Min Li

Diabetes has become a significant global public health challenge, and prediabetes (preD), as the earliest detectable stage of glucose metabolism disorder, constitutes a critical window for disease intervention. Currently, China has not established diagnostic criteria for HbA1c in preD, and there is limited understanding of the molecular mechanisms at the critical transition points during disease progression. This study employs a refined stratification strategy for HbA1c at intervals of 0.3%, integrating the Dynamic Network Biomarker (DNB) theory with high-throughput proteomics technology, combined with longitudinal cohort validation and machine learning methods, to systematically depict the disease progression characteristics, spanning from a healthy physiological state through the prediabetic stage and ultimately to the onset of type 2 diabetes (T2D). This cross-sectional cohort consisted of 110 subjects, divided into three groups: healthy controls (20), prediabetic (50), and type 2 diabetic (40). Of these, 28 went on to complete a 2-year longitudinal follow-up assessment. The results indicate that the HbA1c range of 6.0–6.2% (D stage) meets the three criteria of the DNB theory (high inter-molecular coherence, decoupling from external networks, and enhanced volatility), suggesting that this stage may represent a critical state for the transition from preD to T2D. A total of 37 core DNB proteins were identified through proteomics analysis, with the majority of functional annotations focused on biological processes involving extracellular matrix remodeling, inflammatory response, and insulin signaling pathways. In the longitudinal follow-up validation, the predictive efficacy of the ADAM10 protein for clinical outcomes was significant (AUC = 0.768), outperforming traditional indicators like HbA1c, demonstrating its potential value as a novel biomarker. There are several limitations in the present investigation. With the relatively small number of subjects, the short follow-up period, and the single center, single ethnic study design, the findings have limited generalizability. Additionally, the lack of functional validation of some of the important molecular targets is a methodological limitation that should be recognized. Therefore, the identified critical transition window and the clinical predictive value of DNB molecules need to be further validated through large-scale, multi-center, long-term cohort studies to obtain more reliable evidence-based medical evidence, providing a scientific basis for the precise diagnosis and early intervention of preD in the Chinese population.

Background: Non-alcoholic fatty liver disease (NAFLD) constitutes the most prevalent chronic liver disease worldwide. Progression to non-alcoholic steatohepatitis (NASH), the immune cell reservoir within the liver undergoes remodeling, exacerbating liver inflammation and potentially leading to liver fibrosis. Jiangtang Qingre Formula (JQF) is an effective prescription for the clinical treatment of NAFLD. However, its underlying mechanism of action remains unclear.Methods: Using a high-fat diet-induced NAFLD mouse model, we evaluated JQF’s effects with biochemical tests and histopathology. Single-cell RNA sequencing and spatial transcriptomics furthered our understanding of NAFLD pathophysiology and JQF’s treatment mechanisms.Results: Our findings initially revealed significant improvements in JQF on hepatic steatosis, inflammation, fibrosis and glucose tolerance in NAFLD mice. Furthermore, significant changes were observed in the immune cells including monocytes, macrophages, and T cells in the livers of NAFLD mice. Notably, regions infiltrated by T cells presented the most severe liver inflammation and fibrosis. Importantly, JQF effectively modulated these immune cells. Advanced subcluster and cell communication analyses identified key macrophage (KCs, MoMFs) and T cell (Tc, Th2) subpopulations in JQF’s therapeutic actions. Further SCENIC analysis additionally uncovered the essential transcription factors that regulate these cell subclusters, such as Stat2, Mta3, Eomes, and Etv5.Conclusion: Overall, our research suggests a promising potential therapeutic agent and identifies critical cell populations and transcription factors that contribute to its therapeutic effects, thereby revealing potential therapeutic targets for NAFLD.

