ObjectiveTo evaluate the detection specificity for clinical samples and the detection capability for standard substances of five commercially available multiplex polymerase chain reaction (PCR) nucleic acid detection kits (hereinafter referred to as the kits) for respiratory pathogens, and to provide a reference for selecting appropriate detection kits for multi-pathogen nucleic acid testing of respiratory infections. MethodsA total of 60 respiratory pathogen-positive clinical samples with known redults were selected and tested using the five kits (labeled as A, B, C, D, and E). The detection rates and Kappa coefficients were calculated to evaluate the consistency between the results from these kits and those from single-pathogen PCR kits. According to the limit of detection (LOD) provided by the kits, standard substances of respiratory pathogens (including 12 types such as influenza virus, Mycoplasma pneumoniae, and Bordetella pertussis) were diluted to four concentrations (250, 500, 1 000, and 2 000 copies·mL⁻¹). All five kits were used for detection to evaluate their respective detection capabilities. ResultsCompared with the results from single-pathogen PCR kits, the five tested kits demonstrated good consistency (all Kappa >0.80). Among them, Kit A had the highest detection rate (100.00%), followed by Kits C and E (98.33%), and then Kits B and D (95.00%). All five kits showed a relatively low false negative rate (FNR) for samples with a cycle threshold (Ct) value ≤35 (≤2.38%). However, for samples with Ct values>35, the FNR increased accordingly(average FNR=6.67%, P=0.029). Kit C exhibited the highest detection sensitivity for the tested standard substances (average LOD: 458.33 copies·mL⁻¹), followed by Kit D, then Kits A/E, and finally Kit B. ConclusionThe five multiplex PCR kits showed good consistency with single-pathogen detection results, but each had its own performance emphasis. Kit A, with the highest detection rate and high throughput, is suitable for targeted viral screening. Kit B, covering the broadest pathogen spectrum (including fungi/bacteria), is suitable for comprehensive respiratory pathogen screening. Kits C, D and E, are applicable for rapid detection. It is important to note that the detection efficacy of all kits decreases for low viral load samples with Ct values >35. In practical application, selection should be based on specific screening objectives, throughput requirements, and sample types.

Objective To develop and validate a machine learning-based predictive model to assess the in-hospital mortality risk of patients with myocardial infarction(MI)complicated by heart failure(HF)undergoing percutaneous coronary intervention(PCI).Methods This retrospective study analyzed MI patients with HF who underwent PCI at The First Affiliated Hospital of Xinjiang Medical University from January 2019 to January 2023.Patient data,including demographic characteristics,vital signs,laboratory test results,imaging parameters and medication use,were collected and randomly divided into a training set(70％)and a validation set(30％).The extreme gradient boosting(XGBoost)model was used to identify variables significantly associated with in-hospital mortality,and the Shapley additive explanations(SHAP)model was applied to assess feature importance.A predictive model was then constructed using univariate and multivariate Logistic regression analyses.Model performance was evaluated using receiver operating characteristic(ROC)curves,area under the curve(AUC)values,calibration curves,and decision curve analysis.Finally,a nomogram was developed for intuitive risk assessment.Results A total of 1 214 MI patients with HF were included in the study,with a median age of 64 years.The in-hospital mortality rate was 7.41％(90 deaths).XGBoost feature selection identified ten key predictive variables:age,myoglobin,albumin,fasting blood glucose,N-terminal pro-B-type natriuretic peptide(NT-proBNP),diabetes mellitus,creatinine,cystatin C,procalcitonin,and left ventricular ejection fraction.Based on these variables,a Logistic regression model was developed,with seven final predictors:age,diabetes mellitus,creatinine,fasting blood glucose,cystatin C,NT-proBNP,and albumin.The model demonstrated high predictive accuracy,with AUC value of 0.869(95％CI:0.84-0.89)in the training set and 0.827(95％CI:0.79-0.85)in the validation set.The calibration curve indicated that the predicted probabilities were consistent with the actual observed outcomes,and decision curve analysis showed that the model had a high net benefit across various decision thresholds.Conclusion This study developed a machine learning-based predictive model incorporating Logistic regression to assess the in-hospital mortality risk of MI patients with HF undergoing PCI.The model demonstrated high predictive performance and clinical utility.The nomogram derived from this model provides an intuitive tool for individualized risk assessment,aiding clinicians in the early identification of high-risk patients,optimizing intervention strategies,and improving patient outcomes.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.

