding to Co-Cr_w (Figure 6a), while in the protein content for DNMT1, the cells treated with Co-Cr_w seemed to decrease its profile (Figure 6(a’,a”)). Regarding DNMT3A, the mRNA showed that there were no differences in cells responding to the Co-Cr_w medium, while in the cells that received the Co-Cr_wo-conditioned medium, the profile was higher (Figure 6b); considering the protein profile of DNMT3A, it showed a very similar response with DNMT1, where the group that received the Co-Cr_w medium showed a decrease in its protein content (Figure 6(b’,b”)). Furthermore, we evaluated the effects of Co-Cr-enriched media on DNMT3B expression (mRNA); we found that there were no significances between groups treated with different media in relation to the control (Figure 6c). However, the protein levels showed a significative increase in the Co-Cr_wo and Co-Cr_w groups when compared with the control (Figure 6(c’,c”)). ## 3.5. DNA Demethylation-Related TETs Were Investigated in Response to Co-Cr Alloys TETs are enzymes responsible for removing the methyl group from DNA strands, which were investigated here (Figure 7). Comparing the behavior of TET1, we verified that the Co-Cr_w-conditioned medium promoted the higher expression of mRNA (~four-fold changes; Figure 7a), but it does not reflect the protein content in response to both groups of cells exposed to Co-Cr (Figure 7(a’,a”)). Performing a very similar profile, TET2 (mRNA) was higher in response to the Co-Cr_w group (~15-fold changes; Figure 7b) compared with the control, while the protein content was higher only in response to the Co-Cr_wo group (Figure 7(b’,b”)). Altogether, it seems clear that Co-Cr requires a repertoire of genes and proteins related to epigenetic machinery in endothelial cells, and it opens new perspectives to better know their effects on the functional performance of blood vessels during angiogenesis responding to Co-Cr during its osseointegration. ## 4. Discussion Epigenetic mechanisms control the levels of gene expression and the possible phenotype changes in cells [32,41]. Specifically, epigenetic metabolism is performed by the mechanisms of acetylation, methylation, micro-RNA (miRNAs), and long non-coding RNA (lnc-RNAs) controls [42,43,44,45,46]. As angiogenesis is widely known to be decisive during bone oppositional growth during the osseointegration of biomaterials in dentistry and medicine, the goal here was to better address the epigenetic mechanism, which is able to drive the phenotype of endothelial cells responding to Co-Cr. Although there are robust reports in the literature about its physicochemical properties regarding Co-Cr, its effect on epigenetic mechanisms in endothelial cells is barely known. Our data show that Co-Cr requires DNMTs, specifically, DNMT1, which is known to be an important player during the S-phase of the cell cycle [47,48,49], while DNMT3A and DNMT3B are related during new DNA strand methylation [50,51]. Among DNMTs, Co-Cr requires significant DNMT3B involvement, as well as both TET1 and TET2, which may result in an increase in DNA demethylation. Conversely, the balance between DNMTs and TETs determines the methylation profile of DNA strands in eukaryotic cells. It is important to mention that although there is an expected proportional translation of mRNA transcripts into protein, our data bring special attention to this, which opens up the possibility of action from posttranscriptional-based mechanisms requiring miRNAs and lnc-RNAs. Another point to be considered here is the ability of proteasomes to turn over intracellular proteins such as those DNMTs and TETs. Altogether, this mechanism is new to the literature, mainly considering the potential effect of cobalt in promoting a hypoxia condition [52], and it might contribute to endothelial cell proliferation and, thus, coordinate angiogenesis. Therefore, the repercussion of this condition needs to be better investigated by looking at the behavior of epigenetic players related to cytoskeleton rearrangement, such as HDACs, which are able to modulate the polymerization of microtubules and were also discussed during cell cycle progression [53,54,55]. In this context, HDAC6 seems to have a more significant effect on endothelial cells responding to Co-Cr, and it might be related to survival and proliferative molecular mechanisms related to endothelial cells [56]. Among them, JNK is related to important cellular survival signaling that involves cytoskeleton rearrangement [57]. Finally, the requirement of SIRT1 was also another very interesting datum obtained in this study. SIRT1 is associated with a capacity to modulate the expression of HIF1A in response to hypoxia microenvironments, thus presenting a protective effect. Additionally, SIRT1, a mammalian homolog of yeast silent information regulator 2 (Sir2), is a survival factor that is involved in lifespan extension, and recently, it has been reported with respect to HIF1A, as it deacetylates its lysine residues. It is important to declare that, as SIRT1 is a druggable molecule, it might be assembled in biotechnological platforms to predict the response of cells to biomaterials. Of note, HIF1A, a transcription factor that mediates the crosstalk between angiogenesis and osteogenesis, is expected during bone growth. ## 5. Conclusions Altogether, our study brings a descriptive repertoire of molecules related to epigenetic metabolism in endothelial cells responding to Co-Cr, and it opens new perspectives to investigate whether this mechanism might affect blood vessel-related properties considering cell adhesion, cell cycle progression, and the sprouting of the vessels during the osteointegration mechanism of implantable devices. 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--- title: 'Women’s Experiences Regarding Physical Activity during the Postpartum Period: A Feminist Poststructuralist Study' authors: - Neda Akbari-Nassaji - Megan Aston - Jean Hughes - Christine Cassidy - Britney Benoit journal: Nursing Reports year: 2023 pmcid: PMC10052032 doi: 10.3390/nursrep13010041 license: CC BY 4.0 --- # Women’s Experiences Regarding Physical Activity during the Postpartum Period: A Feminist Poststructuralist Study ## Abstract Although recovery after birth can be promoted through bodily movement, many women do not engage in regular postpartum physical activity. While research studies have identified some of the reasons behind their decisions, including a lack of time, only a limited number of studies have been carried out to explore how postpartum physical activity is socially and institutionally constructed. Thus, the present study aimed to investigate the experiences of women regarding postpartum physical activity in Nova Scotia. Six postpartum mothers participated in semi-structured, virtual, in-depth interviews. Women’s experiences of postpartum physical activity were examined through a discourse analysis guided by feminist poststructuralism. The following themes were identified: (a) socialization in different ways; (b) social support; (c) mental and emotional health; and (d) being a good role model for their children. The findings indicated that all women perceived postpartum exercise as a positive behavior that can promote mental health, although some postpartum mothers experienced social isolation and a lack of support. Furthermore, social discourses about motherhood caused the personal needs of mothers to be disregarded. The results showed that collaboration among health care providers, mothers, investigators, and community groups is necessary to promote and support mothers’ engagement in postpartum physical activity. ## 1. Introduction The postpartum period is a crucial transition time, and some women find it difficult to participate in physical activity. In recent decades, numerous studies have shown that physical exercise during and after pregnancy has considerable advantages for women and their babies [1,2]. Regular physical exercise throughout the postpartum period may benefit the mental and physical health of the individual, including through weight control [3]. According to Bean and Lesser [4], women who do not have complications during and/or after childbirth can return to physical activity a few days after delivery or once they feel they are ready [4]. While many women believe that physical activity during the postpartum period can be an appropriate decision, the majority of women do not engage in physical activity after childbirth. For instance, Garshasbi et al. [ 5], in their quantitative research study involving 200 participants in Iran, found that only $3\%$ of postpartum women participated in physical activity at a moderate level. In this research study, they found that a lack of time and energy were the most significant limiting factors for engaging in postpartum physical activity [5]. The same findings were also reported by other researchers in different geographic areas including Australia, the United Kingdom, and the United States [2,6,7]. Moreover, factors including a lack of confidence and motivation were reported as the other important factors that discouraged women from engaging in postpartum physical activity [2]. Extensive research studies have focused on the benefits of exercise during pregnancy and after childbirth, or on identifying the barriers or enablers of postpartum physical activity in order to explain the reasons behind women’s decisions [2,8,9]. A few researchers have attempted to look at the issue of engaging in physical activity from social perspectives [10,11]. Krik [11] believes that society has a crucial role in affecting how behavior is undertaken by individuals, or in explaining the reason for that behavior [11]. More specifically, a limited number of studies indicate how postpartum physical activity is experienced by women and is influenced by dominant social and cultural practices, attitudes, and norms. In order to promote postpartum physical activity it is necessary to understand the beliefs, values, practices, subjectivities, and relations of power among postpartum women residing in a province of Atlantic Canada that has been predominantly constructed through a Western discourse. Feminist poststructuralism is both a theoretical lens and a research methodology [12,13,14]. It can be used to explore how discourses around physical activity after childbirth may influence individuals’ practices. In addition, it offers a rigorous way of comprehending the experiences and reasons why women choose to do exercise following childbirth. The effectiveness of feminist poststructuralism as a lens to explore beliefs, values, and practices of individuals in the postpartum period can be found in the literature [12,13]. Consequently, this study aimed to learn more about how social and institutional factors shape women’s postpartum experiences with physical activity. ## 2.1. Theoretical Framework This research study applied feminist poststructuralism as a theory [14]. Feminist poststructuralism offers a lens to understand how experiences are personally, socially, and institutionally constructed, and how different subject positions play roles in forming these experiences [15]. According to Weedon [14], “the principles of feminist poststructuralism can be applied to all discursive practices as a way of analyzing how they are structured, what power relations they produce and reproduce, where there are resistances and where we might look for weak points more open to challenge and transformation” ([14], p. 136). It can provide insight into a wide range of health issues by examining how social, institutional, and political constructs shape power relations between people [13]. Important concepts of feminist poststructuralism are language, meaning, beliefs, values, practices, subjectivity, relations of power, and agency [14,16,17]. For example, agency helps to understand how people decide in different situations through challenging or accepting different discourses or meanings associated with their experiences. How people position themselves in relation to others is considered subjectivity [13]. These concepts are used to deconstruct the social and institutional constructions [17]. Moreover, when certain tenets of feminist poststructuralism are used to deconstruct discourses, constructs, and relations of power, solutions may then be illuminated through a process of reconstruction and examination of the taken for granted [17]. ## 2.2. The Researchers A team of nurses who were experts in maternal and child health care, mental health, and marginalized populations carried out this research study. All team members had experience in applying qualitative research methods and feminist poststructuralism. All team members had experience in academic education and clinical practice. ## 2.3. The Qualitative Research Study and Participants Women who were in the postpartum period (up to 12 months after giving birth) with firsthand experiences regarding postpartum physical activity were recruited using a purposive sampling strategy. They had to be capable of speaking and comprehending English and be at least 19 years old. They also needed to live in Nova Scotia and have a phone or internet connection. As a recruiting approach, electronic poster advertising was utilized. The recruiting advert was posted on the website mumsns.ca and circulated across the website’s connected social media platforms including Twitter, Instagram, and Facebook. For accessible communication, women were given the investigator’s contact information, including their phone number and email address. Fifty postpartum women responded to this call. As the aim of the research study was to develop a comprehensive understanding of women’s experiences through in-depth interviews, and to demonstrate the effective application of the research methodology, we could only interview a limited number of postpartum women. ## 2.4. Data Collection Method Semi-structured, in-depth interviews were used to collect the data. Each interview was virtually conducted using a telephone due to the COVID-19 outbreak and restrictions. All participants had the opportunity to choose whether they wanted their interview to take place on the phone or using a video platform such as Zoom. All participants preferred to engage in interviews using a phone. All interviews were audio-tape recorded. Every interview took approximately 45–60 min. Every participant had to complete a consent form and submit information about their demographics, including their race and gender, living situation, location, and the number of children they had. Interviews were started with broad questions, after which we used probes depending on participants’ answers. All interviews were carried out by the first author. During the interview, she introduced herself as a maternal–child nurse who was a Master’s student. ## 2.5. Context of the Research Study This research was carried out in Nova Scotia, a Canadian province mostly encircled by the Atlantic Ocean. Throughout the year, the climate varies from sunny days in summer to windy and snowy weather in winter [18]. Consequently, In Nova Scotia, many outdoor activities can be limited depending on the weather. All interviews were carried out during the month of April 2021 when schools were still closed, and restaurants were just re-opening in Halifax. People were also just beginning to be vaccinated against COVID-19. Therefore, some of the participants’ experiences were impacted by the social restrictions of COVID-19 regarding staying at home. ## 2.6. Data Storage To maintain confidentiality, the first author of this paper changed all identifying information of participants. All research materials were saved electronically on a private internal OneDrive. ## 2.7. Data Analysis Transcribing was started after each interview was finished. The research team members examined the interviews independently. Notes and memos were also utilized to preserve the details of the research study. They were added to interviews after finishing each interview. Discourse analysis was employed to analyze the data. In this research study, the method of discourse analysis was guided by feminist poststructural discourse analysis, which has been recommended by Aston [12]. This open guidance explains that after identifying the beliefs, values, and practices included in the data, discourses, power relations, agency, and subjectivity should be recognized. Special attention should be paid to social, personal, or institutional discourses, and they can take several forms, such as dichotomizing, dominating, suppressing, or being invisible; nonetheless, the context has a considerable influence on them [12]. Data collection and analysis were carried out concurrently. The beliefs, values, and practices were retrieved from every quote by giving special consideration to the participants’ word selection to maintain the meaning derived from their specific experiences. Following that, the quotations related to social and institutional discourse were analyzed. Relations of power were simultaneously incorporated into understandings of how participants used their subjectivity and agency through different discourses. The research reporting adhered to the COREQ reporting guidelines for qualitative research. ## 2.8. Ethical Considerations Participants were given a complete explanation regarding the study’s aims, potential risks, and benefits, and they provided consent before the interview began. The mothers had the right to withdraw from the study whenever they wished up to one week after their interview. Given that in a qualitative research study people talk about their feelings and experiences, it might lead to anxiety and distress; thus, if a participant felt anxious or distressed due to interview questions, they were provided with a list of mental health centers they could contact if they wanted to speak with a mental health care professional. ## 3. Results Six women participated in the study, with a mean age of 34 years; the youngest mother was 20 years old and the oldest mother was 41 years old. One participant was a single parent, while the other participants lived with their husbands. One participant was from the Middle East, while five participants were white and from Canada. In terms of residency, five participants resided in cities or towns, whereas just one lived in a rural region. In terms of physical activity, for all participants the definition of physical activity was varied and ranged from walking to regular running. Resuming these activities was difficult for all participants during the postpartum period. Their babies ranged in age from 4.5 to 10 months, with an average age of 7 months. Four women had other children ranging from one to four more. The siblings ranged in age from 2 to 19 years. All participants had education levels higher than high school, ranging from community college to a Master’s degree. The identities of all participants have been altered to maintain confidentiality. The findings were grouped into the following themes: (a) socialization in different ways; (b) social support; (c) mental and emotional health; and (d) being a good role model for their children. ## 3.1. Socialization in Different Ways Almost all participants expressed that they valued socializing, yet they also expressed concerns that they had minimal opportunities to socialize. Socialization was valued by participants for a variety of reasons: Some participants liked to participate in postpartum physical activity to deal with feelings of isolation. A few participants liked to participate in postpartum physical activity to ensure the normal health and development of their babies. The other participants liked to engage in postpartum physical activity to improve their mental health. Postpartum isolation was reported by some participants, and they made an effort to interrupt this feeling by finding particular ways to meet others via physical activity. For example, Anne (participant #3) valued doing physical activity with a friend; thus, she would not feel alone and could get some exercise. She explained during the interview: Socialization for a few participants was complex. Some participants wanted to keep the children close to themselves because it gave them a sense of security, yet at the same time they wanted to engage in postpartum physical activity with another person. For Anne (participant #3), being away from her baby bothered her, as she mentioned during the interview: This participant (#3) described her postpartum situation as stressful because it was a new experience with her baby to try to figure out how best to care for him. She felt that she had to ‘be beside’ him and ‘watch’ him ‘every single second’. This made it difficult for her to leave her baby, exercise, and socialize. However, she did. Anne explained during the interview: She feels emotionally responsible for her infant, which decreased her “motivation” to exercise. Her values and beliefs about caring for her infant influenced her decision to exercise. For Anne, being a mother meant that she had to be continuously with her child. Anne believed that her subject position as a mother needed to include constant care. This might be influenced by a mothering discourse that perpetuates the idea that mothers need to be with their babies all the time in the early stages of postpartum. Anne undoubtedly shared this belief. It was this belief that was making her decision to exercise on her own away from her baby difficult. Other participants were also concerned about their socialization. For example, for Caroline (participant #6), interacting with other people gave her a sense of being healthy and “normal.” She explained that engaging in postpartum physical activity with other individuals created the opportunity for her child to interact with other children. Moreover, mothers could support each other in terms of taking care of their babies, talking about positive ideas, and getting rid of negative thoughts. Caroline’s subjectivity as a mother was evident from her notion that she, as a mother, had the responsibility to make sure that the growth and development of her baby was similar to that of other children, and that she felt she was doing her duties correctly, which gave her a sense of comfort. Caroline had been diagnosed with an anxiety disorder 15 years previously and, when she experienced isolation and doubt, wondered if this might have contributed to her concerns about what was normal and healthy for herself and her baby. This feeling of isolation was created by her postpartum circumstances of being at home without contact with other people outside of her home. This was partly created by social discourses of postpartum, in which parents are often at home by themselves with a newborn both physically and emotionally, without support from family or friends. This was also exacerbated by COVID-19 restrictions, whereby people were asked to stay home as much as possible. Caroline decided to use her agency and chose to find other parents to spend time with through physical activity, so she could talk with them and feel normal. She chose to not perpetuate the social discourse that expected mothers to be able to figure out how to take care of their newborn ‘naturally’ on their own [19]. Given that stigma towards people with mental health problems is socially constructed, mental health issues continue to be uncomfortable for people to discuss and are thereby kept invisible or silenced [20,21,22]; Rather than telling people that she had mental health issues, Caroline chose to address them by socializing with friends. ## 3.2. Social Support During the postpartum phase, all participants constructed social support in diverse ways. All participants acknowledged that it would be easier to engage in physical exercise if they had social support, which included both practical and emotional assistance. A few participants defined social support as a person who provides care for the baby or performs household duties. Without such support, it was not easy to participate in postpartum physical exercise. For one participant being away from her child was a major barrier in spite of her husband being home and providing care for the baby. For other participants the presence of other people who provided care was important. Most participants received this assistance from their partners or family members. Beth (participant #2), who was from a Middle Eastern country, mentioned that she would like to participate in postpartum physical activity but faced a lack of social and family support. This participant said: All participants made it evident that they needed social support to engage in postpartum physical activity, but for each participant the source and types of support were different. Emotional, informational, and instrumental (e.g., tangible assistance) are different types of social support [23]. Participants in this research study stated that they needed either emotional or instrumental support, or both, to engage in postpartum physical activity. For Anne (participant #3) and Sara (participant #4), social support meant a person who encouraged them to participate in postpartum physical activity, and they both received this support from their partners. Anne’s husband provided care for the baby when she was engaging in physical activity. In the following quotes, Anne explained how her husband respected her idea against social and institutional messages that “mothers should be all” for their children [24]. This support made it easier for Anne to decide to engage in postpartum physical activity. She explained during the interview: Sara valued postpartum physical activity and believed that mothers should overcome challenges that prevented them from doing physical activity by getting help and support from their partners, friends, family members, or community. Sara explained during the interview: Caroline believed that women needed family support in order to be able to do postpartum physical activity: However, despite believing that postpartum physical activity is significant, Caroline had limited engagement in it due to the challenges she faced as she explained during the interview: Caroline’s words illustrated again that postpartum women were in need of instrumental and emotional support to engage in physical activity. ## 3.3. Mental and Emotional Health All participants noted that they liked to participate in postpartum physical activity in order to experience feeling “happy” and having “fun”. For all postpartum mothers, “happy” and “fun” experiences were important because they had positive effects on their mental health. Some mothers also reported that physical activity helped them to reduce their worries and concerns that they experienced as parents during the postpartum period. For example, Caroline (participant #6) was concerned because she could not fulfill her duties as a mother during the exacerbation of her illness. She valued mental well-being and postpartum physical activity because they gave her the energy she needed to do her duties as a mother. These beliefs were probably influenced by institutional health discourses that support the message that postpartum exercise can reduce the signs and symptoms of postpartum depression [1]. Caroline’s mental health and her subject position as becoming a “better mom” may have contributed to her worries and concerns about her parenting role, which may have been influenced by cultural and social expectations of what parents should be like. Caroline thought that she would be a “better mom” if she could support and guide her children better. While she acknowledged the importance of both physical and mental health, she thought that the exacerbations of her mental illness made her mental health even more important than the physical health. She said: Overall, it appears that Caroline dichotomized health into two distinct categories: mental health and physical health. She placed more importance on mental than physical health. She may have also challenged the link between physical and mental health. There was some variation in how participants experienced the effects of exercise on their mental health. While some women believed that physical activity had an impact on their general mental health, others expressed that it had an impact on a particular area of mental health (positive emotions). For instance, Ellena (participant #5), indicated that the goal of physical activity was to “enjoy” it, since enjoyment can reduce stress, and low levels of stress can enhance pleasant feelings, which can improve mental health. She also realized that enjoyment allowed her to alleviate the distress which was related to interacting with her child or dealing with the COVID-19 outbreak. She also believed that doing physical activity was enjoyable because it was something she could do just for herself. She positioned herself subjectively against the dominant and normative social construction of mothers who are often expected to be everything for their children [24]. Thus, Ellena’s agency was to engage in postpartum physical activity. Similar feelings were reported by other participants, as Sara (participant #4) mentioned: It was evident that the majority of participants resisted the common responsibilities that are often socially constructed for mothers, such as they should be “all for their children” [24]. Thus, doing something solely for themselves made them “happy”. ## 3.4. Being a Good Role Model for Their Children One important value for all participants was that their children engage in physical activity. All participants believed that their own behaviors could affect their child’s behavior, and it could start as early as the first 3–12 months after birth. Some participants started to think about their role to promote physical activity in their children beginning in the postpartum period. In the following quote, Mary (participant #1) explained how she could influence her children with her behavior: There was a specific relation of power between postpartum mothers and their babies. The mothers thought the role modeling helped them to teach their children about their beliefs and values regarding physical activity, using a non-hierarchical approach. For example, Anne (participant #3) realized that she had the potential to educate her child about the advantages of physical activity, instead of telling her son what to do directly as she explained during the interview: Anne’s subjectivity as a mother can be seen in her statement “the relation between physical activity and being a mother is just teaching”. This indicates her belief that there are certain social norms to being a mother. More specifically, she is referring to being part of a mothering discourse that perpetuates the belief that mothers are meant to teach their children. In this instance, she believed that she had a responsibility to teach her baby the importance of being active. The majority of participants were anxious about how their children would be affected by social media or spending time in front of a screen instead of engaging in physical activity. For example, Sara (participant #4) noted that sitting in front of the television and eating junk food was a stream that was inevitable for her children, but she attempted to prevent it. As a result, Sara viewed herself as a mother who had power and control over what she wanted her child to learn. The advantage of parents’ role modelling is that it can help parents reinforce desired behaviors in themselves. For example, mothers must practice physical activity themselves if they want to promote it in their children. ## 4. Discussion In this research study, we demonstrated how social and institutional discourses shape women’s experiences of postpartum physical activity. The participants in this study liked to engage in postpartum physical activity to improve their mental health, promote physical activity in their children, and overcome their sense of isolation. For some mothers, engaging in postpartum physical activity improved their mood and well-being [1,25]. Pregnancy, delivery, and the postpartum period are crucial life events, in which alterations in mental and physical health are possible. There is much evidence illustrating the positive relationship between postpartum physical activity and positive mood and well-being [26,27]. Moreover, other investigators in a systematic review found a positive relationship between postpartum physical activity and a decreased rate of depression in this period [8]. Improved mental well-being can also lead to decreased postpartum depression [26]. It seems that the participants in this research study relied on some medical discourses that promoted engagement in postpartum physical activity. These beliefs and values should be supported by health care professionals and educational programs. Moreover, all participants in this research study reported that they preferred social support while engaging in postpartum physical activity. Participants’ construction of social support illustrated that many mothers felt the need for emotional or instrumental support, or both, to engage in postpartum physical activity. Most mothers constructed instrumental support as an individual who could take care of the babies or perform household chores. The role of social support in promoting postpartum physical activity has been presented in previous literature [2,28]. The findings also illustrated that one non-Canadian mother was not able to receive enough support from immediate family members as they lived in another country. It showed how different beliefs, values, practices, and the structure of the family may affect mothers’ perceived social support regarding postpartum physical activity. It also illustrated that people from different cultures constructed social support and family support differently. Further, it has implications for health care professionals to consider cultural differences and the availability of resources when they want to provide care, support, or consultation for this group of postpartum women. Government officials, health promotion clinics, health care professionals, non-governmental organizations, and women and their families need to work together to explore the best ways to support postpartum women to engage in postpartum physical activity, and identify existing resources to support postpartum mothers to engage in postpartum physical activity. For example, some non-governmental organizations could set up group exercise classes that offer childcare facilities. Additionally, mothers “are expected to be fulfilled solely by their roles as mothers while ignoring other desires and needs” ([24], p. 22). If mothers do not fulfil these needs, they are considered to be selfish and careless. Therefore, in several societies and families women’s own needs are ignored. All the women in this research study challenged the discourse of the ever-giving mother and the idea that mothers should be everything for their children, as many of them would like to do something solely for themselves. It is recommended that educational workshops be held for postpartum mothers and their families to teach them about the health needs of mothers in the postpartum period. The present research also found that postpartum women experienced social isolation and tried to deal with their sense of isolation. The mothers discovered that postpartum physical activity assisted them with meeting new people and minimizing feelings of loneliness. This finding was congruent with Liva’s earlier research study [29]. Most participants in that research were on maternity leave, and many reported experiencing social isolation throughout the postpartum period. These feelings resulted from increased parental responsibilities and commitments imposed on new mothers under pressure to adjust their daily routines to meet their infant’s schedule. It is crucial to handle postpartum social isolation, since it may result in additional health problems such as stress, anxiety, and depression. Postpartum women may use tactics, such as postpartum physical exercise, to feel less isolation [30], which participants in the current study aimed to accomplish. However, according to the conclusions of this inquiry, the COVID-19 outbreak exacerbated the issue. Indeed, all participants’ physical activity was influenced by restrictions due to COVID-19. In response, online support groups or physical activity apps may have been effective. These applications may provide the necessary encouragement for mothers to engage in physical activity [31]. However, more research is needed to explore the effect of these new technologies specifically in promoting postpartum physical activity. Health care professionals, researchers, and community groups working with families should collaborate to find the best approaches to promote physical activity in postpartum women. Additionally, all participants did not like to try new places for engaging in physical activity, meet new people, go to the gyms, or public places due to COVID-19 restrictions. Thus, the COVID-19 outbreak influenced participants’ physical activity directly or indirectly. If participants had somebody to take care of their babies, they could engage in physical activity. Again, it illustrated the importance of providing support to mothers to engage in postpartum physical activity as the postpartum period can be isolating for most parents. The findings showed that all participants expressed a desire to participate in postpartum physical exercise to be role models for their children. In a research study that was carried out by Garriguet et al. [ 32], their results showed that there was a direct relationship between parents’ physical activity and children’s physical activity. Parents played a crucial role in encouraging and promoting their children’s physical activity [32]. It is important to note that childhood sedentary behavior contributes to health issues, such as obesity, and is exacerbated by prolonged television viewing and frequent computer use. It is also common to eat junk food when watching television [33]. These behaviors create great worries and concerns in families that were reported by participants in the current study. Fostering parental role modeling of healthy behavior is one of the strategies recommended by experts to prevent a sedentary lifestyle and promote physical activity in children [33]. However, more research is needed to explore the effect of postpartum mothers’ role modeling on infants. ## Limitations This study only included postpartum mothers who were able to speak English, and all of them were well-educated; thus, the experiences of people who spoke other languages and had a different level of education were not discussed. It is recommended that future studies involve different groups of people in terms of race, culture, level of education, and social economic status. Another limitation was the format of the interviews. The COVID-19 outbreak forced all interviews to be conducted over the phone. Therefore, despite the fact that firsthand data were obtained, comprehending the participants’ body language was not possible. It is recommended that for future studies, various formats of interviews, including face-to-face, video calls, and phone are utilized. Additionally, this study was conducted during the COVID-19 pandemic, and this isolation may have affected the participants’ experiences in unique ways. However, research conducted by previous researchers [15] demonstrated that postpartum experiences of new parents during COVID-19 were seen to be exacerbated. For example, isolation was present before COVID-19 but was elevated during the pandemic. ## 5. Conclusions This study illustrated that participating in postpartum physical activity was influenced by different discourses on mothering and health. For example, contending with the social discourse that mothers are expected to be primary, selfless care takers influenced the way they chose to participate in postpartum physical activity. Discourses on mental health also impacted the way participants spoke about the way physical activity influenced their own mental health. The belief that mothers are teachers was taken up in different ways for participants when they chose to role model physical activity for their infants and children. The meaning of support was different among mothers depending on how they felt about the relationship they had with their baby and other family members. Participation in physical activity happened more often for mothers who received emotional or instrumental support from their partners or immediate family members than mothers who did not have such support. For a few mothers, support referred to a person who could provide care for their babies or do domestic chores. In summary, it was evident that the postpartum period is a challenging time and deciding how to engage in physical activity is influenced by postpartum discourses. ## References 1. Kołomańska-Bogucka D., Mazur-Bialy A.I.. Physical activity and the occurrence of postnatal depression: A systematic review. Medicina (2019.0) 55. DOI: 10.3390/medicina55090560 2. 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--- title: COVID-19 Is a Confounder of Increased Candida Airway Colonisation authors: - Margaux Froidefond - Jacques Sevestre - Hervé Chaudet - Stéphane Ranque journal: Pathogens year: 2023 pmcid: PMC10052038 doi: 10.3390/pathogens12030463 license: CC BY 4.0 --- # COVID-19 Is a Confounder of Increased Candida Airway Colonisation ## Abstract An increased incidence of invasive fungal infection was reported in SARS-CoV-2-infected patients hospitalised in the intensive care unit. However, the impact of COVID-19 on Candida airway colonisation has not yet been assessed. This study aimed to test the impact of several factors on Candida airway colonisation, including SARS-CoV-2 infection. We conducted a two-pronged monocentric retrospective study. First, we analysed the prevalence of positive yeast culture in respiratory samples obtained from 23 departments of the University Hospital of Marseille between 1 January 2018 and 31 March 2022. We then conducted a case-control study, comparing patients with documented Candida airway colonisation to two control groups. We observed an increase in the prevalence of yeast isolation over the study period. The case-control study included 300 patients. In the multivariate logistic regression, diabetes, mechanical ventilation, length of stay in the hospital, invasive fungal disease, and the use of antibacterials were independently associated with Candida airway colonisation. The association of SARS-CoV-2 infection with an increased risk of Candida airway colonisation is likely to be a consequence of confounding factors. Nevertheless, we found the length of stay in the hospital, mechanical ventilation, diabetes, and the use of antibacterials to be statistically significant independent risk factors of Candida airway colonisation. ## 1. Introduction In December 2019, the first case of SARS-CoV-2 infection was described in Wuhan, China, heralding the emergence of a global pandemic responsible for 546 million cases and 6.3 million deaths [1,2]. The morbidity associated with COVID-19 is heterogeneous, ranging from asymptomatic infections to acute respiratory distress syndrome (ARDS), requiring urgent hospitalisation in an intensive care unit (ICU) [3]. ICU hospitalisation and subsequent invasive therapies may generate infectious complications, potentially associated with significant morbidity and mortality [4]. Yeast isolation from respiratory samples is common, notably in ICU patients receiving mechanical ventilation [5,6]. Yeast colonisation has been reported in $30\%$ of patients receiving ventilation over 48 h and in up to $50\%$ of patients diagnosed with ventilator-associated pneumonia (VAP) [7]. Similarly, recent studies report such respiratory colonisation in up to $21\%$ of patients with COVID-19 [8]. The known risk factors for Candida airway colonisation include exposure to broad-spectrum antibiotics, the use of corticosteroids and immunosuppressants, the use of mechanical ventilation, neutropaenia, and diabetes [9,10]. Some studies have also reported that the duration of mechanical ventilation and the length of stay in the ICU are associated with a poor clinical outcome [11,12]. However, data regarding the impact of SARS-CoV-2 infection on respiratory tract colonisation by Candida yeast are scarce. This study aimed to assess the association of risk factors, particularly SARS-CoV-2 infection, with Candida respiratory tract colonisation. A secondary objective was to assess the effect of systemic antibiotic treatments on Candida airway colonisation. ## 2.1. Study Design We conducted a two-pronged, single-centre retrospective study. The first approach involved a longitudinal observational study based on the “Méditerranée Infection Data Warehousing and Surveillance” (MIDAS) database. This programme, hosted at the Institut Hospitalo-Universitaire (IHU) Méditerranée Infection, combines syndromic and conventional surveillance and collects data from all the samples received at the microbiology laboratory, any subsequent tests performed, and the results obtained, on a weekly basis [13]. We analysed the prevalence of yeast isolation in respiratory samples from patients hospitalised in 21 units at the Assistance Publique—Hôpitaux de Marseille (AP-HM) university hospital of Marseille (France) from 1 January 2018 to 31 March 2022. The second approach was a case-control study comparing patients with Candida airway colonisation to two groups of control patients, who had no positive respiratory sample yeast culture. ## 2.2. Inclusion Criteria The patients included in the study between 1 April 2021 and 30 November 2021 were required to meet the following inclusion criteria: Be over 18 years old. Be hospitalised in the AP-HM during the study period, with at least three respiratory samples obtained for the culture. ## 2.3. Exclusion Criteria Patients under 18 years of age, patients without respiratory samples, or patients who objected to the use of personal data for research purposes were excluded from the analysis. ## 2.4. Case Definition Candida airway colonisation cases were defined by three or more respiratory samples growing yeasts on culture and obtained on separate days. ## 2.5. Control Definitions The patients included in the control groups had to meet the following criteria: Absence of yeast cultured from at least three respiratory samples obtained on separate days. The positive control (BactC) group included patients with a positive bacterial culture (Haemophilus influenzae, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa...) in a respiratory sample. The negative control (NegC) group included patients for whom respiratory sample cultures were negative, i.e., neither bacteria nor yeast were cultured. ## 2.6. Data Collection In the first part of the study, the respiratory sample culture results from 21 units of the AP-HM were collected through the MIDAS programme. In the second part of the study, clinical data were collected through the hospital computerised medical records. The demographic information collected included: sex, age, medical history (obesity, high blood pressure (HBP), heart disease, diabetes, smoking, chronic respiratory failure, chronic renal failure with a global filtration rate (GFR) < 60 mL/min/1.73 m2), a history of haematological disease, cancer, a history of transplantation, immunosuppression, and the use of immunosuppressive therapy (long-term corticosteroid therapy, cancer chemotherapy, or anti-rejection therapy for transplant patients). The data collected on the hospital stay included: length of stay, hospitalisation in the ICU or medical ward, diagnosis of SARS-CoV-2 infection with identification of the variant, use of oxygen therapy and delivery technique (low-dose oxygen therapy, high-flow nasal cannula (HFNC), non-invasive ventilation (NIV), mechanical ventilation (MV)), use of extracorporeal membrane oxygenation (ECMO), use of enteral or parenteral nutrition, abdominal surgery during hospitalisation, the administration of antibacterial, antiviral, or antifungal antibiotics, diagnosis of invasive fungal disease during the stay, detection of respiratory viruses, the type of respiratory samples obtained (bronchoalveolar lavage (BAL), tracheobronchial aspiration (TBA), sputum cytobacteriological examination (CBES)), the use of immunomodulatory therapies (notably, dexamethasone, methylprednisolone, and tocilizumab), and the patient’s outcome (deceased or alive). The time from admission to isolation of the first yeast in a respiratory sample was noted in patients in the case group. Similarly, for the BactC group, the time between admission and the first positive bacterial culture of respiratory samples was recorded. ## 2.7. Statistical Analysis The case-control study data were analysed using SAS 9.2 for Windows (SAS Institute Inc., Cary, NC, USA). Continuous variables were expressed as the mean (SD), while categorical variables were expressed as proportions and percentages. Continuous variables were compared using ANOVA. Categorical variables were compared using the Chi square or Fisher’s exact tests, as required. All statistical tests were two-sided, with a $p \leq 0.05$ significance level. Univariate and multivariate unconditional logistic regression analyses were performed to estimate odds ratios (ORs) with a $95\%$ confidence interval (CI). All covariates with a $p \leq 0.20$ significance level in the univariate analysis were included in the multivariate analyses. Three multivariate logistical regression models were computed: the case group was compared either to (i) all controls (including both the NegC and BactC groups), (ii) only the BactC, or (iii) only the NegC groups. For each control group model, a stepwise selection was performed to retain the most parsimonious model, including the covariates that displayed an independent statistically significant effect on the risk of airway fungal colonisation. ## 3.1. Time Trends in the Prevalence of Yeast-Positive Culture in Respiratory Samples Between 1 January 2018 and 31 March 2022, a total of 17,408 respiratory samples were collected, of which 12,881 grew bacteria and/or fungi in culture. Most (17,102 ($98.2\%$)) of the samples collected over the study period originated from ICU patients. Yeast was isolated in 3593 samples, amounting to $28\%$ of the positive cultures. The distribution of yeast species during this period is described in Figure 1. Of those samples, 2658 ($74\%$) grew C. albicans, 272 ($8\%$) grew C. tropicalis, 217 ($6\%$) grew C. glabrata, 123 ($3\%$) grew C. dubliniensis, and 115 ($3\%$) grew C. parapsilosis. The prevalence of yeast isolation increased from February 2020, concomitantly with the onset of the COVID-19 epidemic in Marseille, with a predominance of C. albicans ($17\%$ of yeasts isolated). In April 2020, up to $23\%$ of culture samples grew C. albicans. This trend continued over the following year, with C. albicans being isolated from $24\%$ of respiratory samples in May 2021. A relative decrease in the prevalence of C. albicans occurred in July 2021 ($16\%$), August 2021 ($17\%$), and November 2021 ($14\%$). Finally, in 2022, $20\%$ of the samples were positive for C. albicans in January, $22\%$ in February, and $19\%$ in March. This time trend is illustrated in Figure 2 and Figure 3. ## 3.2. Patient Demographics Between 1 April 2021 and 30 November 2021, 300 patients (100 in each group) were included in the case-control study (Table 1). The three groups were homogeneous regarding age ($$p \leq 0.8752$$) and sex ($$p \leq 0.7605$$). A total of 80 patients ($80\%$) in the case group were admitted to the ICU, compared to 62 ($62\%$) and 18 ($18\%$) patients in the BactC and NegC groups, respectively ($p \leq 10$−4). Comorbidities were homogenously distributed among the three groups. Of the 79 patients with a history of chronic respiratory failure, 32 had chronic obstructive pulmonary disease (COPD), 18 had cystic fibrosis, 8 had diffuse interstitial lung disease, 7 had pulmonary fibrosis, 6 had bronchial dilatation, 6 had emphysema, 1 had severe asthma, and 1 had respiratory failure consecutive to pulmonary tuberculosis. Diabetes was statistically significantly ($p \leq 10$−4) more frequent in the case group ($31\%$) compared to the BactC and NegC groups—$26\%$ and $7\%$, respectively. In contrast, solid malignancies were rarer ($$p \leq 0.0114$$) in the case group ($7\%$) compared to the BactC and NegC groups—$16\%$ and $22\%$, respectively. Similarly, immunosuppression was rarer ($$p \leq 0.0212$$) in the case group ($17\%$) compared to the BactC and NegC groups—$31\%$ and $33\%$, respectively. Among immunocompromised patients, 42 had a history of organ transplantation, including 33 lung transplant patients, 16 had a history of chronic inflammatory or autoimmune disease, 12 were receiving cancer chemotherapy, 7 had been treated for a haematological disease, and 4 were infected with HIV. ## 3.3. Characteristics of Hospital Stay The use of parenteral nutrition ($$p \leq 0.1697$$) and oxygen delivery devices, including low-dose oxygen ($$p \leq 0.2129$$), HNFC ($$p \leq 0.6004$$), and non-invasive ventilation ($$p \leq 0.2529$$), was homogenously distributed within the three groups. In contrast to BAL ($$p \leq 0.8788$$) and CBES ($$p \leq 0.9505$$), TBA was statistically significantly most often performed in the case group ($p \leq 10$−4). Regarding the factors associated with the ICU, MV ($p \leq 10$−4), ECMO ($p \leq 10$−4), central venous catheter ($p \leq 10$−4), abdominal surgery during hospitalisation ($$p \leq 0.0323$$), and parenteral nutrition implementation ($p \leq 10$−4) were statistically significantly most often observed in the case group patients. Similarly, the mean hospital stay was longer ($p \leq 10$−4) in the case group, with 46 (±37) days compared to 26 (±22) and 9 (± 8) days for the BactC and NegC groups, respectively. Case-fatality rates were also higher ($$p \leq 0.0032$$), with 29 ($29\%$) fatal outcomes in the case group compared to 23 ($23\%$) and 10 ($10\%$) in the BactC and NegC groups, respectively. ## 3.4. Microbiological Characteristics A total of 53 ($53\%$) patients in the case group had SARS-Co-V-2 infection, compared with $29\%$ and $17\%$ in the BactC and NegC groups, respectively ($p \leq 10$−4). The mean timescale between hospital admission and the first culture-positive respiratory sample was seven days in both the Case and BactC patients. Within the Candida genus (Figure 4), C. albicans ($57\%$) was predominantly isolated, followed by C. glabrata ($17\%$), C. dubliniensis ($7\%$), Kluyveromyces marxianus ($5\%$), and C. tropicalis ($4\%$). Of the 91 respiratory samples with a positive bacterial culture in the case group patients, the most frequent bacterial coinfection involved Enterobacteriaceae ($47\%$), including Klebsiella pneumoniae ($18\%$), followed by Pseudomonas aeruginosa ($19\%$) and methicillin-susceptible Staphylococcus aureus ($11\%$) (Figure 5). In the BactC group patients, 138 respiratory specimens yielded Enterobacteriaceae ($40\%$), including E. coli ($11\%$) and Klebsiella sp. ( $9\%$), $28\%$ yielded P. aeruginosa, and $17\%$ yielded methicillin-susceptible S. aureus. The distribution of bacterial species is illustrated in Figure S1. The use of antibacterial therapy was significantly more frequent ($p \leq 10$−4) in the case and BactC patients ($88\%$ each) compared to those in the NegC group ($35\%$). A viral respiratory infection was more frequently diagnosed ($p \leq 10$−4) in patients in the case group ($25\%$) compared to patients in the BactC ($13\%$) and NegC ($1\%$) groups. Antiviral treatment was initiated during the hospital stay in 27 ($27\%$) patients in the case group compared to $12\%$ and $1\%$ in the BactC and the NegC groups, respectively ($p \leq 10$−4). Invasive fungal disease (IFD) occurred in 16 patients ($16\%$) in the case group (five candidaemia, ten pulmonary aspergillosis, and one C. albicans pleurisy). In the BactC group, fungal infection was documented in three patients (one candidaemia and two pulmonary aspergilloses). No fungal infections were documented in the NegC group ($p \leq 10$−4). Twenty-six ($26\%$) patients in the case group received systemic antifungal therapy, compared with $5\%$ and $2\%$ in the BactC and the NegC groups, respectively ($p \leq 10$−4). Notably, two patients in the NegC group received pre-emptive antifungal therapy. ## 3.5. Description of Candidaemia Cases The clinical characteristics and microbiological findings of the five case group patients who developed candidaemia during their ICU stay are presented in Table 2. Comparatively, one patient from the BactC group developed C. parapsilosis candidaemia. This patient was 53 years old, without comorbidities at admission, and had been hospitalised for 46 days in the ICU for polytrauma management. He was intubated, had no documented SARS-CoV-2 infection, and had not had abdominal surgery. No Candida colonisation had been documented in previous samples. The initial caspofungin antifungal treatment was then switched to fluconazole. Additionally, a documented Enterobacter cloacae and K. pneumoniae VAP was treated with piperacillin-tazobactam. ## 3.6. Documented SARS-CoV-2 Infection A SARS-Co-V-2 infection was diagnosed in 53 ($53\%$) patients in the case group, compared to $29\%$ and $17\%$ in the BactC and NegC groups, respectively. The Alpha variant was the most frequently involved. It was documented in 26 patients from the case group, 9 patients from the BactC group, and 10 patients from the NegC group. The Delta variant was detected in 13 patients in the case group, 9 patients in the BactC group, and 1 patient in the NegC group (Figure S2). The Alpha variant was predominant during April and May, whereas the Delta variant became predominant from July 2021. The monthly distribution of variants between April and November 2021 is shown in Figure S3. The immunomodulatory treatments used against SARS-CoV-2 are summarised in Table 3. Dexamethasone treatment was more frequently ($p \leq 10$−4) used in the case group patients ($53\%$), compared with $28\%$ and $10\%$ in the BactC and NegC groups, respectively. Methylprednisolone was initiated in $37\%$, compared with $16\%$ and $3\%$ in the BactC and NegC groups, respectively ($p \leq 10$−4). Tocilizumab was homogenously ($$p \leq 0.6045$$) prescribed in the case ($6\%$) and BactC ($7\%$) groups. ## 3.7. Exposure to Antibacterials The exposure to antibacterials in each patient group is summarised in Table S1. Piperacillin-tazobactam was the most frequent antibacterial used. It was administered in $44\%$ of patients in the case group, compared with $34\%$ and $14\%$ in the BactC and NegC groups, respectively. Carbapenem was administered in $35\%$ of the case group patients. In the BactC group patients, cefotaxime, ceftriaxone ($23\%$), and group A penicillins ($23\%$) were the most used after piperacillin-tazobactam. Penicillin A was administered in $13\%$ of the NegC group patients. ## 3.8. Multivariate Analysis The results of the multivariate analyses are summarised in Table 4. The first analysis, comparing the case group and both control groups (BactC+NegC), found a statistically significant association between Candida airway colonisation and diabetes, mechanical ventilation, length of hospital stay, the development of invasive fungal disease, and the use of some antibacterial antibiotics, including carbapenems, cefepime, and piperacillin/tazobactam. When compared to the BactC group, Candida airway colonisation was statistically significantly associated with mechanical ventilation, diabetes, length of hospital stay, and the use of cefepime and carbapenems. In contrast, a history of solid malignancy appeared to be a protective factor. When compared to the NegC group, Candida airway colonisation was statistically significantly associated with the length of hospitalisation, antifungal treatment, and linezolid administration. ## 4. Discussion Our first finding was a dramatic increase in the number of respiratory samples analysed at the AP-HM university hospital microbiology laboratory since March 2020, in comparison with the two previous years. Most of the respiratory samples originated from ICU patients, and the prevalence of positive yeast (mainly Candida spp.) culture increased in parallel. This increased prevalence of Candida airway colonisation was concomitant to the SARS-CoV-2 epidemic and roughly correlated with the successive epidemic waves in France, notably in March and April 2020, the last quarter of 2020, from February to May 2021, in August and September 2021, and from December 2021 to January 2022 [14]. One explanation for this increased number of respiratory samples is probably the rising number of patients admitted to the ICU due to severe SARS-CoV-2 infection since March 2020. Some 106,000 patients with COVID-19 were admitted to ICUs between 1 March 2020 and 30 June 2021 in France. Comparatively, 19,000 patients were admitted to French ICUs due to severe influenza between 2014 and 2019 [15]. The documentation of possible respiratory coinfections in ICU patients is probably the main reason for this increase in respiratory samples. Most patients admitted to the ICU received mechanical ventilation and were thus exposed to VAP [8]. The distribution of yeast species, C. albicans ($57\%$) and C. glabrata ($17\%$), in the respiratory sample cultures that we observed was in line with previous reports [5]. Similarly, the seven-day timeframe between admission and the first positive Candida culture that we observed was comparable to the 6 ± 1.6-day timeframe reported by Hedderwick et al. in 16 ICU patients [16]. Several studies have assessed the risk of candidaemia in SARS-CoV-2-infected patients [17,18,19,20,21]. We tested whether SARS-CoV-2 infection was an independent factor of Candida airway colonisation. In our univariate analysis, SARS-CoV-2 infection was statistically significantly more frequently diagnosed in patients with Candida spp. airway colonisation. However, SARS-CoV-2 infection is likely to be a confounding factor, since its independent effect was not statistically significant in the multivariate analysis. Likewise, patients with Candida spp. airway colonisation were significantly more frequently hospitalised in the ICU, which is in line with previous studies that reported $50\%$ to $86\%$ Candida colonisation rates in patients who had a prolonged stay in the ICU [22,23,24,25]. However, this association was not statistically significant in the multivariate analysis, which highlighted ICU-related factors such as mechanical ventilation as independent risk factors of Candida spp. airway colonisation. In the univariate analysis, diabetes, mechanical ventilation, ECMO, central venous catheters, abdominal surgery, length of hospitalisation, and antibacterial therapy were associated with colonisation. A fatal outcome occurred more frequently in colonised patients. However, the multivariate analysis only found diabetes, length of hospitalisation, mechanical ventilation, and antibacterial therapy to be associated with Candida colonisation. Regarding mechanical ventilation, Arastehfar et al. reported respiratory Candida colonisation in $20\%$ of patients after 48 h of mechanical ventilation [18]. In line with our findings, several studies reported the association of a protracted hospital stay and mechanical ventilation with Candida airway colonisation [5,19,26]. Keeping with our findings, Chakraborti et al. and Erami et al. identified diabetes as a risk factor for Candida airway colonisation [10,27]. However, in contrast to Erami et al., who identified solid malignancies, chronic renal failure, and pre-existing cardiovascular diseases as Candida airway colonisation risk factors, none of these factors were significant in our study [10]. In contrast, we found that a solid malignancy history protected from Candida airway colonisation. This debatable result could be explained by the heterogeneity of the patient population in each study. The predominance of ICU patients in our study represents a recruitment bias because patients with advanced cancer are generally not admitted to the ICU. The role of chronic renal failure remains a matter of debate [16]. In our study, the use of antibacterials was statistically significantly associated with an increased risk of Candida airway colonisation. Subgroup analyses identified some antibacterials that were more frequently associated with a risk of colonisation—notably, carbapenems and cefepime. These results are aligned with those of Delisle et al. and Charles et al., who reported an increased use of antibacterials in Candida-colonised patients [12,28]. Notably, these two studies reported on broad-spectrum antibacterials but did not specify which antibacterial classes were used. The development of invasive fungal disease and the use of antifungal therapy were associated with Candida colonisation when compared to non-colonised (NegC) patients with culture-negative respiratory specimens. One explanation might be that patients in the NegC group were less severe and less likely to be treated with systemic antifungals than ICU patients. Five fungaemia occurred in the group of patients colonised with Candida ($5\%$), whereas only one occurred in the non-colonised patient group. These data are in line with several previous studies [29]. Moreover, the relevance of assessing Candida colonisation in patients at risk of invasive candidiasis has been demonstrated by Pittet et al. [ 22]. The use of high-dose corticosteroids (dexamethasone and methylprednisolone) was not shown to be an independent risk factor in our multivariate analysis. Indeed, its effect on Candida colonisation remains under debate [16]. Likewise, in contrast to other studies, we did not find that tocilizumab was an independent risk factor for Candida colonisation, which might be due to the relatively small number of patients treated with it [23,24]. Our multivariate analysis did not show a difference in mortality between the colonised and non-colonised groups. It should be noted that the association between Candida colonisation and ICU patients’ mortality is disputed, with conflicting reports in the literature [12]. Among the colonised patients in our study, only one had a documented Candida lung infection. Candida pneumonia is a rare infection. In their study on 25 autopsied patients, El-Biary et al. reported 10 who were colonised with Candida, only 2 of whom had histologically documented pneumonia [30]. Similarly, among 232 autopsied ICU patients, Meersseman et al. reported histologically documented pneumonia in 135 ($58\%$). Of these, 77 ($57\%$) had Candida spp. isolated from pre-mortem respiratory samples, and none displayed histological features of Candida pneumonia. The limitations of our study include its monocentric design, which means that our results can only be extrapolated to other settings with caution. Retrospective studies are also known to be prone to bias. Nevertheless, our findings are strengthened by our choice to define colonisation through the positive culture of three distinct respiratory samples, whereas other studies define colonisation on the basis of a single positive sample [29,31]. This is likely to increase the robustness of our findings. Furthermore, our choice to use distinct patient control groups allowed us to highlight robust risk factors, which have an impact on a fairly heterogeneous group of patients. ## 5. Conclusions Both the incidence and prevalence of Candida-positive respiratory samples increased in parallel to the SARS-CoV-2 epidemic. However, SARS-CoV-2 infection is likely to be a confounding factor rather than an independent risk factor. While SARS-CoV-2 infection was statistically significantly more frequently diagnosed in patients with Candida airway colonisation in our univariate analysis, the length of hospitalisation, the use of mechanical ventilation, diabetes, and the use of antibacterial antibiotics, but not SARS-CoV-2 infection, were independently associated with Candida airway colonisation in our multivariate analysis. 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--- title: 'Significant Interactions between Adipokines and Vitamin D Combined with the Estimated Glomerular Filtration Rate: A Geriatric Case Study' authors: - Monika Biercewicz - Katarzyna Kwiatkowska - Kornelia Kędziora-Kornatowska - Magdalena Krintus - Robert Ślusarz - Barbara Ruszkowska-Ciastek journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10052050 doi: 10.3390/jcm12062370 license: CC BY 4.0 --- # Significant Interactions between Adipokines and Vitamin D Combined with the Estimated Glomerular Filtration Rate: A Geriatric Case Study ## Abstract Vitamin D deficiency is an important issue in the worldwide population, especially in older people. According to the World Health Organization data, in 2030, 1 in 6 people in the world will be 60 years old or older. The main storage site for vitamin D is adipose tissue. Further, 25(OH)D regulates the expression of adipogenic genes and apoptosis of adipocytes and directly influences the secretion of the appetite-regulating hormone—leptin. Thus, we investigated the impact of the serum concentrations of leptin, adiponectin, omentin, ghrelin, visfatin, and biochemical parameters on vitamin D and estimated glomerular filtration rate (eGFR) in geriatric females. Our studies indicate that the leptin, visfatin and ghrelin are linked with vitamin D concentration and the eGFR rate in the geriatric females. [ 1] Background: Vitamin D deficiency is common in older people, and researchers are looking for a link between vitamin D deficiency and the occurrence of diseases in advanced age. The study aimed to evaluate the association between serum 25(OH)D levels and clinical variables in older females. [ 2] Methods: We investigated the impact of the serum concentrations of leptin, adiponectin, omentin, ghrelin, visfatin, and biochemical parameters on vitamin D and estimated the glomerular filtration rate (eGFR) in 74 geriatric females. [ 3] Results: We observed a significantly higher concentration of creatinine and visfatin in the G2 stage (eGFR = 60–89 mL/min$\frac{.}{1.73}$ m2). We performed an additional analysis to exclude the effect of vitamin D supplementation and obtained a significantly higher vitamin D concentration in the G2 stage. We found significantly lower vitamin D concentrations in older people. In addition, in a person with low levels of vitamin D, we observed significantly lower levels of albumin and ghrelin. Older patients (80 to 89 years old) had significantly lower levels of vitamin D, albumin, insulin, HOMA-IR, and ghrelin than younger patients (60 to 69 years old). Spearman’s correlations performed to examine the relationship between clinical variables seemed to confirm previous results. According to ROC curve analysis, leptin concentration was the strongest predictor of vitamin D fluctuations (the area under the curve, AUC = 0.685; with $79.5\%$ sensitivity and $51.4\%$ specificity; $$p \leq 0.0291$$). However, visfatin reached the most accurate AUCROC = 0.651 with $84.2\%$ sensitivity and $49.1\%$ specificity for predicting effects on eGFR. [ 4] Conclusions: The results suggest that serum levels of leptin, visfatin, and ghrelin are linked with vitamin D concentration and the eGFR rate in the population of geriatric females. ## 1. Introduction Longevity can be considered a success for mankind. However, the price we have to pay for this is high and associated with the occurrence of many age-related disorders. According to the data from 2020, individuals aged 65 and older represent approximately $20\%$ of the total population in the European Union (EU) [1]. This means that almost one in five people in the EU is aged 65 or over. In the overall U.S. population, people aged 65 and older make up $17\%$ and women almost $18\%$ [2]. According to the World Health Organization data, in 2030, 1 in 6 people in the world will be 60 years old or older [3]. Vitamin D (25(OH)D) deficiency is a serious problem in the worldwide population, especially in older people. To better understand the genesis of vitamin D deficiency, it is necessary to trace the path of vitamin D metabolism. Further, 25(OH)D is supplied to the body in two ways: with food and through skin synthesis. Vitamin D supplied to the body undergoes double hydroxylation—in the liver (hydroxylation at position 25 with the formation of 25-hydroxyvitamin D3 (25OHD); the main metabolite precipitating in the blood) and kidneys (hydroxylation at position 1 with the formation of 1,25-hydroxyvitamin D3 (1,25OHD), a metabolite with hormone activity) [4]. According to current data, hydroxylation at position 1 may also occur in other tissues, e.g., breast, prostate, or macrophages [5]. The role of vitamin D is not limited to its classic function of maintaining calcium and phosphate homeostasis (protective effect against rickets, osteoporosis, and osteomalacia). Vitamin D inhibits activation of the RAS (renin-angiotensin system), which results in decreased nephron destruction and lower blood pressure [6]. It leads to a decrease in endothelin synthesis and vascular smooth muscle cell proliferation and improves vascular endothelial function [7]. In addition, 25(OH)D affects the conversion of proinsulin to insulin and increases tissue sensitivity to insulin [8]. Interactions with the vitamin D receptor (VDR) located on pancreatic beta cells cause insulin secretion [9]. The beneficial effect of vitamin D on immunity is due to the presence of VDR receptors in macrophages. Macrophages recognize bacteria (lipopolysaccharide LPS) through toll-like receptors (TLRs). TLR binding leads to increased expression of both 1-α-hydroxylase and VDR [10]. The neuroprotective effect of vitamin D is related to a reduction of Ca2+ level in the brain (high calcium level can cause neurotoxicity), also via inhibition of brain gamma-glutamyl transpeptidase, which reduces hydrogen peroxide concentration by increasing glutathione concentration [11]. Vitamin D demonstrates anti-cancer effects based on mechanisms of proliferation, angiogenesis suppression, and activation of apoptosis. Additionally, 25(OH)D through the VDR binds to a regulatory site in the promoter of the p21 gene, which leads to cell-cycle inhibition in the G1 phase. Vitamin D activates apoptosis by inhibiting the expression of the protooncogene bcl-2 and increasing the expression of the proapoptotic protein Bax. Interestingly, vitamin D inhibits the activation of gene transcription for IL-8, which is a strong stimulant of angiogenesis [12]. Additionally, the main storage site for vitamin D is adipose tissue. Further, 25(OH)D regulates the expression of adipogenic genes and apoptosis of adipocytes and directly influences the secretion of the appetite-regulating hormone—leptin. Some studies indicate another function of vitamin D; it regulates the secretion of adiponectin, which sensitizes tissues to insulin [13]. In the older population, vitamin D deficiency is associated with decreased absorption from the GI tract due to gastroenterological diseases or drugs. In geriatric populations, 25(OH)D deficiency occurs due to the loss of active nephrons. Older individuals avoid exposure to sunlight during summer (a lack of cutaneous synthesis) [5]. Geriatric patients are often malnourished and do not receive adequate supplies of vitamin D from their diet. Some of those patients also experience a loss of body fat and muscle tissue, which causes a change in the secretion of adipokines [14]. Vitamin D deficiency promotes the occurrence of diabetes type 2. Patients have increased secretion of pro-inflammatory cytokines, e.g., IL-6, which is responsible for pancreatic beta cell apoptosis [8,9]. Vitamin D deficiency may lead to neurodegenerative disorders, schizophrenia, and depression. Zdrojewicz et al. have found a correlation between low blood levels of vitamin D and increased incidence and greater aggressiveness of prostate, breast, and colorectal cancers [7]. The main objective of this study was to assess the potential association between serum 25(OH)D levels and clinical variables in the population of geriatric females. Since vitamin D is substantial for numerous physiopathological processes, we also estimated the diagnostic power of selected parameters in the prediction of vitamin D deficiency and kidney function deterioration in older females. ## 2.1. Recruitment and Participants The study comprised a total of 74 older women. The median age of patients was 74.5 years old (60 to 89 years old). Patients admitted to the Geriatrics Clinic of University Hospital No. 1 in Bydgoszcz, Poland, between March 2017 and November 2018, were selected (Figure 1). Patients were hospitalized to determine the extent of impairment, treatment, rehabilitation priorities, needs, and options for providing further treatment/rehabilitation/care and to determine the elder’s ability to function independently. The main inclusion criteria were female gender and the age of >60 years. In order to exclude the effect of female hormones, we selected patients who had their last menstruation at the maximum age of 57 years. The exclusion criteria were as follows: dehydration, oedema, liver disease, chronic kidney disease at more than stage 2, deformation of upper limbs, cancer, bone marrow proliferative disorders, cachexia, or severe dementia. The supplementary exclusion criteria were as follows: male gender, chronic immobilization, prior stroke, eGFR (the estimated glomerular filtration rate) < 60 mL/min$\frac{.}{1.73}$ m2, and insulin therapy. ## 2.2. Ethical Approval This trial was performed under appropriate institutional ethics approvals (permission no. KB/$\frac{470}{2016}$; WN707). Written informed consent was obtained from each patient. This study was performed in accordance with the Helsinki Declaration and relevant regulations. ## 2.3. Demographic Profiles and Clinical Characteristics Collection Figure 1 and Table 1 show the baseline and clinical characteristics of the enrolled patients. Complete clinical history included information on the participant’s date of birth, residence, marital status, education, smoking habit (current smoker: yes/no), alcohol consumption, day of last menses, number of children, main disease (reason for hospitalization), and other chronic diseases. Most of the women lived in a city ($75.68\%$). The primary diseases that patients suffered from were hypertension (23 patients), diabetes (23 patients), and anaemia (4 patients). Patients were divided into two subgroups according to the eGFR level using recommendations outlined in The Kidney Disease: Improving Global Outcomes (KDIGO). Nineteen of the patients belong to the G1 and 55 to the G2 stage. Only 3 patients out of 74 were supplementing vitamin D (one with the G1 stage and two with the G2). Body mass index (BMI), defined as the body weight (in kilograms) divided by the square of height (in meters), and waist-hip ratio (WHR) were calculated for all patients. Most women, according to the WHO recommendations, were overweight (32 patients) and obese (26 patients). ## 2.4. Biochemical and Hematological Assays Routine blood tests were performed upon patient admission. The standard blood collection protocols were respected; patients had been fasting, after 30 min of rest and after twelve hours of overnight fasting. Serum parameters, such as vitamin D, albumin, hsCRP (high-sensitivity C-reactive protein), glucose, insulin, creatinine, calcium, and parathyroid hormone (PTH) were determined using automated analyzers applying biochemical methods. Complete blood count was determined by using an automatic white blood cell count. The blood was collected without anticoagulants, centrifuged, and then stored at –80 °C until analysis. ## 2.4.1. Serum Leptin Assays Serum leptin levels were measured using a high-sensitivity human leptin ELISA kit (enzyme-linked immunosorbent assay kit for leptin (LEP) Cloud-Clone Corp., catalogue number SEA084Hu). The detectable range of leptin was 0.156–10 ng/mL. The minimum detection dose of leptin was 0.054 ng/mL, the within-label coefficient of variation was <$10\%$ and the run-to-run coefficient of variation was <$12\%$. ## 2.4.2. Serum Adiponectin Measurement Serum adiponectin levels were determined using a high-sensitivity human adiponectin ELISA kit (enzyme-linked immunosorbent assay kit for adiponectin (ADPN) Cloud-Clone Corp., catalogue number SEA605Hu). The detection range of adiponectin was 0.156–10 ng/mL. The minimum detectable dose of adiponectin was 0.061 ng/mL, the within-label coefficient of variation (within-run) was <$10\%$, and the between-label coefficient of variation (run-to-run) was <$12\%$. ## 2.4.3. Serum Omentin Analysis Serum omentin levels were assayed using a high-sensitivity human omentin ELISA kit (enzyme-linked immunosorbent assay kit for intelectin 1/omentin (ITLN1) Cloud-Clone Corp., catalogue number SEA933Hu). The detectable range of omentin was 1.56–100 ng/mL. The minimum dose of omentin detectable was 0.59 ng/mL, the within-label coefficient of variation (within-run) was <$10\%$, and the between-label coefficient of variation (run-to-run) was <$12\%$. ## 2.4.4. Serum Ghrelin Assays Serum ghrelin levels were assessed using a high-sensitivity human ghrelin ELISA kit (enzyme-linked immunosorbent assay kit for ghrelin (GHRL) Cloud-Clone Corp., catalogue number CEA991Hu). The detectable range of ghrelin was 123.5–10,000 pg/mL. The minimum detection dose of ghrelin was 49.5 pg/mL, the intra-label coefficient of variation was <$10\%$, and the inter-run coefficient of variation was <$12\%$. ## 2.4.5. Serum Visfatin Measurement Serum visfatin levels were assessed using a high-sensitivity human visfatin ELISA kit (enzyme-linked immunosorbent assay kit for visfatin (VF) Cloud-Clone Corp., catalogue number SEA638Hu). The detection range of visfatin was 1.56–100 ng/mL. The minimum detectable dose of visfatin was 0.55 ng/mL, the intra-series coefficient of variation was <$10\%$, and the inter-series coefficient of variation was <$12\%$. ## 2.5. Anthropometric Calculation Waist-hip ratio (WHR) was calculated using a computer program. The interpretation of the WHR result is as follows: <0.8 (low), 0.8–0.89 (medium), >0.9 (high). ## 2.6. eGFR Calculation The estimated glomerular filtration rate (eGFR, (mL/min/per 1.73 m2) was estimated according to the 4-variable modification of diet in renal disease (MDRD) study formula as follows:eGFR = 186 × (serum creatinine (mg/dL))−1.154 × (age)−0.203 × (0.742 gender index for female) ## 2.7. Statistical/Data Analysis Statistical analysis was done using Statistica version 13.1 (StatStoft®, Cracow, Poland). The Shapiro–Wilk test was used to check the normality of data distribution. Comparisons between two groups of continuous data were performed using the Student t-test (normal distribution) or Mann–Whitney test (non-normal distribution). Comparisons between more than two groups of continuous data were performed by univariate ANOVA analysis with normal distributions or the Kruskal–Wallis ANOVA analysis in the case of variables with non-normal distributions. Patients’ data are presented as mean and standard deviation or median and interquartile range (IQR) as suitable. In order to assess the relations between studied variables, a correlation analysis was performed. Spearman’s rank order correlation test was used to test the correlations between the studied parameters. The receiver operating characteristic curves (ROC), AUC (area under a curve), and Youden’s index were also used in the analysis. Statistical significance was predetermined as $p \leq 0.05.$ ## 3.1. Baseline Characteristics Among patients admitted to the Geriatrics Clinic of University Hospital No. 1 in Bydgoszcz, Poland between March 2017 and November 2018, 74 women were selected who passed the inclusion and exclusion criteria for the study. Median age was 74.5 age (IQR 60–89 years old). Twenty-five women were between 60–69 years, 70–79 years were 27 women, and 22 women were between 80–89 years. According to The Kidney Disease: Improving Global Outcomes (KDIGO) recommendation, 19 of patients belong to G1 and 55 to G2 stage. In agreement with the body mass index (BMI), most women were overweight (32 patients) and obese (26 patients). Table 1 and Table 2 present the characteristics of the study population. ## 3.2. eGFR Assessment Table 3 presents results for the clinical variables classified by eGFR stages. According to KDIGO classes, patients were divided into two stages: 19 cases were G1 and 55 subjects were G2. Significant higher concentrations of creatinine and visfatin were observed in the G2 stage (p ≤0.0001, $$p \leq 0.0521$$ respectively). Analysis showed a significant upward trend toward higher vitamin D levels in G2 stage subjects ($$p \leq 0.0757$$). Additional analysis was performed in order to exclude the effect of vitamin D supplementation. Three patients were excluded from the analysis: one with G1 stage and two with G2 stage. According to this analysis, significant difference was reached with respect to vitamin D concentration and CKD stages ($$p \leq 0.0466$$, median G1 = 13.65 ng/mL, G2 = 18.70 ng/mL), (Table S1. Clinical characteristics of patients according to KDIGO classes excluding vitamin D supplementation). ## 3.3. Association between Vitamin D Concentration and Clinical Variables Table 4 shows the differences between clinical characteristics according to vitamin D level. Patients were divided into three equal groups. Lower levels of vitamin D were observed in older individuals ($$p \leq 0.0001$$). It was observed that older people with relevant vitamin D deficiency (<15 mg/dL) showed significantly lower albumin and ghrelin levels ($$p \leq 0.0015$$, $$p \leq 0.0397$$, respectively). Additionally, the concentrations of hsCRP, creatinine, and leptin tend to be significant; hsCRP and leptin have higher levels in those patients who had a lower concentration of vitamin D ($$p \leq 0.0954$$, $$p \leq 0.0575$$, respectively). The concentration of creatinine has decreasing levels when there are lower levels of vitamin D ($$p \leq 0.0911$$). ## 3.4. Age Groups Analysis Table 5 shows the comparison of clinical variables according to the age of the patients. Participants of this study were divided into three age subgroups: 60 to 69 years old (25 women), 70 to 79 years old (27 women), and 80 to 89 years old (22 women). Older patients (80 to 89 years) showed significantly lower levels of vitamin D, albumin, insulin, HOMA-IR, and ghrelin than younger patients (60 to 69 years old) ($$p \leq 0.0082$$, $$p \leq 0.0004$$, $$p \leq 0.0208$$, $$p \leq 0.0079$$, $$p \leq 0.0086$$, respectively). However, there was a trend toward lower glucose levels in older people than in younger individuals ($$p \leq 0.0677$$). The concentration of adiponectin was higher in older patients compared to those who were younger ($$p \leq 0.0627$$). ## 3.5. Relationship between Clinical Variables Correlation analysis was performed to find relationships between the clinical variables. The analysis was carried out using Spearman’s rank correlation and is presented in the form of heatmaps (Figure 2 and Figure 3). As a result (Figure 2), vitamin D was found to correlate negatively with age, hsCRP, WHR (r = −0.3924, r = −0.2539, r = −0.2482) and correlate positively with albumin ($r = 0.3861$). Insulin positively correlated with hsCRP, glucose, WHR, ($r = 0.2382$, $r = 0.3088$, $r = 0.315$) and most strongly with BMI ($r = 0.4336$). HOMA-IR negatively correlated with age (r = −0.2577) and positively correlated with BMI, hsCRP, glucose, WHR ($r = 0.4303$, $r = 0.2688$, $r = 0.5053$, $r = 0.2921$). Adiponectin negatively correlated with albumin (r = −0.2487). Leptin positively correlated with BMI, hsCRP ($r = 0.5561$, $r = 0.4182$). Ghrelin negatively correlated with age (r = −0.3864). In Figure 3, vitamin D positively correlated with ghrelin ($r = 0.2496$) and negatively correlated with leptin (r = −0.2986). Insulin positively correlated with HOMA-IR and leptin ($r = 0.9632$, $r = 0.4489$). HOMA-IR positively correlated with leptin ($r = 0.4091$). Ghrelin negatively correlated with adiponectin (r = −0.2581). Adiponectin positively correlated with omentin ($r = 0.2996$). ## 3.6. Tests of Sensitivity and Specificity The ROC (receiver operating characteristic) curves for separate laboratory parameters were constructed to distinguish factors affecting vitamin D concentrations (Table 6, Figure 4 and Figure 5). The areas under the curve with a $95\%$ confidence interval were established (AUC, $95\%$ thresholds with sensitivity and specificity). The borderline of the diagnostic usefulness of the test based on the AUC > 0.5 and $p \leq 0.05$ was reached for albumin and leptin. We found out that the cut-off point for albumin was 3.70 g/dL with $56.4\%$ sensitivity and $71.4\%$ specificity; for leptin, it was 7.38 ng/mL with $79.5\%$ sensitivity and $51.4\%$ specificity. The most accurate AUCROC value for predicting effects on vitamin D is the AUC for leptin which is 0.685. The ROC curves (Figure 6 and Figure 7) for separate laboratory parameters were constructed to distinguish factors that affect the eGFR stages (G1 and G2). All data are presented in Table 7. The areas under the curve with a $95\%$ confidence interval were established (AUC, $95\%$ thresholds with sensitivity and specificity). The borderline of the diagnostic usefulness of the test based on the AUC > 0.5 and $p \leq 0.05$ was reached for creatinine and was 0.68 mg/dL with $100.0\%$ sensitivity and $96.4\%$ specificity and for visfatin was 22,450.00 ng/mL with $84.2\%$ sensitivity and $49.1\%$ specificity. Additionally, we observed a tendency that vitamin D affects eGFR with a cut-off point of 13.9 mg/dL with $52.5\%$ sensitivity and $78.2\%$ specificity. The most accurate AUCROC value for predicting effects on eGFR is the AUC for creatinine (0.995), which is obvious because eGFR is calculated from creatinine. The following AUC was for visfatin (AUC = 0.651). ## 4. Discussion Physiological aging is a process of progressive, regressive, and irreversible changes in the tissues and organs of the body, determined by genetic factors and modified by coexisting diseases, lifestyle, and environmental factors. At the biological level, physiological aging leads to physicochemical changes in cells, including degeneration, apoptosis, amyloid accumulation, metabolism slowdown, and the impaired ability for self-regulation, adaptation, and regeneration. With the discovery of receptors for vitamin D located in many different tissues and organs, the role of vitamin D and its effect on body function have become the focus of numerous investigations. Epidemiological studies show a link between vitamin D deficiency and the incidence of diseases of old age [15]. Adipose tissue, the largest organ in humans, is associated with longevity mechanisms and metabolic disorders of old age. With age, the distribution and composition of adipose tissue, and the profile of secreted adipokines change and the glomerular filtration rate declines [16,17]. In the first stage of our study, we compared patients with different eGFR stages (G1 and G2) and various clinical parameters. Paradoxically, in our analysis, we observed that there is a significantly higher concentration of vitamin D in the G2 stage than in the G1 stage (after the elimination of supplementary impact). Our results from ROC curves demonstrated that vitamin D effects on the eGFR stages have a tendency toward significance. Visfatin is a protein, which is one of the adipokines. Its most important action is to act as a proinflammatory cytokine, which stimulates the expression of inflammatory cytokines, such as interleukin 6 (IL-6), tumor necrosis factor α and β. The study of Syed Ali Fathima et. al. suggested that visfatin can be a novel marker of endothelial dysfunction in CKD patients [18]. This is confirmed by our research in which we observed a significantly higher concentration of visfatin in the G2 stage than G1. Furthermore, the ROC curve indicated that visfatin affects an eGFR stage (AUC = 0.651) and the cut-off was 22450.00 ng/mL with $84.2\%$ sensitivity and $49.1\%$ specificity. Based on this, it is possible to distinguish between patients with the G1 and G2 stages of CKD. The study group was divided into three almost equal groups according to vitamin D concentrations. In our analysis, we observed that vitamin D concentrations were lower in older patients and those with lower albumin levels. A study by Kwon et al. showed that concomitant reductions in vitamin D and albumin in older people are associated with reduced muscle strength and balance ability, which may translate into a loss of independence [19]. These results are confirmed by Spearman’s correlation, in which vitamin D correlates negatively with age. Vitamin D is absorbed from the intestine and the skin. This may be due to avoidance of sun and gastrointestinal problems [4]. Additionally, the concentration of vitamin D depends on the dietary intake; unfortunately, geriatric patients often develop nutritional disorders, and patients are often malnourished and experiencing the ‘anorexia of aging’ [20]. Ghrelin is a peptide hormone that plays a key role in the neurohormonal regulation of food intake (stimulates appetite), energy homeostasis, and growth hormone (GH) secretion [21]. In our study, along with a lower concentration of vitamin D, we also observed a lower concentration of ghrelin. These results are confirmed by Spearman’s correlation, in which vitamin D correlates positively with ghrelin. Vitamin D plays a role in stimulating the secretion of adipokines (leptin, adiponectin, resistin) and consequently affects the energy homeostasis of the body [13]. Our results suggest that vitamin D also affects ghrelin secretion. Furthermore, in our study, we observed higher leptin levels in patients with low vitamin D levels (with a trend toward significance). These results are confirmed by Spearman’s correlation, in which vitamin D correlates negatively with leptin. Our results from ROC curves demonstrated that leptin has a major effect on vitamin D concentration (AUC = 0.685), and the cut-off for leptin was 7.38 ng/mL with $79.5\%$ sensitivity and $51.4\%$ specificity. Based on this, it is possible to distinguish between patients with low and high concentrations of vitamin D (cut-off point 18.5 ng/mL). Leptin is a peptide hormone synthesized by white adipose tissue [22]. It regulates energy homeostasis, reproductive and immune function, and metabolism (satiety hormone) [23]. Our results confirm the researchers’ findings. Gangloff et. al. showed an inverse relationship between vitamin D concentration and leptin secretion [24]. In addition, in our study, we observed higher C-reactive protein levels in patients with low vitamin D levels (with a trend toward significance). These results are confirmed by Spearman’s correlation, in which vitamin D correlates negatively with hsCRP. Laird et al. suggested that there is an inverse correlation between vitamin D levels and CRP levels as a biomarker of inflammation [25]. Vitamin D plays a key role in the modulation of the inflammatory system, regulates the production of inflammatory cytokines, and inhibits the proliferation of pro-inflammatory cells [26]. Vitamin D deficiency, through impaired cellular response, affects the immune system, which is related to the occurrence of, for example, inflammatory bowel diseases. Vitamin D modulating the immune system can also affect the course of cancer and infectious diseases [27]. The study cohort was categorized into three subgroups: 60 to 69 years (25 women), 70 to 79 years (27 women), and 80 to 89 years (22 women). In our study, we observed that the concentration of vitamin D was lower in older patients. Aging plays an important role in the conversion of active forms of vitamin D. Several studies suggested that the production of active forms of vitamin D is reduced by $50\%$ as a result of a decline in functioning nephrons. Vitamin D concentrations are also affected by exposure to sunlight. From April to September, the concentration of this vitamin increases by 10 ng/mL, resulting in only 4 months of the year where the concentration of the vitamin is lower. However, this is not always the case for older people, as they often avoid sunlight [28]. Decreased albumin levels as a result of malnutrition are the strongest predictor of morbidity and mortality. In our study, we observed a lower concentration of albumin in older patients. Vitamin D modulates pro-inflammatory cytokines that are associated with malnutrition, i.e., IL-1, Il-7, TNF-α [29]. The phenomenon of glucose intolerance associated with aging is not entirely clear. Glucose intolerance is a component of many factors, including increased body fat mass, decreased physical activity, medications, concomitant diseases, defects in insulin secretion, and decreased liver sensitivity that inhibit glucose output [30]. In our study, we observed a decrease in insulin concentration in relation to age, which supports the thesis that insulin secretion is impaired in older patients. Our observation is consistent with Gary et al. who observed that insulin decreases with age as a result of progressive damage to organs such as the pancreas [31]. Our results are of interest because we observed significantly lower concentrations of glucose due to age (with a tendency to significance). Based on the data obtained, it can be speculated that hyperglycemia may be observed less frequently in aging women. Homeostasis model assessment of insulin resistance (HOMA-IR) is a simple and useful method for evaluating insulin sensitivity. In our study, HOMA-IR reduced with age. These results are confirmed by Spearman’s correlation, in which HOMA-IR correlates negatively with age. Ghrelin stimulates appetite and the secretion of growth hormone (GH). In our study, we observed that ghrelin secretion was lower in older patients. These results are confirmed by Spearman’s correlation, in which HOMA-IR correlates negatively with ghrelin. Decreased GH secretion is associated with decreased lean body mass and increased fat mass. This altered lipid metabolism results in increased mortality (development of vascular disease) [32]. One of the factors affecting ghrelin secretion is sex hormones. In this study, they were eliminated because the patients were postmenopausal. Adiponectin is a protein synthesized in adipose tissue. It reduces insulin resistance and has anti-inflammatory and anti-atherosclerotic effects. Serum adiponectin levels are affected by many factors, including age [33]. In our study, we observed higher concentrations of adiponectin in patients aged 70 to 79 than in those aged 60 to 69 years (with a tendency to significance). Considering that adiponectin has an anti-atherosclerotic effect, it is interesting to note that it increases in older people, which may suggest that older people are somehow not likely to develop atherosclerosis. ## Limitations of the Study There are some limitations that we would like to introduce. We enrolled a small number of patients; which could constitute a bias; data should be confirmed in larger populations. The study was performed in a daily clinical routine, the sample size was dependent on receiving patients’ consent for participation and meeting with patients’ restricted inclusion criteria. Since we only analyzed women of Polish descent, our findings are, therefore, not necessarily directly suitable for other ethnic groups ## 5. Conclusions Despite the limited number of geriatric individuals included in the study, our results uncover some relevant issues: [1] The link between the concentration of vitamin D and eGFR was found in geriatric populations. Based on our study, we postulate that vitamin D concentration can predict chronic kidney disease. [ 2] According to the Youden index, we suggest that the cut-off point 22,450.00 ng/mL of visfatin concentration assessed in serum through an immunoenzymatic method may serve as a value which discriminates between patients with impaired eGFR and those without it. [ 3] Our results indicate that leptin may be used as an adequate, non-invasive prognostic biomarker of vitamin D deficiency in older females. Leptin reached the most accurate AUCROC = 0.685; ($$p \leq 0.0291$$) for vitamin D deficiency prediction, with a cut-off value of 7.38 ng/mL with $79.5\%$ sensitivity and $51.4\%$ specificity. [ 4] Lower vitamin D concentration is associated with lower ghrelin levels in older women and indirectly with nutritional status expressed by low albumin levels. [ 5] Further study in this regard is needed to confirm our findings. ## References 1. 