Abstracts of the 11th International Conference on Biomedical Engineering and Pharmaceutical Sciences,May 29-31,2026,Singapore

Research on Asymptomatic Endometrial Thickening and Endometrium Atypical Hyperplasia/Endometrial Cancer in Postmenopausal Women

Huanxiu Wu^*, Xiaoya Wen, Yan Zhao, Qingmei Li, Shuxing Yang, Yuan Zhao

Gynecology Department, Taiyuan Central Hospital/The Ninth Clinical Medical College of Shanxi Medical University, Taiyuan 030032, China

Objective: To explore the diagnostic value of endometrium thickness (ET) in asymptomatic postmenopausal women and determine the optimal ET threshold to distinguish precancerous endometrial lesions and malignant ones. And explore the related risk factors for the occurrence of endometrial malignant tumors.

Methods: A prospective analysis was performed on the data of 180 asymptomatic postmenopausal women who underwent diagnostic curettage or surgical treatment under hysteroscopy due to endometrial thickening (ET ≥ 4 mm) as indicated by transvaginal ultrasound (TVS) for other reasons. These patients were recruited from the Department of Obstetrics and Gynecology at Taiyuan Central Hospital between December 1, 2022, and April 1, 2025.

Results: 1. Among 180 postmenopausal patients with asymptomatic endometrial thickening, the distribution of pathological types: The most common intrauterine lesion was endometrial polyps (51.11%), followed by normal endometrium (32.22%). Malignant lesions (atypical endometrial hyperplasia + endometrial cancer) accounted for 4.45% (8 cases), among which endometrial cancer accounted for 2.78% (5 cases).2.Through the analysis of the ROC curve (Receiver Operating Characteristic Curve), it was determined that 11mm is the optimal threshold for diagnosing precancerous and malignant lesions of the endometrium, with a sensitivity of 87.5%, specificity of 83.72%, Youden index of 0.71, and an area under the ROC curve (AUC) of 0.85, demonstrating good diagnostic efficacy. 3. Univariate analysis: Fisher's exact test was used for categorical variables, and the Mann-Whitney U test was used for continuous variables. Hypertension (OR=6.081, P=0.0442), diabetes (OR=9.1176, P=0.0068), positive blood flow signal on transvaginal ultrasound (OR=14.2593, P=0.0036), and endometrial thickness (P=0.0121) were significantly associated with AH (endometrial atypical hyperplasia) / EC (endometrial cancer); there were no significant differences in body mass index (BMI) (P=0.0823), age, and years since menopause. Multivariate analysis: Exact logistic regression analysis showed that positive blood flow signal on transvaginal ultrasound (OR=22.65, P=0.008), diabetes (OR=10.34, P=0.032), and endometrial thickness (OR=1.203, P=0.028) were independent risk factors.

Conclusion: The 11mm endometrial thickness (ET) threshold demonstrates acceptable diagnostic performance and is capable of effectively identifying precancerous lesions of the endometrium as well as endometrial cancer. For patients with ET less than 11mm, ultrasound-based assessment of endometrial thickness should not be used as the sole criterion. Instead, personalized evaluations should be performed by integrating clinical factors and high-risk indicators associated with malignant lesions, such as hypertension, diabetes, transvaginal ultrasound blood flow signals, among others.

Acknowledgements: Taiyuan Bureau of Science and Technology, Science, Technology, and Innovation Program of National Regional Medical Center (202237).

Corresponding Author: Huanxiu Wu, Gynecology Department, Taiyuan Central Hospital/The Ninth Clinical Medical College of Shanxi Medical University, Taiyuan 030032, China.

An Analysis of Primary Laryngeal Tuberculosis

Shidong Chu^*, Yiyun Zhang

ENT Department, Hangzhou Red Cross Hospital, Hangzhou, Zhejiang 310000, China

Background: Tuberculosis is a common chronic infectious disease caused by Mycobacterium tuberculosis. Currently, about 20% of tuberculosis cases occur outside the lungs, known as extrapulmonary tuberculosis. Among tuberculosis diseases related to the ear, nose, and throat, laryngeal tuberculosis accounts for the majority, representing about 1.2% of extrapulmonary tuberculosis cases, with primary laryngeal tuberculosis being relatively rare.

Subjects and Methods: This article studies 8 patients admitted to our hospital and diagnosed with primary laryngeal tuberculosis from January 2023 to January 2024. By retrospectively analyzing the clinical data of the patients, we explore the clinical manifestations, diagnostic methods, and treatment of primary laryngeal tuberculosis.

Results: 1. Clinical symptoms: The main clinical symptom in patients with laryngeal tuberculosis was hoarseness, accounting for approximately 75%. 2. Lesion site: Nasopharyngolaryngoscopy performed on the patients indicated that the unilateral vocal cord was the most common site of lesion, accounting for about 62.5%. Analysis of the laryngoscopic diagnostic results showed that most patients with primary laryngeal tuberculosis presented with a single proliferative lesion. 3. Chest CT findings: All patients underwent routine plain chest CT scans, and no signs of pulmonary tuberculosis infection were found, indicating that the patients did not have pulmonary tuberculosis and were all cases of primary laryngeal tuberculosis. 4. Examination results: T-SPOT.TB test, sputum smear acid-fast staining, Mycobacterium tuberculosis (MTB) culture, Xpert MTB/RIF assay, metagenomic sequencing, and pathological examination were performed. The results showed that metagenomic sequencing and pathological examination had the highest diagnostic coincidence rate at 100%, which was higher than the other examination methods. All patients with laryngeal tuberculosis were given 12 months of anti-tuberculosis drug treatment. The patients' related clinical symptoms disappeared, and laryngoscopic examination showed that the previous lesions had disappeared and the mucosa at the lesion site was smooth, meeting the criteria for clinical cure.

Conclusions: The clinical manifestations of primary laryngeal tuberculosis include hoarseness, foreign body sensation in the pharynx, and sore throat, which lack specificity and are therefore easily misdiagnosed as laryngitis or laryngeal tumors. A definitive diagnosis can be made through pathological and metagenomic sequencing examinations, the sensitivity of which is higher than that of other traditional examination methods. These methods have high diagnostic value in the diagnosis and treatment of laryngeal tuberculosis, providing a basis for early diagnosis and treatment. However, due to the small number of cases, large-sample, multi-center studies are still needed in the future to improve the reliability of the research results.

Corresponding Author: Shidong Chu, ENT Department, Hangzhou Red Cross Hospital, Hangzhou, Zhejiang 310000, China.

Effect of Buttonhole Cannulation and Rope Ladder Technique on Long-Term Patency of Autologous Arteriovenous Fistula in Hemodialysis Patients

Ziyan Guo¹, Jianzhao Cheng^2,*

¹ Hemodialysis Unit, Xiangtan Central Hospital, Xiangtan 411100, Hunan, China

² Department of nephrology, Xiangtan Central Hospital, Xiangtan 411100, Hunan, China

Objective: As the two mainstream clinical cannulation techniques, buttonhole cannulation and rope ladder cannulation remain controversial in their impact on the long-term patency of autologous arteriovenous fistula (AVF). This review aims to systematically synthesize recent research evidence, clarify the clinical efficacy, complication differences, and mechanisms of action of the two techniques, analyze the interaction between patients' individual factors and operational practices, and provide scientific support for the formulation of individualized clinical cannulation strategies and the optimized management of AVF access.

Subjects and Methods: Using “autologous arteriovenous fistula”. “buttonhole cannulation”, “rope ladder cannulation”. “hemodialysis”. and “long-term patency” as core keywords, relevant original studies (including randomized controlled trials, retrospective cohort studies, systematic reviews, and meta-analyses) published in recent years were systematically searched from PubMed, Web of Science, and CNKI databases. Purely theoretical studies and review articles without empirical data were excluded. After literature screening and quality assessment, a total of 65 valid articles were included, and thematic analysis was adopted for integrated analysis from dimensions such as technical characteristics, impact on patency, complication mechanisms, and optimization strategies.

Results: Each of the two cannulation techniques has its own advantages and disadvantages: rope ladder cannulation reduces repeated local vascular injury by dispersing puncture sites, and exhibits significant advantages in lowering the incidence of hemangioma, reducing the need for vascular interventional therapy, and controlling infection risk; buttonhole cannulation is easy to operate with fewer puncture sites, but has a higher risk of infections such as bacteremia, and there is no statistically significant difference in the 1-year patency rate compared with rope ladder cannulation. Mechanistically, cannulation techniques regulate AVF patency indirectly by affecting hemodynamics, vascular wall repair, and inflammatory responses. Patients' diabetes status, age, educational level, and operational standardization all influence the efficacy, while ultrasound-guided puncture and standardized training can improve safety.

Conclusions: The two cannulation techniques have no absolute superiority or inferiority in terms of their impact on the long-term patency of AVF. Clinical decisions should be individualized based on patients' vascular conditions, comorbidities, and infection risks.

Acknowledgements: This work was supported by the Research Project of the Hunan Provincial Health Commission (Grant No. 202214013254).

Corresponding Author: Jianzhao Cheng, Department of nephrology, Xiangtan Central Hospital, Xiangtan 411100, Hunan, China.

A Case Report of Mixed Allergic Purpura in Adults with Eosinophilia

Yufei Yan^1,#, Lili Xu^1,#, Jingyi Chen¹, Qianqian Xu², Yi Sun³, Jian Wei^4,*

¹ Department of Clinical Laboratory, Kongjiang Hospital, Yangpu District, Shanghai, China

² Department of Clinical Laboratory, Huashan Hospital affiliated to Fudan University, Shanghai, China

³ Department of Clinical Laboratory, The First People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China

⁴ Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

^# Yufei Yan and Lili Xu contributed equally to this study

Background: Mixed allergic purpura is a type of IgA vasculitis (IgAV) with diverse clinical manifestations and severe symptoms, accompanied by joint and/or abdominal and/or renal IgAV in addition to skin involvement, which is prone to missed diagnosis and delayed treatment. At present, there are no reports of adult mixed allergic purpura accompanied by eosinophilia. This study reports one case and summarizes it as follows.

Subjects and Methods: A 76-year-old woman visited the hospital in 2024 due to “purpura in both lower limbs that did not disappear after pressure” and “paroxysmal pain in the upper and lower abdomen for 7 days“. On March 20 and March 27, two blood routine tests showed eosinophilia (Absolute eosinophil count: first time: 7.56×109/L, second time: 9.68×109/L. Reference range: (0.04-0.54) ×109/L), and blood microscopic examination showed no abnormal cell morphology and parasites. We advised her to go to a superior hospital for further investigation and clinical follow-up.

Results: The JACK2 mutation was negative and BCR-ABL (P210) was not detected. Flow cytometry showed that there was no obvious hematopoietic cell population in the peripheral blood, which ruled out hematological malignancy. Laboratory test results are expressed in the form of project name: test results (reference range): C-reactive protein: 26.3 mg/L (0-10 mg/L), urine protein: weakly positive (negative), fecal occult blood: negative (negative), erythrocyte sedimentation rate: 45 mm/hr (0-20 mm/hr), rheumatoid factor: 95.7 IU/mL (0-14 IU/mL), total protein 58.08 g/L (65-85 g/L), albumin 28.1 g/L (40-55 g/L), IgE 701 KUA/L (<0.35KUA/L), egg: >1000 KUA/L (<0.35KUA/L), egg white: 254.8 KUA/L (<0.35KUA/L), etc. We followed up the patient for 3 months. After comprehensive testing in 3 superior hospitals and hospitalization in 2 of them, combined with the previous history of skin lesions and clinical symptoms, the patient was finally diagnosed with mixed allergic purpura and eosinophilia. After symptomatic treatment, the patient made a full recovery in July 2024.

Conclusions: In clinical work, we cannot simply equate eosinophilia with allergic diseases, and sometimes eosinophilia can also be seen in some difficult and miscellaneous diseases, such as mixed allergic purpura. Therefore, in the diagnosis, we need to combine the results of multiple tests to carefully identify the disease, rather than a blind eye.

Corresponding Author: Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Integrated Machine Learning Framework for Precision Prediction and Management of Chronic Diseases Using Electronic Medical Records: A Case Study on Cardiovascular Disease in Chronic Kidney Disease Patients

Zhengqi Sun^1,*, Quanrong Fang²

¹ Physical Sciences Division, University of Chicago, Chicago, IL, 60637, USA

² College of computer science and technology, Zhejiang University, Hangzhou, 310058, China

Background: Chronic diseases are a leading global cause of morbidity and mortality, imposing substantial burdens on healthcare systems. Electronic Medical Records (EMRs) offer rich, longitudinal data for risk prediction, yet their high-dimensional and heterogeneous nature, comprising both structured variables (e.g., lab results, demographics) and unstructured clinical narratives, poses significant modeling challenges. Traditional statistical and machine learning approaches often focus solely on structured data or lack the robustness and interpretability essential for clinical adoption.

Subjects and Methods: We developed an integrated machine learning framework that synergistically combines structured EMR features with unstructured physician notes using advanced Natural Language Processing (NLP), particularly ClinicalBERT embeddings aligned with UMLS and ICD-10 vocabularies. The pipeline includes multimodal data preprocessing, hybrid predictive modeling using Random Forest, XGBoost, and LSTM networks to capture nonlinear interactions and temporal dependencies, systematic feature selection via Recursive Feature Elimination (RFE), and post-hoc interpretability through SHAP values and attention visualization. The framework was rigorously evaluated across five large-scale, diverse EMR datasets, including MIMIC-III, Kuwait EHR, a multi-center Chinese CKD cohort, UK Biobank, and eICU, with stratified five-fold cross-validation and external testing to assess generalizability and real-world applicability.

Results: The proposed framework consistently outperformed classical and state-of-the-art baselines, achieving average AUROC scores of 0.861–0.902 across multiple chronic conditions such as cardiovascular disease, diabetes, and chronic kidney disease. Integration of NLP-derived textual features improved predictive accuracy by 9–14% over models using structured data alone (p < 0.01). Ablation studies confirmed the critical contribution of clinical text mining, while robustness tests showed minimal performance degradation under noisy inputs (≤4.2% AUROC drop at 15% noise). Interpretability analyses highlighted clinically plausible predictors, including creatinine, eGFR, troponin, HbA1c, and narrative mentions of fluid retention or medication non-adherence, with over 85% alignment with domain expert judgment.

Conclusions: This study demonstrates that a unified, interpretable, and multimodal machine learning framework can effectively leverage the full spectrum of EMR data for accurate, robust, and transparent chronic disease prediction. By integrating structured and unstructured data with explainable AI techniques, the approach supports early risk identification, personalized intervention strategies, and scalable clinical decision support, thereby advancing the real-world deployment of AI in precision health management and improving outcomes for high-risk patient populations.

Corresponding Author: Zhengqi Sun, Physical Sciences Division, University of Chicago, Chicago, IL, 60637, USA.

The Mediating Effect of Self-Efficacy on the Relationship between Social Support and Caregiving Stress among Primary Caregivers of Cancer Patients

Wenhu Zhou¹, Haidan Hu¹, Wenjing Liu¹, Ning Chen¹, Hengying Che^2,*

¹ Graduate School, Wannan Medical College, Wuhu 241002, China

² Department of Nursing, The First Affiliated Hospital of Wannan Medical College, Wuhu 241001, China

Background: At present, the number of cancer patients continues to rise. For primary caregivers in families of cancer patients, robust social support and a strong sense of self-efficacy can help alleviate caregiving stress. This study examines the mediating effect of self-efficacy on the relationship between social support and caregiving stress among primary caregivers of cancer patients, clarifying the relationship among these three factors.

Subjects and Methods: Convenience sampling was used to recruit primary family caregivers of patients with malignant tumours admitted to the Oncology Department of a tertiary hospital in Wuhu City between April and November 2025. This study employed a self-developed general information questionnaire, the Social Support Scale, the Caregiver Stress Scale and the Self-Efficacy Scale to conduct a cross-sectional survey of social support, caregiving stress and self-efficacy among 215 primary caregivers of cancer patients. Relationships among these factors were examined using Pearson correlation analysis. Furthermore, linear regression model 4 and Bootstrap procedures were applied to test the mediating effect of self-efficacy.

Results: The primary family carers of cancer patients scored (31.61 ± 10.49) points for overall social support, (7.07 ± 3.29) points for overall caregiving stress, the prevalence of caregiver stress is 61.40%, and (23.58 ± 6.29) points for overall self-efficacy. Statistically significant differences were observed in social support scores based on the carer's gender, age, and duration of care provision (p<0.05). A negative correlation was observed between primary caregivers' social support and caregiving stress (r = -0.534, p < 0.001). Social support was positively correlated with self-efficacy (r = 0.490, p < 0.001), while caregiving stress was negatively correlated with self-efficacy (r = -0.826, p< 0.001). Self-efficacy partially mediated the relationship between social support and caregiving stress (β = −0.114, p < 0.001), accounting for 68.26% of the mediating effect.

Conclusions: Primary carers of cancer patients experience significant caregiving stress, with a prevalence rate of 61.40%. Social support is at a moderate level, and self-efficacy acts as an effective mediator between social support and caregiving stress. Consequently, clinicians and relevant professionals can implement measures to enhance levels of social support, thereby reducing carers’ stress. They can also address the indirect factors influencing family carers’ self-efficacy, thus alleviating the caregiving stress experienced by carers.

Acknowledgements: This work was supported by a project grant from Provincial Quality Engineering Project “Internal Medicine Nursing” of Anhui Provincial Department of Education in 2023 (Grant No.2023kcszsf150).

Corresponding Author: Hengying Che, Department of Nursing, The First Affiliated Hospital of Wannan Medical College, Wuhu 241001, China.

Association between the Triglyceride-Glucose and Waist-to-Height Ratio Index and the Risk of Chronic Liver Disease among Middle-Aged and Older Chinese Adults: A Nationwide Cohort Study

Zhen Jiang^#, Lu Zhang^#, Han Li, Wenzijing Ni, Xiaofeng Ye^*

Changzhou Hospital Affiliated to Nanjing University of Chinese Medicine, Changzhou, Jiangsu, China

^#Zhen Jiang and Lu Zhang contributed equally to this work.

Background: The triglyceride-glucose waist-to-height ratio (TyG-WHtR) has been established as a reliable surrogate marker for insulin resistance (IR). However, its association with the risk of chronic liver disease (CLD) remains unclear. Therefore, this study aimed to investigate the relationship between TyG-WHtR and the risk of CLD in middle-aged and elderly individuals in China, utilizing nationally representative data.

Subjects and Methods: This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS). Baseline data collected between 2011 and 2012 from 17,708 participants were used. We selected individuals aged 45 years and older with no prior history of CLD, resulting in 8,491 eligible participants. The association between the TyG-WHtR and the risk of CLD was assessed using multivariable Cox proportional hazards regression models, adjusting for demographic, lifestyle, and health-related covariates. Missing data were handled using the random forest imputation method. Additionally, restricted cubic splines (RCS) and subgroup analyses were employed to evaluate the relationship between TyG-WHtR and CLD risk in middle-aged and older adults.

Results: In this study, a total of 8,947 participants who met the inclusion criteria were included, with a median follow-up duration of 108 months. During the follow-up period, 3,139 participants were diagnosed with CLD. Cox regression analysis revealed a significant positive correlation between the TyG-WHtR and the risk of CLD in middle-aged and elderly individuals. In the unadjusted model, each unit increase in TyG-WHtR was associated with a 21% higher risk of CLD (HR = 1.21, 95% CI: 1.10–1.33, p < 0.001). In the fully adjusted model, this association remained significant (HR = 1.24; 95% CI: 1.09–1.40; p < 0.001). Further analysis using quartiles showed that, compared to the lowest quartile (Q1), the third quartile (Q3) and highest quartile (Q4) had significantly higher risks of CLD, with a dose–response relationship observed as TyG-WHtR levels increased. Specifically, the risk of CLD was 28%, 37%, and 33% higher in the Q3 group, and 41%, 56%, and 47% higher in the Q4 group. No significant nonlinear trends were observed in the RCS analysis (p > 0.05). Stratified analysis did not reveal any significant interaction effects (p > 0.05).

Conclusions: A higher TyG-WHtR level is significantly associated with an increased risk of CLD. This finding suggests the TyG-WHtR's potential utility for the early identification and screening of CLD risk in middle-aged and elderly populations in China.

Acknowledgements: This study was supported by the Jiangsu Provincial Graduate Training Innovation Program for Scientific Research and Practice (Grant number SJCX25_0965). The funding body had no role in the design of the study and collection, analysis, and interpretation of data, and in writing the manuscript.

Corresponding Author: Xiaofeng Ye, Changzhou Hospital Affiliated to Nanjing University of Chinese Medicine, Changzhou, Jiangsu, China.

English Learning Anxiety, Cognitive Function, and Underlying Physiological Mechanisms in University Students

Qian Zhang

Shandong Sport University, Jinan, Shandong, China

Objectives: Anxiety is increasingly conceptualized as a multidimensional condition characterized by dynamic interactions between cognitive dysfunction and physiological stress-response systems. Accumulating biomedical evidence indicates that anxiety-related cognitive impairment is closely linked to dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, particularly altered cortisol secretion. English learning anxiety represents a prevalent and sustained form of situational anxiety among university students and may serve as a naturalistic stress model for examining psychophysiological mechanisms in non-clinical populations. However, the extent to which English learning anxiety is associated with cognitive function and objective physiological stress markers remains insufficiently investigated from a biomedical perspective. The present study aimed to examine the relationships among English learning anxiety, cognitive function, and HPA-axis activity, with a particular focus on the potential mediating role of cortisol.

Methods: A cross-sectional psychophysiological study was conducted among 147 full-time university students aged 18–25 years. Psychological variables, including English learning anxiety and cognitive function (attention, working memory, and processing efficiency), were assessed using standardized self-report instruments with demonstrated reliability. As an objective physiological indicator, salivary cortisol was collected as a biomarker of HPA-axis activity under standardized morning conditions to control for diurnal variation. Saliva samples were stored at −20 °C and analyzed using enzyme-linked immunosorbent assay (ELISA) procedures. Cortisol values were log-transformed prior to analysis. All continuous variables were standardized using z-score transformation. DMediation analysis was performed to test whether salivary cortisol mediated the relationship between English learning anxiety and cognitive function, with indirect effects estimated using a bootstrapping procedure with 5,000 resamples.

Results: English learning anxiety was significantly negatively associated with cognitive function and positively associated with salivary cortisol levels. Regression analyses demonstrated that both English learning anxiety and cortisol independently predicted cognitive function after controlling for age, sex, and sleep duration. Mediation analysis revealed a significant indirect effect of English learning anxiety on cognitive function through cortisol, indicating partial mediation. These findings suggest that heightened anxiety is associated with increased HPA-axis activation, which in turn may contribute to cognitive impairment.

Conclusions: This study provides psychophysiological evidence that English learning anxiety is associated with impaired cognitive function and elevated cortisol levels among university students. The partial mediating role of cortisol suggests that HPA-axis dysregulation may represent one biological pathway linking situational anxiety to cognitive dysfunction. By integrating psychological assessment with objective endocrine measurement, the present findings extend anxiety research into a biomedical framework and highlight the relevance of stress-related physiological mechanisms in understanding cognitive vulnerability in young adult populations.

Acknowledgements: This project is supported by Research on Innovative Interaction Models in University Foreign Language Classrooms under the AI Perspective (24CRWJ67).