Objective To analyze the long-term trend in the disease burden of congenital birth defects(CBDs)among neonates in China from 1990 to 2021,compare the trend with global patterns,and identify key subtypes along with their association with socioeconomic status to provide evidence for public health interventions.Methods Utilizing data from the Global Burden of Disease Study 2021(GBD 2021),we extracted indicators including disability-adjusted life years(DALYs),mortality,and prevalence for the neonatal period(＜28 days)in China,encompassing ten major CBD subtypes.Joinpoint regression analysis was employed to calculate annual percent changes and estimate annual percent changes(EAPC),with comparisons of subtype composition between 1990 and 2021.Nonlinear regression was used to assess the relationship between DALYs rates and the Socio-demographic Index(SDI).Results From 1990 to 2021,DALYs rates for neonatal CBDs declined significantly both globally and in China,with China's EAPC at-4.67％[95％CI:(—5.06,—4.28)],substantially exceeding the global average of-1.70％[95％CI:(—1.75,—1.64)].Congenital heart anomalies remained the primary burden,while neural tube defects and orofacial clefts in China showed notable reductions(EAPCs of-7.25％and-11.22％,respectively).However,DALYs rates for congenital musculoskeletal and limb anomalies exceeded global expected levels.A resurgence in the prevalence was observed post-2015,with higher burdens in males.DALYs rates exhibited a negative correlation with SDI.Conclusion China has achieved significant reductions in the neonatal CBDs burden,surpassing global trends;yet challenges persist in managing congenital heart anomalies and musculoskeletal defects.Future efforts should focus on enhancing early screening,surgical interventions,and regional equity to align with global health objectives.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

Objective:By sequencing and analyzing the biliary flora by 16S rDNA high-throughput sequencing technology,to identify the main flora associated with gallbladder stone formation and the main flora regulated by the Dahuang lingxian(DHLX),pre-liminary investigation the effect of DHLX on the biliary flora.Methods:The 50 male guinea pigs were randomly divided into Normal group,Model group,DHLX group.There were 15 guinea pigs in the normal group and 20 guinea pigs in the DHLX group,and 20 guin-ea pigs in the model group:the guinea pig model of gallstone was replicated with high-fat lithogenic diet,which was simultaneously ad-ministrated by gavage.After continuous intervention for 8 weeks,bile and gallbladder tissue samples were collected,and the gallstone formation rate of guinea pigs in each group was calculated,the pathological morphological changes of gallbladder tissue were detected by HE,T-CHO,TBA,LPS,IL-6,TNF-α were detected by ELISA,and the changes of biliary flora were detected by 16S rDNA;the correlation between biliary flora and bile index was detected by Pearson statistical method.Results:The stone formation rate of guinea pigs in the normal group was 8.3%,the rate of model stone composition was 90.8%,and the stone composition rate of DHLX group was 36.4%,and the HE staining results showed that compared with the normal group,the mucous membrane of the guinea pig in the model group was thickened,the columnar epithelial cells were arranged in a large number of inflammatory cells,and the columnar epi-thelial cells of the gallbladder mucosa in the chinese medicine group were arranged neatly compared with the model group,the thick-ness of the mucosa was reduced compared with the model group,and some inflammatory cells were infiltrated;ELISA results showed that compared with the normal group,the expressions of T-CHO,LPS,IL-6 and TNF-α in the bile of guinea pigs in the model group were significantly increased(P<0.01),while the content of TBA was significantly reduced(P<0.01);compared with the model group,the expression of LPS and IL-6 in the bile of the DHLX group were significantly reduced(P<0.01).The results of 16S rDNA showed that compared with the normal group the Ace index and Chao1 index of the model group were significantly reduced(P<0.01),and the Chao1 index of the DHLX group was significantly higher than that of the model group(P<0.05);biliary flora at the genera level was mainly composed of Burkholderia,Sphingomycetes,Breghamus,Delfortella,Pseudomonas;correlation analysis showed that total cholesterol was negatively correlated with the abundance of Methyloversatilis(P<0.05),and total bile acids were positively corre-lated with the abundance of Burkholderia(P<0.05),and Pseudomonas erythrocytes,Rhizobia,the abundance of Phreatobacter was negatively correlated(P<0.01)and LPS was positively correlated with the abundance of Pseudomonas erythrocytes(P<0.01).Conclu-sion:Biliary microflora disorder exists in the formation of biliary stones,and biliary microflora may participate in the formation of stones by regulating cholesterol,bile acids and LPS.DHLX can regulate the changes in the abundance of the microflora,make the structure of the microflora become normal,reduce the inflammation of the gallbladder,and prevent the formation of gallstones.

