Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

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.

Background Ozone (O₃) is a major air pollutant. The existing monitoring system has uneven distribution of sites, insufficient coverage in underdeveloped areas, and low temporal resolution, making it difficult to obtain hourly data. This limits the dynamic identification of pollution and the formulation of prevention and control strategies. Objective To construct an hourly O₃ concentration estimation model based on ensemble machine learning, aiming to improve the accuracy of pollution exposure assessment and explore O₃ health impacts. Methods This study integrated land use regression modeling with modern machine learning techniques, employing random forest and XGBoost algorithms to construct base models, and stacking integration using non-negative least squares. The ensemble model was trained and validated across China using high-resolution, multi-source geographic data (e.g., meteorologicaldata, population density, land cover types, and aerosol optical thickness). It was tested in Taiyuan City, combined with a distributed lag non-linear model to analyze the association between O₃ and emergency admissions. Results The constructed ensemble model performed well in predicting O₃ concentration, with a higher coefficient of determination (R²) and a lower root-mean-square deviation (RMSE) compared to the single models. The R² improved from 0.90 to 0.92, and the RMSE decreased from 11.41 to 10.62, enhancing both prediction accuracy and generalization ability. In the application to Taiyuan City, the model successfully imputed the hourly-level data for the entire year. The distributed lag non-linear model analysis revealed that the relative risk (RR) values for the 6th to 8th days following O₃ exposure were 1.14 (95%CI: 1.01, 1.29), 1.16 (95%CI: 1.02, 1.31), and 1.14 (95%CI: 1.01, 1.29), respectively, which were significantly higher than 1, indicating a significant lagged association (lagged 6-8 d) between O₃ and the number of emergency room visits. Conclusion A high-precision, hourly-level O₃ concentration estimation model is successfully constructed by combining the land use regression model with an ensemble machine learning approach to provide a scientific basis for environmental policy formulation and public health intervention. The application of the model verifies its generalization ability and practical application value, which can provide a new technical framework for subsequent environmental health research.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

AIM:To identify surrogate clinical bio-markers for profiling the eosinophilic status of an individual patient over induced sputum analysis.METHODS:We conducted a cross-sectional study on 100 asthmatic patients whose induced sputum was successfully collected.Subjects were further classified into either EA or NEA based on whether the percentage of sputum eosinophil count(SEC％)was≥3％.Demographic and clinical data were col-lected,including basic information,routine blood tests,lung function tests,bronchodilator reversibili-ty tests,fractional exhaled nitric oxide(FeNO),the Asthma Control Test(ACT)and the Asthma Control Questionnaire(ACQ).All variables significantly asso-ciated with EA were candidates for multivariate lo-gistic regression analysis.A scoring system present-ed as a nomogram for the prediction of EA was de-veloped.RESULTS:In the univariate analysis,com-pared with NEA subjects,those with EA were of older age and had worse asthma control and lung function in addition to higher values of blood eosin-ophils,serum IgE and FeNO.Multivariable logistic regression analysis revealed that age,FeNOx serum IgE and blood eosinophil count(BEC)were identi-fied as independent risk factors for eosinophilic asthma,which were all included in the nomogram.CONCLUSION:A combination assessment including age,FeNOx serum IgE and BEC could be applicable to clinicians in identifying eosinophilic asthma and is easier,faster,more inexpensive and more readily available than the induced sputum test.