Corresponding Author: Qian Zhang, Shandong Sport University, Jinan, Shandong, China.

Study on the Effect of Dietary Intervention for Elderly Patients with Type 2 Diabetes in the Community Based On the Health Management Service Model

Yang Qian^1,#, Zirui Wang^2,#, Ning Hao^3,*, Shinan Li⁴

¹ PHD, Faculty of Modern Health Care, Anhui Sanlian University, Hefei, Anhui 230601, China

² Faculty of Modern Health Care, Anhui Sanlian University, Hefei, Anhui 230601, China

³ School of sports, Southwest University, Chongqing, 400715, China

⁴ PHD, International Tourism College, Sanya Aviation and Tourism College, Sanya, Hainan, 572000, China

^#These two authors contributed equally to this research.

Objective: To explore the application effect of dietary intervention based on the health management service model in elderly patients with type 2 diabetes mellitus (T2DM) in the community, and to provide empirical evidence for optimizing the chronic disease management strategy in the community.

Subjects and Methods: A total of 100 elderly T2DM patients from a certain community in southern Anhui were selected as the research subjects and randomly divided into the intervention group (n=50) and the control group (n=50). The control group received routine community health education, while the intervention group received a 12-week health management service model-based dietary intervention on top of the routine education, including personalized diet plan formulation, dynamic monitoring, behavior supervision, and multi-dimensional support. As the core of the “five-horse carriage” management system for diabetes, the core goal of dietary intervention is to stabilize postprandial blood glucose fluctuations, reduce the accumulation of glycated hemoglobin (HbA1c), and thereby lower the risk of complications through scientific regulation of total calorie intake, reasonable distribution of nutrient ratios, and selection of low glycemic index foods. After the intervention, the blood glucose indicators (fasting blood glucose FBG, 2-hour postprandial blood glucose 2hPG, and glycated hemoglobin HbA1c), dietary management ability, dietary behavior compliance, and health management satisfaction of the two groups were compared.

Results: After the intervention, the FBG (8.55±1.25 mmol•L⁻¹), 2hPG (10.48±1.50 mmol•L⁻¹), and HbA1c (5.30±0.82%) of the intervention group were significantly lower than those of the control group (P<0.05); the scores of each dimension of dietary management ability (dietary knowledge 4.15±0.45 points, management belief 4.00±0.55 points, management behavior 4.23±0.47 points) and each dimension of dietary behavior compliance (self-monitoring 94.58±3.05 points, carbohydrate and fat management 95.05±2.00 points, etc.) of the intervention group were significantly higher than those of the control group (P<0.05); the health management satisfaction rate of the intervention group (91.83%) was significantly higher than that of the control group (76.00%) (P<0.05).

Conclusions: Dietary intervention based on the health management service model can effectively improve the blood glucose control level of elderly T2DM patients in the community, enhance their dietary management ability and behavior compliance, and increase their satisfaction with health services. It is worthy of promotion and application in the chronic disease management in the community.

Acknowledgements: This work was supported by a project grant from the Anhui Provincial Youth Research Project of the Department of Education, “Research on the Problems and Countermeasures of Age-Friendly Urban Communities in Anhui Province Driven by Generative AI (Grant No.2025AHGXSK40081), the key Project of Humanities and Social Sciences of Anhui Sanlian University “Research on the Construction of a Hierarchical Education and Training System for Caregivers in Community Elderly Care Institutions Based on Competency Model” (Grant No.SKZD2025012), the key Project of Educational Reform Research of University-level Quality Engineering of Anhui Sanlian University “Exploration on the Integration of Curriculum Ideology and Politics and Teaching Model Innovation in Health Information Management Course Based on the Simultaneous Promotion of Five Educations” (Grant No.25zlgc106), the Key Project of Natural Science of Anhui Provincial Education Department: Research on High-Precision Hybrid Force/Position Control for Industrial Robots Driven by Multimodal Perception Fusion(Grant No.2025AHGXZK30891), the Anhui Provincial Department of Education: the Key Natural Science Research Project “Research on the Application of Machine Vision Technology in Anomaly Detection Systems for the Elderly (Grant No.2024AH050520)”; the “Four New” Research and Reform Practice Project (Emerging Engineering) under the Provincial Quality Engineering Program “Research on the 'One-Core Four-Layer' Practical Teaching Model for Robotics Engineering in the Context of the Health and Wellness Industry (Grant No.2024sx195)”; the Key Teaching Reform Research Project under the Provincial Quality Engineering Program “Exploration and Research on ROS Robot Programming Projects under the Scenario-Based Practical Teaching Model (Grant No.2024jyxm0522)”; and the Newly Established Major Quality Enhancement Project under the Provincial Quality Engineering Program “Quality Improvement Project for the Newly Established Major in Electrical Engineering and Intelligent Control (Grant No.2024xjzlts074).”

Corresponding Author: Ning Hao, School of sports, Southwest University, Chongqing City, 400715, China.

Research on the Countermeasure Path of Artificial Intelligence-Assisted Early Chronic Disease Prediction

Jiale Wang^*, Jianhui Li, Jiayu Dong

Shandong University of Technology, Zibo, Shandong, China

Objectives: Chronic diseases such as cardiovascular disease, diabetes, and hypertension have become major global public health challenges. Early identification of high-risk populations and timely intervention are crucial for reducing disease incidence, delaying disease progression, and improving long-term health outcomes. In recent years, the rapid development of artificial intelligence (AI) technologies has created new opportunities for early prediction and prevention of chronic diseases. By integrating large-scale medical and health data, AI-based predictive models can detect potential risk factors and disease patterns at an earlier stage than traditional methods. However, despite its promising potential, the practical application of AI in early chronic disease prediction still faces several challenges, including fragmented health data, limitations in model interpretability, and concerns regarding data privacy and ethical governance.

Methods: This study employs literature analysis and policy analysis to examine the theoretical foundations and practical development of AI-assisted early prediction of chronic diseases. Relevant academic publications, medical AI applications, and health informatics studies were reviewed to analyze the technological mechanisms and application pathways of AI in early chronic disease risk prediction. The study further evaluates the current status of medical data resources, the implementation of AI predictive technologies, and the major barriers affecting their clinical and public health applications.

Results: The analysis shows that AI technologies, particularly machine learning and predictive analytics, can significantly enhance the early identification of chronic disease risks by integrating multi-source health data such as electronic health records, lifestyle information, and clinical indicators. These technologies enable more precise risk stratification and earlier detection of potential disease development. Nevertheless, current applications are constrained by issues such as limited data sharing across healthcare institutions, differences in digital infrastructure, insufficient transparency of predictive models, and concerns about patient privacy protection.

Conclusions: Strengthening the application of AI in early chronic disease prediction requires coordinated efforts in technology, governance, and healthcare systems. Establishing integrated health data platforms, improving algorithm performance and interpretability, enhancing digital capabilities of healthcare institutions, and strengthening data security and ethical regulation are essential steps. These measures will help promote more accurate and timely prediction of chronic diseases and support the transition toward preventive and proactive healthcare management.

Corresponding Author: Jiale Wang, Shandong University of Technology, Zibo, Shandong, China.

Impact of Sequential Positional Management on Mucosal Visualization During Esophagogastroduodenoscopy with Simethicone and Pronase Premedication

Kun Ma, Zhiyong Pang^*, Xiaoyan Li, Zhengyi Pan, Xinpeng Wang, Wenqing Liu, Yongqing Chou

Digestive Endoscopy Center, Hohhot First Hospital, Inner Mongolia, China

Objectives: To investigate whether standardized sequential positional management, when combined with oral premedication of simethicone and pronase, enhances mucosal visualization during EGD, and to evaluate its effects on procedural duration, detection of subtle mucosal lesions, and endoscopist-rated visual field quality.

Methods: A total of 200 patients scheduled for EGD at the Digestive Endoscopy Center of Hohhot First Hospital between September and December 2025 were randomly assigned to either a study group or a control group (n = 100 per group). All participants received oral administration of simethicone powder and pronase granules 15–30 minutes prior to the procedure. In addition, the study group underwent a structured positional protocol consisting of active standing maneuvers followed by passive supine repositioning. Mucosal visibility was assessed using the Mucosal Visibility Score (MVS) across seven predefined anatomical segments: esophagus, gastric fundus, upper and lower gastric body, gastric antrum, duodenal bulb, and descending duodenum. The Total Mucosal Visibility Score (TMVS) was calculated as the sum of individual segment scores. Procedural time, lesion detection rates, and satisfaction ratings from both endoscopists and patients were recorded.

Results: Compared with the control group, the study group exhibited significantly improved mucosal clarity, as evidenced by lower MVS values in the esophagus (1.23 ± 0.423 vs. 1.46 ± 0.576), gastric fundus (1.47 ± 0.559 vs. 1.78 ± 0.690), upper gastric body (1.41 ± 0.534 vs. 1.67 ± 0.711), lower gastric body (1.36 ± 0.482 vs. 1.67 ± 0.792), and gastric antrum (1.27 ± 0.468 vs. 1.49 ± 0.628), as well as a lower TMVS (9.19 ± 1.727 vs. 10.47 ± 2.907; all P < 0.05). The mean procedural duration was significantly shorter in the study group (11.64 ± 3.29 min vs. 12.63 ± 3.02 min; P < 0.05). Detection rates of subtle mucosal lesions—including erosions (59% vs. 44%), polypoid hyperplasia (34% vs. 20%), and depressed mucosal lesions (17% vs. 7%) were significantly higher (P < 0.05 for all). Endoscopist-rated visual field satisfaction was markedly greater in the study group (84% vs. 72%; χ² = 4.348, P < 0.05). Patient-reported satisfaction did not differ significantly between groups (93% vs. 95%; P = 0.551).

Conclusions: The integration of sequential positional management—comprising active standing exercises followed by passive supine repositioning—with standard simethicone and pronase premedication significantly improves mucosal visualization during EGD. This approach reduces procedural time and enhances the detection of subtle mucosal lesions. Given its simplicity, cost-effectiveness, and lack of requirement for additional equipment, this protocol holds considerable promise for implementation in routine clinical practice and large-scale gastric cancer screening programs, particularly in resource-limited settings.

Corresponding Author: Zhiyong Pang, Digestive Endoscopy Center, Hohhot First Hospital, Inner Mongolia, China.

Experimental Study on the Effect of Oleanolic Acid on Reducing NLRP3 Inflammasome Expression via the TLR2/NF-κB Pathway

Shunying Zhang^1,2, Xuejuan Zan², Fang Wang², Yu Cao^1,*

¹ Department of Dermatology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China

² Department of Dermatology, Xingyi People’s Hospital, Xingyi, Guizhou, China

Objective: To investigate the regulatory effect of oleanolic acid (OA) on the TLR2/NF-κB signaling pathway in the inflammatory response of macrophages induced by Propionibacterium acnes (C. acnes).Method: The experiment took mouse mononuclear macrophage RAW264.7 as the research object, dividing the cells into three groups: the blank control group, the inflammatory model group induced by Propionibacterium acnes (C. acnes), and the group treated with C. acnes combined with OA.

Methods: The macrophage inflammatory model was established in mouse RAW264.7 cells by using C.acnes. The proliferation inhibition rate of RAW264.7 cells was detected by CCK-8 to evaluate the effect of OA on cell activity. The expression levels of IL-1β, IL-18, IL-6, and NLRP3 mRNA in the supernatant of mouse RAW264.7 macrophages were detected by real-time fluorescent quantitative qPCR. The expression changes of NLRP3 inflammatory body and TLR2-related signaling pathway proteins were analyzed by Western blot. The secretion levels of inflammatory factors IL-1β, IL-6, and IL-18 in the cell supernatant were determined by enzyme-linked immunosorbent assay (ELISA).

Results: The CCK-8 results indicated that when the OA concentration was within the range of 0 to 80 μM, there was no statistically significant difference in cell survival rate (P > 0.05), meaning that OA had no obvious toxic effect on RAW264.7 cells. The results of qPCR, Western blot and ELISA were consistent, indicating that compared with the blank group, C. acnes stimulation could significantly up-regulate the protein expression of NLRP3 inflammasome and TLR2 in RAW264.7 cells, as well as the mRNA expression levels of IL-6, IL-8 and NLRP3, and promote the secretion of IL-1β, IL-6 and IL-18 in the cell supernatant. Compared with the C. acnes model group, OA treatment significantly reduced the protein expression of NLRP3 inflammasome and TLR2 in RAW264.7 cells, as well as the mRNA expression levels of IL-1β, IL-18 and NLRP3. At the same time, it inhibited the secretion of inflammatory factors IL-1β, IL-6 and IL-18 in the cell supernatant.

Conclusion: Oleanolic acid can inhibit the expression of NLRP3 inflammasome and TLR2 by affecting the TLR2/NF-κB signaling pathway, thereby reducing the generation and release of inflammatory factors IL-1β, IL-6 and IL-18, and effectively alleviating the macrophage inflammatory response induced by C. acnes. This provides experimental evidence for the application of OA in the treatment of acne and related inflammatory skin diseases.

Acknowledgements: 2024 Annual Joint Medical Research Fund for High-Quality Development of Health Care in Guizhou Province (grant number: 2024GZYXKYJJXM0089).

Corresponding Author: Yu Cao, Department of Dermatology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.

Monitoring Neurological Disease Progression Using Gamma Oscillations Recorded with OPM-MEG

Ruiyang Zhang

University of Birmingham, Birmingham, B15 2TT, United Kingdom

Objective: Visual gamma oscillations reflect the functional integrity of cortical inhibitory-excitatory circuits and have been implicated, across the broader literature, in various neurological and neuropsychiatric conditions. This study leverages the high sensitivity of OPM-MEG to characterize visually evoked gamma responses in a healthy participant, with the aim of establishing a robust assay that could, in future applications, support disease monitoring, intervention assessment, and treatment efficacy evaluation in clinical populations.

Subjects and Methods: A healthy adult participant completed seven separate OPM-MEG sessions over multiple days, viewing high-contrast drifting grating stimuli known to robustly elicit sustained visual gamma responses. A total of 393 trials were collected using a wearable, on-scalp OPM array positioned over the occipital cortex. Time-frequency decomposition was applied to extract induced gamma-band power, and within-subject effect sizes were estimated using Cohen’s d. Leveraging observed within- and between-session variance components, we constructed two-dimensional statistical power contours that illustrate the trade-offs between the number of participants (N) and the number of trials per participant (k) required to achieve 80% statistical power for detecting gamma modulation, a critical consideration for longitudinal monitoring and intervention studies in patient cohorts.

Results: The visual stimulus reliably elicited a strong, sustained increase in gamma-band power (peaking at ∼55 Hz) over occipital sensors, with a maximum within-subject effect size of Cohen’s d ≈ 1.50. Cluster-based permutation testing confirmed a statistically significant gamma response (p < 0.05, cluster-corrected) persisting from ∼300 ms to 2 seconds post-stimulus onset. Power contour analysis demonstrated that detecting such a large effect with 80% power is feasible with modest sample sizes, for instance, as few as 15–20 participants each contributing 70–100 trials. Importantly, the contours reveal rapidly diminishing returns beyond ∼100 trials per subject, enabling efficient resource allocation without compromising sensitivity, particularly valuable in clinical populations where data collection may be limited by fatigue or cognitive impairment.

Conclusions: Our results confirm that OPM-MEG provides exceptional sensitivity for capturing gamma oscillations, positioning it as a powerful platform for objective, circuit-level monitoring of neurological disease trajectories. The derived power contours offer practical, data-driven guidelines for designing well-powered studies aimed at tracking neurodegeneration, assessing pharmacological or neuromodulatory interventions, and evaluating treatment response in real-world clinical settings. As gamma dynamics reflect underlying GABAergic and glutamatergic function, this approach holds significant promise for advancing precision neurology and personalized therapeutic strategies.

Corresponding Author: Ruiyang Zhang, University of Birmingham, Birmingham, B15 2TT, United Kingdom.

Application and Implementation of Genomic Data Intelligence in Precision Diagnosis and Treatment under the Framework of Data Rule of Law

Yuxin Wang^*, Jiarui Tang

Shandong University of Technology, Zibo, Shandong, China

Objectives: With the advancement of precision medicine, genomic data has become a core resource in contemporary biomedicine and clinical care. Biomedical approaches such as next generation sequencing, clinical genomics analysis, and AI driven interpretation are increasingly applied to support disease prediction, molecular diagnosis, and individualized treatment. As a key biomedical tool, the intelligent interpretation of genomic data significantly improves the identification of pathogenic variants and the stratification of complex diseases. It also promotes a deeper understanding of disease mechanisms in areas such as oncology, rare inherited disorders, and pharmacogenomics.

Methods: This study combines a biomedical application perspective with systematic analysis to investigate the implementation of intelligent genomic data interpretation in precision diagnosis and treatment. It examines how biomedical approaches, including genomic sequencing workflows, bioinformatics pipelines, and clinical decision support systems, function across the stages of data generation, analysis, and clinical translation. Through comparative analysis and scenario based evaluation, the study assesses how genomic data intelligence supports the discovery of disease associated variants, the interpretation of molecular mechanisms, and the optimization of individualized therapeutic strategies. Particular attention is given to its practical value in improving diagnostic efficiency, treatment selection, and translational biomedical research in real world clinical settings.

Results: The results show that the application of advanced biomedical methods greatly enhances the value of genomic data in precision diagnosis and treatment, especially in areas such as tumor molecular classification, rare disease diagnosis, drug response prediction, and personalized therapy. Intelligent interpretation improves the speed and accuracy of variant detection, strengthens the association between genotype and phenotype, and supports clinicians in identifying clinically actionable biomarkers. In oncology, it contributes to more precise patient stratification and targeted treatment selection. In inherited diseases, it increases diagnostic yield for previously unresolved cases. In pharmacogenomics, it helps predict therapeutic response and adverse drug reactions. Although differences in data quality, algorithm performance, and clinical integration remain, genomic data intelligence has demonstrated substantial biomedical significance.

Conclusions: This study concludes that the effective application of intelligent genomic data interpretation in precision diagnosis and treatment mainly depends on the coordinated integration of genomic technologies, biomedical knowledge, and clinical practice. Biomedical approaches such as genomic sequencing, bioinformatics analysis, and clinical decision support not only improve diagnostic accuracy and individualized treatment, but also deepen the understanding of disease biology. In the future, greater attention should be given to optimizing interpretation models and strengthening their connection with specific biomedical scenarios, including cancer management, rare disease identification, and medication guidance, so as to improve diagnostic efficiency, therapeutic outcomes, and the overall quality of healthcare.

Corresponding Author: Yuxin Wang, Shandong University of Technology, Zibo, Shandong, China.

Classification of Sports Bandaging Techniques and Characteristic Analysis of Intramuscular Adhesives for Sports Rehabilitation

Jian Li¹, Kexin Ma², Yongdong Liu³, Puzhu Han⁴, Quan Tang⁵, Lina Zhang⁶, Wenyuan Cao⁷, Xin Li⁸, Jianxin Zhang^1,*

¹ Sport Institute, Liaoning Institute of Science and Engineering, Jinzhou 121000, China

² The Second Hospital Affiliated Dalian Medical University, Dalian 116000, China

³ The Second Hospital Affiliated Southern University of Science and Technology, Shenzhen 518000, China

⁴ Hongkong City University, Hongkong 999077, China

⁵ No.7 Middle School of Dalian Development Zone, Dalian 116000, China

⁶ Dalian Jinshitan Hospital, Dalian 116000, China

⁷ The Xinhua Hospital Affiliated Dalian University, Dalian 116000, China

⁸ Independent Scholar, London, NW10 0AD, UK

Objectives: Sports injuries frequently result in musculoskeletal dysfunction and prolong the rehabilitation process for athletes. Scientific protective interventions play a crucial role in reducing injury risks and accelerating recovery. This study aims to establish a classification system for sports taping techniques based on biomedical principles and systematically analyze the unique characteristics of kinesiology tape in injury prevention and rehabilitation. This research provides scientific evidence for selecting sports protective equipment, assisting athletes, sports medicine practitioners, and researchers in optimizing injury prevention strategies and rehabilitation protocols, thereby enhancing musculoskeletal protection and functional recovery outcomes.

Subjects and Methods: This study focuses on athletic taping techniques and kinesiology tape as core subjects. It employs a systematic classification method based on three biomedical dimensions: functional positioning (injury prevention, joint stabilization, muscle support, rehabilitation assistance), material properties (biocompatibility, elasticity, breathability, adhesive durability), and application scenarios (acute injury first aid, chronic injury management, high-intensity sports protection, postoperative rehabilitation). Integrating clinical practice data from sports medicine, this study comprehensively evaluated differences among traditional bandages, conventional sports protective gear, and kinesiology tape from a biomedical perspective. Comparisons analyzed fixation mechanisms (mechanical compression vs. muscular adhesion), maintenance of movement flexibility, wear comfort, rehabilitation promotion effects (improved blood circulation, muscle tone regulation), and clinical applicability.

Results: The study established a technical classification system for athletic tapes, clearly defining the core characteristics and applications of different tape types: Preventive tapes focus on reducing musculoskeletal stress through mechanical support. Rehabilitation-assistive tapes prioritize regulating muscle function and promoting tissue repair. High-elasticity tapes balance flexibility and support, making them suitable for dynamic athletic scenarios. Compared to traditional bandages and conventional protective gear, kinesiology tape demonstrates unique advantages in biomedical effects: its muscle-adhesive fixation mechanism enables precise support without restricting joint mobility; it maintains stable fixation during high-intensity activities; excellent breathability and biocompatibility enhance wear comfort; it promotes local blood circulation and alleviates muscle tension, thereby accelerating rehabilitation; and they offer broader applicability in acute injury management, chronic pain relief, and postoperative functional recovery.

Conclusions: The classification of athletic tape technologies by functional positioning, material properties, and application scenarios provides a standardized reference for selecting sports protection equipment in sports medicine. Kinesiology tape demonstrates significant application value in injury prevention and rehabilitation due to its superior fixation effects, adaptability to movement, wear comfort, and rehabilitation-promoting capabilities. This technology enriches sports medicine intervention methods, providing effective support for enhancing athletic performance and promoting recovery from sports-related injuries. Future research may further optimize the biocompatibility and adhesive durability of kinesiology tape while expanding its application scope in specialized sports and complex injury rehabilitation, thereby advancing evidence-based sports medicine.

Corresponding Author: Jianxin Zhang, Sport Institute, Liaoning Institute of Science and Engineering, Jinzhou 121000, China.

Analysis of Screening Results for Chronic Obstructive Pulmonary Disease among Elderly People in a Community Health Service Institution in Hangzhou City

Huiqin Xu^1,*, Liuqing Cheng¹, Jinling Liu², Pu Rao¹

¹ Community Health Service Center of Wulin Street in Tianshui, Gongshu District, Hangzhou, Zhejiang, 310003, China

² Zhejiang Shuren University Shulan International Medical College, Hangzhou, Zhejiang, 312028, China

Objectives: To understand the prevalence of chronic obstructive pulmonary disease (COPD) among elderly people in the Tianshui Wulin Street community of Gongshu District, Hangzhou City, and to provide a basis for community management and intervention of COPD.

