Objective: To explore the relationship between snack consumption and depressive symptoms in first year junior high school students with different left behind experiences in Yunnan Province, so as to provide a basis for improving depressive symptoms among first year junior high school students with different left behind experiences. Methods: From October to December 2022,a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County) in Yunnan Province for a questionnaire survey. The Chinese version of Depression Anxiety Stress Scale-21 was applied to assess depressive symptoms in first year junior high school students, and snack consumption was collected by employing food frequency questionnaire. The generalized linear model was used to analyze the association between first year junior high school students snack consumption and depressive symptoms, and the analysis was stratified according to left behind experience. Results: The detection rates of depressive symptoms among firstyear junior high school students with and without left behind experience were 36.25% and 26.91%, respectively. After controlling for confounding variables, the generalized linear model analysis showed that sweet snacks ( β=0.16, 95%CI =0.07-0.25), fast food ( β=0.14, 95%CI =0.04-0.23) and carbonated drinks ( β=0.09, 95%CI =0.01-0.17) of first year junior high school students with left behind experience (all P <0.05). Compared with those without such behavior, the risk of depressive symptoms was higher in consumption of fast food ( β=0.13, 95%CI =0.07-0.18) and carbonated drinks ( β=0.10, 95%CI =0.06-0.15)among first year junior high school students without left behind experience (both P <0.05). Conclusion Snack consumption among first year junior high school students in Yunnan may increase the risk of developing depressive symptoms, while first year junior high school students with left behind experience may have a greater risk of developing depressive symptoms.

ObjectiveTo analyze the output and efficiency of chronic disease management services for hypertension and diabetes in community health service institutions in Shanghai, to evaluate the allocation and efficiency of chronic disease management resources, and to provide references for improving the efficiency of chronic disease management in Shanghai’s communities. MethodsA total of 73 community health institutions from 15 districts of Shanghai were selected. Based on the chronic disease management resource data of community health institutions in 2019, 2021, and 2023, descriptive methods and the BCC model in Data Envelopment Analysis (DEA) were used to analyze the resource allocation, service output, and the efficiency of chronic disease management services in community health institutions in Shanghai. ResultsFrom 2019 to 2023, the indicators of resource allocation and service output of community health service institutions in Shanghai all showed upward trends. In terms of service efficiency, the average number of chronic disease patients managed by each health technician decreased from 237 to 231, and the number of patients served per 1 000 working hours decreased from 54 to 44. DEA efficiency analyses showed that the average overall efficiency increased from 0.867 in 2019 to 0.886 in 2021 and then decreased to 0.811 in 2023. The average technical efficiency decreased from 0.901 to 0.847, which was the main reason for the decline in overall efficiency. The average scale efficiency showed an initial increase followed by a decrease, rising from 0.961 in 2019 to 0.977 in 2021 and dropping back to 0.955 in 2023. The number of strong effective districts (overall efficiency=1.000) decreased from 6 in 2019 to 3 in 2023, and the efficiency differences between districts expanded. The range of overall efficiency widened from 0.622‒1.000 to 0.513‒1.000, indicating a decline in overall efficiency and an increase in inter-district heterogeneity. ConclusionFrom 2019 to 2023, the total volume of resource allocation and service output for chronic disease management in community health service institutions in Shanghai increased continuously. However, both the service output efficiency and the overall resource allocation efficiency declined, driven primarily by a decrease in technical efficiency, and accompanied by widening inter‑district disparities.