Objective To observe the value of venous phase CT radiomics for diagnosing colorectal cancer(CRC)complicated with tumor deposit(TD)and/or lymph node metastasis(LNM).Methods Totally 263 CRC patients were retrospectively enrolled and divided into TD(+)LNM(+)group(group A,n=103),TD(+)LNM(-)group(group B,n=63)and TD(-)LNM(+)group(group C,n=97)based on pathological results,also randomly divided into training set(n=210)and test set(n=53)at the ratio of 8∶2.Radiomics features of CRC were screened based on venous phase CT images.Radiomics models were constructed with support vector machine(SVM),multilayer perceptron(MLP)and K-nearest neighbor(KNN),respectively,and their diagnostic efficacy were analyzed.Results In both training set and test set,SVM model had the highest overall efficacy for diagnosing CRC complicated with TD and/or LNM.Due to the uneven distribution of sample sizes among 3 groups,DeLong test was performed on the micro-averaged area under the curve(Micro AUC),which was more robust for handling class imbalance problems.In training set,significant differences were found between SVM and MLP models,as well as between SVM and KNN models(both P＜0.05),while in test set,significant differences were observed between each 2 models(all P＜0.05).Conclusion Venous phase CT radiomics models,especially SVM model was helpful for diagnosing CRC complicated with TD and/or LNM.

Objective:To understand the prevalence of frailty and the importance of its influencing factors in adult population in Shaanxi Province.Methods:The data were from Shaanxi baseline survey of natural population cohort study in northwest China during 2018-2019. The frailty index (FI) was constructed to evaluate the frailty status of the population, and XGboost model combined with Shapley method was used to analyze the importance of the sociodemographic and life behavior factors affecting the prevalence of frailty by gender and age.Results:A total of 25 079 subjects were included, in whom 964 (3.8%) had frailty, and there was no significant difference in the overall prevalence of frailty between women (3.9%) and men (3.8%) ( P=0.629), but there was a gender specific difference in the distribution of FI ( P<0.001), and the proportion of the pre-frailty in men was higher than that in women. The prevalence of frailty increased with age ( P<0.001), the prevalence of frailty were 1.3%, 2.5% and 7.8% in young, middle-aged and elderly women, respectively, and 1.9%, 2.7% and 5.5% in young, middle-aged and elderly men, respectively. Sociodemographic characteristics and lifestyle patterns were both influencing factors for the prevalence of frailty, but their importance varied with gender and age. The top five contributing factors were education level, staying up late, annual family income level, sedentary time and marital status in young women, and staying up late, smoking, annual family income level, sedentary time and drinking in young men. The top five contributing factors were education level, annual family income level, passive exposure to smoking, staying up late, and sedentary time in middle-aged women, and annual family income level, education level, sedentary time, staying up late and drinking in middle-aged men. The top five contributing factors were annual family income level, passive exposure to smoking, sedentary time, marital status, and smartphone use in elderly women, and education level, annual family income level, smoking, smartphone use and sedentary time in elderly men. Conclusions:There are gender specific differences in the distribution of FI in Shaanxi. The prevalence of frailty increased with age, but young and middle-aged people also have frailty risk. The prevalence of frailty in young men was mainly related to unhealthy life behaviors, such as staying up late, smoking, sedentary behavior and drinking, while the prevalence of frailty in middle-aged and elderly men and women were more affected by sociodemographic factors, such as education level, economic status and marital status.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

ABSTRCT AIM:To verify the effect of polygona-tum polysaccharide(PSP)combined with TGF-β3 in inducing the differentiation of rat tendon-derived stem cells(TDSCs)into chondrocytes by activating the TGF-β3/Smad2 pathway.METHODS:TDSCs were extracted from rat tail tendons using enzyme digestion,purified,passaged,and identified via flow cytometry.TDSCs were treated with different concentrations of PSP,and the optimal growth con-centration was determined using the CCK-8 assay.TDSCs were divided into four groups:PSP,TGF-β3,PSP+TGF-β3,and Control for differentiation induc-tion.Chondrogenic differentiation was evaluated using morphological observations,toluidine blue staining,immunofluorescence staining,and West-ern blot analysis to detect COLⅡ,SOX9,and AGG.Western blot was also used to measure the expres-sion levels of Smad2 and p-Smad2 to evaluate the activation of the TGF-β3/Smad2 pathway after chondrogenic induction.RESULTS:Flow cytometry analysis showed that TDSCs highly expressed CD90 and CD29,while CD11b and CD45 expression was low.The CCK-8 assay indicated that 5 μmol/L PSP was the optimal intervention dose.Toluidine blue staining revealed that the blue staining area in the PSP,PSP+TGF-β3,and TGF-β3 groups was larger compared to the Control group.Immunofluores-cence analysis demonstrated that COLⅡ expression was significantly increased in the PSP,TGF-β3,and PSP+TGF-β3 groups,with the highest expression in the PSP+TGF-β3 group(P＜0.05).Western blot analy-sis showed that the levels of p-Smad2/Smad2,COLⅡ,SOX9,and AGG were elevated in the PSP,TGF-β3,and PSP+TGF-β3 groups,with the highest ex-pression in the PSP+TGF-β3 group(P＜0.05).Compared to the Control group,the TGF-β3 and PSP groups also showed significantly increased expression(P＜0.05).CONCLUSION:PSP promotes the proliferation and chondrogenic differentiation of TDSCs,possibly by activating the TGF-β3/Smad2 pathway.