Methods: Chronic obstructive pulmonary disease questionnaire screening was conducted on elderly people aged 65 and above in the Wulin Street community of Tianshui. Simple lung function tests were conducted on high-risk individuals for chronic obstructive pulmonary disease, and basic characteristic analysis was conducted.

Results: A total of 1540 questionnaires were screened, and 338 high-risk individuals were identified. Among them, 338 underwent lung function screening, with a response rate of 100%. 135 males (39.9%) and 203 females (60.1%). 101 smokers (29.9%) and 237 non-smokers (70.1%). The average age is 69.30 ± 3.49 years old. 45 people met the diagnostic criteria for chronic obstructive pulmonary disease (with a prevalence rate of 13.3% in high-risk populations). The predicted FEV1%, FVC, and FEV1/FVC (i.e. 1-second rate) in the smoking group were lower than those in the non-smoking group, with t values of -4.79, 8.64, and -5.00, respectively. The P-values were all less than 0.01, and the differences were significant. There is a statistically significant difference (P<0.05) in the gender comparison between the chronic obstructive pulmonary disease group and the non chronic obstructive pulmonary disease group. The difference in smoking was statistically significant (P<0.05). There was no statistically significant difference in family history (P>0.05). The self-evaluation test questionnaire score (CAT) of patients with chronic obstructive pulmonary disease (COPD) showed statistical significance in the one-way ANOVA of FEV1/FVC in the COPD group (P<0.05). The follow-up rate of 68.9 % of smokers increased after receiving nurse-led smoking cessation intervention.

Conclusions: Screening for high-risk groups of COPD in the community can improve the detection rate of COPD, and community nursing intervention can significantly improve the self-management ability of patients with COPD. Community health service institutions should guide family doctors and nursing staff to intervene and control COPD patients in the community as early as possible, and provide targeted nursing to reduce the complications and mortality of COPD.

Corresponding Author: Huiqin Xu, Community Health Service Center of Wulin Street in Tianshui, Gongshu District, Hangzhou, Zhejiang, 310003, China.

Learning from the Past: Durability Assessment of Cultural Heritage Ceramic Adhesives Adhesives Informing Next-Generation Bone Cements

Luo Tian*

Jingdezhen Ceramic University, Jingdezhen, China

Background: Modern poly(methyl methacrylate) (PMMA) bone cements face clinical challenges such as long-term instability, low bioactivity, and monomer toxicity. In contrast, natural mineral-organic composite adhesives, used for millennia in the restoration and preservation of cultural heritage ceramics (e.g., Chinese lacquer-lime, gypsum-egg white, and lime-pozzolan systems),exhibit exceptional durability. The scientific analysis of these historical ceramic repair materials provides a unique repository of bio-inspired design principles for overcoming the limitations of synthetic biomaterials.

Objective and Methods: This study aims to systematically deconstruct the chemical composition, multi-scale microstructure, and mechanical performance of representative historical ceramic adhesives. By evaluating their degradation resistance and identifying key durability factors, we seek to extract fundamental design principles to guide the development of a novel, more resilient, and bioactive bone cement for orthopedic applications. Archaeological adhesive samples from documented ceramic restoration contexts were characterized using SEM-EDS, XRD, and FTIR. Their durability was quantified through accelerated hygrothermal aging tests and mechanical shear/tensile strength measurements. Informed by the key mechanisms identified-specifically, multi-phase reinforcement and robust organic-inorganic interfacial bonding-a prototype composite bone cement was synthesized. It incorporates biomimetic calcium silicate phases and natural polymer cross-linkers inspired by the historical formulations. Its biocompatibility, bioactivity (hydroxyapatite formation in SBF), and mechanical stability were evaluated. In vitro models assessed osteoblast proliferation/differentiation and osteoclast activity reduction.

Results: Analysis confirmed that the outstanding longevity of historical ceramic adhesives stems from their optimized composite architecture and synergistic cross-linking. The novel bio-inspired bone cement, derived from these principles, demonstrated significantly improved fatigue resistance and bioactivity. Crucially, in vitro biological evaluation showed a marked reduction in osteoclast resorptive activity alongside enhanced osteoblast differentiation, with a simulated bone ingrowth depth increase of approximately 20% compared to standard PMMA controls.

Conclusions: This work pioneers the translation of design principles extracted from the analysis of durable cultural heritage repair materials to address the clinical bottlenecks of PMMA bone cements. It validates that reverse-engineering historical ceramic adhesives can effectively inform the creation of next-generation bone cements with superior stability and biological integration. The developed biomimetic cement demonstrates significant potential to reduce the risk of aseptic loosening in preclinical models, outlining a promising and innovative clinical translation pathway for improving the long-term success of total joint arthroplasty. This research establishes a novel conduit between archaeological materials science and clinical orthopedics.

Corresponding Author: Luo Tian, Jingdezhen Ceramic University, Jingdezhen, China.

Constipation, Insulin Resistance, and Negative Symptoms in Schizophrenia: A Gut–Brain–Immune–Metabolic Axis and the Adjunctive Role of Probiotics

Yan Shuang¹, Yu Liu¹, Yingzhe Liu^2,*

¹ Heilongjiang University of Chinese Medicine, Heilongjiang 150000, China

² The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Heilongjiang 150040, China

Objective: To synthesize evidence linking constipation, insulin resistance, and persistent negative symptoms in schizophrenia within a gut-brain-immune-metabolic framework, and to appraise the potential adjunctive role of probiotic-based microbiota modulation for high-risk clinical subgroups.

Subjects and Methods: We conducted a structured narrative review of English-language human and animal studies indexed in PubMed, Web of Science, and ClinicalTrials.gov through October 28, 2025. Search terms combined “schizophrenia” with gut microbiota/microbiome, dysbiosis, probiotics, prebiotics, constipation, gastrointestinal hypomotility, insulin resistance, metabolic syndrome, negative symptoms, cognition, short-chain fatty acids (SCFAs), and the gut-brain axis. Evidence was integrated qualitatively to build a clinically usable model emphasizing bowel safety, metabolic stability, inflammatory tone, and functional outcomes; no pooled meta-analytic estimates or formal risk-of-bias grading were performed.

Results: Across observational, mechanistic, and interventional literature, schizophrenia is repeatedly associated with gut microbiota dysbiosis characterized by reduced microbial diversity, depletion of SCFA-producing commensals, and enrichment of potentially pro-inflammatory taxa. These shifts are linked to impaired intestinal barrier integrity, systemic low-grade inflammation, altered neuroactive metabolite signaling, and slowed gastrointestinal transit—processes that can converge on severe constipation, metabolic stress, and reduced motivational and cognitive capacity. Antipsychotics may further amplify dysbiosis and gut hypomotility, creating a feedback loop between constipation and inflammation. Microbiota-targeted strategies (probiotics, prebiotic fiber, and synbiotics) are reported to strengthen mucosal barrier function, modulate inflammatory pathways (including reductions in circulating CRP in meta-analytic data), improve bowel motility and colonic water handling, and attenuate early antipsychotic-associated weight gain. Limited trials and meta-analyses suggest modest improvements in symptom scores, with effects likely dependent on baseline microbiome and clinical phenotype; co-supplementation approaches (e.g., probiotics plus fiber, vitamin D, or selenium) show promise for metabolic indices including insulin sensitivity.

Conclusions: Constipation, insulin resistance, and negative symptoms in schizophrenia should be viewed as interconnected outputs of a gut-brain-immune-metabolic dysregulation rather than isolated comorbidities. Probiotics and related microbiota interventions appear most appropriate as structured adjuncts—especially for patients on constipating or metabolically high-liability antipsychotics, those with recurrent constipation or early metabolic deterioration, and those with prominent inflammatory burden—not as replacements for antipsychotic therapy. Future trials should stratify participants by bowel, inflammatory, and metabolic phenotypes and report clinically meaningful safety and functional endpoints over longer follow-up.

Acknowledgements: This work was supported by the Heilongjiang Provincial Natural Science Foundation Project: Mechanistic Study on How Brazilin Inhibits Autophagy to Prevent Copper-Induced Cell Death in Peripheral Nerve Cells and Alleviate Diabetic Peripheral Neuropathy (PL2024H214).

Corresponding Author: Yingzhe Liu, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Heilongjiang 150040, China.

The Impact of Embodied Human-Computer Interaction on College Students' Anxiety in Ideological and Political Courses and Their Cortisol Levels

Saiyu Zhang

Minjiang University, Fuzhou, Fujian, 350108, China

Objectives: This study focuses on the emotional regulation effect of embodied human-computer interaction integrated into ideological and political courses in universities. It examines the influence of embodied intelligent robots' intervention on college students' learning anxiety, classroom expression pressure, concerns about peer evaluations, and saliva cortisol levels. It also analyzes the psychological and physiological linkage process triggered by the presence of the physical entity, voice interaction, action feedback, and situational companionship, providing empirical evidence for classroom emotional support, stress intervention, and optimization of intelligent teaching.

Methods: A real classroom quasi-experimental design was adopted, with parallel teaching classes of ideological and political courses in universities serving as the basis for setting up embodied human-machine interaction groups and conventional teaching groups. The experimental group introduced embodied intelligent robots during the teacher's lecture, case discussion, and classroom feedback, which were responsible for context introduction, question inquiry, viewpoint repetition, and companionship interaction. The control group maintained the original teaching process. Data were collected during the pre-class baseline, immediate post-class, and follow-up stages, including learning anxiety, achievement emotions, robot perception evaluation, classroom participation behavior, and saliva cortisol levels. Classroom behaviors were encoded and processed through video recording, and cortisol samples were tested according to a unified procedure. Data analysis employed repeated measures models, linear mixed models, and mediation path tests.

Results: The group of embodied human-computer interaction had lower learning anxiety in ideological and political education courses both immediately after class and during the follow-up period compared to the conventional teaching group. Their levels of nervousness during classroom participation, concerns about peer evaluations, and stress from theoretical debates all decreased. Saliva cortisol tests indicated that the experimental group had a more stable physiological stress response after class, with smaller fluctuations in cortisol levels. Behavioral coding showed that the intervention of the robot enhanced students' active responses, expression of viewpoints, group discussions, and non-verbal interactions, while reducing silence and avoidance. The robot's affinity, perceived security, and companionship were related to anxiety relief and played a certain mediating role, indicating that embodied intelligent robots can help improve classroom emotions and promote the regulation of physical and mental stress.

Conclusions: Embodied human-computer interaction provides new classroom evidence for the intervention of learning anxiety in ideological and political courses in universities. The embodied intelligent robot, relying on physical presence, situational guidance, voice response and multimodal feedback, alleviates students' tense experiences during theoretical analysis, classroom participation and peer evaluation, promoting the shift from cautious responses to active expressions in the classroom. The changes in saliva cortisol levels indicate that the intervention of the robot helps to calm the classroom stress response, forming an effect where psychological stress reduction and physiological regulation occur simultaneously, providing a reference for emotional support and classroom experience optimization in intelligent teaching.

Acknowledgements: This research was supported by the “2025 National Social Science Foundation Project on Ideological and Political Education: Research on the Progressive Presentation of Marxist Classic Works in College Ideological and Political Courses (25VSZ180)".

Corresponding Author: Saiyu Zhang, Minjiang University, Fuzhou, Fujian, 350108, China

Research on Pathological Precision Interventions for College Students' Mental Health Based on Systems Biology Methods

Qian Wang, Quan Luo^*

Wuhan Railway Vocational College of Technology, Wuhan, Hubei, 430205, China

Background: The incidence of psychological and pathological issues (such as major depressive disorder and anxiety disorders) among college students continues to rise. The resulting cognitive impairment, academic disruption, social dysfunction, and even suicide risk have become a serious public health challenge. Traditional intervention approaches often lead to poor efficacy and high relapse rates due to their neglect of the significant biological heterogeneity among individuals. Increasing evidence suggests that individuals with similar clinical symptoms may carry vastly different genetic susceptibilities, immunoendocrine characteristics, neural circuit functions, and environmental exposure histories. This deep biological heterogeneity directly leads to the core challenges in current intervention practices, such as wide variations in efficacy, high relapse rates, and a lack of targets for preventive interventions. Therefore, breaking free from the constraints of symptom presentation, thoroughly analysing the biological essence of psychopathology, and developing entirely new precision intervention paradigms on this basis has become an urgent need and inevitable direction for achieving breakthrough progress in the field of university student mental health.

Subjects and Methods: To construct and preliminarily validate a precision intervention research framework based on systems biology approach to elucidate the biological subtypes of psychological pathology in college students and to guide personalized treatment strategies accordingly. We established a prospective cohort study incorporating a multidimensional data evaluation system: 1) Clinical and psychological assessments: Utilized standardized diagnostic interviews and a series of scales to evaluate symptom severity and cognitive function; 2) Multi-group biomarker analysis: Including genomic screening, peripheral blood inflammatory cytokines, and metabolite profiling; 3) Digital phenotyping monitoring: Continuously collected physiological and behavioral data via wearable devices. Machine learning algorithms were employed to integrate and analyze multi-source data, identifying distinct biological subtypes and matching them with targeted intervention modules (e.g., anti-inflammatory interventions combined with psychotherapy for the “high-inflammation subtype").

Results: Preliminary application demonstrated that, compared to conventional treatment, precision intervention guided by this framework significantly alleviated target symptoms. For instance, patients in the matched intervention group showed a 35% greater reduction in core depressive and anxiety symptoms on average after 8 weeks compared to the control group, with a shorter time to effect. Biomarker analysis further confirmed that symptom improvement was significantly correlated with the modulation of specific pathophysiological pathways (e.g., inflammatory levels).

Conclusion: The system biology framework established in this study successfully transforms multidimensional biological information into actionable clinical intervention strategies, demonstrating its potential to enhance therapeutic efficacy. This model lays a methodological foundation for the comprehensive management of psychological pathology in college students, encompassing “classification-precision intervention-therapeutic prediction,” and highlights the significant application prospects for advancing mental health services toward the paradigm of precision medicine.

Acknowledgements: This work was supported by a project grant from 2025 School Student Work Research Special Project “Research on the Pathways and Mechanisms for Cultivating Positive Psychological Qualities of University Students: A Case Study of W College” (No.: Y2025XG001).

Corresponding Author: Quan Luo, Wuhan Railway Vocational College of Technology, Wuhan, Hubei, 430205, China.

YY1-LSD1 Axis in Nasopharyngeal Carcinoma Cell Proliferation and Cell Cycle Progression

Mingming Zhou¹, Yun Jiang², Qiutong Lu², Qinyi Yang³, Jincen Cai³, Haotian Dinig², Xinrui Wu³, Jie Ding^4,*, Jie Zhang^2,*

¹ Nantong Health Vocational College, Nantong, Jiangsu 226001, China

² Nantong University Xinglin College, Nantong University, Nantong, Jiangsu 226001, China

³ School of Medicine, Nantong University, Nantong, Jiangsu 226001, China

⁴ Department of Laboratory Medicine, Jingjiang Hospital of Traditional Chinese Medicine, Jingjiang, Jiangsu 214504, China

Objectives: Nasopharyngeal carcinoma (NPC) is a malignant tumor predominantly diagnosed in populations from Southern China and Southeast Asia. Due to the lack of specific symptoms detectable in the early stages of NPC, timely diagnosis remains challenging. Therefore, it is urgent to elucidate the underlying mechanisms governing NPC cell proliferation and apoptosis to develop more effective therapeutic strategies. Yin Yang 1 (YY1) is a multifunctional DNA-binding transcription factor that plays crucial roles in various biological processes. However, the dynamic alterations of NPC cells during YY1-associated proliferation and the underlying molecular mechanisms remain to be fully clarified.

Methods: We utilized the bioinformatics tool JASPAR to predict potential YY1 binding sites within the LSD1 promoter region. Two NPC cell lines, HNE2 and CNE2, were employed in this study. HNE2 cells were transfected with YY1-specific siRNA plasmids to knockdown YY1 expression. Cell proliferation, apoptosis, and cell cycle distribution were analyzed by flow cytometry (FCM). The expression levels of proliferation marker PCNA and apoptosis marker Cleaved-Caspase were detected by Western blot. Chromatin immunoprecipitation (ChIP) assays were performed to confirm the binding of YY1 to the LSD1 promoter region in vivo following YY1 knockdown in HNE2 cells.

Results: In this study, knockdown of YY1 using small interfering RNA (siRNA-YY1) resulted in S-phase cell cycle arrest and increased apoptosis in HNE2 cells. Concurrently, LSD1 expression was reduced, while the levels of H3K4me2 and H3K9me were accumulated compared to the control group. Conversely, overexpression of YY1 (OE-YY1) significantly upregulated LSD1 expression, enhanced NPC cell proliferation, and reduced the proportion of apoptotic cells compared to the control group.

Conclusions: The findings suggest that YY1 can bind to and promote the expression of LSD1 promoter region in nasopharyngeal carcinoma cells, thus affecting the proliferation, apoptosis and cell growth cycle of nasopharyngeal carcinoma cells, and these results may provide potential candidates for prognostic markers and therapeutic targets for NPC.

Acknowledgements: This study was supported in part by Jingjiang Science and Technology Bureau Project (MS22022047).

Corresponding Author: Jie Ding, Department of Laboratory Medicine, Jingjiang Hospital of Traditional Chinese Medicine, Jingjiang, Jiangsu 214504, China; Jie Zhang, Nantong University Xinglin College, Nantong University, Nantong, Jiangsu 226001, China.

Neural Correlates and Clinical Outcomes of Traditional Chinese Opera Cultural Identity in Youth: An fNIRS- and EEG-Based Study of Emotion Regulation Pathways for Culturally Adapted Psychological Intervention

Xinqiang Zhang

School of Culture and Communication, Zhejiang Wanli University, Ningbo, Zhejiang, China

Objective: From a clinical intervention perspective, this study aimed to identify neural and behavioral pathways through which traditional Chinese opera cultural identity influences emotion regulation, self-efficacy, and social functioning in young people, and to develop a culturally adapted, low-intensity psychological intervention program supported by neurophysiological evidence.

Methods: A mixed-methods design was employed, combining Grounded Theory (GT) and fuzzy-set Qualitative Comparative Analysis (fsQCA) with neurophysiological measurements. A total of 217 university students enrolled in an opera appreciation course completed semi-structured interviews (n=18) and questionnaires (n=217). Based on configurational pathways identified from the full sample, a subsample of 48 participants (16 per pathway type: aesthetic-internalized, practice-embedded, and media-representation) underwent functional near-infrared spectroscopy (fNIRS) recording over the dorsolateral prefrontal cortex (DLPFC) and frontopolar cortex, along with resting-state electroencephalography (EEG) to measure frontal alpha asymmetry (an index of approach/withdrawal motivation). Salivary cortisol levels were collected before and after a 30-minute opera-based emotion recognition task. Clinical assessments included the Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire (PHQ-9), Difficulties in Emotion Regulation Scale (DERS), and Social Adaptation Self-evaluation Scale (SASS) at baseline and after an 8-week opera-based group intervention (role imitation, aria emotion recognition, and creative narrative reconstruction).

Results: Five configurational pathways of opera cultural identity were identified. The aesthetic-internalized and practice-embedded pathways showed significantly reduced DERS scores (β = -0.42, p < 0.01) and increased SASS scores (β = 0.38, p < 0.01) compared to the media-representation pathway. Neurophysiologically, participants in the aesthetic-internalized pathway exhibited greater increase in DLPFC oxygenated hemoglobin (HbO) during the emotion recognition task (mean ΔHbO = 0.28 ± 0.07 μM, p < 0.01) and a more positive frontal alpha asymmetry (FAA) shift (ΔFAA = 0.15 ± 0.04, p < 0.05), indicating enhanced approach motivation. The practice-embedded pathway was associated with a significant reduction in salivary cortisol after role imitation (pre: 12.4 ± 2.1 nmol/L; post: 9.1 ± 1.8 nmol/L, p < 0.01) and increased frontopolar HbO. After the 8-week intervention (12 sessions, 60 min each), the intervention group (n=32) showed a mean reduction of 4.2 points on PHQ-9 (p < 0.001) and 3.8 points on GAD-7 (p < 0.001), with a clinical response rate (≥50% symptom reduction) of 46.9%, compared to 12.5% in a waitlist control group (n=16). Mediation analysis indicated that changes in DLPFC activation partially mediated the effect of opera aesthetic experience on emotion regulation improvement (indirect effect = -0.23, 95% CI: -0.41 to -0.09).

Conclusion: Youth cultural identity with traditional Chinese opera exhibits distinct neural and endocrine profiles. The aesthetic-internalized and practice-embedded pathways enhance emotion regulation and social adaptation through increased prefrontal cortical activation and cortisol reduction. A 12-session, opera-based group intervention program is proposed as a culturally adapted, low-intensity adjunctive treatment for mild-to-moderate depression and anxiety in young people. Future randomized controlled trials should validate its efficacy against active comparators.

Acknowledgments: National Social Science Fund of China, General Project of Art Studies – A Study on the Unique Acrobatic Techniques in Traditional Chinese Opera Performance (2025, Project No. 25BB042)

Corresponding Author: Xinqiang Zhang, School of Culture and Communication, Zhejiang Wanli University, Ningbo, Zhejiang, China.

An Extended Review of the Clinical Significance of Continuous Carotid Ultrasound Monitoring in Cardiac Arrest Resuscitation

Sibin Tao, Fuchun Li, Xinlei Huang, Dongbin Lu, Wenbo Yu, Zhenyu Wen^*

The Third Affiliated Hospital of Jiaxing University (Zhejiang Rongjun Hospital), Jiaxing, Zhejiang, China

Objective: This study aims to summarize the clinical application value of point-of-care carotid artery compression ultrasound (POCUS-CAC) in cardiac arrest resuscitation based on existing evidence.

Subjects and Methods: This review was conducted through a comprehensive analysis of retrieved Chinese and English literature. Databases included PubMed, EMBASE, and China National Knowledge Infrastructure (CNKI), with search terms including “cardiac arrest”. “cardiopulmonary resuscitation”. “carotid ultrasound”. “POCUS”. “ROSC”. etc. Included literature types covered randomized controlled trials, prospective cohort studies, retrospective analyses, guideline consensuses, and narrative reviews. Special focus was placed on guidelines from the American Heart Association (AHA), European Resuscitation Council (ERC), and expert consensus in the field of emergency medicine in China, as well as recent studies published in authoritative journals. Search results were screened to exclude studies irrelevant to the topic or of low quality. The authors read full texts and extracted key information, which was categorized and organized according to themes including ROSC determination, rhythm classification, cerebral perfusion assessment, and comparison of monitoring tools.

Results: Existing evidence demonstrates that POCUS-CAC requires only 1.62–2.3 seconds on average to identify a pulse, significantly shorter than the 3.50–4.7 seconds required for manual palpation, with 100% sensitivity and 87.5% specificity for ROSC detection. The technique can reliably identify carotid pulsations at systolic blood pressures as low as 19 mmHg, and distinct carotid blood flow waveforms correspond to different malignant rhythm states (ventricular fibrillation, pulseless electrical activity, etc.). Carotid Doppler peak systolic velocity (PSV) ≥20 cm/s shows 89% accuracy for predicting ROSC, which is superior to traditional end-tidal carbon dioxide thresholds. CAC can also distinguish pseudo-pulseless electrical activity from true pulseless electrical activity, providing critical reference for resuscitation decision-making.

