Effects of Yulin Tong Bu formula on modulating gut microbiota and fecal metabolite interactions in mice with polycystic ovary syndrome

Exploring the multifaceted therapeutic mechanism of Schisanlactone E (XTS) in APP/PS1 mouse model of Alzheimer's disease through multi-omics analysis

Background

Schisanlactone E, also known as XueTongSu (XTS), is an active compound extracted from the traditional Tujia medicine Kadsura heteroclita ("XueTong"). Recent studies highlight its anti-inflammatory and antioxidant properties, yet the mechanisms of XTS's therapeutic effects on Alzheimer's disease (AD) are unclear. This study aims to elucidate the therapeutic efficacy and mechanisms of XTS in AD.

Methods

Ten C57BL/6 mice were assigned to the control group (NC), and twenty APP/PS1 transgenic mice were randomly divided into the model group (M) (10 mice) and the XTS treatment group (Tre) (10 mice). After an acclimatization period of 7 days, intraperitoneal injections were administered over a 60-day treatment period. The NC and M groups received saline, while the Tre group received XTS at 2 mg/kg. Learning and memory abilities were assessed using the Morris Water Maze (MWM) test. Histopathological changes were evaluated using hematoxylin and eosin (HE) and Nissl staining, and immunofluorescence was used to assess pathological products and glial cell activation. Cytokine levels (IL-1β, IL-6, TNF-α) in the hippocampus were quantified by qPCR. 16S rDNA sequencing analyzed gut microbiota metabolic alterations, and metabolomic analysis was performed on cortical samples. The KEGG database was used to analyze the regulatory mechanisms of XTS in AD treatment.

Results

XTS significantly improved learning and spatial memory in APP/PS1 mice and ameliorated histopathological changes, reducing Aβ plaque aggregation and glial cell activation. XTS decreased the expression of inflammatory cytokines IL-1β, IL-6, and TNF-α. It also enhanced gut microbiota diversity, notably increasing Akkermansia species, and modulated levels of metabolites such as isosakuranetin, 5-KETE, 4-methylcatechol, and sphinganine. Pathway analysis indicated that XTS regulated carbohydrate metabolism, neuroactive ligand-receptor interactions, and alanine, aspartate, and glutamate metabolism, mitigating gut microbiota dysbiosis and metabolic disturbances.

Conclusion

XTS ameliorates cognitive deficits, pathological changes, and inflammatory responses in APP/PS1 mice. It significantly modulates the gut microbiota, particularly increasing Akkermansia abundance, and influences levels of key metabolites in both the gut and brain. These findings suggest that XTS exerts anti-AD effects through the microbial-gut-brain axis (MGBA).

Study and evaluation of a gelatin- silver oxide nanoparticles releasing nitric oxide production of wound healing dressing for diabetic ulcer

This study aimed to develop a novel Gelatin silver oxide material for releasing nitric oxide bionanocomposite wound dressing with enhanced mechanical, chemical, and antibacterial properties for the treatment of diabetic wounds. The gelatin- silver oxide nanoparticles (Ag2O-NP) bio nanocomposite was prepared using chitosan and gelatin polymers incorporated with silver oxide nanoparticles through the freeze-drying method. The samples were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. Results showed that the Ag2O-NP nanoparticles increased porosity, decreased pore size, and improved elastic modulus. The Ag2O-NP wound dressing exhibited the most effective antibacterial properties against Staphylococcus aureus and Escherichia coli. Among the samples, the wound dressing containing silver oxide nanoparticles demonstrated superior physical and mechanical properties, with 48% porosity, a tensile strength of 3.2 MPa, and an elastic modulus of 51.7 MPa. The fabricated wound dressings had a volume ratio of empty space to total volume ranging from 40% to 60%. In parallel, considering the complications of diabetes and its impact on the vascular system, another aspect of the research focused on developing a per2mediated wound dressing capable of releasing nitric oxide gas to regenerate damaged vessels and accelerate diabetic wound healing. Chitosan, a biocompatible and biodegradable polymer, was selected as the substrate for the wound dressing, and beta-glycerophosphate (GPβ), tripolyphosphate (TPP), and per2mediated alginate (AL) were used as crosslinkers. The chitosan-alginate (CS-AL) wound dressing exhibited optimal characteristics in terms of hole count and uniformity in the scanning electron microscope test. It also demonstrated superior water absorption (3854%) and minimal air permeability. Furthermore, the CS-AL sample exhibited an 80% degradation rate after 14 days, indicating its suitability as a wound dressing. The wound dressing was loaded with S-nitrosoglutathione (GSNO) powder, and the successful release of nitric oxide gas was confirmed through the grease test, showing a peak at a wavelength of 540 nm. Subsequent investigations revealed that the treatment of human umbilical vein endothelial cells (HUVECs) with high glucose led to a decrease in the expression of PER2 and SIRT1, while the expression of PER2 increased, which may subsequently enhance the expression of SIRT1 and promote cell proliferation activity. However, upon treatment of the cells with the modified materials, an increase in the expression of PER2 and SIRT1 was observed, resulting in a partial restoration of cell proliferative activity. This comprehensive study successfully developed per2-mediated bio-nanocomposite wound dressings with improved physical, mechanical, chemical, and antibacterial properties. The incorporation of silver oxide nanoparticles enhanced the antimicrobial activity, while the released nitric oxide gas from the dressing demonstrated the ability to mitigate vascular endothelial cell damage induced by high glucose levels. These advancements show promising potential for facilitating the healing process of diabetic wounds by addressing complications associated with diabetes and enhancing overall wound healing.

