OBJECTIVE To study the protective effect and potential mechanism of chikusetsu saponin Ⅳ a （chsⅣ） on renal function in diabetic nephropathy （DN） model rats. METHODS DN rat model was established by high-fat diet combined with streptozotocin injection. Thirty-six model rats were randomly divided into model group （i.g. administration of normal saline， high-fat diet）， chsⅣ low-dose and high-dose groups （i.g. administration of 90， 180 mg/kg chsⅣ， high-fat diet）， with 12 rats in each group. Additionally， 10 normal rats were set as the control group （i.g. administration of normal saline， regular diet）. From the 5th to the 12th week after streptozotocin injection， they were given intragastric administration of relevant drug or normal saline， once a day. After the last medication， the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine and urine protein as well as the levels of reduced glutathione （GSH）， superoxide dismutase （SOD） and malondialdehyde （MDA） in renal tissues were measured. Additionally， the insulin resistance index was calculated. Hematoxylin-eosin， periodic acid-Schiff， and Masson staining techniques were employed to examine the histopathological alterations in the renal tissue. The expressions of Notch signaling pathway-related proteins in renal tissue were detected by immunohistochemical staining and Western blot methods. RESULTS Compared with model group， the histomorphological of renal tissues in the chsⅣ low- and high-dose groups were significantly improved， with significant decreases in renal histological scores， mesangial expansion index， and glomerulosclerosis scores （ P ＜0.05）； the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine， urine protein and homeostasis model assessment for insulin resistance， as well as MDA content， the expression levels of Notch1， Notch intracellular domain， hairy and enhancer of Split 1 and Delta-like protein 1 in renal tissue were all significantly decreased （ P ＜0.05）. The levels of GSH and SOD in renal tissue were significantly elevated （ P ＜0.05）. Moreover， the improvement in these indicators was significantly more pronounced in the chsⅣ high-dose group compared to the chsⅣ low-dose group （ P ＜0.05）. CONCLUSIONS ChsⅣ can ameliorate renal pathological damage and functional impairment in DN rats. Its underlying mechanisms include restoration of glucose homeostasis and insulin sensitivity， attenuation of renal oxidative stress， and suppression of aberrant Notch signaling pathway activation.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

OBJECTIVE To investigate the effect and mechanism of Jingangteng capsules in the treatment of non-alcoholic fatty liver disease （NAFLD）. METHODS Thirty-two SD rats were randomly divided into normal group and modeling group. The modeling group was fed a high-fat diet to establish a NAFLD model. The successfully modeled rats were then randomly divided into model group， atorvastatin group[positive control， 2 mg/（kg·d）]， and Jingangteng capsules low- and high-dose groups [0.63 and 2.52 mg/（kg·d）]， with 6 rats in each group. The pathological changes of the liver were observed by hematoxylin-eosin staining and oil red O staining. Enzyme-linked immunosorbent assay was performed to determine the serum levels of triglycerides （TG）， total cholesterol （TC）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， alanine transaminase （ALT）， aspartate transaminase （AST）， tumour necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， IL-6， IL-18. 16S rDNA amplicon sequencing and metabolomics techniques were applied to explore the effects of Jingangteng capsules on gut microbiota and metabolisms in NAFLD rats. Based on the E-mail：591146765@qq.com metabolomics results， Western blot analysis was performed to detect proteins related to the nuclear factor kappa-B （NF-κB）/NOD-like receptor family protein 3 （NLRP3） signaling pathway in the livers of NAFLD rats. RESULTS The experimental results showed that Jingangteng capsules could significantly reduce the serum levels of TG， TC， LDL-C， AST， ALT， TNF-α， IL-1β， IL-6， IL-18， while increased the level of HDL-C， and alleviated the hepatic cellular steatosis and inflammatory infiltration in NAFLD rats. They could regulate the gut microbiota disorders in NAFLD rats， significantly increased the relative abundance of Romboutsia and Oscillospira， and significantly decreased the relative abundance of Blautia （P＜0.05）. They also regulated metabolic disorders primarily by affecting secondary bile acid biosynthesis， fatty acid degradation， O-antigen nucleotide sugar biosynthesis， etc. Results of Western blot assay showed that they significantly reduced the phosphorylation levels of NF-κB p65 and NF-κB inhibitor α， and the protein expression levels of NLRP3， caspase-1 and ASC （P＜0.05 or P＜0.01）. CONCLUSIONS Jingangteng capsules could improve inflammation， lipid accumulation and liver injury in NAFLD rats， regulate the disorders of gut microbiota and metabolisms， and inhibit NF-κB/NLRP3 signaling pathway. Their therapeutic effects against NAFLD are mediated through the inhibition of the NF-κB/NLRP3 signaling pathway.

