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.

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.

Objective To explore the mechanism of Luzhongjiangu Decoction in treating Osteonecrosis of the femoral head(ONFH).Methods Animal experiments were conducted to validate the therapeutic effect of Luzhongjiangu Decoction on ONFH.Network pharmacology was employed to screen potential targets,and molecular docking was used to verify the affinity between ligands and receptors.Fifty rats were randomly divided into blank group,model group,high-dose Luzhongjiangu Decoction groups,medium-dose Luzhongjiangu Decoction groups and low-dose Luzhongjiangu Decoction groups.After treatment,the therapeutic effect was evaluated by bone histomorphometry,bone histopathology and the expression of osteogenic related proteins.The serum metabolic differences were detected by UHPLC-QE-MS non-targeted metabonomics technique,followed by metabolic pathway enrichment analysis.Network pharmacology and metabolomics were integrated,and molecular docking was employed to further investigate the underlying mechanisms..Results The experimental results showed that Luzhongjiangu Decoction can significantly increase the expression of OCN,OPN and other osteogenic related factors,increase bone mineral density,alleviate the destruction of bone trabeculae,compared with that in the model group(P<0.01).The metabolomics test showed that compared with model group,Luzhongjiangu Decoction could callback 34 kinds of serum metabolic differences,involving 21 metabolic pathways,the main metabolic pathways were arachidonic acid metabolism,steroid hormone biosynthesis,primary bile acid biosynthesis,lysine degradation and so on.Network pharmacological results suggested that 185 active components and 1040 targets,551 disease targets and 76 intersection targets were obtained.The key pathways of Luzhongjiangu Decoction in the treatment of ONFH,which were analyzed by KEGG,involved HIF-1 signaling pathway,thyroid hormone signaling pathway,Calcium signaling pathway and so on.Integrated analysis showed that Luzhongjiangu Decoction may treat ONFH through seven metabolic pathways including arginine and proline metabolism,arachidonic acid metabolism,and steroid hormone biosynthesis;the molecular docking results also revealed correlation between potential pharmacodynamic substances and core target genes.Conclusion Luzhongjiangu Decoction can regulate the balance between proliferation and apoptosis of bone cells in a hypoxic environment by affecting the metabolic pathways such as arachidonic acid metabolism and HIF-1 signaling pathway,thereby exerting a therapeutic effect on osteonecrosis of the femoral head.

The aim of this study is to establish a rapid,efficient,and sensitive method for detecting the infectious laryngotracheitis virus(ILTV).The DNA of ILTV was extracted and used as a tem-plate to develop a recombinant enzyme-mediated isothermal amplification(RAA)fluorescence de-tection method for ILTV through optimization of conditions,sensitivity analysis,and repeatability assessment.Additionally,the nucleic acids of avian influenza virus(AIV),IBV,and Newcastle dis-ease virus(NDV)were detected to verify the specificity of this method.Finally,this method was applied to analyze 59 clinical samples collected from multiple large-scale chicken farms in Hebei Province,and the results were compared with those obtained from real-time fluorescence quantifi-cation(qPCR)and PCR methods according to national standards.The results showed that the RAA detection method established in this study had a reaction system of 25.0 μL buffer,2.1 μL primer,0.6 μL probe,5.0 μL magnesium acetate,and 5.0 μL template.The reaction temperature was 39 ℃ and the amplification time was within 20 minutes.The sensitivity of this method was 101 copies/μL,and the specificity detection was 100％.Testing of 59 clinical samples showed that 17 were detected positive by both RAA fluorescence and qPCR,and 12 were detected by PCR,and the detection rate of RAA(fluorescence)was consistent with real-time fluorescence quantification and qPCR,which was higher than that of the PCR assay.The research results indicate that the RAA fluorescence method has a short detection time,good specificity and sensitivity,and can be used for rapid detection of ILTV.