The IL-12 family of heterodimeric cytokines in polycystic ovarian syndrome: biological role in induction, regulation, and treatment

Polycystic ovary syndrome (PCOS) is a diverse endocrine disorder widely recognized as the prevailing metabolic condition among women in their reproductive years. The precise pathophysiological mechanisms underlying PCOS remain incompletely understood. However, existing evidence suggests that the development of PCOS may be linked to factors such as abdominal obesity, hyperandrogenism, and insulin resistance (IR). Excessive central adiposity in women with PCOS may lead to the development of a chronic, low-grade inflammation characterized by the activation of proinflammatory cytokines. The cytokines that belong to the IL-12 family are a collection of distinct heterodimeric cytokines that include IL-12, IL-23, IL-27, and IL-35. Recent research has provided further evidence regarding the significance of IL-12 cytokines in influencing both innate and adaptive immune responses in different diseases. Additionally, these studies have discovered diverse roles for certain members of the IL-12 family, encompassing multiple immunological functions that can either act as effectors or regulators. In this discourse, we examine the distinctive and atypical structural and functional attributes of this particular cytokine family. This study aims to offer a comprehensive overview of the pathophysiological significance of the IL-12 family cytokines in PCOS patients. Additionally, the therapeutic potential of the cytokines as novel approaches for PCOS treatment will be proposed.

The Novel Insight of Gut Microbiota from Mouse Model to Clinical Patients and the Role of NF-κB Pathway in Polycystic Ovary Syndrome

Polycystic Ovary Syndrome (PCOS) is a metabolic disorder characterized by hyperandrogenism and related symptoms in women of reproductive age. Emerging evidence suggests that chronic low-grade inflammation plays a significant role in the development of PCOS. The gut microbiota, a complex bacterial ecosystem, has been extensively studied for various diseases, including PCOS, while the underlying mechanisms are not fully understood. This review comprehensively summarizes the changes in gut microbiota and metabolites observed in PCOS and their potential association with the condition. Additionally, we discuss the role of abnormal nuclear factor κB signaling in the pathogenesis of PCOS. These findings offer valuable insights into the mechanisms of PCOS and may pave the way for the development of control and therapeutic strategies for this condition in clinical practice. By bridging the gap between mouse models and clinical patients, this review contributes to a better understanding of the interplay between gut microbiota and inflammation in PCOS, thus paving new ways for future investigations and interventions.

Effects of Glucagon-Like Peptide-1 Receptor Agonists on Gut Microbiota in Dehydroepiandrosterone-Induced Polycystic Ovary Syndrome Mice: Compared Evaluation of Liraglutide and Semaglutide Intervention

Purpose

Polycystic ovary syndrome (PCOS) is a frequent cause of infertility in reproductive-age women. Our work aims to evaluate the effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) on gut microbiota, with metabolic parameters including body weight and the hormone profile in PCOS.

