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.

The liver has diverse functions such as metabolism， detoxification， and immune defense， and the maintenance of hepatic microenvironment homeostasis is crucial for overall bodily health. The hepatic microenvironment consists of the components such as parenchymal cells， non-parenchymal cells， and non-cellular components. Chronic inflammatory responses induced by various etiological factors may promote the formation and progression of liver fibrosis. During the dynamic progression of liver fibrosis， from the early to advanced stages， various components within the hepatic microenvironment undergo a series of changes， which can promote the malignant progression of liver fibrosis. An in-depth exploration of the mechanisms underlying such changes in each component of the liver fibrosis microenvironment is of great significance for understanding the pathogenesis of liver fibrosis and discovering potential treatment strategies.

Liver cancer is one of the most common malignant tumors worldwide. Currently, the available treatment methods cannot fully control its recurrence and mortality rate. Establishing appropriate animal models for liver cancer is crucial for developing new treatment technologies and strategies. The patient-derived xenograft (PDX) model preserves the tumor's microenvironment and heterogeneity, which makes it advantageous for biological research, drug evaluation, personalized medicine, and other purposes. This article reviews the development, preparation techniques, application fields, and challenges of PDX models in liver cancer, providing insights for the research and exploration of PDX models in diagnostic and therapeutic strategies of liver cancer.
Liver Neoplasms/drug therapy* ; Animals ; Humans ; Xenograft Model Antitumor Assays/methods* ; Mice ; Disease Models, Animal

OBJECTIVES: Depression is a common negative emotion that can significantly impact physical and mental health. Due to their occupational characteristics, medical staff are more susceptible to depression compared to the general population. This study aims to explore the influence of future-oriented coping on depression among medical staff and the mediating roles of psychological resilience and perceived stress, providing theoretical guidance for depression intervention strategies in this group. METHODS: A cross-sectional survey was conducted among medical staff at a tertiary hospital using convenience sampling. Data were collected via the "Wenjuanxing" platform. A total of 754 questionnaires were distributed; after excluding invalid responses (e.g., duplicate IPs or insufficient completion time), 655 valid questionnaires were retained (valid response rate: 86.87%). Instruments included a demographic questionnaire, the Future-Oriented Coping Scale, the Connor-Davidson Resilience Scale, the Perceived Stress Scale, and the Self-Rating Depression Scale. All scales demonstrated high internal consistency (Cronbach's α>0.88) and validity. SPSS 27.0 was used for descriptive analysis, and PROCESS macro (Model 6) was used to test the chain mediation model. Harman's one-factor test was applied to control for common method bias. RESULTS: Descriptive analyses showed that future-oriented coping was positively correlated with psychological resilience and negatively correlated with perceived stress and depression. Mediation analysis revealed that future-oriented coping significantly predicted lower depression levels among medical staff (β=-0.283, P<0.001). Psychological resilience partially mediated the relationship (effect size=-0.329, accounting for 34.13% of the total effect), as did perceived stress (effect size=-0.099, 10.27%). A significant chain mediation path was identified: "future-oriented coping → psychological resilience → perceived stress → depression" (effect size=-0.253, 26.24%). The total indirect effect accounted for 70.64% of the overall effect, highlighting the substantial role of the mediating pathways. CONCLUSIONS Future-oriented coping can reduce depressive symptoms in medical staff, with psychological resilience and perceived stress serving as key mediators in a chain structure. These findings suggest that enhancing future-oriented coping strategies and psychological resilience may improve stress adaptation and reduce depression levels in this population.
Humans ; Adaptation, Psychological ; Resilience, Psychological ; Cross-Sectional Studies ; Depression/psychology* ; Surveys and Questionnaires ; Stress, Psychological/psychology* ; Male ; Female ; Adult ; Middle Aged ; Medical Staff/psychology* ; Occupational Stress/psychology*

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.

Objective:To establish a quantitative diagnostic standard for Crohn's disease with dampness syndrome based on clinical data using a disease syndrome combination model and conduct bidirectional validation.Methods:256 patients with Crohn's disease from the Department of Spleen and Stomach Diseases at Guangdong Provincial Hospital of Chinese Medicine, the Department of Gastroenterology at the Sixth Affiliated Hospital of Sun Yat-sen University, and the Outpatient Department of Guangdong Provincial Hospital of Chinese Medicine from October 2021 to January 2022 were selected as the observation objects. They were divided into an operation group of 205 patients and a verification group of 51 patients in an 8:2 ratio using a random number table method. The frequency advantage method, χ2 test, and binary logistic regression analysis were used to screen for relevant standard factors. The conditional probability method was used to assign scores to relevant items, and the maximum likelihood method was used to determine the quantitative diagnostic threshold. A quantitative diagnostic standard for Crohn's disease with dampness syndrome based on disease syndrome combination was established, and it was retrospectively analyzed and prospectively verified. Results:On the basis of the 20 candidate quantitative diagnostic criteria items for Crohn's disease dampness syndrome, binary logistic regression analysis was performed to calculate the OR values between each item. The quantitative diagnostic criteria for Crohn's disease with dampness syndrome included tongue coating greasiness (7 points), body heaviness (13 points), waist and knee soreness (8 points), head weight (9 points), bland mouth (6 points), anal heaviness (8 points), uncomfortable bowel movements (8 points), and sticky stools (7 points), with a quantitative diagnostic threshold of 11. Conclusion:The scoring of relevant items in the quantitative diagnostic criteria for Crohn's disease with dampness syndrome is reasonable and has good diagnostic value, which can provide reference for further quantitative research on Crohn's disease syndromes.