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--- title: Natural Product Skatole Ameliorates Lipotoxicity-Induced Multiple Hepatic Damage under Hyperlipidemic Conditions in Hepatocytes authors: - Sin-Hyoung Hong - Yeonhee Hong - Minji Lee - Byeong-Rak Keum - Gun-Hwa Kim journal: Nutrients year: 2023 pmcid: PMC10052055 doi: 10.3390/nu15061490 license: CC BY 4.0 --- # Natural Product Skatole Ameliorates Lipotoxicity-Induced Multiple Hepatic Damage under Hyperlipidemic Conditions in Hepatocytes ## Abstract Skatole (3-methylindole, 3MI) is a natural-origin compound derived from plants, insects, and microbial metabolites in human intestines. Skatole has an anti-lipid peroxidation effect and is a biomarker for several diseases. However, its effect on hepatocyte lipid metabolism and lipotoxicity has not been elucidated. Hepatic lipotoxicity is induced by excess saturated free fatty acids in hyperlipidemia, which directly damages the hepatocytes. Lipotoxicity is involved in several metabolic diseases and hepatocytes, particularly affecting nonalcoholic fatty liver disease (NAFLD) progression. NAFLD is caused by the accumulation of fat by excessive free fatty acids (FFAs) in the blood and is accompanied by hepatic damage, such as endoplasmic reticulum (ER) stress, abnormal glucose and insulin metabolism, oxidative stress, and lipoapoptosis with lipid accumulation. Hepatic lipotoxicity causes multiple hepatic damages in NAFLD and has a directly effect on the progression from NAFLD to nonalcoholic steatohepatitis (NASH). This study confirmed that the natural compound skatole improves various damages to hepatocytes caused by lipotoxicity in hyperlipidemic conditions. To induce lipotoxicity, we exposed HepG2, SNU-449, and Huh7 cells to palmitic acid, a saturated fatty acid, and confirmed the protective effect of skatole. Skatole inhibited fat accumulation in the hepatocytes, reduced ER and oxidative stress, and recovered insulin resistance and glucose uptake. Importantly, skatole reduced lipoapoptosis by regulating caspase activity. In conclusion, skatole ameliorated multiple types of hepatocyte damage induced by lipotoxicity in the presence of excess free fatty acids. ## 1. Introduction Nonalcoholic fatty liver disease (NAFLD) is caused by increased levels of free fatty acids (FFAs) due to metabolic diseases such as obesity and diabetes. It is a progressive liver disease caused by de novo lipogenesis [1]. NAFLD is the most common liver disease worldwide and is estimated to affect more than $30\%$ of the population [2]. Patients with NAFLD have increased levels of serum FFAs [3]. Moreover, FFAs induce excessive lipid accumulation in the liver, which is closely related to the pathogenesis of NAFLD [4]. Hepatic lipotoxicity occurs in cells with excess amounts of toxic lipids; therefore, circulating FFAs directly promote hepatic lipotoxicity [3]. In response to excess FFAs, hepatocytes undergo hepatic de novo lipogenesis. Subsequently, FFAs activate oxidative mechanisms such as lipid peroxidation [5] and induce oxidative stress [6,7] by producing reactive oxygen species (ROS) [8]. The hepatic lipotoxicity mechanism involves endo-plasmic reticulum (ER) stress and lipoapoptosis. FFAs directly induce protein unfolding and stimulate biosensors involved in ER stress such as PKR-like endoplasmic reticulum kinase (PERK) in the endoplasmic reticulum to induce nucleus signaling 1 (IRE1α), activating transcription factor 6 (ATF-6) [9], and the expression of these proteins is regulated by the binding immunoglobulin protein (BiP) [10]. When FFAs induce ER stress, c-Jun N-terminal kinases (JNK) increase C/EBP homologous protein (CHOP) levels in hepatocytes [11,12]. Continuous intracellular ER stress activates apoptotic pathways such as caspase cleavage, and which leads to lipoapoptosis in hepatocytes [13,14]. Tumor necrosis factor-alpha (TNF-α) is stimulated by FFAs, the decrease in anti-apoptotic protein B-cell lymphoma 2 (Bcl-2), and the increase in pro-apoptotic protein Bcl-2-associated X protein (Bax) and upregulation of caspase activity results in apoptosis [15]. Poly-ADP-ribose-polymerase (PARP) is related to lipoapoptosis mechanisms [16,17], and interleukin 6 (IL-6) and p38 mitogen-activated protein kinases (p38) initiate an inflammatory signaling pathway in response to FFAs [18]. Furthermore, increased FFA levels in the blood induce insulin resistance (IR) and gluconeogenesis. This leads to reduced glucose uptake in the liver [19] and induction of de novo lipogenesis in hepatocytes and steatosis characteristics resulting from excessive lipid accumulation [20]. FFA-induced hepatic lipotoxicity and subsequent ER stress, lipoapoptosis signaling, and inflammatory responses promote the progression of NAFLD to nonalcoholic steatohepatitis (NASH) [21]. The current therapeutic strategies targeting NAFLD aim to treat endoplasmic reticulum stress, oxidative stress, inflammation, and apoptosis induced by lipotoxicity, but there are no available therapeutic agents for the fundamental causes of lipotoxicity [22]. Palmitic acid (PA) is a representative composition of saturated FFAs in the human body [23] and is frequently used in the research of steatosis in the liver [24]. Since PA induces abnormal accumulation of lipids in hepatocytes and the development of hepatic steatosis in NAFLD [25], several previous studies have used PA-treated hepatocytes to induce various kinds of damage seen in NAFLD, including lipotoxicity [26,27,28]. Skatole is a naturally produced biologically active compound derived from the leaves of plants including jasmine [29] and Tecoma stans [30]. In addition, skatole is a microbial metabolite and is used as an ingredient in perfumes [31]. In humans, skatole is produced during tryptophan metabolism by bacteria in the intestines of vertebrates and is a component of feces and saliva in the intestines [32,33]. According to several studies, skatole levels are used as a biomarker to detect various pathological conditions in the human body [34], such as colorectal cancer [35], irritable bowel syndrome [36], and schizophrenia [37] by detecting the concentration of skatole and its metabolites in human urine or fecal samples. Some studies have reported that exposure to skatole causes pneumotoxicity [38,39] in bronchiolar exocrine cells. Although these studies have shown that toxicity occurs with high skatole concentrations, skatole has an antioxidant effect that prevents lipid peroxidation in the pulmonary alveolar epithelium [40]. Studies on skatole-induced toxicity in the lungs have been limited to rodents and ruminants in vivo [41,42], and there is a lack of research on the toxic effects of skatole on hepatocytes and its therapeutic potential. In the present study, we investigated the potential protective effect of skatole on hepatocytes in hyperlipidemic conditions and evaluated whether skatole modulates functions related to hepatic lipotoxicity-induced types of damage in FFA-stimulated hepatocytes. ## 2.1. Cell Culture, Preparation of Compounds, and Treatment HepG2 cells were purchased from ATCC (Manassas, VA, USA), and SNU-449 and Huh7 cells were purchased from the Korean Cell Line Bank (Seoul, Korea). All cells were cultured in Dulbecco’s modified Eagle’s medium (Hyclone, Logan, UT, USA) supplemented with $10\%$ fetal bovine serum (Gibco, Grand Island, NY, USA) and $1\%$ penicillin/streptomycin (Hyclone) at 37 °C in a humidified environment containing $5\%$ CO2. Skatole (purity ≥ $98\%$) was purchased from Selleckchem (Houston, TX, USA), and PA was prepared by conjugation of sodium palmitate (Sigma-Aldrich, St Louis, MO, USA) and fatty-acid-free bovine serum albumin (Sigma-Aldrich) according to Sigma-Aldrich’s instructions. A concentration of 0.25 mM PA was used to induce lipotoxicity-related damage by previously described methods [26,43]. ## 2.2. Cell Viability Assay Cells were seeded at a density of 2 × 104 cells/well in a 96-well plate and incubated at 37 °C in CO2 for 18 h before treatment. To determine the cytotoxicity effect of skatole, cells were treated with different concentrations of skatole (0, 1, 5, 10 μΜ) for different time periods (6, 12, 24, 48 h). To determine the cytotoxicity effect of FFAs and skatole, hepatocytes were treated with 0.25 mM PA and 1–10 μΜ skatole were treated for 24 h. All cells were incubated at 37 °C in atmosphere of CO2. After treatment, the Cell Counting Kit-8 (CCK-8) (Dojindo Molecular Technologies, Rockville, MD, USA) was added to the PA and skatole treated hepatocytes and additionally incubated for 1 h. Finally, the optical density was evaluated using SpectraMax M4 plate reader (Molecular Devices, San Jose, CA, USA) at 450 nm. Cell viability was normalized to the value of the control group and shown as a percentage. ## 2.3. Endoplasmic Reticulum Staining Cells were seeded at a density of 2 × 104 cells/well in a 96-well plate and incubated for 18 h before treatment. After treatment with PA and skatole, cells were stained with ER-Tracker for 1 h at 37 °C in an atmosphere of $5\%$ CO2. The nuclei were stained with 0.1 µg/mL Hoechst 33342 (ChemoMetec, Bohemia, NY, USA) for 5 min at 25 °C and examined using an Opera Quadruple Enhanced High Sensitivity (QEHS) microscope (PerkinElmer, Boston, MA, USA) with an objective at 20× magnification, and the relative fluorescence was quantified using Columbus software (PerkinElmer, Boston, MA, USA). ## 2.4. Reactive Oxygen Species (ROS) Production To measure ROS production, hepatocytes were seeded at a density of 2 × 104 cells/well in a 96-well plate and incubated for 18 h before treatment. PA and skatole-treated cells and untreated cells were stained with 5 μM cell-permeant 2′,7′-dichlorodihydrofuorescein diacetate, H2DCFDA (Thermo Fisher Scientific, Cleveland, OH, USA), and 0.1 µg/mL Hoechst 33342 (ChemoMetec). Figures were obtained using the Opera QEHS microscope (PerkinElmer) with an objective at 20× magnification, and the relative fluorescence was quantified using Columbus software (PerkinElmer). ## 2.5. Western Blotting Cells were seeded at a density of 2 × 106 cells/well in a 6-well plate and harvested 24 h after treatment with 0.25 mM PA and 5 μΜ skatole. Total proteins were isolated from the PA and skatole treated hepatocytes using RIPA lysis extraction buffer (Thermo Fisher Scientific) or Phospho-safe buffer (Thermo Fisher Scientific) containing a proteinase inhibitor cocktail (Thermo Fisher Scientific) and phosphatase inhibitor cocktail (GenDEPOT, Barker, TX, USA), according to the manufacturer’s instructions. Protein concentrations in the cell lysates were determined using a bicinchoninic acid assay (BCA) protein assay kit (Thermo Fisher Scientific). Proteins (20 μg) were loaded and separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels and transferred to a polyvinylidene fluoride (PVDF) membrane (Merck, Darmstadt, Germany). After blocking with blocking solution ($5\%$ BSA/TBST) at 25 °C for 1 h, we incubated the membrane with the primary antibody at 4 °C for 18 h. The primary antibodies used are listed in Supplementary Table S1. Subsequently, horseradish peroxidase (HRP)-conjugated secondary antibodies were used to probe the membrane for 1 h at 25 °C. The proteins were visualized using ImageQuant LAS-4000 mini (GE Healthcare, Chicago, IL, USA), and the relative protein expression levels were measured using ImageJ software (US National Institutes of Health, Bethesda, MD, USA) [44]. ## 2.6. Apoptosis Assay Cells were harvested 24 h after treatment with or without 0.25 mM PA and 5 μΜ skatole and cultured in a $5\%$ CO2 incubator at 37 °C. After washing in phosphate buffered saline (PBS), the pellet was re-suspended in 1× annexin V binding buffer (BD Biosciences, San Jose, CA, USA), and the cell suspension (1 × 105 cells) was transferred to a new tube. The cell suspension was incubated with annexin V-FITC (BD Biosciences) and propidium iodide (PI) (Chemometec) for 15 min at 37 °C in the dark. Apoptotic cells were assessed by flow cytometry using a CytoFLEX cell sorter (Beckman Coulter, Brea, CA, USA) and CytExpert software (Beckman Coulter, Brea, CA, USA). ## 2.7. Caspase Activity According to the manufacturer’s instructions, caspase activity was measured using the FAM-FLICA in vitro caspase detection kit (ImmunoChemistry Technologies, Bloomington, MN, USA). Cells were harvested 24 h after PA and skatole treatment and cultured in a $5\%$ CO2 at 37 °C. After treatment, the pellet was re-suspended in apoptosis wash buffer, and the cell suspension (1 × 105 cells) was transferred to a new tube. In the dark, the cell suspension was incubated with 1x FAM-FLICA caspase 3&7 for 1 h at 37 °C. Caspase activity was detected using an EnSpire multimode plate reader (PerkinElmer) at 488 nm emission/515 nm excitation. ## 2.8. Nile Red Staining For the assay of lipid accumulation in PA-treated cells, the cells were seeded at a density of 1 × 104 cells/well in a 96-well plate and incubated at 37 °C in an atmosphere of $5\%$ CO2 for 24 h. After PA and skatole treatment, the cells were fixed with a $4\%$ paraformaldehyde solution in PBS (Thermo Fisher Scientific) for 15 min at 25 °C. The fixed cells were incubated with 1 μg/mL Nile Red (Invitrogen, Waltham, MA, USA) at 37 °C for 10 min in the dark. Subsequently, the nuclei were stained with 0.1 µg/mL Hoechst 33342 (ChemoMetec) for 5 min at 25 °C. The images of the stained cells were obtained using the Opera QEHS microscope with an objective at 20× magnification, and the relative fluorescence was quantified using Columbus software. ## 2.9. Lipid Peroxidation Assay According to the manufacturer’s instructions, the intracellular malondialdehyde (MDA) concentration was measured using a Lipid Peroxidation Assay Kit (Sigma-Aldrich) in cell lysates. The MDA contents were detected using an EnSpire multimode plate reader (PerkinElmer) at 532 nm emission/553 nm excitation. ## 2.10. Glucose Uptake Following the manufacturer’s protocol, glucose uptake was measured using a Glucose Uptake Cell-Based Assay Kit (Cayman, Ann Arbor, MI, USA). Cells were treated with 100 μg/mL 2-deoxy-2-[(7-nitro-2,1,3-benzoxadiazol-4-yl) amino]-D-glucose (2-NBDG) and incubated in PBS for 4 h. Glucose uptake was measured using an EnSpire multimode plate reader (PerkinElmer) at 485 nm emission and 535 nm excitation. ## 2.11. Statistical Analysis All results are presented as the mean ± standard deviation (SD). One-way analysis of variance (ANOVA) was performed with Tukey’s Multiple Comparison post hoc test using GraphPad Prism 5 software (GraphPad, San Diego, CA, USA) for statistical analysis. The statistical significance was set to $p \leq 0.05.$ At least three independent samples were performed for all experiments. ## 3.1. Skatole Regulates Lipid and Glucose Metabolism in HepG2 Cells with PA Treatmnet In previous studies, PA-treated HepG2 cells were widely used for research on hepatic damage associated with NAFLD [27,43]. We prepared an in vitro NAFLD model in which lipotoxicity was induced by treating HepG2 cells with 0.25 mM PA for 24 h. In a preliminary study, we performed efficacy screening for hepatic steatosis using a natural product library L1400 (Selleckchem) and confirmed the association between skatole and hepatic lipid metabolism (results not shown). To clarify the effects of skatole on lipid and glucose metabolism in hepatocytes related to lipotoxicity, PA-treated HepG2 cells were exposed to different concentrations of skatole in the range of 1–10 μM for 24 h. Skatole significantly decreased lipid accumulation at a concentration of 5 μM in HepG2 cells (Figure 1A,B). Similarly, 5 μM skatole treatment had an inhibitory effect on the expression of lipogenic factors (Figure 1C,D). Subsequently, we confirmed that skatole restored the glucose uptake of HepG2 cells at concentrations above 5 μM (Figure 1E), and the expression levels of gluconeogenesis-related proteins, D-glucose-6-phosphate phosphohydrolase (G6Pase), and phosphoenolpyruvate carboxykinase 1 (PCK1), and IR-related protein phosphor-protein kinase B (AKT) were regulated by skatole treatment (Figure 1F,G). These results indicate the effect of 5 μM skatole on PA-induced abnormal lipid and glucose metabolism; thus, 5 μM skatole was used for subsequent experiments. ## 3.2. Skatole Suppressed PA-Induced ER Stress and ROS Production in HepG2 Cells We evaluated whether skatole could control ER and oxidative stress caused by FFA-induced lipotoxicity. Initially, we investigated the effect of skatole on ER stress. Similar to a previous study that evaluated ER stress with ER fluorescence intensity in hepatocytes [45], we evaluated the regulatory effect of skatole on ER stress using fluorescence microscopy. Skatole reduced PA-induced ER intensity in HepG2 cells, suggesting that ER stress is suppressed by skatole treatment (Figure 2A,B), including reduced expression of the ER stress-related proteins, PERK, IRE1α, ATF-6, CHOP, BiP, JNK, and phosphor-eukaryotic initiation factor 2α (phosphor-eIF2α) (Figure 2C,D). Subsequently, we investigated the effect of skatole on oxidative stress. When HepG2 cells were exposed to PA, intracellular ROS levels in the HepG2 cells significantly increased compared to the control group. However, treatment with PA followed by skatole decreased ROS levels (Figure 2E,F). Next, we investigated lipid peroxidation levels by evaluating the intracellular MDA content. Similar to ROS levels, lipid peroxidation levels were downregulated by the skatole treatment of HepG2 cells (Figure 2G). These results suggest that skatole suppresses ER stress and ROS production in PA-treated HepG2 cells. ## 3.3. Skatole Attenuates PA-Induced Lipotoxicity by Reducing Apoptosis, Caspase Activity, and Inflammation in HepG2 Cells FFAs increase the population of apoptotic hepatocytes [46,47,48]. Thus, we evaluated changes in apoptotic parameters to clarify whether skatole attenuates lipotoxicity-induced inflammatory and lipoapoptosis signaling in hepatocytes. HepG2 cells were initially exposed to 1–10 μM skatole for up to 48 h to verify that skatole has a non-toxic effect on cells (Figure 3A). In addition, we confirmed that treatment with more than 5 μM of skatole restored the cell viability of the 0.25 mM PA-treated HepG2 cells (Figure 3B). Then, apoptotic cell populations in HepG2 cells were evaluated to determine the anti-apoptotic effect of skatole. The skatole-treated group exhibited decreased counts of total apoptotic cells and a significantly decreased number of late apoptotic cells (Figure 3C–E). In the same context, the levels of caspase activity were increased by PA treatment but were recovered to the level of the control group after skatole treatment (Figure 3F). In addition, skatole treatment decreased the expression levels of the apoptosis-related proteins, cleaved PARP and cleaved Caspase-3, and the pro-apoptotic protein, Bax (Figure 3G,H). During apoptosis, inflammatory signaling was stimulated. Therefore, we investigated the expression of inflammation-related proteins. As expected, skatole increased the expression of the anti-apoptotic protein, Bcl-2, and regulated the expression of inflammation-related proteins such as TNF-α, IL-6, and phosphor-p38 (Figure 3I,J). These results suggest that skatole treatment may significantly protect hepatocytes from PA-induced lipotoxicity, including apoptosis, caspase activation, and inflammation. ## 3.4. Skatole Is Non-Cytotoxic and Skatole Treatment Reduces ER Stress, Apoptosis, and Caspase Activity in SNU-449 and Huh7 Cells PA-treated SNU-449 and Huh7 cells were used to study abnormal intracellular hepatocyte metabolism induced by excess lipid accumulation, similar to the pathogenesis of NAFLD [26,42,49,50]. To further clarify the protective effects of skatole on hepatocytes undergoing lipotoxicity, we studied its effects using two additional hepatocytes: SNU-449 and Huh7 cells. First, we confirmed that skatole was non-cytotoxic to SNU-449 and Huh7 cells. We evaluated cell viability when cells were treated with skatole alone at concentrations of 1–10 μM for up to 48 h, and skatole did not affect cell viability in either hepatocyte (Figure 4A). Then, we investigated whether skatole treatment improves ER stress, an important characteristic of hepatic lipotoxicity. The upregulated fluorescence ER intensity by PA was restored by skatole treatment (Figure 4B,C), and the protein levels of ER stress markers were also downregulated by skatole treatment in SNU-449 and Huh7 cells (Figure 4D,E). Subsequently, to determine the concentration of skatole at which cytotoxicity caused by PA exposure was ameliorated, we measured the cell viability of SNU-449 and Huh7 cells treated with 0.25 mM PA and 1–10 μM skatole for 24 h (Figure 4F). As a result, SNU-449 and Huh7 cells treated with more than 5 μM showed anti-cytotoxic effects against PA treatment. To verify the effect of skatole on apoptotic features related to lipotoxicity, the apoptotic cell population was evaluated. Similar to the HepG2 cells, the apoptotic cell population ratio induced by PA was significantly reduced by skatole in SNU-449 and Huh7 cells. In particular, the late apoptotic cell population ratio tended to considerably decrease (Figure 4G,H). Furthermore, our results confirmed that caspase activity, one of the factors involved in apoptosis, and the expressed protein levels of the apoptotic protein, caspase-3, were also reduced by skatole in SNU-449 and Huh7 cells (Figure 4I–K). Notably, in Huh7 cells, caspase activity induced by PA was more sensitive to skatole than that in HepG2 cells and was noticeably reduced by skatole treatment to the levels of the control groups. The above results indicate that skatole reduces ER stress not only in HepG2 cells but also in other hepatocytes and protects cells from lipotoxicity by regulating apoptosis-related signaling such as that of caspase-3, thereby reducing apoptosis. ## 3.5. Skatole Treatment Reduces Lipid Accumulation and ROS Production and Enhances Glucose Uptake in SNU-449 and Huh7 Cells As discussed earlier, lipotoxicity caused by FFAs is closely related to impaired lipid accumulation, ROS production, and glucose uptake in hepatocytes. Thus, we evaluated whether skatole could restore these lipotoxicity-related features in SNU-449 and Huh7 cells. Lipid accumulation in SNU-449 and Huh7 cells was downregulated by 5 μM skatole (Figure 5A,B). Furthermore, we confirmed that skatole restored glucose uptake in a concentration-dependent manner, which was previously reduced by PA to normal levels in both SNU-449 and Huh7 cells (Figure 5C), and ROS production was decreased by treatment with 5 μM skatole (Figure 5D,E). These results confirmed that 5 μM skatole treatment has an anti-lipotoxic effect on hepatocytes treated with excessive PA. ## 4. Discussion Here, we describe the beneficial role of skatole in reducing hepatic damage induced by lipotoxicity in three different hepatocytes, i.e., HepG2, SNU-449, and Huh7 cells. This protective effect involves reduced ER stress, oxidative stress, lipogenesis, caspase activity, and apoptosis. In addition, skatole improved lipotoxicity-induced IR and glucose uptake in hepatocytes. In general, it has been found that skatole can act as a ligand for aryl hydrocarbon receptor (AhR) and regulate the expression of specific genes of the cyp family, the target gene of AhR, in several cell lines and primary human cells [51,52,53]. Several reports have indicated that high skatole concentrations are toxic via cyp enzyme activities [54,55,56] and cyp-mediated oxidation induced by skatole [57]. However, in the human colon cancer cell line Caco-2, cell viability decreased with treatment of 250 μM skatole for 72 h, which is a higher dose than was used in our study. In addition, Caco-2 cells exposed to 1000 μM of skatole for 24 h showed an increase in cyp1a1 protein level but no statistically significant change in apoptosis levels [58]. According to another previous study, skatole induced the AhR target gene, cyp1a1, in human primary hepatocytes when treated at 200 μM. However, a low-concentration skatole treatment was reported to have no significant association with AhR signaling. In addition, skatole showed a low affinity for the AhR ligand in Hepa1c1c7, a hepatoma cell line [59]. Considering these previous studies, a low-concentration skatole treatment has an insignificant effect on hepatocyte AhR, cyp enzymes, and cell viability. In line with previous studies, in our study, a low-concentration skatole treatment did not affect hepatocyte cell viability but showed a protective effect. In this paper, we describe the protective role of skatole in hepatic lipotoxicity, which is caused by exposure to excess lipids and carbohydrates that damage the liver. Similar to our findings, indole-propionic acid (IPA), a 3-substituted indole-like skatole [60] and one of the microbial-derived metabolites of tryptophan, reduced lipotoxicity during the development of NAFLD and improved insulin sensitivity in diabetic animal models [61,62]. In addition, IPA has been reported to prevent lipotoxicity, hepatic lipid synthesis, and inflammatory factors caused by NAFLD [63,64]. In a previous study, J774A.1 cells treated with 250 or 500 μM of IPA showed reduced inflammation in vitro, and hepatic inflammation and injuries were reduced in rats treated with 20 mg/kg/day of IPA [65]. In this study, we determined the lowest concentration of skatole (5 μM) that shows a protective effect for several types of FFA-induced damage. According to previous studies and our findings, these indole metabolites may modulate hepatic lipotoxicity via various mechanisms in the body and have potential for therapeutic approaches. Indole metabolites, which are produced by the human gut microbiome, have been reported to regulate the immune response [66], and recent studies have shown that they are associated with NAFLD via the gut–liver axis [67]. Furthermore, a previous study showed that the concentration of indole metabolites in the blood of obese patients with NAFLD was reduced compared to that of healthy subjects [68]. Hence, the concentration of indole metabolites can be regarded as a factor related to NAFLD. Despite this association, the relevance of skatole in hepatic metabolic processes has been limited to studies in pigs [69], and the role of skatole in NAFLD and its metabolic processes in the liver is not fully understood. Lipotoxicity is a promising therapeutic target for various metabolic diseases, such as type 2 diabetes [70], ischemic heart disease, and insulin resistance of skeletal muscle [71]. In addition, recent studies have reported that natural compounds can ameliorate hepatic lipotoxicity [72], and hepatic lipotoxicity is a promising target for the development of therapeutic agents for NAFLD [73]. 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--- title: Capsicum baccatum Red Pepper Prevents Cardiometabolic Risk in Rats Fed with an Ultra-Processed Diet authors: - Aline Rigon Zimmer - Bianca Franco Leonardi - Eduardo Rigon Zimmer - Alexandre Pastoris Muller - Grace Gosmann - Luis Valmor Cruz Portela journal: Metabolites year: 2023 pmcid: PMC10052057 doi: 10.3390/metabo13030385 license: CC BY 4.0 --- # Capsicum baccatum Red Pepper Prevents Cardiometabolic Risk in Rats Fed with an Ultra-Processed Diet ## Abstract Metabolic syndrome is a serious health condition reaching epidemic proportions worldwide and is closely linked to an increased risk of cardiovascular problems. The lack of appropriate treatment paves the way for developing new therapeutic agents as a high priority in the current research. In this study, we evaluated the protective effects of Capsicum baccatum red pepper on metabolic syndrome scenarios induced by an ultra-processed diet in rats. After four months, the ultra-processed diet increased central obesity, triglycerides, total cholesterol, LDL-cholesterol plasma levels, and impaired glucose tolerance. The oral administration of C. baccatum concomitantly with the ultra-processed diet avoided the accumulation of adipose tissue in the visceral region, reduced the total cholesterol and LDL fraction, and improved glucose homeostasis, factors commonly associated with metabolic syndrome. The data presented herein reveal an important preventive action of C. baccatum in developing metabolic disorders among animals fed a hypercaloric diet, significantly reducing their cardiometabolic risk. Allied with the absence of toxic effects after chronic use, our study suggests C. baccatum red pepper as a secure and enriched source of bioactive compounds promising to protect against pathological processes associated with metabolic syndrome. ## 1. Introduction Metabolic syndrome is a complex disorder represented by a set of factors commonly associated with insulin resistance, central obesity, glucose intolerance, hypertension, hypertriglyceridemia, and low levels of HDL-cholesterol [1]. The association of metabolic disorders such as the increase in plasma cholesterol and the imbalance in glucose homeostasis may lead to the development of metabolic syndrome, which has been reaching a broad segment of the adult population [2]. Enormous interest has arisen in the scientific community for that clinical condition, since it is characterized by a number of factors or conditions at risk of cardiovascular disease [3]. Metabolic syndrome increases the risk of cardiovascular disease by five-times, increasing the overall mortality rate 1.6 times [4]. Several factors contribute to the development of metabolic disorders such as the consumption of ultra-processed diets rich in sugar and fat as well as a sedentary lifestyle. As a consequence, an increase in obesity and the emergence of pathologies such as type 2 diabetes, dyslipidemia, and metabolic syndrome has been observed [5,6,7]. A common alternative frequently used by patients suffering from chronic conditions associated with metabolic disorders refers to the use of natural products with popular description of glycemic and cholesterol control and anti-obesity effects. In the literature, several reports mention plant-based dietary interventions for controlling diabetes and dyslipidemia, and some of them have demonstrated effectiveness in preclinical and clinical trials [8,9,10,11,12]. The genus Capsicum, from the Solanaceae family, consists of several species of peppers and have shown interesting therapeutic potential in this context. Various studies conducted with Capsicum species, in particular concerning the species C. annuum and C. frutescens, have demonstrated analgesic and anti-inflammatory activities as well as beneficial properties on glucose and lipid metabolism [13,14,15,16,17,18,19,20,21,22]. The species of Capsicum baccatum var. pendulum (pimenta dedo-de-moça), one of the most consumed peppers in Brazil, demonstrates potential as an antioxidant and anti-inflammatory agent [23,24,25]. Recently, after a bioguided assay, our group showed that the butanol (BUT) extract of C. baccatum presented anti-inflammatory and antioxidant properties correlated with the flavonoid and total phenolic contents [23]. Furthermore, no adverse effects were observed on behavioral, hematological, and metabolic parameters after long-term oral administration of C. baccatum, suggesting a level of pharmacological safety [26]. The biological potential and safety of C. baccatum BUT extract open the perspective to a deeper understanding of its effects in chronic disorders involving inflammatory pathways and oxidative burden. The inflammatory and redox status are important components associated with chronic diseases that include most forms of cardiovascular disease, type 2 diabetes, and metabolic syndrome, representing the greatest health threats [3,27,28,29]. Continuing the pharmacological investigation of C. baccatum, our study aimed to evaluate the impact of BUT extract administration in a metabolic syndrome scenario induced by an ultra-processed highly palatable (HP) diet in rats. This kind of diet, rich in saturated fat and sucrose, produces a state of obesity, dyslipidemia, and glucose intolerance, mimicking several risk factors that contribute to the development of the metabolic syndrome. Thereby, Wistar rats were submitted to 4 months of an ultra-processed HP diet and received BUT extract orally during the diet period. The C. baccatum BUT extract was selected due to its appreciable anti-inflammatory, and antioxidant activities previously reported [23]. It is important to emphasize the lack of studies regarding the use of this plant species in metabolic syndrome and the possible prevention of cardiovascular risk factors. ## 2.1. Plant Material and Extraction Capsicum baccatum var. pendulum (Willd.) Eshbaugh (Solanaceae) fruit was obtained from a cultivated area in Turuçu, Rio Grande do Sul, Brazil, after being allowed access to genetic resources of the Brazilian Genetic Patrimony Management Council (CGEN number $\frac{010393}{2015}$-3). A voucher specimen (ICN 181469) was identified and deposited at the Herbarium of the Universidade Federal of Rio Grande do Sul (UFRGS). The fruit of red pepper was dried in a circulating air stove (40 °C) and triturated to powder. The fruit was submitted to successive extractions in a Soxhlet apparatus in order to obtain the butanol (BUT) dried extract, enriched in bioactive substances (187.51 mg of total phenolic compounds and 54.68 mg of flavonoids per gram of dried extract), as previously described [23]. ## 2.2. Animals and Experimental Design Adult 60 days Wistar male rats (Rattus norvegicus), weighing 200–250 g, were obtained from the Central Animal House of the Department of Biochemistry (UFRGS). The animals were maintained under controlled temperature (22 ± 2 °C) and humidity (55 ± $10\%$) conditions on a 12 h light-dark cycle (7:00 a.m. and 7:00 p.m.). Animal care followed the international standards for animal protection and official governmental guidelines and was approved by the Ethical Committee on animal use of UFRGS, Brazil (approval number 19446). The rats were randomly assigned to one of four experimental groups: [1] the standard diet (SD) group ($$n = 10$$), which received standard laboratory rat chow ($50\%$ carbohydrate from starch, $25\%$ protein, and $4\%$ fat) and saline daily by gavage for 130 days; [2] the SD group plus BUT extract (SD + BUT, $$n = 10$$), which received standard laboratory rat chow and 200 mg/kg of C. baccatum BUT extract daily by gavage for 130 days; [3] the ultra-processed highly palatable (HP) diet group ($$n = 10$$), which received an enriched diet in simple sugars and saturated fat ($65\%$ carbohydrates ($34\%$ from condensed milk, $8\%$ from sucrose, and $23\%$ from starch), $25\%$ protein, and $10\%$ of fat (soybean oil) and saline daily by gavage for 130 days; and [4] the HP diet group plus BUT extract (HP + BUT, $$n = 10$$), which received HP diet and 200 mg/kg of C. baccatum BUT extract daily by gavage for 130 days [30]. The dosage of 200 mg/kg of C. baccatum was selected considering our previous study showed relevant anti-inflammatory and antioxidant properties [23,26]. In addition, the 130 days (nearly 18 weeks) of diet exposure was established according to previous studies of our research group and collaborators, suggesting 13 to 19 weeks of diet consumption to significantly impact the metabolic outcomes in the animals [30,31,32]. All animals had free access to food and water. The animals’ body weight was measured weekly throughout the study period. The initial and final body weight and the weight gain were compared among groups. Clinical signs of toxicity, general appearance, and mortality were monitored daily during the experimental period. ## 2.3. Blood Sampling, Organs, and Tissues Collections At the end of the experimental protocol, the animals were anesthetized (ketamine:xylazine, 100:10 mg/kg, i.p.) for blood sampling for hematological and biochemical analysis. After blood collection, animals were humanely sacrificed (exsanguinated), quickly dissected, and the liver, brain, heart, and kidneys were excised and weighed individually. Fat tissues from the retroperitoneal and epididymal regions were dissected and weighed as previously described [33], and the total fat mass was considered as the sum of both. Organ/tissue absolute weight was compared with the final body weight of each rat on the day of sacrifice to determine the relative organ/tissue weight (absolute organ/tissue weight (g) × 100/animal body weight (g). ## 2.4. Glucose Tolerance Test and Glycosylated Hemoglobin A glucose tolerance test was performed 130 days after the beginning of animal experimentation. A $50\%$ glucose solution was injected to 8 h fasted rats (i.p, 2 g/kg body weight), and the blood sample was collected by a small puncture on the tail immediately before, 30, 60, and 120 min after the injection [34]. At each time, glucose was measured by a glucosimeter (AccuChek Active, Roche Diagnostics®, São Paulo, SP, Brazil). In addition, glycosylated hemoglobin was determined by ELISA kits (Katal Biotecnológica® Ind. Co., Ltd., Belo Horizonte, MG, Brazil, https://www.katal.com.br/Reagentes (accessed on 2 March 2023) at the end of treatment. ## 2.5. Lipid Profile and Atherogenic Index The lipid profile of the animals that received the different diets (SD or HP), treated or not with the C. baccatum BUT extract, was evaluated through the measurement of the total content of triglycerides (TG), total cholesterol (TC), and the fractions of high-density (HDL-c) and low-density (LDL-c) lipoprotein cholesterol with commercial kits (Katal Biotecnológica® Ind. Co., Ltd., Belo Horizonte, MG, Brazil, https://www.katal.com.br/Reagentes (accessed on 2 March 2023). The atherogenic index (AI), which is the measure of the atherosclerotic lesion extent based on serum lipids, was determined in all groups as (TC)/(HDL-c) [35]. ## 2.6. Biochemical and Hematological Analysis For the assessment of renal and hepatic functions, the plasma levels of creatinine, urea, albumin, alanine aminotransferase (ALT), alkaline phosphatase (ALP), and gamma-glutamyl transpeptidase (GGT) were measured through commercial kits (Katal Biotecnológica® Ind. Co., Ltd., Belo Horizonte, MG, Brazil, https://www.katal.com.br/Reagentes (accessed on 2 March 2023). All analyses were performed at Spectramax® M5 (Molecular Devices, San Jose, CA, USA). Furthermore, the following hematological parameters were determined by using a semiautomatic blood analyzer (MS4, USA): hemoglobin (Hb), red blood cell (RBC) count, hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), white blood cell (WBC) count, the cytological differential (percentage of lymphocytes and neutrophils), and platelets. ## 2.7. Behavioral Tasks The effects of the C. baccatum BUT extract on spontaneous locomotion, exploratory activities as well as the anxiety-like behavior of the animals were evaluated by the open field task [36], the light–dark exploration task [37], and the elevated plus-maze task [38]. After each trial, the apparatus was cleaned with an ethanol solution ($70\%$). All behavioral tasks were performed between 1:00 PM and 5:00 PM. A video camera positioned above the apparatus was used to record all experimental sessions, and the analysis were performed using a computer-operated tracking system (ANY-maze®, Stoelting, Woods Dale, IL, USA). ## 2.7.1. Open Field Task The open field task is a widely used model for the evaluation of spontaneous locomotion and exploratory activities. The rats were gently placed in the center of the arena (50 × 50 cm; 50-cm-high walls), and the total distance travelled, and mean speed were measured for 10 min [36]. ## 2.7.2. Light–Dark Exploration Task The rats were submitted to the light–dark task as described by Crawley and Goodwin [37]. The task consisted of a box (40 × 50 × 60 cm) divided equally into two compartments: the light compartment (60 W light), and the dark compartment (room illumination at 20 W). Rodents are nocturnal animals, preferring darker areas, and the decrease in the exploratory activity in the light area is taken as a measure of anxiety. Animals were gently placed in the corner of the light compartment and left free to explore for 5 min. The following parameters were analyzed: [1] the total time spent in the light compartment; [2] the number of transitions from light to dark, defined as placing the four paws into the light compartment; and [3] the risk assessment behavior index (RA, i.e., the number of investigations of the light compartment by placing some but not all paws). ## 2.7.3. Elevated Plus-Maze Task The elevated plus-maze measures anxiety-like behavior in rodents and was performed as previously described [38]. The experiments were conducted under a dim red light in a quiet room. The animals were placed individually on the central platform (5 × 5 cm) of the plus-maze facing one of the open arms and recorded with a video camera for 5 min. The time spent in the open (50 × 10 cm) and closed arms (50 × 10 × 40 cm), the number of entries into the arms, the total distance travelled, and the mean speed were analyzed. ## 2.8. Statistical Analysis Statistical analysis was performed using GraphPad Prism® 8.0. The results were expressed as the mean ± standard error of the mean (S.E.M.) and statistically analyzed by two-way analysis of variance (ANOVA), followed by a Tukey’s test for multiple comparisons. Differences were considered significant at $p \leq 0.05.$ ## 3.1. Body Weight, Adipose Tissue Weights The body weight was monitored throughout the entire trial period (Figure 1A,B) to evaluate the effects of the HP diet intake and the use of the BUT extract of C. baccatum on the animal’s body composition. At the end of the experiment, animals receiving the HP diet had significantly higher weight gain ($67\%$ increase) than the animals that received the SD diet ($49\%$ increase), demonstrating that the HP diet induced an obesity profile (Figure 1B). Evaluating the effects of the BUT extract on body weight, we can verify a reduction in the final weight of the group receiving the SD diet plus BUT extract, despite no differences in the weight gain compared to the control group (SD) (Figure 1B). Furthermore, the group receiving the BUT extract and HP diet (HP+BUT) showed no significant differences in the final body weight and weight gain when compared with the control group (SD), indicating that treatment with the C. baccatum extract exhibited a downward in the weight gain over time (Figure 1A,B). When evaluating the fat tissue deposits, specifically in response to different diets, a substantial increase in the total ($107.2\%$) and retroperitoneal ($209.0\%$) fat pad weight in rats consuming the HP diet was observed compared to the control group (Figure 1C). Notably, the treatment with the BUT extract significantly avoided the accumulation of adipose tissue in the abdominal region of the rats fed a HP diet (Figure 1D), suggesting that there were significant physiological adjustments in regulatory pathways of lipid metabolism, promoting lower triglyceride storage in visceral tissues. Overall, these data highlight the prophylactical positive effect of C. baccatum red pepper on the body weight gain and central obesity of rats submitted to an ultra-processed diet, indicating an anti-obesity potential. ## 3.2. Lipid and Glycemic Profiles The lipid profile of animals treated or not with the BUT extract that received a SD or HP diet is shown in Figure 2A–E. It was verified that there was a significant increase in the content of triglycerides ($46.8\%$ increase, Figure 2A), total cholesterol ($182.3\%$ increase, Figure 2B), and LDL-cholesterol levels ($534.0\%$ increase, Figure 2D) in animals receiving the HP diet compared to animals that received the SD diet. The treatment with the BUT extract (200 mg/kg, per os) for 130 days was able to prevent the increase in the total content of cholesterol (Figure 2B) and LDL-c fraction (Figure 2D) in animals receiving the HP diet (HP + BUT), avoiding the rise in these two parameters in a condition of high intake of carbohydrates and lipids. There was no difference in the plasma HDL-cholesterol among the experimental groups (Figure 2C). In the determination of the AI (Figure 2E), a widely used parameter for estimating cardiovascular risk, a marked increase in the risk (3.3 times) was observed among the animals that received only the HP diet. On the other hand, the treatment with C. baccatum provided a significant reduction in AI compared to the HP group, reducing around two times the risk of cardiovascular events to which these animals were submitted. The plasma glucose profile of animals receiving both diets, treated or not with the C. baccatum BUT extract, was assessed through the glucose tolerance test (GTT). The HP diet triggered significant changes in glucose homeostasis since an impairment in glucose tolerance was evident after 130 days of diet consumption (Figure 2G,H). After this period, the plasma glucose of the animals of the HP group was higher at all time points of the GGT (fasting, 30, 60, and 120 min). The most interesting result is that animals treated with the BUT extract did not develop this glucose intolerance in the presence of the HP diet, maintaining glucose levels in this group (HP + BUT), similar to those observed in the control animals (SD group, Figure 2G). The total AUC of the plasma glucose levels resulting from GGT remained approximately $35\%$ and $30\%$ lower in SD and HP+BUT, respectively, compared to the HP group (Figure 2H). These findings suggest that the C. baccatum extract reduced the blood glucose levels and improved glucose tolerance. When the glycosylated hemoglobin of animals was measured, there were no significant differences (Figure 2F). ## 3.3. Examination of the Organs, Biochemical, and Hematological Analysis All animals appeared healthy at the end of the experimental period. No clinical signs of toxicity including hair loss, piloerection, changes in skin, eyes, or oral mucosa, nor death were observed (Supplementary Figure S1). Visceral examinations of the brain, heart, kidney, and liver of the control and treated rats revealed no visible lesions. Moreover, in Table 1, no significant alterations in the relative weight of the organs were observed among groups ($p \leq 0.05$). In order to determine the impact of the different diets and C. baccatum BUT extract on the kidney and liver function, some biochemical markers were analyzed (Table 1). There was no significant difference among groups in ALT, ALP, GGT, albumin, urea, and creatinine at the end of the experiment compared to the control group (SD). In the hematological evaluation, there were no significant differences among groups in the analyzed parameters: RBC count, Hb, HCT, MCV, MCH, MCHC, RDW, platelets, WBC count, and lymphocyte and neutrophil content (Table 1). ## 3.4. Behavioral Tasks In the behavioral assessment of the different groups, a decrease in exploratory activity and spontaneous locomotion was observed in animals that received the HP diet since they showed a decrease in the total distance travelled (Figure 3A–B) and mean speed (Figure 3C) during the open field task. Figure 3A,D show the analysis of the total distance traveled by the animals throughout the experiment minute by minute, and the degree of occupation of the box, respectively. These data clearly demonstrate the sedentary behavior of the animals receiving the HP diet. Interestingly, the treatment with 200 mg/kg BUT extract reversed this effect of the HP diet, normalizing the exploratory activity and spontaneous locomotion of the animals (HP + BUT). Regarding the anxiogenic profile of animals, no changes were observed in the light–dark exploration task (Figure 3E–G) and in the elevated plus-maze task (Figure 3H–M). In the light–dark exploration task, there was no difference in the total time spent in the light compartment (Figure 3E), the number of transitions from light to dark (Figure 3F), and the risk assessment behavior index (Figure 3G) compared to the control group. Similarly, in the elevated plus-maze task, no differences were observed among groups in the total distance travelled (Figure 3H, and Supplementary Figure S2), mean speed (Figure 3I), entries in open (Figure 3J) and closed arms (Figure 3K), and time spent in open (Figure 3L) and closed arms (Figure 3M). These results indicate that the BUT extract did not cause alterations in the anxiety-like behavior of the animals. ## 4. Discussion Diet has been recognized as one of the most critical factors in managing metabolic disorders such as dyslipidemia, diabetes mellitus, and metabolic syndrome [6,39]. An ultra-processed high palatable diet (HP), also named the cafeteria diet, or Western-style diet, is enriched in simple sugars and saturated fat, and its consumption contributes to weight gain, obesity, and insulin resistance [2,7]. Many authors have reported the potential of some spices such as garlic, onion, and peppers to influence the body metabolism by experimentally documented investigations [12,13,40,41]. Red peppers are common in worldwide gastronomy and have been extensively consumed for centuries. The specie Capsicum baccatum var. pendulum is the most consumed species in Brazil, and concentrations of total phenols and flavonoids were significantly greater in the C. baccatum fruit compared with other species of peppers more broadly studied such as C. annuum or C. frutescens [23,24,42]. A recent chemical characterization of C. baccatum fruit identified 42 phenolic substances, and the flavonoids quercetin 3-O-rhamnoside, luteolin 7-O-glycoside, and naringenin were the most abundant compounds described [43]. These polyphenolic compounds are related to positive influences on lipid and glycemic metabolism [44,45,46,47], beyond presenting important antioxidant and anti-inflammatory activities [24,48]. Hence, a large prospective cohort investigated the dietary intake of individual polyphenols and their association with 5-year body weight change. Interestingly, the strongest inverse association with body weight was observed for quercetin 3-O-rhamnoside, suggesting that it may play a protective role against obesity with adipose tissue and systemic oxidative stress as a possible therapeutic target [49]. In addition, naringin has shown beneficial health effects in animals and humans including improved lipid and glucose metabolism and ameliorated cardiovascular dysfunctions [50,51]. Previously, our research group demonstrated that the BUT extract of C. baccatum showed the highest antioxidant and anti-inflammatory activities, and the total phenolic and flavonoid contents were positively correlated with both effects [23]. Furthermore, we demonstrated that 60 days of oral administration of the BUT extract had no toxic effects on hematologic, metabolic, and behavioral outcomes in normal male CF1 mice [26]. However, despite our findings, the physiological and pharmacological potential of C. baccatum has been scarcely explored. Based on these results, this study was designed to evaluate the effects of the Capsicum baccatum BUT extract on the lipid and glycemic metabolism of animals in conditions of unfavorable diet, mimicking a metabolic syndrome scenario, looking for an agent that associates activities that could be potentially promising for protection against cardiovascular risk factors. In this concern, the rats received different diets concomitantly with 200 mg/kg of the C. baccatum BUT extract or saline solution by gavage for 130 days. At the beginning of the experimental period, the mean body weights of the animals in all groups were very similar. However, at the end of the protocol, the mean body weight of rats fed with the HF diet was significantly greater than those receiving the SD diet. Interestingly, the administration of the C. baccatum extract associated with the HF diet prevented excessive weight gain, despite a similar dietary intake among the rats in the study. The animals’ lipid profile assessment after 130 days found that the treatment of C. baccatum BUT extract exerted beneficial effects by preventing the increase in serum total cholesterol and LDL-c fraction, thereby avoiding the rise in the atherogenic index (AI), even when the diet remained high in saturated fats and sugar. The classic lipid profile of the metabolic syndrome is characterized by elevated triglycerides, LDL-c, and low HDL-c, conditions that add to other components to determine a high cardiovascular risk [1]. The value and safety of lowering plasma LDL-c and AI in treating cardiovascular disease have been established unequivocally. In its native and oxidized forms, LDL-c causes direct endothelial cell injury and dysfunction, predisposing to an inflammatory response in the artery wall that promotes the development of an atherosclerotic plaque. Clinical studies have shown that decreasing plasma LDL-c significantly reduces coronary heart disease morbidity and mortality. The same occurs with AI. The higher the AI, the bigger the risk of fatty infiltration in the heart, coronaries, liver, and kidney, promoting oxidative damage to these organs [52,53]. Regarding the glycemic profile of the animals, the BUT extract demonstrated a significant antihyperglycemic ability since, in the presence of high carbohydrate consumption, was able to avoid the emergence of a profile of glucose intolerance, keeping the blood glucose levels of the animals similar to the control group. Insulin resistance and changes in glucose transporters are frequently present in metabolic syndrome. The excess of circulating free fatty acids, which originate from adipose tissue and triglyceride-rich lipoproteins, is an important contributing factor to this frame of insulin resistance. In the liver, free fatty acids increase the production of glucose, triglycerides, and low-density lipoproteins (LDL and VLDL). In the muscle, it reduces insulin sensitivity, inhibiting the uptake of glucose insulin-mediated. All of these factors influence the loss of glycemic control [54]. Another essential parameter in the relationship between metabolism and health concerns body fat distribution. The overweight associated with abdominal fat accumulation (visceral or central obesity) has emerged as a significant risk factor for cardiovascular disease and an essential component in diagnosing metabolic syndrome. Contemporary studies suggest that the accumulation of adipose tissue in the abdominal region precedes the development of other components of this syndrome [55,56]. The visceral adipose tissue is the fat deposit with higher atherogenic potential. On this site, the adipocytes have intense lipolytic activity, releasing large amounts of free fatty acids in the systemic circulation, increasing the endogenous synthesis of lipoproteins [57,58]. The treatment with the C. baccatum BUT extract significantly reduced the central obesity of the rats fed the HP diet. This finding, associated with the anti-dyslipidemic effects and the improvement in glucose homeostasis, corroborates the reduction in cardiometabolic risk in the presence of the C. baccatum BUT extract. Upon the need to establish the safety of the chronic use of the BUT extract in rats as well as ensure that the observed effects on the metabolism of are not related to toxicological changes, a behavioral, biochemical, and hematological evaluation was conducted. Furthermore, it is clearly important to perform studies to predict the safety profile of plant species using well-defined methodologies, simulating population use, and preconizing the cumulative toxic effects over long-term administration, as achieved in this research. Regarding the biochemical and hematological evaluation, no significant alterations that provided evidence of undesirable effects for the C. baccatum BUT extract were observed. Furthermore, no signs of toxicity induced by the BUT extract were observed in the hematopoietic system. A normal macroscopic appearance of all organs, particularly for the kidney and liver, the absence of toxicity was confirmed by the serum biochemical markers of the function of these organs. Behavioral assessment was performed through the open field, the light–dark, and the elevated plus-maze tasks. No differences were observed among the groups in the light–dark, and elevated plus-maze tasks, evidencing that the C. baccatum BUT extract does not induce anxiety-like behavior in the animals. In the open field task, there was a prejudice in the locomotor function of animals receiving the HP diet, confirmed by the reduction in total distance travelled and the mean speed during the test. These alterations may reflect an obese phenotype developed by the animals fed the HP diet once the final body weight of these animals was significantly higher. However, the group that received the HP diet and the C. baccatum BUT extract did not show this sedentary-like behavior presented by the HP group. Beyond differences in body weight, lipid, and glycemic profiles, the HP group animals showed a higher abdominal fat pad content than animals fed with the same diet but treated with the BUT extract. This set of factors might have contributed to the animals receiving C. baccatum but did not demonstrate alterations in exploratory activities and spontaneous locomotion. Hence, the results of the evaluation of the chronic use of C. baccatum in rats did not show any apparent toxic effect on the analyzed parameters. ## 5. Conclusions The data presented herein suggest that consuming an ultra-processed highly palatable (HP) diet leads to a phenotype of central obesity, unfavorable lipid profile, impaired glucose tolerance, and significantly increased cardiovascular risk. On the other hand, the administration of the C. baccatum BUT extract to rats associated with the HP diet prevented the increase in the total cholesterol and LDL-c levels, the imbalance in glucose homeostasis, and the visceral obesity, significantly reducing the cardiometabolic threat. 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--- title: 'Selenium Nanoparticles Based on Morinda officinalis Polysaccharides: Characterization, Anti-Cancer Activities, and Immune-Enhancing Activities Evaluation In Vitro' authors: - Mengxin Yao - Yuan Deng - Zhimin Zhao - Depo Yang - Guohui Wan - Xinjun Xu journal: Molecules year: 2023 pmcid: PMC10052065 doi: 10.3390/molecules28062426 license: CC BY 4.0 --- # Selenium Nanoparticles Based on Morinda officinalis Polysaccharides: Characterization, Anti-Cancer Activities, and Immune-Enhancing Activities Evaluation In Vitro ## Abstract Recently, selenium nanoparticles have been drawing attention worldwide, and it is crucial to increase the stability of nano-Se. Morinda officinalis polysaccharides (MOP) are the main active component in Morinda officinalis radix. However, their low activity has limited their application. A novel selenium nanoparticle (Se-MOP) was prepared to solve these problems using MOP as a dispersant. The zeta potential was measured to evaluate the stability, and UV and ATR-FTIR were used to investigate the binding type of selenium and MOP. The morphology was observed by the TEM method. Furthermore, the inhibitory effect on five selected cancer cells (HepG2, MCF-7, AGS, PC9, and HCT8) was evaluated, showing remarkable inhibition of all five cancer cells. The mechanism of inhibition was also investigated by cell circle assay, and it was found that Se-MOP could induce cell circle G0/G1 phase arrest. Immune-enhancing activities were evaluated by measuring the proliferation and cytokines of mouse spleen lymphocytes in vitro and quantitative RT-PCR. The results indicated that single stimulation of Se-MOP and synergistic stimulation with PHA or LPS increased immune capacity and improved immune by increasing the expression of cytokines. ## 1. Introduction Selenium (Se) is an essential element for human beings. It was discovered in nature in two forms: inorganic and organic selenium. Sodium selenite and selenate are two forms of inorganic selenium that are included as components of dietary supplements [1]. Selenoproteins and selenium analogs of amid acids (e.g., selenomethionine and selenocysteine) are two forms of organic selenium found in plants, animal foods, and selenium yeast [2,3]. In metabolism, selenium plays a vital role in synthesizing the active center of glutathione peroxidase and other significant enzymes. In low selenium supply, the specific proliferation ability of T cells and the number of natural killer cells are both decreased [1,4]. The risk of suffering from Keshan disease [5], cardiovascular diseases [6,7], type 2 diabetes [8], and cancer [9,10,11] may rise due to a deficiency of selenium. China has abundant selenium resources but needs to be more balanced. A long and narrow selenium-deficiency zone from the east to the southwest hinterland has caused over one hundred million people to suffer from low selenium supply [12]. However, Enshi, a city in Hubei Province, China, is renowned as the “Selenium Capital” worldwide. Several incidents of selenium poisoning occurred in this city due to excess inorganic selenium supplements in the soil [13]. To fully use selenium resources in China, reducing the toxicity of inorganic selenium and improving the efficiency of selenium supplementation are crucial. Nano-selenium is a new zero-valent elemental selenium type, the least toxic form of selenium known [14]. Usually, zero-valent elemental selenium cannot be absorbed by humans directly. However, nano-selenium has completely different properties, including color changing (from black or gray to orange), increased water solubility, and significantly increased bioactivities [15]. It was reported in one study that the nano-selenium particle size and bioactivities were negatively correlated [16]. The biggest problem with selenium nanoparticles is their tendency to aggregate [17]. Based on this situation, researchers sought a proper dispersant and turned their attention to polysaccharides, a naturally macromolecular substance. Liu et al. reported a redox reaction between sodium selenite and ascorbic acid generated nano-selenium through the addition of Oudemansiella radicata polysaccharides as a dispersant [18]. Morinda officinalis radix, a geo-authentic crude drug of Guangdong province, is a widely-used traditional Chinese medicine. Morinda officinalis polysaccharide (MOP) is one of the foremost effective components with many pharmacological activities, such as antioxidation, anti-depression, anti-osteoporosis, immune system enhancement, and reproductive capacity enhancement [19,20,21,22,23,24]. Xu obtained a homogeneous MOP, and its molecular weight was 63 KDa. It comprised arabinose, glucose, rhamnose, galactose, etc. [ 25]. Moreover, MOP has been used as an immunopotentiator [26] and leukopenia treatment in mice [27]. Furthermore, the MOP has numerous active hydroxyl groups and excellent water solubility with non-toxicity. These properties indicate the potential of MOP becoming a suitable nanoparticle dispersant. Therefore, in this article, a novel nano-selenium-MOP (Se-MOP) was prepared from sodium selenite and ascorbic acid and used MOP as a dispersant. The characterization of Se-MOP was determined by various methods. Furthermore, five kinds of cancer cells were chosen to evaluate the inhibitory effect. Moreover, the immune enhancement was also evaluated in vitro. ## 2.1.1. Measurement of Size and Zeta-Potential The results are shown in Table 1. The particle size of Se-MOP was 67.25 ± 0.99 nm ($$n = 3$$). In contrast, the particle size of MOP was 153.97 ± 10.65 nm ($$n = 3$$). The polydispersity index (PDI) average of Se-MOP was 0.10 ± 0.02 ($$n = 3$$). All PDI values were close to 0.1, manifesting a narrow range of distribution (Figure 1), suggesting the even size of all particles. The zeta potential of Se-MOP was −21.17 ± 0.47 mV ($$n = 3$$). The zeta potential result showed that selenium nanoparticles with MOP had good stability. The detailed size distribution report by intensity is shown in Figure S1. ## 2.1.2. UV Spectrometry Analysis The result of UV spectrometry analysis is shown in Figure 2. MOP did not have absorption peaks in the 200–800 nm wavelength range. However, sodium selenite had a maximum absorption peak of 212 nm, while Se-MOP had a maximum absorption peak of 266 nm. The different absorption of UV spectrometry analysis results demonstrated that Se-MOP varied from MOP and sodium selenite. ## 2.1.3. ATR-FTIR Spectrometry Analysis The typical characteristic peaks of Se-MOP and MOP are shown in Figure 3. Hydroxyl stretching vibration peaks were at 3238 cm−1 and 3257 cm−1. Characteristic peaks at 1591 cm−1 and 1594 cm−1 were related to binding water. CH2 shear vibration peaks were at 1405 cm−1 and 1404 cm−1. The pyran ring’s C-H variable angle vibration peaks were at 1400 cm−1~1200 cm−1. C-O-C stretching vibration peaks of the pyran ring were at 1026 cm−1 and 1022 cm−1. Asymmetric ring stretching vibration peaks of D-glucopyranose were at 929 cm−1 and 934 cm−1. Transverse vibration peaks of the methine groups were at 871 cm−1 and 876 cm−1. The furan ring’s C-H variable angle vibration peaks were at 829 cm−1 and 818 cm−1. Moreover, when MOP was combined with selenium, hydroxyl vibration peaks shifted from 3257 cm−1 to 3238 cm−1, and a new peak appeared at 668 cm−1. ## 2.1.4. Transmission Electron Microscopy (TEM) Analysis Different views of Se-MOP were observed by TEM (Figure 4). The particle size of Se-MOP was 40–80 nm. Furthermore, these particles were spherical, even-sized, and well-dispersed. TEM analysis attested that MOP was a good dispersant for nano-se. ## 2.2. Selenium Content Determination The plot was drawn with selenium content (μg) as abscissa and absorbance value as ordinate. The standard equation was $y = 0.251$x + 0.0089, $r = 0.9999.$ The selenium content of Se-MOP was (0.99 ± 0.01)% ($$n = 3$$). ## 2.3.1. Anti-Tumor Activity of Se-MOP and MOP The in vitro anti-tumor activity of Se-MOP and MOP on HepG2, MCF-7, AGS, PC9, and HCT8 cells was evaluated using CCK8 assay. As shown in Figure 5, after treated with different concentrations of Se-MOP and MOP (0, 3.125, 6.25, 12.5, 25, 50, 100, 200, and 400 μg/mL) for 48 h and 72 h, Se-MOP showed significant inhibition effects on HepG2, MCF-7, AGS, PC9, and HCT8 cells ($p \leq 0.01$) and PC9, MCF-7,and AGS cells were inhibited in a dose-dependent manner as well. At the same time, MOP only had weak anti-tumor activity. Among these cancer cells, Se-MOP must have shown the most significant inhibition effect by HepG2, with the lowest IC50 value of 2 μg/mL at 48 h and 1 μg/mL at 72 h. ## 2.3.2. Cell Cycle Arrest Induced by Se-MOP A PI staining assay was performed and analyzed using flow cytometry. After being treated with different concentrations of Se-MOP (0, 5, 25, 50, 100, 200, and 400 μg/mL) for 24 h, the cell percentage of G1 phases was decreased, while the percentage of G2 phases was increased in a dose-dependent manner (Figure 6A). These cancer cells phases were further quantified by Modfit software. The percentage of cancer cells in the G1 region was decreased from $53.43\%$ to $4.328\%$ after treatment with Se-MOP (0, 5, 25, 50, 100, 200, and 400 μg/mL) for 24 h ($p \leq 0.05$, $p \leq 0.01$, $p \leq 0.001$, and $p \leq 0.0001$) (Figure 6B). Meanwhile, the percentage of cancer cells in the G2 region was increased from $15.35\%$ to $64.87\%$ after being treated with Se-MOP (0, 5, 25, 50, 100, 200, and 400 μg/mL) for 24 h ($p \leq 0.05$, $p \leq 0.01$, $p \leq 0.001$, and $p \leq 0.0001$) (Figure 6B). ## 2.4.1. Effects of Se-MOP and MOP on Lymphocyte Proliferation and Maximum Proliferation Rate With single stimulation of Se-MOP, or in synergistic stimulation of Se-MOP (0.195–200 μg/mL) with PHA (10 μg/mL) and LPS (5 μg/mL) after 48 h, lymphocyte cells were detected for the viability using CCK8 assay. As shown in Figure 7A, after being treated with Se-MOP at 0.195–200 μg/mL, compared to the control group, the number of lymphocytes increased at 3.125–25 μg/mL, in which the maximum proliferation rate was at 12.5 μg/mL. At the same time, inhibition was also shown at other concentrations. Similar results were displayed in synergistic stimulation of Se-MOP (0.195–200 μg/mL) with PHA (10 μg/mL) and LPS (5 μg/mL) after 48 h. The concentration of Se-MOP from 0.195 μg/mL to 12.5 μg/mL revealed that lymphocyte proliferation was in dose dependence except for 12.5 μg/mL. For the LPS treatment with Se-MOP, there were an increased number of lymphocytes at 1.56–25 μg/mL, and the concentration of maximum proliferation rate was also 12.5 μg/mL. These results led to a similar conclusion: Se-MOP promoted lymphocyte proliferation and increased immunity. ## 2.4.2. Effects of Se-MOP on Gene Expression of IL-2, IL-4, and IFN-γ in Mouse Spleen Lymphocytes To avoid the cytotoxicity of lymphocytes, Se-MOP at the indicated concentrations (0.195, 0.39, 0.78, 1.56, 3.125, 6.25, 12.5, 25 μg/mL) was verified for safety and at proliferation concentration for the following assays. The different concentrations of Se-MOP (0.195, 0.39, 0.78, 1.56, 3.125, 6.25, 12.5, 25 μg/mL) were added after being treated with PHA (10 μg/mL), respectively, for 48 h and then the mRNA expressions of cytokines were detected. The relative expression of IFN-γ, IL-2, and IL-4 mRNA in each group is shown in Figure 7B and Table 2. Compared to the PHA control group, the Se-MOP concentration at 0.78–6.25 μg/mL showed significantly increased relative expression of IFN-γ, at 3.924, 5.313, 3.872 and 2.676 times higher, respectively. Additionally, at the Se-MOP concentration of 0.195–25 μg/mL, relative expressions of IL-2 were 1.492, 1.677, 2.538, 3.754, 2.21, 1.849, 1.625, and 1.496 times higher than that of the PHA group, among which at the concentration of 1.56 μg/mL, the content of IL-2 was the highest. Moreover, it was a similar increased content at the concentration of 0.39–6.25 μg/mL, with 1.721, 7.418, 2.09, 1.948, and 1.764 times higher than that of control group. Se-MOP could improve immunity by increasing cytokine expression, such as that of IFN-γ, IL-2, and IL-4. ## 3. Discussion Zeta potential is a significant indicator in evaluating the stability of nanoparticles. Zeta potential, which refers to the potential of the shear plane, is an important index to characterize the stability of a colloidal dispersion system and an index to measure the intensity of mutual repulsion or attraction between particles. The positive or negative of the zeta potential represents which charge the particle carries. The absolute value of the zeta potential is positively correlated with the repulsion between particles. The higher the absolute value, the more stable the dispersion system. When there is no noticeable difference in the zeta potential, the smaller the particle size, the higher the solution’s stability. In Section 2.1.1, MOP mean size was trending by $12.5\%$. Moreover, the count rate and size increased, suggesting the sample may have been aggregating. After the modification of MOP, the two influence each other, the particle size of Se-MOP decreased, the zeta potential exceeded the spatial stability value −20 mV, and to the sample did not aggregate easily. It was reported that the zeta potential should be close to 20 mV to maintain sterically stable [28]. Gao et al. determined that the zeta potential of Polyporus umbellatus polysaccharide nano-selenium was −22.6 mV, and it could be stored for 84 days at 4 °C in the dark [29]. The color of nano-selenium changes obviously in the process of formation. During the formation, the color of the nano-selenium solution changes from colorless to red, leading to surface plasmon resonance [30]. The surface plasmon resonance of metal is essential in determining metal nanoparticles’ optical properties. Macroscopically, this resonance is shown as the light absorption of metal nanoparticles, which have absorption bands in the UV-Vis region [31]. It was reported that the position of the maximum absorption peak is related to the particle size of nano-selenium in UV detection. When the particle size was about 200 nm, the maximum absorption peak was near 600 nm; when the particle size was lower than 100 nm, the maximum absorption peak was 200–300 nm [32]. Therefore, these results confirmed that new, stable particles were formed, and the particle size was below 100 nm. ATR-FTIR was used to investigate the binding type preliminarily between selenium nanoparticles and MOP. Apparently, Se-MOP had the skeleton of MOP. Moreover, the shift of the hydroxyl vibration peaks to a lower wavenumber and increased intensity indicated that hydrogen bonds were formed. More intriguingly, there was a weak peak of Se-MOP at 668 cm−1, which could be considered an Se-H bond absorption peak. Zhu et al. reported the same peak at 669 cm−1 characterized by FT-IR, and further proved there was Se-H in C-6 connections using NMR spectra [33]. Results from ATR-FTIR proved that Se-MOP had the skeleton of MOP, and selenium may combine with MOP through Se-H bonds. The latter result requires further evidence to be obtained using NMR spectra in follow-up studies. TEM can directly observe the size and morphology of nano-particles, which is the first choice of many researchers [34]. The results discussed in Section 2.1.4 showed that the Se-MOP particles were spherical, even-sized, and well-dispersed. The TEM, size, and zeta potential, and UV-Vis results confirmed each other. Moreover, it was found in Section 2.2 that the selenium content of Se-MOP was high. The World Health Organization (WHO) ‘s maximum allowable daily selenium intake is 400 μg [35]. If Se-MOP were used to supplement selenium, no more than 0.04 g per day would be required, which would significantly improve the efficiency of the selenium supplement. The anti-tumor activity result provided evidence that the new formation of Se-MOP could significantly improve the anti-tumor activity of native MOP in several tumor cells, which has also been verified by previous studies. Zhang et al. confirmed that selenium nanoparticles from dandelion polysaccharide exerted anti-tumor activity on A549 cells, HepG2 cells, and Hela cells through inducing cell apoptosis [36]. Similarly to this conclusion, rabinogalactans/selenium nanoparticles composites (LAG-SeNPs) constructed by Tang et al. exerted a better inhibition of A549 cell, HepG2 cell, and MCF-7 cell proliferation [37]. A cell cycle assay was performed and analyzed using flow cytometry to investigate further the possible anti-tumor mechanism of Se-MOP on HepG2 cells. As a process of cell proliferation, the cell cycle is an orderly occurrence of the replication of genomic DNA, followed by an equal division of the genome into two similar cells, initially divided into two phases: mitosis and interphase. Whether cells complete the proliferation process is closely related to whether cells experience the whole phase of the cell cycle smoothly, which is regulated with extreme precision. The different stage of the cell cycle has different characteristics and functions of regulation. For interphase, it was further divided into three phases: G1 phase, S phase, and G2 phase. The G1 phase is characterized by the synthesis of mRNAs and proteins required for DNA replication. At the same time, the S phase is the phase of DNA replication. The G2 phase is the late stage of DNA synthesis and the preparation period for mitosis. With fewer and fewer mRNAs and proteins synthesized, it was apparent that there was not sufficient material to support DNA replication, which also caused cell cycle arrest. Together, the cell cycle assay results demonstrated that Se-MOP could inhibit the proliferation of cancer cells by cell cycle G0/G1 phase arrest. Coincidentally, Venkateswaran [38] also reported similar results for human PCA cells (LNCaP, PC3, PC3-AR2, and PC3-M) incubated with and without Seleno-DL-methionine, in which treatment with selenium caused G1 arrest and an $80\%$ reduction in the S phase of LNCaP [37]. In this study, we investigated the preliminary mechanisms underlying the short-term (24 h) effects of Se-MOP on the cell cycle of liver cancer cells. The results of cell cycle arrest may lead to apoptosis [39]. Previous studies have shown that different methods can induce apoptosis in HepG2 cells. It has been reported that selenium–sorafenib complexes can effectively activate the Ca2+ signaling system and cause endoplasmic reticulum stress [40], while glucan-selenium nanoparticles (Glucan-SeNPs) can activate Caspase-3 and Caspase-9 [41]. This experiment provides a basis for exploring the specific mechanism of apoptosis in the future. The previous results in Section 2.4.1 showed that Se-MOP stimulated lymphocyte proliferation in vitro and enhanced cellular immune function. The mouse spleen lymphocytes were conducted as the experimental model to explore the mechanism of enhancing the immunity of selenium. After being stimulated by PHA, the lymphocytes were transformed into lymphoblasts, further proliferated, and released lymphokines, increasing the phagocytosis of macrophages. Lipopolysaccharide (LPS) is a potent activator of immune cells, including B cells, monocytes, and macrophages, which is required for stimulation to produce cytokines. Cytokine is a small, non-specific immune molecule other than immunoglobulin and complement, which can mediate and regulate the immune and inflammatory responses of the body. They have a variety of biological activities, such as regulating immunity, inhibiting tumor proliferation, and so on. IFN-γ and IL-2 play essential roles in the body’s immune response and are natural immune enhancers, while IL-4 mainly is involved in maintaining the normal immune function of the organism. In general, the immune ability was enhanced by single stimulation of Se-MOP and synergistic stimulation with PHA or LPS, increasing the expression of cytokines, such as IFN-γ, IL-2, and IL-4. From the results of the cytokine expression, when the concentration of Se-MOP was moderate, the relative expression of cytokines was the highest. When the concentrations of Se-MOP were 1.56 μg/mL, 1.56 μg/mL, and 0.78 μg/mL, the relative expression levels of IFN-γ, IL-2, and IL-4 cytokines were the highest. This is consistent with the trend of PHA synergistically stimulating mouse spleen lymphocytes. Mao et al. [ 42] found that the combination of Astragalus polysaccharide and selenium nanoparticles (Se-GP11) had no toxic effect on HepG-2 cells in vitro, but could significantly inhibit the growth of HepG2 tumors in vivo. It increased the level of interleukin 2. This is similar to the results of our in vitro experiment, providing a research direction for subsequent in vivo experiments. In previous studies, selenium can synergize with sufficient IL-4 to activate the receptor γ (PPAR-γ)-reliant pathway, promoting macrophages from M1 to M2 [43]. In this experiment, Se-MOP can increase the relative expression of IL-4. Combined with the previous studies, the effect of Se-MOP may also be related to the inhibition of inflammation in M2 macrophages, which provides a research direction for later studies. IFN-γ is associated with CD8+ T cell function [44]. In future studies, the cytotoxic activity of selenium on tumors and its effects on the immune microenvironment of tumors can be studied. This article aims to investigate the mutual influence between nano-selenium and MOP, as well as the improvement of MOP activity by selenium. The possible binding modes between nano-selenium particles and MOP are speculated in this article and require further verification using one-dimensional or two-dimensional NMR methods. Furthermore, the activity of bare nano-selenium particles will be compared with Se-MOPs in subsequent experiments. Moreover, in vivo experiments are required to verify the in vitro activity in this article. Finally, further research on the mechanism of anti-cancer and immune enhancement is needed. ## 4.1. Materials and Reagents The MOP was prepared as reported previously [45]. Sodium selenite was purchased from Sigma-Aldrich (St. Louis, MI, USA). Ascorbic acid was purchased from Zhiyuan Co. (Tianjin, China). Carbon support films were purchased from Zhongjingkeyi (Beijing, China) Films Technology Co., Ltd. (Beijing, China). Phytohemagglutinin (PHA) was purchased from Selleck Co., Ltd. (Huston, TX, USA). Lipopolysaccharide (LPS) was purchased from Sigma-Aldrich (St. Louis, MI, USA). Trizol reagent was purchased from ThermoFisher (Waltham, MA, USA). Cell Counting Kit-8 was purchased from GlpBio (Montclair, NJ, USA). Evo M-MLV RT Premix for qPCR was purchased from Accurate Biology (Changsha, China). SYBR Green-Premix Pro Taq HS Qpcr Kit II was purchased from Accurate Biology (Changsha, China). Mycoplasma Stain Assay Kit was purchased from Beyotime (Shanghai, China). All other reagents were analytically pure. ## 4.2. Apparatus The Supo HHS-6 electro-thermostatic water bath and the Evela N-1200A rotary evaporator were used. The freeze-drying method was operated by Biosafer Biosafer-10A and Christ Alpha 1–2 LD plus vacuum freeze-dryers. The size distribution and zeta potential were determined using a Malvern Zetasizer nano ZS analyzer. The UV used a Shimadzu UV-2600 UV-vis spectrophotometer, and the ATR-FTIR used a Perkin Elmer Spectrum two infrared analyzer. The JEOL JEM-2010HR was operated for TEM observation. The cell cycles were performed by a Beckman CytoFLEX S flow cytometry analyzer. Cell proliferation was determined with a Multiskan FC ThermoFisher microplate reader. The quantitative RT-PCR was conducted with 7500 apparatus, Applied Biosystems (Waltham, MA, USA). ## 4.3. Preparation of Se-MOP MOP was dissolved in water to prepare a 5 mg/mL solution. Sodium selenite was dissolved in water to prepare a 10 mmol/L solution. Ascorbic acid was dissolved in water to prepare a 50 mmol/L solution and kept in the dark. MOP solution of 2 mL and sodium selenite solution of 5 mL was put in a 50 mL colorimetric tube. Water was added to the 25 mL scale line and mixed well. The mixture was pre-heated in the water bath 50 °C for 20 min, and an ascorbic acid solution of 3 mL was added to the mixture (molar ratio of sodium selenite to ascorbic acid = 1:3). Water was added to the 50 mL scale line and mixed well. The mixture was heated in the water bath at 50 °C for 4 h. The reaction was terminated by stopping heating. The reaction mixture was transferred into a round-bottom flask and concentrated by rotary evaporation. The concentration was vacuum freeze-dried for 24 h. Eventually, the Se-MOP dry powder was collected. ## 4.4.1. Measurement of Particle Size and Zeta Potential Se-MOP solution in a quantity of 10 mL before freeze-drying and diluted MOP solution from Section 4.3 were measured for particle size, PDI, and zeta potential using a laser particle size analyzer. ## 4.4.2. UV Spectrometry Analysis Se-MOP dry powder was dissolved in water to prepare a 0.3 mg/mL solution. Sodium selenite and MOP were prepared in the same concentrations in separate solutions by the same method. Each solution was scanned by an Ultraviolet spectrophotometer with a quartz cuvette in the 200–800 nm wavelength range, using water as reference. ## 4.4.3. ATR-FTIR Spectrometry Analysis Se-MOP dry powder 10 mg was placed on the prism and pressed into a thin tablet. The tablet was measured on an ATR-FTIR spectrometer in the range of 4000–400 cm−1. ## 4.4.4. TEM Analysis Before freeze-drying, Se-MOP solution 5 mL was processed by ultrasonic machine for 20 min. Afterward, the solution was filtrated into a syringe through the 220 μm millipore filter. The filtrate was dropped into a carbon support film (mesh number: 300). The carbon support film was placed in a dryer for 72 h, and then the morphology of the Se-MOP was observed by TEM. ## 4.5. Selenium Content Determination The method was derived from [46,47] and was modified. Organic matter was removed from the sample after digestion. The zero-valent nano-selenium was oxidized to Se (IV) by the oxidant. O-phenylenediamine reacted with Se (IV) to form a complex (Figure 8). The complex was extracted by toluene. A UV-vis spectrophotometer detected the content of the complex. Sodium selenite was used as the reference material to draw the standard curve. The detailed procedures are demonstrated as follows. ## 4.5.1. Standard Curve Plotting All procedures were operated in the dark. Sodium selenite 10.27 mg was dissolved in water in a 25 mL volumetric flask. Water was precisely added to the scale line to get the standard selenium solution (selenium content: 187.56 μg/mL). Standard selenium solution (0.1 mL, 0.2 mL, 0.4 mL, 0.8 mL, and 1.6 mL) was separately transferred into a 20 mL volumetric flask. Each volumetric flask was added to 2 mL $2\%$ o-phenylenediamine solution and 2 mL of water. Later, the pH value of the reaction mixture was adjusted to two. Water was added to the scale line, and the system reacted for 1 h. After the reaction, the mixture was extracted with 20 mL toluene, and the organic layer was retained. The absorbance of the organic layer was measured at a wavelength of 334 nm by an ultraviolet spectrophotometer with a quartz cuvette, using toluene as a reference. A standard curve was plotted based on the former results. ## 4.5.2. Se-MOP Digestion and Determination Se-MOP dry powder in a quantity of 50 mg was placed in a ceramic crucible with a lid. Concentrated nitric acid in a quantity of 1 mL was added to the Se-MOP solution, which was then digested for 8 h. Afterwards, the crucible was heated with an electric hot plate until the liquid within was nearly dried. H2O2 solution ($30\%$) of 0.3 mL was added dropwise. The crucible was heated again until the liquid within was colorless. The inner side of the crucible was washed with 0.1 mL water, and the crucible was heated until no smoke was produced. The digested liquid was transferred into a 10 mL volumetric flask, and water was precisely added to the scale line. The sample was made for later selenium determination and a 2 mL sample was transferred into a 20 mL volumetric flask. Other procedures were the same as described in Section 4.5.1. The absorbance was used to calculate the selenium content. ## 4.6.1. Cancer Cell Culture HCT8, AGS, HePG2, MCF-7, and PC9 cell lines were obtained from the American Type Culture Collection (ATCC). HCT8 and PC9 cells were cultured in Roswell Park Memorial Institute-1640 (RPMI1640, Corning, USA) with $10\%$ FBS and $1\%$ Penicillin and Streptomycin at 37 °C in $5\%$ CO2. AGS, HePG2, and MCF-7 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM, Corning, USA), with $10\%$ FBS and $1\%$ Penicillin and Streptomycin at 37 °C in $5\%$ CO2. All cell lines were stored in multiple backups upon receipt to reduce risk of phenotypic drift, and tested to determine whether they were mycoplasma-free by Mycoplasma Stain Assay Kit. ## 4.6.2. Cell Proliferation For the CCK8 assay, HCT8, AGS, HePG2, MCF-7, and PC9 cells were seeded at 5000 cells per well in 96-well plates with fresh medium overnight. Se-MOP and MOP were diluted with serum-free medium to a final concentration of 0 μg/mL, 3.125 μg/mL, 6.25 μg/mL, 12.5 μg/mL, 25 μg/mL, 50 μg/mL, 100 μg/mL, 200 μg/mL, and 400 μg/mL, respectively, and added into 96-well plates in the next day. Cell viability was assayed by using the Cell Counting Kit-8 at 48, 72 h. The microplates were incubated at 37 °C for an additional 2 h. Absorbance was read at 450 nm using a microplate reader (Multiskan FC, ThermoFisher, USA). ## 4.6.3. Cell Cycle Assays Propidium iodide staining and flow cytometry were adapted from Cell Cycle Staining Kit. HePG2 cells were plated in 60 mm cell culture dishes overnight for cell cycle detection. Se-MOP was diluted with serum-free medium to final concentrations of 5 μg/mL, 25 μg/mL, 50 μg/mL, 100 μg/mL, 200 μg/mL, and 400 μg/mL, and added into cell culture dishes for another 24 h. These cells were trypsinized, collected, and washed twice with PBS. They were then resuspended in 1 mL DNA staining solution and 10 μL permeabilization solution, oscillated for 5–10 s, and incubated at 37 °C for 30 min in the dark. Then, cells were stained, followed by flow cytometry analysis. ## 4.7.1. Determination of Proliferation of Mouse Spleen Lymphocytes In Vitro All mouse procedures were approved and carried out in accordance with the Institutional Animal Care and Use Committee of Sun Yat-Sen University (No. 44008500029369). We used 5-week-old ICR male mice for all our mouse experiments. The method of preparing mouse spleen lymphocytes followed that of Luo [48] and they were counted by trypan blue staining. Se-MOP and MOP were diluted with RPMI1640 medium from 200 μg/mL to 0.195 μg/mL in 11 concentration gradients (200, 100, 50, 25, 12.5, 6.25, 3.125, 1.56, 0.78, 0.39, and 0.195 μg/mL). Mouse spleen lymphocytes were seeded at 150,000 cells/mL at 100 μL per well in 96-well plates with fresh RPMI1640 medium containing $10\%$ FBS, $1\%$ penicillin and streptomycin. PHA solution (to a final concentration of 10 μg/mL), LPS solution (to a final concentration of 5 μg/mL), and the blank medium were added and incubated at 37 °C, respectively. Then, Se-MOP and MOP dilution for each concentration were added into 96-well plates, respectively, and left overnight. Cell viability was assayed using Cell Counting Kit-8 over 48 h. The microplates were incubated at 37 °C for an additional 2 h. Absorbance was read at 450 nm using a microplate reader. ## 4.7.2. Determination of Cytokines of Mouse Spleen lymphocytes In Vitro and Quantitative RT-PCR The spleen lymphocytes of 5-week-old ICR male mice was prepared as above. Mouse spleen lymphocytes were seeded at 1 × 107 cells/mL at 1 mL per well in 6-well plates with fresh RPMI1640 medium containing $10\%$ FBS, $1\%$ penicillin and streptomycin and PHA solution (to a final concentration of 10 μg/mL) was added and incubated at 37 °C. Se-MOP was diluted with RPMI1640 medium from 200 μg/mL to 0.195 μg/mL in eleven concentration gradients (25, 12.5, 6.25, 3.125, 1.56, 0.78, 0.39, and 0.195 μg/mL) and added to 6-well plates, respectively. The spleen lymphocytes were collected for 48 h incubation. Total RNA was isolated using Trizol reagent according to the manufacturer’s instruction, and cDNA was synthesized using the Evo M-MLV RT Premix for qPCR. The resulting cDNA was used for quantitative RT-PCR using SYBR Green-Premix Pro Taq HS Qpcr Kit II in 7500 apparatus (Applied Biosystems). β-actin mRNA was the housekeeping gene used to normalize the expression of mRNAs. RT-PCR primer sequences are listed in Supplementary Materials (Table S1). ## 5. Conclusions A new kind of selenium nanoparticle, Se-MOP, was prepared successfully. The UV spectra demonstrated that new nanoparticles existed. The TEM results showed that the Se-MOP particles were spherical, even-sized, and well-dispersed, and the zeta potential proved its good stability. Additionally, the binding type between selenium particles and MOP was tentatively investigated by ATR-FTIR spectra. Se-MOP showed significant inhibition effects on all selected five cancer cells. The mechanism may be that Se-MOP could inhibit the proliferation of cancer cells by cell cycle G0/G1 phase arrest. Single Se-MOP stimulation and synergistic stimulation with PHA or LPS increased immune capacity. When the concentration of Se-MOP was in the middle (1.56, 3.125, 6.25, 12.5, 25 μg/mL), the cytokines’ relative expression was generally significant. This was consistent with the trend of the Se-MOP and PHA synergistic stimulation results. These results indicate that Se-MOP could improve immunity by increasing cytokine expression. However, the possible binding modes between nano-selenium particles and MOP are only speculated in this article and require further verification. The activity of bare nano-selenium particles should be compared with that of Se-MOP. Moreover, further research on anti-cancer and immune enhancement mechanisms and in vivo experiments are needed. Despite the limitations, we discovered that nano-selenium was successfully dispersed with the help of Morinda officinalis polysaccharide in this study. After combining with nano-selenium, the activity of Morinda officinalis polysaccharide was significantly enhanced. 