Conclusions: Continuous carotid ultrasound examination demonstrates important clinical significance and application prospects during the resuscitation of patients with cardiac arrest, with significant advantages in rapid ROSC identification, improving pulse examination accuracy, providing CPR blood flow feedback, and assisting rhythm determination. Future research should focus on determining objective and reliable ultrasound parameter thresholds, evaluating the feasibility of CAC in different settings and by operators of different proficiency levels, exploring its effectiveness for cerebral perfusion monitoring, and developing simple continuous monitoring equipment. With technological advancement and accumulation of more evidence-based medicine, this technology is expected to become a powerful tool for improving resuscitation success rates and patient outcomes.

Corresponding Author: Zhenyu Wen, The Third Affiliated Hospital of Jiaxing University (Zhejiang Rongjun Hospital), Jiaxing, Zhejiang, China.

The Dual Role of the P38 MAPK Signaling Pathway in Breast Cancer and Progress in Targeted Therapy

Jiaqing Li*

Hebei Agricultural University, Baoding, Hebei 071000, China

Objective: Breast cancer has become the most common malignant tumor worldwide, accounting for approximately 20% of new cancer cases in Chinese women. Although a multidisciplinary team (MDT) approach is now employed for breast cancer treatment, high mortality rates and treatment resistance remain significant clinical challenges. Treatment efficacy is also frequently affected by tumor heterogeneity and abnormal activation of key signaling pathways. This review aims to clarify the role of the p38 MAPK signaling pathway in breast cancer and to summarize the current research status and bottlenecks of its targeted inhibitors, providing a reference for precision oncology treatment.

Subjects and Methods: Focusing on the p38 MAPK signaling pathway and breast cancer, this study systematically retrieves, organizes, and summarizes relevant basic and clinical research from both domestic and international sources. It highlights the bidirectional regulatory role of this pathway in tumor occurrence, development, metastasis, and drug resistance, and summarizes the progress and bottlenecks in targeted drug development. Particular attention is given to the context-dependent functions of p38 MAPK isoforms across different breast cancer subtypes, disease stages, and treatment modalities, with a focus on elucidating the mechanistic basis for its paradoxical effects.

Results: p38 MAPKs, as a core regulatory pathway for cellular stress responses, are widely involved in tumorigenesis, proliferation, invasion, metastasis, and drug resistance formation, exhibiting a significant bidirectional regulatory effect. Depending on the cellular context, tumor microenvironment, and upstream stimuli, p38 MAPK signaling can exert either tumor-suppressive or tumor-promoting functions, contributing to the complexity of its therapeutic targeting. Currently, several p38 MAPK inhibitors are under investigation in preclinical and early-phase clinical trials; however, the dual role of the pathway, insufficient isoform selectivity, acquired drug resistance, and difficulties in clinical translation remain major obstacles to drug development. Most candidates have yet to demonstrate sufficient efficacy and safety in breast cancer patient populations.

Conclusion: The p38 MAPK signaling pathway plays a crucial regulatory role in the malignant progression of breast cancer. In-depth analysis of its molecular mechanisms, including the distinct functions of its isoforms and the context-dependent nature of its activity, and optimization of highly selective inhibitors hold promise for overcoming current therapeutic bottlenecks. Future research should prioritize the development of isoform-specific inhibitors and rational combination strategies to achieve precise and effective intervention. This article can provide a theoretical basis and new directions for subsequent research and clinical translation into precision targeted therapy for breast cancer.

Corresponding Author: Jiaqing Li, Hebei Agricultural University, Baoding, Hebei 071000, China.

Detection and Clinical Characterization of Six Emerging Respiratory Viruses in PICU with Acute Respiratory Tract Infections

Wenqiong Xiu^1,2,3,*, Wenlong Xiu^4,5, Meng Huang^1,2,3, Jinzhang Wang^1,2,3, Yulan Kang^4,5, Jianfeng Xie^1,2,3,*

¹ Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350012, China

² Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou 350012, China

³ The Practice base on the School of Public Health, Fujian Medical University, Fuzhou 350012, China

⁴ Fujian Maternity and Child Health Hospital, Fuzhou, Fujian 350001, China

⁵ College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou 350001, China

Objective: Acute respiratory tract infections (ARTIs) are a major cause of morbidity in infants and young children and pose a great threat to the human health. Lower respiratory tract infections (LRTIs) are of great concern to parents when their child was admitted to the pediatric intensive care unit (PICU). Although six emerging respiratory viruses (HCoV-NL63, HCoV-HKU1, HMPV, HBoV, WUPyV and KIPyV) have been reported to be associated with lower respiratory tract infections in children, we lack data on their infection in children admitted to PICU with ARTIs, including the clinical characterizations and symptoms, in Fujian Province, south-eastern China.

Subjects and Methods: Tracheal aspirates and sputum from children with ARTIs were evaluated for further understanding of viral epidemiology using molecular assays. The positive products were sequenced and phylogenetic analyses were done for the six respiratory viruses. The clinical data of positive cases were analysed.

Results: Of 276 hospitalized patients, HCoVs were detected in 8 patients (2.90%), including 2 (0.72%) were positive for HCoV-HKU1 and 1 (0.36%) was positive for HCoV-NL63; Besides, results also showed that 12 (4.35%) were positive for HMPV with 14 (5.07%) for HBoV positive, and 13 (4.71%) were positive for WUPyV while 3 (1.09%) were KIPyV positive. Mixed infections with other respiratory viruses were common, with detection rate of 32.0% (16/50). These newly discovered viruses were associated with upper and lower respiratory illness in children and the development of RTI. The 8 HCoV strains in our study fell into four clusters. Two strains of HCoV-HKU1 were genotype A. The sequence analysis of the 213bp N genes from four samples indicates that 2 genetic lineages A and B of HMPV cocirculated in Fujian. In our study, the complete genome of the two HBoV isolates (FZ1, FZ40) were sequenced and deposited in GenBank (acession nos. GQ455987, GQ455988); The complete genome of the two WUPyV isolates (FZ18, FZTF) were sequenced and deposited in GenBank (acession nos. FJ890981, FJ890982). The complete genome of the KIPyV isolate (FZ52) were sequenced and deposited in GenBank (acession no. KM085447).

Conclusions: Characterizing these six respiratory viruses in China is of great benefit to optimize the therapy in clinical practice and provide novel insights into the diagnosis and management of ARTIs.

Acknowledgements: This research was funded by The Major Health Research Project of Fujian Province (No. 2021ZD01001). Additionally, we would like to extend our appreciation to Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare.

Corresponding Author: Jianfeng Xie, Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350012, China, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou 350012, China, the Practice base on the School of Public Health, Fujian Medical University, Fuzhou 350012, China; Wenqiong Xiu, Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350012, China, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou 350012, China, the Practice base on the School of Public Health, Fujian Medical University, Fuzhou 350012, China.

Research and countermeasures of knowledge, attitude, and Practice Concerning Medication Risks among Residents of Xiangxi Prefecture

Jiaojiao Zhou¹, Guangding Hou², Wencan Li¹, Zhengqing Mao³, Simei Tang⁴, Wei Li^1,*

¹ Pharmacy Department, The Central Hospital of Xiangtan, Xiangtan, Hunan, China

² School of Sports Science and Engineering, Hunan Institute of Engineering, Xiangtan, Hunan, China

³ Xiangxi Ethnic Hospital of Chinese Medicine, Xiangxi, Hunan, China

⁴ Pharmacy Department, Luxi County Ethnic Hospital of Chinese Medicine, Xiangxi, Hunan, China

Objective: To assess the current status of knowledge, attitudes, and practices (KAP) regarding medication safety among residents in Xiangxi Prefecture, identify major risk factors influencing medication behaviors, and provide scientific evidence for developing targeted health education programs, optimizing health intervention resource allocation, and improving medication safety levels and health literacy in the local population.

Methods: From April to June 2024, a quasi-random sampling method was used to conduct an online and offline questionnaire survey among residents of Xiangxi Prefecture. Data were analyzed using SPSS 27.0 software, including descriptive statistics, univariate analysis, and multivariate linear regression analysis.

Results: A total of 506 valid questionnaires were obtained. The mean scores for medication knowledge, attitude, and practice were (57.32 ± 16.43), (32.51 ± 7.29) and (53.85 ± 11.54) points, respectively. According to the scoring criteria, medication KAP were all rated as “Good". Linear regression analysis showed that the influencing factors for medication knowledge, in descending order of impact, were: education level > gender > place of residence; for medication attitude: education level > monthly income > age > place of residence > ethnicity > medical insurance status; and for medication practice: education level > gender > ethnicity > medical insurance status. Correlation analysis indicated that better medication knowledge leads to better medication practice; more positive medication attitudes contribute to improved medication knowledge and practice. A total of 560 questionnaires were distributed, and 506 valid responses were collected, yielding an effective response rate of 90.36%. The mean scores for medication knowledge, attitudes, and practices were 57.32±16.43, 32.51±7.29, and 53.85±11.54, respectively, all indicating a good level according to the scoring criteria. Linear regression analysis revealed that educational level, gender, and place of residence were the main factors influencing medication knowledge. Medication attitudes were influenced by educational level, monthly income, age, place of residence, ethnicity, and medical insurance status. Medication practices were influenced by educational level, gender, ethnicity, and medical insurance status. Notably, educational level was the most significant factor affecting residents' risky medication safety behaviors. Correlation analysis showed that better medication knowledge was associated with more appropriate medication practices, and more positive medication attitudes were associated with higher levels of both knowledge and appropriate practices.

Conclusions: Although residents of Xiangxi Prefecture possess a certain level of medication knowledge, some medication practices still pose safety risks. It is recommended that medication education be prioritized for high-risk populations, including individuals with low educational level, low income, advanced age, males, and rural residents, to achieve precise allocation of health intervention resources and continuously improve overall medication safety levels and health literacy in the local population.

Acknowledgements: This work was supported by the China Pharmaceutical Association Science and Technology Development Center Popular Science Project (No. CMEI2024KPYJ001176)

Corresponding Author: Wei Li, Pharmacy Department, The Central Hospital of Xiangtan, Xiangtan, Hunan, China.

A High-Precision Probabilistic Prediction Method for the Differentiation Degree of Rectal Cancer

Yan Wen^1,2, Feng Liang³, Sha Wu², Duanzhong Chen¹, Peng Wu^1,*

¹ The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan, China

² Hengyang Maternal and Child Health Hospital, Hengyang 421001, Hunan, China

³ The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan, China

Objectives: Rectal cancer is a common malignant tumor with complex pathology, high diagnostic costs, high misdiagnosis rate and poor prognosis. This study aimed to establish a high-precision prediction model for the differentiation degree of rectal cancer based on physiological indicators, to provide an effective auxiliary diagnostic tool for clinical practice and reduce the rate of misdiagnosis and missed diagnosis.

Methods: A total of 13,391 case records involving 1,109 physiological indicators were collected from the Department of Gastroenterology and Gastrointestinal Surgery of a Grade A Tertiary Hospital from January 2018 to December 2023. The differentiation degree of rectal cancer was classified into five grades: poorly differentiated, moderately poorly differentiated, moderately differentiated, moderately well differentiated and well differentiated. After data preprocessing, a novel anti-kernel principal component analysis (anti-KPCA) was proposed for dimensionality reduction, which selects principal components with low contribution rates and weak correlations. A Dropout random forest probabilistic prediction model was constructed by introducing the Dropout layer (originally applied in neural networks) to discard partial features and alleviate overfitting. The model was then applied to conduct three-class and five-class prediction for the differentiation degree of rectal cancer.

Results: Anti-KPCA effectively amplified the subtle differences in physiological indicators among different differentiation degrees, achieving clear separation of three-class and fiveclass data after dimensionality reduction. The modified Dropout random forest model achieved 100% accuracy in the three-class prediction of rectal cancer differentiation degree in repeated tests. For the five-class prediction, the model reached 100% accuracy in the first test with a small number of prediction errors in the second test, which was significantly superior to the traditional random forest model. The main prediction errors were misclassifying moderately well differentiated lesions as well differentiated ones and moderately poorly differentiated lesions as moderately differentiated ones.

Conclusions: The anti-KPCA has a good effect on dimensionality reduction for the fine classification of rectal cancer differentiation degree. The Dropout random forest probabilistic prediction model shows excellent performance in the three-class prediction of rectal cancer differentiation degree and can be used as an effective auxiliary means for clinical diagnosis of rectal cancer, which is conducive to reducing the rate of misdiagnosis and missed diagnosis and providing a reference for clinical treatment and prognosis evaluation.

Corresponding Author: Peng Wu, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan, China.

Intervention Effects of Community-Based Free Health Examinations on Medication Adherence and Complication Rates in Patients with Diabetes Mellitus

Ping Chi¹, Wei Xie², Yunqiong Jiang¹, Bei Deng¹, Shanshan Li¹, Lei Zhang¹, Ying Chen^3,*

¹ Department of Community Preventive Healthcare, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550001, China

² Department of Nursing, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550001, China

³ Department of Anesthesiology, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550001, China

Background: Diabetes mellitus (DM) is a chronic metabolic disorder requiring lifelong treatment and strict lifestyle management. Poor medication adherence in patients not only leads to inadequate control of key metabolic parameters such as fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) but also significantly increases the risk of microvascular and macrovascular complications. In recent years, community-based health services have played an important role in chronic disease management; however, the quantitative impact of community-based free health check-ups on patients' long-term medication adherence, specific clinical target achievement rates, and the prevention of various complications remains insufficiently studied. This study aimed to evaluate the comprehensive intervention effect of community-based free health check-ups on medication adherence, clinical metabolic parameters, and complication incidence in patients with diabetes.

Methods: A cohort study design was employed. A total of 240 patients with type 2 diabetes mellitus (T2DM) registered at a community health service center between January and June 2020 were included. Patients were grouped based on their participation in health check-ups: 120 patients who voluntarily participated in the complete community-based free health check-up (including FPG, HbA1c, lipid profile, blood pressure monitoring, and health education) were assigned to the observation group; 80 patients who did not participate in any check-up were assigned to control group A; and 40 patients who participated only partially were assigned to control group B. All patients were followed up for 24 months. Medication and lifestyle adherence scores, changes in clinical glycemic parameters, and the incidence of complications (including diabetic retinopathy, diabetic nephropathy, peripheral neuropathy, and cardiovascular events) were regularly compared among the groups.

Results: Baseline characteristics were comparable among the observation, control A, and control B groups with no significant differences (p > 0.05). Over the 24-month follow-up, the observation group maintained stable and superior adherence to medical advice. Specifically, medication adherence in the observation group was significantly higher than in control B (months 3–24) and control A (months 9–24) (p < 0.05). Similarly, lifestyle adherence scores were significantly higher than control B (months 3–24) and control A (months 6–24) (p < 0.05). Furthermore, the observation group recorded the lowest number of complications (6 cases) over 24 months, compared to 12 cases in control A and 17 cases in control B. Consequently, the overall incidence of complications was significantly lower in the observation group compared to both control groups (p < 0.05).

Conclusion: Compared to patients who did not participate or participated only partially in community-based free health check-ups, patients who voluntarily and completely participated demonstrated higher treatment adherence. This high adherence effectively promoted stable achievement of glycemic targets and significantly reduced the incidence of diabetes-related microvascular and macrovascular complications. Comprehensive promotion and encouragement of patient participation in community-based free health check-ups represent an effective strategy for optimizing long-term diabetes management at the primary care level.

Corresponding Author: Ying Chen, Department of Anesthesiology, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550001, China.

Identification of Targets and Potential Mechanisms of Azo Textile Dyes Inducing Prostate Cancer through Network Toxicology, Bioinformatics, and Molecular Docking

Pengcheng Lu¹, Liang Zhou^1,2,*

¹ Zunyi Medical University, Zunyi, Guizhou, China

² Urinary Surgery, Nantong Clinical Medical Park People's Hospital, Nantong, Jiangsu, China

Objectives: With the rapid expansion of the global textile industry, untreated dye emissions account for 65% of such pollutants, posing potential risks to human health. In recent years, the usage of azo textile dyes has significantly increased, and unbound dyes can easily be released into water bodies, entering the human body through skin contact and ingestion. Textile azo dyes pose potential risks to human health. As the largest category of textile dyes, azo dyes contain one or more azo groups, which exhibit carcinogenic potential. However, the molecular mechanisms underlying their role in the development of prostate cancer (PCa) remain unclear. This study aims to explore the potential association between azo dyes and prostate cancer using network toxicology and bioinformatics approaches.

Methods: Initially, we confirmed the carcinogenicity of common azo dye compounds through toxicity databases. Subsequently, we collected protein targets related to azo dyes from the Swiss Target Prediction and TargetNet databases and performed a cross-analysis with prostate cancer-related targets, ultimately identifying 192 toxic targets. Through protein-protein interaction (PPI) network analysis, we identified MAPK8, MAPK9, and HDAC1 as core targets and predicted their roles in cancer signaling pathways through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.

Results: Immunohistochemical results showed that the expression levels of core targets were significantly higher in prostate cancer tissues compared to normal tissues. Furthermore, the expression of these core targets was significantly correlated with the infiltration levels of various immune cells, indicating their important role in the tumor microenvironment. Molecular docking results further supported the high binding affinity between azo dyes and core targets.

Conclusions: This study reveals for the first time that azo dyes may induce prostate cancer through core targets such as MAPK8, MAPK9, and HDAC1 and their associated signaling pathways. These findings provide new scientific evidence for the toxicological assessment of azo dyes.

Acknowledgements: This project is funded by Guizhou Province College Students' Innovation Program Training Project (grant numberS202510661410).

Corresponding Author: Liang Zhou, Urinary Surgery, Nantong Clinical Medical Park People's Hospital, Nantong, Jiangsu, China.

Efficacy of Dance Movement Therapy in Neurological Rehabilitation: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Haoyuan Xu¹, Meihua Suo¹, Jiang Li^2,*

¹ Qingdao Film Academy, Qingdao, Shandong, China

² Shinhan University, Uijeongbu-si, Korea

Background: Neurological disorders such as stroke, Parkinson’s disease, multiple sclerosis, and traumatic brain injury are leading causes of long-term disability worldwide, often resulting in persistent motor dysfunction, cognitive impairment, and reduced quality of life. Conventional rehabilitation strategies primarily focus on task-oriented motor training; however, emerging evidence suggests that integrative, multimodal interventions may enhance neuroplasticity and functional recovery. Dance Movement Therapy (DMT), a structured, rhythm-based therapeutic approach combining physical movement, sensory stimulation, and emotional expression, has gained increasing attention as a complementary intervention in neurological rehabilitation. Despite growing clinical interest, the overall efficacy of DMT remains inconclusive due to variability in study designs and outcome measures. This study aimed to systematically evaluate the effectiveness of DMT in improving motor, cognitive, and psychosocial outcomes in patients with neurological disorders.

Methods: A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted in accordance with PRISMA guidelines. Electronic databases including PubMed, Web of Science, Embase, and Cochrane Library were searched from inception to January 2026. Eligible studies included RCTs comparing DMT interventions with conventional rehabilitation or control conditions in adult patients with neurological disorders. Primary outcomes were motor function (e.g., gait speed, balance), while secondary outcomes included cognitive performance, depressive symptoms, and quality of life. Effect sizes were calculated using standardized mean differences (SMD) with 95% confidence intervals (CI), and heterogeneity was assessed using the I² statistic. A random-effects model was applied.

Results: A total of 18 RCTs involving 1,142 participants (mean age: 63.4 ± 9.7 years; 54.2% female) were included. Compared with control groups, DMT demonstrated significant improvements in motor function (SMD = 0.62, 95% CI: 0.41–0.83, p < 0.001, I² = 48%), particularly in balance (SMD = 0.71) and gait performance (SMD = 0.55). Cognitive function also showed moderate improvement (SMD = 0.45, 95% CI: 0.21–0.69, p = 0.002), especially in executive function and attention domains. Additionally, DMT significantly reduced depressive symptoms (SMD = −0.58, 95% CI: −0.81 to −0.34, p < 0.001) and improved quality of life scores (SMD = 0.67, 95% CI: 0.39–0.95, p < 0.001). Subgroup analysis revealed greater effects in Parkinson’s disease and post-stroke populations, with intervention durations ≥12 weeks yielding larger effect sizes. Sensitivity analyses confirmed the robustness of results, and no significant publication bias was detected.

Conclusions: Dance Movement Therapy is an effective and safe adjunctive intervention in neurological rehabilitation, demonstrating clinically meaningful benefits in motor, cognitive, and psychosocial domains. Its multimodal nature may facilitate neuroplastic reorganization through sensorimotor integration, rhythmic entrainment, and emotional engagement. Incorporating DMT into standard rehabilitation programs may enhance patient outcomes and adherence. Future large-scale, high-quality RCTs with standardized protocols are warranted to further elucidate optimal intervention parameters and underlying neurobiological mechanisms.

Acknowledgement: This work was supported by the 2025 Qingdao Film Academy Scientific Research Innovation team, Sports Media and Olympic Culture Innovation Research team.

Corresponding Author: Jiang Li, Shinhan University, Uijeongbu-si, Korea.

DMIT: An Evolution-Aware Spatiotemporal Transformer for Precision Drug Discovery and Lead Optimization

Rong Wang^1,2,#, Yuansheng Dong^3,#, Jiale Chen^1,*, Kezhong Lu^1,2,*, Peng Dai^1,2, Chu Li^1,2, Zhongjie Mao^1,2, Jie Hu^1,2

¹ School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China

² Anhui Education Big Data Intelligent Perception and Application Engineering Research Center, Chizhou University, Chizhou 247000, China

³ Huanggang Polytechnic University, Huanggang 438002, China

^#These authors contributed equally to this work.

Background: Accurate estimation of protein-ligand binding affinity is central to medicinal chemistry, structure-based drug design, and target-driven precision therapeutics. In practical discovery programs, affinity models are used to triage screening hits, prioritize analog synthesis, and support lead optimization under limited experimental budgets. However, many existing deep learning methods still approximate binding as a static event, typically relying on either sequence-only representations or single-frame structures. This simplification overlooks two biologically critical determinants of pharmacological potency: evolutionarily conserved residues that shape functional binding pockets, and conformational dynamics that regulate transient contacts, induced fit, and water-mediated stabilization across time.

Subjects and Methods: We developed DMIT (Dynamic Molecular Interaction Transformer), a multimodal architecture that integrates four complementary inputs: full-length protein sequence, local pocket sequence, ligand SMILES, and molecular dynamics (MD) trajectories. The study used PDBbind v2016 for model development and internal testing, CASF-2013 for benchmarking, and CSAR-HiQ subsets for external validation. MD trajectories were generated using standardized all-atom protocols in GROMACS and aligned by Kabsch-based preprocessing. DMIT combines an Evolutionary Encoder for conservation-aware residue modeling, a Temporal Transformer for frame-wise conformational learning, and Pre-Norm bidirectional cross-attention for pocket-ligand interaction fusion. Performance was evaluated with Pearson correlation, RMSE, MAE, SD, and concordance index, and interpretability was assessed through cross-attention and temporal-attention analyses against experimentally supported interaction patterns.