Objective:To establish a stable rat model of sequelae of pelvic inflammatory disease(SPID)with clinical characteristics,and to provide a reliable experimental model for the study of the pharmcological effect and mechanism of SPID.Methods:Twenty-four 7-week-old SD rats were divided into sham operation group,model-A(108 cfu/mL mixed bacterial solution,0.2 mL),model-B(109 cfu/mL mixed bacterial solution 0.2 mL),and model-C(108 cfu/mL E.coli 0.2 mL).The weight of the rat's uterine was weighed and the uterine index was calculated.The automatic hematology analyzer was used to detect the blood routine;hematoxylin-eosin staining(HE)and masson staining were used to detect uterine pathlogical changes in rats.Enzyme-linked immunosorbent assay(ELISA)was used to detect interleukin-1β(IL-1β),interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in rat uterine tissue homogenates.Western blot was used to detect the expression of proteins related to NF-κB signaling pathway.Results:Compared with the sham operation group,the uterine index of model-A,model-B,and model-C were significantly increased(P＜0.05,P＜0.01).The levels of WBC and NE in the model-A increased significantly(P＜0.01).The level of LY in model-B decreased significantly(P＜0.01).The levels of IL-1β,TNF-α in model-A,model-B,and model-C were significantly increased(P＜0.01).The levels of IL-6 in model-A and model-B were significantly increased(P＜0.05,P＜0.01).The collagen volume fraction of model-A and model-B were significantly increased(P＜0.01).Mechanism study indicates that the expression levels of p-IKKβ/IKKβ,p-IκBα/IκBα and p-p65/p65 in model-A were significantly increased(P＜0.01),and the expression levels of IκBα/β-actin were significantly decreased(P＜0.01).The expression level of p-IKKβ/IKKβ in model-B was significantly increased(P＜0.01).Conclusions:A stable rat model of SPID that conforms to clinical characteristics can be successfully constructed by combining 0.2 mL of mixed bacterial solution with a concentration of 108 cfu/mL and mechanical injury.This modeling method intervened in the expression of the NF-κB inflammatory signaling pathway.

Objective:To compare the clinical efficacy of catheter-directed thrombolysis (CDT) via the contralateral femoral vein approach (CFVA-CDT) and the calf deep vein approach (CVA-CDT) in the treatment of acute mixed-type lower extremity deep vein thrombosis (DVT).Methods:Patients treated with CFVA-CDT and CVA-CDT for acute mixed-type DVT were retrospectively collected from January 2018 to December 2021, totaling 49 and 32 patients, respectively. The relevant technical indicators, thrombolysis rates in the iliac-femoral vein segment and femoral-popliteal vein segment, clinical efficacy, and the incidence of lower extremity deep vein patency, venous valve insufficiency, and post-thrombotic syndrome (PTS), as well as the severity of chronic venous disease in the affected limb (VCSS score) during a 2-year follow-up period were retrospectively compared between the two venous access CDT groups. The t-test was used for comparing quantitative data, while the chi-square test or Fisher′s exact test was used for categorical data.Results:During CFVA-CDT procedure, 6-8 F vascular sheaths were used, and balloon dilation of 2~6 mm was more frequently employed (65.31%, 32/49) to expand venous stenosis/occlusion segments before successful sheath placement compared to the CVA-CDT group (37.50%, 12/32), and the difference was statistically significant ( P=0.014). In the CVA-CDT group, 31.25% (10/32) of patients had a maximum sheath size of 6 F, while the remainder used 4 or 5 F sheaths. Among them, 34.38% (11/32) of patients required re-puncture of the popliteal or femoral vein for larger sheaths (≥8 F) for thrombus aspiration and subsequent endovascular treatment during or after thrombolysis. The effective thrombolysis rates (≥50%) in the iliac-femoral vein segment were not significantly different between the two groups ( P=0.778). The effective thrombolysis rate of the femoral-popliteal venous segment is related to the presence or absence of popliteal vein opacification on lower extremity venous antegrade venography. There was no significant difference between the groups when the popliteal vein was visualized ( P=1.000). While the popliteal vein was not visualized, the CVA-CDT group (75.0%, 15/20) was significantly better than the CFVA-CDT group (34.38%, 11/32), and the difference was statistically significant ( P=0.004). There was no significant difference in clinical efficacy between the two groups ( P=0.819). During follow-up, the femoral-popliteal vein patency rate in the CVA-CDT group (87.50%, 28/32) was significantly higher than in the CFVA-CDT group (44.90%, 22/49), the difference was statistically significant ( P<0.001). Conclusions:Successful CFVA-CDT requires the assistance of more ancillary devices, while the use of larger sheaths is more limited in CVA-CDT due to the smaller caliber of the calf deep veins. The presence or absence of popliteal vein opacification on lower extremity venous antegrade venography may influence the effective thrombolysis of the femoral-popliteal venous segment thrombus in patients with acute mixed deep vein thrombosis (DVT) treated with CFVA-CDT and CVA-CDT. Compared to CFVA-CDT, CVA-CDT can improve the patency rate of the femoral-popliteal venous segment.