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--- title: 'Building a Low-Cost Wireless Biofeedback Solution: Applying Design Science Research Methodology' authors: - Chih-Feng Cheng - Chiuhsiang Joe Lin journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10052076 doi: 10.3390/s23062920 license: CC BY 4.0 --- # Building a Low-Cost Wireless Biofeedback Solution: Applying Design Science Research Methodology ## Abstract In recent years, affective computing has emerged as a promising approach to studying user experience, replacing subjective methods that rely on participants’ self-evaluation. Affective computing uses biometrics to recognize people’s emotional states as they interact with a product. However, the cost of medical-grade biofeedback systems is prohibitive for researchers with limited budgets. An alternative solution is to use consumer-grade devices, which are more affordable. However, these devices require proprietary software to collect data, complicating data processing, synchronization, and integration. Additionally, researchers need multiple computers to control the biofeedback system, increasing equipment costs and complexity. To address these challenges, we developed a low-cost biofeedback platform using inexpensive hardware and open-source libraries. Our software can serve as a system development kit for future studies. We conducted a simple experiment with one participant to validate the platform’s effectiveness, using one baseline and two tasks that elicited distinct responses. Our low-cost biofeedback platform provides a reference architecture for researchers with limited budgets who wish to incorporate biometrics into their studies. This platform can be used to develop affective computing models in various domains, including ergonomics, human factors engineering, user experience, human behavioral studies, and human–robot interaction. ## 1. Introduction Biofeedback involves using electrical instruments to measure a person’s biometric responses, including brainwaves, heart rate, skin conductance, facial expressions, respiration, peripheral skin temperature, and muscle tone [1,2]. These biometric signals are often referred to as physiological [3,4,5] and psychophysiological signals [6]. The applications of biofeedback are broad and include medical purposes, such as physical and occupational therapy [7,8,9,10], psychological clinics [11,12,13,14], and cognitive research [15,16,17,18]. To ensure the accuracy and quality of their work, researchers often use medical-grade devices in biofeedback studies. The results obtained from medical-grade equipment provide a comparable standard for other research, which is particularly important for medical applications. Therefore, the use of medically certified instruments in therapeutic studies is mandatory. However, the high price of such equipment can be a significant barrier to its widespread adoption. Manufacturers must acquire an FDA class II or CE IIa certification for their products to meet medical certification requirements, making them excellent and reliable, but costly. ## 1.1. Consumer-Grade Physiological Sensors Applied in Research Cost can be a concern when using medically certified devices for non-medical purposes [19]. In recent years, consumer-grade biometric devices have been extended to non-medical fields, such as measuring pupils’ attention in education [20], brain–computer interfaces in human–computer interaction [21], workers’ mental load in human–robot collaboration [22], and affective computing [23,24]. Some consumer-grade biometric devices have been reported to be as accurate as medical-grade products [25,26] or can be used for health care purposes [27]. When selecting wearable sensors for Industry 5.0 applications, the two top features to consider are system development kit (SDK) support for real-time data streaming and wireless communication protocols. Three communication protocols are widely used in the industry sector. Experts recognize that the Bluetooth Low Energy (BLE) protocol is much more important than ANT+ and Wi-Fi. Every wearable device on the market supports BLE, the mainstream communication protocol. Other features, such as weight and comfort for workers without obstructions, are also important considerations [28]. Photoplethysmography (PPG) is prevalent in the application of individual health care [27]. Bolanos et al. [ 29] indicated that heart rate variability (HRV) derived from PPG has excellent potential to replace the one from ECG. Recently, no significant differences have been reported in the HRV features derived from PPG and ECG signals in time, frequency, and non-linear domains [30]. However, PPG should be used only when the user is resting [31,32] due to motion artifacts caused by the movement of the PPG sensor over the tissue, skin deformation due to muscle contraction, and blood flow dynamics [33,34]. Nevertheless, an algorithm can reduce movement artifacts using user kinematics data from embedded accelerometers [35]. PPG is a non-invasive, low-cost, and wearable wireless device that can be an alternative to electrocardiogram (ECG) technology for heart rate (HR) monitoring. Although ECG has been continuously improved in terms of measurement accuracy and wearing comfort, the flexibility, portability, and convenience for users have not been enhanced [27]. In contrast, PPG does not require several electrodes to be placed on specific body locations. Users can wear a PPG device like a watch, with flexibility of movement, portability to any location, and convenience to monitor HR all day. These features make PPG suitable for non-medical activities [27], such as user experience studies [36]. In recent years, there has been an extension of the use of PPG to non-medical fields, such as measuring pupils’ attention in education [20], brain–computer interfaces in human–computer interaction [21,22], and affective computing [23,24]. Some consumer-grade biometric devices have been reported to be as accurate as medical-grade products [25,26] and can be used for health care purposes [27]. Two review papers [19,36] provide a list of consumer-grade EEG devices and a comprehensive literature survey for researchers’ reference. The key results are summarized below: four brands, namely, NeuroSky, Emotive, Interaxon, and OpenBCI, provide consumer-grade EEG products with high potential. Most EEG products are equipped with dry sensors, single channels, and BLE or classical Bluetooth communication protocols to stream data. The sampling frequency ranges from 128 to 512 Hz. The classification accuracy of the machine learning algorithm for the responded study ranges between $60\%$ to $90\%$, as cited in the literature in the categories of cognition, education, entertainment, and brain–computer interaction. When comparing the performance of the power spectra, NeuroSky MindWave is similar to two medical-level EEG devices. Emotive EPOC is worse than the benchmark medical-level rival, Interaxon Muse, which demonstrates lower reliability than medical-level products. The results for OpenBCI resemble those of medical-grade devices. Moreover, a random time lag is a common phenomenon in wireless EEG devices. Consumer-grade electroencephalography (EEG) products have been widely accepted for non-medical applications [19,36]. Similarly, PPG devices are popular for non-medical health care [37,38]. Innovations in technology over the last decade have advanced consumer-grade wearable sensors, enabling them to prosper in the market. The wireless, wearable, and lightweight features make consumer-grade products capable of collecting data continuously with no time or location limits. As a result, users do not feel discomfort after wearing such devices for a long period. In addition, they are easy to use and even novices can handle them easily. In contrast, a medical-grade EEG system is accurate, but it comes at the price of a complex structure and long setup time [36]. ECG does not offer users the flexibility, portability, or convenience offered by medical-grade EEG [27]. Consequently, medical-grade device applications are usually limited to the laboratory [19,36]. Another point to note is that for research requiring high data retention, reliable communication, no real-time data transmission, and involving field investigations, wearable devices with temporary memory storage should be considered, with data uploaded to cloud servers at regular intervals. Examples of such research include investigations of the relationship between human well-being and daily experiences [39] or the relationship between human emotions and daily life events [40]. Physiological signals are excellent objective metrics for such research, and when combined with subjective assessments from participants, they can provide valuable insights. However, such studies involve scenarios that are not pre-designed or controlled; therefore, experiments can only be conducted in real-life settings. Carrying around another real-time data collection system is not feasible. ## 1.2. Relationship between User Experience and Users’ Emotional State Norman coined and proposed the term “user experience” [41]; however, initially, this term lacked a clear definition. Years later, Norman and Nielsen defined UX as “meeting the exact needs of the customer” and “a joy to own, a joy to use” [42]. Some experts organized a special interest group (SIG) to comprehensively investigate UX. There are many definitions of UX in the survey results of the published literature or on the websites of UX organizations [43]. The conclusion of the SIG suggests that researchers may choose their preferred definition from the identified list, which includes Norman and Nielsen’s definition. The evaluation of UX traditionally uses participants’ self-evaluation through a questionnaire or personal interview after experiencing a product. This assessment method relies on the participants’ subjective perceptions, and is referred to as subjective evaluation. In contrast, UX evaluation based on biometrics is considered an objective method as it uses signals generated from the human autonomic nervous system. The SIG mentioned in the previous paragraph identified eighty-six UX evaluation tools [44], but only four of these use physiological signals or facial expressions to assess UX. Therefore, thirty-three subjective methods utilize emotion/affect/hedonic as the index for UX evaluation. This finding is consistent with Norman and Nielsen’s definition, and implies that UX is related to a user’s emotional state after experiencing a product. Moreover, the limited number of tools using objective methods suggests that researchers should investigate this topic in greater depth. ## 1.3. Affective Computing as a Tool for User Experience Evaluation Affective computing [45] is an algorithm that recognizes a human’s emotional state [46] through biometric signals [47]. Accordingly, a user’s perceived pleasure while experiencing a product estimated using biometrics might serve as a UX metric. When a user experiences pleasurable emotions such as joy or positive valence for a product, it is reasonable to believe that this product generates a good user experience. Conversely, a user responding with anger or negative valence signals a poor user experience if. Instead of relying on a user self-report assessment or verbal expressions––referred to as subjective evaluation, and used in traditional UX studies––the affective computing applied in UX research is considered an objective method [46]. Consequently, researchers interested in user experience (UX) use affective computing to recognize users’ emotional states when they experience a specific software or product [48,49,50,51,52]. Although subjective methods are related to the assessment target, the participants may have cognitive bias [53] and may not be sufficiently robust [54]. An objective assessment could compensate for this disadvantage [55]. Thus, subjective measures should not be the sole metrics used to evaluate UX [49]. Using a subjective assessment of human emotion may be unreliable since emotions are often swift, hard to perceive, and sometimes have multiple states [56]. Additionally, participants may be afraid to confess their emotions to the researcher. Worse, some participants may answer questions by imagining what the researcher expects them to say [56]. In contrast, an objective metric could assist researchers to fill the gap caused by using subjective methods to evaluate the UX of a specific product. For example, a case study evaluated participants’ user experience of three different virtual dressing websites using verbal expressions and biometrics [56]. There was no difference between the websites in terms of positive expressions resulting from verbal expressions. However, the percentage of engagement and attention, the positive/negative emotion, and the joy derived from biometrics showed that the three websites differed. This result illustrates the value of biometrics. Moreover, affective computing can be applied in robotics to increase people’s enjoyment while interacting with robots. Physiological signals were one of the elements acting as medical robots’ human–machine interface. Using flexible electronics and devices makes the interface biocompatible, functional, conformable, and low-cost, resulting in an excellent user experience [57]. Service robots in the health care sector can aid patients with cognitive obstruction via built-in affective computing algorithms [58]. In commerce, empowering service robots with emotion recognition is a highly popular topic in research [59,60,61,62,63,64]. Some emotion recognition databases are available for service robots [65,66]. Accordingly, users’ emotional state during the experience with robots is a critical metric of human–robot interaction [67,68,69]. Affective computing algorithms built into robots allow machines to recognize humans’ emotional states. The present study focused on single-electrode electroencephalography (EEG), photoplethysmography (PPG) technology in heart rate (HR), galvanic skin response (GSR), and facial expressions, which are the biometrics frequently applied in affective computing studies [4,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84]. Although subjective methods are commonly used for UX assessment, they have some limitations. For example, participants may have cognitive biases [53] or the methods may not be sufficiently robust [54]. To compensate for these limitations, objective assessments could be used [55]. Therefore, subjective measures should not be the only metric used for UX evaluation [49]. Assessing human emotions subjectively can also be unreliable since emotions can be swift, hard to perceive, and have multiple states [56]. Additionally, participants may be reluctant to reveal their emotions to the researcher, and some participants may answer questions based on what they think the researcher expects them to say [56]. ## 1.4. Motivations and Objectives This research aims to assist researchers who are interested in applying affective computing to investigate human behavior but are limited by a restricted budget for medical-grade instruments. While various consumer-grade alternatives are available, there are drawbacks to using these commercial products. Firstly, most consumer devices only provide a single biometric signal, which means that a study typically requires multiple physiological signals from different manufacturers. This means the software is not an integrated system, such as that used in medical-grade devices. Therefore, researchers must use multiple, specific software programs simultaneously to collect data. Consequently, each instrument may need an independent computer or mobile device, and software manipulation is more complex than with an integrated system. Moreover, it is impossible to synchronize data from different consumer alternatives in terms of timestamps, even with multiple experimenters collaborating to press the buttons simultaneously. This can lead to a minimal time gap of less than one second, which may be insufficient for some psychology studies. Finally, the data processing of different signals distributed in many files can also be troublesome. The objective of this research is to use affordable hardware and free software libraries to develop a low-cost biofeedback platform for biometrics-related studies, such as human factors engineering, user experience, human behavioral studies, and human–robot interaction. The specific aim of the hardware is achieved by using consumer products or electronic modules designed for Arduino makers rather than medical-grade instruments. Another objective of the software is achieved through the use of open-source libraries that can be used free of charge. The software is an object-oriented programming (OOP) class that serves as a software development kit (SDK), which can be reused for other research or as a standalone biometrics collecting system. An SDK design allows researchers to integrate data collection with their experimental stimulus into a single system through customized coding. Nonintegrated devices require at least one additional computer beside the one controlling the experiment stimulus [85]. Moreover, the integrated software simplifies researchers’ manipulation during experimentation. A single button click triggers the stimulus, and the data collection is synchronized. Therefore, the biofeedback platform developed in this study improves the ease of operation in experiments and reduces equipment costs. ## 2. Methods Design science research (DSR) is a problem-solving paradigm achieved through the invention of innovative artifacts [86]. DSR has been adopted as a legitimate research paradigm in the information system research community to develop innovative software [87]. The design science research methodology (DSRM) is the most commonly applied model in research communities [86]. One possible entry point in DSRM is problem-centered initiation, where the ultimate goal is to design and develop an artifact for the identified problem. This study aims to solve a problem that many junior researchers encounter by developing a reusable hardware/software architecture. Accordingly, the DSRM framework is a suitable paradigm for this study. Figure 1 shows the development procedure of the low-cost biofeedback system in this study. The DSRM paradigm involves six activities, with activity one being to identify the problem and motivate, as stated in Section 1.4. Similarly, the objectives of this paper, defined in activity two are also described in Section 1.4. The design and development, demonstration, and evaluation in activities three to five are presented in the results section below. The last activity, communication, is the purpose of this paper. ## 3.1.1. Activity 3: Design and Development During the first stage of hardware selection, biofeedback sensors for Arduino were identified as the preferred choice due to their cost-effectiveness. Table 1 presents the survey results of the available sensors in Taiwan’s makers market. These sensors can be purchased from local suppliers or manufacturers’ websites worldwide. Many third-party companies manufacture EEG solutions using only NeuroSky’s ThinkGear ASIC Module (TGAM). The TGAM module generates EEG signals automatically, while its EEG module board integrates a classical Bluetooth module, HC-06, which makes it easy to connect to a personal computer. This allows users to easily access the EEG signals via the PC’s COM port. The TGAM module provides eight spectrum signals and two eSense meters, which measure attention and meditation. Another feature, Poor Signal, provides signal quality information for users. Ideally, the value of Poor Signal should be zero. All the spectrum features are calculated from the raw EEG values by an algorithm inside the integrated circuit, updated with a frequency of one Hz. However, the sampling rate of the raw EEG values is 512 Hz. Three PPG-type sensors were selected for HR monitoring from six modules designed by three companies. All three products have one LED to emit green light and one phototransistor to receive the reflection from the veins. Since this low-cost system could be applied in field studies in the future, the ease of applying the sensor on the human body and its esthetic appearance were considered. Therefore, chest strap products were excluded. Ear clip sensors were also excluded because of their unattractive appearance, which could discourage people from participating in research. Consequently, the Heart Rate Monitor Sensor for Arduino, Pulse Sensor, and Grove-Finger-Clip Heart Rate Sensor with a shell were selected for the next activity. Moreover, only one GSR device designed by SEEED is available in the market. Grove-GSR Sensor measures the resistance of humans. However, the value measured by a sensor is noisy. Therefore, a high-pass filter should filter the data before being applied. This research used a simple moving-average method to reduce the effect of the white noise generated by the sensors (EEG and GSR). Although the unit of measured GSR value is intensity, the manufacturer offers a formula to convert an intensity value to Ohm. Thus, this study selected one EEG, one GSR, and three HR sensors from the discrete physiological sensor for Arduino makers in the design and development activity. ## 3.1.2. Activities 4 and 5: Demonstration and Evaluation We utilized the library provided by the HR and GSR sensor manufacturer to develop a simple program in Arduino Studio to test the functionality. The EEG test program was developed using Python. In addition to the desired function, the quality and stability of the biometric signal were evaluated. Furthermore, the generated signal had to be clear and without interruption for two hours. User feedback on the comfort of wearing the sensor was also considered. Only when all of these criteria were satisfied, a specific physiological sensor was adopted. The TGAM module was excluded from the current research because the value of Poor Signal was not zero most of the time during our trials. In addition, the values of the EEG signals oscillated significantly during connection. These signals were gathered by a program using NeuroSkyPy, a Python package for the NeuroSky TGAM module in the Python Package Index (PyPI), with Python 3.10, and executed in console mode. A similar issue with EEG occurred with the HR sensors. Although all three products successfully measured people’s heart rates, they did not work constantly. Sometimes, people’s heart rate was lower than 50 beats per minute. Consequently, the three devices were unable to sense people’s heart rates at times. Since all three candidates were too unstable to work properly, the signal quality was poor. Therefore, the heart rate monitor for Arduino was not applied to the low-cost biofeedback system in the current study. Fortunately, the GSR test result with members from our laboratory satisfied the desired criteria. Therefore, this GSR sensor for Arduino makers was chosen for the low-cost biofeedback system. To summarize, GSR is the only sensor for Arduino makers used in this study. The study also considered EEG and heart rate monitor sensors from consumer-grade devices on the market. The development process iterated back to activity three. ## 3.2.1. Activity 3: Design and Development There are numerous consumer-grade EEG devices available on the market, including products from NeuroSky, Emotiv, Interaxon, and OpenBCI, as suggested by Sawangjai and colleagues [19]. The most critical condition for the current project was PyPI open-source library support. Table 2 summarizes the characteristics of the libraries for the target EEG in this study. For an open-source package, the essential consideration is whether a specific team maintains and documents the usage of the library. The version, release date, and documentation of the library on the website are crucial features to consider. The second condition was that the implemented library operation system had to be compatible with the platform used in this study, namely, Windows. All four products satisfied the requirements of the current study. The next step was to physically evaluate the hardware. All the target products are available on the local market. However, only NeuroSky has agents in Taiwan, making it the only product we could physically evaluate before purchase. BrainLink Lite is a headband-type EEG that uses NeuroSky’s TGAM, designed by Macrotellect. The electrodes in the headband make firm contact with the forehead, so the user does not feel pain like with other products that use ear clip electrodes for the ground or referred potential. The TGAM module integrates Bluetooth and chargeable lithium cells, and packages these in a tiny plastic shell, making the product light for users to wear. Consequently, users feel more comfortable than with other EEG products. BrainLink’s light, thin, and tiny features make it compatible with head-mounted MR headsets, such as HoloLens 2 (Figure 2). Thus, it is hoped that BrainLink Lite can be used to collect EEG data on the user experience evaluation of XR. Heart rate monitors have become popular in recent years. Not every device displays heart rate information on the hardware display, but all the products share information through Bluetooth Low Energy (BLE) with the specific GATT specification. Developing a low-cost and open-source biometrics system could take advantage of BLE’s standard heart rate specification to simplify integration. Although wristband-type products with heart rate monitor functions are prevalent in the market, most of them can access the information only from the software or mobile application provided by the manufacturers. Commerce competition limits the alternatives of heart rate application in low-cost and open-source biometrics systems. Nevertheless, the patented optical sensor technology in the Rhythm+2.0 heart rate monitor utilizes green and yellow LEDs to measure blood flow for a highly accurate reading with all skin tones [35]. A built-in accelerometer, which is applied to solve the motion artifacts issue caused by human movement [27], assists in providing hyper-accurate measurement. Since the yellow LED improves measurement accuracy for Asian people, the current study considered Rhythm+2.0 as the heart rate monitor for the low-cost, open-source biometrics system. ## 3.2.2. Activity 4 and 5: Demonstration and Evaluation A demonstration involved using the Python code developed earlier for the NeuroSky TGAM device to ensure stable signal quality index (i.e., Poor Signal = 0). This confirmed the suitability of BrainLink Lite for this study. Additionally, a BLE communication program was developed in Python using the bleak library to validate the readings of the Rhythm+2.0 device, which showed heart rate values between 60–90 beats per minute for various members in our laboratory during the validation stage. As the readings were reasonable for individuals in a benign condition, the Rhythm+2.0 device was utilized in the current study. All the required biofeedback devices were selected based on the nominal procedure of the DSRM paradigm, and the project iterated back to the final stage of the design and development activity. ## 3.3.1. Activity 3: Design and Development Another biometric feature, emotion reflected on a person’s face, can be quickly captured using a webcam. Any webcam connected to a computer is generally capable of this function. However, this study employed a mainstream commercial product, Logitech StreamCam, to access users’ faces. Once all the psychophysiological devices were determined, an integrated biofeedback system was developed using Python 3.10. The system featured a graphic user interface (GUI) for excellent usability. The GUI allows the user to input the required information, such as experiment name, treatment of experiment, participant identification, and experiment run. After the necessary data are entered, the sequential operations of the biofeedback system can be performed by clicking ordered buttons from left to right. As the sensors communicate with the integrated system, the psychophysiological signals are displayed on the GUI to make the users aware of the sensors’ working status under experimental conditions. All the signals were respectively represented on a trend chart, and the graphics were updated dynamically with a frequency of one Hz. However, the sampling frequency of the biometrical signal depended on the manufacturer’s design. This study used BLE as the communication protocol of the low-cost system, in line with the survey results in Section 1.1. This is because BLE is recognized as an essential part of the application of wearable sensors. Apart from the physiological sensors mentioned earlier, an ESP32 development board, WEMOS LOLIN32, was used to broadcast the measured value of the GSR sensor. WEMOS LOLIN32 is equipped with features such as BLE communication, it is tiny in terms of size, and is rechargeable using 3.7-volt lithium cells. The GSR value was broadcast with a customized GATT using this package at a frequency of 125 Hz. Its small size was essential for a wearable device, while the rechargeable 3.7-volt lithium cells were light and easy to apply. The experimenter could quickly recharge the battery through the USB-D type interface. Figure 3 shows the sensors/devices used in this research. Our solution costs less than USD one thousand compared with any medical-grade biofeedback system. Table 3 summarizes the free libraries that were used in the low-cost biofeedback system. The sampling frequency of each physiological characteristic is also listed. To make the system easy to use, we designed a GUI (Figure 4) using PySide6 to interact with the experimenter. EEG data were collected through COM port using NeuroSkyPy; HR and GSR values were accessed via BLE GATT using bleak; and face images were captured via a webcam and processed using OpenCV-python. All the data were visualized through dynamic graphs utilizing pyqtgraph. The graphs on the GUI were updated every second, with each update renewing 512 readings of EEG raw value, 125 readings of GSR intensity, and one reading of HR (Figure 4). Table 4 shows the definition of the EEG powers derived by NeuroSky TGAM. Although the powers and eSense meters were not shown on the GUI, they were recorded and saved with other signals when the save button was clicked. Moreover, the software applied a multithreaded framework to integrate these signals effectively. ## 3.3.2. Activity 4: Demonstration To validate the low-cost, open-source biometric integrated system developed in this study, we conducted a simple experiment with one participant. The experiment consisted of one baseline lasting one minute and two tasks lasting ten minutes each. The tasks were designed to test the system’s ability to handle different circumstances. The first task involved playing a popular first-person shooter (FPS) game, DOOM Eternal, using a physical keyboard and mouse. This task was referred to as the “2D game” since the screen is a two-dimensional environment. Figure 5 shows a screenshot of the game. The second task was to prepare the presentation slides using Google Slides in a mixed-reality (MR) environment. This task, which was called “3D slide” for MR science, involved a 3D environment. Figure 6 shows the screen when a user tries to prepare slides using HoloLens 2. There are no reports in the literature regarding the emotional response to using HoloLens 2 to create a slide. However, all the members who participated in the trial run complained about the task and provided feedback that was very different compared with the 2D game. We were only able to confirm that the 3D slide elicits a different response to the 2D game. Previous research [88] has shown that participants with varied experience levels perceived a more positive than negative affect in three FPS games, including the previous version of DOOM. As a result, the shooting game was assumed to create a positive emotional user experience. ## 3.4. Activity 5: Evaluation All of the physiological signals collected by the low-cost biofeedback system showed differences between the two designed scenarios in the experiment. Figure 7, Figure 8 and Figure 9 display the EEG raw values, HR, and GSR, respectively. Each signal has readings in the baseline, the 2D game, and the 3D slide, respectively. The unweighted mean number of data points is 100 for EEG and 125 for GSR. Because there is a considerable amount of data in the EEG raw values and GSR, it means the differences are not easy to observe in the limited width of a graph. Therefore, only the first 600 data points (aligned with the number of HRs) were truncated and displayed in Figure 7 and Figure 9. In addition, this study conducted two sample t-tests based on the data in Figure 7, Figure 8 and Figure 9. Each signal had three types of t-tests (baseline vs. the 2D game, baseline vs. the 3D slide, and the 2D game vs. the 3D slide). Table 5 summarizes the nine t-test results. All significant differences (p-value < 0.05) indicate that the biofeedback system developed in this study has the potential to be applied in future studies. Although the derived EEG power signals are not shown in Figure 6, Table 6 displays the saved powers. The derived power signals were updated with a frequency of one Hz and had no noise (Poor Signal is zero). Figure 10 shows the users’ facial expressions at the beginning of the 2D game and during the 2D game, respectively. A smiling face during the game experience is distinguished from a neutral face before the game starts. ## 4.1. Considerations of Selecting Sensors for Arduino Makers When selecting EEG products, researchers should take into account the utility frequency. There are two power line frequencies used worldwide: 50 Hz and 60 Hz, depending on the region or country. If an EEG device uses a different frequency from the electricity system in the researcher’s region or country, the signal will be biased from the correct value due to noise. The TGAM module for Arduino makers in this study is designed for users with a 50 Hz utility frequency. Therefore, the poor signal was not zero, indicating the presence of noise because the power frequency in Taiwan is 60 Hz. There are many PPG-type HR sensor options available in the makers’ market, and every manufacturer provides example codes and libraries for their users. However, the stability of acquiring the signal successfully and the accuracy of the reading value are not reported by the manufacturers. Due to the limitations of PPG technology, researchers have suggested using an LED matrix instead of a single LED to increase accuracy and stability [27]. Therefore, manufacturers targeting Arduino makers should endeavor to improve reliable measurement with more LEDs. However, consumer HR monitors with at least two LEDs are popular. The Rhythm+2.0 used in this study uses an extra yellow LED to obtain a more accurate measurement for Asian people [35]. All consumer HR monitors support the BLE function with a unique UUID, which makes accessing data with mobile equipment through applications quick. Unfortunately, most mainstream products can only be accessed through the specific software provided by the manufacturer. As a result, researchers wishing to integrate consumer-grade HR devices into their research face data processing difficulties. Investigators are usually interested in specific events in their research, and precise logging of the start/end time point when the onset occurred is complex, requiring more effort when using this type of product in research. ## 4.2. Performance of the Low-Cost Biofeedback Platform Developed in This Study While no noise obstructs the EEG signal with a 60 Hz chip, the poor signal is always zero (Table 6). The waveform obtained from the BrainLink Lite device (Figure 4) closely resembles those reported in the literature. The raw values obtained from the two different tasks show differences (Figure 5), indicating that the single-electrode wireless EEG can be applied in human behavior studies. This finding is consistent with the literature [89,90]. Although it is difficult to explain the meaning of EEG raw values directly, a noticeable difference exists (Figure 7). Further power analysis (Table 6) could help to explain the results more comprehensively. In contrast, the heart rate (HR) readings can directly explain the relationship between experimental settings. For example, the heart rate of the 2D game (Figure 8) was consistently higher than for the 3D slide, which suggests that the 2D game elicits more excitement from the player. Similarly, the GSR sensor for Arduino makers clearly distinguished between the 2D game and the 3D slide. Unlike the HR, the GSR signal in the 2D game was consistently lower in intensity than the signal in the 3D slide (Figure 9). This finding suggests that the user may have felt more relaxed during the 2D game than during the 3D slide. This is because the former is more enjoyable, while the latter is more frustrating. Our results demonstrate that HR and GSR can be used to evaluate whether the user experience is consistent with the literature [49]. In addition, facial expressions captured by a regular webcam and a mixed-reality headset have been validated as a means of emotion recognition in UX studies [52]. Figure 10 shows the facial expressions in neutral and delighted states during the 2D game in our study. Furthermore, the results of the EEG, HR, GSR, and facial expressions validate that the signals captured by our low-cost biofeedback system match the designed experimental conditions. Therefore, the platform developed in this study has the potential to be applied in future UX studies, which satisfies the first aim of our study. While low-cost biofeedback studies have been reported in the literature, their number is limited. Moreover, the existing literature reports that the hardware used was limited [1]; had a simple user interface for recording, event-marking, and downloading data without integration with the experiment control [91]; or required another computer to execute the experiment [26]. Some studies, such as event-related potential research, require precise biometric accuracy in milliseconds at the occurrence of the event of interest [92]. However, the existing literature cannot meet this specific requirement. This study aimed to integrate low-cost biofeedback hardware with graphic user interface software using open-source libraries to demonstrate its ability to differentiate between design contexts. Biofeedback was used as standalone equipment, without integration with the experiment stimulus. However, the GUI was an object-oriented programming class that can serve as an SDK. Researchers can customize the SDK with their experiment stimulus and synchronize it if necessary, allowing for precise biometric recordings when the desired event occurs in the future. This study achieved its second aim by integrating data collection and experiment control within one single computer system. While consumer-grade wearable devices have been widely used in non-medical applications, researchers need to understand whether the devices they choose satisfy the technical requirements of their study objectives. Compared with medical-grade instruments, consumer-grade products have lower sampling rates, less accuracy, a time lag in real-time data streaming, and may even experience data loss, as indicated in the introduction of this paper. These limitations can result in research failing to achieve desired outcomes. Researchers can utilize the wearable and lightweight biofeedback system to conduct laboratory or field research. Moreover, the low-cost platform’s convenience facilitates the construction of a database based on physiological signals for the development of machine learning models. This database is crucial for affective computing that is used in various fields, such as ergonomics, human factors engineering, user experience, human behavioral studies, and human–robot interaction. ## 5. Conclusions Although self-developed physiological data collection systems are reported in the literature, they typically consist of either a single sensor for collecting one type of signal or multiple sensors that are used independently with various personal computers and software to collect data To the best of our knowledge, the present study is the first to emphasize the importance of integrating low-cost individual sensors and consumer products into a single biofeedback system, developed using open-source software, to create a reusable SDK for future studies. This low-cost biofeedback solution is still at an experimental stage, and more research is required to investigate integrated experimental stimuli. Additionally, other physiological signals, such as electromyography (EMG) or eye-tracker, should be considered in future efforts to integrate the biofeedback platform. Wireless EMG sensors are readily available in the Arduino makers’ market, while all mainstream eye-tracker manufacturers have recently supported open-source Python libraries. A PyPI eye-tracking library for general webcams is also available. The open-source movement has enabled the availability of a diverse and rich low-cost biofeedback platform. A summary of the significant contributions of the current study are listed below. ## References 1. Jani A.B., Bagree R., Roy A.K.. Design of a low-power, low-cost ECG & EMG sensor for wearable biometric and medical application. Proceedings of the 2017 IEEE SENSORS 1-3 2. Silva D.C., Vinhas V., Reis L.P., Oliveira E.. 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--- title: Novel Approach for the Approximation of Vitamin D3 Pharmacokinetics from In Vivo Absorption Studies authors: - Grzegorz Żurek - Magdalena Przybyło - Wojciech Witkiewicz - Marek Langner journal: Pharmaceutics year: 2023 pmcid: PMC10052077 doi: 10.3390/pharmaceutics15030783 license: CC BY 4.0 --- # Novel Approach for the Approximation of Vitamin D3 Pharmacokinetics from In Vivo Absorption Studies ## Abstract The changing environment and modified lifestyles have meant that many vitamins and minerals are deficient in a significant portion of the human population. Therefore, supplementation is a viable nutritional approach, which helps to maintain health and well-being. The supplementation efficiency of a highly hydrophobic compound such as cholecalciferol (logP > 7) depends predominantly on the formulation. To overcome difficulties associated with the evaluation of pharmacokinetics of cholecalciferol, a method based on the short time absorption data in the clinical study and physiologically based mathematical modeling is proposed. The method was used to compare pharmacokinetics of liposomal and oily formulations of vitamin D3. The liposomal formulation was more effective in elevating calcidiol concentration in serum. The determined AUC value for liposomal vitamin D3 formulation was four times bigger than that for the oily formulation. ## 1. Introduction Vitamins are important for maintaining human health and wellbeing. Some of them are available only from exogenous sources as exemplified by vitamin C or vitamin B12. Since they are not produced endogenously, the determination of their pharmacokinetics is a straightforward task, at least from the methodological point of view [1,2]. The pharmacokinetic curve of vitamin C can be derived from a short time clinical study. [ 3,4]. Vitamin D3 is different. It originates from two sources: skin and foodstuff. This and the long half-time (about 20 days) make the determination of its pharmacokinetics challenging [5]. The most direct approach is to use a radiolabeled compound [6]. Regardless of the method used, there are numerous logistic and methodological difficulties making large-scale clinical studies demanding. In the paper, we propose a new method for vitamin D3 pharmacokinetic curve determination. It combines semi-physiological modeling and short time absorption data from clinical studies. Vitamin D3 is a compound, of which a deficiency can lead to numerous health risks [7]. Its importance for human organism functioning is demonstrated by the fact that the vitamin is required for the expression of over 700 genes [8,9]. Vitamin D3 is also critical element of calcium homeostasis [10]. The altered lifestyle of modern man (little exposure to natural sunlight) and changes in nutritional habits has resulted in wide-spread vitamin D3 deficiency [7]. Therefore, effective modes of supplementation are an important element of preventive medicine [11]. Vitamin D3 (cholecalciferol) is a precursor for its physiologically active metabolites calcidiol and calcitriol. The hydrophobic character of vitamin D3 and its metabolites requires complex absorption and redistribution mechanisms [2,12]. This is because hydrophobic compounds can be transferred across aqueous spaces only when associated with other molecule(s), forming water-soluble aggregates. This is critical since the cholecalciferol absorption (intestine) or synthesis (skin) are located in distal places with respect to the location of the first and the second steps of its metabolic transformation into the active form (liver and kidney). The transfer of hydrophobic compounds between the two locations requires mechanisms relying on dedicated and/or nonspecific carriers in the form of proteins and/or lipoproteins. Given orally, the cholecalciferol absorption consists of the sequence of events facilitated by ill-defined aggregates dispersed in the aqueous phase of the gastrointestinal tract. Vitamin D3 can reach the intestine wall only when it is in the aggregate capable to cross the mucus layer [12]. When vitamin D3 reaches enterocytes, it is internalized and released into serum while associated with specific carrier proteins (VDBP) [13,14] or with lipoproteins [15,16]. Its subsequent enzymatic transformation in the liver and kidneys is possible only because of this distribution system. Transport of vitamin D3 and its metabolites is controlled by proteins and/or lipoprotein mediators. It can be assumed that vitamin D3 internalization, redistribution, and subsequent transformation to calcidiol (25(OH)D3), which is routinely used for diagnostic purposes [17], can be qualitatively divided into two phases: before and after the internalization by competent cells in the intestine. Events prior to internalization by enterocytes are characterized by low specificity, whereas subsequent biodistribution and metabolic transformations are facilitated by very specific intracellular and extracellular events [9]. Absorption in the intestine can be greatly modified by changing the vitamin D3 formulation. [ 18,19]. This is because hydrophobic vitamin D3 is not capable of reaching the surface of the enterocyte alone. Instead, the absorption of vitamin D3 consists of a sequence of physicochemical and enzyme-assisted transformations taking place in the gastrointestinal tract [20]. Because water insoluble crystals of vitamin D3 cannot be effectively absorbed, it is commonly given as an oil formulation [15,21,22]. This by itself does not ensure efficient absorption since dispersion of oil in the aqueous phase will form an unstable and heterogenous emulsion [23,24]. For example, the coalescence of oily suspension will affect the digestion processes [12,25]. To be internalized, droplets of oil with vitamin D3 should reach the surface of the enterocytes [26,27]. This happens only when oily droplets can cross the mucus layer containing polymeric mesh formed by mucins. The mucus serves as a filter, preventing large particulates (>400 nm) from reaching enterocytes [28]. Vitamin D3 can be absorbed only when dissolved in particulates which are able to pass the mucus layer. This is difficult to achieve using the oily suspension alone [28,29]. All that will result is the limited capacity of an oily formulation to facilitate the efficient absorption of vitamin D3 [22,30]. Liposomes are convenient and biocompatible oral delivery vehicles [16,22]. They easily accommodate the hydrophobic vitamin D3 within their lipid bilayer and their size can be tailor-made. In addition, the mechanical stability of liposome lipid bilayer ensures that the cargo is delivered to the intestine wall ready for absorption [31,32]. In addition, when exposed to conditions simulating stomach and intestine environments (pH, temperature, bile salts and enzymes), their topology remains unchanged for a sufficiently long time to ensure the effective absorption. The main obstacle for the application of liposomes in everyday products has been the limited scale of available production processes and the belief that they are inherently unstable [33]. Those difficulties have been resolved by the introduction of Liposhell® technology, which is capable of delivering large quantities (tones) of a homogenous suspension of stable liposomes encapsulating a wide variety of active ingredients, including proteins and nucleic acids. The absorption of vitamin D3 in liposomes relies on their endocytosis and trans-endocytosis by enterocytes and possible M cells [6,34]. In addition, the stability of liposomes in the suspension enhances the internalization, regardless of the accompanying foodstuff. Table 1 shows characteristic properties of the two formulations of vitamin D3. The liposome suspension produced using Liposhell® technology is characterized by well-defined population of liposomes, ensuring optimal conditions for their internalization. The Liposhell® technology is based on the formation of tightly packed, uniform with respect to size, lipid vesicles (liposomal gel). The design of the liposome-based delivery strategy assumes that vitamin D3 is located in the hydrophobic core of the lipid bilayer. The stability of the liposome-vitamin D3 system with the presence of lipid vesicles and albumins was evaluated previously using isothermal titration calorimetry [38]. Specifically, no significant thermal signal was observed when liposomes with vitamin D3 were added to vitamin D3-free liposomes or albumins, showing that vitamin D3 does not equilibrate between liposomes and albumin, nor between liposomes. From the experiment, it has been concluded that, during digestion, vitamin D3 remains in liposomes regardless of their fate in the gastrointestinal tract. ## 2.1. Materials Soybean phosphatidylcholine (Phospholipon 90G) and vitamin D3 (cholecalciferol) were purchased from Lipoid GmbH (Ludwigshafen, Germany) and DSM Nutritional Product Ltd. (Village Neuf, France), respectively. Chloroform and methanol were obtained from VWR (Radnor, PA, USA), whereas ethanol and NaOH were from Stanlab (Lublin, Poland). All solutions were prepared with commercially purified water (AquaEngineering, Warsaw, Poland). ## 2.2. Preparation of Liposomal Vitamin D3 Formulation Liposomal vitamin D3 formulation was prepared as described in details elsewhere [36]. In short, liposomes were formed by mixing the organic phase with the aqueous phase (1:1 w/w). The organic phase contains propylene glycol, phospholipids ($20\%$ w/w in the final preparation), and vitamin D3. Next, the viscous gel was extruded through the 100 nm polycarbonate filter (Nucleopore Corp., Pleasanton, CA, USA). The content of phosphatidylcholine was determined by the HPLC-ELSD method [3]. Finally, the lipid gel was diluted 200 times with the glycerol/water (1:1 w/w) mixture and supplemented with natural flavor (0.3 w/w) and pectin (2.45 w/w). Liposomal vitamin D3 was prepared by Lipid Systems Sp. z o.o. ( Wrocław, Poland) under conditions satisfying HACCP and GMP requirements. ## 2.3. Characterization of Liposomal Vitamin D Formulation The size distribution of liposomes in the liposomal vitamin D3 formulation was determined by the dynamic light scattering method with some modifications in the preparation of the measured samples due to the presence of pectin (Zetasizer Nano ZS, Malvern, UK). The quantity of vitamin D3 was determined with RP-HPLC (Reversed-Phase High Liquid Chromatography) according to the method developed by Sazali et al. [ 39], with some modifications. The modular HPLC set composed of a pump (Azura P4.1S, KNAUER, Berlin, Germany), autosampler (Marathon Basic, Spark Holland, Emmen, The Netherlands), peltier column thermostat (Jetstram II Plus, Knaure, Berlin, Germany), and a UV-VIS detector (Azura UVD 2.1L, KNAUER, Berlin, Germany) was used. The separation was achieved using: 4.6 × 250 mm; 5 μm particles, 100 Å pore sizes, column (Eurospher 100-5 C18, KNAUER, Berlin, Germany). The freshly prepared mixture of methanol and water (98:2 v/v) as the isocratic mobile phase was pumped at a flow rate of 1 mL/min at 40 °C. The injection volume was 20 μL. Samples for the calibration curve were prepared at the concentration range of 0.6–9 μg/g of vitamin D3 in ethanol. Samples of liposomal formulations were dissolved in ethanol at the $\frac{4}{10}$ (w/w) ratio, mixed, centrifuged (2800 rpm for 10 min.), and filtered through 0.2 μm cellulose membrane before analysis [40]. ## 2.4. Cryogenic Transmission Electron Microscopy (TEM) Imaging Cryogenic Transmission Electron Microscopy (cryo-TEM) images were collected with a Tecnai F20 X TWIN microscope (FEI Company, Hillsboro, OR, USA) equipped with a field emission gun operating at an acceleration voltage of 200 kV. Images were recorded on the Gatan Rio 16 CMOS 4 k camera and processed with Gatan Microscopy Suite (GMS) software (Gatan Inc., Pleasanton, CA, USA). Specimen preparation was done by the vitrification of the aqueous solutions on grids with holey carbon film (Quantifoil R $\frac{2}{2}$; Quantifoil Micro Tools GmbH, Großlöbichau, Germany). Prior to use, the grids were treated for 15 s in oxygen plasma using a Femto plasma cleaner (Diener Electronic, Ebhausen, Germany). Cryo-samples were prepared by applying a droplet (3 μL) of the suspension to the grid, blotting with filter paper, and immediate freezing in liquid ethane using a fully automated blotting device Vitrobot Mark IV (Thermo Fisher Scientific, Waltham, MA, USA). The vitrified specimens were kept under liquid nitrogen prior the insertion into a cryo-TEMholder Gatan 626 (Gatan Inc., Pleasanton, CA, USA) and analyzed at −178 °C. ## 2.5. Clinical Studies and Quantification of Calcidiol in Serum The clinical experiment has been thoroughly described elsewhere [36]. In summary, the study was performed on 18 healthy volunteers (age 24–65) according to “the cross-over design”. Following a 12 h fasting, each volunteer was given 10,000 IU of vitamin D3, either in the liposomal or oily formulation. After 3 weeks, the experiment was repeated, but volunteers consumed the other vitamin D3 formulation. The marketed product was used as the oily formulation. The quantity of vitamin D3 in oily formulation was used as specified by the producer. Less than 50 μL of blood was drawn from a finger of each volunteer at eight-time points; the reference sample shortly before and 0.5, 1, 1.5, 2, 3, 4, and 5 h following the intake of vitamin D3. Blood samples of the volunteer were collected by qualified personnel, and the concentration of 25(OH)D3 measured by Cambridge Diagnostics Sp. z o.o. ( Poland). All procedures involving humans were approved by the Bioethical Commission at the Research and Development Centre at the Specialized Hospital in Wrocław, number: KB/$\frac{07}{2020.}$ The vitamin D3 absorption was evaluated based on the concentration of calcidiol in serum. Specifically, the initial quantity of 25(OH)D3 (shortly before supplementation, A0) was subtracted from its values at later time points, A(t), and the obtained difference normalized to the initial value [(A(t) − A0)/A0]. Next, the tendency of 25(OH)D3 change was approximated with the linear function using the last square fitting. A straight line was then used to estimate the calcidiol concentration in serum for the pharmacokinetic curve reconstruction. ## 2.6. The Reconstruction of Pharmacokinetic Curve for Calcidiol The absorption of vitamin D3 is followed by its transfer to the liver, where it is metabolically transformed. The literature data show that the pharmacokinetic curve for calcidiol reaches a maximum at three days after supplementation with cholecalciferol. However, the steep rise of calcidiol concentration in serum shortly after supplementation indicates rapid absorption and enzymatic transformation of cholecalciferol to calcidiol in the liver. The shape of the pharmacokinetic curve during the first day after supplementation justifies the assumption that calcidiol can be evaluated even during the first few hours following supplementation. The advantage of such approach is the elimination of possible interferences resulting from unpredictable and difficult to control volunteer behavior, when outside the medical facility (exposure to the sun and/or variation in diets). Consequently, during the reduced time of the experiment, the observed rise of calcidiol is affected exclusively by the absorption efficiency. This is because, after fasting, the supplement will pass the absorption zone in the intestine during the few hours following the supplementation [41]. When a single dose of vitamin D3 is administered, its quantity in serum can be described by the following formula:[1][D3(t)]=−k∫0t[D3(t)]dt where [D3(t)] represents the concentration of vitamin D3 in serum. The amount of vitamin D3 absorbed in the intestine [D3[0]] and can be expressed by the empirical formula [29]:[2][D3[0]]=∫0ttransitJmuc(t)dt where ttransit stands for the time, when vitamin D3 resides in the region of intestine where the absorption is taking place, and Jmuc(t) represents the flux of vitamin D3 across mucus lining the intestine wall. Parameters which define the absorbed quantity—ttransit and Jmuc(t)—depend on vitamin D3 formulation. When formulation disperses uniformly in the stomach content, the transit time will increase. No such effect will be observed when the coalescence occurs [16]. The flux of vitamin D3 across the mucus will depend predominantly on properties of particulates such as surface charge, propensity for enzymatic activity, ability to accommodate bile acids, and most importantly their size. The size of particulates is an important parameter since mucus can be penetrated only when it does not exceed 400–500 nm [26,28]. The quantity of 25(OH)D3 in serum can be approximated by the following equation:[3][25(OH)D3(t)]=∫0t{k[D3(t)]−m[25(OH)D3(t)]}dt [D3(t)] is a cholecalciferol concentration, [25(OH)D3(t)] stands for the concentration of calcidiol, and k and m are constants describing the synthesis (liver) and degradation (kidneys) of calcidiol. It has been assumed that the quantity of vitamin D3 at $t = 0$ equals to the amount of vitamin D3[0] absorbed. The dependence of a calcidiol concentrations on time follows the formula:[4][25(OH)D3(t)]=ckm+ke−ktm−k+αe−mt Except the [D3[0]] value, all other parameters are dependent on metabolic processes. To calculate those parameters, the experimental data from the literature [42] were normalized and the function [4] was optimized with respect to k and m, assuming that the initial calcidiol concentration C[0] = 0. In addition, we assumed that, for a single application, $c = 0$ since logt→∞C(t)=0. The optimalization of the dissipation function equals the average distance between experimental and theoretical points. Consequently, the pharmacokinetic curve of calcidiol can be reconstructed from the combination of time-limited clinical studies and mathematical equations derived from experimental data [42]. ## 3. Results and Discussion The absorption of vitamin D3 in liposomes is most efficient when their size does not exceed 250–300 nm [43]. Figure 1 shows the size distribution of liposomes along with the respective correlation function determined using dynamic light scattering. The average size of liposomes and polydispersity index (PDI) were equal to 117 nm. and 0.23, respectively. Visualization of liposomes with cryoTEM demonstrated that they are spherical, unilamellar, and confirmed the homogeneity of their size distribution. When an oily formulation of vitamin D3 is dispersed in water, it forms a heterogenous emulsion. The two formulations are expected to behave differently in the gastrointestinal tract, affecting the absorption efficiency of vitamin D3. The short clinical experiment showed that the measured absorption rate, evaluated with slopes of linear functions, were statistically different and equaled to 7.03 × 10−5 1/min ± 3.02 × 10−4 1/min and 4.01 × 10−4 1/min ± 7.12 × 10−4 1/min for oily and liposomal formulations, respectively [35]. Those values were used to calculate the calcidiol concentration in serum at ttransit. The developed method was next used in studies regarding characterization of two vitamin D3 formulations. In the analysis it had been assumed that the quantity of cholecalciferol and calcidiol in serum were at a concentration range where all proteins involved in cholecalciferol absorption, distribution, and metabolic transformation were not saturated. This means that the quantities of the absorbed cholecalciferol and the concentration of calcidiol in serum can be quantitatively correlated. Examples of pharmacokinetic curves derived for persons with vitamin D3 deficiency for two different formulations (oily and liposomal) are presented on Figure 2. The reconstructed pharmacokinetic profiles of the oily and liposomal formulations were assessed using the standard single-compartmental pharmacokinetic analysis. Using the methodology, the following pharmacokinetic parameters have been derived: the maximum concentration of calcidiol (Cmax), the area under curve for the first day following the dose (AUC1day), the area under the curve calculated from the 2nd to the 30th day following the dose (AUC2day-30days), and the AUC1day-30day—the area under the plasma concentration–time curve integrated from zero to 30 days following the supplementation (AUC1day-30day), calculated as a sum of AUC1day and AUC2day–30 day. The time at which the maximum concentration is reached (Tmax) and the elimination half-life of calcidiol (t$\frac{1}{2}$) depend exclusively on metabolic processes, meaning that they do not depend on the type of formulation [42] (Table 2). The pharmacokinetics of calcidiol following the supplementation with cholecalciferol depends on the vitamin D3 formulation. Clinical experiment has shown that for persons with a significant deficiency of vitamin D3, the application of liposomal formulation causes a significant and rapid increase of calcidiol concentration in serum. The effect of the oily formulation of cholecalciferol is much smaller. Specifically, AUC1day determined for calcidiol, reflecting the efficiency of cholecalciferol absorption, increased from 0.037 [day·ng/L] to 0.135 [day·ng/L], almost 3.6 times, which makes the increase of the AUC1day-30day from 1.69 [day·ng/L] to 8.5 [day·ng/L], i.e., 5 times. The AUC1day-30day relates to pharmacokinetics of calcidiol, which depends on the quantity of absorbed cholecalciferol and physiological processes affecting its serum concentration. The increase in the maximum concentration of calcidiol is also substantially elevated from 0.067 [day·ng/L] to 0.335 [day·ng/L]. Derived numbers confirmed the prediction that liposomes with well-defined sizes are a far more effective formulation in delivering hydrophobic vitamin D3 then their oily equivalent. ## 4. Discussion The vitamin D3 digestion and absorption processes depend on physiological factors such as low pH and mechanical agitation in the stomach, followed by enzymatic degradation and bile acid emulsification in the intestine. In addition, the digestion will be affected by the presence of foodstuffs and the type of vitamin D3 formulation [12]. The two formulations of cholecalciferol (oil and liposomes) selected for comparison are qualitatively different. Since the formation of an emulsion from the oily formulation is taking place in the gastrointestinal tract, it is impossible to control, and the resulting dispersion of oil will be heterogenous with propensity to coalesce [26,29]. The suspension of liposomes is different; it is a two-phase system, where the hydrophobic region of the spherical lipid bilayer separates two aqueous phases. Liposomes can be produced in such a way that they will form a suspension, which is uniform with respect to the liposome size. In such a system, cholecalciferol is in the hydrophobic region of a liposome-forming lipid bilayer [36]. Liposomes are very stable structures, which cannot be easily destabilized unless their chemical composition is altered. This can be achieved by the action of digestive enzymes or by an association with natural detergents (bile acids) [31,32]. Importantly, dilution or mixing of liposome suspension with foodstuff will not affect their topology, nor their size. The uniform distribution of liposomes within foodstuff results in the extended exposure time. In addition, with appropriate sizes (less than 400 nm), liposomes can enter body compartments by two independent pathways: endocytotic and transendocytotic. Whereas the pathway from endosome to chylomicrons is complicated and time-consuming [44], transcytosis will result in intact liposomes crossing the intestine wall and rapidly entering the immunological system [27]. The latter will accelerate the appearance of cholecalciferol in serum and the subsequent transformation to calcidiol. The oily formulation behaves differently; it may coalesce in the stomach, shortening the exposure time to enterocytes. The additional factor affecting the absorption of vitamin D3 from the oily formulation is its high heterogeneity and low stability upon digestion. In summary, whereas liposomes will remain unchanged or decrease in size, the sizes of oily droplets, characterized by their propensity to coalescence, will increase [35]. With the much shorter residence time in the intestine and a non-optimal size distribution, only aa fraction of oil (vitamin D3) will have access to the surface of enterocytes. The vitamin D3 redistribution mechanisms and its transformation to calcidiol in the liver make it difficult to alter metabolic processes. Consequently, it can be assumed that the quantity of calcidiol will scale with the amount of absorbed vitamin D3. The quantity of absorbed vitamin D3 from a dose will depend on the exposure time and formulation-dependent accessibility for competent cells. The exposure time is a function of peristaltic activity, stomach content, and the distribution of vitamin D3. Clinical data presented by Armas et al. [ 42] shows the pharmacokinetics of radiolabeled vitamin D2 and vitamin D3 following oral administration. The dependence of concentration profiles in the absorption phase of the two formulations are very similar. Dependence of the concentration of calcidiol as a function of time is different. The maximum is reached only on the 5th day for vitamin D2 and on about the 15th day for vitamin D3. These data show that the absorption and biodistribution processes can be analyzed separately and that the character of calcidiol pharmacokinetic curves will be affected by the quantity of absorbed vitamins and the efficiency of the subsequent metabolic processes. Rapid absorption of vitamin D3 justifies the approach, in which the initial rise of calcidiol serum concentration is driven predominantly by the quantity of absorbed vitamin D3. Later, when the absorption phase is completed, the pharmacokinetic profile of calciferol depends exclusively on the metabolic processes [8]. Therefore, the shape of the pharmacokinetic curve is preserved, but the value of AUC will depend exclusively on the quantity of the absorbed vitamin [12,20,45,46,47]). Consequently, the pharmacokinetic curve for a formulation can be reconstructed from the quantity of absorbed vitamin D3 and the predetermined shape of the pharmacokinetic curve [1,48,49]. ## 5. Conclusions The effective supplementation of hydrophobic vitamin D3 requires the application of excipients, which will facilitate its dissolution. However, this by itself will not ensure its effective absorption. The efficient vitamin D3 absorption will take place from formulations in the form of droplets characterized by sizes smaller than 250–300 nm, resulting from the size of the intestine mucus pores [43]. Dispersion of liposomes with vitamin D3 is an example of such a formulation. The absorption of vitamin D3 in liposomal and oily formulations was evaluated using short-term absorption data supplemented with physiology-based mathematical modeling. 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--- title: Role of Dietary Defatted Rice Bran in the Modulation of Gut Microbiota in AOM/DSS-Induced Colitis-Associated Colorectal Cancer Rat Model authors: - Laleewan Tajasuwan - Aikkarach Kettawan - Thanaporn Rungruang - Kansuda Wunjuntuk - Pinidphon Prombutara journal: Nutrients year: 2023 pmcid: PMC10052090 doi: 10.3390/nu15061528 license: CC BY 4.0 --- # Role of Dietary Defatted Rice Bran in the Modulation of Gut Microbiota in AOM/DSS-Induced Colitis-Associated Colorectal Cancer Rat Model ## Abstract Defatted rice bran (DRB) is a by-product of rice bran derived after the oil extraction. DRB contains several bioactive compounds, including dietary fiber and phytochemicals. The supplementation with DRB manifests chemopreventive effects in terms of anti-chronic inflammation, anti-cell proliferation, and anti-tumorigenesis in the azoxymethane (AOM) and dextran sodium sulfate (DSS)-induced colitis-associated colorectal cancer (CRC) model in rats. However, little is known about its effect on gut microbiota. Herein, we investigated the effect of DRB on gut microbiota and short chain fatty acid (SCFA) production, colonic goblet cell loss, and mucus layer thickness in the AOM/DSS-induced colitis-associated CRC rat model. The results suggested that DRB enhanced the production of beneficial bacteria (Alloprevotella, Prevotellaceae UCG-001, Ruminococcus, Roseburia, Butyricicoccus) and lessened the production of harmful bacteria (Turicibacter, Clostridium sensu stricto 1, Escherichia–Shigella, Citrobacter) present in colonic feces, mucosa, and tumors. In addition, DRB also assisted the cecal SCFAs (acetate, propionate, butyrate) production. Furthermore, DRB restored goblet cell loss and improved the thickness of the mucus layer in colonic tissue. These findings suggested that DRB could be used as a prebiotic supplement to modulate gut microbiota dysbiosis, which decreases the risks of CRC, therefore encouraging further research on the utilization of DRB in various nutritional health products to promote the health-beneficial bacteria in the colon. ## 1. Introduction Colorectal cancer (CRC) remains an unresolved global public health burden, ranking third in incidence and mortality worldwide. According to a recent study, CRC cases will reach around 3.2 million in 2040 [1]. Genetics, environmental factors, and gut microbiota have been related to CRC development and progression. CRC occurs in the colon; therefore, it is closely linked to gut microbiota changes. The gut microbiota is vital in maintaining intestinal homeostasis [2]. While gut microbiota dysbiosis (changes in microbial communities) disrupts intestinal homeostasis, leading to increased intestinal epithelium permeability, bacterial pathogens invade the epithelial cells quickly and stimulate the host immune responses [3,4,5]. The binding between microbial ligands (known as microbial associated molecular patterns (MAMPs)) such as lipopolysaccharide (LPS) and peptidoglycan (PGN), present on the bacterial cell surface, and pattern recognition receptors (PRRs) such as toll-like receptors (TLRs) and Nod-like intracellular receptors (NODLRs), present on the host immune cells, results in stimulating host immune responses and producing pro-inflammatory cytokines, which protects the intestinal epithelial cells from bacterial invasion [6]. The prolonged production of pro-inflammatory cytokines induces chronic inflammation in the colon, which can develop to CRC. Therefore, maintaining a healthy gut microbiota with prebiotic or probiotic supplements for the excellent health of colon cells has emerged as an alternative treatment for CRC. Rice bran is the outer layer of milled rice, produced as a by-product in the rice milling process. It contains many nutrients, including starch, dietary fibers, lipids, proteins, vitamins, and minerals [7,8]. Nowadays, rice bran has been widely employed in the manufacturing of rice bran oil. During the industrial production of rice bran oil, large amounts of DRB are produced. During the oil extraction process, some essential nutrients are removed, but DRB still retains compounds of high nutritional value, such as soluble and insoluble dietary fiber, and some phytochemicals [9]. In particular, dietary fiber, an essential component of DRB, has been reported to be associated with increased intestinal microbiota community and could be protected against CRC [10]. In an animal study, Huan Wang et al. determined that finishing pigs fed with $7\%$ of DRB as a substitute for corn had a beneficial effect on the thickness of intestinal wall, and increased Bifidobacterium and Clostridium perfringens in the colon [11]. In a similar study, $10\%$ fermented DRB supplementation in finishing pigs for 30 days enhanced the gut microbial richness and the abundance of fiber-degrading bacteria (Clostridium butyricum and Lactobacillus amylovorus). Moreover, supplementation of $10\%$ fermented DRB also significantly elevated the short-chain fatty acids (acetate and butyrate) in feces [12]. More recently, the insoluble dietary fiber, extracted from DRB by enzymatic treatments, could restore the reduction in species of gut microbiota caused by high-fat diet, increase the richness of the microbial community, and alter the metabolic function of gut microbiota on hyperlipidemia in rats fed with a high-fat diet [13]. Dietary fiber fermented by bacterial enzymes is converted into short-chain fatty acids (SCFAs), primarily acetate, propionate, and butyrate, representing the 90–$95\%$ of the SCFAs present in the colon. The fiber has also shown prebiotic properties in several studies. High dietary fiber intake increases butyrate-producing bacteria and SCFAs production in the colon. SCFAs have been suggested as the key metabolites linking the gut microbiota to inflammation and CRC. SCFAs are absorbed across the epithelial cells (colonocytes) through passive diffusion, and active transport mediated by monocarboxylate transporters 1 (MCT1) and sodium-coupled monocarboxylate transporter 1 (SMCT1) to maintain intestinal homeostasis and generate adenosine triphosphate (ATP) for colonocytes [14]. In addition, SCFAs act as endogenous ligands for G protein-coupled receptors (GPCRs), and intracellular SCFAs affect gene expression by inhibiting the histone deacetylase (HDAC) [15]. The study of SCFAs, especially propionate and butyrate, has highlighted their effects on immune modulation and inflammatory responses. For instance, propionate and butyrate regulate the T cell function through G-protein-coupled receptors (GPR43 and GPR109A), and by inhibition of histone deacetylase (HDAC), which hampers the activation of the NF-κB signaling pathway [16,17]. Likewise, these SCFAs also inhibit the pro-inflammatory cytokine production (IL-6, IL-8, IL-1β, and TNF-α) by leucocytes [16,18]. Moreover, propionate and butyrate affect the differentiation of regulatory T cells (FOXP3) and the production of IL-10, which reduce inflammation [16]. SCFAs also exert anti-carcinogenesis effects in the colon by promoting apoptosis and suppressing the proliferation of tumor cells through the Wnt/β-catenin signaling pathway by inhibiting HDAC activity [14,19,20]. Numerous studies have shown that butyrate is critical for modulating immune and inflammatory responses and mucus barrier function [21]. Moreover, butyrate stimulates mucin secretion, which is essential for mucoprotection. Therefore, the present study investigates the effect of dietary DRB on gut microbiota and SCFAs production, colonic goblet cell loss, and mucus layer thickness in the AOM/DSS-induced colitis-associated CRC model in rats. ## 2.1. Defatted Rice Bran (DRB) DRB was obtained from Thai Ruam Jai Vegetable Oil Co., Ltd. (Phra Nakhon Si Ayutthaya, Thailand). It was procured from a mix of brown Thai rice varieties in the central area of Thailand. After rice milling, the bran was extracted with hexane. DRB was powdered and heated to lower moisture after the oil extraction process, then passed through a 60-mesh sieve and kept in a sealed container under a hygienic condition at −20 °C until further use. ## 2.2. Animal Experiment and Sample Collection All animal experiments followed the ethical procedure guidelines from Siriraj Animal Care and Use Committee, Mahidol University (COA no. $\frac{004}{2562}$). Wistar male rats (age: four weeks old, weight: 90–100 g) were obtained from Nomura Siam International Co., Ltd. (Bangkok, Thailand). All rats were housed in individually ventilated plastic cages (2 rats/cage) under standard conditions (temperature 23 ± 1 °C; humidity 50 ± $10\%$ and 12 h-light/dark cycle) and were allowed access to a standard commercial diet and water. Experimental animal design of the study is shown in Figure 1A. After a one-week adaptation period, rats were randomly administered into six groups: [1] control, [2] defatted rice bran 3 g (DRBL), [3] defatted rice bran 6 g (DRBH), [4] induction, [5] induction + DRBL, and [6] induction + DRBH. The rats of groups 2, 3, 5, and 6 were administered gavaged feeding with 3 and 6 g/kg DRB daily throughout the study, while the control group and induction group received orally sterile water daily. The dose of DRB followed the previous studies [22,23] and then converted to an animal equivalent dose using the ratios of human and rat body surface area [24]. All rat’s body weight and food intake were daily recorded throughout the study (Tables S1 and S2). After two weeks, the rats of groups 4, 5, and 6 were subcutaneously injected with 15 mg/kg AOM (Sigma-Aldrich Pte. Ltd., Singapore) once weekly for 2 weeks. One week later, the rats received $4\%$ (w/v) DSS (TdB Consultancy, Uppsala, Sweden, molecular weight 36–50 kDa) in drinking water for one week, followed further by one week of recovery with regular water and repeated one time for the DSS induction period. All rats were euthanized by CO2 asphyxiation at ten weeks after the first AOM injection. The cecal and colonic luminal contents were collected and stored at −20 °C until further use. In this study, the colonic luminal contents were used and represented as a fecal sample. Afterward, the colon specimens were gently washed with cold phosphate-buffered saline solution (PBS) and the colon’s weight and length were measured (Table S3). Then, the surface of the colonic mucosa was scraped vigorously with a sterile scalpel blade, and the tumor tissues (Figure 1B) were removed and stored at −20 °C until further use for microbiome analysis. The remaining colon specimens were kept in $10\%$ neutral phosphate-buffered formalin for alcian blue/periodic acid-Schiff staining. ## 2.3. Colonic Goblet Cells and Mucus Layer Thickness Evaluation Post $10\%$ neutral phosphate-buffered formalin fixations (at least 24 h), colon specimens were dehydrated in a series of graded ethanol and cleared with xylene. Then, the colons were embedded in a paraffin block, and the transversal sections were cut into 4 µm using a microtome. The paraffin-embedded sections were placed on glass slides, then de-paraffinized with xylene and rehydrated with absolute and $95\%$ ethanol. The colonic sections were stained with alcian blue solution (pH 2.5) for 30 min, periodic acid for 10 min and Schiff solution for 10 min, respectively. The colonic goblet cell and mucus layer thickness were observed under an Olympus SC 180 microscope (Olympus, Shinjuku-ku, Tokyo, Japan) using 4×, 10×, and 40× objectives, and images were captured. Ten different fields per section and three sections per rat were randomly chosen for evaluation. The goblet cell loss is defined as reducing goblet cell numbers relative to baseline goblet cell numbers per crypt. The goblet cell loss was evaluated by counting the number of goblet cells per crypt. At the same time, the mucus layer thickness was measured using Image J software version 1.52a (National Institutes of Health, Bethesda, MD, USA), with the observer being blinded to the analysis. ## 2.4.1. DNA Extraction Metagenomic DNA in colonic luminal contents (feces), mucosa surfaces, and tumor tissues were extracted using the QIAamp Power Fecal Pro DNA kit (Qiagen, Germantown, MD, USA), according to the manufacturer’s instructions. Before DNA extraction, the tumor tissues were lysed using the MasterPure Complete DNA and RNA Purification kit (Lucigen, Middleton, WI, USA), following the manufacturer’s protocol. Negative controls were always performed during extraction to verify this process without contamination. Purification and concentration of the DNA quantified using a NanoDrop spectrophotometer (Implen GmbH, München, Bayern, Germany), and DNA quality was checked by $1\%$ agarose gel electrophoresis. The DNA samples were stored at −20 °C until further analysis. ## 2.4.2. 16S rRNA Amplicon Library Preparation and Sequencing The 16S rRNA gene was amplified from metagenomic DNA samples using a primer targeting the V3–V4 region (16S Forward Primer 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3′ and 16S Reverse Primer 5′-GTCTCG TGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGTATCTAATCC-3′) (Macrogen Inc., Gangnam-gu, Seoul, Republic of Korea) by a thermocycler PCR system (PCRmax Alpha Cycler, Staffordshire, UK). The PCR reaction for colonic luminal contents was composed of a DNA template (2 µL), primers (0.5 µL), ultrapure distilled water (9.5 µL) (Invitrogen, Waltham, MA, USA), and 2× HiFi PCR master mix (12.5 µL) (sparQ HiFi PCR master mix, Quantabio, Beverly, MA, USA), while for mucosa and tumor tissue, the PCR reaction was composed of a DNA template (5 µL), primers (0.5 µL), ultrapure distilled water (6.5 µL), and 2× HiFi PCR master mix (12.5 µL). Negative controls were always performed to verify the process without contamination. PCR was performed under the following conditions: an initial denaturing step at 98 °C for 2 min followed by 28 amplification cycles (for luminal content samples) and 30 amplification cycles (for mucosa and tumor tissue samples) at 98 °C for 20 s, 60 °C for 30 s, and 72 °C for 1 min, and a final extension step at 72 °C for 1 min. 16S V3 and V4 amplicons were verified by agarose gel electrophoresis. Afterwards, PCR products were purified using the sparQ PureMag beads (Quantabio, Beverly, MA, USA). The purified 16S amplicon was indexed using the 2× HiFi PCR master mix and 2.5 µL of each Nextera XT index primer (Nextera XT Index Kit v2, Illumina Inc., San Diego, CA, USA) in a 25 µL PCR reaction, followed by 8 cycles of PCR condition. 