Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

Various therapeuti modailities have been engineered for lung cancer treatment, but their clinic application is severely impeded by the poor therapy efficiency and immunosuppressive microenvironment. Herein, we fabricated a library of small molecule redox-labile nanoparticles (NPs) (i.e., diPTX-2C NPs, diPTX-2S NPs, and diPTX-2Se NPs) by the self-assembly of dimer paclitaxel (PTX) prodrug, and then utilized these NPs with the traditional Chinese medicine (TCM) Qi-Yu-San-Long-Fang (Q) for effective chemoimmunotherapy on Lewis lung carcinoma (LLC)-bearing mice models. Under the high concentration of glutathione (GSH) and H₂O₂, diPTX-2Se NPs could specifically release PTX in cancer cells and exert a higher selectivity and toxicity than normal cells. In LLC tumor-bearing mice, oral administration of Q not only effectively downregulated programmed death ligand-1 (PD-L1) expression, but also remodeled the immunosuppressive tumor immune microenvironment via the increase of CD4⁺ T and CD8⁺ T cell proportion and the repolarization of M2 into M1 macrophages in tumor tissues, collectively achieving superior synergistic treatment outcomes in combination with intravenous PTX prodrug NPs. Besides, we found that the combination regimen also demonstrated excellent chemoimmunotherapeutic performances on low-dose small established tumor and high-dose large established tumor models. This study may shed light on the potent utilization of Chinese and Western-integrative strategy for efficient tumor chemoimmunotherapy.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

OBJECTIVE To establish management index system for rational drug use of key monitoring drugs， and provide reference for the management of key monitoring drugs in the hospitals. METHODS First， the management index system for rational drug use of key monitoring drugs was drafted by collecting the evidence from related medical literature. Next， using a modified Delphi method， twenty experienced experts from the fields of pharmacy， medical practice， healthcare insurance， and finance were selected to participate in two rounds of questionnaire consultations. Based on the expert enthusiasm coefficient， authority coefficient， degree of opinion concentration， and degree of coordination， the final indicators were determined to establish a management index system for rational drug use of key monitored drugs in medical institutions. RESULTS The expert enthusiasm coefficients reached 100% in both rounds of consultation. In first-level， second-level and third-level indicators， the authority coefficients of experts were 0.89， 0.86 and 0.87， and coordination coefficients of the experts in importance score were 0.300 （P＜ 0.05）， 0.125 （P＜0.05） and 0.139 （P＜0.05）， respectively. The average score for the importance of all indicators reached over 3.5， in which the full score ratio ranged from 35% to 100%. Except that the variation coefficient of a third-level indicator “number of specifications purchased for key monitored drugs” was 0.26， the variation coefficients of rest indicators were less than or equal to 0.25. Based on the results of expert consultation， final version of the management index system established in this study， including two first-level indicators （drug procurement and use， and rational drug use）， five second-level indicators （such as the accessibility， cost-effectiveness） and twenty third-level indicators （such as the number of specifications purchased for key monitored drugs， the increase in the cost of key monitored drugs）. CONCLUSIONS The management index system established in this study possesses high reliability and strong operability， and may provide a reference for the management of key monitoring drugs in the hospitals.

Alzheimer's disease (AD) is a common neurodegenerative disorder among the elderly, and BuChE has emerged as a potential therapeutic target. In this study, we reported the development of compound 8e, a selective reversible BuChE inhibitor (eqBuChE IC₅₀ = 0.049 μmol/L, huBuChE IC₅₀ = 0.066 μmol/L), identified through extensive virtual screening and lead optimization. Compound 8e demonstrated favorable blood-brain barrier permeability, good drug-likeness property and pronounced neuroprotective efficacy. Additionally, 8e exhibited significant therapeutic effects in zebrafish AD models and scopolamine-induced cognitive impairments in mice. Further, 8e significantly improved cognitive function in APP/PS1 transgenic mice. Proteomics analysis demonstrated that 8e markedly elevated the expression levels of very low-density lipoprotein receptor (VLDLR), offering valuable insights into its potential modulation of the Reelin-mediated signaling pathway. Thus, compound 8e emerges as a novel and potent BuChE inhibitor for the treatment of AD, with significant implications for further exploration into its mechanisms of action and therapeutic applications.

