The role of machine learning in advancing diabetic foot: a review.

Background: Diabetic foot complications impose a significant strain on healthcare systems worldwide, acting as a principal cause of morbidity and mortality in individuals with diabetes mellitus. While traditional methods in diagnosing and treating these conditions have faced limitations, the emergence of Machine Learning (ML) technologies heralds a new era, offering the promise of revolutionizing diabetic foot care through enhanced precision and tailored treatment strategies. Objective: This review aims to explore the transformative impact of ML on managing diabetic foot complications, highlighting its potential to advance diagnostic accuracy and therapeutic approaches by leveraging developments in medical imaging, biomarker detection, and clinical biomechanics. Methods: A meticulous literature search was executed across PubMed, Scopus, and Google Scholar databases to identify pertinent articles published up to March 2024. The search strategy was carefully crafted, employing a combination of keywords such as "Machine Learning," "Diabetic Foot," "Diabetic Foot Ulcers," "Diabetic Foot Care," "Artificial Intelligence," and "Predictive Modeling." This review offers an in-depth analysis of the foundational principles and algorithms that constitute ML, placing a special emphasis on their relevance to the medical sciences, particularly within the specialized domain of diabetic foot pathology. Through the incorporation of illustrative case studies and schematic diagrams, the review endeavors to elucidate the intricate computational methodologies involved. Results: ML has proven to be invaluable in deriving critical insights from complex datasets, enhancing both the diagnostic precision and therapeutic planning for diabetic foot management. This review highlights the efficacy of ML in clinical decision-making, underscored by comparative analyses of ML algorithms in prognostic assessments and diagnostic applications within diabetic foot care. Conclusion: The review culminates in a prospective assessment of the trajectory of ML applications in the realm of diabetic foot care. We believe that despite challenges such as computational limitations and ethical considerations, ML remains at the forefront of revolutionizing treatment paradigms for the management of diabetic foot complications that are globally applicable and precision-oriented. This technological evolution heralds unprecedented possibilities for treatment and opportunities for enhancing patient care.

Advances in secondary prevention mechanisms of macrovascular complications in type 2 diabetes mellitus patients: a comprehensive review.

Type 2 diabetes mellitus (T2DM) poses a significant global health burden. This is particularly due to its macrovascular complications, such as coronary artery disease, peripheral vascular disease, and cerebrovascular disease, which have emerged as leading contributors to morbidity and mortality. This review comprehensively explores the pathophysiological mechanisms underlying these complications, protective strategies, and both existing and emerging secondary preventive measures. Furthermore, we delve into the applications of experimental models and methodologies in foundational research while also highlighting current research limitations and future directions. Specifically, we focus on the literature published post-2020 concerning the secondary prevention of macrovascular complications in patients with T2DM by conducting a targeted review of studies supported by robust evidence to offer a holistic perspective.

Mitochondrial regulation of diabetic endothelial dysfunction: Pathophysiological links.

Micro- and macrovascular complications frequently occur in patients with diabetes, with endothelial dysfunction playing a key role in the development and progression of the complications. For the early diagnosis and optimal treatment of vascular complications associated with diabetes, it is imperative to comprehend the cellular and molecular mechanisms governing the function of diabetic endothelial cells. Mitochondria function as crucial sensors of environmental and cellular stress regulating endothelial cell viability, structural integrity and function. Impaired mitochondrial quality control mechanisms and mitochondrial dysfunction are the main features of endothelial damage. Hence, targeted mitochondrial therapy is considered promising novel therapeutic options in vascular complications of diabetes. In this review, we focus on the mitochondrial functions in the vascular endothelial cells and the pathophysiological role of mitochondria in diabetic endothelial dysfunction, aiming to provide a reference for related drug development and clinical diagnosis and treatment.

Single-cell sequencing: A promising approach for uncovering the characteristic of pancreatic islet cells in type 2 diabetes.

Single-cell sequencing is a novel and rapidly advancing high-throughput technique that can be used to investigating genomics, transcriptomics, and epigenetics at a single-cell level. Currently, single-cell sequencing can not only be used to draw the pancreatic islet cells map and uncover the characteristics of cellular heterogeneity in type 2 diabetes, but can also be used to label and purify functional beta cells in pancreatic stem cells, improving stem cells and islet organoids therapies. In addition, this technology helps to analyze islet cell dedifferentiation and can be applied to the treatment of type 2 diabetes. In this review, we summarize the development and process of single-cell sequencing, describe the potential applications of single-cell sequencing in the field of type 2 diabetes, and discuss the prospects and limitations of single-cell sequencing to provide a new direction for exploring the pathogenesis of type 2 diabetes and finding therapeutic targets.

