Objective To analyze the infection status and epidemic trends of soil-borne nematode infections in Yubei, Chongqing City, in 2010,2021, and 2022. Methods The local populations from four survey sites of four towns in 2010 and five sites of five towns in 2021 and 2022 were surveyed regarding their basic information using a unified form. Fecal samples of the participants were collected and tested for soil-borne nematode infections using the modified Kato-Katz thick smear method. Results In 2010, 2 049 participants were surveyed, followed by 1 000 participants in 2021 and 2022. The overall prevalence of parasitic infections declined significantly from 3.86% to 0.20%. In 2010, soil-transmitted nematode included hookworms(3.81%) and roundworms(0.29%). In 2021, the infection rates of roundworms and hookworms were 1.70% and 0.10% respectively. Notably, only Ascaris was identified in 2022(0.20%). The≥60 age group consistently exhibited the highest infection rates across all surveys, followed by the 40-59 age group. The infection rates of males in the three surveys were 3.31%,1.92%, and 0.20% respectively, and those of females were 4.37%, 1.46%, and 0.20% respectively. There was no statistically significant difference in the infection rates between males and females. Educational attainment was inversely associated with infection; in 2010, the highest prevalence was observed among those with primary education or below, whereas in 2021, illiterate or semi-literate individuals showed the highest susceptibility. The occupational distribution of infections in 2010 indicated that retirees (8.33%), farmers(4.86%), and homemakers or unemployed individuals(3.45%)were the most affected. However, in 2021 and 2022, farmers emerged as the predominant occupational group with soil-transmitted nematode infections. Conclusions The infection rate of soil-borne nematodes showed a decreasing trend in Yubei, and the infection species changed from hookworms in 2010 to Ascaris in 2022. Farmers, the elderly, and people with low education levels should continue to be the focus of preventive and control efforts.

Objective: To analyze the epidemiological characteristics of hand, foot and mouth disease (HFMD) among children aged 0-9 years in Guangzhou, so as to provide reference basis for further exploring scientifically effective prevention and control measures. Methods: Reported cases of HFMD in children aged 0-9 years in Guangzhou City from 2013-2025 were selected from China disease prevention and control information system, and the incidence in different years was analyzed descriptively; the trends of the composition ratio and incidence in various age groups were analyzed by using the Joinpoint regression model, spatial autocorrelation analyses were performed at the district level, and the seasonal autoregressive integrated moving average model (SARIMA) was applied to predict annual incidence rate for 2026. Results: From 2013 to 2025, the average annual reported incidence rate of HFMD among children aged 0-9 years in Guangzhou was 2 513.98/100 000, showing a fluctuating trend. Peaks of incidence occurred from May to July and from September to October. The male to female ratio was 1.49∶1. The average annual incidence rate was 4 743.99/100 000 in the 0-1 years age group, 3 298.19/100 000 in the 2-5 years age group, and 544.22/ 100 000 in the 6-9 years age group. Joinpoint regression analysis showed a decreasing trend in the proportion of the 0-1 years age group (APC= -6.02 %, t =-3.77) and an increasing trend in the proportion of the 6-9 years age group (APC=16.39%, t =5.67) (both P < 0.05 ). No significant global spatial clustering was observed at the district level; however, local scattered clusters were identified in certain areas. Using the SARIMA(2,0,0)(2,0,0) 12 model, the predicted annual incidence rate of HFMD among children aged 0-9 years in Guangzhou in 2026 was 2 680.56/100 000. Conclusions From 2013 to 2025, the annual incidence rate of HFMD among children aged 0-9 years in Guangzhou exhibited a fluctuating trend; the highest incidence rate is observed in the 0-1 years age group, while the proportion of cases in the 6-9 years age group increase year by year;and local spatial clusters of abnormal distribution are identified. It is essential to enhance risk monitoring and health education in key populations and areas to mitigate the risk of infection in children.

Objective: To examine the effects of combined aerobic and resistance exercise on health related physical fitness (HPF) and depressive symptoms among senior high school freshmen, and to examine whether HPF mediates the relationship between exercise intervention and depressive symptoms, so as to provide a scientific basis for the coordinated promotion of mental health and physical fitness in schools. Methods: In March 2022, 190 senior high school freshmen from a secondary school of Suzhou in Anhui Province were selected by the random cluster sampling method and randomly assigned to an intervention group ( n = 99) and a control group ( n =91). The control group maintained routine activities, while the intervention group underwent a 10 week combined aerobic and resistance exercise program, three sessions per week, 40 minutes per session. Height, weight, standing long jump, sit ups, 20 m shuttle run, and sit and reach were measured before and after the intervention. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale (CES-D). Analysis of covariance (ANCOVA), Mann-Whitney U test, and Wilcoxon test were employed to compare outcomes before and after the intervention, and mediation analysis was conducted. Results: After controlling for pre test scores, ANCOVA results showed that compared with the control group, the intervention group demonstrated the following post intervention changes: a lower body mass index of 0.1 kg/m 2 among girls; higher standing long jump (13.2 cm for boys, 7.4 cm for girls), higher sit ups (5.5 reps for boys, 3.7 reps for girls), higher 20 m shuttle run (7.4 times for boys, 5.1 times for girls), and higher sit and reach (3.2 cm for boys, 0.4 cm for girls) ( F =17.88-84.44); and lower CES-D scores (5.5 for boys, 4.0 for girls) ( Z =-2.51, -2.06) (all P <0.05). The indirect effect of HPF in the relationship between combined aerobic and resistance exercise and depressive symptoms was -2.11, supporting a partial mediation effect ( P < 0.01 ). Conclusions Combined aerobic and resistance exercise improves HPF and alleviates depressive symptoms to varying degrees among senior high school freshmen. HPF served as a partial mediator through which exercise intervention reduces depressive symptoms.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

AIM To investigate the ameliorative effects of Compound Fufangteng Mixture(CFM)on cyclophosphamide(CTX)-induced immunosuppression in mice.METHODS Forty-eight male C57BL/6J mice were randomly divided into the blank control group,the model group,the levamisole hydrochloride group(40 mg/kg)and the low-dose,medium-dose and high-dose CFM groups(3.75,7.5,10 g/kg),with 8 mice in each group,and given respective intervention orally once daily for 14 days.On the 5th to 7th day of administration,with the blank control group given normal saline intraperitoneally,the other groups underwent intraperitoneal CTX injections(80 mg/kg).24 hours after the last administration,organ indices of thymus and spleen were calculated;splenic histopathological alterations were assessed by HE staining;serum levels of IL-2,IL-6 and IgG were quantified using ELISA;splenic CD4+,CD8+T lymphocytes,alongside CD86+and CD206+macrophages populations were analyzed by flow cytometry;and splenic expression of CD4,CD8 and F4/80 was evaluated by immunohistochemical staining.RESULTS In CTX-treated mice,CFM administration mitigated body weight loss;enhanced thymus weight and thymic index;ameliorated splenic immune cell populations,elevated serum levels of cytokines IL-2,IL-6 and IgG in serum;and upregulated splenic levels of CD45+CD3+T lymphocytes and F4/80+CD11b+macrophages,alongside increasing the expression of CD4,CD8 and F4/80 surface markers.CONCLUSION CFM alleviates CTX-induced immunosuppression state in mice by modulating immune cells,restoring immune function and enhancing anti-inflammatory and tissue repair capabilities.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

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.