To explore the differences in biological gas production in the waterlogged zone of a coal seam fire-affected area, in this study the in-situ gas production experiment was conducted with the mine water from aquitard layers in coal seam fire zones in Xinjiang. The results showed that the biogas production first increased and then decreased with the increase in distance, and the highest gas production reached 216.55 mL. The changes in key metabolic pathways during the anaerobic fermentation of coal were analyzed, which showed that as the distance from the aquitard layer in the coal seam fire zone increased, the methanogenesis pathways gradually shifted from acetic acid decarboxylation and carbon dioxide reduction to acetic acid decarboxylation and methylamine methanogenesis. The significant variability in the in-situ mine water reservoir conditions contributed to the differences. In addition, the reservoir pressure and temperature increased as the distance from the fire zone became longer, and the salinity of the farthest mine water in the reverse fault was the highest due to the lack of groundwater supply. Pearson correlation analysis revealed significant correlations of microbial communities with key functional genes and the types and concentrations of ions. The ions significantly influencing microbial enzymatic metabolic activities included Al³⁺, Fe²⁺, Co²⁺, Ni²⁺, Cu²⁺, Zn²⁺, Mg²⁺, PO₄^3-, and Mo⁶⁺. The differences in metabolic pathways were attributed to the integrated effects of a co-occurring environment with multiple ions. The gas production simulation experiments and metagenomic analyses provide data support for the practical application of in-situ biogas experiments, laying a foundation for engineering applications.
Biofuels ; Coal ; Methane/biosynthesis* ; Fires ; Groundwater ; Coal Mining ; Fermentation ; China ; Anaerobiosis

Objective:To investigate the influencing factors for dysphagia in the elderly,to construct a predictive model for dysphagia,and to provide a theoretical basis for clinical practice.Methods:In this case-control study,the patients with dysphagia who attended Department of Geriatrics in the first affiliated hospital of Chongqing Medical University from March 2016 to June 2023 were enrolled as case group,and the patients without dysphagia who attended the same department during the same period of time were enrolled as con-trol group.The correlation analysis,least absolute shrinkage and selection operator(LASSO)regression,and multivariate logistic re-gression analysis were used to investigate the influencing factors for dysphagia;the 10-fold cross-validation Extreme Gradient Boosting(XGBoost)model was used to predict dysphagia,and the SHapley additive exPlanations(SHAP)method was used for model visualiza-tion.Results:There were 1009 cases in the case group and 2125 cases in the control group.The correlation analysis and LASSO re-gression analysis identified 12 factors for the multivariate logistic re-gression analysis,and the results showed that sarcopenia,increasing age,children or caretakers as caregivers,frail health,poor oral health,poor self-care ability,depression,and cognitive impairment were risk factors for dysphagia(odds ratio[OR]>1,P<0.05),and fe-male sex and participation in community activities were protective factors against dysphagia(OR<1,P<0.05).The XGBoost model had a good predictive efficacy,with an accuracy rate of 0.795,a preci-sion rate of 0.711,a sensitivity of 0.613,a specificity of 0.881,an F1 value of 0.661,and an area under the ROC curve of 0.855.The SHAP plot showed that the top five important characteristics were caregiver,oral score,frail health condition,activities of daily living,and cognitive function.Conclusion:There are various influencing factors for dysphagia in the elderly,and the elderly patients with poor oral health,frailty,dependence on others for daily life,and cognitive impairment should be taken seriously in clinical practice.The XGBoost model has a good performance in predicting dysphagia in the elderly,which can provide a reference for clinical practice.

Objective:To explore the internal mechanism by which self-evaluation influences non-suicidal self-injury (NSSI) in adolescent patients with depressive disorder.Methods:Clinical data from 214 adolescent patients with depressive disorder hospitalized at Suzhou Guangji Hospital from March 2022 to January 2024 were prospectively collected. According to the DSM-5 diagnostic criteria for NSSI, participants were divided into an NSSI group (158 cases [38 males, 120 females, age 12-17 (14.2±1.5) years]) and a non-NSSI group (56 cases [20 males, 36 females, age 12-18 (14.5±1.8) years]). A self-developed basic information questionnaire was used to collect demographic data. Standardized tools including the Self-rating Depression Scale (SDS), Inventory of Parent and Peer Attachment (IPPA), Self-acceptance Questionnaire (SAQ), and Perceived Stress Scale-10 (PSS-10) were used to assess their depression level, parental attachment level, self-evaluation/acceptance level, perceived stress level, and other relevant psychological characteristics. Differences in psychological characteristics between the two groups were compared. Logistic regression, correlation analysis, and mediation effect models were used to explore the relationships between variables and NSSI and their mechanisms.Results:The NSSI group had significantly higher total scores on the SDS (41.3±7.7 vs. 34.4±9.3) and PSS-10 (25.5±6.1 vs. 21.3±6.5) than the non-NSSI group ( F=29.12, F=18.17, respectively; all P<0.001). Conversely, the NSSI group had significantly lower total scores on the SAQ (31.2±8.8 vs. 35.9±8.9) and IPPA (56.3±13.6 vs. 63.4±13.8) compared to the non-NSSI group ( F=11.24, F=10.84, respectively; all P<0.001). Stepwise logistic regression analysis identified depression level (SDS total score, OR=1.12, 95% CI: 1.05-1.19), self-evaluation (SAQ subscale score, OR=1.17, 95% CI: 1.04-1.31), and perceived stress (PSS-10 total score, OR=1.11, 95% CI: 1.01-1.22) as predictors of NSSI (all P<0.05). Chain mediation analysis showed that self-evaluation had a significant positive direct effect ( β=0.025, P<0.01) and a negative indirect effect ( β=-0.038, P<0.001) on NSSI, with a negative total effect ( β=-0.012, P<0.05). The indirect effect was realized through three pathways: a single mediation pathway of self-evaluation via perceived stress ( β=-0.016), a single mediation pathway of self-evaluation via depression ( β=-0.011), and a chain mediation pathway of self-evaluation via perceived stress and depression ( β=-0.011) (all P<0.05). Conclusion:Self-evaluation influences NSSI behavior through a dual mechanism involving both direct and indirect effects. The indirect protective effect is primarily achieved by reducing perceived stress and depression levels.