Effect of Polygonatum sibiricum saponins on gut microbiota of mice with ulcerative colitis.

Polygonatum sibiricum is a plant with medicinal and nutritional properties. Saponins are the important biologically active components of Polygonatum sibiricum. In this study, the specific components of Polygonatum sibiricum saponins (PSS) were analyzed, and the regulation effect of PSS on intestinal flora in patients with ulcerative colitis (UC) was investigated by inducing male Kunming mice with dextran sulfate sodium (DSS). PSS could ameliorate the symptoms of weight loss, high DAI score and colon length reduction compared to DSS-induced treatment. Colonic fragments were taken for H&E staining and histopathological scoring. PSS could significantly improve the pathological abnormality of colitis mice. 16S rRNA analysis showed that the intestinal microbial community of mice treated with DSS was significantly damaged. PSS could restore the richness and diversity of intestinal microbial flora, reduce the number of pathogenic bacteria, and increase the abundance of Lactobacillus spp. and Muribaculaceae, and improve the intestinal microbial flora disorder. Generally, PSS had an obvious effect in relieving colitis in mice. This study confirmed that Polygonatum sibiricum saponins play a therapeutic and palliative role in ulcerative colitis by regulating the microbiome balance.

Effects and Mechanistic Role of Mulberry Leaves in Treating Diabetes and its Complications.

Diabetes mellitus (DM) has become a surge burden worldwide owing to its high prevalence and range of associated complications such as coronary artery disease, blindness, stroke, and renal failure. Accordingly, the treatment and management of DM have become a research hotspot. Mulberry leaves (Morus alba L.) have been used in Traditional Chinese Medicine for a long time, with the first record of its use published in Shennong Bencao Jing (Shennong's Classic of Materia Medica). Mulberry leaves (MLs) are considered highly valuable medicinal food homologs that contain polysaccharides, flavonoids, alkaloids, and other bioactive substances. Modern pharmacological studies have shown that MLs have multiple bioactive effects, including hypolipidemic, hypoglycemic, antioxidation, and anti-inflammatory properties, with the ability to protect islet [Formula: see text]-cells, alleviate insulin resistance, and regulate intestinal flora. However, the pharmacological mechanisms of MLs in DM have not been fully elucidated. In this review, we summarize the botanical characterization, traditional use, chemical constituents, pharmacokinetics, and toxicology of MLs, and highlight the mechanisms involved in treating DM and its complications. This review can provide a valuable reference for the further development and utilization of MLs in the prevention and treatment of DM.

Polydopamine-Mediated Immunomodulatory Patch for Diabetic Periodontal Tissue Regeneration Assisted by Metformin-ZIF System.

An essential challenge in diabetic periodontal regeneration is achieving the transition from a hyperglycemic inflammatory microenvironment to a regenerative one. Here, we describe a polydopamine (PDA)-mediated ultralong silk microfiber (PDA-mSF) and metformin (Met)-loaded zeolitic imidazolate framework (ZIF) incorporated into a silk fibroin/gelatin (SG) patch to promote periodontal soft and hard tissue regeneration by regulating the immunomodulatory microenvironment. The PDA-mSF endows the patch with a reactive oxygen species (ROS)-scavenging ability and anti-inflammatory activity, reducing the inflammatory response by suppressing M1 macrophage polarization. Moreover, PDA improves periodontal ligament reconstruction via its cell affinity. Sustained release of Met from the Met-ZIF system confers the patch with antiaging and immunomodulatory abilities by activating M2 macrophage polarization to secrete osteogenesis-related cytokines, while release of Zn2+ also promotes bone regeneration. Consequently, the Met-ZIF system creates a favorable microenvironment for periodontal tissue regeneration. These features synergistically accelerate diabetic periodontal bone and ligament regeneration. Thus, our findings offer a potential therapeutic strategy for hard and soft tissue regeneration in diabetic periodontitis.

Molecular-scale substrate anisotropy, crowding and division drive collective behaviours in cell monolayers.

