Objective: To examine the prevalence of e-cigarette use and associated factors among primary and secondary school students in Pudong New Area, Shanghai, and to explore the pathways linking harm perception of e-cigarettes, interpersonal social influence, and attitudes toward e-cigarette use with experimentation behavior, in order to provide scientific basis for further optimizing the prevention and control strategies of e-cigarette among adolescents. Methods: From September to October 2025, a multi stage cluster random sampling method was used to select 5 144 primary and secondary school students aged 8-19 years from 47 primary and secondary schools in Pudong New Area, Shanghai, to conduct an anonymous questionnaire survey. The questionnaire collected information on e-cigarette use, harm perception of e-cigarette, interpersonal social influence, and attitudes toward e-cigarette use. The Chi-square test was applied to analyze the differences in cigarette and e-cigarette use behavior among primary and secondary school students with different demographic characteristics. Structural equation modeling (SEM) was constructed using Mplus 8.3 software, and the bootstrap method was utilized to test the mediating effects. Results: The reported rates of cigarette experimentation, e-cigarette experimentation, and current e-cigarette use among primary and secondary school students were 1.85%, 2.10%, and 0.70%, respectively. Higher reporting rates of e-cigarette experimentation were observed among boys (2.82%), secondary school students aged 16-19 (3.39%), senior high school students (3.05%), and those with weekly pocket money >100 yuan ( 6.11% ) ( χ 2=11.67, 8.61, 8.00, 54.18, all P <0.05). Structural pathway analysis results demonstrated that e-cigarette harm perception positively predicted interpersonal social influence ( β =0.61) and e-cigarette use attitude ( β = 0.53 ), and interpersonal social influence ( β =0.65) and e-cigarette use attitude ( β =0.25) further promoted e-cigarette experimentation behavior among primary and secondary school students (all P <0.01), with interpersonal social influence playing a major mediating role (indirect effect=0.40). Conclusions E-cigarette experimentation behavior among primary and secondary school students in Pudong New Area is jointly influenced by multiple psychosocial factors. Intervention strategies should strengthen interpersonal social factors such as family and peers on the basis of health education, thereby constructing a comprehensive prevention and control strategy for e-cigarette use among primary and secondary school students.

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 risk factors of Mycoplasma pneumoniae（MP）lobar pneumonia with plastic bronchitis（PB）in pediatric patients，and to establish a risk nomogram prediction model.Methods:The medical informations were collected from pediatric patients diagnosed with MP lobar pneumonia who performed bronchoscopy during hospitalization in the Department of Pediatrics at the Second Affiliated Hospital of Air Force Military Medical University from April 2023 to December 2023.According to the bronchoscopic findings，the patients were divided into PB group and non-PB group.The clinical medical records and ancillary diagnostic findings were retrospectively analyzed.A multivariate Logistic regression model was used to analyze the independent risk factors for children with MP lobar pneumonia complicated with PB.A nomogram model was constructed to predict the risk of PB occurrence. Calibration curves and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the predictive value of the nomogram model for MP lobar pneumonia with PB. The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficacy.Results:A total of 357 pediatric patients diagnosed with MP lobar pneumonia were included，with 92 cases in PB group and 265 cases in non-PB group. No statistically significant differences in gender and age were observed between the two groups（ P>0.05）.The duration of fever and the hospitalization time in PB group were longer than those in non-PB group. The incidences of pleural effusion，consolidation area of a single lung lobe ≥2/3 and atelectasis on chest CT were higher in PB group compared to non-PB group. Additionally,the levels of neutrophil/lymphocyte ratio，C-reactive protein，procalcitonin，D-dimer（D-D），alanine aminotransferase(ALT)，aspartate aminotransferase，lactate dehydrogenase，α-hydroxybutyrate dehydrogenase，interferon-γ（IFN-γ），interleukin（IL）-6，IL-10 and IFN-γ/IL-4 ratio in PB group were higher than those in non-PB group（all P<0.05）.Logistic regression analysis showed elevated D-D, ALT and IFN-γ, pleural effusion and consolidation area of a single lung lobe ≥2/3 were independent risk factors for PB.The nomogram prediction model constructed by the model demonstrated good goodness-of-fit (χ 2=11.316， P=0.184) and provided significant clinical net benefits within a risk threshold range of 0.09–0.65. The area under the ROC curve for combined prediction was 0.771（95% CI 0.716-0.826），with a sensitivity of 0.707 and specificity of 0.706. Conclusion:In children with MP lobar pneumonia, elevated laboratory markers (D-D, ALT, IFN-γ) and imaging features (pleural effusion, consolidation area of a single lung lobe ≥2/3) are critical predictors for early diagnosis of PB.The nomogram prediction model can be used to predict MP lobar pneumonia with PB in early stage.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