Objective To explore the mechanism of honey-processed Hedysari Radix in the regulation of intestinal immunity in rats with spleen qi deficiency,which was based on G protein-coupled receptor 41(GPR41)/GPR43-mediated mitogen-activated protein kinase(MAPK)signaling pathway.Methods The three-factor composite modeling method of eating disorder,diarrhea and fatigue was used to establish a model of spleen qi deficiency,and the rats were randomly divided into model,honey-processed Hedysari Radix,probiotics and blank groups with 15 rats per group.The honey-processed Hedysari Radix group was given by gavage 12.6 g·kg-1 aqueous extract of honey-processed Hedysari Radix.The probiotics group was given 0.625 g·kg-1 bifidobacterium triple viable solution by gavage.The blank and model groups were given the same dose of distilled water by gavage.Four groups were treated for 15 d with once a day.The expression levels of GPR41,GPR43,P38 MAPK,c-Jun N-terminal kinase(JNK)and extracellular regulatory protein kinase 1/2(ERK1/2)in colon tissues were detected by Western blotting.Results The relative expression levels of GPR41 in the blank,model,honey-processed Hedysari Radix and probiotics groups were 0.95±0.07,0.45±0.03,0.84±0.19 and 0.86±0.20;the relative expression levels of GPR43 were 1.17±0.11,0.41±0.06,0.66±0.03 and 0.57±0.01;the phosphorylated ERK1/2/ERK1/2 ratios were 0.16±0.01,0.43±0.01,0.39±0.01 and 0.36±0.02;the phosphorylated JNK/JNK ratios were 0.58±0.05,1.47±0.10,0.90±0.11 and 0.90±0.11;the phosphorylated P38 MAPK/P38 MAPK ratios were 1.77±0.33,3.19±0.03,2.01±0.17 and 2.23±0.59,respectively.Compared with the model group,the differences of above indexes were statistically significant in the honey-processed Hedysari Radix and probiotics groups(P＜0.05,P＜0.01).Conclusion The mechanism of honey-processed Hedysari Radix regulating intestinal immunity in rats with spleen qi deficiency is related to the regulation of GPR41/GPR43 mediated MAPK signaling pathway.

Objective To evaluate the value of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)in differentiating histopathological types of brain metastases from non-small cell lung cancer(NSCLC).Methods Sixty-eight patients with brain metastases confirmed by pathology were collected,including 47 lung adenocarcinoma patients divided into a lung adenocarcinoma group and 21 lung squamous cell carcinoma patients into a lung squamous cell carcinoma group.The two groups were compared in terms of the DCE-MRI derived parameters including volume transfer constant(Ktrans),extra vascular extracellular volume fraction(Ve)and plasma volume fraction(Vp);ROC curves were used to assess the diagnostic efficacy of different quantitative parameters for the pathologic types of brain metastases from lung adenocarcinoma group or lung squamous cell carcinoma.SPSS 22.0 software was used for statistical analysis.Results The lung adenocarcinoma group had the values of Ktrans,Ve,Vp and Ve+Vp higher than those of the lung squamous cell carcinoma group,with the differences being statistically significant(all P＜0.05).ROC curve analysis results showed that Ktrans,Vp and Ve had high differential diagnosis values for the pathologic types of brain metastases from lung adenocarcinoma group or lung squamous cell carcinoma,with the AUC being 1.000,0.998 and 0.875,the optimal Youden index being 0.183 min-1,0.039 and 0.270,the sensitivity being 100.00％,100.00％and 80.56％and the specificity being 100.00％,97.06％and 80.88％,respectively.Conclusion The quantitative parameters of DCE-MRI gain advantages in the differential diagnosis of NSCLC brain metastases,and provide references for the diagnosis and treatment of brain metastases of lung cancer.[Chinese Medical Equipment Journal,2025,46(5):54-59]