The ability of cells to reorganize in response to external stimuli is important in areas ranging from morphogenesis to tissue engineering. While nematic order is common in biological tissues, it typically only extends to small regions of cells interacting via steric repulsion. On isotropic substrates, elongated cells can co-align due to steric effects, forming ordered but randomly oriented finite-size domains. However, we have discovered that flat substrates with nematic order can induce global nematic alignment of dense, spindle-like cells, thereby influencing cell organization and collective motion and driving alignment on the scale of the entire tissue. Remarkably, single cells are not sensitive to the substrate's anisotropy. Rather, the emergence of global nematic order is a collective phenomenon that requires both steric effects and molecular-scale anisotropy of the substrate. To quantify the rich set of behaviours afforded by this system, we analyse velocity, positional and orientational correlations for several thousand cells over days. The establishment of global order is facilitated by enhanced cell division along the substrate's nematic axis, and associated extensile stresses that restructure the cells' actomyosin networks. Our work provides a new understanding of the dynamics of cellular remodelling and organization among weakly interacting cells.

Cholinergic anti-inflammatory pathway mediates diesel exhaust PM2.5-induced pulmonary and systemic inflammation.

Previous research has indicated that the cholinergic anti-inflammatory pathway (CAP) can regulate the duration and intensity of inflammatory responses. A wide range of research has demonstrated that PM2.5 exposure may induce various negative health effects via pulmonary and systemic inflammations. To study the potential role of the CAP in mediating PM2.5-induced effects, mice were treated with vagus nerve electrical stimulation (VNS) to activate the CAP before diesel exhaust PM2.5 (DEP) instillation. Analysis of pulmonary and systemic inflammations in mice demonstrated that VNS significantly reduced the inflammatory responses triggered by DEP. Meanwhile, inhibition of the CAP by vagotomy aggravated DEP-induced pulmonary inflammation. The flow cytometry results showed that DEP influenced the CAP by altering the Th cell balance and macrophage polarization in spleen, and in vitro cell co-culture experiments indicated that this DEP-induced change on macrophage polarization may act via the splenic CD4+ T cells. To further confirm the effect of alpha7 nicotinic acetylcholine receptor (α7nAChR) in this pathway, mice were then treated with α7nAChR inhibitor (α-BGT) or agonist (PNU282987). Our results demonstrated that specific activation of α7nAChR with PNU282987 effectively alleviated DEP-induced pulmonary inflammation, while specific inhibition of α7nAChR with α-BGT exacerbated the inflammatory markers. The present study suggests that PM2.5 have an impact on the CAP, and CAP may play a critical function in mediating PM2.5 exposure-induced inflammatory response. AVAILABILITY OF DATA AND MATERIALS: The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.

Effectiveness and safety of traditional Chinese medicine decoction for diabetic gastroparesis: A network meta-analysis.

BACKGROUND: Diabetic gastroparesis (DGP) is a prevalent complication of diabetes that impairs people's quality of life and places a significant financial burden on them. The gastrointestinal symptoms of DGP patients can be improved by several Traditional Chinese Medicine (TCM) decoctions that have been shown to be effective in treating the disease. There are still many unanswered questions regarding the identification of appropriate therapeutic agents for the treatment of DGP in clinical practice. AIM: To analyze the efficacy of several TCM decoctions in the treatment of DGP using Bayesian network meta-analysis for reference. METHODS: PubMed, EMBASE, Cochrane Library, Web of Science, China National Kno-wledge Infrastructure, The China Biology Medicine DVD, Wanfang, and CQVIP were searched from inception to September 17, 2022, to collect randomized controlled trials (RCTs) about TCM decoctions for DGP. Clinical effects and symptom scores were the primary outcomes. Additionally, we assessed motilin (MOT), somatostatin (SS), gastrin (GAS), gastric emptying rate, gastric emptying time, and adverse drug events as secondary outcomes. RESULTS: A total of 67 eligible RCTs involving 4790 DGP patients and 7 TCM decoctions were included. The results of network meta-analysis (NMA) and surface under the cumulative ranking curve showed that with western medicine (WM) as a common control, the Banxia Xiexin Decoction (BXXD) + WM was most effective in clinical effects and enhancing early satiety scores; the Simo decoction (SMD) + WM was most effective in improving nausea and vomiting scores and anorexia scores, bloating scores; the Chaishao Liujunzi Decoction (CSLJD) was most effective in MOT, the Zhishi Xiaopi Decoction (ZSXPD) was most effective in SS and upgrading emptying rate; the Jianpi Xiaozhi Decoction was most effective in GAS; the CSLJD + WM was most effective in improving gastric emptying time. CONCLUSION: These NMA results suggest that the BXXD + WM and SMD + WM may be one of the potential optimal treatments. Due to various limitations, further large-sample, double-blind, multi-center randomized RCTs are needed.