16S index amplicons were verified by agarose gel electrophoresis. Subsequently, the purified 16S index library was pooled at a concentration of 4 nM, measuring concentration by Qubit ds DNA HS assay kits (Invitrogen, Eugene, OR, USA) and diluted to final loading concentration at 5 pM, using pre-chilled hybridization buffer (HT1) (Illumina Inc., San Diego, CA, USA). Finally, $25\%$ of the whole-genome sequencing (WGS) control library was spiked into the pooled library and added to the Miseq Reagent Kit v2 (500 cycles) (Illumina Inc., San Diego, CA, USA). Cluster generation and 250 bp paired-end read sequencing were performed on an Illumina MiSeq platform at Omics Sciences and Bioinformatics Center (Chulalongkorn University, Bangkok, Thailand). ## 2.4.3. Bioinformatics Analysis FATSQ raw data were generated and de-multiplexed using Miseq reporter software version 3.1. Targeted V3–V4 primer sequences were removed or trimmed, and the data were imported to Quantitative Insights Into Microbial Ecology 2 (QIIME2) software version 2019.7. The imported sequencing reads were preprocessed using the DADA2 program. Denoised reads were clustered into amplicon sequence variants (equivalent to OTUs), and the sequence reads were assigned to operational taxonomic units (OTUs) at $97\%$ nucleotide identity. Then, a phylogenetic tree was built using SEPP QIIME 2 plugin. A rarefaction curve was created, and the Pielou’s evenness, Faith’s phylogenetic diversity, observed OTUs, and Shannon diversity index were also measured alpha diversity within microbial communities. Beta diversity metrics, including Bray–Curtis dissimilarity, Jaccard index, and weighted and unweighted UniFac distance were calculated microbial communities in each sample, and principal coordinate’s analysis (PCoA) plots were generated. Finally, taxonomy was assigned to the OTUs using a Naive–Bayes approach implemented in the scikit learn Python library and the SILVA database, and classification stacked bar plots were created. ## 2.5. Short-Chain Fatty Acid (SCFA) Analysis The cecal SCFA concentrations, including acetic, propionic, and butyric acid, were measured according to a modified method by Ribeiro W.R. et al. [ 25]. The cecal SCFAs were extracted using a liquid–liquid extraction procedure. Approximately 20 mg of cecal contents was removed to microtubes and placed on ice. A total of 200 µL of distilled water was added to the cecal contents and then homogenized using a metal spatula. A total of 20 mg of citric acid, 40 mg of NaCl, 40 µL of 0.1 M HCl, and 200 µL of organic solvents (N-butanol, tetrahydrofuran, and acetonitrile) in 5:3:2 ratios were added into the homogenate samples and mixed vigorously using the vortex for 1 min. The mixture samples were centrifuged at 15,000× g at 4 °C for 10 min. The supernatant was transferred to chromatographic vials equipped with 200 μL inserts and stored at −20 °C until further analysis. The supernatant (2 μL) was injected in a 50:1 split ratio into a gas chromatograph (model 6890N; Agilent Technologies, Santa Clara, CA, USA) equipped with a flame ionization detector (FID) and a capillary column (DB-23, 60 m × 0.25 mm × 0.25 µm) coated with a film of 0.25 µm composed of $74.5\%$ 1-methyl-naphthalene. Helium was used as a carrier gas. The initial oven temperature was maintained at 70 °C for 5 min and increased at 5 °C/min to 80 °C for 5 min. The injector and detector temperatures were set at 250 °C. The SCFA contents in cecal were identified by retention time compared to SCFAs standard (acetic [71251], propionic [94425], and butyric acid [19215], Sigma-Aldrich Pte. Ltd., Singapore). The EZChrom software version 3.3.1 was used to integrate the peak areas. The SCFA concentrations (mg/mL) in each sample were determined by comparing their peak areas with standard calibration curves. Finally, the mg/mL unit was converted to mmol/kg. This procedure calculated a percent recovery range of 90–110 for quality control. ## 2.6. Statistical Analysis The alpha diversity was used to measure the richness and evenness within-microbial communities using the Kruskal–Wallis test. The beta diversity was used to determine the differences in the composition structure of microbial communities among samples. Permutational multivariate analysis of variance (PERMANOVA) tested the differences in beta diversity. The linear discriminant analysis (LDA) effect size (LEfSe) was used to indicate the significantly differential abundance of bacterial genus among groups, with the LDA score >3. Colonic goblet cells, mucus layer thickness, and SCFAs contents were compared using one-way ANOVA followed by post hoc multiple comparisons and analyses using Tukey’s test to compare all experimental groups. Statistical software (SPSS Inc. version 17.0, Chicago, IL, USA) was used to perform all the statistical analyses. Statistical significance was considered at $p \leq 0.05$ for all tests. Data were expressed as means ± standard errors of means (S.E.M). All experiments were performed in triplicate. ## 3.1. DRB Supplementation Protection against Goblet Cell Loss in AOM/DSS-Induced Colitis-Associated CRC Rats The colonic goblet cell loss was evaluated by counting the number of goblet cells per colon crypt. Figure 2A shows the histopathology of colonic tissue sections with goblet cells in the colon crypts in each experimental group. Goblet cells are mucin-secreting glands with a cup-like shape (narrow base and wide apex) located within the simple epithelium of the gastrointestinal tract. The goblet cells showed light blue color when stained with alcian blue and periodic acid-Schiff (PAS) dye. The control, DRBL, and DRBH groups do not show goblet cell loss within the colon crypts. Conversely, the induction, induction + DRBL, and induction + DRBH groups showed a loss of goblet cells. The number of goblet cells per crypt in each experimental group is shown in Figure 2B. The number of goblet cells per crypt in control, DRBL, and DRBH groups was 25.92 ± 0.90, 25.98 ± 0.50, and 27.00 ± 0.52, respectively. There was no significant difference between the three groups. On the other hand, the induction, induction + DRBL, and induction + DRBH groups exhibited a significant decrease in the number of goblet cells (7.57 ± 0.75, 9.08 ± 0.80, and 11.04 ± 0.43, respectively) compared with the control group ($p \leq 0.05$). Apart from this, the induction + DRBH group showed a significant increase compared to the induction group ($p \leq 0.05$). These results indicated that DRB might restore goblet cell loss in the AOM/DSS-induced colitis-associated CRC rats. ## 3.2. DRB Supplementation Restored Intestinal Barrier in AOM/DSS-Induced Colitis-Associated CRC Rats Figure 3A shows the histopathology of colonic tissue sections with mucus layers in each experimental group. The mucus secreted by goblet cells covers the surface of the epithelium of the gastrointestinal tract to lubricate the luminal contents and work as a physical barrier to bacteria and other antigenic substances present in the lumen. The mucus layer stained with alcian blue showed light blue color. The control, DRBL, and DRBH groups showed a firm mucus layer, whereas the induction, induction + DRBL, and induction + DRBH groups showed a thin mucus layer. The mucus layer thickness in each experimental group is shown in Figure 3B. The mucus layer thickness in control, DRBL, and DRBH groups was 32.79 ± 1.69, 33.76 ± 1.75, and 34.71 ± 0.74, respectively. At the same time, thickness in DRBL and DRBH groups was slightly higher than that of the control group but showed no significant difference. In contrast, the induction, induction + DRBL, and induction + DRBH groups showed a significant decrease in the thickness (16.82 ± 0.67, 20.67 ± 0.58, and 24.30 ± 1.41, respectively) compared to the control group ($p \leq 0.05$). However, the induction + DRBH group showed a significant increase in the thickness compared to the induction group ($p \leq 0.05$). These results implicated that DRB might restore mucus layer thickness in the AOM/DSS-induced colitis-associated CRC rats related to goblet cell formation. ## 3.3. DRB Supplementation Modulated the Composition of Gut Microbiota in AOM/DSS-Induced Colitis-Associated CRC Rats To investigate the effect of DRB on gut microbiota changes in AOM/DSS-induced colitis-associated CRC rats, 16s rRNA genes at V3–V4 regions amplified from colonic luminal content (feces), mucosa and tumor were sequenced by using Illumina sequencing. A total of 2,654,123 sequences from 66 samples in feces were generated after quality filtering steps, with an average of 40,213 sequences per sample (ranging from 2365 to 84,982 sequences). In mucosa and tumor, a total of 1,608,742 sequences from 50 samples (33 samples in mucosa and 17 samples in tumor) were generated after quality filtering steps, with an average of 30,937 sequences per sample (ranging from 9064 to 93,018 sequences). Then, after removing low-quality sequences at a quality score of 20, high-quality sequences were selected and clustered into 611 features in feces, and 898 features in mucosa and tumor of amplicon sequence variants (ASVs) processed with the QIIME 2 pipeline. ## 3.3.1. Alpha Diversity The rare fraction curves of alpha diversity measures reached a plateau, indicating that the sequencing depth was appropriate, and represented most of the community in the sample (Figure S1). The alpha diversity analysis was used to measure the richness and evenness within microbial communities using Pielou’s evenness, Faith’s phylogenetic diversity, Observed OTUs, and Shannon diversity index. Pielou’s evenness index represented the evenness within microbial communities. In contrast, Faith’s phylogenetic diversity and Observed OTUs index represented the richness within microbial communities, and the Shannon diversity index represented evenness and richness within microbial communities. Compared to the control group, the alpha diversity analysis in feces (Figure 4) showed a significant increase in the microbial alpha diversity only in the DRBH group according to Pielou’s evenness and Shannon diversity index ($p \leq 0.05$). These results specified that the microbial alpha diversity in feces did not change in the AOM/DSS-induced rats. However, DRBH supplementation increased the evenness and richness of microbial diversity within communities in feces. In addition, the alpha diversity in the tumor (Figure 5) showed a significant decrease in the induction, induction + DRBL, and induction + DRBH groups compared to the control and the induction group in mucosa according to the Pielou’s evenness and Shannon diversity index ($p \leq 0.05$). Contrarily, only the induction + DRBH group showed a significant decrease in the alpha diversity in tumor compared to the control group and the induction group in mucosa according to Faith’s phylogenetic diversity and Observed OTUs index ($p \leq 0.05$). However, the alpha diversity among experimental groups within mucosa and tumor showed no significant difference. These results implicated that the AOM/DSS-induced colitis-associated CRC decreased the microbial alpha diversity in tumors compared to the mucosa. However, DRB supplementation did not affect the microbial alpha diversity in mucosa and tumor. ## 3.3.2. Beta Diversity The beta diversity was used to determine the similarities and differences in the composition structure of microbial communities using the Bray–Curtis dissimilarity, Jaccard index, and weighted and un-weighted UniFac distance. The beta diversity analysis in feces (Figure 6) and in mucosa and tumor (Figure 7) showed a significant difference among the experimental groups according to the Bray–Curtis and Jaccard index. On the contrary, the weighted and un-weighted UniFac distance showed no significant difference in microbial beta diversity among the experimental groups in feces, although in colonic mucosa and tumor, it showed a significant difference for weighted and un-weighted UniFac distance. The results above demonstrated that microbial communities’ composition structure in feces, colonic mucosa, and tumor was differed among the experimental groups using the Bray–Curtis and Jaccard index analysis. ## 3.3.3. Bacterial Taxonomic Composition The relative abundance of bacterial taxa in colonic feces, mucosa, and tumor at the phylum, family, and genus levels were analyzed. The taxonomic composition at the phylum level in feces is shown in Figure 8A. Firmicutes, Verrucomicrobia, Bacteroidetes, Actinobacteria, Proteobacteria, and Patescibacteria were the major phyla in the six experimental groups. Among them, Firmicutes, Verrucomicrobia, and Bacteroidetes were the most abundant phyla. Compared to the control and induction group, the relative abundance of Firmicutes was increased, and Verrucomicrobia was decreased in DRB supplemented groups, although the level of Bacteroidetes in feces was higher in the DRBH group than in the control group (Table S4). Figure 8B shows the family level taxonomic composition. A total of 14 families with a relative abundance of more than $1\%$ in at least one group were identified from the six experimental groups (Table S5). In contrast to the control group, the induction group decreased the relative abundance of Lactobacillaceae and Ruminococcaceae, and increased the levels of Erysipelotrichaceae, and Clostridiaceae, respectively. However, the induction + DRBL and induction + DRBH groups increased the relative abundance of Lactobacillaceae and Ruminococcaceae. They decreased the levels of Erysipelotrichaceae and Clostridiaceae compared to the induction group. Moreover, the DRBL and DRBH groups increased the quantity of Lachnospiraceae, Ruminococcaceae, and Prevotellaceae. Conversely, compared to the control and induction group, the DRB supplemented groups showed a decrease in the level of Akkermansiaceae. The taxonomic composition at the genus level in feces was presented in Figure 8C. Akkermansia, Romboutsia, Lactobacillus, and Muribaculaceae were the major bacterial genera in feces. Table S6 shows the enriched bacterial genera in the DRB groups and in the induction groups. On the other hand, DRBL and DRBH groups revealed the increased relative abundance of Prevotellaceae UGC-001, Roseburia, and Ruminococcaceae compared to the control group. Furthermore, the DRBH group exhibited increased levels of Alloprevotella, Butyricicoccus, and Ruminococcus compared to the control group. On the contrary, the induction group has a high relative abundance of Turicibacter, Clostridium sensu stricto 1, Enterococcus, Escherichia–Shigella, and Citrobacter, respectively. Nevertheless, the induction + DRBL and induction + DRBH groups increased the levels of these bacterial in feces. As shown in Figure 8D, the taxonomic composition at the phylum level in colonic mucosa and tumor of the colon mainly consists of Firmicutes, Bacteroidetes, Verrucomicrobia, Proteobacteria, Actinobacteria, and Patescibacteria phyla. Firmicutes, Bacteroidetes, and Verrucomicrobia were primarily found in the mucosa, while the abundance of Firmicutes, Proteobacteria, and Bacteroidetes was found in tumor (Table S7). The induction group manifested a reduced relative abundance of Bacteroidetes in the mucosa, while Firmicutes and Bacteroidetes were diminished in tumors compared to the control group. In addition, the relative abundance of Proteobacteria was highly boosted in mucosa and tumor of the induction group. However, the induction + DRBL and induction + DRBH groups enhanced the relative abundance of Firmicutes and Bacteroidetes. They reduced the Proteobacteria phyla in mucosa and tumor compared to the induction group. Furthermore, in the mucosa of the DRBL group, the relative abundance of Verrucomicrobia was increased. The taxonomic composition at the family level is shown in Figure 8E. A total of 15 families with a relative abundance of more than $1\%$ in at least one group were identified (Table S8). Compared with mucosa, induction group decreased the relative abundance of bacteria in the tumor, except Lactobacillaceae and Caulobacteraceae, which were found in sufficient amounts in tumor. However, the induction + DRBL and induction + DRBH groups displayed a reduced relative abundance of Caulobacteraceae in tumors compared to the induction group, which manifested a decrease in Muribaculaceae, Ruminococcaceae, Lactobacillaceae, Prevotellaceae, Eggerthellaceae, and Burkholderiaceae bacterial in mucosa compared to the control group. At the same time, Clostridiaceae 1 and Bacteroidaceae were increased. However, the induction + DRBL and induction + DRBH groups increased the relative abundance of Ruminococcaceae, Lactobacillaceae, Prevotellaceae, and Eggerthellaceae in the mucosa and reduced the levels of Clostridiaceae 1. Furthermore, the relative abundance of Akkermansiaceae was increased in the mucosa of the DRBL group, and the level of Prevotellaceae was increased in the mucosa of the DRBH group compared to the control group. At the genus level, Lactobacillus, Akkermansia, Enterococcus, Romboutsia, and Escherichia–Shigella have a significant abundance in mucosa and tumor of the colon (Figure 8F). Table S9 shows the enriched bacterial genera in the DRB and induction groups. Compared to the control group, the DRBL, and DRBH groups increased the relative abundance of Prevotellaceae UCG-001, Roseburia, and Ruminococcus in the mucosa. Moreover, the DRBL group increased the levels of Akkermansia in mucosa compared to the control group. Induction + DRBL and induction + DRBH groups increased the relative abundance of Alloprevotella, Butyricicoccus, Lactobacillus, Prevotellaceae UCG-001, and Ruminococcus in mucosa. They raised the levels of Lactobacillus and Prevotellaceae UCG-001 in tumors compared to the induction group. Alternatively, the relative abundance of Enterococcus, Escherichia–Shigella, Citrobacter, Clostridium sensu stricto 1, and Mycobacterium in the mucosa, and Citrobacter, Escherichia–Shigella, and Mycobacterium in the tumor were increased in the induction group compared to the control group. Nevertheless, the induction + DRBL and induction + DRBH groups reduced the levels of Escherichia–Shigella, Citrobacter, Clostridium sensu stricto 1, and Mycobacterium in mucosa and tumor. These results demonstrated that the bacterial taxonomic profile in feces, mucosa, and tumor was distinct from one another in this model. At the same time, DRB supplementation could alter the gut microbial composition in colonic feces, mucosa, and tumor. ## 3.3.4. Bacterial Biomarkers The linear discriminant analysis (LDA) effect size (LEfSe) analysis with significant differences in the bacterial genus in feces among groups is shown in Figure 9A. The LEfSe analysis showed that the DRBL group significantly increased the relative abundance of Romboutsia with a significant difference in LDA score (>4). The DRBH group has an abundance of three taxa, including Ruminiclostridium 9, Ruminococcus 1, and Lachnospiraceae NK4B4 group, with a significant difference in LDA score (≥3). In the induction group, the relative abundance of Clostridium sensu stricto 1, Caldicoprobacter, and Enterococcus was significantly increased with an LDA score of ≥3. Similarly, while induction + DRBL group showed a remarkable increase in the relative abundance of Ruminococcaceae UCG 009 with an LDA score of ≥3. The LEfSe analysis of bacterial genus in colonic mucosa and tumor (Figure 9B) showed that the control group significantly increased the relative abundance of 19 taxa in the mucosa. Among these, Ruminococcus 2, bacterial belonging to Muribaculaceae and Lachnospiraceae, and unassigned taxa from Muribaculaceae showed a significant difference in LDA score (≥4). The DRBL group revealed a significant increase in the relative abundance of 12 taxa. Among these, Akkermansia, Romboutsia, and Clostridium sensu stricto 1 exhibited a significant difference in LDA score (≥4). The DRBH group showed a notable increase in the relative abundance of 13 taxa in the mucosa. Alloprevotella, Ruminiclos-tridium 9, and some uncultured genera belonging to Muribaculaceae and Lachnospiracoccaceae showed a remarkable difference in LDA score of ≥4. A significant difference in the abundance of 3 taxa in the mucosa was found in the AOM/DSS group. There were Blautia, Angelakisella, and ASF356 from Lachnospiraceae with a significant difference at LDA score ≥3. In the induction + DRBL group, the relative abundance of Turicibacter, Bacteroidales bacterium, BB60 group unassigned taxa, and Candidatus Saccharimonas in the mucosa was significantly increased with an LDA score of ≥3. Similarly, induction + DRBH group showed an increase in the relative abundance of Lachnospiraceae NK4A136 group, Bacteroides, and Prevotellaceae UCG 001 in mucosa with an LDA score of ≥3. In the tumor, the induction group showed that the relative abundance of Enterococcus, Escherichia–Shigella, and Proteus, significantly increased with an LDA score of ≥3. In addition, the relative abundance of seven taxa of the induction + DRBH group in the tumor was significantly increased, including Citrobacter, Brevundimonas, bacterial genera belonging to Enterobacteriaceae, Mycobacterium, Mythylobacerium, Streptomyces, and Bosea with an LDA score of ≥3. ## 3.4. DRB Supplementation Increased Cecal Short-Chain Fatty Acids (SCFAs) Production in AOM/DSS-Induced Colitis-Associated CRC Rats The quantity of SCFAs in cecal contents in each experimental group is shown in Figure 10. Highest amount of acetic acid was observed in cecal contents, followed by propionic acid and butyric acid. The concentration of cecal acetic acid in control, DRBL, DRBH, induction, induction + DRBL, and induction + DRBH groups was found to be 19.50 ± 0.56, 20.12 ± 0.86, 18.74 ± 0.60, 12.83 ± 0.41, 16.80 ± 0.64, and 17.16 ± 0.51 mmol/kg wet sample, respectively. The induction group showed a significant decrease in acetic acid concentration compared to the control group ($p \leq 0.05$). Furthermore, the induction + DRBL and induction + DRBH groups were significantly higher in the acetic acid concentration than the induction group ($p \leq 0.05$). Likewise, the concentration of cecal propionic acid in control, DRBL, DRBH, induction, induction + DRBL, and induction + DRBH group were noted to be 6.18 ± 0.12, 6.47 ± 0.40, 6.23 ± 0.11, 5.20 ± 0.15, 6.08 ± 0.19, and 5.96 ± 0.10 mmol/kg wet sample, respectively. The concentration of propionic acid in the induction group was significantly decreased compared to the control group ($p \leq 0.05$). Moreover, the propionic acid concentration in the induction + DRBL and induction + DRBH groups tend to increase compared to the induction group. Compared to the induction group, the propionic acid concentration in the induction + DRBL and induction + DRBH group showed no significant difference. For the cecal butyric acid, the concentration of control, DRBL, DRBH, induction, induction + DRBL, and induction + DRBH group were determined to be 5.85 ± 0.10, 6.00 ± 0.33, 5.75 ± 0.24, 4.89 ± 0.12, 5.68 ± 0.17, and 5.60 ± 0.28 mmol/kg wet sample, respectively. The butyric acid in the induction group was significantly reduced compared to the control group ($p \leq 0.05$). In the induction + DRBL g and induction + DRBH groups, the propionic acid tends to elevate compared to the induction group. However, both groups showed no significant difference in the butyric acid concentration compared to the induction group. These results demonstrated that DRB intake tends to increase the production of SCFAs in the cecal, especially acetic acid, propionic acid, and butyric acid in the AOM/DSS-induced rats. ## 4. Discussion Our previous investigations demonstrated that DRB have a substantial amount of dietary fiber [26]. The degradation and fermentation of these dietary fibers by bacterial enzymes produce short-chain fatty acids (SCFAs), which serve as an energy source for colonocytes and maintain intestinal homeostasis [27]. It is well known that the administration of DSS induces gut microbiota dysbiosis. Thus, we hypothesize that DRB could improve the gut microbiota in AOM/DSS-induced colitis-associated CRC model. We observed the gut microbiota communities in colonic feces, mucosa, and tumor. From the beta diversity analysis, it was noticed that DRB changes the gut microbiota profiles in feces, mucosa, and tumor. Conversely, the alpha diversity results showed that DRB did not affect the gut microbial community in mucosa and tumor. However, DRB tends to increase alpha diversity in feces. Analysis of taxonomic levels showed that Firmicutes, Bacteroidetes, Actinobacteria, Verrucomicrobiota, and Proteobacteria were the dominant phyla in feces, mucosa, and tumor, which follows the previous studies [28], although the bacterial taxa genus in feces, mucus, and tumors were distinct from one another in this model. In the present study, we determined that DRB could regulate gut microbiota composition in AOM/DSS-induced colitis-associated CRC rat model. At the phylum level, the relative abundance of Proteobacteria was increased in mucosa and tumor of the induction group. At the same time, it was lessened in the induction + DRBL and induction + DRBH groups, respectively. Proteobacteria are intestinal pathogens (harmful bacteria) that can cause inflammation and promote inflammation bowel disease (IBD) and CRC development and progression [29]. In addition, Proteobacteria was found enriched in IBD and CRC patients and AOM/DSS-induced–colitis-associated CRC mice model [30,31]. Correspondingly, the genus of Escherichia–Shigella and Citrobacter belonged to the Proteobacteria phylum and were found in abundance in the feces, mucosa, and tumor of the induction group. Still, it was decreased in the induction + DRBL and induction + DRBH groups. Escherichia–Shigella is (Gram-negative bacteria), primarily found in the gut microbiota of CRC patients, might progress the tumor formation [32]. Likewise, Citrobacter infection could induce immune-mediated responses and inflammation on Wnt signaling, which leads to CRC development [33]. Additionally, we determined that DRB suppressed the increase in the abundance of Turicibacter, Clostridium sensu stricto 1, and Enterococcus in the feces and Clostridium sensu stricto 1 in the mucosa in AOM/DSS-induced rats. At the same time, Mycobacterium were decreased in the mucosa and tumor. These bacteria (Turicibacter, Clostridium sensu stricto 1, Enterococcus, Mycobacterium) are well recognized to associate with CRC development through potential mechanisms including promoting chronic inflammation, DNA damage, and the production of bioactive carcinogenic metabolites, which were increased in animal models of colitis and CRC patients [34,35,36]. In addition, we established that DRB increased the relative abundance of Alloprevotella, Prevotellaceae UCG-001, Ruminococcaceae, Ruminococcus, Butyricicoccus, and Roseburia in the feces of normal rats, while the relative abundance of Lactobacillus, Alloprevotella, Prevotellaceae UCG-001, Ruminococcus, Ruminococcaceae, and Butyricicoccus were increased in AOM/DSS-induced rats with DRB supplementation. In mucosa, we observed that DRB increased Prevotellaceae UCG-001, Roseburia, Ruminococcus in normal rats. In contrast, the levels of Lactobacillus, Alloprevotella, Prevotellaceae UCG-001, and Ruminococcus, and Butyricicoccus were increased in AOM/DSS-induced rats with DRB supplementation. In tumor, the results showed that DRB raised the Lactobacillus and Prevotellaceae UCG-001 levels in AOM/DSS-induced rats. These bacteria, as mentioned above, are associated with high dietary fiber consumption. Dietary fiber is degraded to monosaccharides by fiber-degrading bacteria (Alloprevotella and Prevotellaceae) [37], which enter the cytosol and then fermented into SCFAs by SCFA-producing bacteria (Butyricicoccus, Ruminococcus, Roseburia, Coprococcus, Eubacterium, and Lactobacillus) [37]. Previous reports illustrated that the main bacteria phyla responsible for the degradation of dietary fiber are Bacteroidetes and Firmicutes [38]. Soluble fiber (e.g., pectin, gums, β-glucans, inulin) can be degraded in the ileum and ascending colon. In contrast, insoluble fiber (e.g., cellulose and hemicellulose) is exclusively fermented in the distal colon [38]. Insoluble fiber intake boosts the relative abundance of Bacteroidetes, Euryarchaeota, and Ruminococcaceae, together with Prevotella, Phascolarctobacterium, and Coprococcus at the genus level. On the other hand, intake of soluble fiber results in a higher relative abundance of the phylum Proteobacteria and a lower abundance of Prevotellaceae, along with higher bacterial genera, including Blautia, Solobacterium, Syntrophococcus, Weissella, Olsenella, Atopobium, and Succinivibrio [38]. Therefore, these results might be due to the high dietary fiber content (especially insoluble fiber) in DRB, which may lead to boost the abundance of fiber-degrading and SCFA-producing bacteria. Alloprevotella is a fiber-degrading bacterium that plays an essential role in maintaining intestinal homeostasis and is believed to promote healthy gut microbiota in the host [39]. Prevotellaceae UCG-001 is identified as a probiotic that supports IgA secretion and butyrate production for inhibiting inflammation [40]. A substantial decrease in the abundance of Butyricicoccus and Ruminococcus (Ruminococcaceae family; butyrate-producing bacterium) was observed in inflammatory bowel disease (IBD) fecal microbiota, which in turn improves the clinical outcome of CRC [41]. Roseburia (Lachnospiraceae family) produces a significant amount of butyrate from dietary carbohydrate fermentation and may be necessary to control inflammatory processes in the gut [42]. Lactobacillus, considered a probiotic, produces anti-microbial substances for inhibiting the growth of bacterial pathogens in the intestinal lumen, thus preventing dysbiosis and the development of CRC [43]. These bacteria were considered an anti-inflammatory factor due to their metabolite products, such as SCFAs (especially butyrate), a major energy source of colonocytes and display anti-inflammatory properties [44]. Interestingly, Akkermansia is a mucus-degrading bacterium (phylum Verrucomicrobia), colonized in the mucus layer, which is associated with mucus barrier function due to its ability to degrade mucin [45]. Furthermore, Akkermansia is related to high phenolic compound intake [46]. Previous studies have shown that Akkermansia was inversely correlated with diabetes, obesity, and other diseases [47]. In contrast, other studies suggested that Akkermansia might promote CRC development, since Akkermansia can degrade mucin, damage the mucus barrier, thus leading to the bacterial invasion of epithelial cells, and stimulate immune responses that drive intestinal inflammation and CRC development [48]. Therefore, the health-beneficial and disease-promoting properties of Akkermansia have been further investigated. Therefore, these results indicated that DRB inhibited the AOM/DSS-induced colitis-associated CRC by promoting the fiber-degrading and SCFAs-producing bacteria and inhibiting the production of bacterial pathogens that alleviate the progression of CRC, thus maintaining the mucus barrier in the colon. These findings are consistent with the previous studies reported by Huan et al. The results demonstrated that defatted rice bran (DFRB) as a replacement for corns increased the intestinal wall’s thickness, Bifidobacterium and Lactobacillus levels, and decreased the level of Escherichia coli and Clostridium perfringens in the small and large intestine of finishing pigs [11]. Sheflin et al. reported that the consumption of heat-stabilized rice bran (SRB) 30 g/day for 28 days in healthy adults increased the Bifidobacterium and Ruminococcus genera and branched chain fatty acids after two and four weeks of SRB consumption [22]. Another study showed that the Bifidobacterium longum-fermented, and the non-fermented rice bran increased the abundance of Roseburia, Lachnospiraceae, and Clostridiales in the cecum and colon microbiomes in mice [49]. Parker et al. demonstrated that rice bran-modified human fecal microbiota transplantation (FMT) in AOM/DSS-treated mice decreases the neoplastic lesions in the colon. Moreover, it increases the levels of Flavonifractor and Oscillibacter (correlated with colon health) and reduces the levels of Parabacteroides distasonis associated with increased tumor burden [50]. In addition, in our previous study, we determined that DRB has high phenolic acids, which also contribute to intestinal bacteria [26]. These compounds have the property to promote the growth of Bidifobacteria, such as Faecalibacterium prausnitzii, Lactobacillus sp., and Akkermansia muciniphila, respectively [46]. The findings suggested that hydrolyzed bound phenolics (HBP) from rice bran supplementation improved the gut microbiota dysbiosis in high-fat diet-induced mice, which increased the relative abundance of Bacteroides, Rikenellaceae, Allobaculum, Faecalibaculum, and decreased the relative abundance of Alistipes, Odoribacter, Butyricimonas, Parabacteroides, Romboutsia, Ruminiclostridium 9, Lachnospiraceae, and Erysipelotrichaceae, respectively [51]. The significant findings highlighted that DRB promoted the enrichment of fiber-degrading bacteria, SCFA-producing bacteria, and subsequent production of SCFAs. The Bacteroidetes phylum mainly produces acetate (Akkermansia, Bacteroides, Prevotella, Bifidobacterium, Ruminococcus, Clostridium, Streptococcus, Blautia, Coprococcus) and propionate (Dialister, Bacteroides, Coprococcus, Roseburia, Veillonella, Anaerostipes). In contrast, the Firmicutes phylum (Roseburia, Eubacterium, Coprococcus, Ruminococcus, Clostridium, Anaerostipes) produces butyrate [19]. Herein, we measured the SCFAs, including acetate, propionate, and butyrate in the cecum, a major fermentation site in the rat. The results showed that the concentration of these SCFAs was reduced in the induction group compared to the control group. Moreover, SCFAs were higher in the induction + DRBL and induction + DRBH groups than in the induction group. These results suggested that DRB elevated the production of acetate, propionate, and butyrate in the cecum in AOM/DSS-induced rat model. The increased SCFAs in the study might be due to dietary fiber, a significant component in DRB. The increased production of SCFAs in the cecum of the induction + DRBL and induction + DRBH groups was correlated with the increase in the SCFAs-producing bacteria, including Ruminococcus, Butyricicoccus, and Roseburia, respectively. Furthermore, the increased SCFA production in the induction + DRBL and induction + DRBH groups was related to the decrease in pro-inflammatory markers, including TNF-α, IL-6, NF-κB, and COX-2, together with the reduction in the number of aberrant crypt foci (ACFs), and tumor formation in the colon in our previous study [26]. This is in line with the previous study that showed enzyme-treated rice fiber increased SCFAs (acetate, propionate, and butyrate) contents in the cecum and reduced inflammatory cytokines (TNF-α, IL-4, IFN-γ, IL-1β, IL-6, and IL-12p70) in serum and mucosal in DSS-induced rat [52]. Another study showed that fermented rice bran decreased the pro-inflammatory cytokine transcript levels (TNF-α, IL-1β, IL-6, and IL-17) and inflammatory cell infiltration in the colon tissue. In addition, it elevated the SCFAs production in the feces and colon and Mucin-2 (Muc2) mRNA levels in the colon in colitis mice [53]. Additionally, we investigated the effects of DRB on goblet cell loss and mucus layer thickness in the colon tissue. Previous research illustrated that the administration of DSS decreased the mucus layer thickness and increased mucus permeability in the colon, resulting in easy bacterial penetration in the inner mucus layer, which reaches the epithelial cells [54]. Bacterial invasion activates immune cell infiltration and accelerates colitis and colon cancer development. Chronic inflammation in the colon displays epithelial erosions, goblet cell depletion, crypt architectural distortion (such as shortening and loss), and mucosal fibrosis [55]. Goblet cells secrete mucin to cover the mucosal surfaces with a mucus layer lining that separates the intestinal epithelium from the lumen cavity [56,57,58]. In colonic inflammation, the epithelial cell alteration and goblet cell differentiation result in goblet cell depletion and Muc2 synthesis reductions. Correspondingly, our results showed that goblet cell depletion was found in the induction, induction + DRBL, and induction + DRBH groups compared to the control group. However, the induction + DRBL and induction + DRBH groups reduced goblet cell loss compared to the induction group. Therefore, DRB supplementation might prevent the goblet cell loss in AOM/DSS-induced rat model. As mentioned above, the colonic mucus layer relates to goblet cells. The colonic mucus is composed of mucins (especially mucin 2) that are glycoproteins with specific O-linked glycans (O-glycans) produced by goblet cells [59,60]. The mucus layer is a part of the innate mucosal barrier, acting as the first line of immunological defense against mechanical, chemical, and pathogenic microorganism attacks and contributing to maintaining intestinal homeostasis [61]. Moreover, the mucus can lubricate the epithelial surface and cover the fecal pellet to separate bacteria from epithelium and feces. The mucus layer provides nutrients and attachment sites for bacteria [61]. Several studies suggested colonic inflammation is associated with mucus layer disruption, goblet cell depletion, and reduced Muc2 synthesis [58]. Similarly, our results showed that the mucus layer thickness was reduced in the induction, induction + DRBL, and induction + DRBH groups compared to the control group. However, the induction + DRBL and induction + DRBH groups increased the mucus layer thickness compared to the induction group. Therefore, DRB supplementation might improve the mucus layer disruption in AOM/DSS-induced rat model. This might be due to the DRB, which is a high dietary fiber. Dietary fiber is made of indigestible polysaccharides, and digestive enzymes cannot break them. Thus, dietary fiber is fermented and degraded by bacteria in the colon to produce the metabolite products such as SCFAs that enter the colonic epithelial cells (colonocytes) for their use as energy. SCFAs are oxidized through the β-oxidation pathway to generate carbon dioxide (CO2), which could be converted into bicarbonate (HCO3−) by carbonic anhydrase. This process promotes the stratification of the mucus layers, such as the unfolding of mucin and the resultant inner mucus layer converse to the outer layer and mucin to form a net-like structure [62]. Thus, the thickness of the mucus layer was correlated with the SCFA. There was evidence to confirm that dietary fiber is involved in increasing the thickness of the mucus layer. Desai et al. demonstrated that in mice fed a fiber-free diet, the colonic mucus layer thickness decreased and mucus layer susceptibility to bacterial pathogens increased [63]. Huawei et al. reported that the supplementation with soluble dietary fiber in a murine model of sepsis established by cecal ligation and puncture (CLP) significantly increased the mucus layer thickness and Muc2 expression in colon tissue [64]. Another study by Iain et al. found that rats fed with a fiber deficiency diet decreased the mucus layer thickness and reduced total mucus secretion over 6 h. In comparison, in rats fed with different soluble and insoluble fiber types in their diet, the mucus layer thickness and total mucus secretion over 6 h increased [65]. ## 5. Conclusions Our study showed that the AOM/DSS-induced colitis-associated CRC model altered gut microbiota composition in colonic feces, mucosa, and tumors and also reduced cecal SCFAs production, number of goblet cells, and thickness of mucus layer, while DRB supplementation modulated the gut microbiota dysbiosis by promoting the enrichment of healthy bacteria, including fiber-degrading bacteria and SCFA-producing bacteria. Subsequently, it helps reduce the abundance of harmful bacteria and stimulates the production of SCFAs. Furthermore, DRB supplementation restored goblet cell loss and improved mucus layer thickness. 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--- title: 'Monitoring of Diabetes Mellitus Using the Flash Glucose Monitoring System: The Owners’ Point of View' authors: - Mariachiara Re - Francesca Del Baldo - Antonio Maria Tardo - Federico Fracassi journal: Veterinary Sciences year: 2023 pmcid: PMC10052096 doi: 10.3390/vetsci10030203 license: CC BY 4.0 --- # Monitoring of Diabetes Mellitus Using the Flash Glucose Monitoring System: The Owners’ Point of View ## Abstract ### Simple Summary The flash glucose monitoring system has recently become one of the most common monitoring methods in diabetic dogs and cats. The aim of this study was to evaluate the impact of the flash glucose monitoring system on diabetic pet owners’ quality of life and the satisfaction related to its usability. Fifty diabetic pet owners who used at least one flash glucose monitoring system on their diabetic pet were asked to answer a 30-question survey. A total of $92\%$ of diabetic pet owners reported that their pet had better diabetes control since using the device, while the most challenging aspects were ensuring proper sensor fixation during the wearing period and preventing premature detachment and costs related to its long-term use. In conclusion, the flash glucose monitoring system is considered by diabetic pet owners to be easy to use and less stressful compared to blood glucose curves, while also enabling better glycemic control. Nevertheless, costs related to its long-term use might be difficult to sustain. ### Abstract The flash glucose monitoring system (FGMS) has recently become one of the most common monitoring methods in dogs and cats with diabetes mellitus. The aim of this study was to evaluate the impact of FGMS on the quality of life of diabetic pet owners (DPOs). Fifty DPOs were asked to answer a 30-question survey. More than $80\%$ of DPOs considered FGMS easier to use and less stressful and painful for the animal compared to blood glucose curves (BGCs). Overall, $92\%$ of DPOs reported that their pet had better diabetes control since using FGMS. The most challenging aspects of using the FGMS were ensuring proper sensor fixation during the wearing period ($47\%$), preventing premature detachment ($40\%$), and purchasing the sensor ($34\%$). Moreover, $36\%$ of DPOs reported that the device cost was difficult to afford in the long term. Comparing dogs and cats, a significantly higher number of dogs’ owners found the FGMS to be well-tolerated ($79\%$ vs. $40\%$), less invasive than BGCs ($79\%$ vs. $43\%$), and easier to maintain in situ ($76\%$ vs. $43\%$). In conclusion, FGMS is considered by DPOs to be easy to use and less stressful compared to BGCs, while enabling better glycemic control. Nevertheless, the costs related to its long-term use might be difficult to sustain. ## 1. Introduction Dogs and cats with diabetes mellitus (DM) are frequently treated with exogenous insulin and a specific diet and require regular monitoring to ensure appropriate dosing [1]. In recent years, glucose monitoring has been revolutionized by the advent of continuous glucose monitoring systems (CGMSs). According to the author’s experience, these systems are progressively replacing the use of blood glucose curves (BGCs) and are nowadays one of the most widely used monitoring methods for diabetic pets. The FreeStyle Libre® flash glucose monitoring system (FGMS, Abbott Laboratories Ltd., Chicago, IL, USA) is a commonly used CGMS, thanks to its easy-to-use and long sensor lifespan. This device measures interstitial glucose (IG) concentration, which correlates well with blood glucose (BG) [2,3]. However, a lag time occurs between changes in BG and IG, and the latter also is affected by local factors specific to the tissue in which it is measured [4,5]. In dogs, the FGMS provides detailed IG profiles, allowing for the more accurate detection of nadir and hypoglycemic episodes as compared to BGCs generated by a portable blood glucose meter (PBGM) [6]. It also allows for the detailed identification of the glycemic excursions occurring throughout the day or on different days [7]. In veterinary medicine, it is generally accepted that owner compliance is essential for successfully treating DM [8]. The disease and the treatment commitments are likely to have a considerable impact on owners’ daily routines and quality of life (QoL) and might represent a significant temporal, financial, and emotional burden. In support of this, a recent study showed that more than $30\%$ of diabetic pet owners (DPOs) euthanize their pets due to the negative impact of DM management on their lifestyle [8]. For this reason, it is crucial to consider the impact of DM management and of the different monitoring methods on the QoL of DPOs. In veterinary medicine, the impact of a particular monitoring method on the QoL of DPOs has rarely been investigated. In one study, the use of home blood glucose monitoring was associated with positive changes in the QoL parameters of cats and their owners and significant glycemic improvements [9]. In two recent studies, DPOs were asked to complete a questionnaire regarding their experience with the FGMS [10,11], while a third one has evaluated owner satisfaction with the use of an FGMS through a questionnaire containing 16 yes-or-no questions [12]. The FGMS was considered to be easy to use by DPOs and provided great satisfaction [10,11,12]. Moreover, in human medicine, the use of an FGMS positively influences the QoL of diabetic patients since it significantly reduces the risk of hypoglycemic episodes, which negatively impact the QoL of diabetic patients [13]. Despite the fact that the convenience of the use of an FGMS has been sporadically addressed in previous canine and feline studies, no studies have evaluated the impact on the QoL associated with the use of an FGMS on DPOs. Therefore, the aim of this study was to investigate the impact of an FGMS on diabetic pet owners’ QoL and the satisfaction related to its usability. ## 2.1. Participants and Questionnaire Diabetic pet owners whose animals were admitted to the Veterinary Teaching Hospital of the University of Bologna from July 2021 to September 2022 were asked to complete an online survey (Google Form, https://forms.gle/GHT2y6J1FTzKmwaX6, accessed on 1 December 2022). Owners were considered to be eligible for inclusion in the study if they had used at least one FGMS. The survey was made up of thirty questions, including multiple-choice (M) questions ($\frac{5}{30}$), single-option questions (S) ($\frac{20}{30}$), and free-text statements (F) ($\frac{5}{30}$). The survey was divided into three categories: [1] questions related to the technical use of the FGMS (Table 1), [2] a comparison between the use of an FGMS and the generation of BGCs (Table 2), and [3] the impact of an FGMS on diabetic pets and the QoL of DPOs (Table 3). ## 2.2. FGMS The FGMS used by the owners was FreeStyle Libre Abbott®. This device is available online via the manufacturer’s official website. Its technical features and the application procedures have been described in previous studies [5,14]. Scanning using the sensor needs to be carried out at least every 8 h; it automatically records the IG values every fifteen minutes. The IG trends are transferred from the sensor to a reader when the user brings the handheld reader into close proximity to the sensor. The FreeStyle Libre Link® mobile app can be used as an alternative to the reader. The reader stores the data for 90 days, and, if the scans are performed using the FreeStyle Libre Link® app (software version 2.8.1.6120, Abbott Laboratories Ltd., Chicago, IL, USA), the glucose values are automatically uploaded to Libreview® (https://www.libreview.com, accessed on 1 December 2022) when the phone is connected to the Internet. Libreview® is a free, secure, cloud-based diabetes management system provided by Abbott. The system generates summary glucose reports from the uploaded sensor data, readily available for consultation by healthcare providers. The report provides a graphical trace of the glucose values of a 24 h period, allowing access to previous glucose data. ## 2.3. Statistical Analysis Statistical analysis was carried out using a commercially available software program (MedCalc Software Ltd., Ostend, Belgium, version 20.121). Owing to the small number of cases, the continuous variables were considered to be non-parametric, and descriptive statistics were reported as a median (minimum–maximum). The categorical variables were reported as frequencies, proportions, or percentages. The differences between dog and cat DPOs regarding the tolerability of the sensor, impact on glycemic control, stress degree related to the monitoring methods (FGMS vs. BGCs), and problems related to premature sensor detachment were compared using the Fisher’s exact test. Values of $p \leq 0.05$ were considered significant. ## 3.1. Technical Use of the FGMS Fifty DPOs were enrolled in the study. Of them, $\frac{29}{50}$ ($58\%$) were dog owners and $\frac{21}{50}$ ($42\%$) were cat owners. The median (range) number of FGMSs used by each DPO was 4 (1–10). The number of FGMS used by each DPO was 1 in 5 cases, 2–5 in 29 cases, 6–9 in 7 cases, and 10 or more in 9 cases. Forty-two percent of DPOs reported a premature end of the sensor within 24 h of placement due to early detachment or malfunctioning. Of them, $\frac{24}{21}$ ($76\%$) were dog owners and $\frac{16}{21}$ ($76\%$) were cat owners. Among DPOs who used only one sensor, no one reported an early detachment on the first day of use. The use of the FGMS was proposed to the DPOs by a referral center ($\frac{31}{50}$, $62\%$), was recommended by the primary care veterinarian ($\frac{10}{50}$, $20\%$), or was discovered by the owners themselves ($\frac{9}{50}$, $18\%$). Forty-three percent of the DPOs understood how to use the sensor, based only on the instructions provided by the veterinarian. In contrast, $14\%$ of them ($\frac{28}{50}$) had to find more information on the Internet regarding its use (e.g., sensor manufacturer’s website, Youtube® videos, and online forums). In $58\%$ ($\frac{29}{50}$) of cases, the FGMS was placed exclusively by the veterinarian, while, in $42\%$ ($\frac{21}{50}$) of the DPOs ($68\%$ of dog owners, $\frac{14}{21}$; and $32\%$ of cat owners, $\frac{7}{21}$), it was placed by the owner. A total of $68\%$ ($\frac{34}{50}$) of DPOs ($70\%$ cat owners, $\frac{24}{34}$; and $30\%$ dog owners, $\frac{10}{34}$) reported that additional glue was necessary to better fix the sensor onto the skin. Of these, $26\%$ ($\frac{9}{34}$) used a liquid medical adhesive, and $74\%$ ($\frac{25}{34}$) used a cyanoacrylate glue. Moreover, in $88\%$ of cases ($\frac{44}{50}$), the sensor was protected with an additional bandage (cotton and elastic bandage). The sensor lifespan reported by the manufacturer (14 days) was reached in $20\%$ of cases. The most widely used application area of the sensor was the dorsal aspect of the neck ($78\%$ of cases, $\frac{39}{50}$), followed by the dorsum ($18\%$ of cases, $\frac{9}{50}$). In one case, the sensor was applied on the shoulder blade region, and in another case, it was applied on the lumbar–sacral region. Twenty-six percent ($\frac{13}{50}$) of the DPOs changed the application area for each new sensor, by rotating between their favorite application areas. Forty-nine of the fifty DPOs ($98\%$) used the specific FGMS mobile app as a sensor reader, while only one DPO ($2\%$) used the handheld portable reader. The glucose values obtained using the sensor were transmitted to the veterinarian by means of the Libreview® data-sharing mode in $66\%$ of cases ($\frac{33}{50}$). The remaining DPOs shared glucose values and information regarding animal health by creating Excel files or paper notes. Twenty-five DPOs ($50\%$) began using an FGMS within three months from the DM diagnosis, while the remaining DPOs started using it three months after (up to two years) the DM diagnosis. ## 3.2. Comparison between an FGMS and BGCs Before using an FGMS, all the diabetic pets were monitored with BGCs carried out at home or in the hospital. In particular, all the DPOs included experienced home monitoring by performing at least one BGC at home. When comparing the use of an FGMS with a BGC, we noted that $85\%$ ($\frac{43}{50}$) of the DPOs believed that the FGMS was easier to use than a PBGM. In addition, in $82\%$ ($\frac{41}{50}$) of cases, the FGMS was considered less stressful and painful than a BGC. As shown by Figure 1, $79\%$ of dog owners ($\frac{23}{29}$) considered the FGMS application to be less invasive than carrying out a BGC. In contrast, $57\%$ of cat owners ($\frac{12}{21}$) consider it as invasive as carrying out a BGC; a significant difference was found between canine and feline DPOs ($$p \leq 0.01$$). In the owner’s opinion, the major advantages of using the FGMS were less stress for the animal than carrying out a BGC at home or in the hospital ($\frac{40}{50}$, $79\%$), the possibility of obtaining more information on the glucose trend with less effort ($\frac{34}{50}$, $67\%$), the low invasiveness and better comfort for the animal ($\frac{32}{50}$, $64\%$), the ease of use ($\frac{29}{50}$, $58\%$), and the reliability of the results provided by the FGMS ($\frac{23}{50}$, $45\%$). The long-term use of the device was considered to be too expensive in $36\%$ of cases ($\frac{18}{50}$), difficult to afford in $14\%$ of cases ($\frac{7}{50}$), and affordable in $50\%$ of cases ($\frac{25}{50}$) Overall, $92\%$ of the DPOs ($\frac{46}{50}$) believed their pet had better glycemic control since using the FGMS as a monitoring method. No differences were found between dog and cat DPOs (Figure 2; $$p \leq 0.29$$). ## 3.3. Impact of an FGMS on Diabetic Pets’ and DPOs’ Quality of Life The most challenging and stressful aspects of using the sensor were ensuring adequate fixation during the operating period ($\frac{24}{50}$, $47\%$), preventing self-removal by scratching or licking ($\frac{20}{50}$, $40\%$), and the purchase of the sensor online ($\frac{17}{50}$, $34\%$). In particular, premature sensor detachment was a concern described by $57\%$ ($\frac{12}{21}$) of cat DPOs and by $24\%$ ($\frac{7}{29}$) of dog DPOs (Figure 3 and $$p \leq 0.02$$). In addition, $60\%$ ($\frac{13}{21}$) of cat DPOs reported that the sensor was not well tolerated, and a significant difference was found when compared to dog DPOs (Figure 4). Mild-to-moderate dermatological complications after sensor removal were reported in $18\%$ of cases ($\frac{9}{50}$). Thirty-five of the fifty DPOs ($70\%$) stated that using an FGMS had no negative impact on their QoL. Forty-four percent of the DPOs ($\frac{22}{50}$) felt safer replacing the FGMS whenever the previous sensor stopped working. The continuous access to the glucose data generated a sense of reassurance ($92\%$, $\frac{46}{50}$) or increased anxiety ($8\%$, $\frac{4}{50}$). The number of daily scans carried out by the DPOs is shown in Figure 5. At the time of filling out the survey, $\frac{29}{50}$ DPOs ($58\%$) were still using the FGMS on their diabetic pet, and $84\%$ of them ($\frac{42}{50}$) would continue to use it in the future. The remaining $16\%$ of the DPOs ($\frac{8}{50}$) would not continue using the FGMS owing to its elevated cost ($\frac{32}{50}$, $64\%$), the difficulty of buying it ($\frac{9}{50}$, $18\%$), and the excessive stress for the animal ($\frac{3}{50}$, $6\%$). Forty-seven of the fifty ($94\%$) DPOs would recommend the FGMS to other owners of diabetic pets. ## 4. Discussion The FGMS is an increasingly widespread monitoring method for DM in veterinary patients. The aim of this study was to investigate the impact of an FGMS on DPOs’ QoL and the satisfaction related to its usability. According to the present results, using an FGMS as a monitoring tool provided better glycemic control than BGCs. Moreover, continuous access to the glucose data generated a sense of reassurance in the majority of the DPOs. Despite this, the main drawbacks reported by DPOs were the increased anxiety related to the possibility of having continuous access to their diabetic pet glucose values and the costs related to its use. An FGMS is designed to be worn for fourteen days. Despite this, one of the most negative aspects described by the DPOs was the reduced sensor lifespan. This was especially true in diabetic cats, and the present results are in agreement with those of previous studies [5,10,15]. In contrast, the reduced sensor lifespan was less frequently reported by dog owners. These results are in agreement with those observed in previous studies in which the maximal duration of the FGMS (14 days) was reached in about $70\%$ of cases [12,14]. In fact, the premature detachment of the sensor represents one of the most frequent complications in diabetic cats, with a median sensor wearing time ranging from 5 to 10 days [5,7,10,16]. For this reason, in cats, to extend the sensor-wearing time, it might be advisable to additionally secure the sensor by using more glue. In the present study, approximately two-thirds of the DPOs used additional glue to extend the sensor-wearing time. This was more common among cat owners. The most used type of glue was cyanoacrylate (a multipurpose non-medical glue) due to its low cost and easy availability. Liquid medical adhesive, which is generally applied to fix dressings, patches, and some medical devices, was used in a minority of cases. Despite this, in the present study, only $20\%$ of the sensors reached the working life of 14 days reported by the manufacturer for diabetic patients. The use of skin stitches has recently been described as a method for securing the sensor in cats [16]. In the authors’ cases, skin stitches were not used, mainly due to the excessive invasiveness of the procedure and the need to perform it exclusively in the hospital. Almost half of the DPOs (mainly dog owners) were able to apply the sensor on their own at home. This represented an important factor in reducing costs in the management of diabetic pets. Similar to recent studies, dermatologic complications associated with the use of FGMS were mild and self-limiting [6,10,12,17]. However, severe allergic contact dermatitis, caused by the adhesive part of the sensor, has been reported in diabetic people [18]. In the present study, the most common application site was the dorsal aspect of the neck. This is the area recommended by the authors’ veterinary hospital since it was the most commonly used location in validation studies [5,6,14]. Moreover, this area allows for an additional bandage (applied by almost $90\%$ of the DPOs). The dorsum was the second most common application site, followed by the thoracic wall. In veterinary medicine, two studies have investigated the effect of the sensor location on the performance of another CGMS (Guardian Real-Time). In dogs, the IG measured in the chest site had the best correlation with blood glucose concentration as compared to the neck site; however, the sensor had the shortest lifespan [19]. Conversely, in cats, the dorsal neck area provided superior results in terms of accuracy when compared with the lateral chest-wall and knee fold [20]. Unfortunately, there are no data available as to whether different application sites could influence the performance of the FGMS in dogs and cats. All the glucose values obtained during the sensor-wearing period were transmitted by DPOs to the attending veterinarian for his evaluation to aid in therapeutic decisions. The most widely used data-sharing mode was Libreview®, which is a cloud-based diabetes management system in which the glucose readings from the FGMS can be uploaded and shared with the healthcare professional team. This monitoring method allows monitoring the glucose trend by forming a graphical trace of glucose values over a 24 h period and having access to previous glucose data. Moreover, it provides some metrics, such as the average glucose, coefficient of variation (CV), and time of glucose within/below/above range. To date, in veterinary medicine, a single study addressed one of these parameters (CV) [12]; however, their practical application might increase in the future. In fact, the concept of glycemic variability is emerging in human medicine as an additional glycemic target [21], and a few studies have started to investigate its role in veterinary [22,23]. Several studies have described the accuracy and clinical utility of an FGMS in dogs and cats [6,7]. It has been demonstrated that an FGMS allows for more accurate identification of the glucose nadirs, post-prandial hyperglycemia, hypoglycemic episodes, and day-to-day variations in glycemic control as compared to BGCs. For this reason, the FGMS is being used more and more; therefore, it was decided to also evaluate the owners’ point of view. Approximately $80\%$ of DPOs reported that the use of an FGMS was easier, less stressful, and less painful than carrying out BGCs. This could be explained by the fact that the application of the sensor is fast and painless. Furthermore, a majority of the DPOs were able to apply the sensor themselves. For obtaining a BGC, blood sampling is required, and when the BGC is not carried out at home, the animal requires hospitalization for at least 8–10 h. In addition, the possibility of assessing continuous glucose data remotely by using the Libreview® system allows for insulin-dose adjustments, without taking the animal to the hospital. This aspect is particularly relevant for diabetic cats in which stress hyperglycemia is a common problem in the interpretation of the BGC. Nevertheless, unlike dog owners, cat owners considered the application of an FGMS to be as invasive as carrying out a BGC. This result could be explained by the lower tolerability of the sensor application and wearing by the cats. For this reason, the discomfort from wearing the sensor may be perceived by the DPOs as a sign of excessive invasiveness for the cat. In the current study, $92\%$ of the DPOs believed that their pet had better glycemic control since using the FGMS monitoring method. It was recently reported that, if DM is monitored using a PBGM, glucose fluctuations between blood glucose measurements might be missed, and this could result in erroneous insulin-dose recommendations [24,25]. Moreover, by monitoring glucose trends remotely, insulin-dose adjustments can be performed more frequently and probably more effectively than by carrying out BGCs. Therefore, in the authors’ opinion, these advantages may result in a better perception of glycemic control by DPOs. Nevertheless, these results might be biased by the fact that some dogs and cats were referred for sensor placement, as glucose readings were not possible or difficult to perform, and therefore DPOs asked for a different monitoring method. Regarding the impact of an FGMS on the DPOs’ QoL, $92\%$ of cases experienced a sense of reassurance in being able to continuously know the glucose values of their diabetic pet. Moreover, $42\%$ of DPOs apply the sensor, continuously replacing each sensor at the end of its use with a new one. In veterinary medicine, an FGMS is used as an alternative monitoring method to BGCs. Therefore, in the authors’ clinical practice, they apply the sensor continuously until an optimal insulin dose is identified. Despite the fact that the majority of the DPOs felt a sense of reassurance, $8\%$ of them reported that the chance to have continuous access to their diabetic pet’s glucose values caused increased anxiety. This was highlighted by the fact that $46\%$ of the DPOs carried out between 10 and 20 glucose readings per day, although this is not necessary for the correct functioning of the sensor. In the authors’ opinion, anxiety could probably increase when DPOs detect low glucose values. However, this aspect was not evaluated in the present study. The other major drawbacks associated with the use of the FGMS were its cost and its availability. Currently, in the authors’ country, the FGMS can only be purchased online via the official website of the manufacturer. This aspect is particularly challenging for the elderly or for those who are not familiar with the use of the Internet. In fact, $34\%$ of DPOs stated that availability was one of the most negative aspects associated with the use of the device. Based on these results, the possibility of buying the sensor not only online but also through other sellers could probably make it more usable by all types of DPOs. In addition to this, in $37\%$ of the cases, the long-term use of the device was considered too expensive. This was in agreement with previous studies in which, despite the elevated degree of satisfaction, the cost was reported to be a main drawback [10,12]. Therefore, this seems to be a common problem in different countries. Nevertheless, despite the disadvantages reported, $70\%$ of the DPOs reported that using an FGMS had no negative impact on their QoL; this was in agreement with previous studies in human medicine in which the continuous use of an FGMS was associated with an improved QoL in diabetic patients [26,27,28,29]. Moreover, Overend et al. reported that an FGMS had a positive impact on psychological well-being and self-esteem since patients with type 1 DM experienced more control over their BG values [30]. In total, $84\%$ of the DPOs stated that they would continue to use the device in the future, and $94\%$ of them would recommend it to other DPOs. These data suggest that the overall good DPO satisfaction and owner perceptions of the advantages of FGMS outweigh the disadvantages. The present study had some limitations, including the small sample size, its retrospective nature, and the fact that the survey used was not previously validated. Another limitation of this study is that the degree of stress of the diabetic pet and the DPOs’ QoL were evaluated subjectively and not through specific scores. However, the main limitation was that all the diabetic patients included were monitored at a referral center. In fact, thanks to the specialist medical staff, the DPOs were well-instructed regarding the use of the sensor and how to interpret the glucose data. This might have positively influenced the present results. For this reason, additional studies, also including diabetic pets managed by primary care veterinarians, are needed. ## 5. Conclusions In conclusion, the FGMS was considered easy to use by the DPOs and less stressful when compared to BGCs, while enabling better glycemic control. Moreover, the possibility of having continuous access to the glucose data generated a sense of control in the DPOs. Nevertheless, the cost related to its long-term use might be difficult to sustain. 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--- title: Machine Learning Analysis of RNA-seq Data for Diagnostic and Prognostic Prediction of Colon Cancer authors: - Erkan Bostanci - Engin Kocak - Metehan Unal - Mehmet Serdar Guzel - Koray Acici - Tunc Asuroglu journal: Sensors (Basel, Switzerland) year: 2023 pmcid: PMC10052105 doi: 10.3390/s23063080 license: CC BY 4.0 --- # Machine Learning Analysis of RNA-seq Data for Diagnostic and Prognostic Prediction of Colon Cancer ## Abstract Data from omics studies have been used for prediction and classification of various diseases in biomedical and bioinformatics research. In recent years, Machine Learning (ML) algorithms have been used in many different fields related to healthcare systems, especially for disease prediction and classification tasks. Integration of molecular omics data with ML algorithms has offered a great opportunity to evaluate clinical data. RNA sequence (RNA-seq) analysis has been emerged as the gold standard for transcriptomics analysis. Currently, it is being used widely in clinical research. In our present work, RNA-seq data of extracellular vesicles (EV) from healthy and colon cancer patients are analyzed. Our aim is to develop models for prediction and classification of colon cancer stages. Five different canonical ML and Deep Learning (DL) classifiers are used to predict colon cancer of an individual with processed RNA-seq data. The classes of data are formed on the basis of both colon cancer stages and cancer presence (healthy or cancer). The canonical ML classifiers, which are k-Nearest Neighbor (kNN), Logistic Model Tree (LMT), Random Tree (RT), Random Committee (RC), and Random Forest (RF), are tested with both forms of the data. In addition, to compare the performance with canonical ML models, One-Dimensional Convolutional Neural Network (1-D CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM) DL models are utilized. Hyper-parameter optimizations of DL models are constructed by using genetic meta-heuristic optimization algorithm (GA). The best accuracy in cancer prediction is obtained with RC, LMT, and RF canonical ML algorithms as $97.33\%$. However, RT and kNN show $95.33\%$ performance. The best accuracy in cancer stage classification is achieved with RF as $97.33\%$. This result is followed by LMT, RC, kNN, and RT with $96.33\%$, $96\%$, $94.66\%$, and $94\%$, respectively. According to the results of the experiments with DL algorithms, the best accuracy in cancer prediction is obtained with 1-D CNN as $97.67\%$. BiLSTM and LSTM show $94.33\%$ and $93.67\%$ performance, respectively. In classification of the cancer stages, the best accuracy is achieved with BiLSTM as $98\%$. 1-D CNN and LSTM show $97\%$ and $94.33\%$ performance, respectively. The results reveal that both canonical ML and DL models may outperform each other for different numbers of features. ## 1. Introduction Colorectal cancer is among the most common cancers around the world. It has high incidence and mortality rate with increasing trend. Many factors, such as smoking and alcohol consumption, could contribute to incidence of colorectal cancer. Currently detection methods for colorectal cancer, such as colonoscopy and fecal occult blood test, have various disadvantages. These disadvantages are lower sensitivity and specificity and also bleeding problems. Moreover, many patients can be diagnosed at late stage of colorectal cancer. Therefore, there is a great demand for rapid and reliable detection methods for diagnosis and prognosis of colorectal cancer. In recent years, attention has been drawn to omics technologies in life sciences and clinical analysis. These techniques provide essential information about the pathogenesis of diseases at metabolite, protein, and transcriptome level. Transcriptomics is the general analysis of organism’s transcriptome, in other words, the sum of all RNA transcripts. Transcriptomics have been used to understand nature of diseases and to find diagnostic and prognostic biomarkers. Moreover, high throughput RNA-seq data could provide an opportunity to analyze hundreds of transcripts for a complete view of the expression dynamics of diseases. ML, which is a branch of artificial intelligence, provides computers the ability to create models from data. It has been used in many fields of healthcare [1,2,3]. In particular, using health records in ML systems provides vast opportunities to answer clinical problems [4,5,6]. Another promising area in healthcare is omics technology [7]. Recent developments in genomics, transcriptomics, proteomics, and metabolomics have opened new opportunities for personalized and precision medicine. Omics have been used to understand disease mechanism, treatment efficacy, and lifestyle interventions for diseases [8]. In the last decade, the amount of data produced in omics technologies has increased exponentially. The idea of integrating omics data with ML methods is to provide more comprehensive understanding of biological systems. In particular, evaluation of clinical omics studies has opened a new aspect in diagnosis and prognosis of diseases [9,10,11]. Transcriptomics is the analysis of global transcriptome, which is the complete set of RNA transcripts [12]. It provides an opportunity to analyze the expression level of transcripts for understanding physiological or pathological conditions. Transcriptomics have become one of the most utilized approaches that analyze human diseases at molecular level by using high-throughput methods (RNA array or RNA-seq) [13]. The expression analysis of transcripts is used to find biomarkers and therapeutic targets for many diseases [14,15]. In recent years, ML methods have been applied to transcriptomics data in various clinical studies, and results have provided essential information for future clinical approaches. However, this integration is not easy because transcriptomics analysis is expensive and ML systems require large sample sizes to thrive in prediction tasks. Therefore, previously published studies evaluated ML systems to obtain more information from biological datasets. In the present study, we focused on evaluation of transcriptomics analysis of circulating EVs in ML systems to predict colorectal cancer and to classify cancer stage. EVs, such as exosomes, play an important role in intercellular communications. They carry various types of bioactive molecules, including membrane proteins, lipids, RNAs, and DNA [16]. Their components are highly variable depending on the cells of origin. In cancer research, attention has been drawn to EVs because tumor-derived EVs contain unique materials (such as RNA and protein) for diagnosis and prognosis of cancer [17]. Yuan et al. analyzed RNA profile of plasma EVs in healthy and cancer patients [18]. Their aim was to find novel RNA based biomarkers for diagnosis and prognosis of various cancer types. Their study was one of the largest scale studies on various cancer types. Herein, we analyzed their dataset using different ML and DL approaches and tested the capability of our proposed approach to be used as a diagnostic and prognostic tool. We believe that our approach could contribute to further studies regarding integration of omics data with ML methods. The general framework of the study is given in Figure 1. Our first hypothesis is that DL algorithms will yield higher results in terms of accuracy than canonical ML algorithms since DL algorithms have more parameters and higher learning capacity than ML algorithms. The second hypothesis is in regard to exRNA transcripts that are used to feed both DL and canonical ML algorithms. Since miRNAs are the most abundant exRNA transcripts in homo sapiens and it is known that they are relevant to various cancer types, it is expected that miRNAs will be selected as more informative than other exRNA transcripts by a feature selection algorithm. The third hypothesis is that utilizing more informative exRNA transcripts selected by a feature selection algorithm rather than utilizing all attributes (exRNA transcripts) as inputs to feed the algorithms can improve the performance of the models. To summarize, the aim of the study is to develop canonical ML and DL models for predicting colon cancer and classifying the cancer stage. The experimental results reveal that both ML and DL models show promising performance. In addition, the results of McNemar’s test indicate that a statistically significant difference exists among models. The contribution of this study is fourfold. The first one is the comparison of canonical ML and DL algorithms. According to the experimental results, DL models have higher accuracy than canonical ML models for both cancer prediction and cancer classification. The second one is the development of DL architectures. In the study, instead of using a pre-trained model, all DL models are constructed from scratch and hyper-parameters are optimized by utilizing the GA, which is a meta-heuristic optimization technique. The third one is the feature selection. According to the results, instead of using all attributes, selecting some attributes that are more informative than others for the training phase can increase the accuracy of a model. By reducing the dimension of the feature space, the training time of a model is also shortened. The fourth contribution of the study is the uncovering of exRNA transcripts that may be determinative in colon cancer. Among 493 exRNA transcripts/attributes, 49 of the most informative exRNA transcripts belong to the mature miRNA category. The experimental results reveal that the RF algorithm fed by the most informative 30 and 40 exRNA transcripts outperformed other canonical ML algorithms in terms of accuracy for classifying colon cancer stage. The remainder of the article is organized as follows. Section 2 includes the literature review. In Section 3, information about the data, the data augmentation method, min–max normalization, the attribute selection method, the cross-validation technique, canonical ML and DL algorithms, GA that is used for optimization, evaluation metrics, and statistical tests are presented. Section 4 presents the experimental results, discussion, and practical applicability. In Section 5, the article is concluded. ## 2. Related Works The literature presents different usage of ML algorithms on transcriptomic data. Pantaleo et al. used blood transcriptomics data to train ML algorithms for early detection of Parkinson’s disease (PD) [19]. In this study, a dataset of 550 samples is used to train and test ML models. A feature selection mechanism, which includes RF, is used to reduce the dimensionality. The selected features were used to train the eXtreme Gradient Boosting (XGBoost) model with 10-fold cross validation method. This cross-validation phase is repeated 20 times with different seeds to obtain the best tuning parameters for RF algorithm. The average accuracy of the XGBoost model was $69.3\%$. Nalls et al. designed a model for early diagnosis of PD using Linear Regression [20]. The training dataset contained information of 532 individuals, 367 of which had PD and 165 of which were healthy. In that study, the test set included 1086 samples, 825 of which had PD. They used area under the curve (AUC) and sensitivity as the evaluation metrics, which were 0.923 and 0.834, respectively. Hamey and Göttgens used different ML algorithms to evaluate the similarity of single-cell transcriptomes to the hematopoietic stem cells [21]. In that study, kNN, Linear Regression, Multilayer Perceptron (MLP), RF, and Support Vector Machines (SVM) models were trained with fivefold cross validation. Among these models, MLP and SVM generated the best results regarding hscScore, which defines similarity to gene expression profiles of validated hematopoietic stem cells. Akter et al. used ML models to diagnose endometriosis using RNA-seq and DNA methylation [22]. In that study, the candidate biomarker genes were determined using various techniques, and then four different supervised ML methods, namely Decision Tree (DT), Partial Least Squares Discriminant Analysis (PLSDA), SVM, and RF, were trained. The results were evaluated using different metrics, including accuracy, sensitivity, precision, etc. DT was the overperforming technique among the four ML methods, with $89\%$ accuracy. Sharifi et al. employed tree-based ML methods with meta-analysis to identify transcriptomic biosignature of mastitis disease [23]. These tree-based models, that included RF, successfully detected the best combination of genes as biosignature which helped to diagnose the disease early. DL models have also been used in cancer diagnosis studies. Balaha et al. designed a model for early diagnosis of breast cancer using ultrasound data [24]. The study presented a hybrid model using both CNN and GA. The Transfer Learning method, which included tuning popular pretrained CNN models, were employed. GA was used for parameter optimization and learning. The dataset contained images of breast ultrasound and augmented during the training process. For evaluation metrics, they used loss, accuracy, F1-score, precision, recall, specificity, and AUC. Among the pretrained models, Xception showed the best performance, achieving over $90\%$ accuracy and F1-score. Anaraki et al. proposed a method which used CNNs and GA to classify different stages of brain tumor [25]. The dataset contained brain MR images of individuals who were healthy or suffered from different level of cancer. In that study, they designed an evolving CNN structure rather than existing pretrained models. In the phase of data augmentation, a straightforward method, which included rotation, translation, and scaling, was used. After this step, a total of 16,000 MR images, which included 8000 healthy and 8000 with tumor, were obtained. In the training step, different parameters were used to evolve the CNN with GA, including, but not limited to, number of convolutional, max pooling, fully connected, and dropout layers. In addition, Bootstrap Aggregating was employed to decrease the generalization error. This study showed average accuracy of $90\%$ after seven generations of GA. Dweekat and Lam presented a hybrid system with GA, MLP, and Principal Component Analysis (PCA) to predict cervical cancer [26]. In that study, PCA was used for feature transformation, MLP used as classification model, and GA used to optimize the hyperparameters of MLP. The proposed method outperformed existing techniques with fivefold cross validation, with $96\%$ accuracy. Resmini et al. purposed an ensemble method with GA and SVM to diagnose breast cancer using thermographic data [27]. The reason for using thermographic data in this study was the low measurement cost. The classification system included three stages. In the first stage, best model was selected using GA. In the next stage, GA was also employed to select features. The classification was performed at the last stage. They achieved promising experimental results, with $97\%$ accuracy and $94\%$ AUC. Consiglio et al. used Fuzzy Rules with GA to separate ovarian cancer and other ovarian diseases [28]. Here, GA was employed for the feature selection phase with if–then rules. The purposed method can help to discover changes in the selected genes over the distinguished classes. The dataset in that work contained 21 samples with 45,000 genes that corresponded to the features. After the feature selection phase, a 9000-feature dataset was obtained. The classification task was performed using a Fuzzy-Rule-Based System which included a form of if–then rules. A different set of parameters was prepared for GA, which included 100 to 400 individuals. They reported $100\%$ accuracy on the dataset. Ali and Saeed proposed a system that included hybrid filter and GA to reduce the feature space of microarray data, which generally has high dimensions and causes slow performance on ML algorithms [29]. In the initial step of the study, information gain, information gain ratio, and Chi-square were used for feature selection of cancerous microarray datasets. The next step included employing GA to optimize the feature selection process. The dataset with selected features was used to train different ML algorithms, including DT, kNN, RF, and SVM. Accuracy, recall, precision, and f-measure were used as evaluation metrics. Experimental results indicated that the proposed approach increased the performance of all models regarding all evaluation metrics. The literature presents many different approaches for diagnosis of colon cancer using ML/DL methods. Jiang et al. designed CNN- and ML-based prediction systems for colon cancer [30]. In that study, the system was designed only for stage III of colon cancer and used hematoxylin-and-eosin-stained tissue slides. Gupta et al. [ 31] demonstrated the prediction capabilities of different ML algorithms using information that contained histopathology reports, intra-operative findings, history taking, and chart records. The dataset was not augmented in the training stage and was used as it was. The study focused mainly on stage prediction of the colon cancer and used RF, AdaBoost, SVM, MLP, and kNN as classifiers. The Recursive Feature Elimination method was used as the feature selection algorithm. The accuracy results for the RF, which was the overperforming algorithm, were $74\%$ and $90\%$ when taking only the tumor size as a prognostic factor and taking Tumor Aggression Score as a prognostic factor, respectively. Masud et al. presented a framework to diagnose lung and colon cancer tissues using DL [32]. In that study, a lung and colon cancer histopathological image dataset, which contained 25,000 color images with 5 different classes was used. The classification was performed using a CNN. The framework demonstrated a maximum accuracy of $96\%$. As can be seen from previous studies, ML and DL algorithms were fed by thermographic, MRI, or CT images. We attempted to fill the gap in the literature by utilizing transcriptomic data of individuals. Another gap in the literature is that the hyper-parameters of DL architectures are not optimized. We attempted to contribute to the literature by building DL architectures from scratch and optimizing DL hyper-parameters with the meta-heuristic GA to be utilized in colon cancer prediction and classification. Furthermore, the collection of data is more straightforward and preserves the life quality of the patients compared with classical methods. Our proposed approach offers the benefit of determining disease progression simply by re-obtaining a patient’s exRNA transcript values, without subjecting the patient to procedures that could impact them physically or mentally. ## 3.1. Study Subjects and RNA-seq Analysis In this work, the dataset from Yuan et al. ’s study is used, which has GEO database accession number of GSE71008 [18]. This study contains 50 healthy subjects and 100 patients with colorectal cancer ($$n = 25$$ for each of stages I-IV). The RNA-seq analytical pipeline eRNA (v1.2) was used for the data analysis, including raw data extraction, trimming, sequence alignment, and read count scaling. In Yuan et al. ’s work [18], they used various databases, including miRNA, piwiRNA, siRNA, and FLJ human cDNA. In addition, miRNA isoform analysis and exRNA stability analysis tests were carried out. They used normalized RPM values for comparison between healthy and cancer patients. In this work, similar workflow was employed to analyze RNA-seq data. Normalized RPM level of RNA transcript was utilized for ML systems. In addition, log2-transformed RPM cut off value was determined as 5 for reliable analysis. ## 3.2. Data A total of 150 subjects were separated as shown in Figure 2. As can be seen in Figure 2a, 100 of 150 subjects were cancer patients at a certain level. As seen in Figure 2b, 100 patient individuals were equally divided in 4 stages of the disease. The ML methods generally require large datasets. The data we used in this study were from 150 subjects and may be insufficient for this type of work, and an augmentation of the data was required to achieve a satisfactory performance of ML classifiers [33]. For this purpose, the data were augmented to include 300 samples. Later, considering the large number of features compared with the sample number of the data, a certain number of features were selected, considering that some features may be more important than others. In addition, it is important to note that selecting features reduces the complexity of the data and shortens the training time [34]. For data augmentation, the Synthetic Minority Over-sampling Technique (SMOTE) algorithm was utilized in the study [35,36]. SMOTE was originally developed for imbalanced datasets to oversample the minority class. However, it can also be used to oversample the whole dataset. SMOTE oversamples the minority class by generating synthetic data by working on feature space. This method oversamples by taking every minority class example into account and presenting synthetic examples and joining nearest neighbors to that class. The nearest neighbor count depends on the size of the oversampling process. The first step of generating synthetic examples is calculating the difference between the feature vector of current example and its nearest neighbor. The second step includes multiplying the calculated difference by a randomly generated number between 0 and 1. In the third step, the calculated vector is added to the feature vector of the current example. In our study, first, for a randomly selected healthy sample, 50 augmented healthy samples were generated, while 50 randomly selected cancerous samples were used. Therefore, a total number of 100 healthy samples were obtained. Secondly, for a randomly selected cancerous sample, 100 augmented cancerous samples were generated, while all healthy samples were used. As a result, a total number of 200 cancerous samples were achieved. In total, the size of the dataset was increased to 300 samples while keeping the imbalanced ratio. On the data, normalization was applied to reduce the effect of outliers and guarantee that all attributes have the same scale for both canonical ML and DL algorithms. In our study, min–max normalization was used for data normalization process. Min–max normalization can be seen in the following Equation [1]:[1]x′=x−min(X)max(X)−min(X)(new_max(X)−new_min(X))+new_min(X) In the equation above, x′ and x represent the new normalized and the current values of the attribute, respectively, whereas min(X) and max(X) represent the current minimum and the current maximum values, respectively, in the related attribute column of all samples; new_min(X) and new_max(X) represent the new minimum and the new maximum values, respectively, in the new normalized range. In this study, standard [0–1] min–max normalization is applied for canonical ML algorithms, while [0–255] min–max normalization is preferred for DL algorithms. The reason for this choice is that CNN architecture accepts images as input (in the experiments 1-D CNN is fed by gray scale images). In addition, LSTM and BiLSTM algorithms were fed by input values having a range between 0 and 255. In the dataset that is used in the study, there existed 493 attributes for each sample. To observe the effect of the number of attributes that will be given as inputs to ML and DL algorithms on the performance, a feature selection algorithm was applied. Feature selection can help to reduce dimensionality and, therefore, reduce computational load of ML frameworks. In addition, by selecting relevant features, accuracy of predictions can be increased [37]. Simply, the algorithm calculated the information gain (IG) for each attribute. IG can be defined as expectation of entropy reduction while splitting the samples according to an attribute. In other words, IG determines how much information an attribute supplies about a class. Therefore, the higher value of IG of an attribute, the more informative it is. IG can be calculated as in the following Equations [2] and [3]:[2]IG(C,X)=Entropy(C)−∑x∈XXxX∗Entropy(Xx) [3]Entropy=−∑$i = 1$cP(xi)log2P(xi) In the equations above, C represents the target or class, X represents the attribute vector, and x represents each value of the attribute vector X. While calculating entropy, c represents the number of the cases of the target or briefly the number of classes. Finally, P(xi) represents the probability of a value occurring in the target data. For the experiments, n attributes with the highest IG values were selected to feed the algorithm for training process. In our study 10, 20, 30, 40, and 50 attributes having the highest IG scores were selected, and all experiments were conducted by using these attributes. In addition, the experiments were repeated and compared on the basis of performance by including all attributes. In all experiments, to calculate the performance of the models, based on the evaluation metrics, the 10-fold cross validation technique was employed. According to this technique, the dataset was split into 10 equal parts while maintaining the class ratio. In the next step, the first part was excluded, while the remaining part was used to train the ML or DL algorithm. After the training phase, the obtained model was validated with the excluded part. These processes were repeated until all parts were used to validate the models (Figure 3). To evaluate the final accuracy of a model after 10-fold cross validation, the accuracy results of all folds were taken into consideration. The final accuracy was calculated by averaging the accuracy results of the 10 folds. ## 3.3. Machine Learning Analysis The popularity of ML has tremendously increased over the last decade. This increase has enabled ML to be applied to increasingly more areas. One of the most important applications of ML is the prediction of diseases. By analyzing the data obtained from individuals, the probability of disease can be predicted with high accuracy. The literature presents different approaches of ML in medical domain and disease prediction. In this study, we used 5 canonical ML approaches to predict whether an individual has colon cancer. The selected methods are kNN, LMT, RT, RC, and RF. All canonical ML algorithms were employed with default parameters (Table 1). In addition, DL algorithms were utilized to predict the stage of the cancer and whether an individual has colon cancer. 1-D CNN, LSTM, and BiLSTM DL algorithms were applied in the study and optimized. kNN is the one of the most used approaches of ML. This supervised learning method was presented in 1967 by Cover and Hart [38]. This approach classifies a sample by looking at its previously classified neighbor samples and is independent of the hidden joint distribution on other samples and their classification. The literature has different applications of kNN on cancer diagnosis, particularly in breast cancer [39,40,41,42]. LMT is a supervised classification algorithm, which is the combination of two learning approaches with complementary superiority and weakness: DT and Logistic Regression [43]. The LogitBoost algorithm is used to generate a logistic regression model at each node of these classification trees with logistic reduction functions on their leaves. In this way, it is ensured that the child nodes contain information about the main nodes and that probability estimates are formed for each class. The resulting model is simplified by dividing it according to C4.5 criteria. LMT algorithm is used for disease classification [44,45] and predicting cancer and cancer proteins [46,47]. RT is a DT-based supervised classifier that randomly selects the k number of attributes at each node [48]. The algorithm has no pruning to decrease the error and is very effective on classification and regression tasks. The classifier depends mainly on the single model tree and Random Forest [49]. Previous studies demonstrate that RT classifier is easy to implement, effective, and does not overfit [50,51]. RC is an ensemble classifier which uses base classifiers with the same data but a different number of seed values to make a predictions separately [52]. The algorithm forges final prediction by averaging the results of these individual base classifiers [53]. In the literature, RC is used in disease prediction tasks [54]. RF is another widely used classifier that utilizes a group of unpruned DTs and is accurate on large volumes of data in classification and regression tasks [55]. This group of DTs is built from a training data set and determines the output. Each DT in this group is a separate classifier and has its own predictions from a sample. This algorithm combines all the results from DTs to decide the final prediction [56]. The RF classifier is used to predict different cancer types, such as esophageal [57], breast [58,59], prostate [60], colorectal [56], lung [61], and cervical [62]. LSTM networks are an upgraded version of recurrent neural networks (RNN) [63]. In recent years, they output better classification results when compared with other DL networks on various research areas, such as time series and genome data [64,65]. In order to comprehend LSTM structure, RNN structure needs to be defined. RNNs are neural networks that also have memory and are able to recall all the information that is sequentially captured in the previous element. In other words, RNNs are an efficient way to use data from relatively long series since they perform similar tasks for each element in the series, with output dependent on all previous computations. A network with a feed-forward architecture and an extra cyclic loop is considered as RNN. By using this cyclic loop, RNN carries information throughout the network one time step to the next one. A form of short-term memory, cyclic loops are used to store and retrieve historical data throughout time steps. An RNN that learns temporal patterns estimates the current time-step by using the prior state and the present state. However, RNN architectures come with a disadvantage—vanishing gradients. The issue of vanishing gradients arises when recurrent neural networks are required to learn long-term relationships in time steps. For this requirement, the gradient vector increases or decreases exponentially as it propagates through multiple layers of the RNN to learn long-term dependencies over time steps. LSTM aims to solve this issue. In order to tackle vanishing gradient problem, LSTM uses memory blocks instead of traditional RNN units [65]. Its main advantage over RNNs is that it incorporates a cell state to store long-term states. An LSTM network can remember and connect information from the past to current information [64]. An updated version of LSTM called BiLSTM has emerged in recent years [66]. This architecture enables LSTM to analyze input data both forward and backwards. It actually adds two layers of memory cells to analyze data on both ways. The binding process of hidden states of backward and forward layers creates the representation of input data [67]. 