AIM To study the effects of Jiaotai Pills and their single composition drugs on high-fat diet-induced hypothalamic inflammation in obese mice.METHODS C57BL/6J mice were randomly divided into the normal group(15 mice)and the high-fat group(75 mice).The mice given 12 weeks of high-fat diet feeding were further randomly divided into the model group,the Jiaotai Pills group,the Coptis chinensis group,the Cinnamomum cassia group and the positive metformin group,with 15 mice in each group.After 6 weeks of administration,the mice had their body weight and fasting blood glucose(FBG)levels detected;their hypothalamic expressions of IL-1β,IL-6,TNF-α and Socs3 mRNA detected by RT-qPCR;their hypothalamic expressions of TLR4,MyD88,IKKβ and activated NF-κB protein detected by Western blot;their hypothalamic expressions of Iba1 and GFAP detected by immunohistochemistry;and their ultrastructural changes of nerve tissues observed using transmission electron microscopy(TEM).RESULTS Compared with the model group,each drug group displayed decreased hypothalamic expressions of IL-1β,IL-6,TNF-α and Socs3 mRNA(P＜0.01),and improved number and morphology of nerve cells revealed by TEM.The groups intervened with Jiaotai Pills,or Coptis chinensis,or metformin shared decreased body weight and FBG levels(P＜0.05);decreased protein expressions of TLR4,MyD88,IKKβ and p-NF-κB(P＜0.05);and decreased number of hypothalamic astrocytes and microglia(P＜0.05).Additionally,decreased p-NF-κB protein expression was observed in the Cinnamomum cassia group(P＜0.05).CONCLUSION Jiaotai Pills and their single composition drugs can improve high-fat diet-induced hypothalamic inflammation in obese mice.

Aim To investigate the expression levels of cytoplasmic FMR1-interacting protein-1(CYFIP1)in colorectal cancer and assess the impact of CYFIP1 interaction on the proliferation and apoptosis of colorec-tal cancer cell HT29,along with its potential mecha-nisms.Methods Immunohistochemistry was em-ployed to assess CYFIP1 expression in 32 colorectal cancer tissues and adjacent tissues.Coexpressed genes were identified using the GEPIA2 website to predict potential correlations and binding sites.Following the construction of a siRNA-CYFIP1,alterations in cell proliferation,apoptosis,and levels of apoptosis-related proteins were evaluated through CCK-8 assay,Hoechst 33342/PI double staining assay,and Western blot a-nalysis,respectively.Results The immunohisto-chemical findings revealed a significantly elevated level of CYFIP1 expression in colorectal cancer tissues com-pared to paracancer tissues(P＜0.05).The expres-sion of CYFIP1 did not show any correlation with age and gender,but exhibited associations with TNM stage and lymph node metastasis(P＜0.05).A conserved TP53 binding site was predicted in the 3kbps DNA re-gion upstream of the CYFIP1 gene using GEPIA2,JASPAR databases,and rVista 2.0 promoter prediction software.Following transfection of HT29 cells with siRNA-CYFIP1,the clonogenesis and proliferation of cells significantly decreased(P＜0.05).Additional-ly,the levels of cleaved caspase-3 were elevated,while the expression levels of caspase-3 and Bcl-2 were reduced after transfection with siRNA-CYFIP1(P＜0.05),which might be related to the interaction be-tween CYFIP1 and TP53.Conclusions The upregu-lation of CYFIP1 in colorectal cancer is associated with TNM stage and lymph node metastasis.Upon silen-cing,CYFIP1 demonstrates the ability to suppress pro-liferation in HT29 cells and modulate the expression of apoptotic proteins.

