ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Objective To investigate the relationship of skin failure (SF) with nutritional status in elderly critically ill patients and analyze the predictive efficiency of nutritional status on SF. Methods A total of 340 elderly critically ill patients admitted to the hospital from January 2020 to January 2025 were selected as research subjects. According to whether skin failure occurred, the above patients were classified into skin failure group and non-skin failure group. The nutritional status indicators [serum albumin (ALB), prealbumin (PA), total protein (TP), hemoglobin (Hb), body mass index (BMI), nutritional risk score (NRS 2002)] were compared between both groups. Multivariate analysis was performed on statistically significant indicators, and ROC curve was applied to analyze the predictive value. Results Among the 340 elderly critically ill patients, 142 cases (41.76%) developed skin failure. The ALB, PA, TP, Hb and BMI in the skin failure group were lower than those in the non-skin failure group (P<0.05) while the NRS2002 score was higher (P<0.05). After logistic multivariate analysis, ALB, PA and Hb were independent influencing factors of skin failure (P<0.05). ROC curve analysis revealed that the predictive value of ALB (AUC=0.850, 95%CI: 0.808-0.888, Z=-3.707, P<0.001) was better than that of PA (AUC=0.770, 95%CI: 0.717-0.816, Z=-3.100, P=0.002) or Hb (AUC=0.773, 95%CI: 0.722-0.819, Z=-2.556, P=0.011). Conclusion The occurrence of skin failure in elderly critically ill patients is closely related to nutritional status. ALB, PA and Hb are independent risk factors of SF, and ALB has the best predictive efficiency on SF.

Chronic atrophic gastritis （CAG）， a common digestive system disease， has an unclear pathogenesis. Currently， it is mostly believed to be related to Helicobacter pylori （Hp） infection， immune factors， dietary factors， bile reflux， long-term use of antibiotics and anti-inflammatory drugs， and other factors. Ferroptosis is a regulated cell death mechanism that is iron-dependent and characterized by disruption of iron metabolism and accumulation of lipid peroxides. More and more studies have found that ferroptosis is closely related to the onset of CAG. Professor LI Diangui， a master of traditional Chinese medicine， first proposed the turbid toxin theory， which holds that spleen deficiency and turbid toxin is the main pathogenic mechanism of CAG. Abnormal iron metabolism regulation is a prerequisite for the accumulation of turbid toxin in CAG， and ferroptosis is in accordance with the pathogenic mechanism （spleen deficiency and turbid toxin） of CAG. This article explores the pathological mechanism of spleen deficiency and turbid toxin in CAG from the perspectives of iron metabolism， oxidative stress， and lipid peroxidation， providing theoretical support of traditional Chinese medicine for the modern research on CAG. It enriches the modern scientific connotation of the turbid toxicity theory and provides new ideas and breakthrough points for the clinical treatment of CAG.

Objective To investigate the effects of liraglutide on the gut microbiota of db/db diabetic mice and the predictive value of the microbial structure for the hypoglycemic efficacy.Methods The db/db mice were randomly divided into control group and liraglutide group(0.4 μg/g).Fasting blood glucose levels were measured in the mice,and fecal samples were collected to determine the structure of the gut microbiota.Results Compared with the control group,the liraglutide group exhibi-ted a significant increase in the average number of operational taxonomic unit(OTU)(P＜0.01).The number of observed species,Chao1 index and ACE index were all significantly higher in the liraglutide group than those in the control group(P＜0.05).Additionally,the liraglutide group showed a signifi-cant increase in the relative abundance of Firmicutes and a significant decrease in the abundance of Actinobacteria compared with the control group(P＜0.01).The percentage decrease in blood glucose levels in db/db mice was positively correlated with the abundance of Pseudomonadaceae and negatively correlated with the abundances of Clostridiaceae and Peptostreptococcaceae.Conclusion Liraglutide treatment can modulate the structure of the gut microbiota,increasing the number of OTU and diversity,particularly enhancing the abundance of beneficial bacteria such as Clostridium,Lachnospira and Oscillospira.The gut microbiota structure in mice serves as a predictive factor for the hypoglycemic efficacy of liraglutide,with diabetic mice exhibiting a higher abundance of Pseudomonas being more likely to benefit from liraglutide-induced hypoglycemic therapy.

Objective:To explore the dual mediating effects of health belief and depression among health knowledge, social support, and health behaviors based on the capacity, opportunity, motivation-behavior (COM-B) model, and analyze the influencing factors of health behaviors in patients with ischemic stroke.Methods:This multi-center cluster sampling research recruited ischemic stroke patients ( n=1 696) who were hospitalized in neurology departments of five tertiary hospitals in Henan Province from October 2023 to October 2024. A cross-sectional investigation was conducted using the general information questionnaire, social support rating scale (SSRS), stroke prevention knowledge questionnaire(SPKQ), short form health belief model scale(SF-HBMS), health promoting lifestyle profile-Ⅱ (HPLP-Ⅱ), and patient health questionnaire-9(PHQ-9) to ultimately reveal the pathways and effect sizes among variables. Partial correlation analysis and multiple linear stepwise regression analysis were conducted to examine the relationships among social support, health knowledge, health belief, health behaviors, and depression in stroke patients by SPSS 26.0 software. Structural equation modeling was constructed using AMOS 28.0 software, and the mediating effect was tested using the Bootstrap method. Results:The scores of social support, health knowledge, health belief, and health behaviors among ischemic stroke patients were (37.46±9.94), (26.56±6.84), (75.62±12.62) and (130.79±26.27), respectively. The score of depression was 5.00 (2.00, 8.00). Health behaviors were positively correlated with health knowledge, social support, and health belief( r=0.333, 0.246, 0.267, all P<0.05), while negatively correlated with depression ( r=-0.146, P<0.05). Multiple linear stepwise regression analysis showed that health knowledge, social support, health belief, and depression were all influencing factors of health behaviors in ischemic stroke patients (all P<0.05). Health belief (effect value=0.068, 95% CI=0.048-0.093) and depression (effect value=0.009, 95% CI=0.003-0.018) both played partial mediating roles between health knowledge and health behaviors, accounting for 17.3%(0.077/0.446) of the total effect. Meanwhile, health belief (effect value=0.045, 95% CI=0.029-0.063) and depression (effect value=0.016, 95% CI=0.008-0.027) both played partial mediating roles between social support and health behaviors, accounting for 26.5%(0.061/0.230) of the total effect. Conclusion:Health knowledge and social support can not only directly influence health behaviors but also indirectly affect them through health belief and depression in patients with ischemic stroke.

Type 2 diabetes mellitus(T2DM)is an insulin resistance disease.Improving insulin resis-tance and controlling blood glucose are the main means of clinical treatment for T2DM.Empa-gliflozin is a highly selective sodium-dependent glu-cose transporters(SGLT)2 inhibitor,which is inde-pendent of insulin.It can effectively control blood glucose levels,reduce blood pressure and body weight,protect heart and kidney function,reduce the rehospitalization rate and the risk of death in patients with heart failure(HF),and does not in-crease the risk of hypoglycemia.Empagliflozin can be used alone or in combination with other hypo-glycemic drugs to control blood glucose.This arti-cle reviews the mechanism of action,clinical bene-fits,and combination with other drugs of empa-gliflozin,aiming to provide reference for the clinical use of empagliflozin.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.