Objective : To investigate the factors affecting the outcome of high-risk human papillomavirus ( HR- HPV) infection in patients with normal cervix examined by colposcopy in Hefei area and the relationship between persistent HR-HPV infection and cervical cytology． Methods : Data of colposcopy patients were collected from 478 HR-HPV infected patients with normal cervix through colposcopy．Their age，number of sexual partners，contracep- tive methods and other relevant basic information were recorded．Vaginal interferon use，HR-HPV infection at year 1 and year 2，and cervical liquid-based cytology test ( LCT) results were tracked，univariate and multivariate ana- lyses were performed based on basic information，and ROC curves were plotted． Results : The HR-HPV clearance rate at 1 year was 59. 41% ，and the clearance rate at 2 years was 66. 75%．The other 12 types of infection ( 31， 33，35，39，45，51，52，56，58，59，66，68) were more common than the 16 and 18 types．Univariate and mult- ivariate analyses showed that age＞50 years，number of sexual partners ≥2，and history of cervical conectomy in- creased the risk of persistent HR-HPV infection ( χge = 21. 676，P ＜0. 001; χumber of sexual partners = 8. 262，P =0. 004; χistory of cervical conectomy = 11. 267，P = 0. 001 ) ． The risk of HR-HPV infection was significantly lower when condom or vaginal interferon was used ( χondom use = 10. 885，P = 0. 001; χnterferon use = 4. 099，P = 0. 043) ．The area under the ROC curve (AUC) of combined diagnosis of HR-HPV persistent infection was higher than that of single diagnosis，and the AUC of combined diagnosis was 0. 737．Persistent HR-HPV infection was an independent risk factor for abnormal LCT，and the AUC predicted by the model was 0. 755．No cancer was found in patients with persistent HR-HPV infection for 2 years，and the proportion of abnormal LCT was higher than that in patients with negative HR-HPV．The difference was statistically significant ( χ2 = 39. 64，P＜0. 001) ． Conclusion The combined ROC model constructed for patients＞50 years old，with multiple sexual partners，history of cervical surgery， no vaginal interferon use，and no condom use has certain value in predicting persistent HR-HPV infection，and per- sistent HR-HPV infection has predictive value in predicting LCT abnormalities．

Objective To investigate the predictive value of combined radiomic features derived from chest CT scans with clinical characteristics for epidermal growth factor receptor(EGFR)gene mutations in non-small cell lung cancer(NSCLC).Methods A multi-center case-control study was conducted on the clinical data and CT images of 1 070 NSCLC patients from the radiology departments of the 3 medical institutions between January 2013 and October 2023.The 719 NSCLC patients from the First Affiliated Hospital of Army Medical University were randomly divided into a training set and an internal validation set in a ratio of 7∶3;The 173 patients in the Eastern Theatre General Hospital and the 178 patients in Army Medical Centre of PLA were assigned into the external validation set 1 and 2,respectively.Least absolute shrinkage and selection operator(LASSO)regression was employed to identify the optimal radiomic features,which were subsequently used to construct a radiomics model.Univariate and multivariate logistic regression analyses were applied to identify clinical features associated with EGFR mutation,thereby developing a clinical model.The radiomic and clinical features were subsequently combined to develop a comprehensive model.All the 3 classification models were built using random forest(RF)machine learning.The area under curve(AUC),accuracy,sensitivity and specificity were utilized to evaluate the predictive performance of the models.Calibration curve was plotted to assess the goodness of fit of the comprehensive model,while decision curve analysis was performed to assess the clinical utility of the model.Results The AUC value of the radiomics model was 0.762 4(95%CI:0.692 4～0.825 1),0.745 4(95%CI:0.671 1～0.814 3),and 0.724 7(95%CI:0.639 7～0.801 6),respectively,in the internal validation set,external validation set 1,and external validation set 2;The AUC value of the clinical prediction model was 0.691 7(95%CI:0.627 9～0.757 6),0.652 5(95%CI:0.576 7～0.729 1),and 0.779 2(95%CI:0.712 5～0.847 3),respectively in the above sets in turn;The comprehensive model constructed based on clinical features and radiomic features showed the best predictive efficacy,with an AUC value of 0.818 0(95%CI:0.757 7～0.874 3),0.782 4(95%CI:0.703 1～0.848 2),and 0.796 6(95%CI:0.718 1～0.868 6),respectively in the above sets.Calibration curve analysis indicated that the comprehensive model had a good fit,while decision curve analysis revealed that the model provided a favorable net benefit.Conclusion Our comprehensive model constructed based on chest CT radiomic features and clinical characteristics shows superior predictive performance for EGFR gene mutations in NSCLC across multiple center datasets,which may be helpful for clinical decision-making for treatment strategies.

