Objective: To analyze the epidemiological characteristics of pulmonary tuberculosis (PTB) among college students in Yangzhou from 2020 to 2024, so as to provide a scientific basis for developing prevention and control strategies. Methods: An epidemiological investigation was conducted among 162 college students with PTB, and 7 134 of their contacts were screened. Data were obtained from the tuberculosis information management system and on campus screening records. Using descriptive epidemiological methods, trends in incidence, seasonal distribution, and bacteriological characteristics were analyzed. Results: From 2020 to 2024, the annual average incidence of pulmonary tuberculosis among college students in Yangzhou was 29.42 per 100 000, showing an overall fluctuating downward trend ( χ 2=12.36, P <0.01). Cases were mainly concentrated in summer and autumn, with the highest proportion in autumn (41.36%, 67/162), followed by summer (23.46%, 38/162). The proportion of etiologically positive cases increased from 37.21% in 2020 to 71.43% in 2024; among positive cases, the proportion of latent tuberculosis infection (LTBI) decreased from 66.67% (10/15) to 26.67% (4/15). The etiological positive rate was higher in females than in males ( χ 2= 11.76 , P <0.01). Comparison of screening methods showed that among index cases, the LTBI detection rate of the recombinant Mycobacterium tuberculosis fusion protein skin test (C-TST) was higher than that of the tuberculin skin test (TST), but the difference was not statistically significant ( χ 2=0.65, P =0.42); among close contacts, the detection rate of TST was higher than that of C-TST (15.1%,10.1%; χ 2=5.23, P <0.05). Conclusion From 2020 to 2024, the annual average incidence of pulmonary tuberculosis among college students in Yangzhou showed an overall fluctuating downward trend, with differences in TB infection screening methods and gender.

High myopia(HM)is one of the leading causes of irreversible visual impairment, characterized by pathological changes such as axial elongation and multidimensional abnormalities in fundus biometric parameters. This review systematically summarizes the dynamic characteristics of fundus biometric parameters(including those of the retina, optic disc, macula, and choroid)in HM patients, as visualized via multimodal imaging techniques [e.g., optical coherence tomography(OCT)and optical coherence tomography angiography(OCTA)], and their association with HM progression and related complications. The article further highlights the strategies and advantages of multimodal imaging integration and discusses recent advances and challenges in combining artificial intelligence(AI)with these imaging modalities to automate fundus parameter analysis, lesion detection, risk stratification, and clinical decision-making for HM. This review aims to provide an evidence-based foundation for the early warning, precise intervention, and personalized management of HM, thereby facilitating a clinical paradigm shift from “reactive treatment” to “active health management”.

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Objective To investigate the association between physical activity levels and blood lipids among college freshmen, and to provide scientific evidence for the health management of college freshmen. Methods An electronic questionnaire survey on physical activity was conducted on freshmen of a university, and fasting blood biochemical indicators were detected. The International Physical Activity Questionnaire (IPAQ) short form was used to evaluate the physical activity levels of the participants. Dyslipidemia was defined as an abnormality in any one of the following serum lipid parameters: total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), or non-high-density lipoprotein cholesterol. Binary logistic regression and stratified analyses were employed to explore the relationship between physical activity and blood lipids. Results A total of 3 401 participants were included, with an average age of 18.45 ± 0.92 years, and 60.5% were female. The prevalence of dyslipidemia was 17.7%, with a higher rate among males (22.1%) than females (14.8%). After adjusting for confounding factors related to blood lipids, high-intensity physical activity was negatively associated with the risk of elevated LDL-C among males (OR = 0.36, 95% CI: 0.13–0.99, P = 0.049). Conclusion Among freshmen at a medical college in Hubei Province, high-intensity physical activity is negatively associated with the risk of elevated LDL-C in males, but this association needs to be further confirmed by larger prospective cohort studies.

