Objective: To investigate the prevalence and associated factors of depressive symptoms among junior and senior high school students in Beijing from 2019 to 2023, in order to provide a scientific basis for interventions targeting high risk groups. Methods: From 2019 to 2023, a stratified cluster random sampling method was used to select 88 927 junior and senior high school students from 16 districts in Beijing. The Center for Epidemiologic Studies Depression Scale(CES-D) was conducted to assess depressive symptoms. The Chi square test was used to compare the detection rates of depressive symptoms among different student groups, and the trend Chi square test was employed for trend analysis of detection rates across the years. Multivariate Logistic regression analysis was applied to examine the association between the detection of depressive symptoms and related factors among junior and senior high school students. Results: From 2019 to 2023, the prevalence rates of depressive symptoms among junior and senior high school students in Beijing were 20.45%, 18.19%, 16.64%, 17.89% and 18.17%, respectively, with an overall downward trend ( χ 2 trend =27.51, P <0.01). Multivariate Logistic regression analysis revealed that after adjusting for gender, monitoring year, educational stage,family structure,boarding status and has taken a medical leave of absence in the past year unhealthy dietary behaviors ( OR=1.80, 95%CI =1.73-1.87), physical inactivity ( OR=1.24, 95%CI =1.19-1.29), try smoking ( OR=1.46, 95%CI =1.35-1.58), try alcohol( OR=1.96, 95%CI =1.88-2.05), Internet addiction ( OR=3.88, 95%CI =3.57-4.22), and adverse ear related behavior ( OR=1.82, 95%CI =1.71-1.93) were all associated with an increased risk of depressive symptoms among junior and senior high school students (all P <0.05). Conclusions The prevalence depression symptoms among middle school students in Beijing showed a fluctuating downward trend from 2019 to 2023. Targeted interventions should be adopted to reduce the occurrence of depression symptoms among junior and senior high school students.

Objective: To understand the trends of classroom lighting and illumination of primary and secondary schools in Beijing from 2016 to 2023, so as to provide a scientific basis for targeted improvement measures. Methods: A sampling survey was conducted on the lighting and illumination indicators of 8 390 classrooms in primary and secondary schools in Beijing from 2016 to 2023. The survey included classroom daylight factor, window to floor area ratio, average illuminance and illuminance uniformity on the desks, average illuminance and illuminance uniformity on blackboards, as well as classroom lighting and blackboard illumination sources. Intergroup comparisons were performed using the Kruskal-Wallis H test and the Chi square test, and Spearman correlation analysis was used to examine the trend of classroom lighting and illumination changes. Results: Except the window to floor area ratio, the measured values and compliance rates of all lighting and illumination indicators showed an overall upward trend from 2016 to 2023 (daylight factor r = 0.27, χ 2 trend =206.80, average illuminance on the desk surface r =0.30, χ 2 trend =87.97, illuminance uniformity on the desk surface r =0.14, χ 2 trend =73.59, average illuminance on the blackboard r =0.33, χ 2 trend =477.43, illuminance uniformity on the blackboard r = 0.09, χ 2 trend =50.76) (all P ＜0.01). The lighting and illumination indicators of classrooms (included classroom daylight factor, average illuminance and illuminance uniformity on the desks, average illuminance and illuminance uniformity on blackboards) in urban schools, primary schools, and secondary schools from 2016 to 2023 showed an upward trend (urban r =0.23-0.40, χ 2 trend =88.66-392.18; primary school r =0.12-0.36, χ 2 trend =39.50-281.44; secondary schools r =0.06-0.31, χ 2 trend =11.79-213.73) (all P ＜ 0.01 ). The illuminance uniformity on the blackboard in suburban schools showed a downward trend ( r = -0.09, χ 2 trend =31.53, both P ＜0.01). The illuminance uniformity on the desk surface in suburban schools showed no significant change ( r =0.03, χ 2 trend =1.23, both P ＞0.05). The other indicators showed an upward trend (daylight factor r =0.28, χ 2 trend =40.69, average illuminance on the desk surface r =0.24, χ 2 trend =16.35, average illuminance on the blackboard r =0.25, χ 2 trend =118.05, all P ＜0.01). The trends of classroom and blackboard illumination sources were that fluorescent lamps decreased year by year and LED lamps increased by year (classroom illumination sources χ 2 trend =1 059.82, blackboard illumination sources χ 2 trend =1 070.25, both P ＜0.01). Conclusions The classroom lighting and illumination in primary and secondary schools in Beijing has shown an overall improving trend from 2016 to 2023. However, problems remain, such as limited improvement of illuminance uniformity indicators, late start and poor effect of reconstruction in suburban schools. Further improvements are still needed.