Aim To investigate the effect of cordycepin(COR)on gentamicin(GEN)-induced nephrotoxicity and the molecular mechanism of inhibiting oxidative stress and ferroptosis induced by GEN.Methods The oral SD rats were divided into a control group,GEN group,and GEN+COR group.Following the success-ful setting up of the animal model,the serum creatinine(CR)and urea nitrogen(BUN)levels of rats were measured,and renal tissue injury was assessed using HE staining.In addition,the contents of malondialde-hyde and glutathione in kidney tissues of SD rats in each group were detected,and the expressions of fer-roptosis markers GPX4 and SLC7A11 were analyzed by Western blot.Results Compared with the control group,CR and BUN in GEN-stimulated group signifi-cantly increased(P＜0.01),and the level of CR and BUN was effectively reduced after 50 mg·kg-1 COR oral administration.HE results also showed that COR could alleviate the kidney tissue damage caused by GEN.COR could reverse the increase of malondialde-hyde level and the decrease of glutathione level caused by GEN in rat kidney tissue,and COR could restore the decrease of GPX4 and SLC7A11 protein levels induced by GEN.Conclusion COR can reduce GEN-induced kidney injury by inhibiting oxidative stress and ferrop-tosis.

Objective To investigate the impact of eccentric placement for various types of artificial aortic valves on downstream flow dynamics.Methods A physiological pulsatile circulation simulation system was employed and particle image velocimetry(PIV)was utilized to analyze the downstream flow field variations for bioprosthetic and mechanical valves under two placement conditions:centralized placement(0 mm)and eccentric placement(1 mm).Hemodynamic parameters such as velocity,vorticity,and viscous shear stress were assessed to evaluate the flow field characteristics.Results By analyzing the flow field variations at four characteristic time points,namely,early systole,acceleration phase,peak systole,and deceleration phase,a significant difference in flow field distribution between bioprosthetic and mechanical valves was observed.The bioprosthetic valve exhibited a centrally symmetric jet with a higher flow velocity,whereas the mechanical valve displayed a three-jet structure with a lower central flow velocity.Under eccentric placement,the blood flow in the aortic sinus region was sluggish,with a reduction in average velocity,hindering the formation and maintenance of vortices.During the peak systolic phase,the maximum viscous shear stresses in the sinus region for the bioprosthetic and mechanical valves were 0.45 and 0.67 Pa,respectively,approaching the threshold for endothelial cell damage.Conclusions Eccentric placement of both mechanical and bioprosthetic valves resulted in reduced sinus blood flow velocity and diminished viscous shear stress,creating favorable conditions for thrombus formation.In clinical practice,careful attention should be given to the placement of valve replacement to prevent eccentric placement.

Objective To explore the therapeutic effect of precise disconnection of pargastric varices guided by endoscopic ultrasound in the treatment of esophagogastric variceal bleeding.Method A retrospective analysis was conducted on 20 patients with cirrhosis esophagogastric variceal bleeding treated with endoscopic ultrasound-guided precise disconnection of pargastric varices from January 1,2024 to December 31,2024.The efficacy was analyzed.Result All 20 patients successfully completed the precise disconnection of pargastric varices under the guidance of endoscopic ultrasound.The injection of tissue gel combined with the placement of spring coils(14 cases)and the injection of tissue gel alone(4 cases)successfully blocked the pargastric varices.All patients did not experience perforation,esophageal and cardia stenosis,massive bleeding,septicemia,or ectopic embolization.One patient who received tissue gel alone had slight bleeding from the pargastric varices after surgery and improved after 3 days of treatment to reduce portal vein pressure.Another one patient who received tissue gel alone had a low-grade fever and normal body temperature after 3 days of anti-infection treatment.Conclusion Precise disconnection of pargastric varices under the guidance of endoscopic ultrasound has a good therapeutic effect on esophagogastric variceal bleeding,with fewer complications such as ectopic embolization,massive bleeding,infection,and perforation.However,close follow-up observation is still needed to address the issue of pargastric varices.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.