Patients and Methods

Dehydroepiandrosterone (DHEA)-induced PCOS mice were established and then treated with two GLP-1RAs: liraglutide and novel form semaglutide for four weeks. Changes in body weight and metabolic parameters were measured. Fecal samples were collected and analyzed using metagenomic sequencing.

Results

Liraglutide and semaglutide modulated both alpha and beta diversity of the gut microbiota in PCOS. Liraglutide increased the Bacillota-to-Bacteroidota ratio through up-regulating the abundance of butyrate-producing members of Bacillota like Lachnospiraceae. Moreover, liraglutide showed the ability to reverse the altered microbial composition and the disrupted microbiota functions caused by PCOS. Semaglutide increased the abundance of Helicobacter in PCOS mice (p < 0.01) which was the only bacteria found negatively correlated with body weight. Moreover, pathways involving porphyrin and flavonoids were increased after semaglutide intervention.

Conclusion

Liraglutide and semaglutide improved reproductive and metabolic disorders by modulating the whole structure of gut microbiota in PCOS. The greater efficacy in weight loss compared with liraglutide observed after semaglutide intervention was positively related with Helicobacter. The study may provide new ideas in the treatment and the underlying mechanisms of GLP-1RAs to improve PCOS.

Mood and microbes: a comprehensive review of intestinal microbiota's impact on depression

Depression is considered a multifaceted and intricate mental disorder of growing concern due to its significant impact on global health issues. The human gut microbiota, also known as the "second brain," has an important role in the CNS by regulating it through chemical, immunological, hormonal, and neurological processes. Various studies have found a significant bidirectional link between the brain and the gut, emphasizing the onset of depression therapies. The biological and molecular processes underlying depression and microbiota are required, as the bidirectional association may represent a novel study. However, profound insights into the stratification and diversity of the gut microbiota are still uncommon. This article investigates the emerging evidence of a bacterial relationship between the gut and the brain's neurological system and its potential pathogenicity and relevance. The interplay of microbiota, immune system, nervous system neurotransmitter synthesis, and neuroplasticity transitions is also widely studied. The consequences of stress, dietary fibers, probiotics, prebiotics, and antibiotics on the GB axis are being studied. Multiple studies revealed the processes underlying this axis and led to the development of effective microbiota-based drugs for both prevention and treatment. Therefore, the results support the hypothesis that gut microbiota influences depression and provide a promising area of research for an improved knowledge of the etiology of the disease and future therapies.

Phlorizin, an Important Glucoside: Research Progress on Its Biological Activity and Mechanism

Phlorizin, as a flavonoid from a wide range of sources, is gradually becoming known for its biological activity. Phlorizin can exert antioxidant effects by regulating the IL-1β/IKB-α/NF-KB signaling pathway. At the same time, it exerts its antibacterial activity by reducing intracellular DNA agglutination, reducing intracellular protein and energy synthesis, and destroying intracellular metabolism. In addition, phlorizin also has various pharmacological effects such as antiviral, antidiabetic, antitumor, and hepatoprotective effects. Based on domestic and foreign research reports, this article reviews the plant sources, extraction, and biological activities of phlorizin, providing a reference for improving the clinical application of phlorizin.

Hyperinsulinemia impairs decidualization via AKT-NR4A1 signaling: new insight into polycystic ovary syndrome (PCOS)-related infertility

BACKGROUND

Investigating the underlying molecular mechanisms responsible for endometrial dysfunction in women with PCOS is essential, particularly focusing on the role of hyperinsulinemia.

METHODS

We explored the role of insulin in the decidualization process using a synthetic decidualization assay. To dissect the effects of PI3K/AKT-NR4A signaling, we employed small interfering RNAs (siRNAs) targeting the NR4A genes and inhibitors of the PI3K/AKT pathway. We also investigated the disruption of AKT-NR4A1 signaling in the endometrium of PCOS female rats induced with dehydroepiandrosterone (DHEA). Quantitative real-time PCR (qRT-PCR) and Western blot (WB) analyses were utilized to evaluate gene expression regulation.