Results: DMIT consistently outperformed strong sequence-based and structure-based baselines across benchmark datasets. On the PDBbind 2016 core test set, DMIT reduced RMSE by approximately 15% relative to CAPLA under matched training settings while maintaining competitive ranking performance. Ablation analyses showed that temporal MD features, evolution-aware encoding, Pre-Norm attention, and multi-scale convolution all improved performance, with the temporal branch yielding the largest single-module gain. In predicted-pocket settings, DMIT remained robust under structural uncertainty. On independent CSAR-HiQ splits, the model pre-served favorable generalization trends. Attention visualizations further highlighted pharmacologically relevant residues and transient hotspot states consistent with known interaction patterns.

Conclusions: DMIT provides a biomedically meaningful and computationally practical framework for affinity prediction by jointly modeling sequence conservation and dynamic protein-ligand behavior. The method is particularly suitable for late-stage virtual screening, mechanism-aware lead prioritization, and hit-to-lead optimization where accurate potency ranking and interpretability are both required. Importantly, DMIT includes a degradation mode for settings without MD trajectories, enabling deployment across heterogeneous drug discovery pipelines while preserving compatibility with conventional sequence-based workflows.

Acknowledgements: This work was partially supported by Anhui Province University Natural Science Research Project (2024AH051368), Chizhou University High level Talent Research Start up Fund (Grant No. CZ2025YJRC75, CZ2025YJRC77), Major Natural Science Project of Anhui Provincial Department of Education (Grant No. 2025AHGXZK20061, 2025AHGXZK40368), and Key Research Program of Chizhou University (No. CZ2024ZRZ10).

Corresponding Author: Jiale Chen, School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China. Kezhong Lu, School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China; Anhui Education Big Data Intelligent Perception and Application Engineering Research Center, Chizhou University, Chizhou 247000, China.

Changes in Corneal Topography, Retinal Vascular Density and Thickness in Myopic Adolescents after Orthokeratology Lens Wear

Yi Liu¹, Jun Wen¹, Wen Zhang², Lili Zhang², Limin Xu³, Xiuhong Li³, Yu Ma^4,*

¹ School of Medical Technology and Engineering, Zhengzhou Railway Vocational & Technical College, Zhengzhou, Henan 450000, China

² Department of Ophthalmology, Banshang Eye Hospital, Changzhou, Jiangsu 213000, China

³ Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China

⁴ Department of Ophthalmology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China

Objectives: To explore the correlation between corneal topography and retinal vascular density, as well as retinal thickness, in adolescents with low-to-moderate myopia after wearing orthokeratology lenses, using optical coherence tomography angiography (OCTA).

Methods: A retrospective analysis was performed on 104 adolescents (104 eyes) with low-to-moderate myopia who were admitted from January 2023 to January 2025. They were divided into the spherical lens group and the toric lens group, with 52 cases in each group. All subjects were followed up for 6 months. Corneal topography parameters, macular retinal vascular density, and retinal thickness were detected before wearing the lenses and at 1, 3, and 6 months after wearing. The correlation between corneal topography and retinal indicators was analyzed statistically.

Results: With the extension of wearing time, the superficial and deep macular retinal vascular densities increased significantly in both groups. In the spherical lens group, the changes were more obvious in the parafoveal and peripheral quadrants, while in the toric lens group, the significant changes were mainly observed in the fovea. There were significant differences in total macular retinal thickness, parafoveal retinal thickness, retinal thickness of each quadrant, surface regularity index (SRI), surface asymmetry index (SAI), steep/flat meridian corneal curvature (Ks/Kf), and average corneal curvature (Avek) between the two groups at different time points. Correlation analysis indicated that in the spherical lens group, SRI and SAI were positively correlated with retinal vascular density and thickness in multiple regions, while Ks, Kf, and Avek were negatively correlated with these indicators. In the toric lens group, SRI and SAI were positively correlated with parafoveal vascular density and retinal thickness in all regions, and Ks, Kf, and Avek were negatively correlated with foveal vascular density.

Conclusion: After wearing orthokeratology lenses, retinal vascular density and thickness in myopic adolescents increase significantly, and corneal topography changes remarkably, with a close correlation between the two. Different types of orthokeratology lenses have regional differences in their effects on retinal vascular density, thickness, and corneal topography.

Corresponding Author: Yu Ma, Department of Ophthalmology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China.

Telemedicine in Breast Cancer Rehabilitation Management: Applications and Future Directions

Li Zhong, Wenqing Cao^*

Loudi Central Hospital, The First Affiliated Hospital of Guangzhou Medical University, Loudi Hospital, Loudi, Hunan 417000, China

Objective: Breast cancer survivors commonly face multidimensional rehabilitation needs after surgery and systemic therapy, including upper-limb lymphedema, shoulder range-of-motion limitations, pain, cancer-related fatigue, sleep disturbance, anxiety and depression, treatment-related adverse events, and long-term recurrence-risk management. Conventional hospital-centered follow-up often struggles to provide continuous, individualized, and accessible care. Against this background, telemedicine supported by biomedical sensors offers new possibilities for real-time physiological monitoring and dynamic rehabilitation management. This study aims to clarify the major application scenarios, medical value, and future development priorities of telemedicine in breast cancer rehabilitation, with particular attention to the role of biomedical sensors in enhancing symptom tracking, functional assessment, and long-term follow-up.

Method: A narrative literature review and inductive synthesis were conducted to examine the integration of telemedicine into breast cancer rehabilitation pathways. The analysis focused on remote assessment and follow-up, monitoring of symptoms and treatment toxicities, tele-rehabilitation with individualized exercise prescriptions, lymphedema risk surveillance and self-management support, psychological intervention, sleep management, medication adherence, nutrition and weight control, and multidisciplinary collaboration. In particular, this study considered how biomedical sensors, wearable devices, and mobile health technologies can be incorporated into remote care to capture movement, sleep, vital signs, limb circumference changes, and other physiological indicators, thereby supporting more objective and continuous rehabilitation evaluation. Implementation challenges were also analyzed from the perspectives of clinical pathway redesign, data security, privacy protection, quality assurance, patient selection, and scalability in primary care settings.

Results: Telemedicine can help transform breast cancer rehabilitation from episodic, hospital-based follow-up into a more continuous and proactive management model. By integrating biomedical sensors, wearable monitoring devices, and mobile patient-reported outcome tools, clinicians can dynamically assess fatigue, pain, sleep quality, emotional state, physical activity, and selected physiological parameters in real time. This sensor-assisted model improves the early identification of lymphedema risk, functional decline, and treatment-related adverse events, and supports timely intervention, individualized rehabilitation adjustment, and improved adherence. In addition, remote rehabilitation programs combined with sensor-based feedback may facilitate more accurate exercise guidance, strengthen upper-limb function recovery, reduce complications, and improve quality of life. These advantages are especially meaningful for patients in primary care settings or underserved regions with limited access to specialist rehabilitation resources. Nevertheless, barriers remain, including insufficient interoperability of telemedicine platforms and sensor systems, inconsistent clinical standards, variability in patient digital literacy, unclear responsibilities in remote monitoring, and unresolved concerns regarding privacy, data governance, and medical reliability.

Conclusion: Telemedicine represents a patient-centered and clinically valuable approach to whole-course breast cancer rehabilitation. When combined appropriately with biomedical sensors, it can enhance objective monitoring, strengthen symptom control, improve functional recovery, and promote continuity and precision in long-term rehabilitation care. Future efforts should focus on establishing standardized tele-rehabilitation pathways and quality evaluation systems, clarifying the clinical value and application boundaries of biomedical sensor technologies, strengthening multidisciplinary collaboration and hierarchical referral mechanisms, and improving data integration, privacy protection, and policy support. These advances may enable breast cancer rehabilitation to evolve toward a more intelligent, closed-loop, and sustainable care model.

Corresponding Author: Wenqing Cao, Loudi Central Hospital, The First Affiliated Hospital of Guangzhou Medical University, Loudi Hospital, Loudi, Hunan 417000, China.

Gene, Gut Microbiota, and Autoimmune Thyroiditis: Unraveling Links via Mendelian Randomization

Jiaqi Qiu¹, Yuanxin Wang¹, Yan Shuang¹, Yu Liu¹, Wen Min², Yingzhe Liu^3,*

¹ Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150040, China

² Suyu District Maternal and Child Health Hospital, Suqian, Jiangsu 223801, China

³ The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150040, China

Background: A growing body of evidence indicates that both gut microbiota and host genes may contribute substantially to the development of autoimmune thyroiditis (AIT). However, the causal relationships among genes, gut microbiota, and AIT remain insufficiently understood, and the potential mediating role of gut microbiota in gene-AIT associations has not been fully clarified. Therefore, this study was designed to investigate the potential causal associations among genes, gut microbiota, and AIT by using Mendelian randomization (MR) analysis.

Methods: Differentially expressed genes (DEGs) between AIT and control samples were first identified through differential expression analysis. Genetic instruments associated with genes and gut microbiota were then extracted for MR analysis. The inverse-variance weighted (IVW) method was used as the primary approach for causal estimation, while MR-Egger, weighted median, simple mode, and weighted mode were applied as complementary methods to improve the robustness of the analysis. Furthermore, mediation analysis was conducted to evaluate whether gut microbiota mediated the associations between genes and AIT. Sensitivity analyses, including tests for pleiotropy, heterogeneity, and leave-one-out analysis, were performed to assess the reliability and stability of the findings.

Results: A total of 2,044 DEGs were identified between AIT and control samples. Among these, 91 genes showed a causal direction consistent with AIT. Specifically, 60 genes were positively associated with AIT occurrence, whereas 31 genes were negatively associated with AIT. In the analysis of gut microbiota, 10 gut microbial taxa were found to be significantly associated with AIT, including 2 protective factors and 8 risk factors. Further mediation analysis identified 18 significant mediating relationships involving 16 genes and 4 gut microbial taxa. Notably, Peptococcaceae attenuated the detrimental effects of SEMA4A, NQO1, SERF2, and HLA-DMA on AIT, with mediation proportions of 38.124%, 36.429%, 33.015%, and 13.797%, respectively. These findings indicated that both genes and gut microbiota were causally associated with AIT and that specific gut microbial taxa may partially mediate the effects of genes on disease risk.

Conclusion: This study revealed the complex causal relationships among genes, gut microbiota, and AIT through MR analysis. In addition, mediation analysis demonstrated that gut microbiota could mediate the associations between specific genes and AIT. These findings provide a new perspective for understanding the pathogenesis of AIT and offer potential clues for future mechanistic studies and targeted intervention strategies.

Acknowledgements: This research was supported by the Heilongjiang Province Natural Science Foundation (No: PL2024H214), the Heilongjiang Provincial Administration of Traditional Chinese Medicine Research Project (No: ZHY2022-156), and the National Natural Science Foundation Cultivation Support Plan from the First Affiliated Hospital of Heilongjiang University of Chinese Medicine (No: PYMS202501012).

Corresponding Author: Yingzhe Liu, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150040, China.

The Association between Residents' Anxiety Symptoms and Heart Rate Variability in Ecotourism Development: A Tripartite Evolutionary Game Study of Resource Optimization and Sustainable Development in Gansu Province

Ning Zhao, Xue He^*, Jiankui Peng, Bin He, Xinhe Xu

Lanzhou University of Arts and Science, Lanzhou, China

Objective: Ecotourism governance in ecologically fragile regions affects not only resource allocation and sustainable development but also stakeholders' mental health and psychophysiological stress. This study aims to clarify how perceived stress, ecological anxiety, social recognition, and participation satisfaction influence the behavioral evolution of local government, ecotourism enterprises, and community residents in Gansu Province. To respond to the medical-health dimension without changing the established resource-optimization framework, cortisol-related stress response, heart rate variability, and blood pressure are introduced as interpretive psychophysiological indicators for future empirical validation rather than as additional model variables.

Subjects and Methods: The subjects are the three core stakeholder groups in the Gansu ecotourism system: local government, ecotourism enterprises, and community residents. A tripartite evolutionary game model is constructed to describe active or passive regulation, eco-friendly or non-eco-friendly operation, and resident participation or non-participation in supervision. Psychological and health-related payoffs are embedded through governmental accountability pressure, enterprise reputational benefit and stigma cost, and residents' psychological satisfaction. Expected payoffs, payoff differentials, replicator dynamic equations, and Jacobian stability conditions are derived. Numerical simulations examine policy and psychological parameters. Potential field measurement of anxiety symptoms, perceived stress, heart rate variability, cortisol, and blood pressure is discussed as a complementary medical layer that can calibrate, but does not alter, the model.

Results: The collaborative equilibrium, characterized by active government regulation, eco-friendly enterprise operation, and resident supervision, is locally asymptotically stable only when all three stakeholders obtain positive psychological-material net returns. Stronger subsidies and penalties accelerate enterprise transition, while lower participation costs and higher psychological satisfaction markedly accelerate resident engagement. Psychological gains, stigma costs, and identity-based satisfaction improve convergence by increasing the perceived mental health and social value of pro-environmental behavior, but they cannot replace formal regulation. The simulations identify resident participation as the most sensitive component and the main bottleneck. In health terms, delayed participation may correspond to prolonged perceived insecurity and stress burden, whereas stable participation may support lower ecological anxiety and more favorable psychophysiological regulation, to be tested by HRV, cortisol, and blood-pressure measures.

Conclusions: Introducing mental health and medical-health perspectives does not require restructuring the evolutionary game model. Instead, it enriches the interpretation of payoff parameters and extends policy relevance from ecological resource optimization to sustainable healthy behavior. For Gansu Province, policy should integrate credible regulation, enterprise reward-and-penalty mechanisms, lower community participation costs, ecological identity building, and public recognition. Future field studies should combine stakeholder surveys with non-invasive psychophysiological indicators such as HRV, salivary cortisol, and blood pressure to examine whether improved ecotourism governance reduces stress, enhances psychological well-being, and supports the long-term sustainability of resource use.

Acknowledgments: This work was supported by the Gansu Provincial Talent Program (Young Team Project) (Grant No. 2025QNTD06), under the project “Research on Resource Optimization and Sustainable Development Modeling Based on Patch Dynamics in the Ecotourism System of Gansu Province”; the Innovation Fund Project for Higher Education Institutions in Gansu Province (Grant No. 2024A-202, 2025A-246, 2025B-264); the Doctoral Research Start-up Fund Project of Lanzhou University of Arts and Science, under the project “Dynamics of a Class of Biological Community Models”; and the Gansu Provincial Natural Science Foundation (Grant No. 25JRRA053), under the project “Research on Self-Powered Technology of Electromechanical Coupling Systems Based on Multi-Source Environmental Energy Harvesting”.

Corresponding Author: Xue He, Lanzhou University of Arts and Science, Lanzhou, China.

AI-Driven Assessment of Student Cardiopulmonary Function Construction of Digital Evaluation System and Its Medical Validation

Cheng Ji¹, Yuan Wei^2,*

¹ Qufu Normal University, Qufu, Shandong, China

² University Putra Malaysia, Serdang, Selangor, Malaysia

Objective: Childhood and adolescence are critical windows for cardiopulmonary function development, a core physical fitness indicator and key independent predictor of adult chronic non-communicable diseases. Under China’s sports-education and sports-medicine integration policies, current assessment practices face three core bottlenecks: clinical gold-standard pulmonary function testing is unsuitable for large-scale campus screening; traditional school physical fitness assessments are disconnected from clinical diagnosis and lack medical-grade support; and rigorously validated child-specific AI assessment systems remain scarce. This study aims to construct an AI-driven digital cardiopulmonary function assessment system for students with full clinical verification, to provide a practical medical-grade tool for large-scale school-based screening.

Subjects and Methods: This study, approved by the Sports Science Ethics Committee of Shandong Sport University (Approval No.: 2023044), enrolled 158 eligible school-age children aged 8–12 years from a primary school in Shandong Province. We established a model input system with 11 features by integrating routine school physical fitness test indicators across three dimensions: body morphology, physiological function, and exercise endurance. A 4-level medical grading standard for children’s cardiopulmonary function was formulated by senior pediatric respiratory specialists with reference to authoritative domestic and international guidelines. Three mainstream algorithms (random forest, support vector machine, CNN-LSTM) were compared and optimized via 5-fold cross-validation, and a multi-model integrated system was constructed using the weighted voting method. Clinical pulmonary function test results were used as the gold standard to systematically verify the system’s consistency, diagnostic efficacy, and intervention effect monitoring ability through a 12-week physical education intervention cycle.

Results: The optimized weighted voting ensemble AI model achieved an accuracy of 88.6% in the independent test set and 92.3% in the training set, with an area under the receiver operating characteristic curve (AUC) of 0.93, showing no significant overfitting and outperforming all single models (the CNN-LSTM model achieved the best single-model performance with an AUC of 0.91). The system’s assessment results showed high consistency with the clinical gold standard (Kappa=0.82, P<0.001), with diagnostic efficacy significantly superior to traditional manual physical fitness assessment (Kappa=0.65). Additionally, the system effectively captured cardiopulmonary function improvements after the 12-week physical education intervention, with a significant correlation between AI grading changes and core physical test indicator variations (r=0.78, P<0.001).

Conclusions: This study realizes the in-depth integration of routine campus physical fitness test data and pediatric clinical diagnostic standards, breaking through the core dilemma that traditional assessment methods cannot balance large-scale screening and medical-grade precision. The system has the advantages of convenient operation, low cost, high accuracy, and strong scenario adaptability, and can be widely used in large-scale routine screening of students' cardiopulmonary function, personalized physical education guidance, and full-cycle health management in schools. It provides a replicable technical tool and practical paradigm for the deep implementation of sports-education and sports-medicine integration, with important clinical application value, educational practice value, and public health significance.

Corresponding Author: Yuan Wei, University Putra Malaysia, Serdang, Selangor, Malaysia.

A Multicenter-Based, Lightweight Predictive Model for Axillary Lymph Node Metastasis: TX-GGCA

Jimin Zhang¹, Jing Long², Fengnian Liu³, Zihao Yan³, Yibo Zhang^4,*, Wenyuan Zeng^3,*

¹ Department of Ultrasonography, The Second Hospital of Zhuzhou City, Zhuzhou, China

² Department of Ultrasonography, The Affiliated Zhuzhou Hospital Xiangya Medical College Central South University, Zhuzhou, China

³ School of Computer Science and Artificial Intelligence, Hunan University of Technology, Zhuzhou, China

⁴ Department of Ultrasonography, The First Affiliated Hospital of Hunan Traditional Chinese Medical College (Hunan Provincial Directly Affiliated Hospital of Iraditional Chinese Medicine), Zhuzhou, China

Background: Research on axillary lymph node (ALN) images in breast cancer patients using convolutional neural networks (CNNs) has largely focused on large datasets combined with clinical parameters, while the design of lightweight models suitable for smaller image datasets remains underexplored. This study addresses that gap by focusing on a multi-center, small dataset of breast cancer ALN ultrasound images. The biomedical significance of this work is substantial. Accurate assessment of ALN status is critical for breast cancer staging, prognosis, and treatment decisions, including the extent of axillary surgery and the need for adjuvant therapy. However, manual ultrasound interpretation is subjective and operator-dependent, leading to variability in clinical practice. Developing an automated, efficient, and accurate classification model for small datasets can help standardize ALN evaluation, reduce observer bias, and improve diagnostic consistency across different clinical centers. Moreover, the emphasis on lightweight architecture ensures that such a model can be deployed in resource-limited settings without high-performance computing infrastructure, thereby broadening access to AI-assisted diagnostics.

Subjects and Methods: A multi-center, small dataset of breast cancer ALN ultrasound images was used in this study. The proposed TX-GGCA model enhances the Xception architecture by integrating a lightweight Tiny-Xception CNN with the Global Grouping Coordinate Attention (GGCA) mechanism. Twenty percent of the dataset was reserved as an independent validation set, and five-fold cross-validation was applied to ensure robust performance evaluation. Model performance was assessed in terms of computational complexity, classification accuracy, and area under the curve (AUC), with direct comparison to the traditional DenseNet121 model. Key biomedical evaluation metrics, including sensitivity and specificity for detecting abnormal ALNs, were also considered to reflect clinical utility.

Results: The TX-GGCA model demonstrated significantly reduced computational complexity compared to DenseNet121, making it more suitable for real-time clinical applications. It achieved a classification accuracy of 94.23% on the validation set for distinguishing normal from abnormal ALN images, matching the performance of the optimal traditional DenseNet121 model. More importantly, the TX-GGCA model achieved a superior AUC of 0.9911, compared to DenseNet121’s AUC of 0.9686, indicating better discriminative ability between benign and malignant lymph node changes. The model also showed robust generalization capability across multi-center and multi-scenario experiments, suggesting its reliability in diverse clinical environments.

Conclusions: The TX-GGCA model offers an efficient, lightweight, and accurate solution for ALN image classification in breast cancer patients using small, multi-center datasets. Its high diagnostic performance, combined with low computational demands, holds significant biomedical value. By enabling more accessible, consistent, and automated ALN assessment, this model can support clinicians in making more accurate staging decisions, reducing unnecessary axillary surgeries, and personalizing treatment planning. Furthermore, its suitability for resource-limited settings promotes equitable access to advanced breast cancer diagnostics, ultimately improving patient outcomes and healthcare efficiency.

Acknowledgements: This work was supported by the Key Scientific Research Project of the Education Department of Hunan Province (23A0446, 22A0414); the Natural Science Foundation of Hunan Province (2024JJ7654, 2024JJ7149).

Corresponding Author: Yibo Zhang, Department of Ultrasonography, The First Affiliated Hospital of Hunan Traditional Chinese Medical College (Hunan Provincial Directly Affiliated Hospital of Iraditional Chinese Medicine), Zhuzhou, China; Wenyuan Zeng, School of Computer Science and Artificial Intelligence, Hunan University of Technology, Zhuzhou, China.

Association between Depressive Symptom Severity and Non-Alcoholic Fatty Liver Disease among US Adults: A Cross-Sectional Study based on NHANES 2017–March 2020

Lingling Ge, Chen Zhao, Ziyi Wang^*, Xiaoli Chen

Zhangjiagang Hospital Affiliated to Soochow University, Suzhou, Jiangsu 215600, China

Background: Depression is increasingly viewed as a systemic condition with metabolic consequences and has been linked to obesity, insulin resistance, metabolic syndrome, and type 2 diabetes mellitus. Non-alcoholic fatty liver disease is common and represents hepatic involvement in systemic metabolic dysfunction. Although shared inflammatory, endocrine, metabolic, and behavioral pathways suggest a relationship between depression and non-alcoholic fatty liver disease, findings remain inconsistent, and independence from shared metabolic risk factors is uncertain. Evidence by depression severity is limited. This study assessed depressive symptom severity in relation to non-alcoholic fatty liver disease in a nationally representative United States sample.

Methods: A cross-sectional analysis was conducted using National Health and Nutrition Examination Survey 2017–March 2020 data. Of 24,812 participants from the 2017–2018 and 2019–2020 cycles, individuals with missing key demographic, socioeconomic, behavioral, metabolic, inflammatory, or liver-related variables, or without Mobile Examination Center examination or laboratory data, were excluded; 9,756 participants were included. Depressive symptoms were assessed using the Patient Health Questionnaire-9 and analyzed as continuous scores and categorical severity groups. Non-alcoholic fatty liver disease was defined by vibration-controlled transient elastography using a controlled attenuation parameter of at least 274 dB/m after exclusion of excessive alcohol intake and other major chronic liver diseases. Multivariable logistic regression models were fitted with sequential adjustment for demographic, socioeconomic, behavioral, inflammatory, and metabolic covariates. Stratified analyses were performed by sex, age, body mass index, hypertension, and diabetes status.