Hepatitis B virus (HBV) infection represents a significant global health challenge. Current therapeutic options, such as interferon and nucleoside analogues (NAs), are limited by issues including long-term medication toxicity, the virus's propensity to develop drug resistance, and the inability to eradicate covalently closed circular DNA (cccDNA). Core protein allosteric modulators (CpAMs), as an emerging class of anti-HBV drugs, target HBcAg to interfere with capsid assembly. This not only blocks viral nucleocapsid formation and inhibits viral replication but also indirectly destabilizes the cccDNA pool, while exhibiting a relatively high genetic barrier to resistance. This article systematically evaluates HBV drug resistance to CpAMs and proposes anti-resistance strategies, including the combination of nucleoside analogues with CpAMs, enhancing protein-drug interactions, targeting HBcAg degradation, designing multi-target inhibitors, and employing combination therapy. Looking ahead, the integration of structural biology, computational chemistry, and immunotherapy will offer innovative approaches for developing novel, highly effective, and low-resistance inhibitors, thereby advancing the functional cure of hepatitis B.

Objective:To investigate the synergistic activity and mechanism of vinegar baked radix bupleurum polysaccharides(VBCP)in combination with oxaliplatin(OXA),and to provide new ideas for the clinical treatment of primary hepatocellular carci-noma.Methods:MTT assay was used to detect the cytotoxic effect of VBCP 3-4 and VBCP 3-3 in combination with OXA on Huh7 cells;ICP-MS was used to measure the uptake rate of OXA by Huh7 cells and evaluate the in vitro synergistic pathway of VBCP 3-4 in combination with OXA;Western blotting was used to measure the expression levels of related transporter proteins in Huh7 cells and explore the synergistic mechanism of VBCP 3-4 in combination and MRP1 in Huh7 cells,and the protein expression level of multidrug resistance-associated protein(MRP)2 was upregulated to 18.11%and 25.00%,respectively(P=0.008,P=0.001),while that of MRP1 was upregulated to 28.51%(P>0.05)and 39.70%(P=0.015),respectively.After the combination of VBCP 3-4 and OXA,the protein expression of MRP2,MRP1,and breast cancer resis-tance protein(BCRP)was inhibited;MRP2 was reduced by 47.38%in the high-dose combination group(P=0.000)and 15.18%in the low-dose combination group(P=0.049);MRP1 was reduced by 64.96%in the high-dose combination group(P=0.000)and 34.63%in the low-dose combination group(P=0.000);BCRP was reduced by 29.00%(P=0.020)in the high-dose combination group.Acting on Huh7 cells alone,VBCP 3-4 significantly reduced the protein expression levels of MRP2,MRP1,and BCRP,and in the high-dose VBCP 3-4 group,MRP2 and MRP1 were reduced by 24.91%and 20.79%,respectively(P=0.004,P=0.005).VBCP 3-4 downregu-lated the protein expression level of BCRP by 15.02%in the high-dose group(P=0.003)and 13.92%in the middle-dose group(P=0.030).Conclusion:VBCP 3-4 exerts a synergistic effect by inhibiting the expression of the efflux transporter proteins MRP1,MRP2,and BCRP,promoting the intake of OXA by Huh7 cells,and increasing the intracellular effective concentration.

Ionizing radiation occurs not only during nuclear and radiological terrorist attacks or nuclear accidents but also in medical applications and daily life. In recent years, the potential toxic effects of low-dose ionizing radiation on the male reproductive system have raised public health concerns. Most specifically, for the testis, a highly sensitive target organ to ionizing radiation, there is an urgent need to determine the mechanisms underlying the association between radiation-induced spermatogenic failure and male infertility. Focusing on the potential injurious effects of low-dose ionizing radiation on spermatogenesis, this review presents a summary and analysis of various underlying mechanisms including oxidative stress, apoptosis, and DNA damage repair and reviews recent domestic and international strategies for protecting against radiation-induced reproductive system damage in order to offer references for future research on the injurious effects of low-dose radiation on spermatogenesis and relevant protection.

