OBJECTIVES: Recent evidence suggests that the gut may be a primary site of metformin action. However, studies on the effects of metformin on gut microbiota remain limited, and its impact on gut microbial metabolites such as short-/medium-chain fatty acids is unclear. This study aims to investigate the effects of metformin on gut microbiota, short-/medium-chain fatty acids, and associated metabolic benefits in high-fat diet rats. METHODS: Twenty-four Sprague-Dawley rats were randomly divided into 3 groups: 1) Normal diet group (ND group), fed standard chow; 2) high-fat diet group (HFD group), fed a high-fat diet; 3) high-fat diet + metformin treatment group (HFD+Met group), fed a high-fat diet for 8 weeks, followed by daily intragastric administration of metformin solution (150 mg/kg body weight) starting in week 9. At the end of the experiment, all rats were sacrificed, and serum, liver, and colonic contents were collected for assessment of glucose and lipid metabolism, liver pathology, gut microbiota composition, and the concentrations of short-/medium-chain fatty acids. RESULTS: Metformin significantly improved HFD-induced glucose and lipid metabolic disorders and liver injury. Compared with the HFD group, the HFD+Met group showed reduced abundance of Blautia, Romboutsia, Bilophila, and Bacteroides, while Lactobacillus abundance significantly increased (all P<0.05). Colonic contents of butyric acid, 2-methyl butyric acid, valeric acid, octanoic acid, and lauric acid were significantly elevated (all P<0.05), whereas acetic acid, isoheptanoic acid, and nonanoic acid levels were significantly decreased (all P<0.05). Spearman correlation analysis revealed that Lactobacillus abundance was negatively correlated with body weight gain and insulin resistance, while butyrate and valerate levels were negatively correlated with insulin resistance and liver injury (all P<0.05). CONCLUSIONS Metformin significantly increases the abundance of beneficial bacteria such as Lactobacillus and promotes the production of short-/medium-chain fatty acids including butyric, valeric, and lauric acid in the colonic contents of HFD rats, suggesting that metformin may regulate host metabolism through modulation of the gut microbiota.
Animals ; Metformin/pharmacology* ; Rats, Sprague-Dawley ; Diet, High-Fat/adverse effects* ; Rats ; Gastrointestinal Microbiome/drug effects* ; Male ; Fatty Acids, Volatile/metabolism* ; Fatty Acids/metabolism*

Although clinical evidence suggests that nonalcoholic fatty liver disease is an established major risk factor for heart failure, it remains unexplored whether sleep disorder-caused hepatic damage contributes to the development of cardiovascular disease (CVD). Here, our findings revealed that sleep fragmentation (SF) displayed notable hepatic detrimental phenotypes, including steatosis and oxidative damage, along with significant abnormalities in cardiac structure and function. All these pathological changes persisted even after sleep recovery for 2 consecutive weeks or more, displaying memory properties. Mechanistically, persistent higher expression of nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4) in the liver was the key initiator of SF-accelerated damage phenotypes. SF epigenetically controlled the acetylation of histone H3 lysine 27 (H3K27ac) enrichment at the Nox4 promoter and markedly increased Nox4 expression in liver even after sleep recovery. Moreover, fine coordination of the circadian clock and hepatic damage was strictly controlled by BMAL1-dependent Sirtuin 1 (Sirt1) transcription after circadian misalignment. Accordingly, genetic manipulation of liver-specific Nox4 or Sirt1, along with pharmacological intervention targeting NOX4 (GLX351322) or SIRT1 (Resveratrol), could effectively erase the epigenetic modification of Nox4 by reducing the H3K27ac level and ameliorate the progression of liver pathology, thereby counteracting SF-evoked sustained CVD. Collectively, our findings may pave the way for strategies to mitigate myocardial injury from persistent hepatic detrimental memory in diabetic patients.

A major obstacle in type 2 diabetes mellitus (T2DM) is sleep fragmentation (SF), which negatively affects testicular function. However, the underlying mechanisms remain to be elucidated. In this study, we demonstrate that SF induces testicular damage through a mechanism involving lipid metabolism, specifically mediated by melatonin (MEL) receptor 1a (MT1). T2DM mice with SF intervention displayed several deleterious phenotypes such as apoptosis, deregulated lipid metabolism, and impaired testicular function. Unexpectedly, sleep recovery (SR) for 2 consecutive weeks could not completely abrogate SF's detrimental effects on lipid deposition and testicular function. Interestingly, MEL and MT1 agonist 2-iodomelatonin (2IM) effectively improved lipid homeostasis, highlighting MEL/2IM as a promising therapeutic drug for SF-trigged testicular damage. Mechanistically, MEL and 2IM activated FGFR1 and sequentially restrained the crosstalk and physical interaction between TAB1 and TAK1, which ultimately suppressed the phosphorylation of TAK1 to block lipid deposition and cell apoptosis caused by SF. The ameliorating effect of MEL/2IM was overtly nullified in Fgfr1 knockout (Fgfr1-KO ^+/- ) diabetic mice. Meanwhile, testicular-specific overexpression of Tak1 abolished the protective effect of FGF1^mut on diabetic mouse testis. Our findings offer valuable insights into the molecular mechanisms underlying the testicular pathogenesis associated with SF and propose a novel therapeutic approach for addressing male infertility in T2DM.