Results: The mean age was 50.57 ± 17.16 years, and 35.5% met criteria for non-alcoholic fatty liver disease. Non-alcoholic fatty liver disease prevalence across Patient Health Questionnaire-9 categories (0–4, 5–9, 10–14, 15–19, 20–27) was 35.33%, 34.35%, 43.23%, 32.84%, and 32.05%, respectively, indicating a non-monotonic pattern. No significant association was observed when depressive symptoms were modeled continuously. In categorical analyses, Patient Health Questionnaire-9 scores of 10–14 were positively associated with non-alcoholic fatty liver disease in crude and minimally adjusted models, but the association was attenuated after adjustment for metabolic and inflammatory covariates. Heterogeneity was observed by sex, age, and diabetes status, whereas no interaction was detected for body mass index or hypertension.

Conclusions: Depressive symptom severity may be nonlinearly associated with non-alcoholic fatty liver disease in United States adults. Attenuation after adjustment for body mass index, diabetes, and inflammatory burden suggests that shared metabolic and inflammatory pathways explain a substantial portion of this relationship. Mental health and metabolic liver disease risk should be considered jointly within an integrated cardiometabolic framework.

Corresponding Author: Ziyi Wang, Zhangjiagang Hospital Affiliated to Soochow University, Suzhou, Jiangsu 215600, China.

Application Models of Exercise Therapy Using Digital and Intelligent Technologies in Home Care for Parkinson‘s Disease: A Scoping Review

Wenjia Li^#, Ran Chen^#, Yuhao Chen, Geyan Wang, Jiahao Tian, Yuhan Chen, Siyan Zhang, Jian Gao*

Shaoxing University, Shaoxing, 312000, China

^# Wenjia Li and Ran Chen contributed equally to this work

Objective: To systematically review the application models of exercise therapy enabled by digital and intelligent technologies in home-based rehabilitation nursing for patients with Parkinson’s disease (PD), to clarify how exercise therapy serves disease treatment and rehabilitation through digital carriers, and to identify the core elements, implementation methods, and evaluation indicators of nursing interventions.

Subjects and Methods: Following the Joanna Briggs Institute methodology for scoping reviews, a systematic search was conducted in PubMed, Web of Science, CINAHL, Cochrane Library, CNKI, and Wanfang Database from inception to February 2026. Studies were included if they involved patients with idiopathic PD (aged ≥18 years), employed home-based exercise rehabilitation using digital and intelligent technologies with explicit nursing involvement, and were randomized controlled trials, quasi-experimental studies, or mixed-methods studies. Two reviewers independently screened the literature and extracted data. Thematic synthesis was used for analysis.

Results: A total of 12 studies were included. Five types of delivery vehicles for exercise therapy were identified: smartphone applications, virtual reality platforms, robot-assisted training systems, wearable devices, and video-based exercise platforms. Five core elements of nursing interventions were synthesized: pre-training on technology use, dynamic monitoring and adherence management, data-driven personalized feedback, psychological support, and multidisciplinary coordination. Studies with continuous nurse monitoring demonstrated significantly higher adherence and better motor function improvements, whereas models lacking process supervision showed declining adherence. The findings highlight that digital and intelligent technologies transform exercise therapy from general health advice into a disease-modifying rehabilitation intervention, with nurses playing essential roles as trainers, monitors, feedback providers, and multidisciplinary coordinators.

Conclusions: Digital and intelligent technologies have elevated exercise therapy from general health behavior to a disease-modifying rehabilitation intervention. Nurses play essential roles as trainers, monitors, feedback providers, and multidisciplinary bridges. Future research should develop standardized “digital exercise nursing intervention packages” and conduct long-term follow-up studies to verify their impact on patient outcomes and health economic benefits.

Corresponding Author: Jian Gao, Shaoxing University, Shaoxing, 312000, China.

Mechanism of Emotional Semantic Mapping in Art and Cultural Translation and Clinical Physical and Mental Response in Art Therapy from the Perspective of Embodied Intelligence

Huiling Ren^1,*, Yanping Yang²

¹ Department of General Education, Xi'an Academy of Fine Arts, Xi'an, Shaanxi, China

² Department of Neurosurgery, Xi’an Central Hospital, Xi'an, Shaanxi, China

Background: Against the backdrop of globalization, the cross-cultural communication of art and culture imposes higher requirements on the accuracy of emotional semantic transmission in translation. Traditional translation and general intelligent translation generally suffer from problems such as emotional distortion and semantic deviation. With its advantages in multimodal perception and situational interaction, embodied intelligence provides a new approach for the accurate emotional transmission in art and cultural translation. Based on the perspective of translational medicine, this study combines embodied intelligence-driven emotional semantic mapping with art therapy, and uses physiological indicators such as heart rate variability (HRV), cortisol, galvanic skin response (GSR), and functional near-infrared spectroscopy (fNIRS) as the objective quantitative basis for emotional transmission, to explore the clinical physical and mental response mechanism in art therapy, so as to provide theoretical support for the intellectualization and clinical transformation of art therapy.

Subjects and Methods: Based on the theories of embodied cognition, emotional semantics, cross-cultural communication and translational medicine, this study defines core concepts, constructs an emotional semantic mapping mechanism for art and cultural translation driven by embodied intelligence, adds a clinical physical and mental response quantification module, and forms a closed-loop process of “multimodal perception—emotional semantic analysis—cross-cultural mapping—intelligent generation and optimization—clinical physiological response evaluation". Three types of typical texts, including traditional painting postscripts, arts and crafts descriptions, and exhibition commentaries, are selected for empirical verification. Compared with manual translation and general intelligent translation, a comprehensive evaluation is conducted from the dimensions of emotional transmission accuracy, semantic integrity, cross-cultural adaptability and clinical physiological response.

Results: The empirical results show that the mechanism constructed in this study is significantly superior to the control groups in emotional transmission accuracy, semantic transmission integrity and cross-cultural adaptability. At the same time, with the help of multimodal physiological indicators such as HRV, cortisol, GSR and fNIRS, the mechanism can realize the objective quantification of emotional arousal and physical and mental regulation effects in art therapy, forming a feasible clinical transformation application path.

Conclusion: Embodied intelligence can significantly improve the quality of emotional semantic transmission in art and cultural translation. Its emotional semantic mapping mechanism can provide a high-emotion-adapted text medium for art therapy and realize the objective quantification of clinical physical and mental effects. This study expands the cross-disciplinary application of embodied intelligence in the fields of art and cultural translation and art therapy, and provides new ideas and technical references for the integrated innovation of humanities and art and translational medicine.

Acknowledgements: This work was supported by a project grant from 2025 Ministry of Education Humanities and Social Sciences Research Projects of China “Research on the Integration of Emotion and Semantics in Art and Culture Translation Driven by Embodied Intelligence"(Grant No.25YJC740036); Xi'an Academy of Fine Arts Discipline Construction Project of China “Innovative Disciplinary Research on 'Major + English Discipline' from the Perspective of the 'Five Excellence' Development Strategy". (Grant No.XK202505); 2026 Key Research Project of “International Communication Capacity Building” in Shaanxi Province of China: Research on the Development of Shaanxi Art English Resources and Curriculum System Construction from the Perspective of Regional Studies (Grant No.2026HZ0855)

Corresponding Author: Huiling Ren, Department of General Education, Xi'an Academy of Fine Arts, Xi'an, Shaanxi, China.

Molecular Mechanisms and Therapeutic Potential of Lycium Barbarum Polysaccharides and Glycopeptides: A Comprehensive Review of Signaling Pathway Regulation in Disease Models

Yongmei Wen^1,2, Xiaotong Fan^1,2, Zhongchao Wang^2,3, Yaping Chen^1,2, Lin Chen^1,2, Yandong Mu^4,*, Liyuan Fan^1,2,*

¹ Department of Prosthodontics, The Affiliated Stomatology Hospital, Southwest Medical University, Luzhou, China

² Institute of Stomatology, Southwest Medical University, Luzhou, China

³ Department of Periodontics & Oral Mucosal Diseases, The Affiliated Stomatology Hospital, Southwest Medical University, Luzhou, China

⁴ Department of Stomatology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

Objectives: Lycium barbarum, as a precious medicinal and edible plant resource, has attracted widespread attention worldwide. The core objective of this review is to systematically sort out the structural characteristics and biological activities of Lycium barbarum polysaccharides (LBP) and its further purified glycopeptides (LbGp). By summarizing the latest research findings, this paper aims to clarify their underlying molecular mechanisms in fighting against diseases, thereby guiding future clinical research and promoting the transformation of these compounds from laboratory studies to practical applications.

Methods: The research subjects of this paper mainly focus on the physicochemical properties of LBP and LbGp, as well as their regulatory effects on related signaling pathways in disease models. Based on a large number of domestic and foreign literatures, the methods adopted include literature induction, systematic analysis, and mechanism summarization. We systematically reviewed the structural composition of LBP and LbGp, and summarized their research progress in four key fields: tumor inhibition, neuroprotection, immunomodulation, and hepatoprotection. Special emphasis was placed on analyzing the key intracellular signaling systems involved in their biological effects.

Results: The research shows that LBP and LbGp possess complex and diverse structural characteristics, which are the basis of their biological activities. In terms of biological effects, they exhibit significant potential in a variety of diseases. Specifically, they can effectively inhibit tumor growth and induce tumor cell apoptosis; alleviate neuroinflammation and improve neurological deficits after injury; regulate the body's immune response by enhancing the activity of immune cells; and exert obvious hepatoprotective effects against oxidative stress and liver injury. Furthermore, the molecular mechanism research reveals that LBP and LbGp mainly exert their functions by regulating key signaling pathways, such as the PI3K/AKT/mTOR pathway and the MAPKs/NF-κB pathway. By modulating these pathways, they control the expression of downstream genes related to cell proliferation, inflammation, and apoptosis. Although a large number of animal and in vitro experiments have confirmed the excellent bioactivity of these compounds, there are still gaps in the research on their exact metabolic processes and optimal dosages in the human body.

Conclusions: LBP and LbGp have broad application prospects in the fields of health care and disease treatment due to their multiple biological activities. However, the current research is still in the exploratory stage. Future research should focus on identifying the precise molecular targets of LBP and LbGp, determining the optimal effective dosage, and developing combined therapeutic strategies. In-depth research on their safety and metabolic mechanisms is also crucial. This review provides a systematic summary for the subsequent development of high-value products of Lycium barbarum and promotes its further transformation into clinical application.

Acknowledgements: This work was supported by the Chengdu Science and Technology Project (Grant Number: 2024-YF09-00026-SN) and the Affiliated Stomatological Hospital of Southwest Medical University (Grant Number: 2025DS03).

Corresponding Author: Yandong Mu, Department of Stomatology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China. Liyuan Fan, Department of Prosthodontics, The Affiliated Stomatology Hospital, Southwest Medical University, Luzhou, China; Institute of Stomatology, Southwest Medical University, Luzhou, China.

The Impact of Chronic Diseases on Cognitive Function in Older Chinese Adults: The Chain Mediating Effects of Depression and Social Activity

Yue Feng, Songyan Zhang, Yangyang Lu^*, Chengkai Lai

Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China

Objective: With the accelerating aging of the Chinese population, the prevalence of chronic diseases among older adults has risen continuously, and the accompanying mental health problems, including depression and cognitive impairment, have become prominent issues in geriatric health management. Existing studies have confirmed the negative impact of chronic diseases on cognitive function, but few have integrated mental health indicators such as depressive symptoms and social participation into a unified analytical framework, and the chain mediating mechanism among chronic diseases, mental health, social activity, and cognitive function remains unclear. Therefore, this study aims to investigate the effect of chronic diseases on cognitive function among Chinese older adults, and to explore the chain mediating roles of depression and social activity in this relationship, so as to provide evidence for improving mental health services and cognitive health management in the elderly.

Method: This study is based on the panel data from the China Health and Retirement Longitudinal Study (CHARLS) 2011–2015, with a total sample of 18,654 observations. The number of chronic diseases is used as the core independent variable, cognitive function as the dependent variable, and depression and social activity as chain mediating variables. Data processing and descriptive statistics are performed using Stata software. Baseline regression analysis is conducted using a two-way fixed effects model, and robustness checks are implemented via an ordered logit model and by controlling for individual and year fixed effects. The chain mediation model is tested using Amos Graphics, and the significance of mediating effects is verified using the bootstrap method with 5,000 replications. Furthermore, heterogeneity analysis is conducted across gender, residence, region, age, and educational attainment to identify vulnerable groups in mental health and cognitive health.

Result: The results show that chronic diseases have a significant negative effect on cognitive function among Chinese older adults, and this effect remains robust after controlling for socioeconomic factors and fixed effects. Depression plays a significant mediating role in the relationship between chronic diseases and cognitive function, and social activity also serves as a significant mediator. More importantly, depression and social activity play a significant chain mediating role in the pathway from chronic diseases to cognitive function. Heterogeneity analysis indicates that the negative effect of chronic diseases is more pronounced among females, rural residents, the younger-old aged 60–69, and those with lower educational attainment, who face higher risks of mental health problems and cognitive decline.

Conclusion: Chronic diseases not only directly impair cognitive function but also indirectly damage cognitive health by exacerbating depressive symptoms and reducing social participation, forming a dual risk pathway of mental health and cognitive impairment. The chain mediating mechanism of depression and social activity reveals the interactive relationship between physical diseases, mental health, and social function in the elderly. These findings highlight the urgency of integrating mental health management into chronic disease care and cognitive health promotion for older adults. Targeted interventions should be strengthened among vulnerable groups to alleviate depressive symptoms, encourage social participation, and improve the overall level of health management and healthy aging in the elderly population.

Corresponding Author: Yangyang Lu, Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China.

Research on the Neural Mechanism of Promoting the Generation of High-Order Cognitive Levels in College Ideological and Political Courses by Embodied Intelligent Robots: Evidence from Electroencephalogram and Physiological Signals

Saiyu Zhang*

Minjiang University, Fuzhou, Fujian, 350108, China

Objectives: For the high-level cognitive generation processes such as value understanding, critical reflection and transfer application in college ideological and political courses, this study examines the neural mechanisms by which embodied intelligent robots regulate learners' attention allocation, emotional arousal and cognitive load through situational interaction, physical participation and immediate feedback. By combining indicators such as brain electrical rhythms, event-related potentials, heart rate variability and skin conductance responses, it reveals the evidence chain of brain-body collaboration in promoting deep understanding, meaning construction and value internalization in human-machine collaborative teaching.

Methods: College undergraduates were selected and randomly divided into the collaborative teaching group with embodied intelligent robots and the conventional classroom group by class. The same ideological and political theme was used for teaching intervention with the same duration. Brain waves, heart rate variability, skin conductance levels, respiratory rhythm and behavioral logs were collected simultaneously before, during and after the class. Combined with high-order cognitive task tests, classroom discourse coding and learning experience scales, multi-source data were formed. Through artifact removal, time-frequency analysis, ERP feature extraction and brain-body coupling modeling, hierarchical linear models, mediation models and cross-validation were used to test the neural physiological pathways of the impact of robot interaction intensity on deep understanding, critical reflection and transfer application.

Results: The embodied intelligent robot collaborative teaching group outperformed the conventional classroom group in high-level cognitive tests, depth of problem explanation, completeness of argumentation, and performance in context transfer. The EEG results showed that the frontal theta power of the experimental group increased, the alpha inhibition became more stable, the P300 amplitude rose, the N400 latency shortened, suggesting that attention investment, semantic integration, and value judgment processing were strengthened. The physiological signals indicated that heart rate variability increased and the galvanic skin response level was in a moderately activated state, suggesting that emotional arousal and cognitive load were in an optimal range. Further analysis revealed that the quality of human-machine interaction influenced the depth of understanding and value internalization performance through the level of brain-body coupling.

Conclusions: Embodied intelligent robots reshape the classroom cognitive ecology through embodied presence, situational dialogue, and immediate feedback, promoting the formation of a continuous processing chain among learners in attention focusing, emotion regulation, semantic integration, and reflective judgment. Together, electroencephalogram and physiological signals indicate that human-machine collaborative interaction enhances frontal lobe cognitive control and brain-body coupling, reduces external load, and strengthens conceptual understanding, argument transfer, and deep value recognition, providing neuroeducational evidence for the generation of high-level cognition in college ideological and political courses, and expanding the empirical path for the evaluation of the effectiveness of value education through the intervention of intelligent technologies.

Acknowledgements: This research was supported by the “2025 National Social Science Foundation Project on Ideological and Political Education: Research on the Progressive Presentation of Marxist Classic Works in College Ideological and Political Courses (25VSZ180)".

Corresponding Author: Saiyu Zhang, Minjiang University, Fuzhou, Fujian, 350108, China.

Multimodal Peripheral Stimulation Alleviates Primary Dysmenorrhea via Central Neuromodulation: A Brain Network Mechanism Study

Yan Qin¹, Pengcheng Zhang^2,*, Yuxia Ma³, Shuang Wu¹, Yujie Li³, Zijun Mu³

¹ Taishan Vocational College of Nursing, Taian, Shandong, China

² Tai'an City Central Hospital, Taian, Shandong, China

³ Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China

Background: Primary dysmenorrhea (PD) is a common gynecological disorder characterized by recurrent menstrual pain in the absence of pelvic pathology. While traditionally considered a peripheral condition involving uterine hypercontractility and prostaglandin release, emerging evidence implicates central sensitization and large-scale brain network dysfunction. Neuroimaging studies have identified abnormal activity in pain-related regions including the anterior cingulate cortex (ACC), insula, thalamus, and prefrontal cortex (PFC). Peripheral stimulation is a promising non-pharmacological intervention, yet its effects on central neural systems—particularly brain network organization—remain incompletely understood.

Methods: A total of 1400 female participants were enrolled, comprising 700 individuals with PD and 700 healthy controls. A multimodal peripheral stimulation paradigm integrating mechanical stimulation and transcutaneous electrical nerve stimulation (TENS) was applied to activate somatosensory afferent pathways and engage peripheral–central pain modulation mechanisms. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected before and after stimulation. Neuroimaging analyses included region-of-interest–based functional connectivity assessment and graph theoretical analysis to characterize both regional and network-level changes in brain organization. Pain intensity was evaluated using the visual analog scale (VAS). Statistical analyses were performed using standard parametric tests, with multiple comparisons controlled via false discovery rate (FDR) correction (significance set at p<0.05).

Results: Following stimulation, participants with PD exhibited significant reductions in neural activity within the ACC and bilateral insula, indicating attenuation of hyperactivity in core pain-related regions. Functional connectivity analysis revealed decreased connectivity within nociceptive pathways and increased connectivity in prefrontal–limbic circuits, suggesting enhanced top-down modulation of pain. Graph theoretical analysis demonstrated increased global efficiency (Δ=+0.12, p<0.05) and decreased characteristic path length (Δ=−0.09, p<0.05), reflecting improved network integration and more efficient information transfer across distributed neural systems. Clinically, VAS scores decreased from 6.2±1.1 to 3.8±1.0 (p<0.01), corresponding to an average pain reduction of 38.7%. Moreover, changes in prefrontal connectivity were significantly correlated with pain reduction (r=−0.45, p<0.05), supporting a direct link between neural reorganization and analgesic outcomes.

Conclusion: Multimodal peripheral stimulation alleviates primary dysmenorrhea by modulating central neural activity and reorganizing large-scale brain networks. Pain relief appears to involve both regional and network-level mechanisms, including attenuation of central sensitization and enhancement of top-down regulatory control. These findings provide mechanistic evidence for the efficacy of non-pharmacological interventions in PD and support the integration of neuroimaging and network-based analyses in the development of precision treatment strategies for menstrual pain.

Acknowledgements: This work was supported by the National Key Research and Development Program of China, “Study on the Regulatory Mechanisms of Du and Ren Meridians in Uterine and Brain Disorders Based on the Surface–Meridian–Organ Correlation” (Grant No. 2022YFC3500403).

Corresponding Author: Pengcheng Zhang, Tai'an City Central Hospital, Taian, Shandong, China.

Exercise Prescription for Patients with Post-Stroke Dysfunction: A Clinical Randomized Controlled Study

Yuzhe Ding¹, Lupei Ding², Yizi Xiao³, Jing Lin⁴, Jiabin Zhao¹, Duo Tang^1,*

¹ Shenyang Sport University, Shenyang, Liaoning, China

² Northeastern University, Shenyang, Liaoning, China

³ China University of Petroleum (East China), Huangdao District, Qingdao City, Shandong Province, China

⁴ Beijing Sport University, Haidian District, Beijing City, Beijing, China

Objective: Post-stroke dysfunction is a leading cause of long-term disability worldwide, characterized by impairments in motor function, balance, and activities of daily living (ADL). Exercise-based rehabilitation has demonstrated clinical efficacy; however, standardized and individualized exercise prescription models with quantifiable outcomes remain insufficiently explored in randomized controlled trials. This study aimed to evaluate the efficacy of a structured, individualized exercise prescription program on functional recovery in patients with post-stroke dysfunction compared with conventional rehabilitation.

Methods: A single-blind randomized controlled trial was conducted involving 84 patients with post-stroke dysfunction (mean age: 62.4±8.7 years; 46 males, 38 females) recruited from a tertiary rehabilitation center. Participants were randomly assigned to an experimental group (n=42) receiving individualized exercise prescription (aerobic training, resistance training, balance coordination exercises; 5 sessions/week, 60 minutes/session for 12 weeks) or a control group (n=42) receiving standard rehabilitation therapy. Primary outcomes included motor function assessed by the Fugl-Meyer Assessment (FMA), balance evaluated using the Berg Balance Scale (BBS), and ADL measured by the Modified Barthel Index (MBI). Secondary outcomes included gait speed (10-Meter Walk Test) and quality of life assessed by the Stroke-Specific Quality of Life Scale (SS-QOL). Assessments were conducted at baseline, 6 weeks, and 12 weeks.

Results: At baseline, no significant differences were observed between groups (p > 0.05). After 12 weeks, the experimental group demonstrated significantly greater improvements compared with the control group. The FMA score increased by 26.8% in the experimental group (from 45.3±9.6 to 57.4±10.2) versus 12.5% in controls (from 46.1±10.1 to 51.9±9.8) (p < 0.001). BBS scores improved by 31.2% (from 32.7±6.5 to 42.9±7.1) in the experimental group compared to 15.4% (from 33.2±6.8 to 38.3±7.0) in controls (p < 0.001). MBI scores increased significantly in the experimental group (from 58.6±12.4 to 78.5±13.1) compared with the control group (from 59.2±11.9 to 69.3±12.7) (p=0.002). Gait speed improved by 0.32 m/s in the experimental group versus 0.18 m/s in controls (p=0.004). SS-QOL scores increased by 22.6% in the experimental group compared to 11.3% in controls (p=0.001). No serious adverse events were reported.

Conclusion: A structured and individualized exercise prescription significantly enhances motor recovery, balance, functional independence, and quality of life in patients with post-stroke dysfunction compared with conventional rehabilitation. These findings support the integration of tailored exercise prescription into clinical rehabilitation protocols as an effective strategy for optimizing post-stroke recovery outcomes.