1-D CNN is a modified version of CNN DL model [68]. In this version, one dimensional convolutional layers and sub-samplings are used to build feature space [69]. The one-dimensional convolution patch is handled by a number of convolution and pooling layers in the model, which extract features from one-dimensional input using a local receptive field and shared weights. These shared weights adjust the number of training parameters to be less than traditional CNN architectures. Through the use of several convolution filters, feature maps in the convolution and sub-sampling layers derive discriminant feature representations from many input vector segments. The 1-D CNN classifier is constructed with sample class information in the training process, and the gradient descent algorithm is utilized for adjusting network parameters [70]. The general structure of CNN consists of convolution, pooling, and a fully connected layer [69]. In the convolution layer, several convolution filters are employed to extract representative information from the raw data. Neurons are connected locally, thus reducing calculation load. In pooling layer, a process called sub-sampling is used to obtain more detailed feature maps at a lower resolution. The fully connected layer generally comes before the output layer to forward features to final classification phase [71]. The experimental setup for canonical ML algorithms can be seen in Table 1, Table 2, Table 3 and Table 4, which indicate the hyper-parameters of the proposed 1-D CNN architecture. Table 5 and Table 6 show hyper-parameters to build LSTM and BiLSTM architectures from scratch. Therefore, the results can be reobtained for each model by utilizing the optimized hyper-parameters. All canonical ML and DL algorithms have some advantages and disadvantages. Their performances are closely related to the utilized dataset. The advantages and disadvantages of the algorithms utilized in this study are explained briefly. In our study, kNN is chosen since it is easy to implement and it makes no assumptions about the data. However, it has a disadvantage in dealing with imbalanced data. LMT algorithm is expected to provide accurate results since it combines decision tree and logistic regression algorithms. In contrast, due to its high computational cost, it is not a preferred algorithm. The advantage of RC is that it takes into account the results of different classifiers. Likewise, this situation can lead to a disadvantage. If the majority of the classifiers make an incorrect prediction, the algorithm’s prediction will also be incorrect. RF’s advantage is that it is composed of uncorrelated decision trees. In other words, the trees that form the forest are not similar. Therefore, the algorithm has a high generalization capacity and handles imbalanced data. Nevertheless, if a dataset does not have some informative attributes, prediction performance of RF will suffer. As with RF, the performance of the RT algorithm directly depends on whether there are some informative attributes in the dataset. Consequently, if a dataset is an imbalanced one and some of the attributes have importance, it will be more likely expected that RF yields better accuracy than other ML algorithms. CNN is chosen because it exhibits high performance when classifying images. Since an image is a matrix, we can build a model using CNN architecture if we express each sample as a 1-D matrix. LSTM and BiLSTM are efficient in processing sequential data. In addition, if we have 1-D matrices as inputs, we can feed these algorithms. All DL algorithms utilized in the study suffer from the training time to build a model. To compare the algorithms, some evaluation metrics are needed. One metric is not sufficient to reveal the superiority of an algorithm. To support the accuracy of the algorithms, statistical tests are applied on the results. In this study, the Kappa statistic and McNemar’s test were utilized to validate the results. While experimenting with DL algorithms, values of some hyper-parameters needed to be optimized. Therefore, for each DL algorithm, GA, a meta-heuristic approach, was utilized for optimization. GA is a meta-heuristic search algorithm that mimics the evolutionary process, having the principle of the survival of the fittest. Especially in cancer diagnosis, GA has a wide range of use [27,72]. In this study, GA was utilized to optimize hyper-parameters of DL algorithms. Each possible solution was represented by a chromosome in GA. A chromosome is composed of genes that represent the hyper-parameters to be optimized of a DL architecture. All chromosomes form a population where the optimal chromosome, which satisfies the fitness function, is attempted to be found. Firstly, a population is initialized randomly. Secondly, fitness value of all chromosomes is evaluated in the population. Thirdly, the parent chromosomes that will form the next generation are chosen. Crossover and mutation operations are applied on chosen chromosomes. The third step is repeated until a stopping criterion is met. Some of the chromosomes pass on the next generation directly; these chromosomes are called elites. In our study, the number of generations was selected as 100, and it was used as the stopping criterion. The percentage of elites was selected as $5\%$ of the population. The crossover operation that determines the fraction of the next generation was applied on $80\%$ of the population. The rest of the population was mutated while surviving to the next generation. Since GA does not guarantee the global minimum, a large population size of 200 was selected to reduce the probability of obtaining a local minimum while increasing the run time of the algorithm. To produce children chromosomes, scattered crossover was utilized for crossover operation (Figure 4). In scattered crossover, after selecting the parent chromosomes, a randomly created binary vector determines the genes of the child chromosome (Equation [4]). [ 4]gi(Cc)={gi(Cp2), bi=0gi(Cp1), bi=1 In Equation [4], gi represents the ith gene in the child chromosome (Cc) and parent chromosomes (Cp1 and Cp2), while bi represents the ith value in the random binary vector. For 1-D CNN DL, hyper-parameters, such as filter size and number of filters, were optimized for each convolutional layer by applying GA. General structure of the 1-D CNN architecture is shown in Figure 5. The number of convolutional layers to be added in the 1-D CNN architecture was determined by the size of the input (attributes). Therefore, for each number of attributes (10, 20, 30, 40, 50, and all attributes that form the feature vector) different numbers of convolutional and max pooling layers existed in the related 1-D CNN architecture (Table 2). For each convolutional layer, the stride parameter was selected as 1 and zero padding was applied, when necessary, to make the output as the same size as the input. After each convolutional layer, there existed a max pooling layer in the architecture. Max pooling layers halve the size of the input to perform down sampling. To ensure that, the stride parameter and pool size parameter were selected as 2 and 3, respectively, and zero padding was applied, when necessary. Consequently, different numbers of convolutional and max pooling layers were added according to the size of the input in the architecture until the output size was 1. Optimized values by applying GA for 1-D CNN architecture can be seen in Table 3 and Table 4 for both cancer prediction and cancer stage classification. In order to make a consistent comparison, the number of layers obtained for 1-D CNN was also used for LSTM and BiLSTM models. For LSTM and BiLSTM DL algorithms, the number of hidden units in each LSTM and BiLSTM layers was optimized by applying GA (Table 5 and Table 6). The general structure of the LSTM and BiLSTM architectures is shown in Figure 6. For each of the DL algorithms, adaptive moment estimation (Adam) optimizer was utilized, and early stopping was applied to prevent overfitting. In addition, data shuffling was enabled before each training epoch. ## 3.4. Evaluation Criteria In this study, different evaluation methods were used to test the performance of ML and DL models over the data. The first metric of this study was classification accuracy, which was calculated by the ratio of the number of correct predictions to the total number of samples/predictions [5]. The accuracy will be high if most of the samples are correctly predicted. [ 5]Accuracy=Number of Correct PredictionsTotal Number of Predictions The second metric that was used in this study is the Root Mean Square Error (RMSE), which is a widely used method to measure the gap between classification predictions and actual classes [73]. The equation to calculate RMSE can be seen in [6]:[6]RMSE=∑$$n = 1$$N(r^n−rn)2N In Equation [6], r^n is predicted values, rn is observed values, and N is the number of observations. The results of RMSE are lower when the correct classification is employed. The Kappa statistic, which was presented by J. Cohen [74], is another metric that was used to evaluate the results of this study. Kappa statistic is a measure of the degree of agreement between two evaluations in a dataset [75]. Thus, it is expected that the classifiers with more overlapping prediction will generate higher Kappa values [76]. These values can be interpreted considering Table 7 according to Landis and Koch [77]. ## 3.5. Statistical Tests In this study, a statistical test—McNemar’s test—is employed to measure the statistical significance of the results. McNemar’s test [78] is a nominal variant of the Chi-square test which is utilized to analysis matched pairs of data. In this test, two different methods result in four possible outputs, which can be seen in Table 8. In Table 8, the number of times both algorithms failed or succeeded are represented by Nff and Nss, respectively. These parameters are insignificant when comparing two algorithms performance in McNemar’s test. On the other hand, Nfs and Nsf indicate the number of times one algorithm succeeded and the other failed. These two parameters were used to calculate the z score (Equation [7]), which is the numerical representation of difference between performance of two algorithms. [ 7]z=(\|Nsf−Nfs\|−1)Nsf+Nfs If the z score is 0, then it can be interpreted as the two algorithms showing similar performance, which denotes insignificance. When the z score is a positive value, performances of algorithms differ from each other. In addition, it is important to note that z scores have corresponding confidence scores which can be seen in Table 9. ## 4.1. Experimental Results The synopsis of the proposed approach included the following steps:[1]The obtained data that was composed of exRNA profiles/samples for healthy individuals and cancer patients was augmented by utilizing the SMOTE algorithm.[2]Normalization was applied on the data to reduce the effect of outlier samples.[3]A feature selection algorithm that calculates the information gain of each feature/attribute forming the data was applied. The algorithm ranked each attribute in descending order of value according to how informative it was.[4]The samples with the different numbers of attributes according to their ranks were utilized as inputs to feed the canonical ML and DL algorithms to build models.[5]The 10-fold cross-validation technique was utilized when building each model.[6]To optimize the hyper-parameters of the DL architectures, the GA was utilized.[7]The performance that each model achieved in terms of accuracy, RMSE, and Kappa statistic was determined.[8]To reveal whether the performances of the models were statistically significant, McNemar’s test was applied. In our present study, publicly available RNA-seq data of healthy individuals and colon cancer patients were downloaded and analyzed. We determined approximately 10 million raw sequence reads. Of these raw reads, approximately $40\%$ were mapped into the reference RNA sequences. The data have been tested with five canonical ML and three DL algorithms mentioned before. All results are given as graphs in Figure 7, Figure 8, Figure 9 and Figure 10. In these figures, the x-axis corresponds to number of attributes, and the y-axis corresponds to achieved accuracy. The results of canonical ML algorithms can be seen in Figure 7 and Figure 8 for predicting cancerous samples and stage of the cancer, respectively. As seen in Figure 7, all five canonical ML methods yielded adequate results when predicting cancerous or healthy samples. All methods returned over $92\%$ accuracy, which was the lowest result generated by RT method when 10 attributes were selected. Attribute selection was utilized to reduce the complexity of the models and shorten the training time. In general, selecting certain attributes did not improve the accuracy results. The RC, LMT, and RF methods provided the best results when all the attributes were used, while selecting attributes resulted in reduced accuracy of the LMT and RF methods. On average, RC and RF were the most successful methods when predicting the existence of cancer. The results of the second test, which included predicting stages of cancer, can be seen in Figure 8. In this part of the study, the data included samples from healthy individuals and cancer patients at certain stages. The results wwere very promising, considering all five methods successfully classified at least $91\%$ of the samples. Although there was no direct or inverse effect of attribute selection, the best result was achieved using RF when 30 and 40 attributes were selected out of 493 exRNA transcripts. Here, we can say that using the most informative 30 attributes was sufficient to classify the stage of the cancer. The most 50 informative attributes according to our feature selection method were: tRNA-Glu (also known as TRNAE3), hsa-miR-873-3p, hsa-miR-132-5p, hsa-miR-335-5p, hsa-miR-219a-5p, hsa-miR-139-3p, hsa-miR-22-5p, hsa-miR-409-3p, hsa-miR-152-3p, hsa-let-7e-5p, hsa-miR-425-5p, hsa-miR-543, hsa-miR-411-5p, hsa-miR-501-3p, hsa-miR-874-3p, hsa-miR-140-5p, hsa-miR-26a-1-3p, hsa-let-7i-3p, hsa-miR-660-5p, hsa-miR-378c, hsa-miR-19b-3p, hsa-miR-29c-3p, hsa-miR-370-3p, hsa-miR-130a-3p, hsa-miR-30c-5p, hsa-miR-363-3p, hsa-miR-30a-3p, hsa-miR-676-3p, hsa-miR-23b-3p, hsa-miR-767-5p, hsa-miR-145-3p, hsa-miR-1246, hsa-miR-885-5p, hsa-miR-125b-2-3p, hsa-miR-10b-5p, hsa-miR-1298-5p, hsa-miR-125a-3p, hsa-miR-339-3p, hsa-miR-23b-3p, hsa-miR-129-2-3p, hsa-miR-206, hsa-miR-34c-5p, hsa-miR-105-5p, hsa-miR-760, hsa-miR-330-5p, hsa-let-7d-5p, hsa-miR-10a-5p, hsa-miR-204-3p, hsa-miR-28-3p, and hsa-miR-99b-3p. As can be seen from the most informative 50 attributes, all attributes, except the first one, belong to the mature microRNA category. In general, the different methods had varying performances for changing numbers of attributes. RC achieved better performance if the number of attributes was relatively low, and as the selected number of attributes was increased, RF yielded the best results. Additionally, the LMT stood out as the best method when all attributes were used for evaluation. The results of DL algorithms can be seen in Figure 9 and Figure 10 for predicting cancer and stage of the cancer, respectively. According to the Figure 9, the highest accuracy was obtained by 1-D CNN model, while 50 attributes were utilized to train the convolutional neural network. In the LSTM model, the highest accuracy was obtained by including all attributes in the training, while in the BiLSTM model, the highest score was achieved by using both 50 and all attributes. It can be said that 50 attributes having the highest IG values were distinctive for binary classification with 1-D CNN model. According to Figure 10, for predicting the stage of the cancer, the highest accuracy was obtained by BiLSTM model with $98\%$, while all attributes were utilized to feed the classifier for predicting the stage of the cancer. The second highest accuracy rate of $97\%$ was obtained with 1-D CNN model by enabling all attributes as the input of the classifier. However, the lowest accuracy rate of $88\%$ was achieved with LSTM model by handling 10 attributes. Considering the utilization of all attributes, it was revealed that LSTM had the lowest accuracy rate once again. Nevertheless, LSTM model exceeded the $90\%$ accuracy rate with all numbers of attributes, except when 10 attributes were selected as input. The Kappa statistics and RMSE results of two experiments for canonical ML algorithms can be seen in Table 10 and Table 11. The results were obtained by using the dataset with all attributes. LMT algorithm showed the best performance regarding Kappa, but RC was the best algorithm considering RMSE on the state dataset. In Table 11, it can be clearly seen that LMT was superior on both the Kappa statistic and RMSE. These results support the accuracy graphs by showing the dominance of LMT on the dataset with all features. In addition, it is important to mention that all Kappa statistic values presented “Almost Perfect” agreement, considering Table 7. The Kappa statistics and RMSE results of two experiments for DL algorithms in order to predict cancer and classify cancer stage can be seen in Table 12 and Table 13, respectively. The results were obtained by using the dataset with all attributes. According to Table 12, among the DL models, the best performance was achieved by BiLSTM. Compared with canonical ML models, DL models showed low performance in terms of Kappa value and RMSE. For both evaluation metrics, the best model among DL models showed $7\%$ less performance than the best model among canonical ML models. However, the results were consistent with the accuracy performance and Kappa statistic values that indicated “Almost Perfect” agreement, considering Table 7. According to the Table 13, the highest values for both Kappa and RMSE were achieved by BiLSTM model. These achievements endorsed the accuracy performance by revealing the superiority of BiLSTM on classifying the stage of the cancer. In addition, it is important to mention that all Kappa statistic values indicated “Almost Perfect” agreement, considering Table 7. In addition, BiLSTM outperformed LMT in terms of Kappa but did not gain an advantage over RC and LMT in terms of RMSE. The results of McNemar’s test for canonical ML algorithms to predict cancer and classify cancer stage can be seen in Table A1 and Table A2, respectively. The results of McNemar’s test for DL algorithms to predict cancer and classify cancer stage can be seen in Table A3 and Table A4, respectively. In these tables the arrowheads show the superior classifier on the related dataset. The selected number of features are 10, 20, 30, 40, 50, and all respective attributes. Bold numbers (>1.96) indicate more than $95\%$ confidence level for two-tailed predictions. The aforementioned tables show the statistical significance of the results by comparing two classifiers. In all tables, every sub-column represents the results for different numbers of attributes. In addition, the values over 1.96, which corresponds to the $95\%$ confidence level for two-tailed predictions, are marked bold in the tables. In Table A1, which shows the z scores of algorithms on the state dataset, it can be clearly seen that RF and RC outperformed other algorithms by having 18 and 17 arrowheads, respectively. In addition, there are three values exceeding 2.576, that represent a $99.5\%$ confidence level. Two of these three values belong to RC, and the other one belongs to RF, which indicates the superiority of these classifiers. Z scores of algorithms on the stage dataset can be seen in Table A2. In this table, the RF classifier has 20 arrowheads, demonstrating more dominant performance than previous table. In addition, by having 14 arrowheads, the RC classifier performed second best algorithm on this dataset. In the table, seven values are marked in bold for RF classifier, which also indicates the superiority of this classifier. Another remarkable result is that RF classifier has four values representing $99.5\%$ confidence level. It is also worth mentioning that LMT classifier has only seven arrowheads, and two of them have a confidence level of $99.5\%$. According to Table A3, it is revealed that 1-D CNN model outperformed other models by having nine arrowheads. Three of them are marked in bold representing $97.5\%$ and $95\%$ confidence levels for one-tailed and two-tailed predictions, respectively. In addition, one of them indicates $99.5\%$ and $99\%$ confidence levels for one-tailed and two-tailed predictions, respectively. Among these DL models, BiLSTM comes second with five arrowheads, whereas LSTM is the last with two arrowheads. It is worth mentioning that the 1-D CNN model showed a statistically significant difference versus the LSTM model for 10, 40, and all attributes to predict cancer. In Table A4, the 1-D CNN model outperformed other DL models by having nine arrowheads to classify cancer stages. Four of them are marked in bold, representing $97.5\%$ and $95\%$ confidence levels for one-tailed and two-tailed predictions, respectively. In addition, one of them indicates $99.5\%$ and $99\%$ confidence levels for one-tailed and two-tailed predictions, respectively. Among these DL models, BiLSTM comes second with seven arrowheads, whereas LSTM is the last with one arrowhead. It is useful to emphasize that the 1-D CNN model showed a statistically significant difference with the highest confidence level versus the LSTM model while utilizing all attributes to classify cancer stage. Our first hypothesis is validated according to the accuracy performance of canonical ML and DL models. For colon cancer prediction, the best accuracy was obtained by the 1-D CNN DL model with $97.67\%$, which outperformed other canonical ML models. Furthermore, for cancer stage classification, the best accuracy was obtained by the BiLSTM DL model with $98\%$, which outperformed other canonical ML models. The second hypothesis is also validated by the feature selection algorithm that simply ranked the attributes according to the value of IG. It is revealed that 49 of the most informative 50 exRNA transcripts were miRNAs, and they belonged to the mature miRNA category. The third hypothesis is validated for colon cancer prediction and cancer stage classification by canonical ML models. RC and RF models with $97.33\%$ accuracy performance, fed by the most informative 10 and 50 exRNA transcripts, respectively, outperformed other ML models in cancer prediction. It is clearly seen that performance improvement could not be achieved when the number of exRNA transcripts used was increased. In cancer stage classification, RF model achieved the best accuracy performance with $97.33\%$ by utilizing the most informative 30 and 40 exRNA transcripts. According to the accuracy performance of DL models for colon cancer prediction, the third hypothesis is also validated. The best accuracy performance was achieved with $97.67\%$ by the 1-D CNN model utilizing only the most informative 50 exRNA transcripts. However, in cancer stage classification, the third hypothesis is invalidated by the accuracy performance of DL models. The best accuracy performance was achieved with $98\%$ by the BiLSTM model utilizing all exRNA transcripts. On the other hand, this result is consistent with the findings of Yuan et al. ’s study [18]. According to that study, as the stage of the disease progresses, the number of small non-coding RNAs (including miRNA, piwiRNA, and siRNA) increases. Therefore, the best accuracy performance can be expected by utilizing all exRNA transcripts that include other miRNAs, piwiRNAs, and siRNAs to classify cancer stage. ## 4.2. Practical Applicability Our proposed approach can have an applicability in practice. It can be utilized for both diagnosis and prognosis. Our approach alone should not be considered to diagnose colon cancer. The main goal is to assist medical doctors as a second opinion during diagnosis/prognosis and to speed up the process of treatment planning (Figure 11). A scenario for the practical applicability of the approach can be as follows:-An individual with health complaints applies to a health institution.-A diagnosis is made after a medical doctor’s examination and modern medical tests (healthy or colon cancer).-The medical doctor may misdiagnose or seek a second opinion, as the symptoms will not be the same in every individual.-The medical doctors may disagree on a diagnosis, as they may also come from different medical traditions.-At this stage, the approach we propose can become a part of the medical process.-After the exRNA profile of the individual is obtained, it is given to the canonical ML and DL models as input.-According to the results of the different models, the medical doctors can agree on a diagnosis or confirm their diagnosis.-It becomes important to determine the stage of the disease after the diagnosis.-Our approach can be utilized not only for diagnosing colon cancer but also for determining the stage of the cancer.-If the disease has not progressed to the final stages, early detection of the cancer accelerates treatment planning and improves the patient’s likelihood of recovery and quality of life. The advantage of our proposed approach is that re-obtaining a patient’s exRNA transcript values—without requiring procedures that affect the patient physically and psychologically—is sufficient to determine whether the disease is progressing. Our approach can be applied to other types of cancer as well. All that is required is to obtain the exRNA profiles from healthy individuals and patients with a specific cancer. Later, canonical ML and DL models can be obtained and optimized from the data. Additionally, the models can be retrained with new inputs and become more robust and less error-prone. Considering the workload on medical doctors in the COVID-19 pandemic, the efficacy of our approach can be better understood. If our approach is utilized, it can be provided that doctors make consistent decisions supported by artificial intelligence and shorten the time they spend per patient. Therefore, medical doctors can have time to spare for resting and preparing for other patient appointments. ## 5. Conclusions In this study, five canonical ML and three DL models were utilized to predict whether an individual has colon cancer and to classify the stage of the cancer. We used RNA-seq data of EVs, which was deposited at NCBI. EVs have drawn attention for early diagnosis of cancer. They carry DNA, RNA, protein, and metabolites between cancer cells for cellular communication. Therefore, evaluation of molecular components in vesicles provides detailed information about cancer progression. In recent years, transcriptome structure of vesicles has been analyzed frequently to find biomarkers. We focused on total transcriptome structure with ML and DL models to find new perspectives which could be used in clinical practice. One of the remarkable results of the study is that although hyper-parameters of canonical ML models were not optimized, they showed as high accuracy performance as DL models did for predicting cancer and classifying cancer stage. However, DL models achieved the best accuracy results by applying a meta-heuristic search algorithm, namely GA, resulting in a longer model training duration. Input data were normalized between 0 and 255 to create the 1-D CNN model in cancer prediction. The highest accuracy rate was obtained with this method. From this point of view, we consider that this method can also be used in the prediction of other cancer types. Another important aspect of the study is that BiLSTM model outperformed both canonical ML models and other DL models in terms of accuracy of classifying cancer stages. This can be explained by the learning ability of bidirectional long-term dependencies in sequence data through the layers in the BiLSTM architecture. Therefore, we determined that BiLSTM can reveal the relationships among various types of RNA within samples. Despite the limited amount of data available, DL and ML architectures achieved promising results. This situation proves that the proposed approach has potential for building an efficient prediction framework for colon cancer studies. Several shortcomings exist in the study. Only GA is considered for hyper-parameter estimation of DL models. In future studies, other meta-heuristic optimization algorithms, such as particle swarm optimization, ant colony, and gray wolf optimization, could be employed to compare the performances. This will increase validity and impact of the proposed approach. Since DL architectures have a high computational need to train data, this need can hinder the implementation performance of the proposed approach. In future studies, this issue can be investigated by using parallel computing tools and advanced Graphics Processor units. 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--- title: Oxylipins as Biomarkers for Aromatase Inhibitor-Induced Arthralgia (AIA) in Breast Cancer Patients authors: - Jessica A. Martinez - Betsy C. Wertheim - Denise J. Roe - Mihra S. Taljanovic - H-H. Sherry Chow - Wade Chew - Sima Ehsani - Sao Jiralerspong - Jennifer Segar - Pavani Chalasani journal: Metabolites year: 2023 pmcid: PMC10052117 doi: 10.3390/metabo13030452 license: CC BY 4.0 --- # Oxylipins as Biomarkers for Aromatase Inhibitor-Induced Arthralgia (AIA) in Breast Cancer Patients ## Abstract Aromatase inhibitor-induced arthralgia (AIA) presents a major problem for patients with breast cancer but is poorly understood. This prospective study explored the inflammatory metabolomic changes in the development of AIA. This single-arm, prospective clinical trial enrolled 28 postmenopausal women with early-stage (0–3) ER+ breast cancer starting adjuvant anastrozole. Patients completed the Breast Cancer Prevention Trial (BCPT) Symptom Checklist and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) at 0, 3, and 6 months. The plasma levels of four polyunsaturated fatty acids (PUFAs) and 48 oxylipins were quantified at each timepoint. The subscores for WOMAC-pain and stiffness as well as BCPT-total, hot flash, and musculoskeletal pain significantly increased from baseline to 6 months (all $p \leq 0.05$). PUFA and oxylipin levels were stable over time. The baseline levels of 8-HETE were positively associated with worsening BCPT-total, BCPT-hot flash, BCPT-musculoskeletal pain, WOMAC-pain, and WOMAC- stiffness at 6 months (all $p \leq 0.05$). Both 9-HOTrE and 13(S)-HOTrE were related to worsening hot flash, and 5-HETE was related to worsening stiffness (all $p \leq 0.05$). This is the first study to prospectively characterize oxylipin and PUFA levels in patients with breast cancer starting adjuvant anastrozole. The oxylipin 8-HETE should be investigated further as a potential biomarker for AIA. ## 1. Introduction Adjuvant aromatase inhibitors (AIs) are the recommended endocrine treatment for postmenopausal women diagnosed with early-stage, estrogen receptor-positive (ER+) breast cancer. AIs are also used in premenopausal women in combination with gonadotropin-releasing hormone agonists (GnRH). The three third-generation AIs in routine clinical use—anastrozole, letrozole, and exemestane—have similar efficacy and toxicity profiles when compared across studies. The standard recommended duration was five years until recent clinical trials showed that extended therapy (10 years) improves the disease-free survival rate in patients with high-risk ER+ breast cancer [1]. Despite these benefits, adherence remains a challenge, as AI therapy is associated with significant, activity-limiting musculoskeletal symptoms, including arthralgia, myalgia, and joint stiffness, collectively called AI-induced arthralgia (AIA). Symptoms can manifest early after the initiation of AI therapy and worsen up to two years. High rates of AI non-adherence (estimated at up to $50\%$ by year three) due to an intolerance to the side effects, notably AIA, are now linked to a reduced benefit [2,3]. The majority of pharmacological and non-pharmacological intervention studies for AIA are negative. This is most likely due to the enrolment of patients who are on adjuvant AIs rather than the enrolment of those “at high risk” for developing AIA. Currently, there is a need for clinically validated biomarkers to predict who is at risk for AIA, explain AIA progression, and guide intervention studies to improve quality of life and reduce death from breast cancer by improving AI adherence. While AIA is a well-known problem, the mechanism for its development is not well understood and grossly understudied. AIs block peripheral estrogen synthesis, thereby further decreasing estrogen levels [4]. Preclinical data suggest that AIA is directly related to loss of the anti-nociceptive action of estradiol; however, the level of estradiol depletion is not correlated with the degree of AIA symptoms [5]. Inflammation also plays a role in exacerbating AIA symptoms [6], and non-steroidal anti-inflammatory drugs (NSAIDs) provide relief for some women with AIA [7]. Our group previously reported that, in patients with breast cancer who are stable on an AI, intervention with the NSAID sulindac for six months resulted in improved pain, stiffness, and physical function as assessed by the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) Index [8]. However, inflammation alone is unlikely to be the cause of AIA [9]. To date, there are no clear metabolic pathways identified to explain AIA etiology or to determine targets for interventions. Oxylipins are produced via metabolism of ω-6 and ω-3 polyunsaturated fatty acids (PUFAs) by cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome P450 (CYP450) enzymes. NSAIDs target COX, which metabolizes ω-6 and ω-3 PUFA to inflammatory prostaglandins [10]. Oxylipins have a spectrum of biological activity, including pro- and anti-inflammatory effects, as well as the induction and inhibition of pain. The presence of underlying inflammation and the nociceptive activity of oxylipins, may be a contributing factor for pain [11,12,13]. Our group previously published an overview of the oxylipin pathway and biological outcomes [14]. Oxylipin profiles are implicated in the development of inflammatory conditions including rheumatoid arthritis [15]. Preliminary evidence also implicates both the CYP450 and LOX pathways in the development of tendinopathy [16,17]. We previously published that tendon stiffness may play a role in the pain experienced by women taking AIs [18,19]. AIs are also involved in the upregulation of the CYP450 pathway [20] and cross-talk between the estrogen receptor (ER) and LOX-mediated oxylipins [21], suggesting a role of oxylipins in AIA. These findings suggest that the development or progression of AIA is likely attributed, in part, to an unfavorable oxylipin profile. Alterations in the entire oxylipin cascade that result in multiple biological effects, including inflammation, the development of tendon stiffness, and increased nociception [22], may play a role in the development of AIA in patients with breast cancer. We conducted a prospective study to further explore these inflammatory metabolomic changes in the development of AIA. Women were enrolled after the completion of their definitive treatment at the initiation of their AI and were followed for six months. We previously reported in a subgroup of these patients that baseline stiffness in the abductor pollicis longus tendon evaluated using shear wave elastography could be used to predict the development of AIA [19]. Here we report the blood-based inflammatory biomarkers evaluated in these patients. To the best of our knowledge, this is the first study to report an inflammatory profile at baseline and the changes while on AI therapy. ## 2.1. Study Design This single-arm, prospective clinical trial was conducted at the University of Arizona Cancer Center (NCT03665077). It was approved by the institutional review board, and all patients enrolled signed an informed consent. Postmenopausal women with early-stage (0–3) ER+ breast cancer who were candidates for adjuvant AI therapy and had completed their definitive treatment (surgery ± radiation) were enrolled into this study. The exclusion criteria included having received chemotherapy (adjuvant or neo-adjuvant), prior endocrine therapy (AI or tamoxifen), history of rheumatoid arthritis or other autoimmune arthritis, active daily NSAID use (other than low-dose aspirin), and active use of any corticosteroids or immunosuppressive therapies. Participants were recruited during their initial visit with their oncologist prior to the initiation of AI therapy. They completed blood draws and questionnaires at 0, 3, and 6 months after initiating AI therapy (Figure 1). To decrease confounding effects, adjuvant AI therapy was initiated 6 weeks after the completion of their definitive treatment. All women enrolled in this study were started on adjuvant anastrozole. ## 2.2. Arthralgia and Depression Outcome Measures BCPT: The Breast Cancer Prevention Trial (BCPT) Symptom Checklist is a 42-item questionnaire validated in breast cancer survivors [23]. The BCPT total score comprises 8 subscores: hot flash (3 questions), nausea (3 questions), bladder control (2 questions), vaginal problems (3 questions), musculoskeletal pain (3 questions), cognitive problems (4 questions), weight problems (4 questions), and arm problems (2 questions). For each question, women indicate the presence or absence of symptoms and the extent to which they are bothered by those symptoms on a five-point Likert scale ranging from 0 (not at all) to 4 (extremely). The musculoskeletal pain (MS) subscale has been shown to be responsive to changes in AIA and is calculated as the mean of the responses to three questions addressing general aches and pains, joint pain, and muscle stiffness [24]. In the case of missing data for any question within the subscales, the entire subscale was considered missing. WOMAC: The WOMAC is a 24-item instrument developed to assess pain (5 items), stiffness (2 items), and physical function (17 items) in participants with hip and/or knee osteoarthritis as well as for AIA [25,26]. Here, we evaluated the 3 subscales and the total score using the 5-point Likert format (0 = none to 4 = extreme). As discussed in Bellamy [25], for convenience and for comparison purposes to previous studies, the total scores and each subscale were normalized to a range of 0–100. In the case of missing data, the subscales were considered valid as long as no more than 1 item was missing for pain or stiffness, and no more than 4 items were missing for physical function. Patient Health Questionnaire (PHQ)-9: The Patient Health Questionnaire (PHQ)-9 is a validated multipurpose tool used for screening, diagnosing, monitoring, and measuring the severity of depression [27]. It has been reported that up to $50\%$ of newly diagnosed patients with breast cancer have symptoms of depression or anxiety [28], and the perception of pain may be altered in individuals with symptoms of depression [29]. The PHQ-9 is a 9-item questionnaire that asks how often a person has been bothered by symptoms within the past 2 weeks. Responses are measured on a 4-point Likert scale, including “0 = not at all”, “1 = several days”, “2 = more than half of the days”, and “3 = nearly every day”. ## 2.3. Plasma Sample Collection and Preparation At collection, triphenylphosphine (TPP) and butylated hydroxytoluene (BHT $0.2\%$ w/w) (MilliporeSigma, Burlington, MA, USA) were added to plasma that was collected in EDTA tubes. TPP reduces peroxides to their monohydroxy equivalents, and BHT quenches radical catalyzed reactions [30]. Both reagents prevent peroxyl radical propagated transformations of fatty acids. Three 300 µL aliquots of plasma plus antioxidant were frozen immediately at −80 °C. Based on our experience, oxylipins are not stable through multiple freeze-thaw cycles. Therefore, all samples were thawed only once for batch analysis. Plasma samples were prepared for ultra-performance liquid chromatography (UPLC–MS) analysis as described in detail by Liu et al. [ 31]. Briefly, 250 µL plasma was spiked with a set of odd chain length analogues and deuterated isomers of several target analytes, including hydroxyeicosatetraenoic acids, thromboxanes, epoxides, prostaglandins, and diols, contained in 10 µL methanol (Cayman Chemical, Ann Arbor, MI, USA). Samples were then subjected to solid phase extraction using Oasis Prime HLB 3 mL, 60 mg sorbent (Waters, Milford, MA, USA). Eluents were evaporated to dryness and reconstituted in 50 µL methanol. Spiked samples were then vortexed, centrifuged, and transferred to autosampler vials for analysis. ## 2.4. Reverse Phase Chromatography with UPLC–MS Oxylipin profiling was performed using UPLC with an Agilent Ultivo QQQ MS system coupled to an Agilent 1290 Infinity II UPLC system (Agilent, Santa Clara, CA, USA). Chromatographic separation of the oxylipins was achieved using a gradient of water, methanol, and acetonitrile, all with $0.1\%$ acetic acid (v/v). The acquisition parameters were as previously described [32] with minor modifications, and the MS data were used for quantification. Surrogate analytes and internal and external standards were used to monitor extraction efficiency and ensure accurate quantitation with standard curves. The acquired data were quantified using Quant-My-Way (Agilent, Santa Clara, CA, USA) using 9 isotope-labeled internal standards. Here we report the data for oxylipins with >$80\%$ of values above the limit of detection (43 of 62 oxylipins) and for 4 PUFAs: arachidonic acid (ARA), linoleic acid (LA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) (Cayman Chemical, Ann Arbor, MI, USA). UPLC was performed in 2 separate batches, ensuring that repeat measures across time for the same participant were all included in the same batch. ## 2.5. Statistical Analysis Baseline characteristics were summarized using the median [interquartile range (IQR)] for continuous variables and proportions for categorical variables. The symptom scores and oxylipin levels were summarized at each time point using the mean ± standard deviation (SD). The associations between the baseline PUFA/oxylipin levels and baseline symptom scores were tested using Spearman correlations. The changes in symptom scores across time were tested using linear mixed-effects models with time (interval since baseline) as a continuous variable, adjusted for baseline symptom score, and clustered on the participant. Additional models further adjusted for age at baseline, BMI at baseline, and definitive therapy (mastectomy versus lumpectomy). Similar mixed-effects models were constructed for changes in PUFAs and oxylipins across time and adjusted for baseline level and batch. The associations between the baseline PUFA/oxylipin levels and symptom scores across time were tested using linear mixed-effects models as described above. PUFAs and oxylipins were log-transformed in all models. The statistical analyses were conducted using Stata 17.0 (StataCorp, College Station, TX, USA), and no adjustments were made for multiple comparisons. ## 3.1. Participants and Characteristics Of the 30 patients recruited, one was ineligible due to prior therapies, and one withdrew on the same day as enrollment per difficulty with the blood draw, thus yielding a sample size of 28. The median (IQR) age was 66.0 (63.1–72.6) years at enrollment (Table 1). Median (IQR) time since diagnosis was 4.7 (3.6–5.9) months. Median (IQR) BMI was 25.1 (23.0–31.3) kg/m2, and the cohort was $89.3\%$ non-Hispanic white. For their definitive breast surgery, $78.6\%$ received a lumpectomy, and $67.9\%$ required radiation. There were eight ($28.6\%$) participants with stage 0 breast cancer, seventeen ($60.7\%$) stage I, and three ($10.7\%$) stage II. There were eight participants regularly taking low-dose aspirin (81 mg) and one participant taking other (non-NSAID) pain medication. ## 3.2. Change in Symptom Scores BCPT, WOMAC, and PHQ-9 mean ± SD scores at baseline, three, and six months are presented in Table 2. In the fully adjusted model, there was a significant increase in the BCPT-total score ($$p \leq 0.008$$) and BCPT-MS subscore ($p \leq 0.001$) by six months. The BCPT-MS subscale has been shown to be responsive to changes in AIA with scores > 1.5, indicating clinically relevant arthralgia [24,33]. At baseline, there were five of 28 ($18\%$) women with a score > 1.5 on the BCPT-MS subscale, seven of 22 ($32\%$) at three months, and nine of 24 ($38\%$) at six months. The BCPT-hot flash subscore also significantly increased by six months ($$p \leq 0.005$$). There was no change in the other BCPT subscores (nausea, bladder control, vaginal problems, cognitive problems, weight problems, and arm problems) across the 6-month study period. WOMAC-pain significantly increased across time ($$p \leq 0.047$$); however, only eight of 24 women experienced a worsening of their symptoms. The mean ± SD change in the pain score for these eight women was 18.8 ± 7.9. WOMAC-stiffness also significantly increased ($$p \leq 0.031$$), which was driven by 11 of 24 women who experienced a worsening of their symptoms (27.3 ± 12.3 point change from baseline to six months for those 11 participants). Changes in the physical function subscore or the total score were not statistically significant. However, 14 women experienced a worsening of the physical function subscore (9.7 ± 8.0 point change from baseline to six months), and 14 women experienced a worsening of the WOMAC-total score (10.2 ± 8.2 point change from baseline to six months). There were no significant changes in the PHQ-9 total score for depression. ## 3.3. Correlation between Oxylipins and Symptom Scores at Baseline Plasma samples were not available for three participants, thus yielding a sample size of 25 for these analyses. There were four PUFAs (EPA, DHA, ARA, and LA) plus 62 of their oxygenated lipid metabolites (oxylipins) in the original analytical platform. Of the 62 oxylipins, 43 had >$80\%$ of samples with levels above the limit of detection [14]. Table S1 shows the mean ± SD at baseline, three, and six months for the four PUFAs that were quantified, and Table S2 shows the mean ± SD at baseline, three, and six months for the 43 oxylipins. To characterize the relationship between the oxylipins and symptoms, the oxylipin and PUFA levels in the plasma were correlated with the symptom scores at baseline. There were no significant correlations between any oxylipins or PUFAs and the BCPT-total score or the BCPT-hot flash, BCPT-MS, or BCPT-cognitive subscores. Significantly correlated oxylipins with BCPT subscores are as follows: nausea with 9-OxoODE (ρ = 0.41; $$p \leq 0.041$$), bladder control with 8[9]-EET (ρ = 0.42; $$p \leq 0.037$$), vaginal problems with 5[6]-DiHET (ρ = 0.46; $$p \leq 0.024$$), weight problems with 8-HETE (ρ = 0.42; $$p \leq 0.039$$) and 15-HETE (ρ = 0.54; $$p \leq 0.005$$), and arm problems were negatively correlated with 13[14]-EpDPA (ρ = −0.45; $$p \leq 0.024$$), 16[17]-EpDPA (ρ = −0.41; $$p \leq 0.042$$), and 19[20]-EpDPA (ρ = −0.41; $$p \leq 0.042$$). The PHQ-9 total score was significantly correlated with 9-OxoODE (ρ = 0.50; $$p \leq 0.010$$) and negatively correlated with 8[9]-EpETE (ρ = −0.41; $$p \leq 0.039$$). There were no significant correlations between the WOMAC-total, stiffness, physical function, or pain subscores and any oxylipins or PUFAs (data not shown). ## 3.4. Change in PUFAs and Oxylipins PUFA levels were stable across time (Table S1). Two EPA products, 8[9]-EpETE and 8[15]-DiHETE, significantly increased from baseline to six months (both $p \leq 0.05$). There were no significant changes in any other oxylipins (Table S2). ## 3.5. Baseline Oxylipins Predict Changes in Symptom Scores Baseline PUFAs and oxylipins were individually included in the mixed models to test their association with symptom scores across time. No PUFAs were significantly associated with any symptom scores across time. The ARA metabolite derived from 15-LOX, 8-HETE, was positively associated with worsening BCPT-total ($$p \leq 0.017$$), BCPT-hot flash ($$p \leq 0.007$$), BCPT-MS ($$p \leq 0.018$$), WOMAC-pain ($$p \leq 0.001$$), and WOMAC-stiffness ($$p \leq 0.049$$). Two LOX-derived metabolites from alpha linolenic acid were significantly related to worsening BCPT-hot flash: 9-HOTrE ($$p \leq 0.005$$) and 13(S)-HOTrE ($$p \leq 0.025$$). The 5-LOX metabolite of arachidonic acid, 5-HETE, was also significantly related to worsening WOMAC-stiffness ($$p \leq 0.026$$). Given that 8-HETE was the only oxylipin related to several AIA outcomes, Figure 2 illustrates the box plots comparing the baseline batch-adjusted 8-HETE measures among the participants who did and did not experience worsening symptoms (BCPT total, BCPT hot flash, BCPT-MS, WOMAC-pain, and WOMAC-stiffness) over six months. All scores were higher at baseline among those women that went on to have worsening symptoms by six months. ## 4. Discussion The primary purpose of this study was to determine whether any baseline oxylipins or PUFAs could predict who might develop symptoms related to AIA. In this preliminary study, we found that baseline levels of 8-HETE were significantly related to worsening symptoms of AIA from baseline to six months of adjuvant therapy with anastrozole. 8-HETE is produced primarily from arachidonic acid via 15-LOX [34]. Early work showed that 8-HETE is a strong activator of peroxisome proliferator-activated receptor (PPAR) alpha and a weak activator of PPAR gamma, regulators of lipid homeostasis [35], and induces differentiation of preadipocytes [36]. Compounds that induce differentiation of adipocytes have been shown to inhibit aromatase expression and, thus, estrogen synthesis by adipose tissue [37]. To our knowledge, no studies have yet determined whether there is a relationship between 8-HETE and estrogen levels in circulation or in tissues. Another study showed that 8-HETE levels were higher in patients that had experienced a myocardial infarction relative to matched controls, and 8-HETE was significantly positively correlated with the pro-inflammatory cytokine tumor necrosis factor-alpha (TNF-α) [38]. In cell culture, $\frac{12}{15}$-LOX overexpression has been directly linked to increased TNF-α production. These data taken together suggest the possibility that additional suppression of estrogen via 8-HETE as well as an inflammatory profile related to overexpression of 15-LOX (and thus 8-HETE production) predisposes women to AIA and explains the relationship between baseline 8-HETE and AIA development observed in our study. In addition to 8-HETE, two LA metabolites produced via the LOX pathway, 13(S)-HOTrE and 9-OxoODE, as well as the α-LA metabolite 9-HOTrE also produced via LOX were all significantly related to the development of hot flashes by six months. To our knowledge, this is the first study to show an association between these oxylipins and hot flashes. Along with other oxidized LA metabolites, 9-OxoODE has been shown to induce nociceptive hypersensitivity in a rat model [22]. Other LOX products of LA, HODEs, have previously been shown to have pro-nociceptive properties in rodent pain behavioral models [39,40,41] and to be involved in inflammatory pain [42] and Achilles tendinopathy [16]. However, in the current study, there was no association between these LOX metabolites and pain scores on treatment with anastrazole. We also noted that four CYP450 metabolites of DHA, all epoxydocasapentaenoic acids [7[8]-EpDPA, 13[14]-EpDPA, 16[17]-EpDPA, and 19[20]-EpDPA)], were significantly negatively correlated with arm pain as assessed with the BCPT arm subscore. To our knowledge, this is the first report to suggest an association between epoxydocasapentaenoic acids and pain. However, very few studies have investigated the relationship between these four epoxydocasapentaenoic acids and clinical outcomes. One clinical trial showed that they are elevated in hemodialysis patients [43]. Preclinical studies have shown that 19[20]-EpDPA increases the browning of white adipose tissue through the GPR120-AMPK signaling pathway [44]. ω-3 PUFAs have been shown to reduce inflammation through GPR120 [45]. Further, 19[20]-EpDPA is a potent vasodilator in microcirculatory vessels [46], and vasodilators have been shown to reduce different types of pain, including neuropathic [47,48]. Thus, women with higher circulating levels of epoxydocasapentaenoic acids may have reduced inflammation and increased vasodilation, which may explain the negative correlation with arm pain in the present study. Interestingly, none of the PUFAs were associated with any symptom scores. Diets with a high ω-6:ω-3 ratio, associated with a Westernized eating pattern, have been associated with increased inflammatory profiles [49]. Conversely, diets rich in EPA and DHA have been associated with reduced pain and inflammation [50]. One study showed in a rat model that ω-6 fatty acids increased nociception related to nerve damage not inflammation, and dietary replacement with ω-3 PUFAs reverted the phenotype [51]. Here, the overall cohort had a 13.5:1 ω-6:ω-3 ratio, similar to the commonly reported 16:1 ratio seen in populations that consume a Western diet. Studies have shown that ratios below 5:1 are needed to have a beneficial effect on disease risk, and suppression of inflammation in rheumatoid arthritis patients was achieved at 3:1 [52]. In the current study, only two participants had an ω-6:ω-3 ratio less than 5:1. When comparing the ratios of the women that developed any symptoms relative to the women that did not in this study, there was no difference. One study in women on AI showed that supplementation with an ω-3 PUFA significantly reduced AIA; however, the reduction in pain was not different than that in the placebo [53]. Our study suggests that, while the presence of ω-3s is important, the underlying metabolism of PUFA may play a more profound role in the development of AIA, and more targeted prevention may be necessary, such as dual COX and LOX pathway inhibitors. We also sought to characterize the change in oxylipins over time with anastrozole treatment. Overall, PUFAs and oxylipins did not change in the patients with breast cancer in response to administration of the AI anastrozole. Two EPA products, 8[9]-EpETE from the CYP450 pathway and 8[15]-DiHETE that is an sEH product, significantly increased from baseline to six months; however, given the large number of statistical tests and the lack of relationship of these oxylipins with pain outcomes, we cannot render any conclusions. To the best of our knowledge, this is the first study to prospectively characterize oxylipin and PUFA levels in women who started adjuvant anastrozole. Our study also contributes to the literature by prospective longitudinal assessment of AIA symptoms with validated questionnaires over six months. The major limitations of our study are the small sample size and small proportion that developed symptoms of AIA, which limited our ability to interpret any changes in metabolomic profiles. Nonetheless, we are able to contribute data on baseline oxylipin and PUFA profiles in postmenopausal women, which should be explored in larger studies. ## 5. Conclusions In conclusion, we found that the baseline level of the 15-LOX product of AA, 8-HETE, was related to worsening of several AIA symptoms. Epoxydocasapentaenoic acids may also play a role given their anti-inflammatory and vasodilating effects. Future studies should investigate 15-LOX and/or CYP450 as potential targetable pathways for AIA management. ## References 1. Goss P.E., Ingle J.N., Pritchard K.I., Robert N.J., Muss H., Gralow J., Gelmon K., Whelan T., Strasser-Weippl K., Rubin S.. 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--- title: The Composition of Subgingival Microbiome in Hidradenitis Suppurativa and Periodontitis Patients authors: - Beata Jastrząb - Barbara Paśnik-Chwalik - Katarzyna Dębska-Łasut - Tomasz Konopka - Piotr K. Krajewski - Jacek C. Szepietowski - Łukasz Matusiak journal: Pathogens year: 2023 pmcid: PMC10052120 doi: 10.3390/pathogens12030377 license: CC BY 4.0 --- # The Composition of Subgingival Microbiome in Hidradenitis Suppurativa and Periodontitis Patients ## Abstract Hidradenitis suppurativa (HS) is a chronic inflammatory disorder of the pilosebaceous unit of the intertriginous body areas. Recent findings have suggested the association between periodontitis and HS. This investigation aimed to characterize and compare the composition of subgingival microbiome between HS, periodontitis, and control patients. The nine crucial perio-pathogenic species and total bacteria were analyzed using RT-PCR based tests in samples collected from 30 patients with periodontitis, 30 patients with HS and 30 controls. Patients with HS were excluded if they had periodontitis and patients with periodontitis were excluded if they had HS. The mean total bacteria count was significantly higher in HS and periodontitis samples than in control samples ($p \leq 0.05$). The majority of perio-pathogens tested were more frequently detected in HS and periodontitis groups than among controls. Treponema denticola was the most common pathogen in individuals with HS ($70\%$) and periodontitis ($86.7\%$), while among controls Capnocytophyga gingivalis was the most frequently detected isolate ($33.2\%$). The results of the present investigation demonstrated that HS and periodontitis patients share some similarities in their subgingival microbiome composition. ## 1. Introduction Hidradenitis suppurativa (HS) is a chronic inflammatory dermatosis that is characterized by deep-seated nodules and abscesses that rupture and lead to sinus tracts formation and scarring. The estimated prevalence of HS ranges from under $1\%$ to $4\%$. These numbers may be underestimated as underdiagnosis or inadequate diagnosis are common events. The age of onset of the disease is usually between puberty and the fourth decade of life, most commonly from age 21 to 29 [1]. This condition most commonly involves the intertriginous skin of the axillary, inguinal, inframammary and genital regions of the body [2]. Because of the physical appearance, painful flare-ups and malodorous discharge, this condition may have a negative psychosocial impact on affected individuals [1,2]. The pathogenic mechanisms underlying HS are not fully elucidated, but genetic predisposition, environmental factors, host-microbe interactions, and immune dysregulation seem to be involved in the disease development [3]. Periodontitis is a multifactorial inflammatory disorder caused by dysbiotic microflora and excessive host response, resulting in progressive destruction of the tooth-supporting apparatus. In the course of the disease, the gingival sulcus is deepened to form a periodontal pocket colonized by perio-pathogens [4]. Although more than 700 different types of bacteria reside in the oral cavity, only a small portion of these microorganisms may trigger the destruction of periodontal tissues [5]. Periodonto-pathogenic species were first grouped by Socransky [6] in five colorimetrically coded complexes—green, yellow, orange, red and purple. The particular dental plaque bacteria colonize the gingival sulcus in the specified order via cell-to-cell coaggregation [7]. Oral Streptococci are the dominant species of the oral cavity and the pioneer colonizers of tooth surfaces [8]. Streptococcus species provide additional binding sites for the subsequent deposition of secondary colonizers. The primary as well as secondary colonizers are considered early colonizers and involve green, yellow and violet complexes and Actinomyces [9]. The growth of these species groups leads to the proliferation of mainly gram-negative anaerobic bridging and late colonizers. The bridging colonizers form the orange complex and enable the multiplication of late colonizers including the red complex species [10]. The association between periodontitis and various autoimmune skin diseases has been recognized previously [11,12,13,14,15,16]. Several cross-sectional investigations reported a higher incidence of periodontitis and more advanced periodontal disease involvement among patients with psoriasis than among controls. This association was positively correlated with psoriasis severity [11,12]. Moreover, a bi-directional relationship between psoriasis and periodontitis has been suggested, with psoriasis contributing to periodontitis, and vice versa [11,12,17]. Psoriasis has also been demonstrated to be associated with characteristics of salivary microbiota and salivary levels of inflammation-related proteins, which differ from those of individuals with periodontitis and controls [18]. Noteworthy, a significantly higher number of missing teeth and lower radiographic bone level were noticed in psoriasis cases compared to control group [11]. Patients with oral pemphigus vulgaris and mucous membrane pemphigoid appear to be more susceptible to periodontitis, that in turn can potentially induce bullous disorders [19]. Individuals with mucous membrane pemphigoid have more gingival inflammation and worse periodontal status than a control population [13]. Significantly higher values of plaque index, probing depth and clinical attachment level were noticed in pemphigus vulgaris patients than among healthy subjects. Several studies revealed significantly worse periodontal status in patients with lichen planus compared to healthy controls [20,21]. Another study showed that increased plaque and calculus deposits are connected with a significantly higher prevalence of atrophic-erosive gingival lesions in individuals with oral lichen planus [22]. Periodontitis has also been linked with the development of other immune-mediated inflammatory disorders, such as inflammatory bowel diseases (IBD), psoriatic arthritis and rheumatoid arthritis [23,24,25]. Several studies demonstrated a high prevalence of periodontitis in patients with IBD [25,26]. Furthermore, IBD patients harbored higher levels of pathogenic bacteria in inflamed subgingival sites compared to patients with periodontitis [26]. The strict association between rheumatoid arthritis and periodontitis has been revealed. Individuals with rheumatoid arthritis were significantly more frequently diagnosed with periodontitis. This prevalence has been reported to be higher in patients at the earliest stages of the disease and in seropositive subjects [24]. Compelling epidemiological evidence confirms that the risk of periodontal disease is elevated for psoriatic arthritis. Periodontitis severity, as defined by clinical attachment level, was higher in the patients with psoriatic arthritis than in the reference group [12,23]. However, the current knowledge on oral health and periodontal status in HS patients is limited. Recent findings suggested that periodontal disease may be linked with HS [27]. In this study, periodontitis was significantly more frequently diagnosed in patients with HS than among controls. HS and periodontitis seem to share some pathogenic similarities. The IL-23/IL-17 axis plays an essential role in the development and progression of periodontitis as well as HS [28,29]. Several studies provide evidence that HS can be associated with specific alterations in the skin microbiome and toll-like receptors (TLRs) act as important factors in the development of both entities [30,31,32]. Although common inflammatory pathways are implicated in the pathogenesis of these disorders, the exact mechanism of relationship between them is unknown. The primary objective of the present study was to characterize the composition of periodontal pathogens and evaluate the quantity of salivary microbiota in HS patients. We compared these data to those in patients with periodontitis and healthy controls, to examine the association between HS and periodontitis. ## 2.1. Study Groups A cross-sectional study was performed from December 2021 until May 2022. Individuals with HS were recruited at the Department of Dermatology, Venereology, and Allergology, Wroclaw Medical University, while individuals with clinical features typical of periodontitis were recruited at the Department of Periodontology, Wroclaw Medical University. A total of 30 healthy controls, 30 HS patients and 30 periodontitis patients were enlisted in the study. The general exclusion criteria were as follows: other systemic diseases, pregnancy, breast-feeding, being under the age of 18, and the use of local and systemic antimicrobials ≤3 months prior to the study baseline. Subjects with HS were excluded if they had periodontitis, and subjects with periodontitis were excluded if they had concomitant HS. The study was approved by the local ethical committee (consent no. $\frac{919}{2021}$, date: 26 November 2021). The objective of the study was clarified and written informed consent was received from each participant before the commencement of the study. ## 2.2. Periodontal Evaluation Periodontal examination was conducted in all patients by a single examiner using the WHO periodontal probe with a probing force of not more than 20 g. The dentition was divided into sextants, and each sextant was examined only if there were two or more teeth present and not indicated for extraction. Diagnosis of periodontitis was established after a complete periodontal inspection using probing depth and attachment loss evaluation. In the current study, periodontitis was defined as the presence of interdental clinical attachment loss (CAL) at two or more non-adjacent teeth or the presence of oral or buccal CAL no less than 3 mm with pocketing >3 mm at ≥two teeth [33]. The severity and extent of the management required were assessed using the staging (stage I: initial periodontitis; stage II: moderate periodontitis; stages III and IV: severe periodontitis), while the progression rate of the periodontitis was assessed using the grading (grade A: slow; grade B: moderate; grade C: rapid rate of progression) [34]. ## 2.3. Dermatological Evaluation All participants in the study were evaluated by a dermatologist for systemic status, cutaneous and mucosal lesions. Patients diagnosed with HS without any other concomitant skin, periodontal or systemic disorder were enrolled in the HS group. In addition, patients from periodontitis and control groups were excluded if they were diagnosed with any chronic cutaneous or systemic disease. HS severity stage was assessed in patients from HS group using the Hurley staging system and International Hidradenitis Suppurativa Severity Score System (IHS4). In addition, after establishment of the IHS4 score, the subjects were subsequently divided into 3 groups (mild, moderate, and severe disease). Cut-off points were employed for mild (≤3 points), moderate (>3 and ≤10 points) and severe HS (>10 points) [35,36]. ## 2.4. Subgingival Plaque Sample Collection The deepest periodontal pocket was identified for every study subject during the clinical periodontal examination and subgingival bacterial plaque samples were obtained. Before sampling, the supragingival bacterial plaque was cleaned, and then each tooth was isolated with cotton rolls and dried thoroughly with an air syringe. A sterile paper point included in the diagnostic kit was introduced inside each gingival sulcus for 20 s using tweezers. The samples were loaded into test tubes and shipped to the MIP International Pharma Research GmbH Laboratory located in Germany, where sample processing was performed. ## 2.5. Microbiological Analysis PET Test® plus is a CE-certified medical device, that is manufactured by MIP Pharma GmbH. The exact protocol for the microbiological examination procedure is confidential to the company. Sample analysis was conducted using a real-time polymerase chain reaction (RT-PCR). The PCR-based test allowed detection and quantification of nine crucial perio-pathogens (Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, Prevotella intermedia, Peptostreptococcus micros, Fusobacterium nucleatum, Eubacterium nodatum, Capnocytophaga gingivalis and Aggregatibacter actinomycetemcomitans) in the study’s samples. Free strand sections of DNA were obtained from lysed bacterial cells and were subsequently subjected to amplification and hybridization using fluorescence-stained starters characteristic of particular periodontal pathogens. The quantitative analysis of the samples was carried out with a reader that measures fluorescence intensity compared to that in reference specimens. According to information from the manufacturer, the threshold determination for all analyzed perio-pathogens was approximately 103 bacteria. ## 2.6. Statistical Analysis Statistical analysis of the obtained results was performed with the use of the IBM SPSS Statistics v. 26 (SPSS INC., Chicago, IL, USA) software. All data was assessed for normal or abnormal distribution. The minimum, maximum, mean, and standard deviation were calculated. Differences in quantitative variables between two groups, depending on the normality, were evaluated using the t-Student test or Mann–Whitney U test. Correlation between quantitative data were assessed, depending on normality, with Pearson’s and Spearman’s correlations. For qualitative data, the Chi-squared test was used. Differences in number of copies of perio-pathogens between more than two groups were assessed, depending on the normality, with the use of the one-way analysis of variance on ranks (ANOVA) or Kruskal-Wallis test with the adjustment according to the Bonferroni correction. A two-sided p of less than 0.05 was considered statistically significant. ## 3. Results The HS, periodontitis and control groups consisted of 12 males and 18 females aged 36.1 ± 11.64 (range, 20–75) years, 12 males and 18 females aged 41.5 ± 9.78 (range, 27–53) years, and 10 males and 20 females aged 33.5 ± 7.40 (range, 20–52) years, respectively. The severity of the disease in the HS group in the majority of patients (14 patients, $46.6\%$) was assessed as Hurley stage II, in eight patients ($26.7\%$) as Hurley stage I, and in eight patients ($26.7\%$) as Hurley stage III. As for IHS4, 12 patients ($40.0\%$) presented with moderate HS, 12 patients ($40.0\%$) presented with severe HS, and six patients ($20.0\%$) presented with mild HS. The mean IHS4 score among HS patients was assesed as 19 ± 22.28 points. The periodontitis stage in the periodontits group in the majority of individuals (14 patients, $46.6\%$) was assessed as stage IV, in 12 patients ($40.0\%$) as stage III, in three patients ($10.0\%$) as stage II, and in one patient ($3.4\%$) as stage I. The most frequent grade was grade B (17 patients, $56.7\%$), while grade C was present in 13 individuals ($43.3\%$), and none of the patients with periodontitis presented with grade A. The average copy-count number of total bacteria was significantly higher in the HS and periodontitis samples than in the control samples ($$p \leq 0.04$$) (Figure 1). Statistically significant differences in the prevalence of periopathogens between groups were found for all bacterial species except A. actinomycetemcomitans (Figure 2). Most perio-pathogenic bacteria were more frequently detected in the subgingival plaque both in HS and periodontitis patients than in healthy controls (Table 1 and Table 2). T.denticola was the most frequently isolated pathogen in individuals with HS ($70\%$) and periodontitis ($86.7\%$), whereas among controls C. gingivalis was the most common microorganism ($33.2\%$). The microbiological results revealed significant differences in the prevalence of periopathogens between HS and periodontitis groups concerned the following species: P.gingivalis, T. forsythia, P. intermedia, P. micros and F. nucleatum. The first four above-mentioned species were significantly more common among periodontitis patients, while F. nucleatum was identified more frequently in HS individuals (Table 3). The average copy number of all periopathogenic bacteria except A.actinomycetemcomitans differed significantly between groups (Figure 3). The average copy-count number of T. denticola, T. forsythia, P. micros and C. gingivalis was significantly higher in both periodontitis and HS groups compared to controls (Table 1 and Table 2). P.gingivalis and P. micros species were expressed at higher level in periodontitis patients than in HS patients (Table 3). Noteworthy, there was no correlation between total bacterial count as well as quantity of particular periopathogens and HS severity assessed both with Hurley and IHS4 scales in the HS group. Similarly, the duration of the disease was not correlated with the copy number of periodontal pathogens. ## 4. Discussion Dental plaque plays a crucial role in the patho-etiology of periodontal disease [37]. Many studies in the literature focus on whether various autoimmune disorders contribute to periodontitis, and conversely, whether periodontitis may influence systemic diseases’ development and spread [25,38,39,40]. The current knowledge on periodontal status in HS is limited. Recent data showed a higher prevalence of periodontitis among HS patients, suggesting possible links between these entities [27]. Our study revealed that HS patients, similarly to periodontitis patients, tended to be more frequently infected with perio-pathogenic bacteria compared to orally healthy controls. Furthermore, the total bacteria count and the DNA copies number of a large portion of perio-pathogenic species were significantly higher in HS and periodontitis groups than among controls. These findings suggest that HS may influence oral homeostasis and HS individuals might be more prone to periodontal disease. On the other hand, periodontal pathogens may also enhance HS progression by promoting an inflammatory milieu. Bacteria genera that were increased in occurrence in HS patients without periodontal disease compared to orally healthy controls were P.gingivalis, T. denticola, T. forsythia, P. micros, F. nucleatum and C. gingivalis. The three first species mentioned above form the red complex that acts as a pathogenic consortium in periodontitis. P. micros and F. nucleatum constitute the orange complex, while C. gingivalis belongs to the green complex [6]. P.gingivalis is a gram-negative, non-motile, anaerobic bacterium of the oral cavity [41]. This bacterial species has been recognized for its role in the regulation of distant inflammatory responses connected with chronic conditions and autoimmune diseases [42]. Several investigations reported that P.gingivalis exposure might be linked to systemic diseases such as rheumatoid arthritis (RA), inflammatory bowel diseases, diabetes mellitus and atherosclerosis [43,44,45,46]. P. gingivalis has been referred to as a master of immune subversion, utilizing unique and intricate sabotage techniques to evade and weaken the host’s immune system [47]. It modifies the functions of various innate immune signaling cascade components such as the complement system, toll-like receptors (TLRs), macrophages, neutrophils, dendritic cells, and T cells [48]. The lipopolysaccharide (LPS) of P. gingivalis exhibits two isoforms responsible for the dual inflammatory response via TLRs modulation. The penta-acylated LPS induces TLR4 and TLR2 when tetra-acylated LPS is a TLR4 antagonist and TLR2 an agonist [49]. P. gingivalis triggers the release of IL-1, IL-6, IL-8, and TNF-α, acting by TLR4/TLR2 in host cells [50]. IL-1β production, maturation, and secretion are tightly modulated by TLR signaling as well as inflammasome activation [51]. P. gingivalis stimulated innate immune cells by the nucleotide-binding domain-like receptor protein 3 (NLRP3) inflammasome. The NLRP3 inflammasome and the following response from the IL-1 family might play an important role in periodontal disease triggered via P. gingivalis challenge through sustained inflammatory milieu [52,53]. T. denticola is a motile oral spirochete, while T. forsythia is a non-motile, rod-shaped microorganism [54,55,56,57]. A recent study examined the correlation between systemic lupus erythematosus (SLE) disease activity and severity and perio-pathogenic bacteria and reported that abundance of T. denticola and T. forsythia was increased in SLE-active periodontal sites compared to that of SLE-inactive and controls [58]. Moreover, serum antibody titers against T. denticola, P. gingivalis, A. actinomycetemcomitans and C. ochracea species were positively correlated with anti-dsDNA titers and reduced complement levels in SLE patients [59]. The study on the association of RA with periodontopathic bacterial infection revealed that serum and synovial fluid antibodies to T. forsythia, P. gingivalis, P. intermedia, and Prevotella melaninogenica were detected in RA patients [60]. Several studies showed that T. denticola enhances the synthesis of various cytokines, including IL-1β, IL-6, IL-8, and TNF-α from different cell types [61,62,63,64]. Conversely, it has also been demonstrated that T. denticola suppresses IL-8 production [65]. The gram-positive anaerobic coccus P. micros was found to be above the detection threshold in RA patients [66]. This bacterium has been reported to induce intracellular signaling mechanisms, resulting in an increased production of pro-inflammatory cytokines such as TNF- α, IL-1beta and IL-6 and chemokines through macrophages [6,67,68]. Noteworthy, C. gingivalis, which is a gram-negative rod, has also been shown to induce the release of IL-6 [69,70]. F. nucleatum was the only perio-pathogenic bacterium that was more prevalent among HS individuals than among periodontitis patients. This gram-negative pathogen has been reported to be associated with many systemic diseases, including atherosclerosis, adverse pregnancy outcomes, polycystic ovary syndrome, colorectal cancer and RA [71,72,73,74,75]. F. nucleatum induces a spectrum of host immune responses and acts as a potent stimulator of inflammatory cytokines. Chronic local infection of F. nucleatum initiates the up-regulation of inflammatory pathways. It stimulates various cytokines, such as IL-6, IL-8 and TNF-α [76,77]. Moreover, chronic inflammation caused by F. nucleatum contributes to the progression of various systemic diseases via modulation of TLRs and promoting CD4+ T cell proliferation and differentiation in Th1 and Th17 [78,79,80]. The role of dysbiosis in HS development is not fully elucidated [32]. The profile of skin microbiota changes with the progression of the disease, but it remains to be determined if this is a primary or secondary event [81]. The preponderance of Staphylococcus was noted in early HS lesions, while gram-negative anaerobic bacteria such as Porphyromonas and Prevotella were predominantly identified in HS tunnels and chronic suppurating lesions [81,82]. Patients affected with HS present elevated levels of pro-inflammatory cytokines, including TNF-α, IL-1β and IL-6, which are also implicated in perio-pathogens-induced immune responses [2,50,67,68]. The expression of IL-1β was significantly increased in the HS lesional and perilesional skin compared with uninvolved HS skin or healthy control skin [83]. TNF-α inhibitors have demonstrated a significant efficacy in individuals with moderate to severe HS [84]. Studies revealed increased serum IL-6 levels in Hurley II and III HS individuals, indicating that IL-6 may participate in the development of HS [85,86]. Moreover, TLRs and NLRP3 inflammasome, which are involved in periodontal bacteria pathogenicity, play also a role in the pathogenesis of HS [87,88]. Some limitations apply to the study. The first concerns the relatively low number of included individuals with HS, resulting from the single-center setting. Nevertheless, as significant differences in the composition of subgingival microbiota were noted, the number of participants might have been sufficient. Furthermore, the lack of follow-up examinations is another limitation and should be considered in future studies. ## 5. 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--- title: Immune Response to CoronaVac and Its Safety in Patients with Type 2 Diabetes Compared with Healthcare Workers authors: - Bothamai Dechates - Thachanun Porntharukchareon - Supamas Sirisreetreerux - Phonthip Therawit - Supanat Worawitchawong - Gaidganok Sornsamdang - Kamonwan Soonklang - Kriangkrai Tawinprai journal: Vaccines year: 2023 pmcid: PMC10052125 doi: 10.3390/vaccines11030684 license: CC BY 4.0 --- # Immune Response to CoronaVac and Its Safety in Patients with Type 2 Diabetes Compared with Healthcare Workers ## Abstract Background: Vaccines for SARS-CoV-2 have been critical for preventing disease. Previous research showed patients with diabetes have impaired immunity. This study aimed to determine the immunity to coronavirus after CoronaVac by comparing patients with type 2 diabetes (T2D) and healthcare workers (HCW). Materials and methods: A prospective cohort study evaluated immune responses and safety after two doses of CoronaVac in T2D and HCW groups at Chulabhorn Hospital. The levels of total antibodies against the receptor-binding domain (anti-RBD) of the SARS-CoV-2 spike protein at baseline and 4 weeks after vaccination were collected. The level of anti-RBD concentrations was reported as geometric mean concentration (GMC) and compared between groups using the geometric mean ratio (GMR). Results: 81 participants were included; 27 had T2D and 54 were HCW. After complete vaccination, anti-RBD concentrations were not significantly different between T2D (57.68 binding antibody units (BAU)/mL, $95\%$ confidence interval (CI) = 29.08; 114.44) and HCW (72.49 BAU/mL, $95\%$ CI = 55.77; 94.22) groups. Subgroup analysis showed the GMC of anti-RBD was significantly lower in T2D patients with dyslipidaemia (50.04 BAU/mL) than in T2D patients without dyslipidaemia (341.64 BAU/mL). Conclusions: The immune response at 4 weeks after two doses of CoronaVac did not significantly differ between patients with T2D and HCW. ## 1. Introduction Beginning with the initial outbreak in December 2019, as of February 2022, the cumulative number of confirmed SARS-CoV-2 cases worldwide had reached more than 400 million, with nearly 6 million deaths. The World Health Organization (WHO) named the disease caused by SARS-CoV-2 coronavirus disease 2019 (COVID-19) [1]. Data from several countries in 2020 showed that 14–$19\%$ of ill patients required hospitalization, and 3–$5\%$ of cases were severe or had complications requiring admission to intensive care units [2]. Diabetes mellitus is one of the underlying noncommunicable diseases that increases the risk for greater severity, more complications and higher mortality associated with COVID-19, likely because patients with diabetes have impaired adaptive and innate immune responses [3]. There are several proposed mechanisms for such complications. One mechanism involves many aspects of white blood cell dysfunction, including neutrophil function and monocyte function, adherence, chemotaxis, phagocytosis, bacterial killing and respiratory burst [4,5,6,7,8,9,10,11,12,13,14]. Other studies supporting this dysfunction found that leukocyte function, granulocyte adherence and phagocytic activity were significantly improved when hyperglycaemia was treated to reduce mean fasting plasma glucose levels [8,11,15,16,17]. Another proposed mechanism in patients with diabetes exposed to transient elevations in glucose involves a rapid reduction in lymphocytes [18]. Hyperglycaemia in diabetic patients was associated with a reduction in T cells, both CD-4 and CD-8 subsets [19]. B- and T-cell responses were compromised and more affected in obese people with type 2 diabetes mellitus [20]. The coronavirus vaccines are important for people with diabetes mellitus to prevent infection and reduce the severity of the infection. Currently, there are several types of coronavirus vaccines, including live-attenuated, inactivated, protein subunit and nucleic acid vaccines. CoronaVac is a Vero-cell-based, aluminium hydroxide-adjuvanted and β-propiolactone-inactivated vaccine [21]. Following the Thailand government’s policy of COVID-19 vaccination in the first phase, a large population in Thailand was vaccinated with CoronaVac. Each 0.5 mL dose of CoronaVac vaccine contains 3 µg of inactivated SARS-CoV-2 virus [22]. The vaccine is intramuscularly administered as two doses, 3 weeks apart (at day 0 and day 21). It is established that patients with diabetes have a lower immunity than the general population. However, there are limited data on the immune response to CoronaVac in patients with diabetes. Therefore, this study aimed to assess the antibody response at 4 weeks after the second dose of CoronaVac, by comparing patients with type 2 diabetes and healthcare workers in Thailand. ## 2.1. Study Design and Participants We conducted a single-centre, age- and sex-matched prospective cohort 1:2 study that evaluated immune responses and safety at 4 weeks after two doses of CoronaVac in patients with type 2 diabetes and healthcare workers at Chulabhorn Hospital. Patients with type 2 diabetes who received CoronaVac were enrolled if they were at least 18 years old. It is important to note that the control group in this study consisted of Chulabhorn Royal Academy employees who were matched in terms of age (within 5 years) and sex to patients with type 2 diabetes. The control group included a range of occupations, such as healthcare providers, healthcare assistants and back-office employees. Importantly, most individuals in the control group had no underlying diseases and were mostly non-diabetic. As such, they may provide a reasonable representation of the general population. Participants with history of COVID-19 infection, cancer, pregnancy, breastfeeding and history of acute illness or blood transfusion within 90 days were excluded. The study was conducted from 1 June to 31 August 2020. This study was approved by the Ethics Committee for Human Research, Chulabhorn Research Institute. All the patients provided written informed consent before participation. This trial was registered with thaiclinicaltrials.org (TCTR20220720001). ## 2.2. Data Collection and Definitions Data collection included age, sex, nationality, existing diseases (diabetes mellitus, hypertension, dyslipidaemia, coronary artery disease, chronic kidney disease, end-stage renal disease and cirrhosis) and haemoglobin (Hb) A1C levels in the 90 days before or after, number of current medications for diabetes, insulin use, glucagon-like peptide 1 receptor agonist use, body mass index (BMI) and history of steroid use in the previous 90 days. Diabetes mellitus was defined according to a history of having been diagnosed with diabetes or history of anti-diabetes medication. Hypertension was defined according to systolic blood pressure of ≥140 mmHg or diastolic blood pressure of ≥90 mmHg, or a history of anti-hypertensive therapy. Overweight and obesity were defined according to BMI. Dyslipidaemia was defined as total cholesterol levels ≥ 220 mg/dL or a history of lipid-lowering therapy. Chronic kidney disease and end-stage renal disease were defined according to creatinine clearance or dialysis status. Other diseases were defined by data in medical records. ## 2.3. Procedure CoronaVac was administered as a 0.5 mL dose intramuscularly injected into the deltoid muscle, with two doses 3 weeks apart (at day 0 and day 21). Reactogenicity was monitored for 30 min after vaccination for immediate events. Thereafter, reactogenicity follow-up was continued at home at days 1 and 7 after vaccination. A 6 mL blood sample was collected to determine serum levels of the total antibodies against the receptor-binding domain (anti-RBD) of the SARS-CoV-2 spike protein at baseline (before the first vaccine dose), and then 4 weeks after the second dose. Anti-RBD concentrations were measured by an electrochemiluminescence immunoassay Elecsys Anti-SARSCoV-2 S (Elecsys-S) kit (Roche Diagnostics, Mannheim, Germany). The range of measurement of anti-RBD antibodies was 0.4–2500 U/mL. The cut-off value for a positive result was >0.8 U/mL, referenced from the manufacturer. Recently, the WHO released an international standard for the measurement of SARS-CoV-2 immunoglobulin that corresponds to the body’s immune response after natural infection or vaccination as binding antibody units (BAU) [23]. Therefore, we used this equation (Elecsys-S $U = 0.972$ × BAU) to transform Elecsys-S data from U to BAU [24]. ## 2.4. Outcomes Our primary goal was to determine the geometric mean concentration (GMC) of anti-RBD antibodies for SARS-CoV-2 at 4 weeks after two doses of CoronaVac in patients with type 2 diabetes and healthcare workers. Comparison of GMC between groups used the geometric mean ratio (GMR). Secondary outcomes were other factors affecting the GMC of anti-RBD in diabetic patients and adverse events after two doses of vaccine. ## 2.5. Sample Size A previous study of the ChAdOx1 nCoV-19 (AZD1222) vaccine showed that the GMC of anti-RBD antibodies for SARS-CoV-2 was 15.13 BAU/mL in patients with diabetes versus 40.2 BAU/mL in healthcare personnel. The standard deviation was 52 [25]. The sample size was calculated to achieve a power of $80\%$ with a significance level of $5\%$ (alpha = 0.05). The number of subjects required was expected to be 68. This estimate was based on the assumption that $10\%$ of the participants may be lost to follow-up. ## 2.6. Statistical Analysis Data entry and analysis were carried out using STATA/SE version 16.1. Continuous variables are shown as the mean ± SD or median and interquartile range. Categorical variables are shown as number and percentage. Anti-RBD antibodies for SARS-CoV-2 were shown as GMC and $95\%$ confidence intervals (CI). Comparison of GMC between groups used multiple linear regression analysis, with $p \leq 0.05$ indicating statistical significance. ## 3.1. Baseline Characteristics A total of 81 participants were included: 27 patients with type 2 diabetes and 54 healthcare workers. Mean ages were not different between groups: 52.48 and 52.11 years for patients with diabetes and healthcare workers, respectively. Baseline characteristics are described in Table 1. Most of the diabetic cases were obese. The median body weight was 76 kg and median BMI was 28.01 kg/m2 in patients with type 2 diabetes. Most healthcare workers were overweight. The median body weight was 65.25 kg and median BMI was 23.61 kg/m2. The majority of patients with diabetes had successful glycaemic control, and the mean Hb A1C was $7.04\%$. Only seven of the diabetic patients ($25.94\%$) had an Hb A1C greater than $8\%$. The mean number of diabetes drugs used was three. Of the patients with diabetes, four used insulin and others had comorbidities, including dyslipidaemia ($92.59\%$), hypertension ($66.67\%$), coronary artery disease ($11.11\%$), cirrhosis ($11.11\%$) and chronic kidney disease ($3.7\%$). There were no patients positive for human immunodeficiency virus or end-stage kidney disease in this study. One of the patients with diabetes used steroids. The study revealed that a small proportion of healthcare workers (9 out of 54) had comorbidities, with the most prevalent comorbidities being hypertension (present in $14.81\%$ of individuals), dyslipidaemia (present in $9.26\%$ of individuals) and coronary artery disease (present in $1.85\%$ of individuals) (Table 1). ## 3.2.1. Primary Outcome Regarding the antibodies present after vaccination, the GMC of anti-RBD antibodies for SARS-CoV-2 at 4 weeks after two doses of CoronaVac was 57.68 BAU/mL ($95\%$ CI 29.08; 114.44) and 72.49 BAU/mL ($95\%$ CI 55.77; 94.22) in age/sex-matched patients with diabetes and healthcare workers, respectively. The GMR between the groups, adjusted for BMI and comorbidities, was 0.85 ($95\%$ CI 0.32; 2.26) and was not significantly different ($$p \leq 0.739$$, Table 2 and Figure 1). ## 3.2.2. Secondary Outcomes A multiple linear regression model was used to compare other factors affecting the GMC of anti-RBD antibodies at 4 weeks after two doses of CoronaVac in patients with diabetes. Potential confounding factors included age, sex, Hb A1C levels, number of current diabetes medications, insulin use, glucagon-like peptide 1 receptor agonist use, BMI, hypertension, dyslipidaemia, coronary artery disease, chronic kidney disease, end-stage renal disease, cirrhosis and steroid use within 90 days (Table 3). Unexpectedly, the factors corresponding to significant differences in anti-RBD antibodies levels in patients with diabetes included dyslipidaemia. The GMC of anti-RBD antibodies was 50.04 and 341.64 BAU/mL in type 2 diabetic patients with or without dyslipidaemia, respectively. The GMR between groups was 0.15 ($95\%$ CI 0.07; 0.30), $p \leq 0.001.