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 develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective To investigate the protective effect and mechanism of schisandrin A(SA)on hydrogen peroxide(H2O2)-induced oxidative stress injury in renal tubular epithelial cells(HK-2).Methods HK-2 cells were cultured in vitro and divided into five groups:blank control group,model control group(treated with 600 μmol·L-1 H2O2 for 2 h),low-dose SA group(0.125 μmol·L-1 SA,24 h pretreatment+H2O2),medium-dose SA group(0.5 μmol·L-1 SA,24 h pretreatment+H2 O2),high-dose SA group(0.75 μmol·L-1 SA,24 h pretreatment+H2O2).The cell survival was assessed by CCK-8 assay;apoptosis level was tested by Annexin V-FITC/PI double staining;cell cycle distribution was detected by propidium iodide staining;oxidative markers(ROS,SOD,MDA,GSH,LDH)was determined with commercial kits;and apoptosis-related proteins(Bax,Bcl-2,Caspase-3,Cytochrome C)was evaluated by Western blot.Results Compared with the blank control,the model group reduced in cell viability and increased in apoptosis(P＜0.01),elevated in the ratio of G0/G1-phase cells and decreased in S-phase cells(P＜0.05),decreased in SOD activity and GSH content(P＜0.01),and increased in the levels of ROS,LDH,and MDA levels(P＜0.01).In all SA dose,cell apoptosis reduced(P＜0.01).In medium/high dose groups,the G0/G1-phase arrest reduced(P＜0.05).In high dose group,the S-phase cells ratio increased(P＜0.05).And in medium/high dose groups,ROS(P＜0.01)decreased in a dose-dependent manner.The SOD activity increased non-significantly in all SA groups.In SA medium/high dose groups,the LDH activity decreased in a dose-dependent manner.In all SA groups,GSH increased(P＜0.01)and MDA decreased,both in a dose-dependent manner.The Bax/Bcl-2 ratio significantly decreased(P＜0.05)in all SA groups.The caspase-3 activity decreased in medium/high dose group(P＜0.05);and Cytochrome C reduced in all SA groups(P＜0.05).Conclusion SA protects HK-2 cells against H2O2-induced oxidative injury by modulating oxidative stress,inhibiting apoptosis,and ameliorating cell cycle arrest.

Objective The aim of this study was to explore the predictive value of the systemic inflammatory immune nutri-tion score(SIINS)for the prognosis of immunotherapy for advanced gastric cancer.Methods A retrospective analysis was conducted on the clinical data of 202 patients with advanced gastric cancer who received treatment with programmed death-1(PD-1)inhibitors at the Harbin Medical University Cancer Hospital from October 2018 to July 2022.The LASSO regression analysis was used to screen prognostic indicators,construct SIINS indicator,determine the optimal cutoff value for predicting prognosis using subject operating characteristic curves,and divide patients into the high SIINS and low SIINS groups.Independent prognostic factors for overall survival(OS)were determined using univariate and multivariate Cox regression analyses.Results Four indicators,including lymphocyte count,lactate dehydrogenase,and neutrophil lymphocytes,were selected to construct the SIINS index.The prognosis of patients in the high SIINS group was significantly lower than that in the low SIINS group(P<0.05).The results of the multifactorial Cox regression a-nalysis showed that the Eastern Cooperative Oncology Group(ECOG)score,Geriatric Nutritional Risk Index(GNRI),SIINS,treatment regimen,and number of treatment lines(P<0.05)could serve as the independent predictive prognosis of immunotherapy for advanced gastric cancer.Conclusion SIINS can predict the prognosis of patients with advanced gastric cancer treated with PD-1 inhibitors.

Objective To provide reference for future basic research and clinical research,the research status and trend of podophyllotoxin were explored.Methods Based on Citespace and R software,the co-occurrence map,keyword clustering and burst analysis of the English literature on podophyllotoxin in the Scientific Core Collection(WoSCC)were carried out to explore the research hotspots and analyze the frontier progress.Results A total of 1220 papers on podophyllotoxin published by 531 institutions from 77 countries and regions were retrieved.The number of published papers showed an overall upward trend.The analysis of the author 's cooperation network map showed that there was cooperation and communication between the authors,but it was relatively scattered,and the cooperation was not close.This phenomenon also existed in the relationship between research institutions.The country with the largest number of papers was China,and the institution was Lanzhou University.869 authors participated in the research in this field,and 422 academic journals published papers on podophyllotoxin.Among them,podophyllotoxin,derivatives,analogues,biological evaluation and etoposide had a high frequency of occurrence,indicating that these fields had high attention and great research potential.Conclusion In recent years,the research on podophyllotoxin and its derivatives in the treatment of tumors has developed rapidly.In addition,the pharmacological effects and gene regulation of podophyllotoxin are also new research trends.The research hotspots show a trend of diversification,which provides strong evidence for further exploring the molecular mechanism of podophyllotoxin in the treatment of various diseases.However,the lack of relatively in-depth basic research has limited the development of clinical research.