RESULTS

Insulin was found to suppress the expression of decidualization markers in human endometrial stromal cells (hESC) in a dose-dependent manner, concurrently triggering an inappropriate activation of the PI3K/AKT pathway. Members of the NR4A family, as downstream effectors in the PI3K/AKT pathway, were implicated in the insulin-induced disruptions during the decidualization process. Moreover, the endometrium of PCOS models showed significantly elevated levels of phosphorylated (Ser473) AKT, with a corresponding reduction in Nr4a1 protein.

CONCLUSIONS

Our research demonstrates that insulin negatively regulates decidualization in hESC via the PI3K/AKT-NR4A pathway. In vivo analysis revealed a significant dysregulation of the AKT-NR4A1 pathway in the endometrium of PCOS rats. These findings offer novel insights into the pathogenesis of infertility and endometrial disorders associated with hyperinsulinemia in PCOS.

Modern Subtype Classification and Outlier Detection Using the Attention Embedder to Transform Ovarian Cancer Diagnosis

Ovarian cancer, a deadly female reproductive system disease, is a significant challenge in medical research due to its notorious lethality. Addressing ovarian cancer in the current medical landscape has become more complex than ever. This research explores the complex field of Ovarian Cancer Subtype Classification and the crucial task of Outlier Detection, driven by a progressive automated system, as the need to fight this unforgiving illness becomes critical. This study primarily uses a unique dataset painstakingly selected from 20 esteemed medical institutes. The dataset includes a wide range of images, such as tissue microarray (TMA) images at 40× magnification and whole-slide images (WSI) at 20× magnification. The research is fully committed to identifying abnormalities within this complex environment, going beyond the classification of subtypes of ovarian cancer. We proposed a new Attention Embedder, a state-of-the-art model with effective results in ovarian cancer subtype classification and outlier detection. Using images magnified WSI, the model demonstrated an astonishing 96.42% training accuracy and 95.10% validation accuracy. Similarly, with images magnified via a TMA, the model performed well, obtaining a validation accuracy of 94.90% and a training accuracy of 93.45%. Our fine-tuned hyperparameter testing resulted in exceptional performance on independent images. At 20× magnification, we achieved an accuracy of 93.56%. Even at 40× magnification, our testing accuracy remained high, at 91.37%. This study highlights how machine learning can revolutionize the medical field's ability to classify ovarian cancer subtypes and identify outliers, giving doctors a valuable tool to lessen the severe effects of the disease. Adopting this novel method is likely to improve the practice of medicine and give people living with ovarian cancer worldwide hope.

Danggui Shaoyao San: comprehensive modulation of the microbiota-gut-brain axis for attenuating Alzheimer's disease-related pathology

Background: Alzheimer's disease (AD), an age-associated neurodegenerative disorder, currently lacks effective clinical therapeutics. Traditional Chinese Medicine (TCM) holds promising potential in AD treatment, exemplified by Danggui Shaoyao San (DSS), a TCM formulation. The precise therapeutic mechanisms of DSS in AD remain to be fully elucidated. This study aims to uncover the therapeutic efficacy and underlying mechanisms of DSS in AD, employing an integrative approach encompassing gut microbiota and metabolomic analyses. Methods: Thirty Sprague-Dawley (SD) rats were allocated into three groups: Blank Control (Con), AD Model (M), and Danggui Shaoyao San (DSS). AD models were established via bilateral intracerebroventricular injections of streptozotocin (STZ). DSS was orally administered at 24 g·kg-1·d-1 (weight of raw herbal materials) for 14 days. Cognitive functions were evaluated using the Morris Water Maze (MWM) test. Pathological alterations were assessed through hematoxylin and eosin (HE) staining. Bloodstream metabolites were characterized, gut microbiota profiled through 16S rDNA sequencing, and cortical metabolomics analyzed. Hippocampal proinflammatory cytokines (IL-1β, IL-6, TNF-α) were quantified using RT-qPCR, and oxidative stress markers (SOD, CAT, GSH-PX, MDA) in brain tissues were measured with biochemical assays. Results: DSS identified a total of 1,625 bloodstream metabolites, predominantly Benzene derivatives, Carboxylic acids, and Fatty Acyls. DSS significantly improved learning and spatial memory in AD rats and ameliorated cerebral tissue pathology. The formulation enriched the probiotic Ligilactobacillus, modulating metabolites like Ophthalmic acid (OA), Phosphocreatine (PCr), Azacridone A, Inosine, and NAD. DSS regulated Purine and Nicotinate-nicotinamide metabolism, restoring balance in the Candidatus Saccharibacteria-OA interplay and stabilizing gut microbiota-metabolite homeostasis. Additionally, DSS reduced hippocampal IL-1β, IL-6, TNF-α expression, attenuating the inflammatory state. It elevated antioxidative enzymes (SOD, CAT, GSH-PX) while reducing MDA levels, indicating diminished oxidative stress in AD rat brains. Conclusion: DSS addresses AD pathology through multifaceted mechanisms, encompassing gut microbiome regulation, specific metabolite modulation, and the mitigation of inflammation and oxidative stress within the brain. This holistic intervention through the Microbial-Gut-Brain Axis (MGBA) underscores DSS's potential as an integrative therapeutic agent in combatting AD.