$ Only one case had a history of steroid use, so we could not draw a conclusion about the effect of steroid use. Analysis for other confounding factors found no significant differences in the GMC of anti-RBD antibodies between other subgroups. ## 3.2.3. Reactogenicity Reactogenicities after two doses of vaccine are shown in Table 4. The most common reactogenicities in patients with type 2 diabetes were injection site reaction and myalgia (as shown in Figure 2), whereas the most common adverse events in healthcare workers were myalgia followed by headache (as shown in Figure 3). Four participants with type 2 diabetes ($14.8\%$) and one healthcare worker ($1.85\%$) had injection site reactions ($$p \leq 0.040$$). Other adverse events, such as fever, headache and fatigue, were not different between the groups. ## 4. Discussion The current study found that 4 weeks after immunization with two doses of CoronaVac, the GMC of anti-RBD antibodies for SARS-CoV-2 in patients with diabetes was not significantly lower than healthcare workers. This result is consistent with previous studies of influenza vaccines, which used inactivated vaccines such as CoronaVac. The antibody responses to an influenza vaccine, as measured by hemagglutination inhibition assays, was similar between well-controlled diabetic elderly and healthy elderly cases [26]. Several previous studies conducted on COVID-19 vaccines’ immunogenicity and effectiveness in patients with diabetes compared to healthy controls. Most of these studies have reported lower vaccine effectiveness and immunogenicity in patients with diabetes when compared to healthy controls [27,28]. However, our study yielded different results, which could be attributed to various factors, such as the type of COVID-19 vaccine used, sample size, levels of glycaemic control and characteristics of the control group. The first factor, vaccine type, is noteworthy, as previous systematic reviews have shown that the majority of COVID-19 vaccines studied are mRNA and recombinant vaccines, while inactivated vaccines comprise a minority. Studies comparing the immunogenicity of different COVID-19 vaccine types have demonstrated that participants who received two doses of Moderna had significantly higher total antibody responses to the receptor-binding domain (RBD) than those who received two doses of AZD1222 ($p \leq 0.0001$) or two doses of Sinopharm ($$p \leq 0.03$$) [29]. These findings align with a systematic review that reported lower efficacy and immunogenicity of inactivated vaccines against COVID-19 infection compared to mRNA and recombinant vaccines [30]. The aforementioned studies have demonstrated that different types of vaccines exhibit varying levels of vaccine effectiveness and immunogenicity. Inactivated vaccines, for instance, have lower immunogenicity and vaccine effectiveness than other vaccines. Consequently, the use of inactivated vaccines in this study could result in a lack of difference in immunogenicity between patients with diabetes and healthcare workers. However, prior research conducted on specific groups, such as those receiving inactivated vaccines for COVID-19, has yielded varying results. For instance, a study examining the CoronaVac and Sinopharm vaccines in patients with diabetes found that anti-RBD-IgG and neutralizing antibodies (Nabs) levels were significantly lower in patients with diabetes ($$n = 89$$) than in healthy controls ($$n = 100$$) after vaccination [31]. Conversely, another study reported no statistically significant differences in immunogenicity between patients with diabetes and healthy controls. For example, a study on the Vero-cell-derived inactivated COVID-19 vaccine in older patients with hypertension and diabetes mellitus found no statistically significant differences in GMT-neutralizing antibody post-vaccination between groups, including elderly patients with hypertension ($$n = 325$$), diabetes ($$n = 328$$), combined hypertension and diabetes ($$n = 292$$) and healthy controls ($$n = 468$$) [32]. Another study involving 76 patients with diabetes ($26.4\%$), who received Pfizer-BioNTech and Sinopharm vaccines and underwent multivariable regression analysis, found no statistically significant negative impact of diabetes mellitus on IgG titre [33]. Hence, it is possible that additional factors may have contributed to the divergent outcomes observed in various studies. One such factor is the level of glycaemic control, which has been shown to impact the immune response. This notion is supported by previous research that demonstrated that diabetic patients with well-controlled blood glucose levels exhibited a more robust immune response following COVID-19 vaccination compared to those with poorly controlled glucose levels [34]. Notably, the majority of the patients with diabetes in our study had well-controlled blood glucose levels, with $60\%$ of them having an HbA1c level of less than or equal to $7\%$. This may have resulted in no observable differences in the level of immunity between the group of patients with diabetes and healthcare workers. The characteristics of the control group may be another potential contributing factor. Several studies have demonstrated that body weight and BMI can impact the level of immunogenicity induced by COVID-19 vaccines. For instance, a systematic review and meta-analysis found that obesity was significantly associated with reduced antibody responses to SARS-CoV-2 vaccines, regardless of whether mRNA vaccines, adenovirus vector vaccines or inactivated virus vaccines were used [35]. The findings of a study on inactivated COVID-19 vaccine were consistent with this systematic review and meta-analysis. The study reported that the S-RBD-neutralizing antibody was significantly lower in the BMI >25.00 kg/m2 group compared to the 21.00–25.00 kg/m2 group ($p \leq 0.05$). Additionally, the S-RBD-neutralizing antibody in both the 21.00–25.00 kg/m2 and >25.00 kg/m2 groups was significantly lower than that of the ≤21.00 kg/m2 group ($p \leq 0.05$) [36]. In our study, the healthcare workers had a median body weight of 65.25 (55–73.5) kg and a median BMI of 23.61 (21.51, 26.24) kg/m2, which is considered overweight in the Asian population. Additionally, 18 cases ($33.33\%$) of healthcare workers had an obese BMI considering the average BMI of the Asian population (BMI > 25 kg/m2). It is well established that overweight and obesity affect the level of immunogenicity of COVID-19 vaccines, and the high proportion of healthcare workers who met the criteria for Asian obesity may have contributed to impaired immunity. Thus, the difference in anti-RBD antibodies levels between the patients with diabetes and healthcare workers was not significant. Another observation we made was that one patient with diabetes had extremely high levels of anti-RBD antibodies (5044.24 MAU/mL) compared to other patients with diabetes, whose geometric mean was 48.57 BAU/mL. This outlier result may have affected the overall analytical results. The results of the subgroup analysis in our study show that the geometric mean concentration (GMC) of anti-RBD antibodies in patients with type 2 diabetes and dyslipidaemia was significantly lower than that of diabetic patients without dyslipidaemia. This finding is consistent with a study by Naruse et al. that investigated the BNT162b2 mRNA COVID-19 vaccine [37]. In this study, univariable analysis revealed that anti-RBD IgG levels were significantly lower in patients with cardiovascular disease and dyslipidaemia compared to healthcare workers 14 days after receiving two doses of the BNT162b2 vaccine. This phenomenon can be attributed to the negative effects of dyslipidaemia on the immune system. Studies have shown that dyslipidaemia can have potential effects on both humoral and cellular immunity, leading to immune dysfunction [38,39]. Furthermore, some studies have found that elderly patients on long-term statin therapy have a lower immune response to post-influenza vaccination compared to those not on statin therapy [40]. However, further research may be needed to determine the impact of dyslipidaemia on immune responses to inactivated vaccines. In this study, only one participant had a history of steroid use, and therefore, it is not possible to draw conclusions about the effect of steroid use on the immune response to the COVID-19 vaccine. Further research with a larger sample size of participants who have a history of steroid use is needed to investigate the impact of steroid use on vaccine efficacy. With respect to reactogenicity, this study shows that patients with diabetes did not experience significantly different adverse events compared to healthcare workers, except for injection site reactions. This finding aligns with another study that examined the safety and immunogenicity of an inactivated COVID-19 vaccine in older individuals with hypertension and diabetes, which found no significant differences in the incidence of adverse reactions within 21 days after two doses of vaccination across the four groups [32]. Similarly, another study found that within 30 days after vaccination, the overall incidence of adverse events in the type 2 diabetes group and the healthcare workers group did not differ significantly [31]. Therefore, it can be assumed that adverse events after two doses of vaccination were generally similar in type 2 diabetes patients and healthcare workers, with injection site reactions being more common in diabetes patients but potentially occurring incidentally. Strengths and limitations: The strength of this study was that it focused on patients with diabetes mellitus type 2, which is a significant risk factor for severe COVID-19 infection. Additionally, the study attempted to minimize bias by matching the age/gender variable with the control group. However, the study’s sample size was limited, which may have affected the statistical differences between the two groups. The study was also conducted at a single centre, which may limit the generalizability of the findings to other populations or settings. Another limitation of this study is that neutralizing anti-bodies were not directly measured due to the complexity and limitations of the analysis. Instead, the study used anti-RBD antibodies as a surrogate marker for vaccine effectiveness. Although this approach provided useful information, it may not fully reflect the true level of neutralizing antibodies. 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--- title: Effect of Agave Fructan Bioconjugates on Metabolic Syndrome Parameters in a Murine Model authors: - Eduardo Padilla-Camberos - Javier Arrizon - Georgina Sandoval journal: Pharmaceuticals year: 2023 pmcid: PMC10052126 doi: 10.3390/ph16030412 license: CC BY 4.0 --- # Effect of Agave Fructan Bioconjugates on Metabolic Syndrome Parameters in a Murine Model ## Abstract Metabolic syndrome is a complex disorder that combines abdominal obesity, dyslipidemia, hypertension, and insulin resistance. Metabolic syndrome affects $25\%$ of the world’s population. Agave fructans have shown positive effects on alterations related to metabolic syndrome, so some investigations have focused on their bioconjugation with fatty acids to increase their biological activity. The objective of this work was to evaluate the effect of agave fructan bioconjugates in a rat model with metabolic syndrome. Agave fructans enzymatically bioconjugated (acylated via food-grade lipase catalysis) with propionate or laurate were administered orally for 8 weeks in rats fed a hypercaloric diet. Animals without treatment were used as the control group, as well as animals fed with a standard diet. The data indicate that the group of animals treated with laurate bioconjugates showed a significant decrease in glucose levels, systolic pressure, weight gain, and visceral adipose tissue, as well as a positive effect of pancreatic lipase inhibition. These results allow us to demonstrate the potential of agave bioconjugates, particularly laurate bioconjugates, for the prevention of diseases associated with metabolic syndrome. ## 1. Introduction Metabolic syndrome is a cluster of metabolic disorders associated with obesity and type 2 diabetes: insulin resistance, hypertension, hyperlipidemia, hyperglycemia, and cardiovascular disease [1,2]. The prevalence of metabolic syndrome fluctuates worldwide as there is a close association with age, sex, race/ethnicity, and the criteria used for diagnosis [3]. It is estimated that approximately $25\%$ of the world’s adult population suffers from metabolic syndrome and that the probability of dying from its complications as well as suffering a stroke increases considerably year by year [4,5]. At present, the main origin of metabolic syndrome has not been established; however, genetic and epigenetic factors, as well as the accelerated lifestyle of individuals and the high caloric intake associated with visceral adiposity, are the main inducers in the development of the syndrome [6,7]. Treatment of people with metabolic syndrome consisting of implementing lifestyle and diet changes, and increasing physical activity can improve the individual components of metabolic syndrome, but reducing cardiovascular risk through treatment of atherogenic dyslipidemia should be addressed directly with medications [8]. To reduce the negative effects of metabolic syndrome on human health, the consumption of bioactive compounds and natural fibers from plants, such as antioxidants and prebiotics, has increased worldwide. In particular, for prebiotics, it is well known that the positive effects of fructans in metabolic syndrome and the biological properties of these polysaccharides depend on the fructosyl linkages inside them, thus they have been used in plant-derived products for the formulation of functional food products against metabolic syndrome. These plant-derived products have played an important role in maintaining human well-being. For hundreds of years, since ancient times, natural products and their derivatives have been used, mainly in the development of pharmaceuticals for the treatment of human conditions [9]. A recent review by Wang et al. remarked on the potential of several polysaccharides obtained from plants for the treatment of metabolic syndrome, with mechanisms of action associated with the regulation of apoptosis, inflammation, and intestinal microbiota, among others. Such polysaccharides have mainly glycosidic bonds α-(1 → 6)-D, α-(1 → 4)-D, and β-(1 → 4)-D, and their biological activities are closely related to their primary and higher structures [10]. Other well studied groups of plant polysaccharides are inulin and fructans. Fructans from Agave genera differ from inulin in the type of linkage. Indeed inulin is lineal, while agave fructans are a complex mixture of fructooligosaccharides containing principally β (2 → 1) linkages, and some β (2 → 6) and branching moieties, leading to ramified structures [11,12]. Fructans from tequila agave (Agave tequilana Weber var. azul) have been shown to have positive effects on metabolic disorders associated with metabolic syndrome [13,14,15,16]. For example, studies evaluating the effects of fructans on glucose concentration in animal models have been consistently positive [17]. For instance, Castillo-Andrade et al. [ 18] evaluated the physiometabolic effects of Agave salmiana fructans as a dietary supplement in male Wistar rats. They found that the inclusion of $12.5\%$ Agave salmiana fructans in the diet of the animals induced beneficial physiometabolic effects after the seventh day of treatment [18,19]. Functionalization of fructans, such as acylation with fatty acids has also been reported, for instance, for inulin by chemical esterification [20], and by enzymatic bioconjugation of Agave tequilana fructans [21]. Some esterified fructans have been tested on metabolic syndrome, but the results were inconclusive, showing an impact on food intake in some cases [20], and no impact on zoometric parameters in others [22]. Animal diet-induced metabolic models are commonly used to study metabolic syndrome because of their simplicity, accuracy, and low cost [23]. The animals most commonly used to develop metabolic syndrome are rats, mainly Wistar and Sprague-Dawley, because they manifest the characteristics of obesity, diabetes, and hypertension. For this study, such a model was chosen and metabolic syndrome was induced with specific diets formulated with fat and carbohydrates that involve a high caloric content [24]. Accordingly, in the present study, we established the metabolic syndrome model in young rats by including a hypercaloric diet and evaluated the effect of agave fructan bioconjugates orally administered on parameters associated with metabolic syndrome. ## 2.1. Synthesis of Agave Fructan Bioconjugates It was previously reported that when enzymatic acylation of agave fructans is performed, only short-chain fructans are acylated [21]; therefore, agave fructans enriched in fructooligosaccharides (FOS) were used. Figure 1 shows the Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight (MALDI-TOF-MS) profile of the FOS used. The m/z distribution ranged from 527.37 to 1826.7, corresponding to FOS with a degree of polymerization (DP) from 3 to 11, respectively (Figure 1). FOS with a DP from 4 to 7 accounted for $53\%$ mol of the total mixture and the most abundant FOS had a DP of 5 ($14.8\%$ mol). The mass distribution of this agave FOS mixture used for the acylation reactions is smaller than that of natural agave fructans with DPs ranging from 3 to 30 [10]. This reduction was caused by industrial processing, which favors agave FOS acylation. Indeed, it was previously shown that the immobilized lipase B from Candida antarctica LipozymeTM 435, preferably acylated FOS up to DP 8 [20]. This could be due to the fact that the access of large molecules to the catalytic site of the lipase is hindered due to steric effects [25]. Two kinds of agave fructan bioconjugates were prepared, with short-chain (propionate) and medium-chain (laurate) acyl groups. Both short- and medium-chain fatty acids have been described as beneficial for the colonic gut microbiota [26]. Indeed, the short-chain fatty acids (SCFAs) acetate, propionate, and butyrate are reported as important fuels for intestinal epithelial cells [6]. Regarding propionate, the results of Byrne et al. in nonobese men suggested that colonic propionate may play an important role in human appetitive and reward-based eating behavior [27]. Medium-chain fatty acids and triglycerides ingestion results in ketone body production, provoking a thermogenic response [28]. Lauric acid showed insulinotropic effects in mouse models [29]. Thus, these fatty acids were investigated as acyl donors for agave fructan bioconjugates. The conversion of these two acyl groups to agave fructan bioconjugates was similar; as an example, Figure 2 shows the HPLC product profile of agave fructan bioconjugates synthesized with laurate. Fructans are not detected by the diode-array, and therefore, the visualized peaks are agave fructan bioconjugate products. Complete consumption of vinyl laurate (acyl donor) was observed. A similar behavior was detected with propionate agave fructan bioconjugates (data not shown). Additionally, a complex range of agave fructan bioconjugate products is obtained (Figure 3), which is due to the acylation at different positions of the hydroxyl groups of the ramified agave fructans. In the same manner, when acylation was carried out with agave fructans with a higher DP, a complex mixture of agave fructan bioconjugates was also observed [20]. Therefore, the highly complex branched structure of agave fructans could cause acylation in hydroxyl groups at different positions [10,11], which could impart different bioactive properties when compared with linear fructans. ## 2.2.1. Induction of Metabolic Syndrome with a Hypercaloric Diet Most of the parameters that were analyzed showed that the animals that received the hypercaloric diet (HD) developed characteristics related to the metabolic syndrome (Table 1 and Table 2). Feed and water consumption in the different experimental groups were as expected according to animal body measures (Table 1). As expected, feed consumption with standard diet (SD) was slightly higher, as HD is more satiating. The use of butter as the main source of fat in the preparation of the hypocaloric diet favored the induction of metabolic syndrome in the animals [24]. Although the scattering in the results is large due to the preparation of the hypercaloric diet in our laboratory, other authors, such as Leonardi et al. [ 30], also showed that there is considerable variability in animal models of metabolic syndrome. On average, animals treated with the propionate (HDFP) and laurate (HDFL) bioconjugates had lower feed ingestion than those treated with HD and hypercaloric plus fructans (HDF) diets. ST-Onge et al. also showed that medium-chain fatty acid triglyceride consumption by overweight men reduced their food intake [31]. ## 2.2.2. Metabolic Syndrome Prevention by Agave Fructan Bioconjugates Table 2 and Figure 4, Figure 5, Figure 6, Figure 7 and Figure 8 show the biochemical and zoomorphic parameters after eight weeks of standard diet (SD), hypercaloric diet (HD), hypercaloric diet plus fructans (HDF), hypercaloric diet plus propionate-bioconjugated fructans (HDFP), and hypercaloric diet plus laurate-bioconjugated fructans (HDFL). The animals that received the treatment with bioconjugates of the medium-chain acyl group (HDFL) showed a decrease in glucose levels when compared to the group with a hypercaloric diet (HD), (Figure 4). For the lipid profile parameters (Table 2), no significant differences were observed except for triglycerides where a significant decrease was observed in the HDFL group compared to the HD group; this effect was previously reported in a study with mice induced to obesity with a high-fat diet, which may be due to the proliferation of crypt cells related to lipid metabolism [19,32]. Previous studies have shown that agave fructans lower glucose levels in mice with obesity induced by a high-fat diet [13]. This reduction may be associated with the inhibition of enzymes related to carbohydrate metabolism, such as alpha amylase and alpha glucosidase, because preliminary studies of our working group demonstrated the postprandial hypoglycemic effect of agave fructans. Previous studies showed a significant $15\%$ decrease in postprandial serum glucose values in C57Bl/6J mice fed a high-fat diet with agave fructans [16]. The HDFL sample group of animals showed a significant decrease in blood pressure (systolic) when compared to the HD group (Figure 5). Increased blood pressure is one of the parameters that is affected by high-fat dietary intake, which promotes the appearance of reactive oxygen species mediated by nuclear factor kappa B and proinflammatory cytokines, and activates the renin–angiotensin–aldosterone system, which is widely documented in the etiology of cardiovascular damage [33,34]. It has been reported that some types of soluble dietary fiber, including fructans, produce short-chain fatty acids by microbial fermentation and can regulate blood pressure [35,36]. Indeed, in a study conducted in rats with metabolic syndrome induced with a high fructose diet, it was found that supplementation with inulin-type fructans showed an antihypertensive effect [37]. Increases in body weight and body fat are among the main parameters related to metabolic syndrome. Different types of fructans have been studied to evaluate their potential as controllers of these parameters. Additionally, the animals that were treated with the HDFL bioconjugate exhibited significantly decreased weight gain, about $31\%$ less than the HD group. The HDFP and HDF groups also showed a lower weight gain than the HD group; however, this difference was not significant (Figure 6). Visceral adipose tissue (Figure 7) was also about $18\%$ lower in the HDFL group than in the group of animals fed an HD diet and the nonbioconjugated fructan group (HDF). These data show that the HDFL group significantly reduced weight gain and visceral adipose mass in HD-induced rats. In healthy rats, no difference in body weight gain or adipose tissue weight was observed when fructans were supplemented in the diet [15]; however, in studies performed with mice of the C57Bl/6J strain fed fructans, a decrease in weight gain of the animals was demonstrated, and this effect was attributed to the induction of satietogenic peptides such as glucagon-like peptide-1 (GLP-1) [16]. It has been shown that rats treated with inulin-type fructans have increased serum levels of GLP-1, which, in addition to its satietogenic effect, inhibits macrophage inflammation [38]. Similarly, agave fructans were observed to prevent weight gain and hepatic steatosis in mice with high-fat-diet-induced obesity [13]. In clinical studies, agave fructans showed a beneficial effect on weight control, body fat and triglycerides in obese people during a 12-week treatment [14]. These effects may be due to the prebiotic activity of the fructans that promote the development of a healthy intestinal microbiota and therefore help to improve metabolic diseases [19,39]. Moreover, bioconjugates previously showed higher prebiotic activity than nonbioconjugated fructans by stimulating the growth of selected beneficial probiotic strains of the intestinal microbiota such as S. boulardii, L. lactis, L. casei, and L. rhamnosus [40]. Increases in body weight and body fat are among the main parameters related to metabolic syndrome. Different types of fructans have been studied to evaluate their potential as controllers of these parameters. Unless pancreatic lipase degrades them, dietary fat is not directly absorbed from the intestine. Therefore, pancreatic lipase inhibitors have been studied as a treatment for obesity induced by a high-fat diet [41]. We selected orlistat, a well-studied pharmacological lipase inhibitor, as a positive control, which at 6 mg/mL gave almost $85\%$ lipase inhibition (Figure 8), while the HDFL biconjugate at 1 mg/mL (used at this concentration because of its lower solubility) inhibited the lipase by $60\%$. This bioconjugate is a promising lipase inhibitor without the disadvantages of using orlistat, which has been associated with several mild-to-moderate gastrointestinal adverse effects [42]. Bioconjugation with propionate (HDFP) had a lesser effect on weight gain, visceral adipose tissue, and pancreatic lipase inhibition, similarly to Chambers et al. [ 20], who reported only weight and adiposity maintenance in acute supplementation with propionated inulin [20]. These results demonstrated that the bioconjugation of agave fructans has a positive effect on metabolic syndrome prevention, especially in the case of the medium-chain acyl group bioconjugate (HDFL). ## 3.1. Synthesis of Agave Fructan Bioconjugates Agave fructan bioconjugates were enzymatically synthesized as described in Patent MX 358789 [40]. Commercially available organic agave fructans enriched in FOS, and OlifructineTM (Nutriagaves, Guadalajara, Jal., Mexico) were used. The batch of OlifructineTM had $53\%$ mol of FOS of DP 4 to 7 (see Section 2.1 and Figure 1). The biocatalyst was the food-grade immobilized lipase B from Candida antarctica LipozymeTM 435 (Novozymes, Denmark, obtained through the broker Biotecsa, Mexico). Acylants (vinyl propionate and vinyl laurate), as well as solvents, were purchased from Sigma Aldrich (Burlington, MA, USA) at the highest purity available. Confirmation of acylation was performed by HPLC as reported previously [21], using a LunaTM C18 column (Phenomenex, Monterrey, NL, Mexico) in a Waters AcquityTM HPLC, using photodiode-array (PDA) detector at 217 nm; which makes it possible to detect the acylant substrates but not the fructans, with the advantage that the peaks observed once the acylant is consumed, correspond only to products. The mobile phase was methanol–water 90:10 at 0.6 mL/min. FOS are not completely soluble in the reactional system; however, once converted to bioconjugates, their solubility increased as the acylation reaction proceeded, as that kind of compound also has emulsification properties [21,25,43]. At the end of reaction, the immobilized lipase was filtered and the reaction solvent was eliminated in a BuchiTM rotary evaporator. Purification of the bioconjugates was not needed, as the conversion of the limiting substrate (acylant) was almost $100\%$ (see Figure 2), and unreacted fructans were insoluble in the reaction solvent. MALDI-TOF mass spectra analyses were performed in a Microflex LT, Bruker Daltonics system, using 2,5-dihydroxy benzoic acid (DHB) as the ionization matrix. Samples diluted (1:10 for propionate or 1:20 for laurate) were mixed with an equal part (v/v) of the matrix solution (10 mg/mL of DBH in ethanol–water; $\frac{1}{1}$; v/v). Then, 1 mL of this mixture was deposited on the target plate and dried at room temperature. The equipment was calibrated from 380 to 3000 m/z with 1-kestose as the standard [43,44]. ## 3.2.1. Preparation of the Special Diet The hypercaloric feed was formulated based on the AIN-93G diet and according to Cheng et al. [ 45] The ingredients: cellulose, carboxymethyl cellulose, L-cystine, choline bitartrate, and butylhydroquinone were purchased from Sigma Aldrich (Burlington, MA, USA). Starch, clarified anhydrous butter, maltodextrin, sucrose, and soybean oil were purchased from a local feed formulating ingredient distributor. Vitamin and mineral premix were purchased from Dyets Inc. (Bethlehem, PA, USA) and casein was purchased from Hilmar Ingredients (Hilmar, CA, USA). The distribution in percentage is shown in Table 3, and macronutrient distribution compared to the standard diet is presented in Table 4. The hypercaloric diet was prepared by mixing all ingredients and baking at 100 °C for 1 h. ## 3.2.2. Animals Thirty male Wistar rats (3–4 weeks, 120 ± 20 g) were randomly housed in acrylic boxes, six animals per box, under standard environmental conditions (12 h artificial light/dark cycle) and water and food ad libitum. The number of animals was determined based on previous studies where 6 animals per group were used [46]. The animals were treated following the guidelines and requirements of the Declaration of Helsinki of the World Medical Association and the recommendations of the Mexican Official Standard for the Production, Care, and Use of Laboratory Animals (Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), Mexican Official Standard NOM-062-ZOO-1999). The protocol was favorably reviewed by the Internal Committee for the Care and Use of Laboratory Animals (CICUAL). Report Code: 2021-002A. ## 3.2.3. Induction of Metabolic Syndrome and Treatment with Agave Fructans and Bioconjugates Each box with animals was assigned a group: Group 1 was considered the control group, which continued to receive standard feed (SD) and did not receive treatment. Group 2 was replaced by a hypercaloric diet (own elaboration) and did not receive treatment (HD). Group 3 consisted of a hypercaloric diet and, in addition, a daily dose of 130 mg/kg of nonbioconjugated fructans (HDF) was administered. Groups 4 and 5 were treated with bioconjugates. Group 4 consisted of a hypercaloric diet and was given a daily dose of 130 mg/kg propionate-bioconjugated fructans (HDFP). The fifth experimental group was fed a hypercaloric diet and a daily dose of 130 mg/kg of laurate-bioconjugated fructans (HDFL) was administered. Samples were administered daily for 8 weeks using an esopharyngeal cannula. The control group was administered phosphate-buffered saline (PBS). Samples were coded to maintain a blinded study. The following parameters were measured during the study: zoometric data such as weight, height, and body mass index (not shown), as well as water and food consumption, were monitored daily. Food intake was calculated by subtracting the amount of residual food from the amount of supply food. Blood pressure was measured at week 7 by a noninvasive method using an occlusion cuff on the rat’s tail (Noninvasive blood pressure system, CODA-M1, Kent Scientific Corporation. Torrington, CT, USA). At the end of 8 weeks, all animals were fasted (12 h) and euthanized by decapitation according to the ethical guidelines described above. Blood was collected in a test tube and centrifuged at 3000× g for 15 min at 4 °C. At the same time, the visceral adipose tissue was excised, washed with 1X PBS solution (Sigma—Aldrich, Burlington, MA, USA), and weighed. The serum obtained was stored at −80 °C for later use. Finally, glucose, cholesterol, triglycerides, LDL, and HDL parameters were measured in the stored serum using Randox kits (catalog numbers: GL2623, CH200, TR210, CH3841, and CH3811). ## 3.2.4. In Vitro Study of Pancreatic Lipase Inhibition Pancreatic lipase participates in the process of absorption of fatty acids from the diet and its inhibition reduces the levels of lipids such as cholesterol in the organism. The activity of porcine pancreatic lipase (type II) was measured by the addition of 1 mM 4-nitrophenyl butyrate as a colorimetric substrate to the fructan samples in 1 mM phosphate-buffered saline (PBS). They were incubated for 30 min at 30 °C and absorbance was measured at 405 nm. Orlistat (6 mg/mL) was used as a positive control based on the method of Kim et al. [ 41]. Fructans/agave fructan bioconjugates were evaluated at 1 mg/mL. ## 4. Conclusions Our findings indicated that bioconjugation of agave fructans enriched in low DP FOS, particularly with medium-chain acyl groups, specifically laurate (HDFL bioconjugate), had a favorable effect on metabolic syndrome prevention. Although metabolic syndrome is a multifactorial condition, and its clinical approach requires integrated management with different pharmacological approaches, HDFL treatment has shown a positive impact on various parameters of metabolic syndrome, and therefore it is a promising dietary adjuvant to prevent metabolic syndrome. However, studies at the cellular and molecular levels are needed to elucidate the mechanisms of action of bioconjugates. ## 5. Patents The processes described in our patent MX 358789 were used for the synthesis of agave fructan bioconjugates. A Mexican patent application for the results presented in this manuscript was presented with the number MX/a/$\frac{2022}{012414.}$ ## References 1. 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--- title: Sleeve Gastrectomy Improves Hepatic Glucose Metabolism by Downregulating FBXO2 and Activating the PI3K-AKT Pathway authors: - Ningyuan Chen - Ruican Cao - Zhao Zhang - Sai Zhou - Sanyuan Hu journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10052132 doi: 10.3390/ijms24065544 license: CC BY 4.0 --- # Sleeve Gastrectomy Improves Hepatic Glucose Metabolism by Downregulating FBXO2 and Activating the PI3K-AKT Pathway ## Abstract Type 2 diabetes mellitus (T2DM), a chronic metabolic disease, is a public health concern that seriously endangers human health. Sleeve gastrectomy (SG) can relieve T2DM by improving glucose homeostasis and enhancing insulin sensitivity. However, its specific underlying mechanism remains elusive. SG and sham surgery were performed on mice fed a high-fat diet (HFD) for 16 weeks. Lipid metabolism was evaluated via histology and serum lipid analysis. Glucose metabolism was evaluated using the oral glucose tolerance test (OGTT) and insulin tolerance test (ITT). Compared with the sham group, the SG group displayed a reduction in liver lipid accumulation and glucose intolerance, and western blot analysis revealed that the AMPK and PI3K-AKT pathways were activated. Furthermore, transcription and translation levels of FBXO2 were reduced after SG. After liver-specific overexpression of FBXO2, the improvement in glucose metabolism observed following SG was blunted; however, the remission of fatty liver was not influenced by the over expression of FBXO2. Our study explores the mechanism of SG in relieving T2DM, indicating that FBXO2 is a noninvasive therapeutic target that warrants further investigation. ## 1. Introduction Type 2 diabetes mellitus (T2DM), a chronic metabolic disease characterized by hyperglycemia, impaired islet cell function, and insulin resistance, accounts for more than $90\%$ of diabetic patients [1,2]. Obesity is a key risk factor for the occurrence and development of pre-diabetes and T2DM. In recent years, the incidence of obesity and T2DM in the world has rapidly increased [3]. Approximately 592 million people will suffer from diabetes worldwide by 2035 [4]. Poor treatment of T2DM leads to serious diseases involving multiple organ systems. Thus, obesity and T2DM have become public health concerns that seriously endanger contemporary human health [5]. Obese patients respond poorly to therapy and have a high failure rate following T2DM treatment due to changing lifestyles and drug administration [6]. The effectiveness and feasibility of bariatric surgery in treating T2DM are gradually being recognized by scholars at home and abroad; this procedure can lead to sustained weight loss and a high T2DM remission rate. The International Diabetes Federation (IDF) and the American Diabetes Association (ADA) named this procedure as one treatment method for diabetes [7,8]. Sleeve gastrectomy (SG) has become the most common bariatric surgery globally. Many studies have also shown that SG is not only a restrictive bariatric surgery but can also significantly relieve T2DM and other obesity-related complications, including improving glucose homeostasis and enhancing insulin sensitivity [9]. SG has been suggested to be superior to traditional drug therapy in terms of controlling blood glucose and improving or even reversing T2DM [10]. Following SG, the mechanism of metabolic improvement depends not only on significant weight loss but also on molecular mechanisms independent of weight loss [11]. The mechanisms of metabolic improvement caused by bariatric surgery focus on three main areas: improved secretion of gastrointestinal hormones such as GLP-1, improved bile acid metabolism, and changes in the gut microbiota [12,13]. These mechanisms can increase insulin sensitivity in the liver; however, the exact underlying mechanism remains unclear. F-box protein is a key protein component of the SKP1-Cullin1-F-box protein (SCF) E3 ligase complex, which participates in the ubiquitination pathway and various biological processes [14]. F-box-only protein 2 (FBXO2) is a member of this family, which can regulate the ubiquitination pathway. Studies have shown that abnormal expression of FBXO2 degrades insulin receptors (IR) in obese mice through ubiquitination, thus disrupting glucose homeostasis [15]. In addition, it has also been reported that FBXO2 plays an important role in Parkinson’s disease and tumor development [16,17]. However, there is little research on FBXO2 and metabolic diseases, and its role in metabolic improvement after bariatric surgery is unclear. This study aimed to determine the changes in FBXO2 after sleeve gastrectomy and its role in glucose homeostasis improvement ## 2.1. SG-Induced Weight Loss and Short-Term Reduction of Food Intake in Mice After 16 weeks of consuming a high-fat diet, all C57 mice were randomly divided into SG and sham surgery groups. No obvious differences were found in body weight between groups before surgery. During the first 2 weeks post-surgery, the food intake of mice in the SG group was lower than that of the sham operation group; however, after 3 weeks, the food intake in the two groups showed no significant difference (Figure 1A). The body weight curves showed that SG surgery induced obvious body weight loss in the first week after surgery in comparison to the sham surgery. Eight weeks after surgery, the SG group showed a greater reduction in weight loss and body size than the sham operation group (Figure 1B,C). We calculated body weight gain from the fourth to the eighth week in both groups and found that weight regain in the SG group was lower than that in the sham group despite identical food intake (Figure 1D). ## 2.2. SG Relieves HFD-Induced Body Glucose and Lipid Metabolism Disorder We further studied lipid and glucose metabolism changes in mice after SG. H&E and ORO staining of liver sections showed that lipid accumulation was obviously reduced in the SG group (Figure 2A). Compared with the sham group, the serum triglyceride level of mice in the SG group decreased significantly. In addition, the serum total cholesterol level showed a slight decrease after SG, although the difference did not reach statistical significance (Figure 2B). We further examined the composition of apolipoproteins and found a significant increase in HDL-C and a distinct decrease in LDL-C after bariatric surgery (Figure 2C). This result was consistent with previous studies. Bariatric surgery could reduce cardiovascular risk events by altering apolipoprotein composition [18]. In glucose metabolism, the OGTT results showed that SG decreased fasting blood glucose and blood glucose levels after 15, 30, 60, and 120 min following 2 g/kg glucose gavage (Figure 2D). The ITT results showed that fasting blood glucose and blood glucose levels after 15, 30, 60, and 120 min following 1 U/kg insulin subcutaneous injection also decreased in SG group mice (Figure 2E). Further, the RT-qPCR results revealed that RNA levels of genes associated with lipogenesis (Fasn, Acly, and Pparg) and lipid uptake (CD36 and Fabp1) in mouse livers were downregulated in the SG group (Figure 2F). In terms of glucose metabolism, mRNA levels of insulin receptor substrate 2 (Irs2), Foxo1, as well as genes associated with glucogenesis (G6pc and Pck1) were downregulated in mouse livers of the SG group compared to those of the sham surgery group (Figure 2G). We further studied the changes in signaling pathways that occurred alongside changes in lipid and glucose metabolism. Western blot analysis showed that the phosphorylation level of AMPKα was significantly increased in the SG group. Conversely, the phosphorylation level of mTOR, which plays a role in hepatic steatosis, was suppressed (Figure 3A). Our results also showed that following SG, the protein level of IR was upregulated and the PI3K-AKT-GSK3β pathway was activated, as evidenced by the increased phosphorylation levels of both AKT and GSK3β in SG groups (Figure 3B). Both of these promote insulin sensitivity and contribute to glucose homeostasis. Our data suggested that sleeve gastrectomy could significantly alleviate HFD-induced hepatic lipid accumulation and improve hepatic glucose metabolism. ## 2.3. SG Reduces Liver FBXO2 Level but Not by Reducing Blood Free Fatty Acid Concentration FBXO2 belongs to the F-box family of proteins and can reportedly disrupt glucose homeostasis through direct interaction with the ubiquitin insulin receptor. It was upregulated in mice fed an HFD [15]. However, the expression of FBXO2 after clinical bariatric surgery in the livers of patients cannot be determined using this type of analysis. After SG in mice, the western blot and immunohistochemistry results showed that the protein levels of FBXO2 were downregulated in the liver (Figure 3C,D). In addition, qPCR results showed that the mRNA levels of FBXO2 were reduced (Figure 3E). Further in vitro study on human HepG2 cells explored the mechanism of the observed downregulation of FBXO2 caused by SG with Oil red O and Nile red staining. When treated with free fatty acids (0.3 μmol sodium oleate), HepG2 cells showed obvious lipid accumulation (Supplementary Figure S2A,B). However, mRNA and protein levels of FBXO2 showed no significant change (Supplementary Figure S2C,D). SG can reduce blood levels of free fatty acids, and our study showed that the reduction in liver FBXO2 level was not affected by this phenomenon but was meditated by an alternative mechanism. Previous studies have shown that FBXO2 was regulated by the NFκB signaling pathway. GLP-1 is one of the main intestinal hormones that play a role in SG, and it has been reported that GLP-1 could reduce NFκB activation, which may cause changes in FBXO2 expression in the liver [12,19]. ## 2.4. Hepatic-Specific Overexpression of FBXO2 Partly Reversed the Remission of Glucose Homeostasis Caused by SG We overexpressed FBXO2 specifically in the liver by injecting AAV-His-FBXO2 into the tail vein following 16 weeks of HFD feeding and before SG, during the 8 weeks post-surgery. The food intake curve results showed that both the SG and SG FBXO2 overexpression groups showed a reduction in food intake at the first two weeks after surgery (Figure 4A). Both the SG and SG FBXO2 overexpression groups showed significant weight loss and reduction in body size compared to the sham operation group (Figure 4B,C). H&E and Oil red O staining of liver sections showed that lipid accumulation was obviously reduced in the SG and SG FBXO2 overexpression groups (Figure 4D). Compared with the sham group, the serum triglyceride levels of mice in the SG and SG FBXO2 overexpression groups decreased significantly. However, the serum T-Cho levels showed no significant difference among the three groups (Figure 4E). A significant increase in HDL-C and a distinct decrease in LDL-C was found in the SG and SG FBXO2 overexpression groups compared with the sham group (Figure 4E). In glucose metabolism, the OGTT and ITT results showed that fasting blood glucose and blood glucose levels at 15, 30, 60, and 120 min following gavage in the SG FBXO2 overexpression group were higher than those in the SG group, but they were lower than those in the sham group and showed statistical differences at some time points (Figure 4G,H). Compared with the SG group, the SG FBXO2 overexpression group showed no significant differences in food intake, body weight, and size (Figure 4A–C). Although overexpression of FBXO2 partly reversed the reduction in lipid accumulation caused by SG (Figure 4D), serum triglyceride, total cholesterol, HDL-C, and LDL-C showed no differences between the two groups (Figure 4E,F). However, overexpression of FBXO2 significantly increased blood glucose levels in OGTT and ITT (Figure 4F,G). Mechanistically, overexpression of FBXO2 did not affect the phosphorylation levels of AMPKα and mTOR after SG (Figure 5A), but it could impair the IR and PI3K-AKT-GSK3β pathway (Figure 5B). Overexpression of FBXO2 significantly decreased the protein level of IR and reduced the protein level of PI3K and phosphorylation level of AKT, while GSK3β caused a decrease in PI3K-AKT signaling pathway activity. Furthermore, the RT-qPCR results showed that there were no significant differences in the mRNA levels of genes associated with lipid metabolism in the SG and SG FBXO2 overexpression groups (Figure 5C). Some of the genes associated with glucose metabolism (Foxo1, Irs2, and G6pc) in the SG FBXO2 overexpression group were upregulated compared to those in the SG group (Figure 5D). This result showed that FBXO2 overexpression could weaken the effect of SG on glucose metabolism through the PI3K-AKT-GSK3β pathway but did not affect the function of SG on lipid metabolism. ## 3. Discussion Type 2 diabetes is a disease that develops rapidly [1]. It primarily manifests as an increase in fasting blood glucose and postprandial blood sugar, accompanied by insulin resistance in multiple organs [20]. A variety of therapeutic drugs have been used to treat type 2 diabetes, which mainly act by improving insulin resistance or directly supplementing insulin [21]. However, conventional drug treatment struggles to stably control and reverse the development of type 2 diabetes, and other organs may be damaged as a result of these therapeutics in the long term. PI3K phosphatidylinositol 3 kinase was discovered in the 1990s [22] and it has been reported that PI3K/AKT signaling plays a very important role in cell physiology, mediating growth factor signaling in biological growth [23,24]. It plays a key role in cellular processes and regulates glucose homeostasis, lipid metabolism, protein synthesis, cell proliferation, and cell survival. AKT is regulated directly by PI3K and participates in the regulation of glucose and lipids [25]. In the intracellular chamber, AKT converts glucose into glucose-6-phosphate by stimulating hexokinase [26]. AKT regulates glycolysis by suppressing glucose-6-phosphate and glycogen synthase kinase 3 (GSK3) and reduces the expression of phosphoenolpyruvate carboxyl kinase (PEPCK) and glucose-6-phosphatase (G6PC) by inhibiting FoxO1, thus reducing gluconeogenesis and glucose levels [27,28,29,30]. In addition, AKT inhibits GSK3 through phosphorylation of GSKβ, thereby activating glycogen synthase (GS) and increasing glycogen synthesis [31]. This classical signaling pathway widely exists in many organs of the body, and it has been reported that the liver can reduce circulating glucose levels when receiving insulin through this mechanism [29]. In the fasting state, glucose is mainly used in the liver for gluconeogenesis and glycogen decomposition. It is then transported to various tissues while inhibiting the synthesis of fatty acids in these tissues. In the fed state, the PI3K/AKT signaling pathway reduces hepatic glucose production (HGP) and glycogen decomposition while increasing glycogen and fatty acid synthesis for storage and subsequent use by other tissues. Such a balance maintains the energy supply after meals and on an empty stomach. In obesity, the slow response of adipose tissue leads to a reduction in FFA uptake and glucose utilization, leading to ectopic accumulation in other tissues [32]. PI3K/AKT is impaired by ectopic lipid accumulation in the liver, insulin resistance, and nonalcoholic fatty liver disease (NAFLD), resulting in increased insulin resistance. Previous studies have shown that SG can effectively alleviate insulin resistance in type 2 diabetes [10,11]. In our experiment, the expression of PI3K in the liver increased after SG. In addition, AKT phosphorylation levels also increased significantly, which was consistent with previous studies [22,24]. However, the mechanism of how SG activated this pathway remained unclear in previous research. IRS is one of the signaling proteins upstream of PI3K. When insulin binds to insulin receptor (IR), the inhibition of IRS is removed. It has been reported that mice with Irs2 gene knockout exhibited selective insulin resistance, while mice lacking Irs1 or Irs1 and Irs2 developed total insulin resistance [33,34]. This indicates that IRS$\frac{1}{2}$ is the cause of selective insulin resistance; in some cases, the insulin signal transduction in the liver remains intact, but the involuntary cellular pathway may be blocked, as described above, resulting in an increase in HGP during insulin resistance. One possible explanation is that the destruction of substrate IRS$\frac{1}{2}$ will cause insulin resistance. In addition, many studies have shown that the level of IRS$\frac{1}{2}$ increases after bariatric surgery [35,36]. These studies provide important insight into the mechanism of PI3K-AKT pathway activation after weight-loss surgery. A previous study showed that FBXO2 is a member of the E3 ubiquitin ligase family and can target ubiquitin insulin signal receptor (IR) to disrupt the insulin signal pathway. Liver-specific overexpression and deletion of FBXO2 have been shown to affect glucose homeostasis [15]. The ubiquitin proteasome pathway is an important regulatory mechanism in vivo. In another study in our laboratory, we found that levels of FBXO2 protein and mRNA in the livers of obese patients were significantly upregulated. These results highlight the significant role of FBXO2 in the occurrence of insulin resistance and abnormal glucose metabolism. In the current study, we found that mRNA and protein levels of FBXO2 in mouse livers decreased significantly after bariatric surgery. The FBXO2-IR axis can be reversed to protect the PI3K-AKT signal pathway using this mechanism, which complements the mechanism that improves insulin sensitivity following SG surgery (Figure 6). Type 2 diabetes can be treated with bariatric surgery, which is being performed with increasing regularity worldwide. There are many ways to perform bariatric surgery. At present, SG is still the most widely performed weight loss surgery in the world [37]. Current studies have shown that SG can play a role in regulating glucose metabolism and homeostasis through a variety of mechanisms [12,13,38]. SG can significantly affect the secretion of intestinal hormones, including GLP-1, GLP-2, PYY, and other hormones [39]. Of these, GLP-1 is the most extensively studied, and GLP-1 receptor agonists have been widely used in the clinical treatment of obesity and type 2 diabetes [40]. GLP-1 also plays an important role in SG by inhibiting appetite [41]. Our study showed that mice the SG group no longer displayed reduced food intake after 3 weeks. This may be related to the special eating habits of rodents. Previous studies have shown that reducing energy intake can significantly improve human metabolic function. However, with the same food intake, SG mice showed lower body weight regain. A recent study showed that IL-27 was upregulated and promoted increased adipose tissue thermogenesis after bariatric surgery, revealing a specific mechanism of weight loss independent of dietary restriction [42]. NAFLD and T2MD often coexist in clinical practice. The excessive accumulation of lipids is one of the most important factors affecting the insulin sensitivity of the liver. As a result, lipotoxicity will increase, resulting in local chronic inflammation and impaired insulin signaling [43]. SG surgery can significantly improve liver lipid accumulation and alleviate insulin resistance through various mechanisms. In the liver, the AMPKα-mTOR signaling pathway plays a regulatory role in glucose and lipid metabolism in the body [44]. Previous studies have shown that long-term mTOR activation will cause significant lipid accumulation, while AMPKα can inhibit the function of mTOR by enhancing the phosphorylation of raptor [45,46]. Our results showed that after weight-loss surgery, the phosphorylation levels of AMPKα were significantly increased and those of mTOR were inhibited. This may explain the reduction in liver lipid accumulation following SG. Our study found that overexpression of FBXO2 did not seem to affect AMPK activation. In addition, overexpression of FBXO2 did not seem to significantly affect the expression of genes related to liver lipid metabolism. However, the results of liver tissue staining showed that overexpression of FBXO2 caused an increase in liver lipid accumulation. We speculate that this phenomenon may be caused by FBXO2 indirectly through PI3K-AKT, or that FBXO2 has other mechanisms that do not depend on the above two pathways to regulate lipid metabolism. These findings warrant further investigation. ## 4.1. Animals and NAFLD Mice Models Male C57BL/6 mice aged 7–8 weeks were acquired from SPF Biotechnology Co. (Beijing, China). All mice were housed at a suitable temperature under a 12-h light/dark cycle. All mice were fed a high-fat diet (HFD) containing $60\%$ kcal from fat (D12492; Xiao Shu You Tai Biotechnology, Beijing, China) for 16 weeks to induce insulin resistance and fatty liver [47]. At the beginning of the experiment, 20 mice were fed HFD. Of these, 4 mice were excluded from the group because they weighed less than 35 g. The 16 mice were subsequently treated with SG operation ($$n = 8$$) and sham operation ($$n = 8$$). Two SG mice died within one week of the operation. After dissection, it was found that one mouse died of gastric fistula and the other death was probably due to pyloric obstruction. No mice in the sham operation group died. We finally selected 6 mice in the SG group and 6 randomly selected mice in the sham group. All mice were sacrificed after continued 10-week HFD feeding post-operation. All mice were euthanized after 12 h fasting to collect samples. The animal research was approved by the Ethics Committee for Animal Research at Shandong Provincial Qian Foshan Hospital (S328; 3 April 2020). ## 4.2. Surgical Procedures The SG surgery has been described previously [48]. Mice were anesthetized with $3\%$ isoflurane before the operation and maintained on $1.5\%$ isoflurane anesthesia during the operation. During the surgery, $70\%$ of the total stomach, including the entire gastric fundus, was removed in mice in the SG group (Supplementary Figure S1). Mice in the sham group were identically anesthetized, and midline incision and stomach exposure were performed, similar to mice in the SG group, without removing any part of the stomach. The mice were resuscitated at 35 °C after surgery to prevent low-temperature damage. Post-operatively, saline was injected subcutaneously into the mouse’s back for rehydration. Mice were checked daily for survival for the first two weeks after surgery. Food intake and body weight were monitored weekly until the mice were euthanized for the collection of the samples. ## 4.3. Mouse Adeno-Associated Virus8 (AAV8) Construction and Injection AAV-His-FBXO2 with TGB promoter was used to construct a liver-specific FBXO2 overexpression mouse model, with AAV-His-Vector serving as the control. At 8 weeks, the mice were administered a dose of 5 × 1012 vector genome (μg)/kg by tail vein injection [49]. The AAVs used above were purchased from WZ Biosciences Inc. (Shandong, China). In this part of the experiment, after adeno-associated virus8 injection and HFD, we obtained 24 obese mice that met the body weight requirement (SG, $$n = 8$$; SG FBXO2 overexpression, $$n = 8$$; and sham operation, $$n = 8$$). Three mice died within two weeks of the operation (SG, $$n = 2$$; SG FBXO2 overexpression, $$n = 1$$). We finally selected 6 mice in the SG group, 6 randomly selected mice in the SG FBXO2 overexpression group, and 6 randomly selected mice in the sham group. ## 4.4. Blood Biochemical Analysis Blood was collected from the tail vein of the mice. Mice serum was obtained after centrifugation of blood at 8000× g for 20 min at 4 °C. The serum levels of triglyceride (TG) total cholesterol (T-Cho), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured using standard determination kits according to the manufacturer’s instructions (Nanjing Jiancheng, Nanjing, China). ## 4.5. Oral Glucose Tolerance Test (OGTT) and Insulin Tolerance Test (ITT) The OGTT and ITT were performed on mice in the SG and sham groups 9 and 10 weeks after the operation. For OGTT, 2 g/kg of glucose was administered orally, and for ITT, 1 U/kg of insulin was injected intravenously into the mice after a 6 h fast. Serum glucose levels were measured at 0, 30, 60, 90, and 120 min using a standard glucometer (Johnson & Johnson, New Brunswick, NJ, USA). ## 4.6. Histological Analysis The liver tissue sections were stained with hematoxylin and eosin (H&E) (Solarbio, Beijing, China) and hepatic fat accumulation was determined using Oil Red O (ORO) staining (Sigma-Aldrich, St. Louis, MO, USA). A light microscope (IX-73; Olympus Corporation, Tokyo, Japan) was used to capture the histological images of the tissue sections. ## 4.7. Cell Lines The human liver HepG2 cell line was used in this study and was cultured in Dulbecco’s Modified Eagle Medium (DMEM) with $10\%$ fetal bovine serum (FBS) and $1\%$ penicillin-streptomycin in a humidified chamber with $5\%$ CO2 at 37 °C. The HepG2 cells were exposed to odium oleate (OA) at a final concentration of 0.3 mM for 24 h to establish an in vitro cell lipid deposition model. The hepG2 cell line was purchased from Shanghai Zhongqiao Xinzhou Biotechnology Co., Ltd. (Shanghai, China). ## 4.8. Western Blot Analysis Briefly, liver tissues and HepG2 cells were lysed in RIPA lysis buffer containing protease and phosphatase inhibitors, followed by western blotting using standard procedures [50]. The primary antibodies used are listed in Table S1. The immunoblotting results were quantified and statistically analyzed using ImageJ (National Institutes of Health, Bethesda, MD, USA) and GraphPad Prism software (GraphPad Software 8.0, San Diego, CA, USA), respectively. ## 4.9. RNA Preparation and Quantitative Real-Time PCR (qPCR) Total RNA was extracted from cells using TRIzol reagent according to the manufacturer’s instructions and then reverse transcribed to generate cDNA (#RR047A; Takara Bio Inc., Shiga, Japan). The SYBR Green qRT-PCR method was applied to quantify real-time PCR amplification (LightCycler 480 II, Roche Diagnostics, Indianapolis, IN, USA). The expression levels were calculated using the Δct-method; some of the results were calculated using a log2 negative logarithm. The primer pairs used in our study are listed in Table S2. ## 4.10. Oil Red O (ORO) and Nile Red Straining in HepG2 Cells Oil red storage solution was prepared with 5 g/L Oil Red O and isopropyl alcohol as a solvent storage fluid. The working solution of ORO (ORO:deionized water = 2:3) was used for Oil Red O staining. Nile red stain was dissolved in acetone and diluted 1:10,000 in 1× PBS for Nile red straining. DAPI was used to stain cell nuclei. ## 4.11. Immunohistochemistry Immunohistochemistry analysis was carried out on paraffin-embedded mouse liver tissue sections. A standard xylene ethanol procedure was used to dewax and rehydrate the tissue. The slices were boiled in citric acid buffer (pH 6.0) for 20 min. The activity of endogenous peroxidase was inhibited in methanol using $3\%$ hydrogen peroxide (UltraVision Hydrogen Peroxide Block; Thermo Fisher Scientific, Waltham, MA, USA) for 15 min. Thereafter, the sections were incubated with FBXO2 antibody (Santa Cruz Biotechnology, Dallas, TX, USA) for 4 h at 37 °C. The HRP polymer (Ultra Vision Quanto Detection System; Thermo Fisher Scientific, Waltham, MA, USA) and DAB chromogen (DAB Peroxidase Substrate Kit; Vector Laboratories, Burlingame, CA, USA) were used to visualize FBXO2 immunoreactivity in the sections. Finally, the sections were counterstained with hematoxylin (ScyTek Laboratories, Logan, UT, USA) and dehydrated. ## 4.12. Statistical Analysis The experimental results are expressed as mean ± standard deviation (SD) and were analyzed using GraphPad Prism version 8.3 software (GraphPad Software). Statistical differences between two experimental groups were evaluated using an unpaired Student’s t-test. Statistical differences among three experimental groups were evaluated using one- or two-way ANOVA. Statistical significance was considered at $p \leq 0.05.$ ## 5. Conclusions This study emphasized the key role of FBXO2 in metabolism. However, we did not investigate the direct factors affecting FBXO2 expression caused by SG. Previous studies have shown that FBXO2 may be affected by the NFκB-IKKβ pathway in the liver [13], and it has been reported that GLP-1 can inhibit the activation of NFκB [41]. We speculate that GLP-1 may be the cause of the downregulation of FBXO2 and could establish a new link in the interaction between liver inflammation and insulin resistance. 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--- title: A Comprehensive Investigation into the Crystallology, Molecule, and Quantum Chemistry Properties of Two New Hydrous Long-Chain Dibasic Ammonium Salts CnH2n+8N2O6 (n = 35 and 37) authors: - Zengbo Ke - Xinhui Fan - Youying Di - Fengying Chen - Xi Han - Ke Yang - Bing Li journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10052139 doi: 10.3390/ijms24065467 license: CC BY 4.0 --- # A Comprehensive Investigation into the Crystallology, Molecule, and Quantum Chemistry Properties of Two New Hydrous Long-Chain Dibasic Ammonium Salts CnH2n+8N2O6 (n = 35 and 37) ## Abstract Through the salification reaction of carboxylation, successful attachment of the long-chain alkanoic acid to the two ends of 1,3-propanediamine was realized, which enabled the doubling of the long-chain alkanoic acid carbon chain. Hydrous 1,3-propanediamine dihexadecanoate (abbreviated as 3C16) and 1,3-propanediamine diheptadecanoate (abbreviated as 3C17) were synthesized afterward, and their crystal structures were characterized by the X-ray single crystal diffraction technique. By analyzing their molecular and crystal structure, their composition, spatial structure, and coordination mode were determined. Two water molecules played important roles in stabilizing the framework of both compounds. Hirshfeld surface analysis revealed the intermolecular interactions between the two molecules. The 3D energy framework map presented the intermolecular interactions more intuitively and digitally, in which dispersion energy plays a dominant role. DFT calculations were performed to analyze the frontier molecular orbitals (HOMO–LUMO). The energy difference between the HOMO–LUMO is 0.2858 eV and 0.2855 eV for 3C16 and 3C17, respectively. DOS diagrams further confirmed the distribution of the frontier molecular orbitals of 3C16 and 3C17. The charge distributions in the compounds were visualized using a molecular electrostatic potential (ESP) surface. ESP maps indicated that the electrophilic sites are localized around the oxygen atom. The crystallographic data and parameters of quantum chemical calculation in this paper will provide data and theoretical support for the development and application of such materials. ## 1. Introduction Long-chain saturated fatty acids play various roles in the new metabolism of animals and plants [1,2,3,4]. Due to their carboxyl group, long-chain saturated fatty acids can undergo an esterification reaction [5,6], acylation reaction [7,8], salt formation reaction [9], oxidation-reduction reactions [10], and decarboxylation reactions [11,12,13]. In recent years, in addition to being widely studied in the field of biochemistry, long-chain saturated fatty acids have also drawn much attention in the field of thermodynamics [14,15], especially in the area of phase change energy storage [16,17,18,19,20,21,22], where they are becoming increasingly popular. The popularity of long-chain saturated fatty acids is attributed to their desirable properties, such as good cycling stability, no supercooling, and no phase separation [23,24]. This type of phase change material and its composites are mainly applied in solar energy generation [25,26,27,28], industrial waste heat recovery [29,30], automobile exhaust utilization [31,32], and building heat storage [33,34]. Modifying long-chain fatty acids by physical and chemical methods to increase their latent heat of phase transition is a very important research field. As a nucleophilic reagent, 1, 3-propylene diamine is alkaline and can form hydrogen bonds. It is often used as an intermediate and solvent in organic synthesis [35,36]. In addition, 1,3-propanediamine plays an important role in photosynthesis and the cultivation of biological strains [37,38]. Amines and their derivatives have been widely reported [39,40]. The binary ammonium salt formed with ethylenediamine and lauric acid as ligands was reported in the literature [41]. The results showed that this kind of binary ammonium salt had good thermodynamic properties. However, the synthesis of long-chain binary ammonium salts with 1,3-propanediamine and long-chain fatty acids as ligands has not been reported. The study of binary ammonium salt by quantum chemical calculation [42,43,44,45] has never been reported. Taking the above into consideration, this paper successfully synthesizes two hydrous long-chain dibasic ammonium salts CnH2n+8N2O6 ($$n = 35$$ and 37) with hexadecanoic acid, heptadecanoic acid, and 1,3-propanediamine as the raw materials, realizing the doubling of the carbon chain length of long-chain dibasic acid. The molecular structures of two compounds are determined by an X-ray single crystal diffractometer. Their intermolecular interactions and hot spots are revealed by Hirshfeld surface analysis. In addition, their frontier molecular orbitals, chemical reaction parameters, electronic state densities, and molecular surface electrostatic potentials are disclosed by DFT theory and the latest quantum chemistry tools. ## 2.1. Descriptions of Crystal Structure The crystal size and data obtained by X-ray single crystal diffraction are shown in Table 1. Table 1 shows that the crystal of the compound hydrous 1,3-propanediamine dihexadecanoate (3C16) is triclinic; a space group is P-1 and $Z = 2$ with unit cell dimensions $a = 6.6497$[8] Å, $b = 8.4340$[9] Å, $c = 35.221$[4] Å, α = 90.747[2]°, β = 90.748[2]°, and γ = 96.969[3]°. The crystal of the compound hydrous 1,3-propanediamine diheptadecanoate (3C17) is triclinic; a space group is P-1 and $Z = 2$ with unit cell dimensions $a = 6.6942$[13] Å, $b = 8.4899$[17] Å, $c = 37.083$[7] Å, α = 92.15[3]°, β = 93.65[3]°, and γ = 97.04[3]°. It can be seen that both crystal systems of the two lactate complexes are triclinic. The two crystal structures have the same crystal system and space group as reported in the literature [41]. Unlike the compound reported in the literature, the number of molecules in a single crystal cell and the lengths of the molecules are different. Figure 1a,b show the molecular elliptical diagrams of 3C16 and 3C17, respectively, indicating that they are typical amphiphilic molecules. The head hydrophilic polar groups, carboxylate ions and ammonium ions, and the hydrophobic non-polar hydrocarbon chains at the tail are folded. The unit cell diagrams of 3C16 and 3C17 are shown in Figure 2a,b, respectively. It can be seen from the cell diagrams that their spatial arrangement is the same. Hydrophilic groups of both compounds are located inside the cell [41]. This can also be seen from the 2D space stacking diagrams in Figure 3 and the 3D space-filling diagram in Figure 4. Strong hydrogen bonding plays an important role in the orderly arrangement of the two molecules in space. Hydrogen bonds in Figure 2a, where amines act as donors and carboxylates act as receptors, include N1-H1A...O3, N1-H1B...O1, N1-H1C...O4, N2-H2C...O1, N2-H2D...O2, and N2-H2E…O2. Hydrogen bonds where H2O acts as donors and carboxylates act as receptors include O5-H5C…O2, O5-H5D…O3, and O6-H6D…O3, and the hydrogen bond where H2O acts as donors and acceptors are O6-H6C…O5. In Figure 2b, hydrogen bonds in which amines serve as donors and carboxylates serve as receptors include N1-H1A...O3, N1-H1B...O2, N1-H1C...O4, N2-H2C...O2, and N2-H2D...O1. Hydrogen bonds in which H2O acts as donors and carboxylates act as receptors include O5-H5C…O1, O5-H5D…O3, and O6-H6C…O3, and the hydrogen bond in which H2O acts as both donor and acceptor are O6-H6D…O5. It can be seen that H2O molecules play an important role in stabilizing the framework of the title compounds. The bond lengths and angles of 3C16 and 3C17 are listed in Table 2 and Table 3, respectively, and the hydrogen bond data are listed in Table 4 and Table 5. The 3D space-filling diagrams of 3C16 and 3C17 are shown in Figure 4a,b, respectively. Hydrogen bonding results in the formation of two-dimensional networks of both compounds, which have interpenetrating layers of organic and inorganic components similar to the layered “sandwich” structure found in perovskite [46,47]. ## 2.2. Hirshfeld Surface Analysis Upon inputting the CIF files, CrystalExplorer 17.5 software was used to generate the Hirshfeld surface and 2D fingerprint plot of the title complexes. de and di, indicated in the 2D fingerprint plot, refer to the length between the Hirshfeld surface and outermost distance of the closest atom, and the shortest distance between the surface and innermost distance of the closest atom, respectively. dnorm is a normalized contact distance derived from de and di. Figure 5 and Figure 6 illustrate how an analysis of the 2D fingerprint plots can be employed to detect patterns corresponding to distinct interactions (H...H, H...O, etc.). Figure 5 suggests that compound 3C16 possesses a close H...H interaction ($79.4\%$), as well as H...O ($8.8\%$) and O...H ($10.6\%$) interactions. Similarly, Figure 6 reveals that compound 3C17 is characterized by a close H...H bond ($80\%$), as well as H...O ($8.5\%$) and O...H ($10.3\%$) interactions. The 2D fingerprints of both molecules also point to the fact that the hydrogen bond donor around the carboxyl group is situated beyond the Hirshfeld surface, whereas the hydrogen bond receptor in the vicinity of the carboxyl group is located within the Hirshfeld surface. As a result of the H...O and O...H interactions, both compounds are featured by distinct red-spotted areas on the Hirshfeld surface of the title compounds, consistent with the data presented in Table 4 and Table 5. Intermolecular interactions of the two molecules are mainly impacted by the O-H...O and O-H...O hydrogen bonds. The mechanical strength of a single crystal is related to the spatial crystal packing. Single crystals with large cavities show a limited capacity for withstanding external forces, whereas those without large cavities exhibit a notable ability to bear considerable forces or stresses [48,49]. We carried out the void analysis on 3C16 and 3C17 crystals, which is based on adding up the atomic electron density by using the Hartree–Fock theory. It is assumed that all the atoms are spherically symmetric while calculating voids. Refer to Table S1 and Figure 7 for detailed void parameters. When the electron density isosurface value is 0.002 au, the void volumes of 3C16 and 3C17 are 214.46 Å3 and 248.87 Å3, respectively. The volume of voids in 3C16 and 3C17 accounts for $10.94\%$ and $11.93\%$ of the total volume, respectively. Since the space occupied by the voids in the two compounds is very small, there is no large cavity in the crystal packing of 3C16 and 3C17. We can speculate that 3C16 and 3C17 have good mechanical properties. The ability of a pair of chemical species (X, Y) to form crystal packing interactions is determined by computing the enrichment ratio. The enrichment ratio is calculated by dividing the proportion of the actual contacts by the theoretical proportion of the random contacts [50,51,52]. For a particular crystal, some contacts are more favorable to forming crystal packing interactions than other contacts. The enrichment ratio for a contact provides the tendency of it to form crystal packing interactions. The contacts with an enrichment ratio greater than one have a higher tendency to form crystal packing interactions as compared to other contacts. Tables S2 and S3 list the enrichment ratios of all possible chemical pairs of 3C16 and C17. From Table S2, it can be seen that the enrichment ratios of C-H contact, O-H contact, and H-H contact in the 3C16 molecule are 0.83, 1.19, and 0.97. From Table S3, it can be seen that the enrichment ratios of C-H contact, O-H contact, and H-H contact in the 3C17 molecule are 0.89, 1.18, and 0.97. It can be seen that the O-H contact in the two molecules is beneficial. ## 2.3. Energy Frameworks The construction of an energy framework provides three-dimensional visualization of the supramolecular assembly within crystal molecules. The energy of molecular interactions is typically represented by four distinct components: electrostatics, polarization, dispersion, and exchange repulsion, expressed as Etot = keleEele + kpolEpol + kdisEdis + krepErep [53]. Using the CrystalExplorer 17.5 software, the energy framework was calculated using the HF method with 3–21G basis set. The energy for molecular interactions was computed using the intermolecular potential method. Three types of intermolecular interaction energies were involved in the energy calculation: electrostatic energy, dispersion energy, and total energy. An energy frame of 2 × 1 × 1 size clusters was generated to calculate the energy. For compounds 3C16 and 3C17, the intermolecular interaction energy frame diagrams along the a, b, and c directions are shown in Figure 8 and Figure 9, respectively. The numerical values of the intermolecular interaction energies involved in the energy calculation are listed in Table 6 and Table 7. The ratio factors of energy computed using the HF/3–21G basis set were found to be kele = 1.019, kpol = 0.651, kdis = 0.901, and krep = 0.811 [54]. Calculations on the data from Table 5 and Table 6 yielded the intermolecular energies for the title compounds; 3C16 had electrostatic, polarization, dispersion, and exchange repulsion energies of 3.5 kJ/mol, −7.4 kJ/mol, −195.5 kJ/mol, and 63.3 kJ/mol, respectively, and 3C17 had electrostatic, polarization, dispersion, and exchange repulsion energies of 4.7 kJ/mol, −7.4 kJ/mol, −196 kJ/mol, and 57 kJ/mol, respectively. The total energies were −126.3 kJ/mol and −130.4 kJ/mol for 3C16 and 3C17, respectively. It can be seen that dispersion energy dominates electrostatic energy in both compounds. The size of the small cylinders in Figure 8 and Figure 9 revealed the strength of intermolecular energy and its correlation to molecular stacking. Note that those weak intermolecular interactions below a certain threshold are omitted to avoid congestion. The absence of cylinders in the energy framework along a particular direction does not necessarily imply the absence of any stabilizing intermolecular interactions. ## 2.4.1. Molecular Geometry Optimization The molecular geometry optimization and frequency calculations of the title compounds were achieved through density functional theory (DFT) [55,56]. DFT is a widely used technique for studying electronic structures in materials science. It is a tool for investigating properties such as geometry optimization, infrared spectra, molecular orbitals, and molecular surface electrostatic potentials. Density functional theoretical (DFT) computations were performed with Gaussian 09 software [57] using the B3LYP/6–31G* basis set. All quantum chemical calculations presented herein were performed within the context of a periodic system to accurately reflect the crystal environment. Optimized geometries of the title compounds were obtained and the comparison of the experimental structures to the molecular optimized structures is shown in Figure 10, which demonstrates the good consistency between the bond lengths and bond angles for the title compounds. For 3C16, the correlation coefficients are R2 = 0.99997 (bond length) and R2 = 0.99971 (bond angle), respectively. For 3C17, the correlation coefficients are R2 = 0.99998 (bond length) and R2 = 0.99984 (bond angle), respectively. Table 2 and Table 3 list the comparisons between the optimized structural parameters, bond lengths, and bond angles for the experimental and calculated results, respectively. ## 2.4.2. Frontier Molecular Orbitals Frontier molecular orbitals (FMOs) play a crucial role in predicting the chemical reactivity and stability of molecules [58,59,60]. FMOs refer to the collective term of a molecule’s highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), the energy gap (i.e., the gap) between the HOMO and the LUMO reveals the charge transfer of electrons. The gap defines the first excited state, reflecting the dynamical stability and chemical reactivity of the molecule. Figure 11 shows the energy level diagram of the frontier molecular orbitals and secondary orbitals for 3C16, where the HOMO and LUMO are both distributed in the carboxyl and amido. The HOMO of the secondary orbitals is distributed in the carboxyl group, indicating the nucleophilic region, and the LUMO is located in the amido group, indicating the electrophilic region. Figure 12 shows the energy level diagrams of the frontier molecular orbitals and secondary orbitals for 3C17, whose distribution of the HOMO and the LUMO on the functional groups is the same as that of 3C16. The energy gap of the frontier molecular orbitals for 3C16 is 0.2858 eV and the energy gap of the secondary orbitals is 0.6803 eV. The energy gap of the frontier molecular orbitals for 3C17 is 0.2855 eV and the energy gap of the secondary orbitals is 0.6966 eV. Through the analysis of frontier molecular orbitals, we can obtain various molecular reactivity descriptors [53] to better understand the chemical properties of the title compounds, where molecular electronegativity (χ) and chemical hardness (η) of the molecules were calculated using the formula, χ = (I + A)/2, and η = (I − A)/2, where I is the ionization energy, which is a measure of the electron giving the ability of the molecules, and A is the electron affinity, which is a measure of the electron receiving ability of the molecules. In numerical terms, I = −EHOMO, and A = −ELUMO. Chemical potential (μ) is opposite to molecular electronegativity in numerical value, i.e., μ = −χ. The chemical flexibility (σ) and electrophilicity index (ω) of the molecules were calculated using the formula, σ = $\frac{1}{2}$η and ω = χ$\frac{2}{2}$η. The calculated results of the reactivity descriptors of 3C16 and 3C17 are listed in Table 7 and Table 8. ## 2.4.3. Density of States The density of states (DOS) is essentially the number of different states of molecular orbitals under a certain energy level [61,62,63], and the corresponding DOS graph is an important analytical tool. TDOS describes the entire system orbits, or with the help of partial density of states (PDOS), contributes to each molecular orbital in the whole system. The overlap population density of states (OPDOS) is useful in examining the interaction between fragments, and its numerical value is positive for covalent bond orbitals and negative for antibonding orbitals. The DOS analysis of the two molecules was performed using the B3LYP density functional method with 6–31G* basis set, and the plots were drawn by the Multiwfn program package. Figure 13a,c depict the DOS of 3C16 and 3C17 drawn by the Hirshfeld method and by different functional groups, respectively. Figure 13a shows that the functional group contributing the most to the HOMO (−2.9334 eV) of 3C16 is carboxyl, followed by amine. Figure 13c reveals that the functional group contributing the most to the HOMO (−2.9943 eV) of 3C17 is carboxyl, followed by amine, which is consistent with the results of Section 2.4.2. The projection of the density of states (PDOS) analysis, as depicted in Figure 13a,c, elucidates the electronic contribution of various functional groups to the frontier molecular orbitals. Notably, the amine groups, upon protonation, exhibit a significant shift in their electronic density, which is reflected in the negative LUMO energy values. The protonation of the amine nitrogen leads to a withdrawal of electron density from the molecular orbitals, resulting in an increase in the LUMO energy. This effect is more pronounced in the crystalline state due to the periodic potential and the interactions with neighboring molecules, which is consistent with the observed negative LUMO energy values. Figure 13b,d shows the DOS of 3C16 and 3C17 plotted according to different angular momenta. Figure 13b,d indicate that the orbitals contributing the most to the HOMO of 3C16 and 3C17 are p orbitals, followed by s orbitals. The analysis of OPDOS results shows that the antibonding orbitals of the two compounds appear in approximately the same position. ## 2.4.4. Molecular Electrostatic Potential The molecular electrostatic potential (ESP) is a crucial concept in wavefunction analysis [64,65,66,67], playing a key role in discussions of electrostatic interactions. ESP analysis helps to identify reactive sites in molecules, which are determined by their electrostatic potential values computed for uniformly distributed regions on a van der Waals surface. The molecular electrostatic potential V(r) at each point r in the surrounding space is generated by the electron and atomic nucleus of the molecule, V(r) = ZA/(RA − r) − ∫ρ(r’)d r’/\|(r − r’)\|, where ZA is the charge at radius RA on the atomic nucleus A, and ρ(r) is the electron density of the molecule. The ESP map was drawn with a combination of Gaussian 09, Multiwfn package, and VMD software [68], based on the B3LYP density functional method and 6–31G* basis set. Figure 14a,b show the molecular surface electrostatic potentials of 3C16 and 3C17, respectively. The red (positive) coloration area on the ESP map indicates the hydro-positive sites, while the blue (negative) coloration area indicates the electro-positive sites. The negative electro-positive sites of 3C16 mainly focus on carboxylic, with a minimum electrostatic potential of −113.50 kcal/mol. The positive electro-positive sites of 3C16 are dispersed around amine, with a maximum electrostatic potential of 110.44 kcal/mol. The distribution of positive and negative electro-positive sites of 3C17 is the same as 3C16, with a minimum electrostatic potential of −112.54 kcal/mol and a maximum electrostatic potential of 110.82 kcal/mol. The detailed data of the electrostatic potential distribution of 3C16 and 3C17 are listed in Figure S1, and Tables S4 and S5. The large difference in electrostatic potential between the two molecules can be used to predict that their active sites can interact strongly with adjacent molecules. Figure 14c,d show the quantitative distribution of the molecular surface electrostatic potential of 3C16 and 3C17. It can be seen from the chart that the molecular surface electrostatic potential of these two molecules is mainly focused between −20~20 kcal/mol. Most of them are near 0 kcal/mol, which is powerful evidence of weak intermolecular and intramolecular interactions. ## 3.1. Sample Synthesis and Instruments All reagents and solvents required for the synthesis were purchased from commercial suppliers in China. Specifically, 1,3-propanediamine, hexadecanoic acid, heptadecanoic acid, and ethanol were all of analytical purity, with specifications above $95\%$. In the experiment, the molar ratio of the two ligand acids to 1,3-propanediamine was 2.5:1. The excess of acid was chosen to ensure that the carboxyl groups fully engage with the two amine groups. The key step in synthesizing 3C16 involved weighing out 0.0038 mol of solid hexadecanoic acid and dissolving it in 100 mL of ethanol solution to form a precursor clear solution for 3C16. To this precursor, 0.0015 mol of 1,3-propanediamine liquid was added dropwise, with the strict condition that no precipitate was allowed to form during the slow addition process. The well-prepared clear solution was then heated on a rotary evaporator with a rotation speed of 1500 r/min and a temperature of 60 °C. Heating was stopped when the solution volume was reduced to 60 mL, and the power was turned off. The key steps for synthesizing 3C17 were similar: 0.0038 mol of solid heptadecanoic acid was weighed out and dissolved in 100 mL of ethanol solution to form a precursor clear solution for 3C17. Again, 0.0015 mol of 1,3-propanediamine liquid was added dropwise, with the same condition regarding the absence of precipitate. Under the same conditions, the well-prepared clear solution was heated on the rotary evaporator, and heating was ceased when the solution volume was reduced to 80 mL, followed by power shutdown. The post-reaction solution needed to be slowly cooled at room temperature, awaiting the crystallization of the sample. The crystallized samples were then subjected to recrystallization treatment. After drying in a vacuum desiccator for six days, the samples were placed in weighing bottles for further use. The actual mass fraction purity of samples 3C16 and 3C17, as determined by high-performance liquid chromatography (HPLC), was above $98\%$. Calculations revealed that the yields of both compounds were over $40\%$. It should be noted that the reaction yield was not the most critical factor, as we had to perform repeated recrystallization on the primary products, at least three times or more. The scheme of the synthesized compounds is shown in Figure 15. Agilent GC 6890N was used for gas chromatography, Vario EL III was used for element analysis, and XD-2700 was used for XRD. ## 3.2. Basic Experimental Data Hydrous 1,3-propanediamine dihexadecanoate (abbreviated as 3C16) and 1,3-propanediamine diheptadecanoate (abbreviated as 3C17) were successfully synthesized. Translucent colorless solid, yield: 3C16: $82\%$ (214 mg); 3C17: $75\%$ (192 mg). XRD (Cu-Kα1 radiation, λ = 0.15406 nm): 3C16: [0 0 3], [1 0 4], [0 1 6], (1 0 7¯), (1 2¯ 0), (1 2¯ 2¯); 3C17: [0 0 3], [1 0 4], [1 0 5], [1 0 6], (1 2¯ 1), (1 2¯ 2¯). The XRD diagrams are shown in Figure 16. Elemental analysis calcd (%) for 3C16 (622.99): C, 67.19; N, 4.42; H, 12.75; O, 15.64; found: C, 67.48; N, 4.50; H, 12.62; O, 15.40. Elemental analysis calcd (%) for 3C17 (651.04): C, 68.02; N, 4.23; H, 12.84; O, 14.91; found: C, 68.26; N, 4.30; H, 12.70; O, 14.74. The oxygen atoms’ content was measured by indirect method. ## 3.3. X-ray Crystallography The crystals were glued to the fine glass fibers and then mounted on the Bruker Smart-1000 CCD diffractometer with Mo-Kα radiation, λ = 0.71073 Å. The intensity data were collected in the φ–ω scan mode at $T = 273$ K. The size of 3C16 is 0.44 × 0.18 × 0.07 mm3. The size of 3C17 is 0.12 × 0.11 × 0.1 mm3. The structures of title compounds were solved by the direct method and the differential Fourier synthesis, and all non-hydrogen atoms were refined anisotropically on F2 by the full-matrix least-squares method. All calculations were performed with the program package SHELXTL [69]. The program used in the building structure was Diamond 3.2 software (Copyright© 1997–2009 by CRYSTAL IMPACT Dr. K. Brandenburg & Dr. H. Putz GbR). We only needed to import the refined CIF into the software for processing. The relevant atomic theories were hydrogenated and refined. The hydrogen atoms were added theoretically, riding on the concerned atoms, and not refined. The crystal data and structure refinement for the title compounds are summarized in Table 1. We applied two compounds of 3C16 and 3C17 to the Cambridge crystal data center (CCDC) with numbers 2238301 and 2238306. ## 3.4. CrystalExplorer In Section 2.3, the CIF format files of title compounds were obtained by the program package SHELXTL. By inputting the CIF files into relevant quantitative calculation software, the weak interaction between complex molecules can be obtained. The graphics software selected for quantum chemical calculation in this experiment was CrystalExplorer 17.5 [70]. CrystalExplorer 17.5 provides a new way of visualizing molecular crystals using the full suite of Hirshfeld surface tools [71]. Hirshfeld surface is the isosurface with a weight coefficient w(r) equal to 0.5. The average charge density of molecules inside the isosurface should exceed the average charge density of all surrounding molecules (w(r) ≤ 0.5 within the isosurface, w(r) ≥ 0.5 outside the isosurface). This ratio is also approximately the ratio of the charge density of real molecules to that of real crystals. Hirshfeld surface [71] is a new definition of molecular surface. Hirshfeld surface analysis can achieve real and continuous 3D visualization, and 2D fingerprint is the two-dimensional representation of Hirshfeld surface analysis. ## 3.5. Multiwfn Multiwfn, fully known as multifunctional wave function analyzer, is a very powerful wave function analysis program written by Chinese scientist Lu Tian [72], which can realize almost all the most important wave function analysis methods in the field of quantum chemistry. Multiwfn has the advantages of being easy to learn and use, efficient, flexible, open source, and free. This program has users all over the world and has been used by more than 1000 academic papers or books. ## 4. Conclusions 3C16 and 3C17 belong to the triclinic system with a space group P-1. It was discovered that H2O plays a vital role in securing the molecular framework of the two molecules. Hirshfeld surface analysis verified the presence of N-H...O intermolecular interaction with the amine donor and O-H...O intermolecular interaction with the H2O donor in both of the molecules. The 2D fingerprint indicated that the major contributions come from H...H (3C16 $79.4\%$, and 3C17 $80\%$) bonds. The void analysis showed that the mechanical properties of the two molecules are strong. The enrichment analysis indicated that these two kinds of intramolecular O-H contacts are powerful. A 3D energy framework construction revealed that dispersion energy was predominant in the two molecules. DFT calculations indicated that the experimental structural parameters are consistent with their theoretical counterparts. FMO analysis was used to determine the reactivity descriptors of the two molecules, and the charge distributions on the ESP diagrams demonstrate the chemical reaction sites of the two molecules. ## References 1. Takamizawa S., Takasaki Y.. 