Background: Natural compounds can positively impact health, and various studies suggest that they regulate glucose‒lipid metabolism by influencing short-chain fatty acids (SCFAs). This metabolism is key to maintaining energy balance and normal physiological functions in the body. This review explores how SCFAs regulate glucose and lipid metabolism and the natural compounds that can modulate these processes through SCFAs. This provides a healthier approach to treating glucose and lipid metabolism disorders in the future. Methods: This article reviews relevant literature on SCFAs and glycolipid metabolism from PubMed and the Web of Science Core Collection (WoSCC). It also highlights a range of natural compounds, including polysaccharides, anthocyanins, quercetins, resveratrols, carotenoids, and betaines, that can regulate glycolipid metabolism through modulation of the SCFA pathway. Results: Natural compounds enrich SCFA-producing bacteria, inhibit harmful bacteria, and regulate operational taxonomic unit (OTU) abundance and the intestinal transport rate in the gut microbiota to affect SCFA content in the intestine. However, most studies have been conducted in animals, lack clinical trials, and involve fewer natural compounds that target SCFAs. More research is needed to support the conclusions and to develop healthier interventions. Conclusions: SCFAs are crucial for human health and are produced mainly by the gut microbiota via dietary fiber fermentation. Eating foods rich in natural compounds, including fruits, vegetables, tea, and coarse fiber foods, can hinder harmful intestinal bacterial growth and promote beneficial bacterial proliferation, thus increasing SCFA levels and regulating glucose and lipid metabolism. By investigating how these compounds impact glycolipid metabolism via the SCFA pathway, novel insights and directions for treating glucolipid metabolism disorders can be provided.

Obesity presents a significant global health challenge, increasing the susceptibility to chronic conditions such as diabetes, cardiovascular disease, and hypertension. Within the context of obesity, lipid metabolism, adipose tissue formation, and inflammation are intricately linked to endoplasmic reticulum stress (ERS). ERS modulates metabolism, insulin signaling, inflammation, as well as cell proliferation and death through the unfolded protein response (UPR) pathway. Serving as a crucial nexus, ERS bridges the functionality of adipose tissue and the inflammatory response. In this review, we comprehensively elucidate the mechanisms by which ERS impacts adipose tissue function and inflammation in obesity, aiming to offer insights into targeting ERS for ameliorating metabolic dysregulation in obesity-associated chronic diseases such as hyperlipidemia, hypertension, fatty liver, and type 2 diabetes.

Aims/hypothesis: Through a comprehensive analysis of the clinical randomized controlled trials of traditional Chinese medicine (TCM) combined with conventional western medicine (CWM) in treating type 2 diabetes(T2DM) in the past ten years, the clinical efficacy and safety of different TCMs combined with CWM were explored. This study aimed to provide specific suggestions for clinical guidance on treating T2DM.Methods: A literature search was conducted in CNKI, WanFang, VIP, CBM, PubMed, Embase, and Web of Science. The search time was limited from 2010 to the present time. The literature type was a controlled clinical trial study of TCM combined with CWM intervention in treating T2DM. The outcome indices of the efficacy evaluation included fasting blood glucose (FBG), 2-hour postprandial blood glucose (2hPG), glycosylated hemoglobin (HbA1c), adverse reactions, and clinical efficacy. Stata 15 and RevMan 5.4 software were used to conduct a network meta-analysis and a traditional meta-analysis.Results: The results showed that shenqi jiangtang granule combined with sulfonylurea, shenqi jiangtang granules combined with metformin and jinlida granules combined with insulin had significant effects on reductions in FBG, 2hPG and clinical efficacy compared with western medicines alone, which included fasting blood glucose [MD=-2.17, 95%CI=(-2.50, -1.85)], blood sugar at 2 hours after a meal [MD=-1.94, 95%CI=(-2.23, -1.65)], and clinical curative effect [OR= 1.73, 95%CI=(0.59, 2.87)].Conclusions: TCM combined with CWM has a very significant effect on treating T2DM compared with CWM alone. According to the network meta-analysis, the best intervention measures of different TCMs for different outcome indicators were obtained.Systematic review registration: identifier 42022350372.