Improved Prediction of Ovarian Cancer Using Ensemble Classifier and Shaply Explainable AI

The importance of detecting and preventing ovarian cancer is of utmost significance for women's overall health and wellness. Referred to as the "silent killer," ovarian cancer exhibits inconspicuous symptoms during its initial phases, posing a challenge for timely identification. Identification of ovarian cancer during its advanced stages significantly diminishes the likelihood of effective treatment and survival. Regular screenings, such as pelvic exams, ultrasound, and blood tests for specific biomarkers, are essential tools for detecting the disease in its early, more treatable stages. This research makes use of the Soochow University ovarian cancer dataset, containing 50 features for the accurate detection of ovarian cancer. The proposed predictive model makes use of a stacked ensemble model, merging the strengths of bagging and boosting classifiers, and aims to enhance predictive accuracy and reliability. This combination harnesses the benefits of variance reduction and improved generalization, contributing to superior ovarian cancer prediction outcomes. The proposed model gives 96.87% accuracy, which is currently the highest model result obtained on this dataset so far using all features. Moreover, the outcomes are elucidated utilizing the explainable artificial intelligence method referred to as SHAPly. The excellence of the suggested model is demonstrated through a comparison of its performance with that of other cutting-edge models.

Intestinal flora study reveals the mechanism of Danggui Shaoyao San and its decomposed recipes to improve cognitive dysfunction in the rat model of Alzheimer's disease

Background

Alzheimer's disease (AD), characterized by a severe decline in cognitive function, significantly impacts patients' quality of life. Traditional Chinese Medicine (TCM) presents notable advantages in AD treatment, closely linked to its regulation of intestinal flora. Nevertheless, a comprehensive exploration of the precise role of intestinal flora in AD remains lacking.

Methods

We induced an AD model through bilateral intracerebroventricular injection of streptozotocin in rats. We divided 36 rats randomly into 6 groups: sham-operated, model, Danggui Shaoyao San (DSS), and 3 DSS decomposed recipes groups. Cognitive abilities were assessed using water maze and open field experiments. Nissl staining examined hippocampal neuron integrity. Western blot analysis determined synaptoprotein expression. Additionally, 16S rDNA high-throughput sequencing analyzed intestinal flora composition.

Results

DSS and its decomposed recipe groups demonstrated improved learning and memory in rats (P<0.01). The open field test indicated increased central zone residence time and locomotor activity distance in these groups (P<0.05). Furthermore, the DSS and decomposed recipe groups exhibited reduced hippocampal neuronal damage and increased expression levels of synapsin I (P<0.05) and PSD95 (P<0.01) proteins. Alpha and Beta diversity analyses showed that the intestinal flora species richness and diversity in the DSS and decomposed recipe groups were similar to those in the sham-operated group, signifying a significant restorative effect (P<0.05).

Conclusion

The combination of DSS and its decomposed recipes can reduce the abundance of harmful gut microbiota, leading to improvements in cognitive and learning abilities.