With the rapid development of artificial intelligence(AI),how to digitize the teaching of Medical Immunology is a new challenge posed by the times and education.This study is based on the advanced teaching model of Medical Immunology,which includes lectures-PAD class-flipped classrooms-expert lecture.By introducing knowledge mapping and AI teaching assistant into the entire learning process,the students not only deepen their understanding of the knowledge system of Medical Immunology,but also ex-ercise their ability to apply immunological knowledge to solve practical clinical problems,enhance their self-learning ability,expres-sion ability,communication ability,on-site performance ability,and cultivate a spirit of unity,cooperation,and exploration.The practice of empowering Medical Immunology teaching with digital intelligence achieves the integration of theory and application,the linkage between in class and out of class teaching,the connection between commonalities and individualities,and the union of abili-ties and qualities in Medical Immunology teaching.It also provides practical basis for exploring the implementation path of digital intel-ligence empowerment in Medical Immunology teaching.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To understand the workflow and key tasks of the transformation of scientific and technological achievements in public hospitals,and propose optimization strategies from the perspective of managers.Methods:Based on the research method of Grounded Theory,semi-structured interviews were conducted among 23 managers of scientific and technological achievements transformation in public hospitals,and relevant concepts and categories were summarized by three stages coding with NVivo 12.Results:Through the three stages of coding,64 initial concepts,19 categories and 4 main categories were sorted out,and a framework diagram of the process of transforming scientific and technological achievements in public hospitals covering four stages was constructed.Conclusion:The scientific and technological achievements of public hospitals can be divided into four phases:project initiation and demand docking,research and development process and achievements incubation,achievements transformation and market docking,product promotion and industrial development,which can be used to achieve high-quality development of scientific and technological achievements through standardized management of the whole process,excavation of high-quality results,enhancement of humanistic construction,accumulation of scientific research experience,and standardization of qualification of technological managers.

Background and Aims:Mucinous adenocarcinoma of the colorectum(MAC)is a distinct histologic subtype of colorectal cancer characterized by high malignancy and low diagnostic accuracy of preoperative biopsy,posing challenges for clinical decision-making.Given the critical role of the inflammatory microenvironment in tumor progression,this study aimed to develop and validate a nomogram model integrating preoperative systemic inflammatory indicators and clinical features to improve the preoperative diagnosis of MAC.Methods:Clinical data of 293 patients with colorectal cancer who underwent radical resection between June 2017 and June 2022 at the First Affiliated Hospital of the University of South China were retrospectively analyzed.Based on postoperative pathology,patients were classified into the mucinous adenocarcinoma(MAC)group and the non-specific adenocarcinoma(AC)group.Propensity score matching(PSM,1∶1)was used to balance age,T stage,and N stage.Differences in preoperative inflammatory indices were compared between groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MAC,which were incorporated into a diagnostic nomogram.The model's discrimination,calibration,and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration plots,and decision curve analysis(DCA).Results:Among the 293 patients,46 had MAC and 247 had AC,with a preoperative colonoscopic diagnostic rate of 54%for MAC.After PSM(43 pairs),platelet count,platelet lymphocyte ratio(PLR),systemic immune inflammation index(SII),inflammation related prognostic index(IPI),and systemic inflammation score(SIS)were significantly higher in the MAC group,while lymphocyte monocyte ratio(LMR)was lower(all P<0.05).Multivariate analysis identified tumor location,maximum tumor diameter,and preoperative IPI as independent predictors.The AUCs of the nomogram in the training(n=206)and validation(n=87)cohorts were 0.759(95%CI=0.662-0.856)and 0.776(95%CI=0.649-0.903),respectively.Calibration plots showed good agreement between predicted and observed probabilities,and DCA demonstrated satisfactory clinical applicability.Conclusion:A nomogram model integrating tumor location,tumor size,and preoperative IPI was successfully developed and validated for preoperative diagnosis of colorectal MAC.This model provides a practical,quantitative tool with good predictive performance to assist clinicians in individualized treatment planning,particularly for patients ineligible for surgical biopsy.

Objective:To explore the expression of bone marrow stromal antigen 2(BST2)in advanced non-small cell lung cancer(NSCLC)tissues and its impact on the prognosis of cisplatin chemotherapy.Methods:This study was a prospective study,127 advanced NSCLC patients who received treatment at Shangrao People's Hospital from January 2022 to December 2023 were prospective selected,all patients received cisplatin+gemcitabine chemotherapy regimen.They were divided into survival group(n=85)and death group(n=42)according to the prognosis.The relationship between expression of BST2 and clinicopathological characteristics was analyzed.The survival situation was analyzed by Kaplan-Meier method.Influencing factors of prognosis after cisplatin chemotherapy were discussed by univariate and multivariate COX regression analyses.Results:The positive expression rate of BST2 in cancer tissues(34.65％)in advanced NSCLC tissues was significantly higher than that in adjacent tissues(7.09％)(P＜0.05).Expression of BST2 was associated with tumor TNM staging,lymph node metastasis and differentiation degree(P＜0.05).The 1-year survival rate of patients with high expression of BST2(56.98％)was significantly lower than that of patients with low expression(87.80％)(P＜0.05).High expression of BST2 and TNM stage Ⅳ were independent prognostic risk factors for cisplatin chemotherapy in patients with advanced NSCLC(P＜0.05).Conclusion:The expressed of BST2 is highly in patients with advanced NSCLC tissues and closely related to cisplatin chemotherapy poor prognosis,suggesting its potential as a prognostic biomarker.