Iron metabolism and ferroptosis in type 2 diabetes mellitus and complications: mechanisms and therapeutic opportunities.

The maintenance of iron homeostasis is essential for proper endocrine function. A growing body of evidence suggests that iron imbalance is a key factor in the development of several endocrine diseases. Nowadays, ferroptosis, an iron-dependent form of regulated cell death, has become increasingly recognized as an important process to mediate the pathogenesis and progression of type 2 diabetes mellitus (T2DM). It has been shown that ferroptosis in pancreas ß cells leads to decreased insulin secretion; and ferroptosis in the liver, fat, and muscle induces insulin resistance. Understanding the mechanisms concerning the regulation of iron metabolism and ferroptosis in T2DM may lead to improved disease management. In this review, we summarized the connection between the metabolic pathways and molecular mechanisms of iron metabolism and ferroptosis in T2DM. Additionally, we discuss the potential targets and pathways concerning ferroptosis in treating T2DM and analysis the current limitations and future directions concerning these novel T2DM treatment targets.

Machine-learning-based detection of degenerative temporomandibular joint diseases using lateral cephalograms.

INTRODUCTION: Degenerative temporomandibular joint diseases (DJDs) are common diseases in dental practice, characterized by a series of degenerative processes in the temporomandibular joint. Early clinical detection of DJD by dental practitioners can be beneficial to prevent or alleviate the further progression of the disease. This study aimed to develop a cephalogram-based multidimensional nomogram to screen DJD. METHODS: A total of 502 patients (170 normal and 332 with DJD) were randomly assigned to a training set (n = 351) or a validation set (n = 151). Thirty-six cephalometric parameters were extracted from the cephalograms to be used as input for a predictive machine-learning algorithm. Multivariable logistic regression was used to construct a combined model for visualization in the form of a nomogram. Receiver operating characteristic curve, calibration testing, and decision curve analyses were conducted to evaluate the performance of the combined model. RESULTS: A Ceph score consisting of 22 cephalometric parameters were significantly associated with DJD (P <0.01). A combined model that consisted of Ceph scores and clinical features (including age, gender, limited mouth opening, crepitus, etc.) performed well in the receiver operating characteristic curve (area under the curve, 0.893), calibration test, and decision curve analyses, indicating its potential clinical value. CONCLUSIONS: This study constructed and verified a multidimensional nomogram consisting of Ceph scores and clinical features, which may contribute to the clinical screening of DJD in dental practice. Future studies are needed to test the reliability of the model with similar parameters.

Maternal exposure to ambient PM2.5 perturbs the metabolic homeostasis of maternal serum and placenta in mice.

Epidemiological and animal studies have shown that maternal fine particulate matters (PM2.5) exposure correlates with various adverse pregnancy outcomes such as low birth weight (LBW) of offspring. However, the underlying biological mechanisms have not been fully understood. In this study, female C57Bl/6 J mice were exposed to filtered air (FA) or concentrated ambient PM2.5 (CAP) during pregestational and gestational periods, and metabolomics was performed to analyze the metabolic features in maternal serum and placenta by liquid chromatography-mass spectrometry (LC-MS). The partial least squares discriminate analysis (PLS-DA) displayed evident clustering of FA- and CAP-exposed samples for both maternal serum and placenta. In addition, pathway analysis identified that vitamin digestion and absorption was perturbed in maternal serum, while metabolic pathways including arachidonic acid metabolism, serotonergic synapse, 2-oxocarboxylic acid metabolism and cAMP signaling pathway were perturbed in placenta. Further analysis indicated that CAP exposure influenced the nutrient transportation capacity of placenta, by not only changing the ratios of some critical metabolites in placenta to maternal serum but also significantly altering the expressions of nutrition transporters in placenta. These findings reaffirm the importance of protecting women from PM2.5 exposure, and also advance our understanding of the toxic actions of ambient PM2.5.

PDX-1: A Promising Therapeutic Target to Reverse Diabetes.

The pancreatic duodenum homeobox-1 (PDX-1) is a transcription factor encoded by a Hox-like homeodomain gene that plays a crucial role in pancreatic development, ß-cell differentiation, and the maintenance of mature ß-cell functions. Research on the relationship between PDX-1 and diabetes has gained much attention because of the increasing prevalence of diabetes melitus (DM). Recent studies have shown that the overexpression of PDX-1 regulates pancreatic development and promotes ß-cell differentiation and insulin secretion. It also plays a vital role in cell remodeling, gene editing, and drug development. Conversely, the absence of PDX-1 increases susceptibility to DM. Therefore, in this review, we summarized the role of PDX-1 in pancreatic development and the pathogenesis of DM. A better understanding of PDX-1 will deepen our knowledge of the pathophysiology of DM and provide a scientific basis for exploring PDX-1 as a potential target for treating diabetes.

Reliable emulation of complex functionals by active learning with error control.

A statistical emulator can be used as a surrogate of complex physics-based calculations to drastically reduce the computational cost. Its successful implementation hinges on an accurate representation of the nonlinear response surface with a high-dimensional input space. Conventional "space-filling" designs, including random sampling and Latin hypercube sampling, become inefficient as the dimensionality of the input variables increases, and the predictive accuracy of the emulator can degrade substantially for a test input distant from the training input set. To address this fundamental challenge, we develop a reliable emulator for predicting complex functionals by active learning with error control (ALEC). The algorithm is applicable to infinite-dimensional mapping with high-fidelity predictions and a controlled predictive error. The computational efficiency has been demonstrated by emulating the classical density functional theory (cDFT) calculations, a statistical-mechanical method widely used in modeling the equilibrium properties of complex molecular systems. We show that ALEC is much more accurate than conventional emulators based on the Gaussian processes with "space-filling" designs and alternative active learning methods. In addition, it is computationally more efficient than direct cDFT calculations. ALEC can be a reliable building block for emulating expensive functionals owing to its minimal computational cost, controllable predictive error, and fully automatic features.

Advances in multi-omics study of biomarkers of glycolipid metabolism disorder.

Glycolipid metabolism disorder are major threats to human health and life. Genetic, environmental, psychological, cellular, and molecular factors contribute to their pathogenesis. Several studies demonstrated that neuroendocrine axis dysfunction, insulin resistance, oxidative stress, chronic inflammatory response, and gut microbiota dysbiosis are core pathological links associated with it. However, the underlying molecular mechanisms and therapeutic targets of glycolipid metabolism disorder remain to be elucidated. Progress in high-throughput technologies has helped clarify the pathophysiology of glycolipid metabolism disorder. In the present review, we explored the ways and means by which genomics, transcriptomics, proteomics, metabolomics, and gut microbiomics could help identify novel candidate biomarkers for the clinical management of glycolipid metabolism disorder. We also discuss the limitations and recommended future research directions of multi-omics studies on these diseases.

P2Y14 receptor in trigeminal ganglion contributes to neuropathic pain in mice.

Trigeminal nerve injury is a common complication of various dental and oral procedures, which could induce trigeminal neuropathic pain but lack effective treatments. P2 purinergic receptors have emerged as novel therapeutic targets for such pain. Recent reports implied that the P2Y14 receptor (P2Y14R) was activated and promoted orofacial inflammatory pain and migraine. However, the role and mechanism of P2Y14R in trigeminal neuropathic pain remain unknown. We induced an orofacial neuropathic pain model by chronic constriction injury of the infraorbital nerve (CCI-ION). Von-Frey tests showed that CCI-ION induced orofacial mechanical hypersensitivity. The increased activating transcription factor 3 (ATF3) expression in the trigeminal ganglion (TG) measured by immunofluorescence confirmed trigeminal nerve injury. Immunofluorescence showed that P2Y14R was expressed in trigeminal ganglion neurons (TGNs) and satellite glial cells (SGCs). RT-qPCR and Western blot identified increased expression of P2Y14R in TG after CCI-ION. CCI-ION also upregulated interleukin-1ß (IL-1ß), interleukin-6 (IL-6), C-C motif chemokine ligand 2 (CCL2), and tumor necrosis factor-α (TNF-α) in TG. Notably, CCI-ION-induced mechanical hypersensitivity and pro-inflammatory cytokines production were decreased by a P2Y14R antagonist (PPTN). Trigeminal administration of P2Y14R agonist (UDP-glucose) evoked orofacial mechanical hypersensitivity and increased pro-inflammatory cytokines above in TG. Furthermore, CCI-ION induced activation of extracellular signal-regulated kinase 1/2 (ERK1/2) and p38 in TG, which also were reduced by PPTN. The inhibitors of ERK1/2 (U0126) and p38 (SB203580) decreased these upregulated pro-inflammatory cytokines after CCI-ION. Collectively, this study revealed that P2Y14R in TG contributed to trigeminal neuropathic pain via ERK- and p38-dependent neuroinflammation. Thus, P2Y14R may be a potential drug target against trigeminal neuropathic pain.