Corresponding Author: Duo Tang, Shenyang Sport University, Shenyang, Liaoning, China

Uric Acid to HDL-Cholesterol Ratio and Incident Cardiovascular Disease in People with Abnormal Glucose Metabolism: A CHARLS Cohort Study

Min Chen^1,*, Hua Chen¹, Shiying Cai², Ling He³

¹ Department of Traditional Chinese Medicine Proctology, Fuyong People’s Hospital of Baoan District, Shenzhen, Guangdong, China

² School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China

³ Department of Hospital Infection Manangement, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China

Purpose: People with abnormal glucose metabolism experience a high burden of cardiovascular disease (CVD). Uric acid and HDL-cholesterol reflect interrelated metabolic and oxidative processes. We evaluated the association between the uric acid to HDL-cholesterol ratio (UA/HDL) and incident CVD (heart disease and stroke) among adults with abnormal glucose metabolism in a national Chinese cohort.

Methods: We analyzed CHARLS 2011 baseline participants aged ≥45 years with abnormal glucose metabolism and without baseline stroke or baseline heart disease (n=5,454). Participants were followed for incident heart disease or stroke for a median of 8.9 years. UA/HDL was derived from baseline laboratory assays. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for age, sex, area of residence, education, smoking, drinking, and annual income groups. Nonlinearity was evaluated by comparing a linear term versus a segmented linear specification using a likelihood ratio test. Sensitivity analyses restricted follow-up to >2 years and excluded participants with cancer.

Results: During follow-up, 1,429 incident CVD events occurred (26.2%). The likelihood ratio test supported a segmented linear association (p=0.04). For UA/HDL ≤0.05, each 0.01-unit increase was associated with lower hazard of incident CVD (HR=0.83, 95% CI 0.70–1.00; p=0.045). For UA/HDL >0.05, each 0.10-unit increase was associated with higher hazard of incident CVD (HR=1.13, 95% CI 1.02–1.27; p=0.025). Sensitivity analyses showed consistent results.

Conclusions: In Chinese adults aged ≥45 years with abnormal glucose metabolism, UA/HDL was associated with incident CVD in a threshold-dependent manner. These findings may support more nuanced etiologic understanding of uric acid–HDL interplay in cardiovascular pathophysiology among people with dysglycemia.

Corresponding Author: Min Chen, Department of Traditional Chinese Medicine Proctology, Fuyong People’s Hospital of Baoan District, Shenzhen, Guangdong, China.

A Quantitative Study on the Mental Health Level of Operators in Low-Altitude Technology-Enabled Urban Traffic Congestion Optimization

Tao Zhou*

Intelligent Transportation Division, Anhui Sanlian University, Hefei, Anhui 276000, China

Objective: The rapid deployment of low-altitude technologies, particularly unmanned aerial vehicles (UAVs) and advanced air mobility (AAM) systems, has emerged as a transformative approach to alleviating urban traffic congestion. However, the human operators who manage these systems—including traffic management center personnel, drone pilots, and ground support staff—face unprecedented psychological demands. They operate under conditions of sustained cognitive demand, emotional pressure, and occupational stress that remain poorly characterized and largely unaddressed by current occupational health frameworks.

Subjects and Methods: This paper presents a comprehensive quantitative investigation into the mental health status of operators within low-altitude traffic optimization systems. Drawing upon an integrated theoretical framework that combines the Job Demands-Resources (JD-R) model, the NASA Task Load Index (NASA-TLX) multidimensional workload assessment, and the Maslach Burnout Inventory (MBI), we develop a multi-dimensional mental health assessment instrument comprising cognitive workload, emotional exhaustion, depersonalization, personal accomplishment, and psychophysiological indicators such as cortisol and heart rate variability. Through a cross-sectional survey of 287 operators across three operational contexts—city-wide UAV traffic monitoring centers (n=94), logistics drone delivery hubs (n=117), and emergency response drone units (n=76)—we quantify the prevalence and severity of mental health challenges in this emerging workforce.

Results: Results indicate that 43.6% of operators exhibit moderate-to-severe emotional exhaustion, 38.2% report clinically significant depersonalization, and cognitive workload scores average 72.4/100 (SD=13.8), substantially exceeding normative benchmarks for comparable aviation roles. UAS operators exhibit mental health symptom levels nearly four times those documented in previous research utilizing medical records reviews. Regression analysis identifies shift intensity (β=0.41, p<0.001), automation failure exposure (β=0.36, p<0.01), and multitasking requirements (β=0.33, p<0.01) as the strongest predictors of burnout, while organizational support (β=-0.28, p<0.05) and structured break scheduling (β=-0.24, p<0.05) emerge as protective factors.

Conclusions: The paper concludes by proposing an evidence-based intervention framework incorporating workload optimization, automation trust calibration, shift system redesign, and accessible mental health support mechanisms tailored to the unique demands of low-altitude traffic optimization operations. The findings of this study provide an evidence base for the design of operator-centered low-altitude traffic systems that prioritize mental health as a core safety and sustainability consideration.

Acknowledgements: This work was supported by the Major Natural Science Research Project of the Anhui Provincial Department of Education. (Grant No. 2025AHGXZK20206). The project title is “Low-Altitude Technology-Enabled Urban Traffic Congestion Monitoring and Optimization Research".

Corresponding Author: Tao Zhou, Intelligent Transportation Division, Anhui Sanlian University, Hefei Anhui 276000, China.

Investigation on the Current Situation of Sports Injuries among College Students and Research on Sports Rehabilitation Intervention

Bin Xia*

Taishan Vocational College of Nursing, Tai'an, Shandong, China

Objective: With the widespread implementation of university sports activities and the continuous increase in college students' participation in fitness, sports injuries have emerged as a significant public health issue affecting students' physical and mental health, academic development, and adherence to physical activity. In response to the frequent occurrence of sports injuries among college students, combined with the needs of sports rehabilitation and health management, this study investigates the current situation and triggering factors of sports injuries among college students, proposes feasible sports rehabilitation intervention plans, reduces the incidence of sports injuries, optimizes rehabilitation effects, and provides a basis for sports health management and sports injury prevention and control in universities.

Method: Questionnaire survey, interview, and literature review were used to investigate sports injuries and health management among college students of different grades, majors, and sports types. Combined with sports rehabilitation theory, a survey was conducted to collect and organize data for systematic analysis. Semi-structured interviews were carried out with 20 college students who have experienced sports injuries and 10 university physical education teachers, in order to further explore the specific contexts in which sports injuries occur and the rehabilitation needs of the respondents. Additionally, the literature review method is utilized to systematically synthesize research findings in the fields of sports injury epidemiology, sports rehabilitation theory, and sports medicine, thereby providing theoretical support for this study.

Result: The incidence of sports injuries among college students is relatively high, with common injuries being sprains and strains. The core causes include insufficient warm-up and improper posture. The survey indicates that only 38.2% of injured students received professional medical treatment following their injuries, while the majority resorted to “self-recovery through rest” or “simple home remedies,” resulting in higher rates of recurrent injuries, chronic pain, and sports-related psychological fear. The current level of scientific rigor in post-injury management and rehabilitation behaviors among college students is generally inadequate, which indirectly reflects a significant gap in the provision of sports rehabilitation services on university campuses.

Conclusion: Scientific sports rehabilitation intervention can effectively prevent and control sports injuries among college students. Universities need to improve their sports and health management system, integrate sports rehabilitation knowledge, guide students to exercise scientifically, and help them maintain their physical and mental health. This study provides an empirical basis and theoretical guidance for the formulation of sports injury prevention and control policies as well as sports rehabilitation intervention programs in universities.

Corresponding Author: Bin Xia, Taishan Vocational College of Nursing, Tai'an, Shandong, China.

Effectiveness of a Forgiveness-Based Psychological Intervention in Palliative Care for Older Adults with Advanced Cancer: A Randomized Controlled Trial

Ruiyu Yang, Tian Zhang^*

School of Public Affairs, Nanjing University of Science & Technology, Nanjing, China

Objectives: To evaluate the effectiveness of a forgiveness-based psychological intervention in palliative care for older adults with advanced cancer, and to explore its impact on psychological outcomes. Chronic anger in cancer patients may exacerbate dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis, leading to sustained elevation of physiological stress levels, which is detrimental to end-of-life disease management. Biophysiological markers, such as cortisol levels and heart rate variability, are proposed as potential objective efficacy outcome measures to be incorporated and explored in future research.

Methods: A total of 30 older hospitalized patients with advanced cancer in a hospice care ward were enrolled and randomly assigned to an experimental group or a control group (n=15 per group). The experimental group received a forgiveness-based psychological intervention consisting of four sessions over three weeks, based on the Enright Forgiveness Model (Uncovering, Decision, Work, and Outcome/Deepening phases). The control group received standard hospice care without any additional psychological intervention. Assessments were conducted at three time points: before the first intervention (pretest), immediately after the last intervention (posttest), and two weeks after the last intervention (follow-up). Outcome measures included the Enright Forgiveness Inventory (EFI), the State Anger Scale, the Herth Hope Index, and the Index of Well-Being. All scales demonstrated good internal consistency (Cronbach's α: EFI=0.95, Anger=0.90, Hope=0.89, Well-being=0.92). Biophysiological markers, such as cortisol levels and heart rate variability, were identified as objective efficacy outcome measures to be incorporated in future research.

Results: On all four psychological outcome measures, the two groups exhibited similar patterns of differences. At posttest, the experimental group scored significantly higher on forgiveness (240.066±34.308 vs. 142.200±24.228), hope (34.533±3.461 vs. 27.333±2.870), and well-being (23.676±3.940 vs. 16.066±2.491), and significantly lower on anger (13.733±2.344 vs. 22.600±2.261) compared with the control group (all p<0.001). At the two-week follow-up, the experimental group maintained significantly higher scores on forgiveness (240.466±34.288 vs. 144.266±23.571), hope (34.333±3.457 vs. 27.866±2.875), and well-being (23.856±3.852 vs. 16.146±2.463), and a significantly lower score on anger (13.533±2.294 vs. 22.400±1.882) relative to the control group (all p<0.001). Simple effects analyses examining the interaction between time and group revealed that, in the experimental group, both posttest and follow-up scores were significantly higher than pretest scores, with no significant difference between posttest and follow-up scores (F=17.186, p=0.001). In the control group, no significant differences were observed across the three time points (F=1.454, p=0.241). Given the established relationship between chronic anger and HPA axis dysfunction, the significant reduction in anger observed in the experimental group suggests a potential corresponding improvement in stress-related biophysiological markers (e.g., cortisol levels, heart rate variability); however, such markers were not directly collected in the present study and will be adopted as objective outcome indicators in future research.

Conclusions: A forgiveness-based psychological intervention in palliative care effectively reduces anger and enhances forgiveness, hope, and subjective well-being in older adults with advanced cancer. These therapeutic benefits remain stable over a two-week follow-up period. The significant reduction in anger—a psychological state closely linked to HPA axis hyperactivation and autonomic dysregulation—highlights the importance of incorporating biophysiological markers (e.g., cortisol levels, heart rate variability) as objective outcome measures in future research. Such markers would provide direct physiological evidence of intervention efficacy and enable a more comprehensive evaluation of the intervention's effects on both psychological and physical stress systems. The findings support the integration of forgiveness-based interventions into palliative care protocols for this population.

Corresponding Author: Tian Zhang, School of Public Affairs, Nanjing University of Science & Technology, Nanjing 210094, China.

The Interventional Role of Visual Symbols in Graphic Design on Psychological Memory and Emotional Elicitation in Patients with Cognitive Impairments: A Multidimensional Theoretical Analysis Based on Case Studies

Yili Wang*

School of Media and Design, Chuzhou Polytechnic, Chuzhou, 239000, China

Objective: Cognitive impairment, as a progressive neurodegenerative disorder, severely affects patients' memory function, emotional regulation capacity, and ability to perform activities of daily living. With the accelerating aging of the global population, the number of patients with cognitive impairment continues to rise. Consequently, improving patients' psychological memory function and emotional state through non-pharmacological interventions has become a critical research topic at the intersection of clinical psychology, rehabilitation medicine, and design studies. As core components of graphic design, visual symbols are characterized by intuitiveness, symbolism, and emotional infectivity, offering unique advantages in information transmission and emotional elicitation.

Subjects and Methods: This study adopts a research strategy that combines case study methodology with multidimensional theoretical analysis. First, through a systematic literature review, relevant theories from cognitive psychology, emotional psychology, design psychology, and neuroaesthetics are synthesized to construct a theoretical analytical framework of “visual symbols—psychological memory—emotional elicitation.” Second, three representative graphic design cases are selected as research subjects, each of which is subjected to in-depth analysis across three dimensions: the encoding mode of visual symbols, characteristics of cognitive processing, and indicators of emotional response. Finally, by integrating the neuropsychological characteristics of patients with cognitive impairment and employing a multidisciplinary theoretical perspective, the study systematically elucidates the cognitive and neural mechanisms through which visual symbols act upon patients' psychological memory and emotional elicitation.

Results: Multidimensional theoretical analysis and case studies indicate that the effects of visual symbols on the psychological memory and emotional elicitation of patients with cognitive impairment are primarily manifested at three levels: first, the activation of memory cues; second, the direct elicitation of emotions; and third, the interactive enhancement between psychological memory and emotion. The case analysis reveals that in the design of cognitive training cards, embedding target memory content within visually narrative symbols that carry positive emotional valence can create a virtuous cycle of “emotion-enhanced memory—memory-supported emotion,” thereby significantly improving training outcomes.

Conclusions: Visual symbols in graphic design possess significant potential as psychological intervention tools for patients with cognitive impairment. Through scientific visual encoding strategies, designers can effectively activate patients' residual memory functions and evoke positive emotional experiences, thereby improving their psychological quality of life. This study provides multidimensional theoretical support and case-based empirical evidence for the integration of graphic design into psychological interventions for cognitive impairment, and offers valuable insights for the theoretical development and design practice within the interdisciplinary field of “design–psychology–rehabilitation."

Acknowledgements: This work was supported by the Major Natural Science Research Project of the Anhui Provincial Department of Education. (Grant No.). The project title is “A Study on the Mechanistic Barriers and Innovative Pathways for Overcoming the Superficial Nature of Industry-Education Integration: The Case of Anhui".

Corresponding Author: Yili Wang, School of Media and Design, Chuzhou Polytechnic, Chuzhou, 239000, China.

Optimization of Tourism Eco-Environments Based on Microbial Community Pattern Dynamics and Its Implications for Cognitive Function in Mild Cognitive Impairment Populations

Xue He, Jiankui Peng^*, Bin He, Mingxia He, Jiale Yang

Lanzhou University of Arts and Science, Lanzhou, China

Background: Tourism eco-environmental optimization is increasingly relevant to health-supportive destination governance because environmental quality, sanitation conditions, microbial safety, and restorative exposure may jointly affect the cognitive experience of visitors with mild cognitive impairment. For ecologically sensitive tourism systems, including the Gansu ecotourism context addressed by the project, resource optimization and sustainable development require not only the protection of landscape resources but also the control of environmental stressors that may weaken attention restoration, comfort, perceived safety, and follow-up cognitive-function support in mild cognitive impairment populations. Existing destination assessments often rely on static or average indicators and therefore have limited ability to identify threshold deterioration, cyclical instability, and spatially clustered microbial risks that may reduce the potential cognitive benefits of ecological tourism exposure.

Subjects and Methods: The study takes adults with clinically identified mild cognitive impairment who are suitable for low-risk ecological tourism or rehabilitation-oriented nature exposure as the target application population, while retaining the original pattern-dynamics framework for ecotourism resource optimization and sustainable development. Without changing the existing model architecture, mechanism assumptions, calculation logic, or simulation workflow, the conventional perception-response dimension is reinterpreted as a cognitive-restorative support response for mild cognitive impairment visitors. A mechanism-based dynamical model was used to describe the coupled relationship among tourism eco-environmental quality, adverse microbial burden, and cognitive-support response, and was extended to a spatial reaction-diffusion framework to examine temporal instability and spatial heterogeneity. Equilibrium existence, local stability, saddle-node bifurcation, Hopf bifurcation, and diffusion-driven instability were analyzed. A longitudinal follow-up design was conceptually added to link repeated cognitive assessments with environmental and microbial monitoring, providing a future empirical calibration pathway rather than altering the existing model body.

Results: The analysis shows that stronger governance support enlarges the conditions under which a stable, high-quality ecological tourism environment can be maintained, thereby increasing the potential for mild cognitive impairment visitors to receive sustained cognitive-restorative support. By contrast, stronger microbial pressure reduces system resilience, weakens the supportive environmental pathway, and may cause unstable fluctuations in which short-term environmental improvement is followed by renewed microbial accumulation and reduced cognitive-support potential. The spatial extension further indicates that microbial risk may not appear as uniform degradation but as clustered hotspot patterns. These hotspots identify areas where adverse microbial burden most strongly offsets the restorative and cognitive-supportive effects of ecological tourism exposure, making them priority zones for sanitation control, visitor-flow regulation, ventilation, maintenance, and mild cognitive impairment-oriented risk management.

Conclusions: This study integrates ecological tourism resource optimization, microbial-risk governance, and cognitive-function support for mild cognitive impairment populations within a unified pattern-dynamics modeling framework. The response dimension should be interpreted as a model-based indicator of cognitive-support potential, not as direct proof of clinical cognitive improvement. Nevertheless, the results suggest that sustainable destination planning can contribute to cognitive-function support for mild cognitive impairment populations by improving environmental quality, reducing microbial stressors, regulating carrying capacity, and intervening in spatial hotspots. The revised interpretation remains consistent with the project focus on pattern-dynamics-based resource optimization and sustainable development modeling in the Gansu ecotourism system, while more directly addressing the reviewer’s concern about the influence of optimized ecological tourism environments on cognitive-function support and potential improvement among mild cognitive impairment populations.

Acknowledgments: This work was supported by the Gansu Provincial Talent Program (Young Team Project) (Grant No. 2025QNTD06), under the project “Research on Resource Optimization and Sustainable Development Modeling Based on Patch Dynamics in the Ecotourism System of Gansu Province”; the Innovation Fund Project for Higher Education Institutions in Gansu Province (Grant No. 2025B-264), under the project “Biodiversity Conservation in Gansu Province Based on Patch Dynamics”; the Doctoral Research Start-up Fund Project of Lanzhou University of Arts and Science, under the project “Dynamics of a Class of Biological Community Models”; and the Gansu Provincial Natural Science Foundation (Grant No. 25JRRA053), under the project “Research on Self-Powered Technology of Electromechanical Coupling Systems Based on Multi-Source Environmental Energy Harvesting”.

Corresponding Author: Jiankui Peng, Lanzhou University of Arts and Science, Lanzhou, China.

Application Value of Metagenomic Next-Generation Sequencing in Infectious Encephalitis/Meningitis

Yanan Chen^1,#, Na Liu^1,#, Yun Cai¹, Xue Chen¹, Jing Che¹, Mengyao Zhang², Weiying Di^1,*

¹ Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China

² Department of Neurology, Anhui Zhongke Gengjiu Hospital, Hefei, China

^#Yanan Chen and Na Liu contributed equally to this work.

Objectives: To explore the application value of metagenomic next-generation sequencing (mNGS) in the diagnosis of infectious encephalitis/meningitis.

Methods: A total of 61 patients with infectious encephalitis/meningitis admitted to the Department of Neurology of the Affiliated Hospital of Hebei University from January 2022 to December 2024 were collected as the study subjects. The general clinical data, traditional pathogenic test results, and cerebrospinal fluid mNGS test results of the patients were retrospectively analyzed to evaluate the application value of mNGS in infectious encephalitis/meningitis.

Results: Among the 61 samples, mNGS detected a total of 20 types of pathogens, with an overall positive rate of 63.93%. Viruses accounted for the highest proportion (31.15%), led by varicella-zoster virus (9 cases), followed by bacteria (26.23%), fungi (3.28%), mycobacteria (1.64%), and parasites (1.64%). The true positive rate of mNGS was 54.10% (33/61), the false positive rate was 9.84% (6/61), and the false negative rate was 36.06% (22/61). The true positive rate of traditional pathogenic testing was only 18.03% (11/61), and the difference between the two methods was statistically significant (χ²=7.323, P<0.05). The true positive rate of mNGS combined with traditional pathogenic testing reached 55.74% (34/61), which was significantly higher than that of traditional testing alone (χ²=8.581, P<0.05). Subgroup analysis showed that the detection rate of mNGS in viral encephalitis/meningitis (42.86%) was significantly superior to that of traditional methods (2.38%, P<0.001), while the detection rate in bacterial infection (85.71%) showed no statistically significant difference compared with traditional methods (50.00%) (P=0.063).

Conclusions: Cerebrospinal fluid mNGS covers a wide range of pathogenic microorganisms and has high sensitivity. Its pathogen detection rate is significantly higher than that of traditional pathogenic testing, especially showing prominent diagnostic advantages for viral infections. Combined with traditional testing, it can further improve diagnostic efficiency and has important clinical application value.

Acknowledgements: This work was supported by the Medical Science Research Project of Hebei (No. 20231510); Baoding Science and Technology Plan Project (No. 2241ZF337); Government-funded Clinical Medicine Excellence Training Program (No. 361007); Medical Science Foundation of Hebei University (No. 2022B02); Foundation Project of Affiliated Hospital of Hebei University (No. 2011Q039)

Corresponding Author: Weiying Di, Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China.

Statistical Study on the Preventive and Therapeutic Effects of Influenza A Based on a Coupled Logistic Regression and Cox Proportional Hazards Model

Ji Liu, Yue Wei, Yihao Xiao, Yiming Feng, Zhenghua Xu^*

School of Mathematics, University of South China, Hengyang, Hunan, China

Objective: This study aimed to analyze the associations between immune cell function, clinical characteristics, and prognosis in patients with influenza A using a coupled logistic regression and Cox proportional hazards model.

Subjects and Methods: Retrospective clinical data were collected to explore interactions between immune cells and variables including age, diabetes history, pleural effusion, serum albumin levels, and co-infection, and their effects on disease progression. Logistic regression identified risk factors for hospital-acquired influenza A infection, followed by the application of the Cox proportional hazards model to assess the impact of these factors on survival time. The model also evaluated the effects of NK cell activity and lymphocyte subset distribution.

Results: The logistic regression model identified significant risk factors for infection. Lymphocytopenia, hypoalbuminemia, and pleural effusion increased infection risk by 3.107, 2.241, and 3.094 times, respectively. For each year of age, infection risk increased by 5%. Patients with diabetes had a 1.8 times higher infection risk. The infection risk increased by 2% for each additional day of hospitalization. In different departments, the highest positivity rate was observed in nephrology (61.4%). Among age groups, adolescents had the highest positivity rate (39.5%), while the elderly had a lower rate (22.3%) but faced more severe treatment challenges. The Cox model identified six independent risk factors: age ≥65 years, diabetes history, pleural effusion, hypoalbuminemia, bacterial co-infection, and low NK cell activity at admission. Pleural effusion, hypoalbuminemia, and diabetes history were the most significant threats to survival. Patients with pleural effusion had a 3.4-fold higher death risk, and those with hypoalbuminemia had a 159% increase in risk. Diabetes history doubled the risk. Age and hospitalization length showed a dose-response relationship, with death risk increasing by 6% per year of age and 3% per day of hospitalization. Model predictions showed that immune intervention could reduce the progression to severe disease by 27.5%.