Lymphatic metastasis is the main metastatic route for colorectal cancer, which increases the risk of cancer recurrence and distant metastasis. The properties of the lymph node metastatic colorectal cancer (LNM-CRC) cells are poorly understood, and effective therapies are still lacking. Here, we found that hypoxia-induced fibroblast activation protein alpha (FAPα) expression in LNM-CRC cells. Gain- or loss-function experiments demonstrated that FAPα enhanced tumor cell migration, invasion, epithelial-mesenchymal transition, stemness, and lymphangiogenesis via activation of the STAT3 pathway. In addition, FAPα in tumor cells induced extracellular matrix remodeling and established an immunosuppressive environment via recruiting regulatory T cells, to promote colorectal cancer lymph node metastasis (CRCLNM). Z-GP-DAVLBH, a FAPα-activated prodrug, inhibited CRCLNM by targeting FAPα-positive LNM-CRC cells. Our study highlights the role of FAPα in tumor cells in CRCLNM and provides a potential therapeutic target and promising strategy for CRCLNM.

Objective:To explore the correlation between time in range (TIR) after short-term treatment and glycated hemoglobin after 3 months (HbA lc-3m) in patients with newly-diagnosed type 2 diabetes mellitus (T2DM). Methods:In this cross-sectional study, a total of 94 patients with newly-diagnosed T2DM who received treatment in the Department of Endocrinology of Inner Mongolia Autonomous Region People′s Hospital were enrolled from January 2018 to September 2022. The patients were followed-up for 3 months and had complete medical record. TIR was divided into three groups according to different target ranges of blood glucose (TIR1: TIR with blood glucose between 3.9 and 10.0 mmol/L, TIR2: TIR with blood glucose between 3.9 and 7.8 mmol/L, TIR3: TIR with fasting, premeal or bedtime blood glucose <6.1 mmol/L and 2 h postprandial blood glucose <8.0 mmol/L). The patients were divided into two groups based on whether their HbA 1c-3m level was less than 6.5%, and the baseline data and variations in TIR for distinct target glucose levels were compared between the two groups. Spearman′s correlation analysis and binary logistic regression analysis were used to analyze the relationship between baseline indicators, TIR after short-term treatment and HbA 1c-3m. Receiver operating characteristic curve (ROC) was drawn to evaluate the predictive ability of different TIR after short-term therapy for HbA 1c-3m. Results:There were statistically significant differences in TIR1 [81.0 (67.5, 94.6)% vs 71.4 (51.7, 85.7)%], TIR2 [57.7 (29.7, 70.8)% vs 40.9 (22.4, 52.3)%] and TIR3 [23.8 (10.2, 39.5)% vs 13.0 (4.8, 25.0)%] between patients with a HbA 1c-3m<6.5% and patients with a HbA 1c-3m≥6.5% (all P<0.05). Spearman correlation analysis showed that among all the patients with newly-diagnosed T2DM, TIR1, TIR2 and TIR3 were all negatively correlated with HbA 1c-3m [6.4 (6.1, 6.9)%] ( r=-0.322, -0.348, -0.303, respectively, all P<0.01). Logistic regression analysis showed that after adjusting for the confounding factors, TIR1 ( OR=1.021, 95% CI: 1.002-1.041; P=0.034), TIR2 ( OR=1.024, 95% CI: 1.006-1.043; P=0.011), TIR3 ( OR=1.037, 95% CI: 1.010-1.065; P=0.008) were all independently related to HbA 1c-3m. When HbA lc-3m<6.5% was taken as the target value, the area under the ROC curve: TIR1 was 0.639 (95% CI: 0.528-0.751), TIR2 was 0.671 (95% CI: 0.560-0.782), TIR3 was 0.659 (95% CI: 0.549-0.770), respectively. When HbA lc-3m<7.0% was taken as the target value, the area under the ROC curve: TIR1 was 0. 730 (95% CI: 0.619-0.841), TIR2 was 0.744 (95% CI: 0.642-0.846), TIR3 was 0.701 (95% CI: 0.588-0.814). There was no significant difference in the area among the three statistics ( P>0.05). Conclusions:For newly-diagnosed T2DM patients, TIR after short-term treatment is negatively correlated with HbA 1c after 3 months and has good predictive value for it.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.