Background and Aims:Mucinous adenocarcinoma of the colorectum(MAC)is a distinct histologic subtype of colorectal cancer characterized by high malignancy and low diagnostic accuracy of preoperative biopsy,posing challenges for clinical decision-making.Given the critical role of the inflammatory microenvironment in tumor progression,this study aimed to develop and validate a nomogram model integrating preoperative systemic inflammatory indicators and clinical features to improve the preoperative diagnosis of MAC.Methods:Clinical data of 293 patients with colorectal cancer who underwent radical resection between June 2017 and June 2022 at the First Affiliated Hospital of the University of South China were retrospectively analyzed.Based on postoperative pathology,patients were classified into the mucinous adenocarcinoma(MAC)group and the non-specific adenocarcinoma(AC)group.Propensity score matching(PSM,1∶1)was used to balance age,T stage,and N stage.Differences in preoperative inflammatory indices were compared between groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MAC,which were incorporated into a diagnostic nomogram.The model's discrimination,calibration,and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration plots,and decision curve analysis(DCA).Results:Among the 293 patients,46 had MAC and 247 had AC,with a preoperative colonoscopic diagnostic rate of 54%for MAC.After PSM(43 pairs),platelet count,platelet lymphocyte ratio(PLR),systemic immune inflammation index(SII),inflammation related prognostic index(IPI),and systemic inflammation score(SIS)were significantly higher in the MAC group,while lymphocyte monocyte ratio(LMR)was lower(all P<0.05).Multivariate analysis identified tumor location,maximum tumor diameter,and preoperative IPI as independent predictors.The AUCs of the nomogram in the training(n=206)and validation(n=87)cohorts were 0.759(95%CI=0.662-0.856)and 0.776(95%CI=0.649-0.903),respectively.Calibration plots showed good agreement between predicted and observed probabilities,and DCA demonstrated satisfactory clinical applicability.Conclusion:A nomogram model integrating tumor location,tumor size,and preoperative IPI was successfully developed and validated for preoperative diagnosis of colorectal MAC.This model provides a practical,quantitative tool with good predictive performance to assist clinicians in individualized treatment planning,particularly for patients ineligible for surgical biopsy.

Objective:To explore the expression of bone marrow stromal antigen 2(BST2)in advanced non-small cell lung cancer(NSCLC)tissues and its impact on the prognosis of cisplatin chemotherapy.Methods:This study was a prospective study,127 advanced NSCLC patients who received treatment at Shangrao People's Hospital from January 2022 to December 2023 were prospective selected,all patients received cisplatin+gemcitabine chemotherapy regimen.They were divided into survival group(n=85)and death group(n=42)according to the prognosis.The relationship between expression of BST2 and clinicopathological characteristics was analyzed.The survival situation was analyzed by Kaplan-Meier method.Influencing factors of prognosis after cisplatin chemotherapy were discussed by univariate and multivariate COX regression analyses.Results:The positive expression rate of BST2 in cancer tissues(34.65％)in advanced NSCLC tissues was significantly higher than that in adjacent tissues(7.09％)(P＜0.05).Expression of BST2 was associated with tumor TNM staging,lymph node metastasis and differentiation degree(P＜0.05).The 1-year survival rate of patients with high expression of BST2(56.98％)was significantly lower than that of patients with low expression(87.80％)(P＜0.05).High expression of BST2 and TNM stage Ⅳ were independent prognostic risk factors for cisplatin chemotherapy in patients with advanced NSCLC(P＜0.05).Conclusion:The expressed of BST2 is highly in patients with advanced NSCLC tissues and closely related to cisplatin chemotherapy poor prognosis,suggesting its potential as a prognostic biomarker.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.