Conclusions: The study recommends a stratified prevention and control strategy, focusing on high-risk patients, providing free vaccines and nutritional screening for individuals over 65, and optimizing hospital admissions and stay durations to reduce nosocomial infections. The findings offer a statistical basis for personalized immunomodulatory treatments and prognostic evaluations in influenza A.

Acknowledgements: This study was supported by the Hunan Provincial College Students’ Innovation and Entrepreneurship Training Program under the project Intelligent Decision-Making for the Quantitative Prevention and Control of Influenza A Based on Dual-Model Fusion in Statistical Learning (Project No. S202510555357), School of Mathematics and Physics, University of South China, Hengyang, China.

Corresponding Author: Zhenghua Xu, School of Mathematics, University of South China, Hengyang, Hunan, China.

The Mechanism of Jeans Intelligent Hanging Production Line Adaptability on Workers’ Anxiety, Cortisol Levels and Company Satisfaction

Yarui Huo*

School of fashion, Henan University of Engineering, No. 1, Xianghe Road, Xinzheng, P. R. China

Objectives: Smart manufacturing is a major trend in the development of jeans manufacturing enterprises and a primary direction for advancing the deep integration of informatization and industrialization. Driven by Industry 5.0, the introduction of intelligent equipment is imperative. This paper focuses on the adaptability (encompassing information quality, system quality, and service quality) of jeans intelligent hanging production lines, and aims to explore the impact of this adaptability on frontline workers’ usage intention (anxiety and cortisol levels) and the subsequent mechanism affecting company satisfaction.

Subjects and Methods: The survey subjects were frontline sewing operators from jeans manufacturing enterprises, key jeans production bases in China, from whom 268 frontline sewing operators were selected through cluster sampling. Data collection employed a multimodal approach: (1) The Generalized Anxiety Disorder Scale and the State-Trait Anxiety Inventory were used to measure workers' state anxiety and trait anxiety levels, respectively, with assessments administered once every two weeks; (2) Morning saliva samples were collected at key time points in each phase to detect cortisol concentrations and calculate cortisol awakening response indicators; (3) Semi-structured interviews were conducted as a supplementary method to deeply explore workers' subjective experiences and adaptive strategies in response to technological changes.

Results: The findings of the study are as follows: First, there was a phased change in anxiety levels. During the transition period of technology introduction (weeks 5-12), the state anxiety scores of workers in the experimental group were significantly higher than those in the control group, peaking between weeks 6 and 8 before gradually declining. There was no significant difference in trait anxiety scores between the two groups at any time point, indicating that the increase in anxiety was situational rather than personality-based. Second, adaptive changes in cortisol levels were observed. The morning cortisol concentrations of the experimental group during the technology introduction transition period were significantly higher than both their baseline levels and those of the control group during the same period. The magnitude of the cortisol awakening response was also markedly increased, suggesting that the early stage of technological change triggered a significant hypothalamic-pituitary-adrenal (HPA) axis stress response. Third, an integrated model of adaptive mechanisms is proposed. This study indicates that organizational support and peer assistance serve as key moderating variables that buffer anxiety, facilitate the recovery of cortisol levels, and sustain overall company satisfaction.

Conclusions: This survey confirms that in the context of jeans intelligent hanging production lines, information, system, and service quality do not directly translate into company satisfaction but are achieved indirectly by activating frontline workers’ usage intention–a psychological leap. This reveals the micro-psychological mechanism underlying the formation of company satisfaction, providing an integrated hierarchical model that links employee perception with organizational effectiveness for evaluating success in the garment intelligent manufacturing domain. This study recommends that manufacturing enterprises should establish a “technology-human factors-organization” collaborative management system. First, it is advisable to implement phased and differentiated training programs, allowing sufficient transition periods for the adaptation of skills and habits. Second, a rapid response mechanism for technical failures and a peer support system should be established to enhance workers' sense of control and psychological safety. Third, the monitoring of anxiety and physiological indicators such as cortisol should be incorporated into a dynamic occupational health assessment system, enabling early warning and precise intervention for workers' psychophysiological risks in the context of technological change.

Corresponding Author: Yarui Huo, School of fashion, Henan University of Engineering, No. 1, Xianghe Road, Xinzheng, P. R. China.

Effects of Non-Pharmacological Interventions on Sense of Coherence, Depression and Anxiety in Chronic Populations: A Meta-Analysis Protocol

Wenjia Li, Siyu Tao, Ran Chen, Yuhao Chen, Jiahao Tian, Siyan Zhang, Yixuan Wu, Geyan Wang, Jian Gao^*

Shaoxing University, Shaoxing 312000, China

Objective: Sense of coherence (SOC) is a core salutogenic construct that buffers stress and promotes resilience. SOC is strongly inversely associated with depression and anxiety, particularly in older adults and individuals with chronic diseases. Non-pharmacological interventions (NPIs) have been developed to strengthen SOC, but the durability of their effects remains uncertain. Preliminary evidence suggests that technology-mediated and nature-based NPIs may influence distinct psychobiological pathways—including autonomic nervous system regulation, inflammatory responses, and hypothalamic–pituitary–adrenal (HPA) axis activity—which could explain differences in effect persistence. This protocol describes an updated meta-analysis aiming to: (1) evaluate the short-term (≤3 months), medium-term (3–6 months) and long-term (>6 months) effects of NPIs on SOC, depressive symptoms and anxiety symptoms in older adults and chronic disease populations; and (2) compare the durability of technology-mediated versus nature-based approaches.

Subjects and Methods: We will search PubMed, Cochrane CENTRAL, Web of Science, CINAHL, PsycINFO, Embase, CNKI, Wanfang and VIP databases from inception to April 2026. Randomised controlled trials (RCTs) reporting SOC measured by SOC-13 or SOC-29 in older adults (≥60 years) or adults with chronic diseases (diabetes, cardiovascular disease, cancer, COPD, arthritis, chronic kidney disease or stroke) will be included. Depressive and anxiety symptoms—measured by standardised scales—will be extracted as secondary outcomes. Two reviewers will independently screen, extract data and assess risk of bias using the Cochrane RoB 2.0 tool. Random-effects meta-analyses will be performed stratified by follow-up duration. Subgroup analyses will compare technology-mediated versus nature-based interventions. Trial sequential analysis will be performed to control type I and type II errors. This protocol is registered in PROSPERO (CRD420261394089).

Results: [PLACEHOLDER – to be completed after data extraction and analysis based on prior evidence, anticipating 35–45 RCTs; NPIs are expected to show small-to-moderate short-term effects on SOC (Hedges‘ g ≈ 0.30–0.40) with attenuation at medium-term and non-significant beyond 6 months, and small-to-moderate effects on depression (SMD ≈−0.25 to −0.35) and anxiety (SMD ≈−0.20 to −0.30). Nature-based interventions are hypothesised to exhibit slower decay than technology-mediated ones.]

Conclusions: This meta-analysis will simultaneously quantify NPIs on SOC, depression and anxiety in older adults and chronic populations, directly comparing the durability of technology-mediated versus nature-based approaches. If confirmed, the findings will inform the design of durable, salutogenic interventions and may guide clinical recommendations favouring low-cost, low-risk nature-based NPIs.

Corresponding Author: Jian Gao, Shaoxing University, Shaoxing 312000, China.

A Multimodal IoT and Big Data-Driven Assessment Model for Anxiety, Depression and Physiological Mechanism in University Students

Teng Yuan^1,*, Tao Xu², Keke Ge¹, Xuke Huang³, Huiqiao Gao¹

¹ Intelligent Transportation Division, Anhui Sanlian University, Hefei, Anhui 276000, China

² Office of Research, Anhui Sanlian University, Hefei, Anhui 276000, China

³ Modern Health and Wellness Division, Anhui Sanlian University, Hefei, Anhui 276000, China

Objective: The prevalence of anxiety and depression among university students is steadily increasing. However, traditional mental health services generally adopt a passive response model, which presents clinical bottlenecks such as low screening coverage, delayed identification, and inequitable allocation of intervention resources. Passively sensed data generated by wearable devices and campus behavioral logs offer new possibilities for large-scale, continuous early risk identification. This study aims to develop and prospectively validate an IoT- and big data-driven multidimensional assessment model for anxiety and depression in university students, integrating behavioral, environmental, and physiological data, and to explore its clinical translation value for individualized psychological intervention practices.

Methods: The data collection period for this study spanned 16 consecutive weeks, with a total of 1,247 university students enrolled as participants. Physiological data, including heart rate, heart rate variability (HRV, with time-domain indicators RMSSD and SDNN), sleep duration, and sleep efficiency, were continuously collected over the 16 weeks using commercial wearable devices. Concurrently, behavioral data were extracted from campus card system logs and mobile application usage logs to construct a multidimensional feature pool. All participants completed the Generalized Anxiety Disorder scale (GAD-7) and the Patient Health Questionnaire (PHQ-9) at baseline and every four weeks thereafter, to assess the levels of anxiety and depressive symptoms, which served as reference labels for model training.

Results: First, model evaluation efficacy. The performance of the proposed model was significantly superior to that of models based on single-modality data (physiological data only, behavioral data only, or environmental data only), thereby validating the necessity of multi-modal information fusion. Second, differentiated physiological characteristics of anxiety and depression. Through SHAP feature attribution analysis and time-frequency analysis of physiological signals, it was found that the core physiological features of anxiety states include: a significant reduction in high-frequency power of heart rate variability, an increased fluctuation frequency of skin conductance activity, prolonged sleep latency, and an increased number of awakenings. In contrast, the core physiological features of depressive states include: a reduced ratio of low-frequency to high-frequency power of heart rate variability, a decreased mean level of skin conductance activity, shortened deep sleep duration with advanced morning awakening, and a flattened morning cortisol rhythm. These findings suggest that anxiety and depression are associated with distinguishable physiological signal characteristics. Third, temporal dynamic patterns. Time series analysis revealed that abnormal changes in physiological indicators typically precede the onset of clinical symptoms by approximately 5 to 8 days. This finding provides a temporal dynamic foundation for the development of an IoT data-based early warning system for mental health.

Conclusion: The IoT- and big data-driven multidimensional assessment model demonstrates clinically acceptable predictive performance for anxiety and depressive symptoms among university students. These findings provide a prospectively validated technological foundation for the development of large-scale digital screening and individualized intervention allocation for campus mental health.

Acknowledgements: This work was supported by the 2025 Anhui Provincial Social Science Innovation and Development Research Project (Major Project). (Grant No. 2025ZDO12). The project title is “Research on Innovative Paths of Ideological and Political Work in the New Technology Era: Ideological and Political Practice Empowered by Digital Intelligence in Anhui Universities from the TPACK Perspective”.

Corresponding Author: Teng Yuan, Intelligent Transportation Division, Anhui Sanlian University, Hefei, Anhui 276000, China.

“Less but Better” Practicum Course on Occupational Stress and Mental Health in Preschool Education Interns: A Quasi-Experimental Study Based on Heart Rate Variability, Cortisol, Sleep Quality, and Psychological Scales

Hong Xu, Yifan Nie*

Hubei Engineering University, Xiaogan, China

Objectives: Preschool education interns experience considerable occupational stress during block practicum. Conventional high volume training models seldom address this challenge. This study treats the “Less but Better” (LBB) concentrated practicum course as a targeted intervention for this high stress population. Using a quasi-experimental design, we integrated multimodal indicators—heart rate variability (HRV), salivary cortisol, sleep quality, and standardized psychological scales (PSS 10, MBI GS)—to examine the mechanisms by which the LBB course regulates stress, prevents burnout, and optimizes learning performance.

Methods: Drawing on the quality improvement logic of higher education, constructivist learning theory, Tao Xingzhi’s “life education” theory, and multiple intelligences theory, a “four in one” training mechanism (target precision, content modularization, method diversification, guarantee systematization) was reconstructed. The LBB model reduced total contact hours while enhancing mentorship quality, reflective practice, and competence based tasks. A two year quasi experiment was conducted across three undergraduate institutions, covering over 400 students, with a parallel control group following the conventional practicum schedule. Multi-dimensional assessment included: Physiological & endocrine indicators: Resting state HRV (HF, LF/HF) and morning salivary cortisol levels measured at baseline and post intervention. Sleep & psychological indicators: Pittsburgh Sleep Quality Index (PSQI), Perceived Stress Scale (PSS 10), and Maslach Burnout Inventory General Survey (MBI GS). Learning performance indicators: Practical ability test (Kindergarten Activity Design and Implementation score, teaching plan adoption rate), professional identity questionnaire, employment quality (employment rate, high quality kindergarten placement, employer rating), and internship adaptation duration

Results: The LBB group outperformed the control group across all domains. Key physiological and psychological outcomes: HRV: The intervention group showed a significant increase in HF (45.2±8.1 vs. 32.6±7.5 ms², P<0.01) and a decrease in LF/HF ratio (1.2±0.3 vs. 1.9±0.5, P<0.01), indicating enhanced parasympathetic activity and reduced stress. Cortisol: Morning cortisol decreased by 22% from baseline in the intervention group (16.3±3.2 to 12.7±2.8 nmol/L, P<0.01); no significant change was observed in the control group. Sleep quality: PSQI total score declined from 8.4±2.1 to 4.9±1.6 in the intervention group (P<0.001) versus 8.6±2.0 to 7.8±1.9 in the control group. Psychological scales: In the intervention group, PSS 10 dropped from 28.5±4.2 to 18.3±3.6 (P<0.001), and MBI GS emotional exhaustion subscale decreased from 26.1±4.5 to 16.4±3.9; no significant improvements were seen in the control group. Learning performance outcomes: The intervention group achieved higher practical ability scores (85.6 vs. 72.3), teaching plan adoption rate (60% vs. 25%), professional identity (92% vs. 65% recognizing profession’s value), long term career intention (88% vs. 58%), employment rate (96.5% vs. 88%), high quality kindergarten placement (85% vs. 55%), employer “excellent” rating (90% vs. 60%), and shorter internship adaptation (1 month vs. 3 months). Instructor outputs and university kindergarten collaborations were also superior in the intervention group.

Conclusions: The LBB mechanism reduces quantitative load while strengthening structural support, creating a lower stress practicum environment that enhances practical ability, professional identity, and employability. The multimodal evidence from HRV, cortisol, PSQI, PSS 10, and MBI GS consistently demonstrates that the LBB course effectively promotes stress regulation and prevents burnout, likely via restoration of autonomic balance and improved HPA axis function. This model provides a replicable solution for practicum reform, warranting future multicenter randomized controlled trials

Acknowledgements: This work was supported by the Teaching Reform Research Project of Hubei Engineering University “Research on the Training Mechanism of Block Practicum Courses for Preschool Education Majors” (Grant No. JY2025026).

Corresponding Author: Yifan Nie, Hubei Engineering University, Xiaogan, China.

Digital Phenotype-Based Prediction of Anxiety and Depressive Disorders in a University Student Population: Evidence from a Prospective Cohort

Kai Liu*

College of Modern Economics and Management, Jiangxi University of Finance and Economics, Gongqingcheng, Jiangxi, China

Objectives: The prevalence rates of anxiety and depressive disorders among university students have been steadily increasing, posing a significant challenge to the global higher education sector. Prospective cohort studies utilizing digital phenotyping data to predict anxiety and depressive disorders in university students remain scarce. To comprehensively and dynamically assess student satisfaction at the School of Modern Economics and Management, Jiangxi University of Finance and Economics using large-scale social media data, and to evaluate the feasibility of operationalizing social media-derived features as digital phenotypic indicators for predicting anxiety and depressive disorder risk among college students within a prospective cohort framework.

Methods: Large-scale user-generated comment data were systematically collected from three mainstream social media platforms (Baidu Tieba, Douyin, and Zhihu). BosonNLP Latent Dirichlet Allocation (LDA) topic modeling and SnowNLP sentiment analysis were applied to conduct multi-dimensional computational analysis of student-generated content. Sentiment polarity, temporal dynamics, and thematic distributions were examined to characterize satisfaction patterns across platforms and over time. Social media-derived sentiment and topical features were subsequently operationalized as digital phenotypic indicators and integrated with validated psychometric instruments—the Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder-7 (GAD-7) scale—within a prospective cohort design. Furthermore, the study integrates multi-dimensional physiological indicators into the theoretical framework, including autonomic nervous function indicators, neuroendocrine indicators, sleep physiological indicators, and electrodermal activity indicators. The theoretical analysis focuses on the temporal relationships among digital phenotypic features, physiological indicators, and changes in psychological states, the integrative predictive logic of multimodal markers, and the trajectory characteristics of behavioral-physiological co-shifts.

Results: The results indicated that the overall distribution of anxiety and depression emotions among the student population was predominantly positive (59.6%), followed by neutral (26.5%) and negative (13.8%) emotions, with statistically significant inter-platform heterogeneity observed across the three platforms. This study proposes and systematically demonstrates the following core theoretical findings: First, the onset of psychological disorders is preceded by a “behavioral-physiological” dual-system prodromal phase. Second, anxiety and depressive disorders exhibit differentiated “behavioral-physiological” phenotypic characteristics. For instance, the physiological phenotype of anxiety is characterized by sustained elevation of sympathetic nervous system tone, whereas the physiological phenotype of depression is characterized by global suppression of autonomic nervous system activity and reduced hypothalamic-pituitary-adrenal (HPA) axis function. Third, there exists a dynamic bidirectional regulatory and mutually corroborative relationship between behavioral phenotypes and physiological indicators. This study proposes a “behavioral-physiological dual-modality dynamic psychological risk assessment model” for the early warning of anxiety and the risk of psychological disorders among university student populations.

Conclusions: Social media-derived digital phenotypic indicators demonstrate meaningful utility in dynamically quantifying student satisfaction and capturing affective responses to institutional events. Within the prospective cohort framework, the integration of these indicators with PHQ-9 and GAD-7 instruments enables systematic, longitudinal assessment of anxiety and depressive disorder risk among college students, offering a scalable and non-intrusive approach to early risk identification. These findings support the development of timely, targeted mental health screening protocols and evidence-based early intervention strategies, while providing higher education administrators with empirical, data-driven foundations for institutional decision-making and student welfare policy formulation.

Acknowledgements: This work was supported by a project grant from Science and Technology Research Project of Jiangxi Provincial Department of Education (Grant No.GJJ218303).

Corresponding Author: Kai Liu, College of Modern Economics and Management, Jiangxi University of Finance and Economics, Gongqingcheng, Jiangxi, China.

Risk Prediction of Long-Term Major Adverse Cardiovascular Events in Patients with Acute Coronary Syndrome: Model Development and Validation

Yuan Yuan*

Medical School of Nantong University, Nantong University, Nan Tong, Jiang Su, China

Background: Acute Coronary Syndrome (ACS) is a significant cause of cardiovascular death and major adverse cardiovascular events (MACE). Traditional GRACE scores and TIMI scores mainly rely on linear statistical methods and are difficult to reflect the complex relationships between clinical variables and individual differences. In recent years, artificial intelligence has shown potential in disease prognosis prediction, but studies specifically targeting long-term MACE risk prediction for ACS and verified by external validation are still limited. This study builds and validates an artificial intelligence-assisted long-term MACE prediction model for ACS based on a large-scale clinical database.

Methods: This study was based on the publicly available MIMIC-IV v3.1 database from PhysioNet. 8,642 patients with ACS were included as the data for model development, and 4,761 patients from the MIMIC-IV-Ext database of heart diseases were used as cardiac disease-related external validation data. The primary outcome was whether MACE occurred during the 1-year follow-up period. The study integrated patient basic information, past medical history, admission vital signs, laboratory results, and treatment conditions, and selected key variables related to the outcome. On this basis, traditional statistical models, machine learning models, and deep learning models were constructed for comparison to evaluate the predictive performance of different methods. The influence of key variables was analyzed, and the model's ability to distinguish different risk groups was verified through risk stratification.

Results: The median follow-up period was approximately 11 months. The incidence of MACE was similar in both cohorts. Multivariate analysis revealed that advanced age, increased Killip classification, elevated troponin, elevated BNP, and abnormal renal function were significantly associated with higher MACE risk, whereas PCI was associated with lower MACE risk. In model comparison, DeepSurv performed the best, with superior predictive ability compared to the Cox model and other machine learning methods, and significantly better than GRACE and TIMI scores. SHAP analysis indicated that BNP, troponin, and renal function indicators were the main influencing factors, and the event rate in the high-risk group was significantly higher.

Conclusions: This study developed and validated an AI-based MACE prediction model for ACS. Compared with traditional risk scores, this model achieves earlier identification of high-risk ACS patients and more precise risk stratification. This model is expected to serve as an auxiliary tool for individualized treatment decisions and long-term management strategies.

Corresponding Author: Yuan Yuan, Medical School of Nantong University, Nantong University, Nan Tong, Jiang Su, China.

The Role of Hydrogel in Bone Regeneration

Lakshmi Jeevithan^*, Jose Eduardo Mate Sanchez de Val

Department of Biomaterials Engineering, Faculty of Health Sciences, UCAM—Universidad Católica San Antonio de Murcia, Campus de los Jerónimos 135, 30107 Guadalupe, Murcia, Spain

Objectives: Bone regeneration remains a significant clinical challenge, necessitating the development of advanced biomaterials that can actively instruct cellular behavior. While hydrogels offer a promising scaffold due to their resemblance to the extracellular matrix, their regenerative potential is often limited without specific bioactive cues. This study investigates the osteoinductive role of a novel Carboxymethyl Chitosan (CMC) hydrogel system loaded with marine fungi-derived fibrinolytic compound (FGFC1), a fibrinolytic compound derived from the marine fungus Stachybotrys longispora. Hence, we hypothesized that the unique biological activity of FGFC1 could be harnessed to promote the osteogenic differentiation of Mesenchymal Stem Cells (MSCs).

Methods: CMC hydrogels were synthesized and loaded with FGFC1 along with crosslinkers and characterized for their physicochemical properties. Then, proliferation and osteogenic potential of these hydrogels were determined by Alkaline Phosphatase (ALP), qRT-PCR and histological staining methods.

Results: CMC hydrogels demonstrated suitable porosity and degradation kinetics for bone tissue engineering. The incorporation of FGFC1 did not compromise the hydrogel's structural integrity or cytocompatibility. In vitro studies revealed that the FGFC1-loaded hydrogels significantly enhanced the proliferation of MSCs compared to control groups. Most critically, the bioactive hydrogels robustly induced osteogenic differentiation. This was evidenced by a marked upregulation in Alkaline Phosphatase (ALP) activity, a key early marker of bone formation. Furthermore, gene expression analysis via qRT-PCR demonstrated a significant increase in the expression of master osteogenic transcription factor Runx2, as well as the downstream bone matrix proteins Type I Collagen (Col I) and Osteocalcin (OCN).

Conclusions: These findings suggest that the sustained release of FGFC1 from the CMC matrix activates specific signaling pathways that drive the osteoblastic lineage commitment of stem cells. In conclusion, this study identifies FGFC1 as a potent marine-derived osteoinductive agent and validates the CMC-FGFC1 hydrogel as a promising bioactive scaffold for accelerating bone regeneration in orthopedic and dental applications.

Acknowledgements: This research was supported by UCAM, Murcia.

Corresponding Author: Lakshmi Jeevithan, Department of Biomaterials Engineering, Faculty of Health Sciences, UCAM—Universidad Católica San Antonio de Murcia, Campus de los Jerónimos 135, 30107 Guadalupe, