AIM To investigate the effects of Gan Jiang-Huang Qin-Huang Lian-Ren Shen Decoction(GJHQHLRSD)on the pyroptosis,pathway of colonic epithelial cells in mouse models of ulcerative colitis(UC).METHODS Among the 63 C57BL/6J mice,13 were randomly selected and assigned to the model group,and the others were divided into the control group,the positive Sulfasalazine Enteric-Coated Tablets group(0.6 g/kg),and low,medium,and high dose GJHQHLRSD groups(3.9,7.8,15.6 g/kg),with 10 mice in each group.The UC mouse model was established using DSS,and the corresponding drugs were administered by gavage.The mice had their general condition observed;their disease activity index(DAI)score assessed;their colon length measured;their histopathological damage of the colon analyzed using HE staining;their colonic IL-1β,IL-8,and TNF-α levels measured by ELISA method;their colonic NLRP3,GSDMD,pro-IL-1β,pro-caspase-1,and IL-1βprotein expression detected by Western blot method;and their cell pyroptosis detected by TUNEL and GSDMD fluorescence double staining.RESULTS Compared with the control group,the model group exhibited significant decrease in body weight and a shortened colon length(P＜0.01);increases in DAI score,levels of IL-1β,IL-8,TNF-α,as well as the protein expressions of NLRP3,GSDMD,and active-caspase-1(P＜0.05,P＜0.01);significant increase of colonic GSDMD and TUNEL positivity;indicating increased tissue damage and inflammatory response.Compared with the model group,the groups intervened with GJHQHLRSD showed a significant increase in body weight and colonic elongation(P＜0.05,P＜0.01);decreases in DAI score,levels of IL-1β,IL-8,TNF-α,as well as the protein expressions of NLRP3,GSDMD,and active-caspase-1(P＜0.05,P＜0.01);a gradient decrease in positivity of GSDMD and TUNEL;indicating a significantly reduced colonic pathological damage.CONCLUSION GJHQHLRSD can improve the DSS-induced inflammatory reaction of colonic mucosa in UC mice,and its mechanism mainly involves the NLRP3/caspase-1,thereby the regulation of the cell pyroptosis process.

Aim To investigate the regulatory mecha-nisms of donepezil on the expression and enzymatic ac-tivity of cytochrome P450 3A4(CYP3A4),elucidate the synergistic impact of hypoxia on CYP3A4 function,and reveal its potential association with drug-induced cardiotoxicity,particularly QT interval prolongation.Methods Western blot,co-immunoprecipitation,and gene knockdown techniques were employed to evaluate the effects of donepezil and hypoxia on CYP3A4 pro-tein expression.CYP3A4 enzymatic activity was as-sessed using an in vitro incubation system with rat liver microsomes combined with high-performance liquid chromatography(HPLC),and the half-maximal inhib-itory concentration(IC50)was determined.Results Donepezil(10 μmol·L-1)and hypoxia reduced CYP3A4 protein expression to 31.75％and 45.90％of the control levels,respectively.Both interventions activated the gp78-mediated ubiquitin-proteasome path-way,significantly increasing CYP3A4 ubiquitination levels by 2.1-fold compared to the control group,thereby promoting proteasomal degradation.Donepezil inhibited CYP3A4 enzyme activity with an IC50 of 83.4μmol·L-1,and hypoxia synergistically enhanced this inhibitory effect,reducing the IC50 to 20.79 μmol·L-1.Conclusion Donepezil downregulates CYP3A4 function through dual mechanisms involving ubiquitin-mediated proteasomal degradation and direct enzymatic inhibition.Hypoxia potentiates this effect,leading to impaired metabolism of CYP3A4 substrate drugs,ele-vated plasma drug concentrations(1.6-2.3-fold in-crease compared to normal metabolic conditions),and an increased risk of QT interval prolongation and other forms of cardiotoxicity.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

The aim of this study is to explore a new path of empowering ideological and political educa-tion in courses with digital intelligence technology,therefore to improve the teaching quality of biology courses in universities,promote the comprehensive implementation of the fundamental task of cultivating morality and talents,and continuously improve the level of"three pronged education".By using the biol-ogy course"Immunology"as a practical carrier,we have constructed a dual-driven framework of"ideo-logical and political guidance+digital intelligence empowerment"utilizing digital tools to further highlight pedagogical feature enhancement,curricular optimization,innovative teaching models,multidimensional assessment,and enhanced teaching refinement.The empowerment of digital intelligence in the ideological and political construction of the course"Immunology"has achieved notable progress.Students' profes-sional abilities and ideological and political literacy have significantly improved,and the proportion of students with excellent grades has been increasing year by year(81.93％of students with good grades or above in 2024),demonstrating outstanding performance in various social practice activities;The course exhibits excellent demonstration and radiation effects on campus,and the teaching results have been sup-ported by the Ministry of Education and provincial-level education reform projects.This study serves as a practical example for the digital transformation of ideological and political education in higher education courses,providing reference and innovative insights for implementing ideological and political elements in other courses of biology majors.

AIM To investigate the effects of Gan Jiang-Huang Qin-Huang Lian-Ren Shen Decoction(GJHQHLRSD)on the pyroptosis,pathway of colonic epithelial cells in mouse models of ulcerative colitis(UC).METHODS Among the 63 C57BL/6J mice,13 were randomly selected and assigned to the model group,and the others were divided into the control group,the positive Sulfasalazine Enteric-Coated Tablets group(0.6 g/kg),and low,medium,and high dose GJHQHLRSD groups(3.9,7.8,15.6 g/kg),with 10 mice in each group.The UC mouse model was established using DSS,and the corresponding drugs were administered by gavage.The mice had their general condition observed;their disease activity index(DAI)score assessed;their colon length measured;their histopathological damage of the colon analyzed using HE staining;their colonic IL-1β,IL-8,and TNF-α levels measured by ELISA method;their colonic NLRP3,GSDMD,pro-IL-1β,pro-caspase-1,and IL-1βprotein expression detected by Western blot method;and their cell pyroptosis detected by TUNEL and GSDMD fluorescence double staining.RESULTS Compared with the control group,the model group exhibited significant decrease in body weight and a shortened colon length(P＜0.01);increases in DAI score,levels of IL-1β,IL-8,TNF-α,as well as the protein expressions of NLRP3,GSDMD,and active-caspase-1(P＜0.05,P＜0.01);significant increase of colonic GSDMD and TUNEL positivity;indicating increased tissue damage and inflammatory response.Compared with the model group,the groups intervened with GJHQHLRSD showed a significant increase in body weight and colonic elongation(P＜0.05,P＜0.01);decreases in DAI score,levels of IL-1β,IL-8,TNF-α,as well as the protein expressions of NLRP3,GSDMD,and active-caspase-1(P＜0.05,P＜0.01);a gradient decrease in positivity of GSDMD and TUNEL;indicating a significantly reduced colonic pathological damage.CONCLUSION GJHQHLRSD can improve the DSS-induced inflammatory reaction of colonic mucosa in UC mice,and its mechanism mainly involves the NLRP3/caspase-1,thereby the regulation of the cell pyroptosis process.

The aim of this study is to explore a new path of empowering ideological and political educa-tion in courses with digital intelligence technology,therefore to improve the teaching quality of biology courses in universities,promote the comprehensive implementation of the fundamental task of cultivating morality and talents,and continuously improve the level of"three pronged education".By using the biol-ogy course"Immunology"as a practical carrier,we have constructed a dual-driven framework of"ideo-logical and political guidance+digital intelligence empowerment"utilizing digital tools to further highlight pedagogical feature enhancement,curricular optimization,innovative teaching models,multidimensional assessment,and enhanced teaching refinement.The empowerment of digital intelligence in the ideological and political construction of the course"Immunology"has achieved notable progress.Students' profes-sional abilities and ideological and political literacy have significantly improved,and the proportion of students with excellent grades has been increasing year by year(81.93％of students with good grades or above in 2024),demonstrating outstanding performance in various social practice activities;The course exhibits excellent demonstration and radiation effects on campus,and the teaching results have been sup-ported by the Ministry of Education and provincial-level education reform projects.This study serves as a practical example for the digital transformation of ideological and political education in higher education courses,providing reference and innovative insights for implementing ideological and political elements in other courses of biology majors.

Aim To investigate the regulatory mecha-nisms of donepezil on the expression and enzymatic ac-tivity of cytochrome P450 3A4(CYP3A4),elucidate the synergistic impact of hypoxia on CYP3A4 function,and reveal its potential association with drug-induced cardiotoxicity,particularly QT interval prolongation.Methods Western blot,co-immunoprecipitation,and gene knockdown techniques were employed to evaluate the effects of donepezil and hypoxia on CYP3A4 pro-tein expression.CYP3A4 enzymatic activity was as-sessed using an in vitro incubation system with rat liver microsomes combined with high-performance liquid chromatography(HPLC),and the half-maximal inhib-itory concentration(IC50)was determined.Results Donepezil(10 μmol·L-1)and hypoxia reduced CYP3A4 protein expression to 31.75％and 45.90％of the control levels,respectively.Both interventions activated the gp78-mediated ubiquitin-proteasome path-way,significantly increasing CYP3A4 ubiquitination levels by 2.1-fold compared to the control group,thereby promoting proteasomal degradation.Donepezil inhibited CYP3A4 enzyme activity with an IC50 of 83.4μmol·L-1,and hypoxia synergistically enhanced this inhibitory effect,reducing the IC50 to 20.79 μmol·L-1.Conclusion Donepezil downregulates CYP3A4 function through dual mechanisms involving ubiquitin-mediated proteasomal degradation and direct enzymatic inhibition.Hypoxia potentiates this effect,leading to impaired metabolism of CYP3A4 substrate drugs,ele-vated plasma drug concentrations(1.6-2.3-fold in-crease compared to normal metabolic conditions),and an increased risk of QT interval prolongation and other forms of cardiotoxicity.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Objective To investigate the predictive value of new simplified insulin resistance(IR)assessment indexes in identifying subclinical left ventricular systolic function impairment in patients with type 2 diabetes mellitus(T2DM).Methods A total of 150 T2DM patients with preserved left ventricular ejection fraction(LVEF≥50%)who were admitted to Department of Endocrinology of the First Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were retrospectively analyzed.All patients underwent two-dimensional speckle tracking echocardiography to measure left ventricular global longitudinal strain(GLS).According to GLS value,the subjects were divided into the normal group(GLS≥18%group,n=80)and the impaired group(GLS<18%group,n=70).Some new simplified IR assessment indicators were calculated and compared between the two groups,including body mass index(BMI),TG/HDL-C ratio,triglyceride-glucose(TyG)index,TyG-BMI index,TyG-WHR and metabolic score for IR(METS-IR).Correlation between the GLS and the new simplified IR assessment indexes was analyzed.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of different simplified IR assessment indexes,with the area under the curve(AUC)calculated.Furthermore,according to whether the subjects were complicated with hypertension,binary logistics regression analysis was performed to explore the independent correlation between the simplified IR assessment index and GLS<18%.Results Total 150 were included with aged(54.5±13.7)years with 96(64.0%)men and 54(36.0%)women.Compared with the GLS≥18%group,the TG/HDL-C ratio,TyG index,TyG-BMI,and METS-IR of subjects in the GLS<18%group were significantly increased(P<0.05).Pearson correlation analysis showed that TG/HDL-C ratio,TyG index,TyG-BMI,TyG-WHR,and METS-IR were negatively correlated with GLS(P<0.05).ROC analysis showed that TyG index had a certain predictive value for the evaluation of GLS<18%(AUC=0.678,95%CI 0.591-0.765,P<0.001).Stratification based on hypertension and further adjusting for confounding factors,TyG index remains significantly associated with GLS<18%(OR=3.249,95%CI 1.045-10.103,P=0.042).Conclusions The novel simplified insulin resistance evaluation indexes are closely associated with left ventricular subclinical systolic dysfunction in T2DM patients with preserved ejection fraction.TyG index is an effective index to identify left ventricular subclinical dysfunction in these populations.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.