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--- title: Renal Stones and Gallstones Correlated with the Ten-Year Risk Estimation of Atherosclerotic Cardiovascular Disease Based on the Pooled Cohort Risk Assessment of Males Aged 40–79 authors: - Hui-Yu Chen - Chih-Jen Chang - Yi-Ching Yang - Feng-Hwa Lu - Zih-Jie Sun - Jin-Shang Wu journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10052154 doi: 10.3390/jcm12062309 license: CC BY 4.0 --- # Renal Stones and Gallstones Correlated with the Ten-Year Risk Estimation of Atherosclerotic Cardiovascular Disease Based on the Pooled Cohort Risk Assessment of Males Aged 40–79 ## Abstract Background: The risk of developing atherosclerotic cardiovascular disease (ASCVD) is unknown for subjects with both gallstones and renal stones, nor is it known whether there is a difference in the risk between gallstones and renal stones. This study aimed to determine the risk relationship between gallstones and renal stones and the risk of ASCVD in a male population. Methods: We recruited 6371 eligible males aged 40 to 79 years old who did not have a documented ASCVD history. The ten-year ASCVD risk was calculated using the pooled cohort equations developed by the American College of Cardiology (ACC) and the American Heart Association (AHA). The ASCVD risk score was classified as a low risk (<$7.5\%$), an intermediate risk ($7.5\%$ to $19.9\%$), or a high risk (≥$20\%$). The diagnosis of gallstones and renal stones was established based on the results of abdominal sonography. Results: Both gallstones and renal stones were associated with a high level of intermediate risk (OR = 3.21, $95\%$ CI = 1.89–5.49, $p \leq 0.001$) and high risk (OR = 3.01, $95\%$ CI = 1.48–6.12, $p \leq 0.001$), compared to individuals with no stones at all, after adjusting for the effects of other clinical variables. The possession of gallstones was associated with a higher level of high ASCVD risk (OR = 1.84, $95\%$ CI = 1.31–2.59, $p \leq 0.05$) than that of renal stones. Conclusions: The ASCVD risk was higher for males with gallstones than for those with renal stones. Men with both types of stones faced a risk of ASCVD that was three times higher than that of men without stones. ## 1. Introduction Renal stone disease and gallstone disease are commonly encountered in clinical practice. The prevalence of renal stones varies between $2\%$ and $20\%$ of the population, while that of gallstones has been reported to be in the range of 10–$15\%$ [1,2]. Previous research has suggested that $90\%$ of renal stones are calcareous stones [3], while gallstones are categorized as either cholesterol stones (80–$90\%$) or pigment stones (10–$20\%$) [4]. Although the mechanisms underlying their development remain unclear, renal stones and gallstones share a number of risk factors, such as obesity, hypertension, diabetes, metabolic syndrome, and dyslipidemia [4,5]. Cardiovascular diseases (CVDs) cause significant morbidity and mortality, leading to around 18 million deaths per year worldwide [6]. Although both genders face the same lifetime risk of CVDs, males generally develop CVDs at a younger age [7]. Regarding CVD prevention, the guidelines of the American College of Cardiology (ACC) and the American Heart Association (AHA) recommend the use of a ten-year atherosclerotic cardiovascular disease (ASCVD) risk estimation [8]. Studies have indicated that the presence of both gallstones [9,10,11] and renal stones [12,13,14] is associated with an increased risk of CVD [9,10,11,12,13,14]. However, to our knowledge, two questions remain unanswered: what is the risk of CVD for males with both gallstones and renal stones? Additionally, is there a difference in CVD risk between gallstones and renal stones? Therefore, the aim of this study was to assess the ASCVD risk across different groups of males: males who had no stones, those with either gallstones or renal stones, and those with both types of stones. ## 2. Methods To carry out this cross-sectional study, we first recruited males of 18 years of age or older who received given check-ups at the health examination center of the National Cheng Kung University Hospital during the period from June 2001 to August 2009. We then excluded individuals who were aged under 40 years old and over 79 years old ($$n = 3400$$), those who had a history of stroke or ischemic heart disease ($$n = 108$$), those who were deemed to be heavy drinkers, defined as an alcohol consumption of 196 gm/week ($$n = 47$$) [15], and those whose abdominal sonography exam showed signs of post-cholecystectomy syndrome ($$n = 106$$). In the final analysis, 6371 people were eligible to participate in the study. The study was approved by the Ethical Committee for Human Research of the National Cheng Kung University Hospital (IRB number: A-ER-111-366). First, the participants were asked to fill out a questionnaire that included information about their personal medical history, as well as habits such as smoking, alcohol consumption, and regular exercise. The formula used for determining the body mass index (BMI) was weight (in kilograms) divided by height (in meters) squared. The behaviors of cigarette smoking and alcohol consumption were scored as currently exhibited and not currently exhibited, and exercise performed regularly was defined as more than 20 min of physical activity performed at least three times a week. The participants were then placed at rest in a supine position for at least 5 min, after which their systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured. They were considered to have hypertension if they either exhibited a blood pressure measurement of SBP/DBP ≥ $\frac{140}{90}$ mmHg or had a positive history of hypertension. All participants were required to fast overnight for 10 h in order to ascertain their levels of glucose, hemoglobin A1c, cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C). An oral glucose tolerance test (75 gm) was performed with subjects who had no history of diabetes. In addition to some participants having a positive history of diabetes, the existence of diabetes mellitus was determined on the basis of a fasting plasma glucose level of ≥7 mmol/L, a 2 h post-load glucose level of ≥11.1 mmol/L, or a hemoglobin A1c level of ≥$6.5\%$. After fasting, all participants underwent abdominal sonography carried out by experienced radiologists who were unaware of this study. The ultrasounds were performed using a convex-type real-time electronic scanner (XarioSSA660A, Toshiba, Tokyo, Japan), with the results used as the basis for the diagnosis of renal stones and gallstones. A diagnosis of renal stones was established when the sonogram showed either [1] light points or light regions in the kidneys accompanied by vertical acoustic shadows or [2] several echo light bands, strong echoes, or acoustic shadows [16]. Sonographic findings of highly reflective echogenic foci in the gallbladder lumen were the basis of a diagnosis of gallstones [17]. We classified the participants according to their results for the sonography test, as individuals who had no stones, those with renal stones, those with gallstones, and those with both types of stones. We calculated the ten-year ASCVD risk using the pooled cohort equations (PCE) designed by the ACC and the AHA [8]. The calculation of the ASCVD risk was based on age, sex, levels of cholesterol and HDL-C, chronic hypertension, diabetes, and smoking habits. The ten-year ASCVD risk scores were categorized as low risk (<$7.5\%$), intermediate risk ($7.5\%$ to $19.9\%$), and high risk (≥$20\%$). ## Statistical Analyses We used the 20th version of the SPSS software (Chicago, IL, USA) to perform the statistical analyses. The continuous variables were expressed as means ± standard deviation, and the categorical variables were expressed as percentages. One-way ANOVA and the chi-square test were used to compare the continuous variables and the categorical variables, respectively, between the groups established on the basis of the presence or absence of gallstones and renal stones. Multinomial logistic regression was used to adjust for the effects of BMI, alcohol consumption, and regular exercise. The adjusted odds ratio (OR) and the $95\%$ confidence interval (CI) were determined in order to assess the associations between the presence or absence of stones and the intermediate level and the high level, respectively, of ASCVD risk. ## 3. Results The ten-year ASCVD risk score for the 6371 eligible males, with an average age of 52.9 ± 8.9 years old, was 9.5 ± $9.7\%$. In terms of their risk levels, 3633 participants ($57\%$) fell into the low-risk category, 2006 ($31.5\%$) were in the intermediate-risk category, and 732 ($11.5\%$) were in the high-risk category. Table 1 summarizes their clinical characteristics according to the presence or absence of stones as none, only gallstones, only renal stones, and both gallstones and renal stones. Significant differences in age, SBP/DBP, history of hypertension and diabetes, serum HbA1C, cholesterol, and ten-year ASCVD risk were found between the groups. The rates of the prevalence of intermediate and high levels of ASCVD risk were $29.8\%$ and $10.6\%$, respectively, for the group without stones, $37.6\%$ and $19.4\%$ for the group with gallstones, $36.9\%$ and $12.5\%$ for the group with renal stones, and $52.1\%$ and $16.9\%$ for the group with both types of stones. Table 2 presents the factors that were independently associated with both intermediate and high levels of ASCVD risk. After adjusting for the effects of BMI, current alcohol consumption, and regular exercise (≥3 times/week) so that these characteristics of the subjects without stones could be used as benchmarks, the ASCVD risk was found to be higher among subjects with both types of stones (intermediate risk: OR = 3.21, $95\%$ CI = 1.88–5.49, $p \leq 0.001$; high risk: OR = 3.01, $95\%$ CI = 1.48– 6.12, $p \leq 0.001$), renal stones (intermediate risk: OR = 1.45, $95\%$ CI = 1.23–1.70, $p \leq 0.001$; high risk: OR = 1.37, $95\%$ CI = 1.09–1.73, $p \leq 0.01$), and gallstones (intermediate risk: OR = 1.78, $95\%$ CI = 1.42–2.24, $p \leq 0.001$; high risk: OR = 2.53, $95\%$ CI = 1.91–3.35, $p \leq 0.001$). We compared the ASCVD risk between subjects with gallstones and those with renal stones after the adjustments for BMI, current alcohol consumption, and regular exercise (≥3 times/week) (see Table 3). The presence of gallstones was associated with a significantly higher level of high ASCVD risk (OR = 1.84, $95\%$ CI = 1.31–2.59, $p \leq 0.05$) compared to the association of the same risk associated level with the possession of renal stones alone, but such a difference was not observed for the intermediate level of risk. On the other hand, subjects with both types of stones faced significantly higher levels of intermediate and high ASCVD risk compared to subjects with only renal stones (intermediate risk: OR = 2.22, $95\%$ CI = 1.28–3.86, $p \leq 0.01$; high risk: OR = 2.19, $95\%$ CI = 1.05–4.57, $p \leq 0.05$). Finally, subjects with both types of stones faced a significantly higher level of intermediate ASCVD risk compared to subjects with only gallstones (intermediate risk: OR = 1.80, $95\%$ CI = 1.01–3.20, $p \leq 0.05$). ## 4. Discussion In this study, the intermediate level (OR = 3.21) and high level (OR = 3.01) of ASCVD risk were three times higher for males with both gallstones and renal stones compared to individuals with no stones. The presence of both types of stones was also associated with a higher intermediate level of ASCVD risk, with OR values that were 1.7 times and 2.2 times higher than the values for the presence of gallstones alone and renal stones alone, respectively. In addition, the high level of ASCVD risk was $84\%$ higher for subjects with only gallstones compared to those with only renal stones. The association of gallstones and renal stones with the risk of CVD found in this study is consistent with the findings of other studies conducted on individuals with either gallstones [9,10,11,18,19,20] or renal stones [12,13,14]. More specifically, a recent meta-analysis conducted by Zhao et al. suggested that the risk of incidence (HR = 1.24) and prevalence (OR = 1.23) of CVD were higher among people with gallstones [9]. In addition, renal stone diseases have been associated with a high risk of subsequently experiencing cardiovascular events [12,14,21,22,23,24,25]. In another meta-analysis conducted by Liu et al., it was reported that the presence of renal stones increased the risk of developing myocardial infarction by $29\%$ (HR = 1.29) and increased the risk of stroke by $40\%$ (HR = 1.40) over a follow-up period of 5 to 11 years [14]. However, none of these studies compared the cardiovascular risk associated with the presence or absence of gallstones and renal stones, nor did they specify the intermediate and high levels of cardiovascular risk. To our knowledge, our study is the first to take into consideration both the intermediate and high risks of CVD among males with both gallstones and renal stones while also comparing the associations of ASCVD with the possession of renal stones and with the possession of gallstones. The association of the presence of gallstones and renal stones and with CVD can be explained based on the common pathophysiology of these conditions, even though the underlying mechanisms are not fully understood [9,24,26]. Gallstones and renal stones share common risk factors such as age, obesity, chronic hypertension, and diabetes mellitus [9,24,26]. There exists a number of possible mechanisms, such as inflammation, insulin resistance, and calcium deposits, that might explain the relationship between both types of stone diseases and an increased risk of CVD. Studies have shown that aberrant inflammation and oxidative stress are involved in the development of renal stones, gallstones, and CVD because they play significant roles in metabolic syndromes, obesity, and insulin resistance [9,26,27,28]. It has also been suggested that insulin resistance and the inflammatory response in the gallbladder and kidneys promote atherosclerosis and vasculopathy in the blood vessels [9,24,27,28]. In addition, insulin resistance has been identified as a determining factor in the formation of gallstones, because it leads to the excess secretion of biliary cholesterol and gallbladder dysmotility [29]. Insulin resistance has also been associated with the formation of renal stones as a result of the increasing deposition of calcium oxalate crystals and decreasing urine pH [5]. In general, calcium has been shown to play an important role in many physiological processes, including blood coagulation, muscle contraction, nerve conduction, and epithelial secretion and absorption [30]. More specifically, it has been suggested that the precipitation of calcium salts is the main factor promoting the formation of renal stones [5] and elevated concentrations of calcium might increase vascular calcification and blood coagulation, which are considered to be factors involved in the development of CVD [31]. In addition, the deposition of calcium salts is important for the formation of pigment gallstones and is a nidus of the development of cholesterol gallstones [30]. It should be noted that it is as yet unknown why subjects with gallstones face a higher cardiovascular risk than those with renal stones. Bile acids are important elements of the diversity and metabolic activity of the microbiota. Additionally, the bile acid pool is conducted by the gut microbiota [32]. Recent research suggests that a disturbance of the secretion of bile acids contributes to the formation of gallstones and dysbiosis of the gut microbiota, the latter of which has emerged as a novel CVD risk [33,34]. Specifically, dysbiosis has been implicated in CVD, together with various aspects of cardiometabolic syndrome: obesity, hypertension, chronic kidney disease, and diabetes. A mechanistic link between the gut microbiota formation of trimethylamine-N-oxide (TMAO) and CVD has been demonstrated [35]. Therefore, it might be possible to partly explain the higher cardiovascular risk associated with gallstones on the basis of the metabolic function of the gut microbiota. In addition to the clinical variables included in the estimation of the ten-year ASCVD risk, such as age and sex, as well as the levels of total cholesterol and of HDL-C and the existence of chronic hypertension, diabetes, and smoking, this study also revealed a relationship between BMI and the risk of ASCVD. A number of studies have shown that BMI [36] is positively related to the future development of CVD, while alcohol consumption [37] and regular exercise [38] have been shown to have an inverse relationship. In the current study, we found that BMI was positively associated with both intermediate and high levels of ASCVD risk, an observation which is compatible with the findings of other studies. [ 36] In this study, after excluding 47 participants who were deemed to be heavy drinkers, all the remaining drinkers reported low to moderate levels of alcohol consumption. In the final analysis, a negative correlation was found between alcohol consumption and an intermediate level of ASCVD risk. This result is consistent with the findings of previous studies, demonstrating that low to moderate levels of alcohol consumption are associated with decreased cardiovascular morbidity and mortality [37]. As for the lack of a significant correlation between low to moderate levels of alcohol consumption and a high level of ASCVD risk, the explanation may be that the impact of these levels of alcohol consumption is relatively weak compared to the impacts of the traditional risk factors for CVD, but further research is required to determine whether or not this assumption is correct. It has been suggested that regular physical activity may be beneficial in either directly or indirectly reducing the risk of CVD [38]. However, to our surprise, we found a positive relationship between regular exercise and an intermediate level of ASCVD risk, although the correlation between regular exercise and a high level of ASCVD risk was insignificant. These findings might be a result of the possibility that people started to perform regular exercise after becoming aware of their cardiovascular risk factors, such as elevated levels of blood pressure, blood glucose, or cholesterol, in this cross-sectional study. In Taiwan, a national preventive health screening program for adults of ≥40 years of age, similar to the health check program carried out by the NHS (National Health Service) in England for adults aged 40–74 years of age, was implemented in 1996. Such findings might provide more opportunities to raise people’s awareness of the benefits of physical activity. There are several limitations of this retrospective cross-sectional study. Firstly, we were unable to make any causal inferences regarding the relationship between the presence of renal stones or gallstones and the risk of ASCVD. To address this shortcoming, prospective research should be carried out as a means of clarifying the cause-and-effect relationships which might be at play. Secondly, since the study involved only males aged 40 to 79 years old, the finding of a relationship between the possession of renal stones and gallstones and the development of CVD cannot be generalized to the entire population. Thirdly, a wide range of sensitivities and specificities have been reported in regard to ultrasonography, probably owing to variations in technique, body habitus, patient population, or interference from bowel gas [39]. In this study, all the abdominal sonographies were carried out by a fixed number of experienced radiologists. Additionally, we could not identify the exact sizes or the specific subtypes of renal stones [40] and gallstones [41] affecting each subject, and the processes through which different sizes and different subtypes form might lead to different cardiovascular risks. Further research may be needed to examine the associations between various subtypes of stones and the risk of CVD. Additionally, although we adjusted for body mass index, alcohol consumption, and exercise to reduce the degree of bias, the influences of diet, medication, and genetics, which were not collected in this study, cannot be completely ruled out. Finally, some studies have reported that the use of pooled cohort equations to estimate ASCVD risk appears to lead to the overestimation of this risk in Asian populations [42]. However, despite the lack of a validated score for an Asian population, the pooled cohort approach remains an option for clinicians who wish to discuss possible strategies for the prevention of CVD with their patients. ## 5. Conclusions Both gallstones and renal stones were associated with high levels of intermediate- and high-level ASCVD risk. The risk was higher in males with gallstones than in those with renal stones. 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--- title: Probiotic Bifidobacterium breve MCC1274 Protects against Oxidative Stress and Neuronal Lipid Droplet Formation via PLIN4 Gene Regulation authors: - François Bernier - Tatsuya Kuhara - Jinzhong Xiao journal: Microorganisms year: 2023 pmcid: PMC10052176 doi: 10.3390/microorganisms11030791 license: CC BY 4.0 --- # Probiotic Bifidobacterium breve MCC1274 Protects against Oxidative Stress and Neuronal Lipid Droplet Formation via PLIN4 Gene Regulation ## Abstract Consumption of Bifidobacterium breve MCC1274 has been shown to improve memory and prevent brain atrophy in populations with mild cognitive impairment (MCI). Preclinical in vivo studies using Alzheimer’s disease (AD) models indicate that this probiotic protects against brain inflammation. There is growing evidence that lipid droplets are associated with brain inflammation, and lipid-associated proteins called perilipins could play an important role in neurodegenerative diseases such as dementia. In this study, we found that B. breve MCC1274 cell extracts significantly decreased the expression of perilipin 4 (PLIN4), which encodes a lipid droplet docking protein whose expression is known to be increased during inflammation in SH-SY5Y cells. Niacin, an MCC1274 cell extract component, increased PLIN4 expression by itself. Moreover, MCC1274 cell extracts and niacin blocked the PLIN4 induction caused by oxidative stress in SH-SY5Y cells, reduced lipid droplet formation, and prevented IL-6 cytokine production. These results offer a possible explanation for the effect of this strain on brain inflammation. ## 1. Introduction Sporadic and familial Alzheimer’s diseases (ADs) are debilitating neurodegenerative conditions that involve the deposition of amyloid plaques and Tau tangles in the brain [1]. The tremendous efforts made by pharmaceutical companies to develop anti-amyloid therapies over the last 20 years have all failed to completely stop the disease progression [2], suggesting that our understanding of the function of amyloid beta and its role in AD etiology is far from clear and that novel strategies are needed to combat this disease. In recent years amyloid beta has gradually come to be recognized as an antimicrobial peptide [3] that is produced in response to brain inflammation and protects the brain against various pathogens. Brain inflammation also occurs in individuals with mild cognitive impairment (MCI), years before AD onset [4]. Increasing evidence suggests that brain inflammation is linked to gut microbiome dysbiosis. A leaky gut–blood barrier permits the release of gut microbes themselves or their toxins into the bloodstream, triggering the amyloid formation cascade and resulting in gradual neuronal cell death [5]. This sequence of events suggests that effective anti-inflammatory therapies could halt AD progression before it becomes irreversible [6]. Recent studies have shed light on how brain cell lipid metabolism undergoes profound changes in response to the oxidative stress experienced by cells during inflammation, as shown by lipid droplet (LD) accumulation in the brain cells of AD patients and in AD mouse models [7,8,9]. These LDs, which are rich in free fatty acids (FFAs), can serve as a transient energy source for neuronal cell mitochondrial beta-oxidation when energy is in high demand, such as during inflammation [10]. LD recruitment to mitochondria to serve as an energy source is mediated by a family of proteins called perilipins (PLIN1-5), which are expressed in various cells throughout the body [11,12]. Neurons and muscle cells rely on PLIN4 to enable mitochondria to use LDs for beta-oxidation under conditions of inflammation and oxidative stress [13]. Although beta-oxidation can generate more ATP than oxidative phosphorylation, it produces more peroxide. It also consumes more oxygen, potentially damaging neurons, which would explain why these cells preferentially use glycolysis and ketolysis to generate ATP under normal conditions [14]. It was recently reported that PLIN4 expression is induced when neurons are exposed to the toxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which impairs mitophagy-mediated repair of damaged mitochondria; this finding supports the neuronal preference for energy production pathways that do not involve beta-oxidation [13]. Probiotics are live microorganisms that can potentially help to treat several mental illnesses [15]. They are “friendly” or “healthy” bacteria that we ingest through foods, beverages, and dietary supplements. Two of the most frequently reported benefits of probiotics are the anti-inflammatory effect that they exert on the central nervous system (CNS) through the gut–brain axis [16,17] and the correction of gut microbiota dysbiosis, which is related to CNS disorders, with poorly understood etiology, and infections [18]. Considerable effort has gone into studying the anti-inflammatory effects of the short-chain fatty acids (SCFAs) produced by probiotics (acetate, butyrate, and propionate) [19]. However, given that SCFAs exhibit low penetration of the brain, other important molecule(s) produced by probiotics are likely to be responsible for their apparent anti-inflammatory effects. Three decades ago, well before SCFAs were identified, certain probiotics such as Lactobacillus and Bifidobacterium were shown to produce and accumulate essential vitamins, such as niacin (vitamin B3) [20,21], that are linked to the regulation of inflammatory processes [22,23]. Recently, our group demonstrated that daily consumption of Bifidobacterium breve MCC1274 improved memory in individuals suffering from mild cognitive impairment (MCI), as well as preventing brain atrophy, in separate randomized double-blind placebo-controlled trials [24,25]. Furthermore, treating APPKI mice (AppNL-G-F) with the same probiotic reduced amyloid plaque deposition, increased alpha-secretase expression, and decreased microglial cell activation [26]. Plasma metabolomics analysis of these mice indicated that MCC1274 consumption increased the levels of several metabolites with known activity against oxidative stress, as well as metabolites related to the mitochondrial TCA cycle, although the specific metabolite(s) responsible for these effects were not identified [27]. In the present study, we asked whether other metabolites generated by this probiotic prevent the inflammation-derived oxidative stress and lipid droplet formation that occur in MCI and Alzheimer’s disease by controlling perilipin gene expression. ## 2.1. Preparation of Live Bacterial Cells Bifidobacterium breve MCC1274 cells (Morinaga Milk Research Center, Zama, Japan) were grown in MRS medium (Difco, Beckton Dickinson, Franklin Lakes, NJ, USA) for 16 h in an anaerobic chamber at 37 °C. The cells were then transferred to 50 mL Falcon tubes (Corning, Reynosa, Mexico) and centrifuged at 8000× g for 10 min. Next, the cell pellets were washed and centrifuged three times with PBS buffer to remove any traces of the MRS fermentation medium. The wet cell pellets were finally resuspended in PBS at 0.3 g per mL (equivalent to 1 × 108 cells/mL). ## 2.2. Chemicals Nicotinic acid (niacin, NA) was purchased from Tokyo Chemical Industry Co., Ltd. (Tokyo, Japan). Nicotinamide riboside chloride (NR) was purchased from eNovation Chemicals, LLC (Bridgewater, NJ, USA). Nicotinamide adenine dinucleotide (NAD+) and nicotinamide (NAM) were purchased from Merck KGaA (Darmstadt, Germany). Acetonitrile (high-performance liquid chromatography [HPLC] grade) was purchased from FUJIFILM Wako Pure Chemical Corporation (Osaka, Japan). Ammonium acetate (suitable for mass spectrometry) and 3-methyl-2-oxindole were purchased from Merck KGaA. Unless otherwise stated, all chemical reagents used were of analytical grade. ## 2.3.1. Preparation of Heat-Killed Cell Extracts MCC1274 cells suspended in PBS (1 × 108 cells/mL) were heated in Eppendorf tubes on a heating block at 98 °C for 10 min; then, they were centrifuged at 4 °C for 10 min at 8000× g. The supernatant (referred to hereafter as “HKS”) was immediately stored at −80 °C for later use in the in vitro cell culture experiments. ## 2.3.2. Preparation of Sonicated Cell Extracts MCC1274 cells suspended in PBS (1 × 108 cells/mL) were sonicated (one sonic pulse every 2 s) on ice in 15 mL conical polypropylene tubes (Corning, Reynosa, Mexico) for 1 h, and the sonicated products were then centrifuged at 4 °C for 10 min at 8000× g. The supernatant (referred to hereafter as “Sonic”) was immediately stored at −80 °C for later use in the in vitro cell culture experiments. ## 2.4. Cell Culture Human neuroblastoma cells SH-SY5Y were obtained from ATCC, USA. The cells were cultured and maintained in Dulbecco’s Modified Eagle Medium (DMEM, Gibco, Grand Island, NY, USA), containing 4.5 g/L glucose, 4 mM glutamine, $10\%$ heat-inactivated fetal bovine serum (Gibco Life Technologies, Grand Island, NY, USA), 25 mM hepes, and $0.1\%$ (v/v) penicillin/streptomycin (Gibco Life Technologies) in an incubator with a $5\%$ CO2 atmosphere at 37 °C. The cell medium was replaced every three days. The bacterial supernatants (HKS or Sonic) were added to the confluent SH-SY5Y cells in 24-well plates to yield a final concentration of $1\%$ v/v. The cells were then incubated for varying amounts of time in a CO2 incubator. Next, the cell medium was aspirated, 0.5 mL TRIzol (Ambion Life Tech., Austin, TX, USA) was added to cells, and the plates were incubated for 5 min at room temperature. The TRIzol–cell solution was then stored at −80 °C for later RNA extraction. For the experiments related to oxidative stress protection, H2O2 was added at the same time as the MCC1274 extracts or NA. ## 2.5. RNA Extraction Total RNA was extracted from the TRIzol-treated cells using a Qiagen RNeasy Plus Universal Mini kit (Qiagen, Hilden, Germany). After extraction, the RNA concentration and quality were determined using a Nanodrop One device (Thermo Scientific, Waltham, MA, USA). ## 2.6. PCR cDNA was synthesized from 1 μg total RNA using a Takara PrimeScript Reagent kit (TakaraBio, Kusatsu, Shiga, Japan) per the manufacturer’s instruction. Real-time PCR was conducted using a BioRad PCR Thermal Cycler with a final reaction volume of 25 μL containing 50 ng cDNA, 1 μL of each primer pair (20 μM), and Takara TB Green Premix Ex Taq II (TII RNaseH Plus), as per the manufacturer’s kit protocol to determine the relative mRNA concentration for each gene of interest under each treatment condition; all reactions were performed in duplicate. The sequences of the primers used for the PCR reactions are shown in Supplementary Table S2. The relative RNA concentrations were determined using a standard curve generated using a preamplified PLIN4 PCR product or GAPDH. The PCR reaction conditions were as follows: 95 °C for 10 s, followed by 40 cycles of 95 °C for 20 s, 64 °C for 20 s, and 72 °C for 10 s. ## 2.7. Measurement of NA and Related Metabolites by Mass Spectrometry The concentrations of the metabolites in the samples (HKS and Sonic) were analyzed using liquid chromatography–tandem mass spectrometry (LC–MS/MS; Vanquish HPLC connected with TSQ-FORTIS, Thermo Fisher Scientific, Waltham, MA, USA). Chromatographic separation was performed using an XBridge® Phenyl column (Waters Corporation, Milford, MA, USA) (4.6 × 150 mm, 5 μm). Mobile phase A (containing 1 g/L ammonium acetate in water) and mobile phase B (methanol) were applied at a flow rate of 0.2 mL/min. Gradient elution was performed between $2\%$ and $50\%$ of phase B. Quantification was achieved by comparing the metabolite peak areas with the corresponding synthetic compound standards and an internal standard (3-methyl-2-oxindole). The precursor ion’s LC–MS/MS spectrum (product ion data) was evaluated to determine the final content of each metabolite (Table 1 and Table S1). ## 2.8. FACS and LD Assay To detect changes in the LDs following treatments, the cells were washed three times with 1X PBS then stained with BODIPY (2 μM) for 20 min. The cells were then trypsinized and collected for fixation with $4\%$ formalin for 30 min, followed by resuspension in Bio-Rad staining buffer (Bio-Rad, Berkeley, CA, USA). We used a Becton Coulter FACS analyzer to detect the average BODIPY signal intensity (FITC) of 10,000 individual cells for each treatment condition ($$n = 4$$). This measurement indicates the number of LDs present in each cell. The siRNA used to knock down human PLIN4 mRNA expression was purchased from Merck Millipore and transfected into cells using Lipofectamine RNAiMAx reagent (ThermoFisher, Waltham, MA, USA), as per the manufacturer’s instructions. ## 2.9. Microscopy Neuroblastoma SH-SY5Y cells were plated at a density of 150,000 cells/well in a microscopy chamber slide and incubated overnight. The next day, compounds and bacterial extracts were added to cells in the presence of H2O2 (200 μM), and the cells were cultured for another 24 h. The following day, the cell medium was aspirated, and the cells were washed three times with PBS before adding BODIPY staining solution (2 μM) to visualize the lipid droplets. After 20 min of staining, the cells were again washed three times with PBS, fixed for 30 min in $4\%$ paraformaldehyde, and then mounted with Hard Set mounting media containing DAPI (Vector Laboratories, Burlingame, CA, USA) for microscopic analysis (Olympus BX 53). ## 2.10. Statistical Analysis For the in vitro cell experiments, statistical analysis was conducted using Microsoft Excel. Significant differences between treatment conditions and controls were determined using the Student’s t-test for two-group comparison and non-repeated measures ANOVA with the Bonferroni post hoc test for multiple-group comparison, respectively. ## 3.1. Metabolites in B. breve MCC1274 Extracts Specifically Reduce PLIN4 Expression in Human Neuroblastoma Cells To test whether B. breve MCC1274-derived metabolites affected perilipin gene expression, SH-SY5Y human neuroblastoma cells were exposed to the two cell extracts (HKs and Sonic) at final concentration of $1\%$ v/v for 1 h, total RNA was extracted, and RT-PCR was conducted to analyze the changes in perilipin mRNA expression. As shown in Figure 1A–E, the metabolite(s) contained in both extracts (HKS, Sonic) reduced PLIN4 expression but not the expression of any other perilipin at the mRNA level. The HKS preparation method, due to its simplicity, was chosen for further experiments. ## 3.2. NA and B. breve MCC1274 Extracts Reduce PLIN4 mRNA Expression in SH-SY5Y Neuroblastoma Cells A recent study suggested that the tryptophan metabolite NA may reduce lipid droplets in microglia cells [28]. Given that certain Bifidobacterium strains can produce NA [21], we performed mass spectrometry of B. breve MCC1274 extracts to detect NA and its metabolites nicotinamide (NAM), nicotinamide riboside (NAR), and nicotinamide adenine dinucleotide (NAD). As shown in Table 1, both the HKS and Sonic preparations contained around 1 µg/mL of NA, which indicates that the $1\%$ (v/v) extract concentration that we used for the SH-SY5Y cell treatment experiments was equivalent to 100 nM of NA. While the B. breve MCC1274 extracts contained sufficient NA to reduce PLIN4 expression, they might also contain substances that generally do not reach the brain and could negate the effect of the NA. Therefore, we tested whether the purified NA had the same effect as the cell extracts by exposing the SH-SY5Y cells to $1\%$ (v/v) B. breve MCC1274 extract, NA, or NAM for 1 h. As shown in Figure 2, B. breve MCC1274 HKS ($1\%$) and NA (30 nM and 100 nM) caused a rapid decrease in the PLIN4 mRNA expression after 1 h of exposure. While treatment with NAM also decreased the PLIN4 mRNA expression, the effect did not reach significance. Treatment with NAR or NAD did not reduce the PLIN4 mRNA expression. ## 3.3. NA and B. breve MCC1274 Extracts Protect against Oxidative Stress Caused by Exposure to H2O2 Brain cell damage in neurodegenerative diseases is linked to increased oxidative stress and LD formation [29]. Therefore, we hypothesized that NA and B. breve MCC1274 extracts might protect SH-SY5Y cells from exposure to peroxide (H2O2), a very potent inducer of oxidative stress, since they both reduced the mRNA expression of PLIN4, which encodes a lipid droplet chaperone protein. As shown in Figure 3, exposing the cells to H2O2 for 24 h caused an increase in the PLIN4 expression that was blocked by treatment with either the NA or B. breve MCC1274 extracts. ## 3.4. NA and B. breve MCC1274 Extracts Reduce LD Formation after Exposure to H2O2 We then looked at changes in the lipid droplet formation when neuroblastoma cells were exposed to H2O2 using fluorescence-activated cell sorting (FACS). We first confirmed that 200 µM H2O2 increased the LD formation in SH-SY5Y cells [30] using BODIPY staining followed by FACS analysis. We then exposed the cells to NA or B. breve MCC1274 extracts (HKS) with 200 µM H2O2 for 24 h, using a random siRNA as a control and PLIN4 siRNA as a positive control. Oleic acid was also used as a control to induce LD formation (Figure 4, Supplemental Figure S1). The data indicated that the NA produced by B. breve MCC1274 suppressed the LD formation caused by oxidative stress, and this effect was dependent on a selective reduction in the PLIN4 mRNA expression. ## 3.5. NA and B. breve MCC1274 Extracts Prevent the Induction of IL-6 Expression When brain cells are exposed to oxidative stress, they not only exhibit increased LD production but also, as reported previously [13], release inflammatory cytokines such as IL-6 as a distress signal directed toward microglia [31]. Using the same H2O2 exposure conditions, we found that NA and MCC1274 HKS extracts blocked the IL-6 cytokine production induced by oxidative stress, suggesting that NA and B. breve MCC1274 prevent H2O2-induced cell damage (Figure 5). ## 4. Discussion Canadian pathologist Rudolf Altschul first identified NA more than 65 years ago as having lipid-lowering properties [32]. NA is still the focus of intensive research as researchers try to understand its numerous positive effects on the human body, particularly the brain and the immune system. Many studies have demonstrated the potential ability of NA to modulate inflammation [22,23,33]. Earlier this year, Moutinho et al. showed that the induction of HCAR2 expression by NA modulated the microglial response and limited disease progression in a mouse model of Alzheimer’s disease [28]. When the NA receptor expression is eliminated, amyloid beta accumulates in mouse brains, indicating a positive role for this receptor in the stress response. When these mice were treated with NA, robust clearance of amyloid plaques was observed, suggesting that NA may repolarize microglial cells from an M1 (proinflammatory) to an M2 (noninflammatory, phagocytic) type. Our findings that NA blocked oxidative stress, LD formation, and IL-6 expression in neuroblastoma cells were consistent with this earlier finding. The results from our previous study of APP KI treated with B. breve MCC1274 also align with this observation that NA can directly affect brain cells experiencing oxidative stress. In our mouse study, B. breve MCC1274 blocked activation of IBA1 expression by microglial cells. Mice that consumed B. breve MCC1274 also had a lower amyloid plaque burden than the control mice and performed better in a memory-related behavioral test [26]. Blood metabolomics identified multiple molecules such as soy isoflavones (e.g., genistein), indole derivatives of tryptophan (e.g., 5-methoxyindoleacetic acid), and other metabolites with potent antioxidative activities in the group of mice that received probiotics. In addition, the levels of glutathione-related metabolites and TCA cycle–related metabolites that could decrease brain oxidative stress were also elevated. Unfortunately, NA could not be detected in the blood due to its short half-life [34]. A clinical trial is currently underway to determine the potential of NA to treat Alzheimer’s patients (https://clinicaltrials.gov/ct2/show/NCT03061474 (accessed on 3 December 2022)). Our group recently conducted two double-blind placebo-controlled trials in individuals suffering from MCI and showed that B. breve MCC1274 could ameliorate memory and prevent brain atrophy [24,25]. The enhanced cognitive function and reduced brain atrophy that we observed in individuals who consumed B. breve MCC1274 daily might be associated with NA production. Interestingly, Chellappa et al. reported that the gut microbiome converts host-derived nicotinamide into nicotinic acid, maintaining circulating nicotinic acid levels even in the absence of dietary consumption of nicotinamide [35]. This new finding implies that consumption of B. breve MCC1274 could enhance the host’s ability to produce NA and induce a reduction in PLIN4 expression even in the absence of oxidative stress conditions, as we observed (Figure 1D). Our finding that NA production by B. breve MCC1274 directly impacts LD formation by reducing PLIN4 expression reduction is interesting given that LD accumulation is a common phenomenon in tumor cells [36]. It also has come to light recently that a higher intratumoral level of PLIN4 is associated with lower survival rates in patients with colorectal or endometrial cancer (https://www.proteinatlas.org/ENSG00000167676-PLIN4/pathology (accessed on 3 December 2022)). Interestingly, these two organs are located close to the intestine, which contains a microbiota known to harbor Bifidobacterium [37], and a lower abundance of Bifidobacterium near colorectal and endometrial tissues has been linked to a higher incidence of these two cancers [38,39]. We think there is a possibility that NA derived from the Bifidobacterium-rich endometrial and colon microbiotas may protect against these cancers by regulating LD formation by cancer cells. Our study had some limitations that we plan to address soon. First, we would like to understand whether the effect of the MCC1274-derived NA on the brain is mediated by the vagal nerve or via a more classic blood absorption route. Second, we would like to determine whether B. breve MCC1274 can restore the impairment of mitochondrial mitophagy associated with increased PLIN4 expression [13]. Moreover, we would like to investigate whether consuming B. breve MCC1274 impacts mitophagy [40,41,42] related to long-term potentiation (LTP) [43] during brain inflammation and under normal conditions in vivo. ## 5. Conclusions In conclusion, our results demonstrate a novel regulatory mechanism(s) by which B. breve MCC1274 reduces PLIN4 expression and LD formation in neuroblastoma cells undergoing oxidative stress. We also showed that the molecule produced by B. breve MCC1274 that is responsible for blocking LD formation and the resulting inflammation is NA. 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--- title: A Lifetime of a Dispenser-Release Rates of Olive Fruit Fly-Associated Yeast Volatile Compounds and Their Influence on Olive Fruit Fly (Bactrocera oleae Rossi) Attraction authors: - Maja Veršić Bratinčević - Ana Bego - Ivana Nižetić Kosović - Maja Jukić Špika - Filipa Burul - Marijana Popović - Tonka Ninčević Runjić - Elda Vitanović journal: Molecules year: 2023 pmcid: PMC10052186 doi: 10.3390/molecules28062431 license: CC BY 4.0 --- # A Lifetime of a Dispenser-Release Rates of Olive Fruit Fly-Associated Yeast Volatile Compounds and Their Influence on Olive Fruit Fly (Bactrocera oleae Rossi) Attraction ## Abstract The objective of this study was to evaluate the release rate, duration, and biological efficiency of yeast volatile compounds associated with olive fruit flies in slow-release dispensers, polypropylene vials, and rubber septa attached to yellow sticky traps under different environmental conditions in order to protect the environment, humans, and nontarget organisms. Isoamyl alcohol, 2-octanone, and 2-phenethyl acetate were placed in dispensers and tested over a four-week experiment. The weight loss of the volatile compounds in both dispensers was measured, and a rapid, inexpensive, and simple HS-GC/FID method was developed to determine the residual amount of volatiles in the septa. 2-Phenethyl acetate stood out in the rubber septa and showed a statistically significant difference in the release ratio compared to the other volatiles under all conditions tested. Our results showed that the attraction of olive fruit flies increased with decreasing concentrations of the tested volatiles. Regarding the number of flies attracted by rubber septa containing 2-phenethyl acetate, significantly better results were obtained than for septa containing isoamyl alcohol and 2-octanone, in contrast to the attraction of olive fruit flies to polypropylene vials containing these compounds but without significant difference. Since the presence of all tested chemicals was detected during the experiment, this opens the possibility of using more environmentally friendly and cost-effective dispensers with a significantly lower amount of semiochemicals. ## 1. Introduction Introducing new strategies or improving existing ones beyond insecticides is critical to maintaining agricultural production and improving our environment and health. Biotechnical methods play a particularly key role in the control of Tephritidae and are used to a much greater extent in the control of Tephritidae than in any other order or family of insect pests [1]. Among the biotechnical methods, the use of semiochemicals is playing an increasingly important role [2,3,4]. Semiochemicals are widely used to monitor and detect insect pests and to suppress populations by attracting and killing, mass trapping, mating disruption, and push–pull strategies [2,5,6]. These are substances or mixtures that allow for the manipulation of insect behavior, both from the same species and from different species, as the release of a single compound from an organism can elicit a behavioral or physiological response [4]. Therefore, behavioral manipulation, as a management tool, could be a great alternative for Tephritidae control, as there is a trend towards reducing the use of insecticides (European Green Deal) and increased resistance towards insecticides, which results in a great need for finding novel, ecologically based measures. This is a promising area, especially in the case of the olive fruit fly (OFF) Bactrocera oleae Rossi (Diptera: Tephritidae), the most economically important pest of olive crops worldwide, which can cause yield losses in both table olive and olive oil production [7]. Semiochemicals represent a wide range of volatile and nonvolatile organic substances or mixtures that depend on various physicochemical properties, such as the nature of the semiochemical itself, its volatility and solubility, and the lifetime of the semiochemical in the environment, highlighting the influence of temperature, which can allow increased diffusion of semiochemicals, as one of the most important abiotic factors [6]. In the context of monitoring and control of OFF, several studies have shown that OFF is indeed attracted to selected semiochemicals such, as plant volatiles [8,9,10,11,12,13,14] and yeast volatiles [15,16,17], the emission of which serves as a volatile signal for insect foraging [18]. Vitanović et al. [ 16] reported the attraction of various yeast species isolated from different habitat sources, such as infested olive fruit, the surface of OFFs, the guts of larvae and adult insects, and other insect species to OFF. Upon further examination of these yeast species, Vitanović et al. [ 15] noted the presence of several volatile compounds, including isoamyl alcohol, 2-phenethyl acetate, isobutanol, isobutyl acetate, 2-phenethyl acetate, and 2-octanone. These volatile compounds (termed olive fruit fly (OFF)-associated yeast volatile compounds) were even more effective than yeast formulations alone, as well as the control treatment, a non-yeast volatile compound. The behavioral manipulation of insect pests requires the controlled release of semiochemicals that mimic natural processes. For such methods of behavioral manipulation to be effective, it is critical to find the most appropriate medium for release. This can be achieved by selecting a releasing device that allows for the sustained release of optimal concentrations of selected semiochemicals to elicit the desired insect responses over the intended time, achieve a repeated and stable release rate, achieve replication-induced behavior, and protect the semiochemicals used from UV light, oxygen, or reactions with dispensers; thus, the devices should tend to be inexpensive and environmentally friendly [19]. The dispensers for the slow release of semiochemicals are mostly polyethylene and polypropylene bags, tubes, bottles, beads, glass, rubber septa, tubes and rods, membranes, polyvinyl chloride, spiral polymer dispensers, cellulose, polyester, spiral polymer dispensers, etc. [ 6,19]. The objective of slow-release devices is to protect semiochemicals from degradation by oxygen and/or UV activity. In addition, certain conditions must be met, including the controlled release of the chemicals at the correct concentration for insect detection, efficiency, and repeatability throughout the application period [6]. In view of this, in our previous study, the presence of OFF-associated yeast volatile compounds was tested over seven days in an olive canopy and analyzed by HS-SPME-GC/FID [17]. The results showed that all of these compounds were present in the dispensers during the experiment in the olive grove. However, to our knowledge, the release rate of OFF-associated yeast volatile compounds has not been studied, and there is little information on their behavior, both under controlled conditions and in the field. To help maximize the effect of the potential attractant for olive fruit fly, our study presents laboratory and field research to better understand and apply semiochemicals, particularly OFF-associated yeast compounds. Thus, the aim of this research was to investigate the release rate of OFF-associated yeast volatile compounds in two types of slow-release dispensers and relate them to their biological efficiency in attracting OFF under different environmental conditions. In addition, the duration of the slow-release dispensers containing volatiles was tested for possible longer-term use in olive groves. ## 2. Results and Discussion The four-week experiment, conducted in October 2021, testing three yeast volatile compounds associated with the olive fruit fly (OFF) and one non-yeast volatile compound, was divided into two parts, as shown in Figure 1. The presence of the tested volatiles in the slow-release dispensers, rubber septa (RS), and polypropylene vials (PPVs) under different environmental conditions was determined by mass measurement and headspace gas chromatography with flame ionization detection (HS-GC/FID), while the attraction of the olive fruit fly to the tested volatiles was monitored for both slow-release dispensers attached to yellow sticky traps (YSTs). ## 2.1.1. Monitoring the Mass Change in the Volatile Compounds in the Slow-Release Dispensers The individual monitoring of the volatile residues of three OFF-associated yeast volatile compounds, namely, isoamyl alcohol, 2-octanone, and 2-phenethyl acetate, and one non-yeast volatile compound, n-hexane, (data presented in Table 1), and consequently release kinetics monitoring were performed in October 2021. The presence of volatile compounds was determined by weight loss measurement and gas chromatography. The release rate of all volatiles was monitored under all conditions, both controlled and field conditions, with both types of dispensers, RS and PPV, by measuring the change in weight starting from the initial weight of the dispenser, the weight of the dispenser with the addition of the volatile, and the weight of the dispenser during the 4 week experiment (Tables S1 and S2). This test was performed to determine the weight change over 4 weeks to obtain data on the possible presence of volatiles in the dispenser during the experiment to adjust the time of use of the dispenser in the field for the attraction of OFFs. As can be seen from the results (Tables S1 and S2), there were differences between the tested volatiles under the different conditions in the different passive dispensers. Thus, as expected, there was a trend of a decrease in mass under all conditions tested, while the greatest changes occurred in the measurement of weight loss in RS under room conditions, with the results reaching negative values (Table S1) for isoamyl alcohol, 2-octanone, and n-hexane. It can be concluded that, in addition to the material of which the dispenser is made, the possibility of moisture absorption, expansion, or contraction of the dispenser itself, due to the temperature or pressure, could affect the instability in the measurement of the mass of the septum. Because the initial volume of the volatile compounds in the PPV dispenser was 20 times greater, the measurement of weight loss over the 4 week experiment was easier to perform. The correlation between the mass change in the rubber septa and the mass change in the polypropylene vials is shown in Table 2. It was shown that there was a strong positive correlation when testing 2-phenethyl acetate and n-hexane in septa and vials under all conditions, while 2-octanone showed a positive correlation only under controlled conditions, those of the environmental chamber. In contrast, isoamyl alcohol showed a weak correlation without statistical significance. Isoamyl alcohol and 2-octanone, loaded in RS, showed the greatest decrease in weight loss in the environmental chamber and loaded in PPV in the field. Contrary to expectations, 2-phenethyl acetate loaded in RS and PPV evaporated faster in the field, concluding that the compounds evaporate faster in the field than under controlled conditions due to the influence of abiotic factors. As expected, the release rate of n-hexane was the fastest under all conditions tested and in both dispensers, as it has the lowest molecular weight value of all volatile compounds tested. In addition, the increased volatility of n-hexane is due to the fact that it is a very nonpolar compound without polar functional groups (Table 1). Kuenen and Siegel [21] used rubber septa in their experiment to determine the release rates of volatile compounds and synthetic pheromone of the Oriental fruit moth and showed variability in the release rate as a function of solvent type and volume. Butler and McDonough [22] used alcohol and acetate molecules detected as sex pheromones of moth species applied to rubber septa and showed that the molecular size was one of the most crucial factors affecting the release ratio. Although it was envisaged that the volatiles would exhibit the fastest rate of evaporation under the highest temperature conditions, in our study the slowest rate of decline was observed when the dispenser masses of all volatiles tested were measured in the environmental chamber, where there was no wind and other climatic factors that could affect the faster evaporation of the volatiles. This is likely due to the interaction of the humidity and temperature values, which is why it was difficult for the volatiles to achieve a constant release. Moreover, when the percentage of humidity is high, there may be a change in mass due to the presence of various other factors, such as the accumulation of dust and other impurities and/or contaminants on the dispensers and the influence of other abiotic factors, which makes it difficult to maintain a constant release rate (zero-order kinetics), which is crucial for determining the duration of the dispenser in field experiments and depends on the climatic conditions, the type of dispenser, and the type of molecule tested [6,23]. Accordingly, our results showed that this type of measurement technique is not precise enough, especially for smaller amounts of volatile compounds in passive dispensers, and the main drawback is precisely the insufficient precision and accuracy for determining the release rates of the tested volatiles. From the obtained results (Tables S1 and S2), it can be concluded that the presence of volatiles can be determined by mass measurement, especially for dispensers with a larger volume of volatile compounds. However, this does not mean that a smaller amount of the tested volatile compounds filled in smaller dispensers were not present in the dispensers, so one of the more accurate analytical techniques would have to be used for a more accurate determination. In addition, a higher concentration and volume of volatiles do not necessarily attract more OFFs. ## 2.1.2. HS-GC/FID Analysis of Volatile Compounds In addition to weighing the dispensers containing the volatiles, an HS-GC/FID analysis was performed to determine the residual amount of each volatile compound (Figure 2 and Figure 3), as the results of the weight change test on RS were not accurate, mainly due to the low weight of the dispenser itself and the added volume of volatile compounds. However, the presence of all tested volatiles in the PPV during the study was not in question, as a 20-fold larger volume was used, in addition to the fact that all of the volatiles were visible; this was also confirmed by the mass measurement (Table S1), where none reached a negative value, so it was not necessary to detect their presence by gas chromatography. The results are presented as peak area results (Figure 2 and Figure 3) and expressed as a mass concentration calculated from calibration curves (Table S3). Three OFF-associated yeast volatile compounds, isoamyl alcohol, 2-octanone, and 2-phenethyl acetate, were tested under controlled conditions and in the field (Figure 2 and Figure 3), while n-hexane, a non-yeast volatile compound, was tested only under field conditions to detect its presence during the 4 week experiment (Figure 3). The release rate of the volatile compounds over time followed an exponential function, described by the following formula, where a represents the initial value, b is the factor of decay, and y is the function’s variable:y = abx [1], where 0 < b < 1.[1] The measured values were fitted to an exponential function using nonlinear least squares [24]. Vitanović et al. [ 15,16] and Bego and Burul et al. [ 17] also demonstrated in their previous studies that some OFF-associated yeast volatile compounds attract OFFs. Therefore, it was necessary to test the individual volatile compounds under controlled conditions and in the field, as well as to test the performance of the diverse types of dispensers to improve our knowledge of the chemical properties of the volatile compounds. As far as we know, the release rate of the tested volatile compounds under controlled conditions and in olive groves has not yet been studied. The results of our study showed the presence of all tested compounds over 4 weeks (Figure 3 and Figure S1). Three OFF-associated yeast volatile compounds were tested under controlled conditions and in the field (Figure 2, Figure 3 and Figure S1), whereas all tested compounds (3 OFF-associated yeast volatile compounds and n-hexane as a non-yeast volatile compound) were analyzed in the field (Figure 3). Under controlled conditions in the environmental chamber, all tested volatile compounds evaporated faster than in the field, as shown in Figure 2. Under all conditions tested, the levels of isoamyl alcohol and 2-octanone decreased sharply during the first week of the experiment, although they were still present. Nevertheless, the presence of all tested volatiles was confirmed and expressed as a percentage of the initial volume of the tested volatile compound under all tested conditions, and they varied from $0.013\%$ in the environmental chamber to $0.862\%$ in the olive grove for isoamyl alcohol, from $0.817\%$ in the environmental chamber to $6.501\%$ under room conditions for 2-octanone, and from $3.133\%$ under room conditions to $22.514\%$ in the environmental chamber for 2-phenethyl acetate, while n-hexane was tested only in the field and reached $3.228\%$ of the initial volume (Figure S1). 2-Phenethyl acetate reached the same level as the other volatile compounds in the environmental chamber after the 2nd week of the experiment, and a slower decline was observed in the field and under room conditions. Overall, 2-phenethyl acetate proved to be the most stable compound with the slowest evaporation under all conditions. In addition, isoamyl alcohol evaporated the fastest under all conditions, followed by 2-octanone (Figure 2 and Figure 3). As expected, the stability of the volatile compounds of the OFF-associated yeast over the 4 week experiment was the most favorable under the controlled laboratory conditions (expressed as the percentage of tested volatile compounds from the initial volume in slow-release dispensers: $0.291\%$ for isoamyl alcohol, $0.978\%$ for 2-octanone, and $4.135\%$ for 2-phenethyl acetate), which is probably due to the less variable climatic parameters, while the volatile compounds in the field were exposed to the influence of abiotic parameters. To observe the influence of the different climatic parameters on the presence of volatile compounds in the rubber septa over the 4 week experiment, a correlation was made, as shown in Table 3. The concentration of volatile compounds correlated with temperature, humidity, and air pressure under all conditions (i.e., under controlled conditions and in the field experiment), with the addition of precipitation, cloud cover, and wind in the field experiment. Of all the climatic parameters tested, temperature, precipitation, cloud cover, and wind showed a negative correlation with the concentration of volatiles tested, while humidity and air pressure were positively correlated. As shown in Table 3, among all tested OFF-associated yeast volatiles, only 2-phenethyl acetate showed a significant negative correlation with temperature under all environmental conditions, both controlled and field conditions. A comparison of the concentration of OFF-associated yeast volatiles with other climatic parameters showed no statistically significant results, either positive or negative. In addition, there was a statistically significant negative correlation between the temperature and concentration of the n-hexane tested in the field. With the exception of isoamyl alcohol, which could only be detected in trace amounts under field conditions, all tested compounds were quantified under all environmental conditions using HS-GC/FID, which confirmed their presence throughout the duration of the experiment. For this reason, we concluded that this technique is the better choice, especially when compared to the results obtained by volatile mass change measurements. This analytical technique is much more accurate, sensitive, and precise and allows for the detection of components that are not easy to measure with an analytical balance due to the use of small volumes and other factors that may affect the result (climatic parameters, accuracy and precision of the balance itself, conditions under which the weighing is performed, etc.). ## 2.2. Field Bioassay: Olive Fruit Fly Attraction to OFF-Associated Yeast Volatile Compounds in an Olive Grove The attraction of Bactrocera oleae to three OFF-associated yeast volatile compounds loaded in RS or PPV and attached to YSTs was studied in an olive grove in October 2021 (Figure 4 and Figure 5). The total number of flies caught on YSTs with RS loaded with each of the OFF-associated yeast volatiles tested is shown in Figure 4. The figure shows that YSTs with RS, loaded with 2-phenethyl acetate, were the most attractive to olive fruit flies of all the traps tested. It is well known that ripening and fermenting fruits emit various volatiles, especially esters and alcohols. Fermentation volatiles, such as esters, serve as attractants for many insect species [25], so it was expected that 2-phenethyl acetate would be one of the most attractive volatiles to olive fruit flies in the field. During the first week of the study, the attraction of all the traps tested was similar, and there were no differences in the number of olive fruit flies caught among them. From the second week until the end of the experiment, the attractiveness of the YSTs with RS loaded with 2-phenethyl acetate increased steadily, and the number of flies caught was twice that of the YSTs with RS, loaded with 2-octanone or isoamyl alcohol, and the control traps (Figure 4). During the study, no differences were observed between male and female catches in any of the traps examined (Figure 6). For each YST pair containing RS with two different OFF-associated yeast volatiles, a Mann–Whitney U test was performed to determine if there were significant differences in attraction for the olive fruit flies (Table 4). The results show that there was a significant difference between the YSTs with RS, filled with 2-phenethyl acetate, and the YSTs filled with 2-octanone and isoamyl alcohol ($$p \leq 0.00916$$ and $$p \leq 0.00547$$, respectively). Yellow sticky traps containing RS filled with 2-phenethyl acetate were significantly more attractive to olive fruit flies in an olive grove than the other volatiles tested. Similarly, there was no significant difference in the attraction for the olive fruit flies between YSTs with RS filled with 2-octanone and isoamyl alcohol ($$p \leq 0.39374$$) (Table 4). In contrast to the above results, the YSTs containing PPV loaded with 2-phenethyl acetate were twice as attractive to olive fruit flies as YSTs containing PPV loaded with 2-octanone or isoamyl alcohol (Figure 5). These results are consistent with those of Vitanović et al. [ 15], in which the authors indicated that isoamyl alcohol added to PPV and attached to YST was twice as attractive to B. oleae in an olive grove as YST with PPV containing 2-phenethyl acetate. Davis et al. [ 26] also showed that isoamyl alcohol was responsible for trapping a large number of other dipterans. The results also show that YSTs with RS, loaded with 2-phenethyl acetate, were four times more attractive to B. oleae than YSTs with PPV containing the same volatile, whereas the opposite was true for the other two OFF-associated yeast volatiles. The number of flies caught on the YSTs with PPV containing 2-phenethyl acetate stopped increasing in the second week, while the number of olive fruit flies caught on the YSTs with PPV containing the other two volatiles tested continued to increase slightly until the end of the study. As with the study of YSTs containing RS as dispensers, there were no differences between the catches of male and female flies on any of the YSTs tested with PPVs during the study (Figure 6). Three Mann–Whitney U tests were also performed, one for each pair of YSTs with PPVs containing two different OFF-associated yeast volatiles, to determine if there were significant differences in the attraction of the olive fruit flies (Table 4). The results show that there was no significant difference in the attraction for B. oleae among the YSTs with PPV containing all tested OFF-associated yeast volatiles (Table 4). According to the results presented in Table 5, 2-phenethyl acetate proved to be significantly more attractive to olive fruit flies when loaded in RS than when filled in PPV and attached to YST ($$p \leq 0.0073$$). The results obtained may be due to the chemical nature of the compound, as well as to a more uniform release from RS than from PPV, since the entire surface is exposed, and the compound is absorbed into the dispenser itself. However, the results of our study also showed that there was no significant difference in attraction of olive fruit flies among the tested dispensers when loaded with the other two OFF-associated yeast volatile compounds ($$p \leq 0.1964$$ and $$p \leq 0.0603$$ for isoamyl alcohol and 2-octanone, respectively) (Table 5). In addition to examining the general attraction of olive fruit flies, the difference between the total number of females and males during the four weeks of the experiment was checked (Figure 6). It is well known that conventional attractants mainly attract only one sex: males [27]; thus, we can emphasize that this type of attractant is suitable for attracting both sexes. Previous studies have shown that 2-phenethyl acetate attracts the olive fruit fly both in the olive grove and in the laboratory [2,3]. Since the differences in the attraction of B. oleae in the olive grove have not yet been investigated with different types of dispensers attached to YSTs from which the abovementioned volatile substance is released, our study was the first of its kind. The results of our study show the advantage of using RS on YST loaded with 2-phenethyl acetate as the most attractive bait for olive fruit fly among all the baits studied. For all of these reasons, the results of our study can contribute to a better understanding of all factors used to monitor and/or control B. oleae, including the most attractive volatile compound and the most effective dispenser. ## 2.3. The Influence of Climatic Parameters on the Attraction of the Olive Fruit Fly Various climatic parameters influence the attraction of olive fruit fly by YST-containing volatile compounds as attractants in two ways: first, by the evaporation of volatiles from dispensers and, second, by the population and development of B. oleae. Of all climatic parameters, temperature and humidity are the most important for the development of most insect species, including the olive fruit fly [17,28,29]. On the other hand, the evaporation of volatiles from dispensers depends not only on climatic conditions, such as temperature, humidity, air pressure, and wind speed, but also on the chemical nature of the compound and the type of dispenser from which it evaporates. Figure 7 shows the climatic conditions during the field bioassay and the number of olive fruit flies caught on YSTs containing RS filled with 2-phenethyl acetate, the volatile compound that was the most attractive to B. oleae of all the volatiles tested in the olive grove. As mentioned above, 2-phenethyl acetate was the most stable of all the volatile compounds studied, evaporated the slowest, and was significantly negatively correlated with temperature under field conditions. In addition to temperature, the concentration of the above volatile compound was also negatively correlated with precipitation, cloud cover, and wind, while it was positively correlated with humidity and air pressure (Table 3). The highest attraction of olive fruit fly to the YSTs containing RS, filled with 2-phenethyl acetate, was observed in the second and third weeks, while the lowest attraction was recorded in the first week of the study. The intensity of the attraction of B. oleae to the mentioned traps can be related to the decrease in the 2-phenethyl acetate concentration. These results can be related to the results of Vitanović et al. [ 15], who showed that the lowest concentrations of 2-phenethyl acetate elicited a better response from olive fruit fly in the laboratory bioassay. Even though temperatures in the first week of the study (up to 22.2 °C) were more optimal for olive fruit fly development [30,31], the fly capture was lower than in the other weeks of the study (15.3–19.3 °C), which could be due to the negative correlation between 2-phenethyl acetate and temperature (Table 3). This implies that temperature has a major influence on the evaporation of certain volatiles and the attraction of B. oleae. In addition to temperature, olive fruit fly development is highly dependent on humidity [32,33], with an optimum of 55–$75\%$ [32], which may also affect the effectiveness of olive fruit fly monitoring and/or control methods [34,35]. This fact is also confirmed by the results of our study, because the indicated optimum humidity was determined exactly on the days when B. oleae was intensively trapped (Figure 7). In addition, the results of our study showed that 2-phenethyl acetate is positively correlated with humidity (Table 3), which means that its evaporation is associated with a higher percentage of humidity. The results of our study confirmed this, as the YSTs with RS, loaded with 2-phenethyl acetate, exerted a better attraction of olive fruit flies when the highest humidity was measured. Moreover, on the days when the tested traps exerted a high attraction of olive fruit flies, a moderate wind prevailed (Figure 7), which may have influenced the release of the tested volatile compounds [20]. It can be assumed that the wind speed was negligible during the study and had no effect on fly capture, since the evaporation of 2-phenethyl alcohol is negatively correlated with wind (Table 3) and wind has a negative effect on B. oleae flight. Finally, the results of our study show the inevitable influence of the high variability of field conditions on the behavior of the chemical in the dispenser and, thus, on its attraction of the olive fruit fly. Under such uncontrolled conditions, it is difficult to infer the trigger of the biological activity of the volatiles, especially since their synergistic or antagonistic effect is certainly present. ## 3.1. Synthetic Volatile Compounds All chemical standards used for this study (Table 1) were obtained from commercial sources and had a purity of ≥$99\%$. Isoamyl alcohol was obtained from Kemika d.d. ( Zagreb, Croatia), 2-phenethyl acetate from Sigma-Aldrich (St. Louis, MO, USA), 2-octanone from Alpha Aesar (Kandel, Germany), n-hexane from VWR International bvba (Leuven, Belgium), and acetone from Kemika d.d. ( Zagreb, Croatia). ## 3.2. Slow-Release Dispensers The release rate of all volatile compounds tested was determined using two types of slow-release dispensers: 4 mL polypropylene vials (PPVs) (Cryotubes, BRAND GMBH + CO KG, Wertheim, Germany) with a 3 mm diameter hole in the lids and rubber septa (RS) (2.4 mm × 5.33 mm, Sigma Aldrich, St. Louis, MO, USA). A total of 0.1 g of cotton and 1 mL of each synthetic volatile compound tested was added to the bottom of a 4 mL PPV [15,24]. The purified RS were loaded with 50 µL of each synthetic volatile compound tested. To absorb the volatile compounds, the loaded RS were placed in a filter fume hood (GS1500; Gruppo Strola, Torino, Italy) for 24 h to absorb the volatile compounds before performing the experiments. Prior to volatile loading, all septa were prepared and cleaned by Soxhlet extraction with n-hexane for 24 h, followed by methylene chloride for 24 h and air-drying in a fume hood for an additional 24 h [20,35]. The cleaned and sealed septa were stored at 4 °C and then subjected to HS-GC/FID analysis to prove the cleanliness of the dispenser and to rule out the presence of interfering substances that could affect further release rate analyses, as well as to rule out interference with OFF field attraction. ## 3.3. Experiment Design The study was conducted in October 2021 and consisted of two separate experiments, as shown in the flowchart (Figure 1). In experiment 1, the release ratio of the OFF-associated yeast was studied by measuring the mass change in the RS and PPV and by measuring the residual volatiles in the RS over 4 weeks under controlled and field conditions. In experiment 2, conducted in an olive orchard, the attraction of olive fruit flies to the volatile compounds of the OFF-associated yeasts was studied. ## Monitoring of the Release Rate of the Tested Volatile Compounds: Experiment 1 The study of the release ratio of the OFF-associated yeast volatile compounds (Experiment 1) consisted of three independent measurements performed under different environmental conditions (i.e., room conditions, environmental chamber conditions, and field conditions) to estimate the release ratio of three OFF-associated yeast volatile compounds (isoamyl alcohol, 2-octanone, and 2-phenethyl acetate) and a non-yeast volatile compound (n-hexane), which was used as a positive control, from two types of dispensers, RS and PPV. To monitor the release ratio of the OFF-associated yeast compounds, the tested RS and PPV were weighed using an analytical balance (Mettler Toledo, OH, USA) before the addition of the volatile compound, 24 h after the addition of the volatile compound, and daily at the same time and under the same conditions to measure the weight loss over the 4 week experiment. To test the presence of the tested volatiles using HS-GC/FID, the rubber septa were placed in triplicate on each measurement day after washing and loading in all environmental conditions tested. The release rate of each tested volatile compound placed in dispensers (50 µL in RS and 1 mL in PPV) was examined individually. The climatic parameters of the environmental conditions measured in the room environment, in the environmental chamber, and in the field are shown in Table 6. The parameters of the environmental conditions in the room were recorded with wireless sensors (Agara temperature and humidity sensor). The environmental chamber (Kambič, Semič, Slovenia) with the central microprocessor control DPC-420 was used to simulate the conditions in the field and to eliminate external influences (mainly temperature fluctuations, wind, solar radiation, precipitation, etc.). A temperature range was set to simulate the average daytime (23 ± 1 °C) and nighttime (17 ± 1 °C) temperatures throughout the experiment. At the same time, the influence of the actual climatic parameters on the release ratio of all studied volatile compounds in the olive grove was tested using the weather data from the nearest weather station [29] (see Table 6). The measurement of the presence of the tested chemicals was performed using two different methods: measuring the changes in the mass and concentration of the individually tested chemicals on the same days (1st, 2nd, 3rd, 4th, 5th, 6th, 7th, 9th, 10th, 11th, 12th, 13th, 14th, 17th, 21st, and 28th days) in triplicate over a 4 week experiment under controlled and field conditions. The mass measurement was performed using an analytical balance (Mettler Toledo, Ohio, SAD) for the compounds loaded in RS and PPV, while the measurement of the residual amount of volatile compounds loaded in RS was performed using HS-GC/FID (Shimadzu, Kyoto, Japan). ## 3.4. Field Bioassay: Experiment 2 The second separate but simultaneous experiment (Experiment 2, Figure 2) was conducted in the olive grove of the Institute for Adriatic Crops (IAC) at the Duilovo site, Split, Croatia (geographic coordinates: 43°30′19.4′′ N 16°29′56.1′′ E), elevation 73 m a.s.l. The olive grove was regularly maintained, except for plant protection measures. During the 4 week experiment, climate [36] data (temperature, humidity, wind speed, precipitation, air pressure, and cloud cover) were collected from the Split airport site [36]. Hourly measurements were aggregated to daily values as follows: air temperature, relative humidity, and air pressure were averaged; wind speed, precipitation, and cloud cover were summed (each parameter separately). Each parameter was then normalized and plotted on a stacked graph. The number of OFFs was divided by the number of days between two consecutive measurements to determine the daily number of OFFs. ## Olive Fruit Flies Trapping The olive fruit fly attraction to OFF-associated yeast volatile compounds was tested using traps consisting of double-sided yellow sticky traps (YST) (17 × 24 cm, Bio Plantella, UNICHEM d.o.o.) and two types of slow-release chemical dispensers, 4 mL PPVs and RS, loaded with 3 OFF-associated yeast volatile compounds, and a positive control, n-hexane. The dispensers were prepared for the experiment following the same protocol as described in Section 3.2. The PPVs, loaded with 1 mL, were attached to the YS traps with cable ties, while the RS, loaded with 50 µL of the tested volatile compound, were placed in a PVC-coated fiberglass insect net and attached to the YSTs. The trap experiment included 8 treatments in triplicate (Table 7). Yellow sticky traps containing PPVs and RS were placed in a random arrangement evenly distributed in the olive orchard. No modifications were made to the slow-release chemical dispensers containing synthetic OFF-associated yeast volatiles. The traps were placed at a height of 1.5 to 2 m above the ground and in a southwesterly direction between every other row in the olive orchard at a distance of ≈15 m within the row. To observe whether the installed dispensers attracted OFFs over the 4 week experiment, the OFFs were counted and removed several times (fourteen) at different time intervals. ## 3.5. HS-GC/FID Analysis The measurement of the amount present of all tested volatile compounds (3 OFF-associated yeast volatile compounds and 1 non-yeast volatile compound) in RS was performed using a gas chromatograph (Nexis GC-2030, Shimadzu, Japan) coupled with a headspace and flame ionization detector (HS-GC/FID). The amount of each tested volatile compound (50 µL in RS) was determined by an in-house method using a SH-RTX-WAX capillary column (30 m × 0.25 mm × 0.25 µm) and quantified by comparing their retention time with the retention time of a standard under the same analysis conditions. The measurements were performed in triplicate. Ultra-high purity helium ($99.999\%$ purity) with a constant flow of 1 mL/min was used as the carrier gas. The oven temperature was set at 40 °C, held for 1 min, increased to 225 °C at a rate of 30 °C/min, and then maintained for an additional minute. The analysis time was 8.17 min. Headspace conditions were set as follows: thermostating at 80 °C for 5 min with a rotation speed of 250 rpm and a needle transfer temperature of 105 °C. The injection temperature was set at 200 °C. The analysis results are expressed as the peak area and as the mass concentration, calculated using calibration curves, using 6 calibration levels for each tested volatile compound, in a linear range from 0.033 to 10.32 ppm, where linearity, the coefficient of determination (R2), slope, and intercept were assessed (Table S4). Acetone was used as an internal standard at a concentration of 0.01 ppm. All analysis was performed in triplicate. ## 3.6.1. Pearson Correlation Coefficient To determine whether there was a correlation between the change in the mass of the OFF-associated yeast volatile compounds in RS and PPV under the environmental conditions tested and a correlation between the concentration of the OFF-associated yeast volatile compounds in the rubber septa and the climatic parameters during the study, a Pearson correlation coefficient analysis was performed. The correlation was considered significant at a value of p ≤ 0.05. The analysis was performed using SPSS software, version 25.0 (IBM Corporation, New York, NY, USA). ## 3.6.2. Mann–Whitney U Test The statistical analysis was performed using the Python programming language [37]. The experimental data were fitted using the nonlinear least squares method from the scipy package. The mean values of the number of flies for each volatile compound tested were compared with the Mann–Whitney U nonparametric test at a significance level of $p \leq 0.05$ using the Stats models package to test whether the number of OFFs attracted to different volatile compounds represented a different population with different mean values. Since the samples were not normally distributed, a nonparametric alternative to the parametric two-sample t-test was chosen. ## 4. Conclusions To enable the manipulation of OFF, the knowledge of the physicochemical properties of semiochemicals and the dispensers used to release them must be expanded to better mimic natural environmental conditions. In our study, we confirmed the presence of all tested OFF-associated yeast volatile compounds by both methods: mass weighing and gas chromatography. Since measuring the mass of the septa with the small amounts of volatiles used in this experiment was not accurate enough to confirm their presence, a more precise analytical technique, HS-GC/FID, was used. This technique was able to confirm the presence of all tested volatiles in the dispensers, which may allow for the longer use of the dispensers, reducing costs and workforce requirements, as dispensers in olive groves need to be replaced less frequently. 