Objective To explore the influencing factors of the construction of public hospital management accounting system,and to construct artificial intelligence models for predictive research,and to achieve software transformation in the later stage for automated evaluation of management accounting in different hospitals.Methods The indicators of management account-ing system were improved through literature analysis and Delphi method,and quantitative scoring standards were established.The automatic prediction of system indicators was realized by building an artificial intelligence model,and the effect of the model was evaluated.The way of software transformation was discussed.Results The coordination coefficient of Kendal in the two rounds of Delphi method questionnaires reached the requirements(P＜0.05),and 6 primary indicators and 23 secondary impact indica-tors were determined.The artificial intelligence model is well modeled,and the area under the Receiver operating characteristic is 0.959,P＜0.001,with high accuracy.Conclusion The index system can provide reference for the monitoring of the daily work of management accounting in public hospitals.Through the establishment of artificial intelligence model,it can be used to evaluate the construction level of management accounting system in different hospitals and provide artificial intelligence automation support.

Purpose To investigate the functional connectivity(FC)pattern between the bilateral lower limb sensorimotor cortex(LSM)and the whole brain in type 2 diabetic peripheral neuropathy(DPN).Materials and Methods A total of 44 DPN patients and 43 healthy controls admitted to Shaanxi Provincial People's Hospital from February 2021 to December 2022 were enrolled prospectively and underwent neuropsychological assessment and resting-state fMRI scans.Using bilateral LSM as the regions of interest,the differences of bilateral LSM and whole brain FC between DPN patients and healthy controls were compared.FC in different brain areas were extracted and correlated with clinical/neuropsychological scores.Results Compared with healthy controls,DPN patients had reduced FC of the LSM with the right cerebellar lobule Ⅵ,the right lateral occipitotemporal cortex,the bilateral rostral prefrontal cortex and the bilateral anterior cingulate gyrus.The FC between LSM and right cerebellar Ⅵ in DPN patients were significantly negatively correlated with fasting blood glucose(r=-0.490,P=0.001).The FC between LSM and bilateral anterior cingulate gyrus in DPN patients were significantly positively correlated with Montreal cognitive assessment scores(r=0.479,P=0.001).Conclusion Abnormal FC between LSM and multiple brain regions,suggesting that DPN may have extensive effects on brain regions that maintain motion and motor control function in type 2 diabetes mellitus patients.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective To explore the influencing factors of the construction of public hospital management accounting system,and to construct artificial intelligence models for predictive research,and to achieve software transformation in the later stage for automated evaluation of management accounting in different hospitals.Methods The indicators of management account-ing system were improved through literature analysis and Delphi method,and quantitative scoring standards were established.The automatic prediction of system indicators was realized by building an artificial intelligence model,and the effect of the model was evaluated.The way of software transformation was discussed.Results The coordination coefficient of Kendal in the two rounds of Delphi method questionnaires reached the requirements(P＜0.05),and 6 primary indicators and 23 secondary impact indica-tors were determined.The artificial intelligence model is well modeled,and the area under the Receiver operating characteristic is 0.959,P＜0.001,with high accuracy.Conclusion The index system can provide reference for the monitoring of the daily work of management accounting in public hospitals.Through the establishment of artificial intelligence model,it can be used to evaluate the construction level of management accounting system in different hospitals and provide artificial intelligence automation support.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