Research progress on the pharmacological effects of berberine targeting mitochondria.

Berberine is a natural active ingredient extracted from the rhizome of Rhizoma Coptidis, which interacts with multiple intracellular targets and exhibits a wide range of pharmacological activities. Previous studies have preliminarily confirmed that the regulation of mitochondrial activity is related to various pharmacological actions of berberine, such as regulating blood sugar and lipid and inhibiting tumor progression. However, the mechanism of berberine's regulation of mitochondrial activity remains to be further studied. This paper summarizes the molecular mechanism of the mitochondrial quality control system and briefly reviews the targets of berberine in regulating mitochondrial activity. It is proposed that berberine mainly regulates glycolipid metabolism by regulating mitochondrial respiratory chain function, promotes tumor cell apoptosis by regulating mitochondrial apoptosis pathway, and protects cardiac function by promoting mitophagy to alleviate mitochondrial dysfunction. It reveals the mechanism of berberine's pharmacological effects from the perspective of mitochondria and provides a scientific basis for the application of berberine in the clinical treatment of diseases.

Modulation of Gut Microbiota and Metabolites by Berberine in Treating Mice With Disturbances in Glucose and Lipid Metabolism.

Introduction: Glucose and lipid metabolism disturbances has become the third major disease after cancer and cardio-cerebrovascular diseases. Emerging evidence shows that berberine can effectively intervene glucose and lipid metabolism disturbances, but the underlying mechanisms of this remain unclear. To investigate this issue, we performed metagenomic and metabolomic analysis in a group of normal mice (the NC group), mice with disturbances in glucose and lipid metabolism (the MC group) and mice with disturbances in glucose and lipid metabolism after berberine intervention (the BER group). Result: Firstly, analysis of the clinical indicators revealed that berberine significantly improved the blood glucose and blood lipid of the host. The fasting blood glucose level decreased by approximately 30% in the BER group after 8 weeks and the oral glucose tolerance test showed that the blood glucose level of the BER group was lower than that of the MC group at any time. Besides, berberine significantly reduced body weight, total plasma cholesterol and triglyceride. Secondly, compared to the NC group, we found dramatically decreased microbial richness and diversity in the MC group and BER group. Thirdly, LDA effect size suggested that berberine significantly altered the overall gut microbiota structure and enriched many bacteria, including Akkermansia (p < 0.01), Eubacterium (p < 0.01) and Ruminococcus (p < 0.01). Fourthly, the metabolomic analysis suggested that there were significant differences in the metabolomics signature of each group. For example, isoleucine (p < 0.01), phenylalanine (p < 0.05), and arbutin (p < 0.05) significantly increased in the MC group, and berberine intervention significantly reduced them. The arbutin content in the BER group was even lower than that in the NC group. Fifthly, by combined analysis of metagenomics and metabolomics, we observed that there were significantly negative correlations between the reduced faecal metabolites (e.g., arbutin) in the BER group and the enriched gut microbiota (e.g., Eubacterium and Ruminococcus) (p < 0.05). Finally, the correlation analysis between gut microbiota and clinical indices indicated that the bacteria (e.g., Eubacterium) enriched in the BER group were negatively associated with the above-mentioned clinical indices (p < 0.05). Conclusion: Overall, our results describe that the changes of gut microbiota and metabolites are associated with berberine improving glucose and lipid metabolism disturbances.