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--- title: Dietary Folate Deficiency Promotes Lactate Metabolic Disorders to Sensitize Lung Cancer Metastasis through MTOR-Signaling-Mediated Druggable Oncotargets authors: - Wan-Jing Chen - Su-Yu Huang - Yi-Wen Chen - Yi-Fang Liu - Rwei-Fen S. Huang journal: Nutrients year: 2023 pmcid: PMC10052195 doi: 10.3390/nu15061514 license: CC BY 4.0 --- # Dietary Folate Deficiency Promotes Lactate Metabolic Disorders to Sensitize Lung Cancer Metastasis through MTOR-Signaling-Mediated Druggable Oncotargets ## Abstract Lactate metabolism plays a pivotal role in cancers but is often overlooked in lung cancer (LC). Folate deficiency has been linked to lung cancer development, but its impact on lactate metabolism and cancer malignancy is unclear. To investigate this, mice were fed either a folate-deficient (FD) or control diet and intrapleurally implanted with lung cancer cells pre-exposed to FD growth medium. Results showed that FD promoted lactate over-production and the formation of tumor oncospheroids (LCSs) with increased metastatic, migration, and invasion potential. Mice implanted with these cells and fed an FD diet developed hyperlactatemia in blood and lungs. This coincided with increased expression of hexokinase 2 (HK2), lactate dehydrogenase (LDH), and decreased expression of pyruvate dehydrogenase (PDH). Pre-treatment of the FD-LCS-implanted mice with the mTORC1 inhibitor, rapamycin, and the anti-metabolic drug metformin abolished FD/LCS-activated mTORC1 and its targets including HIF1α, HK2, LDH, and monocarboxylate transporters (MCT1 and MCT4), which coincided with the reduction in lactate disorders and prevention of LC metastasis. The findings suggest that dietary FD promotes lactate metabolic disorders that sensitize lung cancer metastasis through mTOR-signaling-mediated targets. ## 1. Introduction As an essential nutrient and food functional component, the human body demands sufficient dietary folate for normal one-carbon metabolism in de novo nucleotides synthesis, bioenergetics, and redox balance to support cellular proliferation and organism growth [1]. Dietary folate deficiency (FD) results in a folate-deficient vascular and tissue microenvironment which stresses cellular one-carbon metabolism towards oncogenic transformation with increased risks of cancer malignancy development [2,3,4]. Depending on the magnitude of tissue folate depletion, folate deprivation of cancer cells leads to cell cycle arrest and apoptotic cell death [5,6], and/or selected immortal cancer cells with a stemness phenotype of enhanced cancer metastatic potential in invasion, migration, and self-renewal capability to adapt anchorage-independent growth in the vascular tumor microenvironment (TME) [7,8,9,10,11]. Numerous studies have also shown that FD-diet-fed animals developed systematic bioenergetic deficits due to dysfunctional mitochondria (mt) oxidative phosphorylation (OXPHOS) and elevated mt oxidative damage in DNA, lipids, and proteins of peripheral tissues [12,13,14]. It is as yet not completely understood how cancer cells may survive the FD-induced bioenergetics crisis to establish their metastatic behavior which demands high energy support. A recent advance has proposed that reprogramming the lactate metabolism in the TME of the host regulates tumor progression and metastasis [15]. When primary cancer cells migrate from hypoxic tumor bulk to the vascular avenue for distant metastasis, they demand a high energy supply for anchorage-independent growth survival from the scarce-nutrient TME. Even under a normoxic TME, cancers with dysfunctional mt OXPHOS metabolize most glucose carbon to lactate via anaerobic glycolysis as the alternative fuel for proliferation, known as the Warburg effect [16]. Lactate over-production in tumor-adjacent tissues triggers metabolic-stress-signaling lactate mobilization to acidify the TME and to sustain the cancers’ fuel demand for metastatic development. Such a metabolic coupling event in tumors/tumor-adjacent tissues was named the reverse Warburg effect to support metabolic symbiosis of fuel lactate utilization in malignant cancers [17,18]. Clinical studies have indicated hyperlactatemia is the key predictor of cancer metastases, tumor recurrence, and cancer-related mortality [19,20,21]. Blockage of the reverse Warburg effect to remodel cancer lactate metabolism has been proposed to be a promising therapeutic approach for treating cancer malignancy [22,23]. Lung cancer is the leading cause of cancer-related mortality worldwide [24]. Early stage lung cancers (LCs) are potentially curable, whereas many patients develop metastatic diseases with poor prognostic outcomes. A recent advance in genomic and metabolomic studies suggests that lactate is the distinctive oncometabolite signature of human LC with aggressive oncological behavior [25]. The environmental factors to reprogram lactate metabolism in LC, however, remain poorly defined. Insufficient dietary folate intake has been associated with increased risks of LC carcinogenesis among former and current smokers [26,27]. Several studies have examined an association between circulating folate status and LC carcinogenesis, but results were inconclusive [28,29]. Despite the mixed outcomes in the previous findings, none has explored whether insufficient folate in the diet exerts a metabolic impact on tissue lactate disorders and advanced lung malignancy. There is currently no evidence to unveil whether and the working mechanisms by which such a dietary folate intake factor may regulate lactate metabolism to drive metastatic LC progression. We, therefore, established the in vitro FD-exposed lung carcinoma cell and dietary FD intervention of an FD-exposed LC-implanted mouse model to evaluate [1] the causal effects of dietary FD exposure on lactate metabolic disorders in the TME and LC metastasis and [2] to depict the lactate metabolic effects of dietary FD on the metabolic stress regulator, the mTOR-signaling pathway, and its druggable oncotargets in relation to LC metastasis. The clinical relevance and application are then discussed. ## 2.1. Chemicals and Reagents Folic acid (FA, pteroylmonoglutamic acid), metformin (met), and rapamycin (Rap) were obtained from Sigma Chemical Co. (St Louis, MO, USA). RPMI 1640 medium was purchased from Invitrogen (Grand Island, NY, USA). Penicillin, streptomycin, trypsin, and fetal bovine serum were from Gibco Laboratories (Grand Island, NY, USA). Matrigel was purchased from BD (Franklin Lakes, NJ, USA). mTORC1 inhibitor rapamycin (Rap) and antibodies of Sox2, ALDH1A1, E-cadherin, vimentin, mTORC1, HIF1α, HK2, LDHA, VDAC, G6PDH, PDHE1, ACLY, GLUT$\frac{1}{4}$, and MCT$\frac{1}{4}$ were from Cell Signaling Technology (Boston, MA, USA). Antibodies for beta-actin and GAPDH were from Millipore (Temecula, CA, USA). Millicell culture inserts containing a thin film polycarbonate (PCF) membrane were obtained from Millipore (Billerica, MA, USA). A folate-deficient, L-amino-acid-defined diet was specially formulated by Teklad Global Diets® (Madison, WI, USA). Lacticaseibacillus casei (L. casei) (BCRC®10697) was purchased from the Bioresource Collection and Research Center (Taipei, Taiwan). ## 2.2. Cell Culture and Treatment The Lewis lung carcinoma cells (LC) were obtained from the National Development Center of Biotechnology (Taipei, Taiwan). LC cells were maintained as a monolayer culture in a control RPMI 1640 medium with 2 uM folic acid and supplemented with 2.0 g/L of sodium bicarbonate, $10\%$ (v/v) fetal bovine serum (FBS), 100 U/mL of penicillin, and 100 mg/mL of streptomycin at 37 °C in a humidified $5\%$ CO2 incubator. Folate-deficient (FD) cells were cultured in folate-deficient RPMI 1640 medium supplemented with folic acid at final concentration of 10 nM to mimic serum folate levels of cancer patients in marginal folate deficiency [3,4]. ## 2.3. In Vitro Transwell Invasion Assay Matrigel (BD Biosciences, Franklin Lakes, NJ, USA) was coated onto transwell membranes (Corning Costar, MA, USA) for 12 h. After 72 h of control/folate deprivation, cells (1 × 104) were resuspended in serum-free medium, then seeded into the upper chamber, and 0.6 mL medium with $10\%$ FBS was added to the lower chamber as a chemoattractant. After 24 h incubation, a cotton swab was used to remove non-invading cells on the upper surface of the membrane. The invasive cells, which crossed to the lower surface, were fixed with $4\%$ paraformaldehyde and stained with $0.1\%$ crystal violet (Merck, Darmstadt, Germany). The number of invading cells were counted from 9 randomly selected visual fields with an inverted microscope at 200× magnification. Data were obtained from three independent experiments. ## 2.4. Wound Healing Assay LC cells were seeded onto 12-well plates and incubated with control medium (2 µmol folate) or folate deprivation medium (10 nmol folate) for 48 h. When cell confluence reached approximately $80\%$, a 10 μL pipette tip was used to create wounds, which were made by scraping the cell layer across each culture plate. After wounding, debris was removed by washing the cells with PBS. Wounded cultures were incubated in serum-free medium for 48 h, and then three fields (10×) were randomly taken from each scratch wound and visualized by microscopy to assess cell migration. The migration area of the scratched-wound image was analyzed at 0, 24, and 48 h using Image J software, Version 1.54b (National Institutes of Health, New York, NY, USA). ## 2.5. Spheroid Formation Assay Oncosphere formation was induced by seeding the control and FD cells (1000 cells/mL) in the low-attachment 6-well plate in suspension tumorsphere medium which comprised serum-free Dulbecco’s modified Eagle’s medium supplemented with $2\%$ B-27® (Life Technologies, Carlsbad, CA, USA) plus 20 ng/mL human recombinant epidermal growth factor, 10 ng/mL fibroblast growth factor, 100 IU/mL penicillin, and 100 μg/mL streptomycin. The oncospheres (tight, spherical, non-adherent masses >40 um in diameter) in each well were photographed and counted under a phase-contrast microscope at 200× magnification. ## 2.6. Animal Study and Drug Treatment The experimental protocols were approved by the Institutional Animal Care Committee of Fu Jen Catholic University (approval number: A10260) in accordance with the National Institute of Health guide for the care and use of laboratory animals. Male C57BL/6 mice at 6 weeks of age were fed an amino-acid-defined folate-deficient diet to FD group or a control diet to control group (with folic acid at 2 mg/kg of diet) for 14 days, which were made by Teklad Global Diets® (Supplementary Table S1). Then, the FD and control mice were intrapleurally implanted with saline (sham group) and in vitro control or FD-exposed lung cancers (1 × 106 cells) at various tumor malignancy stages. Drug treatment of rapamycin (Rap: 0.21 mM) and metformin (Met: 1.5 mM) at dose of 200 mg/mL/day was conducted by intraperitoneal injection to the control and FD mice one week prior to LCS transplantation. After 14 days, the mice were sacrificed for tumor burden, multiplicity, weight, and size evaluation. Blood samples and tissues were collected for fuel status analysis. Paired lung tumor tissues were removed and fixed in $10\%$ neutral buffered formalin solution for histological analysis. ## 2.7. Western Blotting Total protein was extracted and Western blotting on total and phosphorus–protein expression was performed according to a previously described protocol [7]. In brief, the quantified proteins were resolved on SDS–polyacrylamide gels and transferred onto a polyvinylidene difluoride membrane. The membranes were then immunoblotted with specific primary antibodies against beta-actin, GAPDH, metabolic enzymes (HK2, LDHA, VDAC, PDH, ACLY, and G6PDH), and components of mTOR-signaling pathways (Akt, mTOR, HIF1α, S6K, AMPK, and IRS-1) and were then incubated with the corresponding horseradish-peroxidase-conjugated IgG secondary antibody. All immunoblots were visualized using a WesternBright ECL substrate kit (Thermo, MA, USA). Actin and GAPDH were used as a loading control. We performed Western blot normalization on the Image LabTM software tools. Background-subtracted protein signals were quantified for both the target protein and the loading control in each lane of the blot. Then, we selected a reference lane and determined a normalization factor by separating the signal from the reference lane to arrive at a normalization factor for each lane. All calculations were performed by the software, including the normalization factor and normalized volumes as per the below formula:normalization factor = total volume (Intensity) reference lane/total lane stain-free volume (Intensity) of each lane.normalized volume = normalization factor × volume (Intensity) ## 2.8. Biochemical Assay L-lactate and glucose levels in blood and tissues were measured using a Lactate/Glucose Colorimetric Assay Kit (Abcam, Cambridge, MA, USA). Tissue redox markers of the NADH/NAD+ and NADPH/NADP+ ratio were analyzed by oxidized lactate with lactate dehydrogenase to generate a product that interacts with a probe to produce a color at λmax = 450 nm (ab65331) using Abcam quantitation kits. ## 2.9. Microbiological Assay for Folate Levels The L. casei assay was performed according to a previously described protocol [30]. Different concentrations of folate standard solution/quantitative tissue homogeneous solution were prepared, of which 100 µL were transferred into a 96-well microtiter plate, then pulsed with 10 µL diluted bacterial solution before incubating at 37 °C for 24 h. The plate was determined at an optical density (OD) of 590 nm. ## 2.10. Statistical Analysis All statistical analyses were performed using SAS, version 9.4 (SAS Institute, Cary, NC, USA) and SPSS Statistics, version 14 (SPSS Inc., Chicago, IL, USA). The continuous variables were compared using one-way ANOVA (analysis of covariance) followed by Scheffe’s post hoc test. Chi-squared test was used for categorial variables. p for interaction of drug and dietary treatment on lactate metabolic parameters was tested using two-way ANOVA analysis. The significance level was set at * $p \leq 0.05$ for all analyses. ## 3.1. FD Effect on Lactate Production and Metastatic Potential of LC Growing at Tumor Malignancy Stages The causal effect of FD exposure on lactate production and metastatic potential of LC was investigated. To recapitulate tumor pathological course during cancer malignancy, LCs were cultivated on a monolayer growing as the primary tumors and cultured in control and FD medium for 4 days. The primary LCs were passaged into low-adherent plates for anchorage-independent oncospheroids’ growth for 7–9 days, designated as LCSs, to mimic aggressive tumors in periphery metastasis. These oncospheroids were then re-cultured into monolayers as the distant metastatic colonized tumors stage (Figure 1a). Compared with the LC cultivated in the control medium (C-LC), FD-LC induced the epithelial mesenchymal transition (EMT) phenotype, evident by significantly increased numbers of mesenchymal elongated cells (Figure 1a,b). Under anchorage-independent growth, FD-LC vs. C-LC cells formed larger oncospheroids (FD-LCSs) with 3-fold increased numbers of oncospheroids (Figure 1a,c). FD-LCS cells re-established EMT phenotype with 3-fold increased numbers of adherent cells (Figure 1a,d). As lactate release was measured under various LC growing stages, both C-LC and C-LCS had slight lactate production whereas FD-LC and FD-LDS displayed a significant 4–5-fold increase in lactate levels compared with their counterpart controls, with the highest lactate production by FD-LDS (Figure 1e). Expression level of the stemness marker, Sox2, as the metastatic index, was the highest in FD-LDS followed by FD-LD, whereas C-LC and C-LCS expressed significantly lower Sox2 levels compared with the FD counterparts (Figure 1f). FD-LCS displayed the highest metastatic potential as compared with the FD-LC and the control counterparts, evident by significant increased migration (Figure 1g) and invasive LC numbers (Figure 1h). ## 3.2. Effect of Dietary FD Intervention on Cancer Metastasis Efficiency and Lactate Metabolic Disorders in the LC-Implanted Mouse Model As C57BL/6 mice were pre-fed with the control and FD diets following intrapleural injection with in vitro control and FD-exposed LCs at various cancer malignant stages, only the FD-LCS transplants that produced high lactate (Figure 1e) could colonize the lung and thoracic tissues of the FD mice with a $100\%$ tumorigenicity (Table 1). The FD-LCS-colonized tumors included 12 metastatic lung carcinomas and 22 metastatic sarcomas in the pectoral muscle of the thorax. Among these tumors, $92\%$ of lung carcinomas and $55\%$ of sarcomas proliferated into large tumors (tumor size > 5 mm) (Figure 2a). Histological examination on lung tissues of the experimental mice confirmed the invasive and proliferative lung tumors of the FD-LCS-implanted FD mice (Figure 2b). The FD-LC transplants with reduced lactate-producing capability (Figure 1e) only colonized one FD mouse to develop a large metastatic sarcoma in the thorax (Table 1 and Figure 2a) and induced lung pre-cancerous lesions despite the absence of lung tumors (Figure 2b). Both the FD-LCS and FD-LC transplants, however, did not develop metastatic cancers in the control-diet-fed mice, as evidenced by a $0\%$ tumorigenicity rate (Table 1 and Figure 2a,b). Even for the C-LCS transplants that displayed migration and invasive capability yet produced little lactate (Figure 1e,h), they did not colonize any metastatic cancer in the FD mice (Table 1). As compared with the control and FD sham groups, the LCS-implanted FD mice developed a high-lactate and folate-deficient TME signified by 2-fold increased vascular lactate (Figure 2c), 1.5-fold increased lung lactate (Figure 2d), and decreased serum (Figure 2e) as well as lung folate (Figure 2f) compared with the other counterparts ($p \leq 0.05$). The metastatic lung tumors of the FD-LCS mice displayed the similarly high serum and lung lactate signature with their paired lung tissues (Figure 2c,d). Notably, metastatic lung tumors of the FD-LCS mice accumulated 2-fold higher folate levels than their tumor-adjacent lung tissues (Figure 2f), despite a 30–$40\%$ folate reduction in the paired lung tissues (Figure 2f) and serum samples of the FD-LCS mice (Figure 2e) compared with those respective folate pools of the FD sham and control counterparts. The results suggested folate redistribution in the TME of FD mice when harboring a heavy tumor load. Overall, the high lactate coupled with the FD-deprived (HL/FD) TME of the FD/LCS mice coincided with a systematic bioenergetic deficit, evident by a $20\%$ lung tissue depletion (Figure 2g) and severe weight loss (Figure 2h), which resembled the symptoms of cancer cachexia in malnourished cancer patients with late-stage metastatic tumors and/or after anti-cancer chemotherapy. ## 3.3. Dietary FD and LC Invasion Modified Lactate Metabolic Targets in Lung and/or Metastatic Tumors of the Experimental Mice To unveil the decisive factors involved in dietary FD- and invaded LC-induced lactate metabolic disorder, expressions of rate-limiting enzymes in aerobic glycolysis and mt OXPHOS in lung/tumors of the control and FD mice were assayed by Western blot. As shown in Figure 3, the FD/LCS mice, relative to the FD sham mice and/or the FD-LC mice, had significantly increased lung expressions of HK2 (Figure 3(a-2)), and reduced expressions of PDHE1 (Figure 3(a-3)) and mt voltage-dependent anion channel protein (VDAC) (Figure 3(a-4)). Compared with the FD sham mice, the enhanced glycolysis and suppressed mt OXPHOS enzyme expressions of the FD-LDS mice were coupled with increased lung expression of LDH for lactate over-production (Figure 3(b-1)). The metastatic lung tumors of the FD/LDS mice displayed a similar alteration of expression profile in lactate-metabolizing enzymes with their paired lung tissues (Figure 3(a-2–a-4),(b-1)), except for GLUT1. The FD diet alone (FD sham) or in combination with LC and LCS transplants did not significantly alter lung expression of GLUT1, yet down-regulated expression of tumors’ GLUT1 (Figure 3(a-1)). As compared to mice fed with the control diet alone (the C sham group), dietary FD per se (FD sham group) significantly suppressed lungs’ mt VADC (Figure 3(a-4)) and promoted LDH expression (Figure 3(b-1)) without affecting expressions of the other tested glycolytic enzymes (Figure 3a,b). Expression of rate-limiting enzymes for anabolic metabolism such as G6PD (Figure 3(b-2)) for the pentose phosphate pathway (PPP) and ACLY (Figure 3(b-3)) for fatty acid synthesis was both significantly up-regulated in the FD sham group vs. the C sham group. In parallel, the redox equivalents as ratios of NADH/NAD+ (Figure 3c) and NADPH/NADP+ (Figure 3d) to support lungs’ anabolism were significantly increased in the FD vs. control sham groups. The enhanced lactate-associated anabolic bioenergetic metabolism in lungs of the FD sham mice remained up-regulated in lungs and also in metastatic tumors of the LCS mice (Figure 3b–d). For the control mice, neither LC nor LCS transplantation altered expressions of LDH (Figure 3(b-1)), anabolic enzymes (Figure 3(b-2,b-3)), and redox status of NADH/NAD+ (Figure 3c), despite the fact that expressions of glycolytic enzyme HK2 (Figure 3(a-2)), mt VDAC (Figure 3(a-4)), and NADPH/NADP+ ratio (Figure 3d) were in part increased by LC or LCS transplants. ## 3.4. Dietary FD and LC Invasion Activated the Metabolic Stress–mTOR-Signaling Pathways Next, we explored whether and how the dietary FD and implanted LC may impact on mTOR-signaling pathways, the master metabolic regulator of glycolytic and mt OXPHOS metabolism. As shown in Figure 4, the FD sham mice relative to the control sham group displayed significantly increased lung p-Akt levels, the upstream regulator of mTOR signaling. This FD-activated signal was further significantly enhanced by FD-LCS transplants in lungs and paired tumor tissues, evidenced by increased p-Akt level expression as compared to those of the FD sham group (Figure 4a,b). Correspondingly, FD activation of mTOR-signaling pathways was apparent by significantly increased expression of pmTOR (Figure 4a,c) and its two downstream targets of p-S6K1 (Figure 4a,d) and HIF1α (Figure 4a,e) in the FD sham mice compared with the control sham mice. LC and LCS transplantation of the FD mice maintained the FD-activated pmTOR (Figure 4b) and HIF1α levels (Figure 4d), and significantly enhanced p-S6K1 expressions (Figure 4c). Paired tumors from the FD/LCS mice displayed a similar activated mTOR-signaling profile with their paired lung tissues (Figure 4a–e). The impact of LC transplantation on mTORC1 activation of the FD mice at expression levels of pmTOR, p-S6K1, and HIF1α was significantly higher in the FD mice than in the control counterparts (Figure 4a–e), suggesting the synergistic effect of FD diet and LC invasion, in particular for FD-LCS, on mTOR metabolic signaling transduction. ## 3.5. Efficiency of Anti-Neoplastic Drug Treatments Rapamycin (Rap) and Metformin (Met) on FD-LCS-Induced LC Metastasis We evaluated the drug effects of rapamycin (Rap), an mTORC1-signaling blocker, and the anti-diabetic drug metformin (Met) on FD/LCS-potentiated cancer metastasis. As shown in Table 2, the FD-LCS transplantation to the FD mice resulted in a $100\%$ metastatic tumor colonization rate ($\frac{8}{8}$) with LC type of lung carcinoma and sarcomas in the pectoral muscle of the thorax, similar to the FD-induced tumorigenicity rate in our prior findings in Table 1 and Figure 2. Pre-treatment of the FD/LCS-implanted mice with Rap and Met drugs essentially prevented LC metastasis in lung and thorax tissues, resulting in a $0\%$ metastatic tumor colonization rate ($\frac{0}{6}$). Neither Rap nor Met pre-treatment of the LCS-implanted mice fed with the control diet affected the $0\%$ metastatic tumor colonization rate found in the control/LCS-implanted mice. Histological examination of lung tissues of these experimental mice revealed pathological lesions with chronic inflammation and lymphocyte aggregation in tumor-associated lungs of the FD/LCS-implanted mice compared with lungs of the control and FD sham mice (saline injection) (Figure 5). Rap and Met treatment of the LCS-transplanted control and FD mice did not result in any pre-cancerous lesions in lungs. The data suggested that Rap and Met treatment inhibited LCS metastases in the FD mice with no cancer effect on the control mice. ## 3.6. Druggable Protein Targets of Rap and Met Treatment in FD/LCS-Activated mTORC1 Signaling and Lactate Metabolic Disorder Towards the end, we deciphered the druggable targets associated with their anti-FD/LCS-induced cancer metastasis. As shown in Figure 6a, Rap treatment abolished FD/LCS-activated mTOR signaling by decreasing the expression of mTORC1 (Figure 6(a-1)) and HIF1α (Figure 6(a-2)), retaining LCS-induced 2-fold increased expression of AMP-dependent protein kinase (AMPK) expression (Figure 6(a-3)), and promoting 5-fold increased expression of insulin receptor substrate (IRS) expression (Figure 6(a-4)) as compared to those in the FD sham and FD/LCS-implanted mice. Rap blockage of FD/LCS-activated mTOR/HIF1α signaling coincided with moderate yet significant inhibition of FD/LCS-induced lung expression of HK2 (Figure 6(b-3)) and a non-significant reduced expression of LDHA (Figure 6(b-4)). In particular, a significant $50\%$ reduced expression of FD/LCS-activated MCT4 (Figure 6(b-6)), a monocarboxylate transporter (MCT4) for lactate exportation, was evident after Rap treatment as compared to their untreated FD counterpart. Rap treatment in mice did not significantly alter FD/LCS-inhibited expression of GLUT1 (Figure 6(b-1)) and GLUT4 (Figure 6(b-2)) and had little impact on FD/LCS-promoted MCT1 (Figure 6(b-5)), the lactate importer (Figure 6(b-4)), as compared with their untreated counterpart. Similar to Rap’s inhibitory effect on mTOR/HIF1α/AMPK signaling, Met treatment abrogated FD/LCS-promoted expression of mTORC1 (Figure 6(a-1)) and HIF1α (Figure 6(a-2)), and sustained FD/LCS-promoted AMPK expression (Figure 6(a-3)) compared with their untreated FD and control counterparts. The striking differential effect of Met treatment from Rap was observed for the IRS target (Figure 6(a-4)), in that Met treatment inhibited LCS-promoted IRS expression, whereas Rap treatment displayed the opposite effect to further the up-regulation of LCS-induced IRS expressions when compared with the control-drug-treated counterparts. Similar to Rap’s modulating effect on the downstream targets of mTOR/ HIF1α/AMPK signaling, Met blockage of the FD/LCS-activated mTOR/HIF1α signaling coincided with significant inhibition of FD/LCS-induced lung expression of HK2 (Figure 6(b-3)) and non-significant reduced LDH expression (Figure 6(b-4)). In particular, Met treatment induced a significant $50\%$ reduced expression of FD/LCS-activated MCT4 (Figure 6(b-6)) in lungs as compared to their FD sham and untreated FD counterparts. Met treatment did not alter FD/LCS-inhibited expression of GLUT1 (Figure 6(b-1)) and GLUT4 (Figure 6(b-2)) and had little impact on FD/LCS-promoted MCT1 (Figure 6(b-5)), the lactate importer, compared with their untreated counterpart. Reversion of FD/LCS-reprogramming lung mTOR/HIF1α/AMPK/IRS signaling and lactate mobilization target expression by Rap and Met subsequently resulted in a significant 7-fold decrease in lung lactate levels compared with their control and untreated counterparts (Figure 6c). Plasma lactate of the FD/LCS mice were little modulated by Rap and Met treatment compared with their drug-untreated counterpart (Figure 6d). The dietary folate intervention significantly interacted with metastatic LCSs (p for interaction = 0.024) and two drug treatments (p for interaction = 0.001) to reduce lung lactate. It is noticeable that Rap and Met treatment of the control mice simultaneously induced 2-fold increased levels of plasma lactate with no effect on the control lungs’ lactate, compared with those of their control sham and control drug-untreated counterparts. The data suggested an off-lung target effect of the drugs on the lactate metabolism of other organs in the control mice. Despite the lack of drug effect on lung lactate levels of the control, both Rap and Met treatment did promote control lungs’ expression of mTORC1 and IRS (Figure 6(a-1–a-4) and increased expression of GLUT4 and MCT1 for glucose/lactate uptake (Figure 6b), without affecting HIF1α/AMPK expression by Rap and by reducing AMPK expression by Met (Figure 6(a-1–a-4)). No drug impact on expression of enzymes in aerobic lactate production (HK2 and LDH) and lactate exporter MCT4 of the control mice was found as compared to the drug-untreated control counterparts. ## 4. Discussion To our knowledge, this is the first study to unveil the lactate metabolic influence of dietary FD to promote lung carcinoma metastases. Implantation of FD-induced high-lactate-producing LCSs to the FD but not control mice resulted in a specific hyperlactatemic TME in the vascular system and lungs to guarantee $100\%$ LCS metastases. This newly identified lactate metabolite biomarker of folate deficiency as a function of LC malignancy is concurrent with numerous clinical studies reporting hyperlactatemia being the diagnostic and prognostic predictor for tumor metastasis and recurrence in lung and other cancers [19,20,21,22]. How folate malnutrition elicits metabolic disorder of hyperlactatemia for LC malignancy remains elusive. In the content of the lactate biosynthesis pathways, over-expression of hexokinase 2 (HK2) and lactate dehydrogenase A (LDHA), the committed steps to regulate magnitude and direction of glucose flux for lactate production, are required for tumor initiation, maintenance, and metastatic cancer spread [31,32]. Inactivation of pyruvate dehydrogenase (PDH) by pyruvate kinase (PK) will block pyruvate entrance into the Krebs cycle to reduce mt OXPHOS and spare glucose carbon for lactate production [33,34]. Several metabolic flux studies revealed that 13C-lactate/glucose fueled aerobic glycolysis and the TCA cycle to sustain the anaplerotic biosynthetic need for the metastatic spread of human lung cancers [25,35,36]. In line with the malignant phenotype of lactate-metabolizing signatures, our data demonstrated that the FD/LCS-metastatic mice reprogrammed lung/metastatic tumors’ fuel metabolism from mt OXPHOS, by suppressed expression of PDH and mt VDAC, to accelerated aerobic glycolysis, by increased expression of HK2, LDHA, and PKM2, for lactate over-production. The data signify the FD/LCS-induced Warburg effect in metastatic tumors/lung tissues. In line with the lactate-acidified TME to shape the metastatic behavior of cancers [15,16,17,18], our data demonstrated that FD exposure of lung adenomas resulted in lactate secretion to acidify the TME and enhanced migration and invasive potentials to support anchorage-independent oncospheroid growth at the peripheral cancer metastatic stage. Even under FD-induced bioenergetics deficit from mt oxidative damage and dysfunctional mt OXPHOS [12,13,14], the FD-promoted hyperlactatemic TME of the vascular system and lungs confer the metastatic advantage of malignant cancer to acquire the alternative lactate fuel for survival and anchorage-independent growth in peripheral conditions, resulting in a $100\%$ metastatic rate. Of the most significant findings, our data demonstrated the molecular regulation of FD/LCS-reprogramming lactate metabolic disorder and LC malignancy through activation of the mTORC1/HIF-1α-signaling pathway, the energy sensor and master regulator of cell fuel metabolism [37]. In the FD sham and FD/LCS mice compared with the control counterparts, activation of lungs’ mTORC1 signaling cascade was evident with up-regulation of the upstream mediator, phosphorylated Akt (p-Akt), which activates phosphorylation of mTORC1 (mechanistic target of rapamycin) kinase and its downstream effector, the ribosomal p70-S6 kinase (pS6k), to stimulate ribosomal activity for protein biosynthesis and the signaling target of hypoxia-inducing factor (HIF-1α) [38]. HIF-1α is a well-characterized powerful transcriptional factor promoting aerobic glycolysis by up-regulation of the expression of GLUT1, HKII, and LDHA for increased glucose uptake and accelerated aerobic glycolysis for lactate production [39]. By the use of lactate as the anabolic fuel source, activation of mTORC1/ HIF-1α in a metastatic-cancers-driven TME has been demonstrated to switch cell lactate metabolism toward increased production of protein, lipids, and nucleotides for tumor biomass expansion and cancer proliferation [40]. Activation of mTORC1 stimulates de novo purine synthesis through control of the mt tetrahydrofolate cycle targeting methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) in serine-driven one-carbon metabolism which raises cellular NADPH/NADP+ and GSH/GSSG ratios to confer anabolic metabolic advantages for cancer metastasis [41,42]. In line with the mTORC1-signaling lactate anabolic metabolism, the FD/LCS-activated mTORC1/HIF-1α signaling cascade coincided with increased lung/tumor expression of rate-limiting enzymes for anabolic metabolism such as G6PDH which drives to the pentose phosphate pathway for nucleotide synthesis, ACLY for fatty acid synthesis, and empowers redox potential by increased ratio of NADPH/NADP+ and NADH/NAD+ in paired lung tumors. Furthermore, activation of mTORC1/HIF-1α signaling regulates lactate/proton symporters of MCT1 for lactate import and MCT-4 for lactate export, which mobilize lactate fuel transfer between stromal and cancer cells to sustain energy supply for cancer malignancies [43]. High lactate primes human fibroblasts to promote mTOR/HIF-1α-mediated lactate production and stromal lung expressions of MCT4 to export lactate for feeding tumors’ energy demands [44]. Knockdown of MCT4 inhibited invasiveness of human lung cancer cells [45]. Over-expression of GLUT1 and MCT4 in lung adenocarcinomas was associated with a poor disease-specific survival [46]. Increased MCT4 expression in cancer cells and stromal cells correlates with worse prognosis across many cancer types including lung cancer [47]. In the present study, blockage of the FD/LCS-activated mTOR/HIF1α signaling by the mTORC1 inhibitor, Rap, abrogated FD/LCS-promoted lungs’ glycolytic lactate production and exportation in lungs by significant inhibition of HK2 and MCT4 expressions to impede lactate supply for metastatic cancer use, and subsequently prevented LCS metastases development. Collectively, our findings identified the Rap druggable biomarkers of mTORC1/HIF-1α signalers and MCT4 lactate exporter as the most plausible anti-cancer therapeutic targets for reversing nutritional FD-potentiated lactate disorders and LCS metastases. More clinically significant, we demonstrate that the FD/LCS-driven lactate metabolic vulnerability for LC metastases can be therapeutically targeted by Met, the conventional anti-diabetic medicine, which has been under extensive pre-clinical investigation and clinical trials for its therapeutic effect of lung cancers [48,49] Resembling the Rap effect, Met treatment inhibited FD/LCS-activated mTORC1 signaling by suppressed expression of mTORC1/HIF-1α signalers, and decreased HKII and the MCT4 lactate exporter to result in Met normalizing lungs’ lactate levels. The molecular signaling targets of Met-treated FD/LCS mice are in line with the previous studies reporting on Met treatment of lung non-small cell lung cancer [50], adenocarcinomas [51], large-cell lung cancers [52], and of Balb/c nude mice implanted with A549 adenocarcinoma cells [53]. Numerous pre-clinical and retrospective clinical studies reported that Met treatment exerts its anti-neoplastic effects in sensitizing diabetic NSCLC patients to cytotoxic drug therapy on activation of the AMP-activated kinase pathway, an early growth signal transduction to counteract mTOR pathway activation in lipid and protein metabolism and in particular to promote apoptotic cancer death [48,49]. In the present study, AMPK expression was the dual target for FD/LCS and drug treatment in that Met/Rap treatment of the FD/LCS mice sustained the FD/LCS-activated AMPK expression with deactivation of mTOR/HIF-1α signaling and its downstream protein expressions. The integrative FD-reprogramming lactate metabolite signatures and mTOR/AMPK/HIF-1α-signaling-mediated druggable targets in the FD/LCS-promoted LC metastatic tumor microenvironment are illustrated in Figure 7. Activation of the AMPK/mTOR/HIF-1α loop-signaling pathway has been identified as the key anti-cancer mechanism to mediate metabolic check-points such as p53 and p21, and induced cell death modes in apoptosis and autophagy upon these cytotoxic drug treatments [40]. A deeper mechanistic insight into AMPK/mTOR-signaling cytotoxic targets upon Met/Rap treatment of FD/LCS mice warrants further studies. It should be noted that Rap/Met treatment exerted little impact on FD/LCS-induced hyperlactatemia yet elicited a two-fold increase in plasma lactate with no lung lactate effect in the control mice. The uncoupling drug effects on lungs and vascular lactate levels of the control and FD/LCS-implanted mice could not be simply attributed to drug-induced lung expression of mTORC1/IRS1/GLUT4/MCT1 for glucose/lactate shuttling between TME compartments of the controls and FD mice. Upon a diverse set of environmental stimuli on metabolic complexity, the FD diet and LCS invasions significantly interacted to complicate drug treated efficiency not only on lung targets, as disclosed in the present study, but also likely on several plausible off-targets of the host in fuel-utilizing organisms such as liver, muscle, and brain which encompass inherent genomic instability and phenotypic plasticity, heterogeneous bioenergetics demands, and differential metabolic mTORC1 signaling regulation in glucose and lactate utilization and mobilization [40]. In human cancer patients, FD-induced low serum folate has been associated with increased risks of tumor late-stage malignancy and poor prognosis rate [3,4]. The FD-diet-generated lactate metabolic susceptibility of the host at the tumor invasive stage, a common clinical malnutrition that cancer patients with cancer cachexia and/or adjuvant chemotherapy frequently encounter and that may not have been diagnosed for targeted effective therapy, may allow cancers to rapidly metastatically evolve and/or give rise to drug-resistant subclones, leading to tumor relapse and therapy failure. Precision targets on the FD-diet- and LCS-induced druggable oncoproteins warrant further studies to provide effective intervention strategies to cope with therapeutic perturbation of cancer lactate metabolism. ## 5. Conclusions In summary, the present in vivo and in vitro study delineates FD-induced and mTORC1/AMPK//HIF-1α-signaling-mediated lactate metabolism disorders in lung cancer metastasis. 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--- title: 'Mycoviruses in Fungi: Carcinogenesis of Fungal Agents May Not Always Be Mycotoxin Related' authors: - Cameron K. Tebbi journal: Journal of Fungi year: 2023 pmcid: PMC10052198 doi: 10.3390/jof9030368 license: CC BY 4.0 --- # Mycoviruses in Fungi: Carcinogenesis of Fungal Agents May Not Always Be Mycotoxin Related ## Abstract Certain viruses have been found to induce diverse biological pathways to carcinogenesis, evidenced by the presence of viral gene products in some tumors. Despite the fact that many fungal agents contain mycoviruses, until recently, their possible direct effects on human health, including carcinogenesis and leukemogenesis, had not been explored. In this regard, most studies of fungal agents have rightly concentrated on their mycotoxin formation and effects. Recently, the direct role of yeasts and fungi in the etiology of cancers, including leukemia, have been investigated. While greater attention has been placed on the carcinogenic effects of Candida, the role of filamentous fungi in carcinogenesis has also been explored. Recent findings from studies using the enzyme-linked immunosorbent assay (ELISA) technique indicate that the plasma of patients with acute lymphoblastic leukemia (ALL) uniformly contains antibodies for a certain mycovirus-containing Aspergillus flavus, while controls are negative. The exposure of mononuclear leukocytes from patients with ALL in full remission, and long-term survivors, to the product of this organism was reported to result in the re-development of typical genetics and cell surface phenotypes characteristic of active ALL. Mycoviruses are known to be able to significantly alter the biological characteristics and functions of their host. The possible carcinogenic and leukemogenic role of mycoviruses, with and without their host, needs to be further investigated. ## 1. Introduction All individuals are routinely exposed to a variety of fungal organisms, for the most part without any detectable significant adverse effects. However, this is not universal and varies based on health status, immunity, existence of other disorders, and type of the organism involved. For example, exposure to Aspergillus spores routinely occurs in healthy populations without any obvious clinically detectable effects. However, the same exposure can result in serious pathogenic effects in individuals with certain underlying diseases such as cancer or immune deficiency disorders. Until recently, the major known direct pathogenic effects of Aspergillus species have included allergies, toxicities, and a variety of infections [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61] (Table 1). A substantial amount of data, however, has been accumulated, indicating that those working in the occupations with a high degree of fungal exposure generally have a higher rate of cancer [5,62,63,64,65]. In contrast, while somewhat controversial [66,67,68,69,70,71,72], individuals with allergy-related diseases and asthma have been reported to generally have a lower rate of cancer, including leukemia and a variety of solid tumors, as compared to the general population [73,74,75,76,77,78,79,80,81,82,83,84]. Some epidemiological data indicates potential roles for IgE, allergy, and atopy in protecting against certain tumors [85,86]. An increased cancer risk in association with IgE immunodeficiency has also been reported [87,88]. Significant information regarding the inverse association between atopic conditions and glioma has been accumulated [89,90]. Some microorganisms are known to have the ability to induce tumor initiation and progression, directly through their effects on the cells, or indirectly by their effects on the immune system. Several studies have correlated the possible involvement and association of fungal species, particularly Candida, with the development and progression of various types of cancer. While most attention has been directed to yeasts in the so-called blastomycete theory of cancer, more recently, other mechanisms, including the possible role of mycoviruses in fungal organisms, have been suggested [91,92,93,94,95,96,97,98,99]. In the recent past, it has been shown that the in vitro exposure of mononuclear cells from individuals who have a history of acute lymphoblastic leukemia (ALL) and are in full remission, without any evidence of the disease, including long-term survivors, to a certain mycovirus-containing Aspergillus flavus (MCAF) results in the re-development of cell surface phenotypes and genetic markers characteristic of active ALL [91]. Such exposure in controls did not induce any changes [91]. If this is due to the certain genetic or epigenetic background in the ALL patients is not clear. In a related study, unlike controls, patients with ALL were found to have antibodies for the products of MCAF [92]. It is of interest that the mycovirus-containing Aspergillus flavus used for these studies was isolated from the home of a patient with ALL and the organism did not produce any aflatoxin [91,92]. A well-known theory for the etiology of ALL in the pediatric age group suggests that the development of this disease is due to a combination of genetic mutations and exposure to infections [100]. This so-called “two-hit” model postulates that ALL evolves in two discrete steps. The first step is in utero initiation by fusion gene formation or hyperdiploidy, which generates a pre-leukemic clone. The second step, which is proposed to only occur in a very small sub-population of the predisposed, is suggested to be exposure to infections and post-natal acquisition of secondary genetic changes that drives conversion to overt ALL. It is postulated that exposure to infections earlier in life are protective, but in their absence, infections later in life trigger the critical secondary mutations [100]. It is suggested that the risk can be further modified by other inherited genetics, and possibly diet, as well as chance. While a number of predisposing genetic factors have been identified, until recent reports [91,92], no certain infectious agents had been proposed. Based on the recent findings, it is postulated that exposure to mycovirus-containing Aspergillus flavus could possibly be one of the post-natal infections that can trigger the second step in the developmental process of ALL [91]. A number of studies have explored the role of viral, bacterial, and fungal organisms in the etiology of a variety of cancers. In the past, many investigations have concentrated on the correlation of viruses with the development of malignant disorders. While such a correlation has been made for many viral agents, less attention has been paid to the fungal organisms, including those containing mycoviruses. Typically, most studies have been based on the statistical relation of the frequency of exposure to a given agent, versus the development of a certain cancer. For example, there is an increased rate of cancer and leukemia [5] in individuals likely be exposed to fungal agents, such as agricultural workers [101]. More recently, experiments have reported direct evidence of some organism’s involvement in the development of certain cancers. For example, some experiments have revealed that DNA specific to the human papilloma virus (HPV) is integrated into the host cell genome. This virus is known to be associated with cervical, anal, penile, vulvar, vaginal, oropharyngeal, and head and neck cancers [102]. HPV type 16 and 18 viral DNAs have been found in cervical cancers and two viral dominant oncogenic genes, E6 and E7, are consistently expressed in HPV-positive malignancies and HPV-infected cancer cells. These oncogenes are known to be associated with the malignant transformation of cells and the alteration of the immune system, causing disruption of natural tumor suppressor pathways, culminating in the proliferation of cervical carcinoma cells [103]. Fungi have a worldwide distribution and virtually can be detected in any environment [104,105,106,107,108,109,110,111,112,113,114]. For example, Aspergilli are found in soil, water, outdoor and indoor, and may produce numerous conidia which can disperse via air movement and possibly insects [104,105,106]. While there are seasonal variations, there is a significant amount of spore and diversity of fungi in air particulate matter [107]. The optimum temperature for the growth of these organisms has a wide range, with significant growth occurring in temperatures ranging from approximately 15 to 30 °C [108,109,110,111]. Lately, the direct effects of yeast and fungi in the etiology of cancers, including leukemia, have also been further explored. Greater attention has been placed on the so called “blastomycete theory of cancer” and the relation of yeasts, especially the Candida species, to carcinogenesis [112]. To a lesser extent, the role of filamentous fungi has also been evaluated. Among the fungal agents, Aspergillus and Candida species are the most investigated for their possible role in carcinogenesis. Aspergilli, due to their widespread distribution and production of mycotoxins, are known for their potential to cause cancer [93,112]. These have been classified and divided into several groups, each with distinct biological and molecular characteristics [93,115,116,117,118]. As noted above, Aspergilli are known to produce a variety of allergic disorders [1,2,3,5], toxicities, and infections [17,22,23,24,54,55,56,57,58,61]. Aspergillus can be associated with tissue damage, burn, keratitis and endophthalmitis, or post operative infection [13,16,119,120,121,122,123,124,125,126,127]. Empyema and pleural aspergillosis, as well as osteomyelitis, can occur, especially in individuals with reduced immunity. The association of Aspergillus infections with a foreign body, including peritoneal dialysis catheters and intravenous lines have been reported. Abscesses in various organs and systems, including skin, subcutaneous tissues, sinuses, oropharynx, lungs, brain, and other organs and systems can occur. In many infection entities, Aspergillus fumigatus or A. flavus are often involved [13,16,119,120,121,122,123,124,125,126,127]. The effects of mycotoxins produced by fungal agents have been long recognized [113,114]. Normally, Candida is located on skin, most of mucosal surfaces, mouth, gastrointestinal tract, and vagina without any detrimental effects. However, Candida species in general, and Candida albicans in particular, have been found to be associated with the development of certain cancers, including oral, esophageal, and gastrointestinal neoplasms. Some of these carcinogenic effects are through the production of specific hydrolytic enzymes metabolizing ethanol to acetaldehyde (ACH). Acetaldehyde is metabolized from ethanol by alcohol dehydrogenases (ADH). ADH is a cell wall protein necessary for the growth of fungi, its metabolism [128], and interaction with host cell proteins to initiate an immune response [128,129,130]. Mutations within host DNA degrade protein molecules and impair their functions which are essential for normal cellular activities and division [131]. ACH, which is a group 1 human carcinogen, can induce the production of pro-inflammatory cytokines and mediators [132,133,134], causing cellular oxidative stress and damage [134], inducing the formation of covalent adducts in protein or DNA residues [131], DNA cross-linking, or chromosomal aberrations [135,136]. The aberrations described can potentially lead to tumor development and progression [95,137]. There is evidence that pathologically, C. albicans can increase the risk of carcinogenesis and metastasis through several other mechanisms, including inflammation, the production of carcinogenic byproducts, the induction of the Th17 response, and molecular mimicry [137,138,139,140,141,142,143,144,145,146]. In addition to several clinical reports associating Candida spp. to carcinogenesis, there are a number of biomolecular findings indicating its ability to cause dysplasia and malignant neoformation in oral epithelium. Candida can produce carcinogens, such as N-nitrosobenzylmethylamine, resulting in the development of malignant disorders including oral cancer [138,139,140,141]. The development of pancreatic cancer has also been attributed to inflammation and immune activation due to an increased nitrosamine exposure. Some of the mechanisms of actions suggested for the carcinogenic effects of Candida include over-expression of P53, Ki-67 labeling index, and Prostaglandin-endoperoxide synthase 2 (COX-2), promoting the production of acid aspartyl-proteinase. Other effects include immune-related mechanisms induced by up-regulation in proinflammatory cytokines such as interleukin (IL)-1α, IL-1β, IL-6, IL-8, and IL-18, tumor necrosis factor (TNF)-α, IFN-b [138,142,143], and the production of carcinogenic acetaldehyde [137,144,146] and candidalysin, which is a cytolytic toxin [146]. ## Mycotoxins More than 350 types of mycotoxins are found in animal feed but the most important are aflatoxin, ochratoxin, fumonisin, and zearalenone [147,148,149,150,151,152,153,154,155,156,157,158]. The pathological condition induced by any mycotoxin depends on sex, immune status, type of mycotoxin, duration, and the amount of mycotoxin. Mycotoxins are responsible for the suppression of the quality of the poultry industry. According to the Food and Agriculture Organization (FAO), $25\%$ of cereal grains are found to be affected by mycotoxins. Aflatoxin is one of the most important mycotoxins produced by A. flavus and A. parasiticus. More than 20 types of aflatoxins are found. The most common derivatives of aflatoxin are B1, B2, M1, and M2. B1 is the most potent carcinogenic mycotoxin and M1 is the most common in milk. The carcinogenesis and leukemogenesis of many fungal species, in animals and humans, have traditionally been attributed to their production of mycotoxin. Mycotoxins are toxic secondary metabolites that are produced by fungal species, particularly those of filamentous fungi which often grow on plant-based agricultural products. The fungal growth occurs prior to the harvest of the crops and during their storage. Mycotoxins can be found in peanuts, grains, corn, millet, sesame seeds, wheat, and animal-derived foods such as milk, eggs, meat, and other commodities, and are highly toxic to humans and animals. A single fungal species can potentially produce several mycotoxins [148,150]. The hepatotoxicity and hepatocarcinogenic effects of fungal agents secondary to the production of mycotoxins in general, and aflatoxin in particular, are well recognized [91,93]. Some mycotoxins affect DNA replication, and therefore, can have mutagenic or teratogenic effects. Exposure to mycotoxins can result in the impairment of metabolic, nutritional, endocrine, immunological, hepatic, reproductive, and other systems. The four basic toxicities of mycotoxins are acute, chronic, mutagenic, and teratogenic effects. Common acute mycotoxin poisoning effects includes deterioration of liver or kidney function, which can potentially lead to death. Some mycotoxins interfere with protein synthesis, causing disorders ranging from skin sensitivity or necrosis to immunodeficiency, depending on the dose exposed. Mycotoxins are neurotoxic, producing symptoms ranging from trembling to brain damage. An example of the major biotoxins produced by Aspergillus species are summarized in Table 2. Aflatoxins, produced by Aspergillus spp., are one of the highly toxic secondary metabolites derived from polyketides. These are known to induce acute intoxication, fulminant hepatic failure, and rhabdomyolysis. Chronic exposure to this toxin can result in cirrhosis of the liver which may lead to hepatocellular and gall bladder carcinoma. Other effects of aflatoxins on human health include disorder of lipid metabolism, depression of protein and enzyme synthesis, and reduced production of hemoglobin and response to vaccines [149,150]. The mycotoxins produced by Penicillium and Fusarium species have adverse effects on heath, including infertility in males and females, destructive effects on the fetus, impairment of growth and development in children, and undesirable health outcomes in various stages of life. These agents can hamper the division and differentiation of the gametes which can result in infertility due to interference with spermatogenesis. Zearalenone has been linked to precocious puberty in females. In animal models, exposure to mycotoxins can promote adverse effects on spermatozoa, Sertoli and Leydig cell function, oocyte maturation, and uterine and ovarian development and function. These agents have the potential to damage the sex organs. Mycotoxins may disturb the endocrine system and alter steroid hormone homeostasis, resulting in subfertility or infertility. These can exert oxidative stress causing sperm DNA damage and reduced fertilization [151,152,153,154,155]. Based on animal studies, mycotoxins can increase the possibility of stillbirth and can pass through the mother’s milk and affect the health of infants [156,157,158,159]. Since mycotoxins can negatively alter cell division, they can affect the fetus and decrease the growth and development of children. Neural tube defects in fetuses have been reported. Adverse effects on fetuses and children include abnormal neural development, causing cognitive disability. In addition, these toxins may cause decreased gastrointestinal absorption resulting in malnutrition and reduced growth [160,161,162,163,164,165]. ## 2. Metabolism of Aflatoxins Aflatoxins are furanocoumarins which are produced by various strains of Aspergillus species and produce various toxicities in animals and humans [166,167,168,169,170,171]. The toxicity and mechanism of action of aflatoxins have been explored [166,167,168,169,170,171]. The carcinogenic and mutagenic activities of aflatoxins are largely attributed to their lactone and difuran rings. Aflatoxins have a furanocoumarin chemical structure, with over 18 types chemically identified. Following ingestion, AFB1 is metabolized to form AFB1-8,9-epoxide, which binds to DNA and forms AFB1-guanine adducts. There are significant individual and age-related differences in the metabolism of AFB1, resulting in variation noted in its toxicity. In vitro metabolism studies reveal that reduction of AFB1 results in the production of aflatoxicol (AFL), which its hydroxylation produces AFM1, its hydration generates AFB2a and its epoxidation AFB1-2,3-epoxide. Of these, epoxide is the most reactive, and is believed to be responsible for the acute and chronic toxicity of AFB. Aflatoxicol can pass through the placenta and damage the fetus. AFB1 is known to be metabolized in the liver by the cytochrome P450 enzyme system (CYPs). Aflatoxin B1-8,9-epoxide (AFB0), which has exo and endo isomers, is a carcinogenic derivate of this toxin. The CYP3A4 and CYP1A2 derivates are primarily responsible for the aflatoxin biotransformation, and the exo isomer formed. Studies in birds indicate that CYP2A6 and, to a lesser extent, CYP1A1 are involved in the bioactivation of AFB1; into AFBO. Regarding DNA, AFB0 binds covalently to the N7 position on guanine, and forms an AFB1-N7-guanine adduct. The endo isomer has lower affinity than the exo; therefore, AFB1-exo-8,9-epoxide is likely the major carcinogenic metabolite [158,171]. The production of the various mycotoxins varies based on numerous factors. For example, fungal organisms overwinter as either resistant structures called sclerotia or as mycelium. The difference in the pattern of sclerotia production is associated with different aflatoxin production. An example is that the S strain of Aspergillus flavus produces numerous but smaller sclerotia, while the L strain generates fewer but larger sclerotia. The products of these subgroups vary significantly. The S strain isolates, designated SB, make only B aflatoxins while those termed SBG produce B and G aflatoxins. It is suggested that these differences may represent a taxon different from Aspergillus flavus. Some strains of Aspergillus flavus do or do not produce aflatoxins B1 and/or B2. Other toxins which may be produced by this organism include cyclopiazonic acid, kojic acid, sterigmatocystin, bnitropropionic acid, aflatrem, aspertoxin, aspergillic acid, and gliotoxin. In addition, Aspergillus flavus can potentially produce other secondary metabolites including versicolorin A dihydroxyaflavinine, paspalinine, and indole. Aflatoxins, which are the most potent hepatocarcinogenic agents, are known to be produced by a variety of Aspergillus species, predominantly A. flavus, nomius, and parasiticus. Of sixteen structurally related toxins, aflatoxins B1, B2, G1, and G2 are of the most concern [166,167]. The metabolites produced by the hepatic metabolism of aflatoxins are responsible for most of their toxicity. Aflatoxin B1 (AFB1) has the most carcinogenic potential, and its carcinogenicity is classified as group 1 by the International Agency for Research on Cancer (IARC). Exposure to the aflatoxin metabolites results in acute liver damage. Should this be continued, it has a high potential for carcinogenesis due to the damage to DNA through adduct formation and interference with protein metabolism [168]. In pregnant animal models, exposure to AFB1 leads to genotoxic changes which predisposes the offspring to morphological abnormalities, behavioral alterations, reproductive disturbances, cancer, and early death in adult life [170,171]. In humans and animals, the signs and symptoms of aflatoxin toxicity depends on the level and duration of exposure, age, gender, health status, concurrent exposure to other toxins, and a number of other variables. Generally, adults have a higher tolerance for aflatoxin and rarely succumb to acute aflatoxicosis. In contrast, children are less tolerant and their exposure results in stunted growth and delayed development. The latter is common in many developing countries [172,173,174]. In general, acute aflatoxicosis due to the ingestion or inhalation of high doses of AFB1 results in acute poisoning. These toxins can be transmitted to the fetus through the placenta, and to infants via breast milk [110,111,148,175,176,177,178,179,180,181,182,183]. Severe damage to the internal organs and systems including liver, kidneys, heart, and the hemopoietic and immune system, along with bleeding, can result in death. For survivors, long-term complications include organ and system failures and carcinogenesis. Post exposure, free AFB1 is present only for a short period of time in the blood. Such exposure can be detected through the measurement of the metabolites of AFB1 including aflatoxin-albumin, aflatoxin M1 (AFM1), aflatoxin P1 (AFP1), aflatoxin Q1 (AFQ1), AFB-N7 guanine, and aflatoxicol (AFL), in blood and biological fluids. In the first 24 h post exposure, the measurement of the breakdown products of AFB1, including AFB1-guanine, in the urine may reflect exposure to this mycotoxin. Measurement of the AFB1-albumin adduct level in the serum provides a more integrated measure of the longer-term exposure. AFM1 is classified as agent 2B by IARC for its carcinogenic potential. Metabolites of aflatoxins are present in the tissues, urine, feces, and milk [184,185,186,187,188,189,190]. The latter is of importance in infants during breastfeeding because of its effects in infants. Likewise, commercially available milk collected from animals fed with various contaminated agricultural commodities may contain this agent. Various metabolites of mycotoxins can be measured in blood, urine, stool, milk, etc. [ 184,185,186,187,188,189,190]. AFM1 can be utilized as a measurable biomarker in the urine. Immunotoxins with small molecules fail to induce any response in the human immune system. Therefore, a major potential danger of exposure to mycotoxins in the diet is the human inability to detect them biologically [2]. Another product of AFB1 is the AFB-N7-guanine biomarker which indicates prolonged exposure to this toxin. DNA alkylation or adduct formation is at nucleophilic sites in DNA, including the N7-position of guanine. The N7-guanine adducts are considered non-promutagenic. These are chemically unstable, since the N7-position does not participate in a Watson–Crick base pairing. The N7-guanine adducts have been shown to convert to ring opened lesions (FAPy) which have much more mutagenic potential, persist longer in the body, and have higher mutagenic potency [191]. A variant with a greater carcinogenic potential is fumonisin B1 (FB1), which is classified by the IARC as a 2B product. This is predominantly produced by Fusarium verticillioides and F. proliferatum and contaminates maize and maize-based foods. FB1 inhibits ceramide synthase and interrupts sphingolipid synthesis via the inhibition of sphingosine-N-acetyltransferase, resulting in oxidative stress, the alteration of DNA methylation, and modulation of autophagy, and results in stress to the endoplasmic reticulum, leading to the reduced production of sphingolipids and the accumulation of sphinganine (Sa) and sphingosine (So). The result is the non-genotoxic mechanism underlying its toxicological and carcinogenic effects. While its effect on human health as yet is not fully discovered, in populations consuming large amounts of contaminated maize-based foods, epidemiological and experimental evidence points to this being a risk factor for esophageal cancer and neural tube defects. In animals, fumonisins can cause leukoencephalomalacia in horses, pulmonary edema in swine, and hepatotoxicity and nephrotoxicity in rats [192,193,194,195]. While most studies focus on a single mycotoxin and its effects on human health, animal studies reveal a complex and possibly additive, synergistic, or antagonistic effect [196,197,198,199]. The association of aflatoxins classified as group1 by the IARC, including aflatoxin B1 (AFB1), aflatoxin B2 (AFB2), aflatoxin G1 (AFG1), aflatoxin G2 (AFG2), and aflatoxin M1 (AFM1), with liver cancer is well documented. Various malignant disorders due to rice and cereal contamination with AFB1, including breast, cervical and esophageal cancers, have been reported [200,201,202,203,204,205,206,207]. A significant amount of data regarding carcinogenicity of mycotoxins, alone or in conjunction with unrelated viruses are available; however, the possible effects of mycoviruses singularly or in combination with their fungal host has not been fully explored. ## 3. Mycoviruses and Cancer For several decades, viruses affecting fungal organisms, known as mycoviruses, have been known to exist [208,209]. However, except for occasional reports, their human pathogenicity and possible role in health has not been fully evaluated. It is estimated that from 30 to $80\%$ of all fungal species, predominantly endophytic fungi, contain mycoviruses. The existence of mycoviruses in Aspergillus species is well recognized. The modulation of fungal toxins such as the loss of aflatoxin production in A. flavus infected with mycovirus has been reported [210,211]. Mycoviruses possess various forms of viral genomes which include double-stranded RNA (dsRNA), single-stranded RNA (ssRNA), and single-stranded DNA (ssDNA). Currently, the International Committee for the Taxonomy of Viruses (ICTV) records 17 taxa, 16 families, and one genus that does not belong to a family. While most mycoviruses have ds RNA linear genomes, positive-sense ss RNA linear genomes including reverse transcribing RNA linear genomes, negative-sense ssRNA linear genomes, or ssDNA circular genomes also exist [212]. Of these, dsRNA segments most commonly affect fungal organisms. Taxonomically, the fungal dsRNA viruses are classified into seven families which include Endornaviridae, Chrysoviridae, Megabirnaviridae, Quadriviridae, Partitiviridae, Reoviridae, and Totiviridae. The transmission of mycoviruses occurs vertically during cell division, forming asexual and sexual spores called sporogenesis, and/or horizontally via mating or hyphal anastomosis through cytoplasmic exchange, and not during the extracellular phase of the viral life cycle. The latter, however has been disputed [212]. Some viruses have a unique self-protective or aggressive ability, producing defensive substances. These products can have a growth-inhibitory activity against several bacterial and fungal species. The term ‘killer strains’ describes yeast and fungal species that can produce ‘killer toxins’ with antimycotic activity for lethal function or self-protection. This killer phenotype is usually associated with double-stranded (ds)RNA mycoviruses and linear dsDNA plasmids. It can also be chromosomally encoded. For example, viruses of the family Totiviridae have a unique ability to produce a killer toxin which is capable of lysing susceptible neighboring strains, while they themselves remain immune to the toxin. Four killer toxins, i.e., K1, K2, K28, and Klus, have been reported. Some dsRNA mycovirus-containing fungal agents have been shown to alter the expression of genes involved in the ribosomal synthesis and programmed cell death of the fungal host. Mycoviruses affecting a human pathogen may also have an effect on the infected individual. For example, Malassezia species produce various skin diseases including dandruff, seborrheic dermatitis, and atopic dermatitis. In one study, this organism was found to contain MrV40 mycovirus, which belongs to the family Totiviridae. In a reported study, the viral nucleic acid from MrV40 had induced a Toll-like receptor 3 (TLR3)-mediated inflammatory immune response in the bone-marrow-derived dendritic cells. This finding may indicate a role for the included mycovirus in the pathogenicity of Malassezia [213,214]. Mycoviruses are known to be able to alter their fungal host’s phenotype, including but not limited to pigmentation, morphology, sexual and asexual sporulation, the production of toxins, and growth. As noted before, the loss of aflatoxin production in A. flavus infected with mycovirus has been reported [210,211]. If these organisms can exert any changes in humans or animals infected with mycovirus-containing fungi has not, as yet, been significantly explored. Viral dsRNA is recognized by Toll-like receptor 3 (TLR-3) and several cytosolic sensors and can provoke interferon production in a TLR-3 dependent or independent fashion [215]. An increased rate of cancer in occupations with higher rate of exposure to fungi, such as agricultural and construction workers, have been found [5,101]. Individuals with allergies have been reported to have a decreased risk of certain cancers compared with the general population. In allergic individuals, lower rate of glioma, laryngeal, esophageal, oral, pancreatic, gastric, colorectal, uterine body cancers, and non-Hodgkin lymphoma have been reported. Reports regarding leukemia, thyroid, lung, melanoma, and breast cancer in this group are conflicting. An increased risk of bladder cancer, lymphoma, myeloma, and prostate cancer in individuals with allergies is reported [68,84,101,215]. It is not clear if in those individuals with allergies and decreased rates of cancer, their allergens include fungi. On the other hand, those with greater exposure to fungi have a higher rate of this disorder. As noted before, patients with acute lymphoblastic leukemia were found to have antibodies to a certain mycovirus-containing Aspergillus flavus and the exposure of mononuclear blood cells from patients with ALL in full remission to its products resulted in the redevelopment of genetic and cell surface phenotypes characteristic of ALL [91,92]. Based on these findings, it has been postulated that this organism may potentially have a correlation with leukemogenesis [91,92]. Research regarding mycovirus-containing organisms and cancer may have etiological value. ## 4. Conclusions The possible role of various organisms in carcinogenesis and leukemogenesis has been suspected. While the role of viral agents in the development and progress of a variety of cancers has often been the subject of these investigations, the carcinogenic effects of fungal agents have also been explored. Until recently, the latter has been mostly concentrated on the contamination effects of mycotoxins. These effects result in major toxicities which are of health and commercial concern. Demonstration of the effects of various viral agents in carcinogenesis is exemplified by cervical carcinoma. Experiments reveal that DNA specific to the human papilloma virus is integrated into the host cell genome, and viral oncoproteins E6 and E7 consequently cause the disruption of natural tumor suppressor pathways, culminating in the proliferation of cervical carcinoma cells. Mycoviruses have been shown to alter the biology of their fungal host, such as the secession of aflatoxin production in Aspergillus spp. as well as the expression of genes involved in ribosomal synthesis and programmed cell death in several species. The effects of mycoviruses alone or in conjunction with their fungal host in human health is poorly evaluated. Recent studies reveal that patients with acute lymphoblastic leukemia in full remission, and long-term survivors, uniformly have antibodies to a certain mycovirus-containing A. flavus. Furthermore, exposure of the mononuclear leukocytes from these patients to the products of the above organism results in the redevelopment of genetic and cell surface phenotypes characteristic of active acute lymphoblastic leukemia pointing to the possible cause and effect relationship. The role of mycoviruses, with and without their hosts in human disorders, particularly in carcinogenesis and leukemogenesis, needs to be explored. ## References 1. Akiyama K., Takizawa H., Suzuki M., Miyachi S., Ichinohe M., Yanagihara Y.. Allergic Bronchopulmonary Aspergillosis due to Aspergillus oryzae. Chest (1987) 91 285-286. DOI: 10.1378/chest.91.2.285 2. Chakrabarti A., Sethi S., Raman D.S.V., Behera D.. Eight-year study of allergic bronchopulmonary aspergillosis in an Indian teaching hospital. 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--- title: Innovative Fabrication of Hollow Microneedle Arrays Enabling Blood Sampling with a Self-Powered Microfluidic Patch authors: - Lorenz Van Hileghem - Shashwat Kushwaha - Agnese Piovesan - Pieter Verboven - Bart Nicolaï - Dominiek Reynaerts - Francesco Dal Dosso - Jeroen Lammertyn journal: Micromachines year: 2023 pmcid: PMC10052199 doi: 10.3390/mi14030615 license: CC BY 4.0 --- # Innovative Fabrication of Hollow Microneedle Arrays Enabling Blood Sampling with a Self-Powered Microfluidic Patch ## Abstract Microneedles are gaining a lot of attention in the context of sampling cutaneous biofluids such as capillary blood. Their minimal invasiveness and user-friendliness make them a prominent substitute for venous puncture or finger-pricking. Although the latter is suitable for self-sampling, the impracticality of manual handling and the difficulty of obtaining enough qualitative sample is driving the search for better solutions. In this context, hollow microneedle arrays (HMNAs) are particularly interesting for completely integrating sample-to-answer solutions as they create a duct between the skin and the sampling device. However, the fabrication of sharp-tipped HMNAs with a high aspect ratio (AR) is challenging, especially since a length of ≥1500 μm is desired to reach the blood capillaries. In this paper, we first described a novel two-step fabrication protocol for HMNAs in stainless steel by percussion laser drilling and subsequent micro-milling. The HMNAs were then integrated into a self-powered microfluidic sampling patch, containing a capillary pump which was optimized to generate negative pressure differences up to 40.9 ± 1.8 kPa. The sampling patch was validated in vitro, showing the feasibility of sampling 40 μL of liquid. It is anticipated that our proof-of-concept is a starting point for more sophisticated all-in-one biofluid sampling and point-of-care testing systems. ## 1. Introduction Blood acts as an important window to monitor our body’s health status. Therefore, millions of blood samples are globally collected daily for diagnostic purposes. The invasive character of a venous puncture not only requires healthcare workers with phlebotomy expertise but also holds the risk of needle-stick injuries, accidental infection after non-sterile usage, and denial by people with an aversion to needles [1]. To decentralize the collection of blood, cutaneous capillary blood is a good alternative as it can easily be self-sampled by finger pricking using an external piercing element [2]. However, in addition to still being relatively invasive, obtaining acceptable quantities while maintaining adequate quality is often challenging [3,4,5]. Furthermore, the generated blood droplet has to be deposited manually on, for instance, the inlet of a point-of-care diagnostic test or a dried blood spot card, which often leads to volume losses or inaccurate results. As a solution for self-sampling, the use of microneedles (MN) received a lot of attention as they are less painful and significantly easier to use [6]. MNs are miniaturized needles that can be employed both to extract biofluids or inject medicine into the skin. For sampling, four major MN types have been described in the literature: solid, porous, hydrogel-forming, and hollow MNs (HMN). When aiming for an integrated blood self-collection device, HMN arrays (HMNAs) are the most interesting as they can form a direct fluidic connection between the cutaneous capillaries and the channels of a microfluidic device [7]. However, they are generally more challenging to fabricate, with many techniques and materials explored so far. Silicon, one of the most common materials used in micro-electromechanical systems, has been processed by means of isotropic etching together with anisotropic deep reactive-ion etching or back-side illumination electrochemical etching [8,9,10,11]. Despite its strength, silicon is brittle and prone to break after insertion in the skin, being problematic as crystalline silicon is not biocompatible [12]. Therefore, polymers such as SU-8, PEGDA, or E-Shell have been used with UV lithographic techniques [13,14,15,16,17,18], whereas PMMA is more suitable to be structured with X-ray lithography or micro-injection molding [19,20,21]. Alternatively, metals have a better strength and ductility [22]. For instance, nickel and titanium have been electroplated or sputtered on structures previously prepared by lithography or etching processes [23], while stainless steel has been used in approaches such as femtosecond-laser machining, electrical discharge machining (EDM) or simply assembling commercially available needles on a base substrate [24,25]. Unfortunately, the above-mentioned HMNA examples are not suitable for blood sampling applications as HMN lengths ≥1500 μm are required to reach the cutaneous capillary network [26,27]. As a creative solution, in-plane configured HMNAs have been fabricated [28]. Though, to be compatible with microfluidic platforms for downstream on-chip sample manipulation, out-of-plane configuration in the form of a patch is required. Hereto, Chaudhri et al. optimized the pre-exposure steps to allow UV lithography on thicker SU-8 layers and fabricated 1540 μm tall HMNAs [26]. However, this technique did not allow for creating a direct fluidic connection with a base plane or beveled sharp tips. Alternatively, Le Thanh et al. presented 1515 μm tall SU-8 HMNAs with pyramidal beveled tips using isotropic etching and inclined UV lithography [29,30]. In addition to SU-8, Miller et al. focused on E-Shell 200 and 300 polymer to create tetrahedron-shaped HMNs by digital light processing 3D printing and 2-photon lithography, respectively [31,32]. Furthermore, metallic HMNAs were achieved as well by a drawing lithography technique and subsequent nickel electro-plating [33,34]. This way, a single out-of-plane hollow MN was achieved with a length of up to 1800 μm. For fabricating a 15° beveled tip, an extra laser cutting step was needed. In follow-up work, the integration of an elastic PDMS chamber with two passive valves allowed the withdrawal of 30 ± 5 μL of blood for downstream processing and analysis on a paper-based sensor for glucose and cholesterol [35]. Among all fabrication procedures for tall HMNAs, the mechanical, biological, and economic advantages of alloys such as stainless steel barely received attention [36]. Furthermore, the main focus on classic microfabrication materials and methods did not solve critical shortcomings such as [1] the challenge to directly create beveled sharp tips, [2] the lack of a direct fluidic connection with the base plane, [3] the need for cleanroom facilities, or [4] the need for intricate fabrication steps that do not allow for batch fabrication. Consequently, the scarcity of useful HMNAs has hampered the progress toward integrated microsampling systems envisioning point-of-care sampling and diagnostic testing. This work presents the fabrication of stainless steel HMNAs and their integration in a self-powered sampling patch. With the goal of overcoming the challenging material properties of stainless steel, a novel two-step approach by laser drilling and micro-milling is first explored and characterized by brightfield microscopy, X-ray microcomputed tomography (μCT), and pressure drop measurements. Next, the HMNAs are integrated with a self-powered imbibing microfluidic pump by liquid encapsulation (SIMPLE), which is first characterized in terms of pressure generation. Finally, the sampling performance of a SIMPLE-based sampling patch is validated on an in vitro skin equivalent. ## 2.1. Reagents and Materials Stainless steel grade 304 plates (2 mm thick) and grade 303 rods (50 mm diameter) were acquired from Dejond (Antwerp, Belgium). Milling and chamfer tools were obtained from DIXI Polytool (Le Locle, Switzerland), with a detailed tool list in Table S1 of the Supplementary Information. Acetone was obtained from Acros Organics (Geel, Belgium). PVC plastic films of 180 and 300 μm thickness were bought from Delbo (Maldegem, Belgium). Double-sided pressure-sensitive adhesive (PSA) tapes 200 MP types 7956 MP (153 μm thick) and 7945 MP (127 μm thick) and transfer tape type 467 MP (58 μm thick) were acquired from 3M (Maplewood, MN, USA). Sigma-Aldrich (Overijse, Belgium) delivered Whatman quantitative filter paper grades 40, 43, and 598. Aquapel hydrophobic agent was obtained from Aquapel (Butler County, PA,USA). Aqueous dye was obtained from Darwin Microfluidics (Paris, France). Agarose powder and glycerol bidistilled $99.5\%$ were obtained from, respectively, Melford (Ipswich, UK) and VWR (Leuven, Belgium). ## 2.2. Hollow Microneedle Fabrication Process HMNAs were fabricated in a two-step approach, which is schematically shown in Figure 1. First, stainless steel was selected for its [1] mechanical advantage to penetrate skin without buckling or breaking high-AR HMNs, [2] hardness and machinability to obtain sharp and durable tips, [3] availability in medical and hemocompatible grades, and [4] resistance to corrosion keeping the material sterile. On top of these advantages, grade 303 was selected because of its machinability. Then, a batch of workpieces was prepared by cutting the stainless steel rod into 5 mm thick discs by wire-EDM (AgieCharmilles CUT E 600, GF Machining Solutions, Biel, Switzerland) and milling pockets with a resulting thickness of 2 mm (Figure 1a) with a micro-milling center (MMP, Kern Microtechnik, Eschenlohe, Germany). Next, the workpiece with a pocket was manually aligned upside down on the XY-stage of a JK 2000 laser processing system (Lumonics, Rugby, UK) with Nd:YAG medium, operated with a repetition rate of 50 Hz. Percussion laser drilling (Figure 1b), i.e., repeated laser pulses with a pulse duration τ (0.7–1.5 ms), was exploited to create microholes serving as HMN lumens. Combinations of (low) laser energies (1.0 and 1.3 J) and laser pulse durations (0.7–1.5 ms) were screened by measuring the resulting lumen equivalent diameter (ED) and circularity (C) at both the laser entry and exit side by brightfield (BF) microscopy (see Section 2.3). An O2 gas flow of 6 bar was used to improve material combustion upon laser-induced heating. Before removing the workpiece from the laser cutter, a reference feature was cut (Figure 1c) to align the workpiece based on the precise location of the lumens with a stereomicroscope (Keyence VHX-500F, Osaka, Japan). The workpiece was then clamped on the micro-milling center, where the needle bevels were cut by an engraving tool (Figure 1d). The bevels were finished first, as longer needle shafts (i.e., with larger length/diameter ratio) result in unstable machining. Afterward, the shafts were finished to achieve final tolerances using an end mill cutter (Figure 1e–f). The outer shape of the HMNAs around the laser-drilled micro-lumen was designed to yield a length of 1700 μm, an outer diameter of 450 μm and a sharp tip angle of 25°. Because of the geometric limitations of the engraving tool, an inter-needle distance of 650 μm was chosen. ## 2.3. Microscopic and Tomographic Inspections BF microscopic images were obtained for both sides of the lumen, using an Eclipse Ti-e microscope (Nikon, Tokio, Japan), a pT-100-WHT LED source (CoolLED, Andover, MA, USA), and a Nikon Plan 10× objective. Matlab (MathWorks, Natick, MA, USA) was used to analyze the binarized images to obtain the equivalent diameter (ED) 4A/π and circularity (C) 4Aπ/P2 for each lumen at both sides, with A the area and P the perimeter. X-ray micro-computed tomography (μCT) was performed at the KU Leuven XCT Core Facility. Laser-drilled blocks of stainless steel were imaged in a Phoenix Nanotom S (General Electric Research, New York, NY, USA) with a diamond-tungsten target. The source voltage and current were 120 kV and 77 μA, respectively, and the achieved voxel size was 2.2 μm. Furthermore, an aluminum filter of 300 μm was used. This setup was used to acquire 1500 radiographic projections over a 360° angle, using 3 frame averaging. NRecon software (Bruker microCT, Kontich, Belgium) was used for reconstructing the scanned volume and subdividing it into slices. Next, the slices were imported into Matlab for binarization and de-speckling by removing all clusters below 100 pixels. Subsequently, the feature was rotated using the air–metal interface to align the lumen perpendicularly so that the ED and taper angle (to quantify the conical shape of the obtained lumen) could be characterized by function of the depth. The entire HMNAs were Imaged on a TESCAN UniTOM XL μCT-system (TESCAN XRE, Ghent, Belgium) with a reflection tungsten target. The source voltage and current were 180 kV and 88 μA, respectively, and the achieved voxel size was 4.0 μm. Again, an aluminum filter, here 1 mm thick, was used. A total of 3500 projections were acquired over a 360° angle with an exposure time of 360 ms and two projection averaging. The sample was scanned under a manually set inclination angle to reduce streak artifacts. Volume reconstruction was performed using the TESCAN reconstruction software Acquila (TESCAN XRE, Ghent, Belgium), and image processing, volume rendering, and manual alignment with the principal axes were executed in Avizo 2020.R1 (Visual Sciences Group, Bordeaux, France). The image processing consisted of a median filter with 3 subsequent iterations to reduce the image noise and a thresholding operation to segment the solid phase. The binarized volume was then visualized in 3D using the Volume Rendering function present in Avizo. ## 2.4. Microfluidic Chip Fabrication The low-cost, rapid prototyping method by Yuen et al. was adopted for the fabrication of microfluidic devices [37]. Chips used for the HMNA flow characterization (Section 3.2) were prepared by cutting microfluidic channels in PSA tape using a Speedy 300 CO2 laser cutter (Trotec, Boldon Colliery, UK) and laminated between two PVC layers (180 μm) containing the liquid in- and outlets. The latter features were previously cut out by a Maxx Air 24″ digital craft cutter (KNK, Orlando, FL, USA). Devices used for the characterization of SIMPLE [38,39,40,41] pressure generation (Section 3.3) were equipped with a hydrophilic stop valve (HSV), hydrophobic barriers (HB), and a filter paper pump (Whatman grade 40) before laminating with the PVC layers (300 μm thick). All paper was cut with a Silhouette Cameo craft cutter (Silhouette, UT, USA). HBs were prepared by cutting 1.5 × 3 mm2 rectangular Whatman grade 43 filter paper pieces and by impregnating the filter paper with Aquapel, as previously reported [42]. The HSV consisted of untreated Whatman grade 43 filter paper pieces (same size as HB). Finally, the sampling patches with integrated HMNA (Section 3.4) were fabricated using transfer tape reinforcement on the paper pump tip. The connection of the finger-press activation spot to the sample liquid channel was provided through an HB so that upon activation, no air could be displaced in the direction of the inlet, and thus the skin, while working liquid displacement toward the filter paper pump would be more effective. PVC layers of 180 μm thick were used and the bottom PVC layer was provided with a 2 mm inlet hole to connect with the HMNA. The latter was attached with a PSA 7945 MP connection ring with inner dimensions of 6 × 6 mm2. ## 2.5. Flow Characterization of the HMNAs Flow characterization of the HMNAs was performed using a LineUp push/pull pressure controller (Fluigent, Paris, France) combined with a flow sensor (Model Medium, Fluigent, Paris, France) to achieve a steady water flow rate while monitoring the required pressure in real-time at 0.1 Hz. A high flow rate of 50 μL/min was pushed through each individual needle lumen. Pushing was chosen over pulling for convenience and to avoid any air between the HMN and the pressure pump system in between different repetitions. This was completed by attaching the fabricated HMNAs to a chip with a single, straight fluidic channel having a width of 1.5 mm and outlet hole diameter of 2 mm and by using a PSA connector piece with a hole < 0.5 mm. Additionally, for each measurement, the attached HMNA was immersed in water to avoid any effect at the water/air interface of droplet formation. Baseline pressures were obtained by repeating for each lumen the same measurement without the needle attached, resulting in pressure drops solely caused by the flow through the HMN lumens. Between experimental repetitions, the HMNAs were cleaned in a Branson 1510 Ultrasonic Cleaner (Branson Ultrasonics, Brookfield, CT, USA) in acetone for 20 min to remove any possible debris. More details on the setup can be found in Section S2 of the Supplementary Information. ## 2.6. SIMPLE Pressure Generation Measurements of the pressure generated by the SIMPLE were based on Boyle’s law, which describes the relationship between the pressure (P) and volume (V) of an ideal gas given a constant temperature as PV = k, with k a certain constant. Therefore, a pre-defined air volume enclosed in an air chamber on-chip was expanded by the SIMPLE. Figure 2 depicts the chip design used. A Harvard PHD 2000 syringe pump (Harvard Apparatus, Holliston, MA, USA) was operated to push the activation liquid ($\frac{1}{50}$ diluted green aqueous dye in distilled water) further toward the HSV at a flow rate of 35 μL/min, leading to the activation of the pump by pushing the working liquid into the filter paper tip. As soon as the HSV was saturated, the syringe pump remained connected after stopping the flow rate. During the wicking of the working liquid ($\frac{1}{50}$ diluted blue aqueous dye in distilled water) by the porous material of the SIMPLE, which created negative pressure in the air chamber, the activation liquid was prevented to leak from the HSV to the air plug chamber by means of the HB-2. The generated pressure was indirectly obtained by measuring the decrease in volume of the working liquid in its chamber. Hereto, the chip operation was recorded by a C920 digital webcam (Logitech, Lausanne, Switzerland) for subsequent analysis using an in-house developed software. The pressure Pfin [Pa] was calculated as:[1]Pfin=Patm·VinVfin−Patm with Patm equal to 101.33 kPa (the atmospheric pressure), Vin (L) the initial air plug volume and Vfin 9 L) the expanded air plug volume. To avoid deflection of the chamber upon pressure reduction, which would lead to an overestimation of the generated pressures, PVC layers 300 μm thick were used. For more details on this setup, the reader is referred to Section S3 of the Supplementary Information. ## 2.7. Validation of a Self-Powered Biofluid Sampling Patch with In Vitro Models To assess the fluidic performance of the self-powered biofluid sampling patch, three samples were prepared: (i) colored distilled water ($\frac{1}{10}$ aqueous red dye); (ii) blood mimicking fluid ($53.8\%$ v/v) glycerol diluted in colored distilled water ($\frac{1}{10}$ aqueous red dye); (iii) agarose gel ($2.65\%$ w/v), prepared by dissolving agarose powder in colored distilled water ($\frac{1}{100}$ aqueous red dye) on a hotplate (130 °C) under constant stirring with a magnetic stirring bar. When solidified at room temperature, the agarose gel was placed to saturate into a container filled with red-colored distilled water ($\frac{1}{10}$ aqueous red dye). Before each experiment, its surface was dipped dry with a paper cloth and further dried to air to avoid liquid uptake from the surface. The sampling patch was then gently placed on top of the agarose gel and pushed down perpendicularly to assure insertion of the HMNA shafts without rupturing the hydrogel by horizontal movement. ## 3.1. HMNA Fabrication The first aim of this work was to fabricate HMNAs with a suitable length to reach the skin’s blood capillaries. Hereto, we chose top-down micromachining of stainless steel. The mechanical advantage of this alloy for skin puncture makes it, consequently, a challenging material with respect to machinability. To create microlumens with a depth of up to 2 mm and an ED between 100–200 μm and to keep the final HMN design sufficiently thin while avoiding too large pressure drops, percussion laser drilling was investigated. Despite the fact that femtosecond lasers are the go-to approach for creating small features, they are not suited for creating high-AR microlumens with this depth due to the typically large taper angles caused by the plasma shielding effect [43]. Therefore, a high-power millisecond laser was exploited aiming to reach the targeted microlumen dimensions with a low amount of taper (<1°) and high C (>0.9). The overview of the screening results in terms of ED and C is given in Figure S4 of the Supplementary Information. As expected, to drill completely through the stainless steel substrate with a success rate of $100\%$, shorter pulses (0.9 ms) were only needed in case of a higher laser output energy (1.3 J). However, this also resulted in a larger ED, lower C, and overall larger variability. This can be explained by the larger heat-affected zone by a single laser pulse removing more material at once, which can be expected to be less controllable [44]. Hence, only the results for the lowest energy at which the laser setup could be set, 1.0 J, met the requirements, as shown in Figure 3. Figure 3a shows that reducing the output energy to 1.0 J yielded lumens well within the set requirements. Furthermore, Figure 3b demonstrates that for a pulse duration of 1.3 ms, the variability of C is clearly higher compared to larger width. This can be explained by the $8\%$ of the repetitions that failed to completely drill through the material. A pulse duration ≥ 1.4 ms yielded a $100\%$ success rate and lower variability. However, as no significantly different results were obtained between a pulse duration of 1.4 and 1.5 ms, we chose to continue the microlumen fabrication with 1.4 ms in combination with a laser output of 1.0 J. Even though the targeted microlumens were obtained, the significantly higher ED ($p \leq 0.05$) for the laser entry versus exit sides suggested a significant amount of taper. To visualize this in detail, microlumens fabricated with the laser settings combination 1.0 J and 1.4 ms were scanned by μCT. The cross-section in Figure 3c shows that, in fact, nearly straight microlumens were achieved with the diameter only considerably increasing at the laser entry side. Based on this, it was decided to laser drill the lumens from the backside of the workpiece to let the wider laser entry side coincide with the HMNA base plate instead of the tip. For the next fabrication step, the workpiece was aligned on the micro-milling center based on the reference cut to produce 5 × 5 HMNAs according to the procedure described in Section 2.2. The needles were characterized by μCT scanning with an achieved voxel size of 4.0 μm3 to inspect the entire HMNAs externally as well as internally. A reconstructed 3D image of a machined HMNA obtained by μCT is shown in Figure 4, demonstrating that none of the 25 HMNs have major artifacts such as broken tips or irregular shapes. Figure 4c portrays the cross-section through one row of the HMNA, showing that the lumens are open after machining, although, a few of the lumens show some irregularities. Their possible impact on the flow through the HMNs is discussed in Section 3.2 (see also Supplementary Information Section S6). Furthermore, the distal tip size was found to be comparable to the image voxel size, indicating sharp tips. Finally, the out-of-plane height and outer diameter were 1647 ± 12 μm and 451 ± 9 μm, respectively. Nevertheless, as a result of the limited scanning resolution, being 7 μm, it should be noted that these measurements are only giving an indication that the aimed requirements for blood sampling are met, without offering a precise characterization. ## 3.2. Flow Characterization of the HMNAs To assess the machining variability, the pressure drops over the individual needles were analyzed for three different arrays, with three technical repetitions each. A high flow rate (50 μL/min) was applied, based on the maximal flow rates found in the literature for microneedle-based blood sampling [34,45]. Figure 5 depicts the spatial distribution of the average pressure drops per HMN (bar charts with error bars can be found in Figure S5 of the Supplementary Information). The liquid was flowing through all of the HMN lumens and overall, $87\%$ of the measured pressure drops were below 10 kPa and $36\%$ below 1 kPa. Despite the overall satisfying results, some pressure drops were clearly deviating as highlighted in blue for pressure drops > 10 kPa. This variability can be attributed to the variability in the lumen diameter, the presence of burrs or debris, and surface roughness as a result of the microfabrication process. μCT visualizes this partly (see cross-sections with some large burrs in Figure 5 [46]) as it is limited to structures larger than the scanning resolution of 7 μm. In this regard, it is important to stress that there is a strong fourth-order effect from the lumen diameter on the measured pressure drops, according to the Hagen–Poisseuille equation:[2]ΔP=128μLQπD4 with ∆P (Pa) the pressure drop, μ (Pa·s) the dynamic viscosity, L (m) the length of the lumen, Q (m3/s) the flow rate and D (m) the diameter of the lumen. However, it must be noted that Equation [2] assumes smooth and straight channels and can therefore only be used as a mathematical theoretical background and a rough approximation for discussing the flow through the individual microlumens. To statistically assess the machining variability, the pressure drops for the three arrays were compared by the non-parametric Kruskal–Wallis test. With a p-value of 0.093, significant differences between the three HMNAs could not be shown. After removing the statistical outliers, the p-value further increased to 0.145. For details on the statistics is referred to Tables S2 and S3 of the Supplementary Information. ## 3.3. Characterization of SIMPLE Pressure Generation The microfabricated and characterized HMNAs were then integrated with the SIMPLE microfluidic platform capable of pulling liquids in a self-powered and controlled way [47,48], as a proof-of-concept of a self-powered microsampling patch. An important parameter for cutaneous biofluid extraction from the skin is the pressure difference the system can overcome. The SIMPLE chip design and fabrication were optimized to achieve a maximum generated pressure difference. Figure 6 depicts the pressure difference generated by four chips equipped with filter paper pumps (Whatman 40 quantitative filter paper) shaped as circular sectors of 60°, fabricated as described in Section 2.4. It was shown that the lack of a tight sealing between the filter paper and the surrounding plastics allowed air backflow, leading to the termination of the pumping (see Section S7 of the Supplementary Information). This issue was solved by laminating transfer tape on both sides of the porous paper tip to seal the filter paper pump with the top and bottom PVC layers (see inset of Figure 6). As a result, after one hour, the generated pressure differences by the chips with filter paper pumps reached values of 40.9 ± 1.8 kPa (Figure 6), which is more than sufficient for biofluid extraction from the skin. For comparison, mosquitoes generate pressures up to 7 kPa for capillary blood extraction through their 20 μm diameter fascicle [49,50]. ## 3.4. Validation of Self-Powered Biofluid Microsampling Patch with In Vitro Models Finally, a self-powered microsampling patch was assembled by integrating an HMNA with an SIMPLE chip using a PSA connection. The patch has the size of a regular credit card (86 × 54 mm2, design shown in Figure 7a), an ideal feature for self-sampling applications. The chip can be easily activated by a finger press on the activation spot (Figure 7b) to bring the working liquid (blue) into contact with the filter paper pump, which starts creating a pressure difference to withdraw the sample. Validation of its operational performance was completed for three different in vitro model systems. First, red colored distilled water was drawn from an open liquid container by immersing the HMN tips into the liquid. Next, tests were run with a glycerol-based blood mimicking fluid (Figure 7c) with a viscosity of about 4 cP [51]. Although whole blood is a non-Newtonian fluid, the relatively large lumen and microfluidic channel dimensions are not expected to cause a substantially large Fåhræus–Lindqvist effect, which describes the decreasing apparent viscosity for blood flow through microchannels [52]. However, the surface roughness after laser drilling might result in a further decreasing apparent viscosity, making a Newtonian blood mimicking fluid a worst-case scenario [53]. In a third model setup, the extraction of fluid from the human skin was mimicked by inserting the HMNAs in a $2.65\%$ (w/v) agarose gel saturated with colored liquids according to [54] (Figure 7d). Volumes up to 40 μL were successfully sampled with a success rate of $100\%$. No significant difference in the flow rates was measured for sampling water and blood equivalent (see Supplementary Information Section S8). The average flow rate was reduced, and the variability increased when sampling from skin equivalent. This is expected to be caused by manual HMN insertion or differences in HMNs effectively sampling due to the path of least resistance, e.g., by clogging of the needle lumens with agarose. These results demonstrate that the combination of HMNA and SIMPLE delivers a small and flexible microsampling patch with a large sampling volume capacity. ## 4. Conclusions This study demonstrated the two-step fabrication and characterization of stainless steel HMNAs and their integration in a self-powered sampling patch toward a decentralized collection of capillary blood. First, percussion laser drilling by pulsed laser drilling on a single spot was explored for different laser settings. Pulses of 1.4 s in combination with a laser output energy of 1.0 J resulted in nearly straight microlumens with ED well within the required range of 100–200 μm and C higher than 0.9. Therefore, these settings were chosen for the subsequent micro-milling of 5 × 5 HMNAs. The μCT scans of full HMNAs showed a good agreement with the designed dimensions. The measured height (base-to-tip) and the outer diameters were on average 1647.1 ± 12.3 μm and 451.1 ± 8.5μm, respectively. Furthermore, all tips appeared to be sharp without artifacts. Flows through each individual lumen were characterized to assess the sampling capacity of each needle in the HMNAs. In particular, for a flow rate as high as 50 μL/min, the average pressure drops were below 10 kPa in $87\%$ of the HMNs. These results show that the proposed two-step protocol is able to produce stainless steel HMNAs with out-of-plane shafts taller than 1500 μm and sharp tips necessary to reach skin capillaries for blood sampling. Next, the HMNAs were integrated with an SIMPLE microfluidic platform as a proof-of-concept of a self-powered sampling patch. Hereto, it was shown that SIMPLE is able to overcome negative pressure differences up to 40.9 ± 1.8 kPa. Finally, sampling patches with an integrated HMNA were validated by sampling up to 40 μL using three in vitro models: water, a blood-mimicking glycerol solution, and a skin-mimicking agarose gel. This study showed by a proof-of-concept that a flexible sampling patch with large capacity can be obtained by integrating an HMNA with an SIMPLE pumping unit. A unique advantage of the SIMPLE technology is that it allows for further manipulation of the withdrawn sample in a downstream microfluidic network, e.g., precise metering, loading of dried blood spots, or a myriad of diagnostic applications completely on-chip [41,48,55]. Furthermore, the fabrication of tall HMNs in stainless steel has been proven to be possible and improvements to minimize the production anomalies resulting from machining this challenging material have been suggested by the authors. Finally, the possibility to make this chip flexible is interesting for interacting with highly variable curvature of different bodies and body parts in a “wearables” format during sample acquisition. 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