Integrated strategy facilitates rapid in-depth chemome characterization of traditional Chinese medicine prescriptions: Shengbai oral liquid as a case

Chemome characterization is the prerequisite for either therapeutic mechanism clarification or quality control of traditional Chinese medicine prescriptions (TCMPs). Liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) currently serves as the most popular analytical tool; however, chemome characterization is still challenged by MS/MS spectral acquisition and post-acquisition data processing. Here, an integrated strategy was proposed for in-depth chemome clarification of Shengbai oral liquid (SBOL). Gas phase ion fractionation with staggered mass ranges was demonstrated to be the superior acquisition method regarding MS2 spectrum coverage in this study, and narrower mass range further advanced coverage. To facilitate information extraction, all ingredient materials were measured in parallel to form an in-house library, where each MS1 -MS2 item generated a square mass-to-charge ratio (m/z) frame to capture the tagged identity and each chemical family produced a pentagon frame for mass defect features to accomplish chemical analogs-targeted quasi-molecular ion extraction. Square m/z frame imprinting captured 355 identities, while mass defect frames extracted 275 compounds. Attributing to comprehensive MS2 spectrum acquisition and efficient data processing, 355 components were captured and tentatively identified, resulting in a clarified chemical composition for SBOL. Therefore, the proposed strategy should be meaningful for the chemome characterization of TCMPs.

Glycyrrhizin ameliorates impaired glucose metabolism and ovarian dysfunction in a polycystic ovary syndrome mouse model

The aim of this study was to determine the impact of glycyrrhizin, an inhibitor of high mobility group box 1, on glucose metabolic disorders and ovarian dysfunction in mice with polycystic ovary syndrome. We generated a polycystic ovary syndrome mouse model by using dehydroepiandrosterone plus high-fat diet. Glycyrrhizin (100 mg/kg) was intraperitoneally injected into the polycystic ovary syndrome mice and the effects on body weight, glucose tolerance, insulin sensitivity, estrous cycle, hormone profiles, ovarian pathology, glucolipid metabolism, and some molecular mechanisms were investigated. Increased number of cystic follicles, hormonal disorders, impaired glucose tolerance, and decreased insulin sensitivity in the polycystic ovary syndrome mice were reverted by glycyrrhizin. The increased high mobility group box 1 levels in the serum and ovarian tissues of the polycystic ovary syndrome mice were also reduced by glycyrrhizin. Furthermore, increased expressions of toll-like receptor 9, myeloid differentiation factor 88, and nuclear factor kappa B as well as reduced expressions of insulin receptor, phosphorylated protein kinase B, and glucose transporter type 4 were restored by glycyrrhizin in the polycystic ovary syndrome mice. Glycyrrhizin could suppress the polycystic ovary syndrome-induced upregulation of high mobility group box 1, several inflammatory marker genes, and the toll-like receptor 9/myeloid differentiation factor 88/nuclear factor kappa B pathways, while inhibiting the insulin receptor/phosphorylated protein kinase B/glucose transporter type 4 pathways. Hence, glycyrrhizin is a promising therapeutic agent against polycystic ovary syndrome.

Identification of the hub genes in polycystic ovary syndrome based on disease-associated molecule network

Revealing the key genes involved in polycystic ovary syndrome (PCOS) and elucidating its pathogenic mechanism is of extreme importance for the development of targeted clinical therapy for PCOS. Investigating disease by integrating several associated and interacting molecules in biological systems will make it possible to discover new pathogenic genes. In this study, an integrative disease-associated molecule network, combining protein-protein interactions and protein-metabolites interactions (PPMI) network was constructed based on the PCOS-associated genes and metabolites systematically collected. This new PPMI strategy identified several potential PCOS-associated genes, which have unreported in previous publications. Moreover, the systematic analysis of five benchmarks data sets indicated the DERL1 was identified as downregulated in PCOS granulosa cell and has good classification performance between PCOS patients and healthy controls. CCR2 and DVL3 were upregulated in PCOS adipose tissues and have good classification performance. The expression of novel gene FXR2 identified in this study is significantly increased in ovarian granulosa cells of PCOS patients compared with controls via quantitative analysis. Our study uncovers substantial differences in the PCOS-specific tissue and provides a plethora of information on dysregulated genes and metabolites that are linked to PCOS. This knowledgebase could have the potential to benefit the scientific and clinical community. In sum, the identification of novel gene associated with PCOS provides valuable insights into the underlying molecular mechanisms of PCOS and could potentially lead to the development of new diagnostic and therapeutic strategies.