In recent years,our understanding of neutrophil extracellular traps(NETs)has been deepened with advancements in technology.Extensive research has demonstrated that NETs are intricately linked to autoimmunity and contribute to the path-ogenesis of autoimmune diseases through multiple mechanisms,such as serving as a source of self-antigens,activating the com-plement system,or modulating other immune cells.Notably,the interaction between NETs and immune cells plays a critical role in disease progression.This article primarily reviews the relationship of NETs with dendritic cells,macrophages,B cells,and CD4 T cells in autoimmune diseases,providing insights into potential therapeutic strategies by NETs level modulation and NETs-immune cell interactions intervenion.

Objective To analyze in depth the job satisfaction and influencing factors of medical staff in tertiary public hospitals in Gansu Province,especially to explore the important factors affecting the survival and development of hospitals as core talents,in order to provide reference for promoting the stable development of medical staff in medical institutions in Gansu Prov-ince.Methods From July to October 2024,a random sampling method was used to select relevant personnel from tertiary public hospitals in Gansu Province for a questionnaire survey.Descriptive analysis were conducted on the collected data.Multivariate lo-gistic regression analysis was used to identify the main influencing factors of job satisfaction among medical staff.The difference is statistically significant with P＜0.05,and the test level is α=0.05.Results 1 890 questionnaires were distributed and 1 885 valid questionnaires were collected,with an effective rate of 99.74％.The overall job satisfaction score of medical staff in tertiary hospitals in Gansu Province is 3.06±0.86,which is at a moderate level.Hospitals can consider improving management models,establishing scientific,reasonable,and humane management systems,enhancing doctors'sense of belonging,and improving sat-isfaction;The satisfaction brought by salary to medical staff is higher than promotion opportunities and career development,indi-cating that a reasonable salary incentive system in hospitals,with excellent performance and compensation,can increase doctors'subjective well-being and improve satisfaction.Optimising the allocation of health human resources and appropriately in creasing personnel allocation based can help improve doctors'job satisfaction.Conclusion The overall job satisfaction of medical staff in tertiary hospitals in Gansu Province is generally satisfactory,and there are statistically significant differences in job satisfaction a-mong medical staff with different work experience,education level and monthly income(P＜0.05).When formulating policies and measures,the government pays attention to factors that affect the job satisfaction of medical personnel,optimizes the alloca-tion of health human resources,continuously improves incentive mechanisms,and improves hospital management models,enhan-cing the job satisfaction of medical staff and laying the foundation for promoting the developmrnt of provincial health talent team.

Purpose To investigate the functional connectivity(FC)pattern between the bilateral lower limb sensorimotor cortex(LSM)and the whole brain in type 2 diabetic peripheral neuropathy(DPN).Materials and Methods A total of 44 DPN patients and 43 healthy controls admitted to Shaanxi Provincial People's Hospital from February 2021 to December 2022 were enrolled prospectively and underwent neuropsychological assessment and resting-state fMRI scans.Using bilateral LSM as the regions of interest,the differences of bilateral LSM and whole brain FC between DPN patients and healthy controls were compared.FC in different brain areas were extracted and correlated with clinical/neuropsychological scores.Results Compared with healthy controls,DPN patients had reduced FC of the LSM with the right cerebellar lobule Ⅵ,the right lateral occipitotemporal cortex,the bilateral rostral prefrontal cortex and the bilateral anterior cingulate gyrus.The FC between LSM and right cerebellar Ⅵ in DPN patients were significantly negatively correlated with fasting blood glucose(r=-0.490,P=0.001).The FC between LSM and bilateral anterior cingulate gyrus in DPN patients were significantly positively correlated with Montreal cognitive assessment scores(r=0.479,P=0.001).Conclusion Abnormal FC between LSM and multiple brain regions,suggesting that DPN may have extensive effects on brain regions that maintain motion and motor control function in type 2 diabetes mellitus patients.