Hashimoto thyroiditis(HT)is one of the most common autoimmune diseases."Wood depression and earth stagnation"is its important pathogenesis.Liver depression and qi stagnation,wood depression multiplies the earth,spleen deficiency and earth stagnation,phlegm and blood stasis intermingle,resulting in wood depression and earth stagnation.Or middle-earth stagnation insults wood in turn,liver yang deficiency,wood depression,and failure to disperse and discharge,resulting in earth stagnation and wood depression.It may be related to the intestinal immune mechanism in modern medical study.Based on the theory of"wood depression and earth stagnation",this article discussed the pathogenesis of HT from the perspective of wood depression and imbalance of microbe-gut-brain axis,earth stagnation and dysbiosis of intestinal flora,damage to the intestinal barrier,and proposed the treatment principles,i.e.,"disperse stagnated liver qi for relieving qi stagnation,ascend yang and regulate qi""eliminate stagnation and remove turbidity,invigorate spleen and restore normal movement",which could provide the ideas for mechanism research and clinical treatment of HT.

Neurodegenerative diseases(NDs)are a series of disorders characterized by varying degrees of cognitive and mobility impairment,with increasing incidence in recent years.Currently,the treatment of these diseases is mainly based on drug therapy,and there are no effective methods for reversing the course of the diseases.Corni Fructus has the efficacy of tonifying the liver and kidney,and astringency and arresting,which is effective to various types of NDs.This article summarized the pharmacological effects of Corni Fructus,including anti-inflammatory,anti-oxidative stress,regulation of mitochondrial function,modulation of autophagy,inhibition of neuronal apoptosis,and epigenetic modulation,and sorted out the research progress of Corni Fructus and its active components in the treatment of NDs,such as Alzheimer disease,Parkinson disease,multiple sclerosis,and so on,with a view to providing a reference for further research and clinical application of Corni Fructus in NDs.

Objective:To analysis the influenced factors of readmission in hospital among patients with mood disorder,construct predictive models and compare the predictive performance of the models.Methods:The electron-ic medical record data of patients with mood disorder admitted to Beijing Anding Hospital from January 2010 to De-cember 2018 were retrospectively collected.Utilizing stepwise logistic regression to analyze the related factors of re-admission in patients with mood disorder.Logistic regression,support vector machine,random forest,extreme gradi-ent boosting(XGBoost)algorithms and convolutional neural networks(CNN)were used to construct a readmission prediction model and compare the predictive performances of the different models by using the accuracy,precision,recall,et.al.Results:A total of 6 234 patients with mood disorder were enrolled,24.9％(n=1 549)patients were readmitted after discharge.The stepwise logistic regression results revealed that readmissions were more likely to occur in patients with mood disorder who were female,had comorbidities,had a treatment outcome of cure,were treated with MECT and were on second-generation antipsychotics(OR=1.26,1.68,1.26,1.35,1.18).The CNN model demonstrated the highest accuracy,precision,and F1 scores,all at 0.87,with a recall of 0.86.The random forest achieved a recall of 0.86 and an AUC of 0.95.Conclusion:Readmission of patients with mood disorder is influenced by a multitude of factors.The convolutional neural networks and random forest models outperform other models in prediction.