Objective:To establish a tumor tissue xenograft (PDX) model derived from liver cancer patients and explore the factors affecting tumorigenicity of liver cancer in the PDX model.Methods:The hepatocellular carcinoma tissues were inoculated subcutaneously in the axilla of NPG mice using the tissue block method to establish a PDX model. The demographic characteristics and related clinical examination data of 60 hepatocellular carcinoma patients were collected using the electronic medical record system and comprehensive medical information system of Beijing You'an Hospital, affiliated to Capital Medical University. The hepatocellular carcinoma samples of 24 cases were sequenced using the Oak Wing TM-808 gene detection reagent and high-throughput sequencing technology. SPSS 17.0 statistical software was used for statistical analysis, and the count data were analyzed using the χ2 test. Results:The tumorigenicity rate of PDX samples from 60 patients with liver cancer was 35% (21/60). The average tumorigenic duration in the PDX-P0 generation was 110.71±50.45 days. There were statistically significant differences ( P<0.05) corresponding to Edmondson grade ( χ2=5.910, P=0.015) and Ki67 expression ( χ2=4.615, P=0.032) among PDX with tumorigenicity and without tumorigenicity between the liver cancer samples. There was no statistically significant difference in gene mutation (TOP25) among PDX with tumorigenicity and without tumorigenicity between liver cancer samples. Conclusion:The factors affecting the tumorigenicity of liver cancer in PDX models are complex. The high pathological grade and strong Ki67 expression may be the key factors for the completion of liver cancer in PDX models.

Objective To investigate the risk factors of thrombus head shedding and bleeding during endoscopic treatment of patients with esophageal varices veins,and build a risk prediction model.Methods 209 cases of esophageal varices with thrombus head found by endoscopy from February 2009 to July 2024 were retrospectively analyzed,and divided into non-shedding group(n=186)and shedding group(n=23)according to whether thrombus head shedding bleeding occurred during endoscopic treatment.Clinical and endoscopic data of the two groups were compared.Statistically significant factors were included in multivariate Logistic regression analysis and their independent risk factors were explored.A nomogram risk prediction model was constructed by R software,and its prediction efficiency was evaluated.Results Multivariate Logistic regression analysis showed that red thrombus head((O＾R)=6.231,95%CI:1.748～22.208),thrombus head diameter≥3 mm((O＾R)=4.355,95%CI:1.341～14.144),conical thrombus head((O＾R)=8.555,95%CI:2.427～30.154),and the presence of hematoma in the stomach((O＾R)=7.079,95%CI:1.665～30.103)were risk factors for bleeding after thrombus head shedding during endoscopic diagnosis and treatment.A nomogram prediction model was constructed with a sensitivity of 0.870(95%CI:0.732～1.000)and a specificity of 0.887(95%CI:0.842～0.933).Conclusion The thrombus head being red,conical in shape,with a diameter of≥3 mm and the presence of hematoma in the stomach are independent risk factors for thrombus head shedding and bleeding during endoscopic diagnosis and treatment.Timely intervention should be made for the above factors to benefit patients.

Objective:To analyze the epidemiological characteristics of rabies in China during 2024 to understand the patterns of disease transmission and provide a scientific basis for optimizing prevention strategies and advancing the rabies elimination process.Methods:Data on the national rabies epidemic in 2024 and case-specific information from national surveillance sites were collected from China's National Notifiable Disease Reporting System（NNDRS）. Descriptive epidemiological methods were used to analyze the disease trends and epidemic characteristics.Results:In 2024，China reported 167 human rabies cases across 20 provincial-level administrative divisions（PLADs），resulting in 148 fatalities. This represents a 39.17% increase from 2023（120 cases）and the highest annual incidence recorded since 2019. The epidemic exhibited a distinct geographic clustering in central and southern China，with four provinces（Henan，Guangxi，Hunan，and Hubei）accounting for 62.87%（105/167）of nationally reported cases. October（20 cases）and November（20 cases）recorded the highest monthly incidence，while February had the lowest（2 cases）. Farmers constituted the primary affected demographic（80.84%），with a marked male predominance（male-to-female ratio：2.15∶1）-higher than the 2023 ratio（1.86∶1）. Cases spanned all age groups，predominantly affecting middle-aged and older adults. Analysis of 54 cases revealed dogs as the primary exposure source（93.88%），with domestic dogs constituting 75.00% of these.The laboratory diagnosis rate of rabies cases in 2024 was 43.71%（73/167）.Conclusion:After 16 consecutive years of decline，China's rabies epidemic rebounded in 2024，primarily driven by deficiencies in domestic dog management and weaknesses in post-exposure prophylaxis. Key recommendations include enhancing canine vaccination coverage in high-risk areas，implementing targeted health education for farmers and middle-aged and older adults，improving standardized post-exposure treatment protocols，and optimizing integrated surveillance-alert-response systems，ultimately advancing the achievement of rabies elimination goals.