Objective To evaluate the predictive value of deep learning features from chest CT images combined with clinical and radiomics features for epidermal growth factor receptor(EGFR)mutations in non-small cell lung cancer(NSCLC).Methods This case-control study retrospectively analyzed clinical and imaging data of 1 070 NSCLC patients from radiology departments at three hospitals(January 2013 to October 2023).Patients were divided into:a training set(n=502)and internal validation set(n=217)via 7∶3 randomization of 719 cases from the First Affiliated Hospital of Army Medical University;external validation set 1(n=173)from General Hospital of Eastern Theater Command;external validation set 2(n=178)from Daping Hospital of Army Medical University.Deep learning features were extracted using a 2.5D convolutional neural network(CNN)with ResNet101 backbone,radiomics features were derived from CT images,and clinical risk factors were identified to construct models.An integrated model combined deep learning,clinical,and radiomics features.All four models were developed using random forest(RF)classifiers.Calibration curves assessed goodness-of-fit,and decision curve analysis(DCA)evaluated clinical utility.Results The deep learning model achieved AUCs of 0.833 7(95%CI:0.770 6～0.884 7),0.815 1(0.741 6～0.882 8),and 0.810 1(0.745 2～0.873 6)in the internal and two external validation sets,respectively.Clinical models yielded AUCs of 0.731 0(0.660 2～0.802 1),0.746 0(0.666 4～0.824 9),and 0.813 4(0.743 1～0.883 6);radiomics models showed AUCs of 0.762 4(0.692 4～0.825 1),0.745 4(0.671 1～0.814 3),and 0.724 7(0.639 7～0.801 6).The integrated model demonstrated optimal performance with AUCs of 0.905 5(0.857 0～0.945 4),0.832 7(0.763 3～0.896 4),and 0.889 0(0.834 4～0.934 3).DCA indicated significant net benefit for EGFR prediction at threshold probabilities of 0.15～0.85 using the integrated model.Conclusion Deep learning features from CT images effectively predict EGFR mutation status in NSCLC.The integrated model combining deep learning,clinical,and radiomics features further enhances predictive performance.

Objective To investigate the common diseases and the causes of diseases in Chinese Antarctic researchers,so as to provide reference for the medical support.Methods Medical records of 1 127 people with injuries and diseases who participated in four Antarctic scientific expeditions(the 31st,35th,36th,and 39th time)were retrospectively analyzed.The causes of the injuries and diseases as well as the implications for nursing were investigated.Results The top 10 diseases in the four Antarctic expeditions were acute soft tissue injury,dermatomycosis,pharyngitis,insomnia,periodontitis,gastroenteritis,motion sickness,acute upper respiratory infection,primary hypertension,and frostbite.The causes of the diseases in the four Antarctic expeditions were analyzed,and the nursing of different diseases was proposed.Conclusion It is necessary to take preventive measures based on the characteristics of injuries and diseases during Antarctic expeditions,so as to effectively prevent and treat these diseases and provide more comprehensive medical support for Antarctic scientific expeditions.

OBJECTIVE To investigate the effects of renally inappropriate medication （RIM） on the frailty of elderly patients with diabetes. METHODS The data of elderly patients with diabetes mellitus admitted to a third-grade class A hospital in Yunnan province from January to December 2022 were collected， and Beers criteria （2019 edition） and Chinese version of FRAIL scale were used to evaluate RIM and the frailty of the patients； the patients were divided into the trial group （with RIM） and the control group （without RIM） according to whether there was RIM. The propensity score matching was used to balance confounding factors between two groups， and the influence of RIM on the frailty of elderly diabetic patients was analyzed by the Logistic regression model. RESULTS Among the 367 patients， 80 patients （21.80%） had RIM， the drugs involved RIM were spironolactone （82.56%）， rivaroxaban （13.95%） and gabapentin （3.49%）. After reaching the balance between groups using the propensity score matching method， the incidence of frailty was 77.94% in trial group and 27.94% in control group （P＜0.001）； the difference was not statistically significant in other confounding factors between the two groups （P＞0.05）. Results of Logistic regression analysis showed that the risk of frailty in the experimental group was 3.118 times that of the control group （odds ratio was 3.118，95% confidence interval was 1.758-5.530， P＜0.001）. CONCLUSIONS RIM is a risk factor for the frailty of elderly patients with diabetes， which can be considered as an indicator for early identification and screening of the frailty of elderly diabetes patients.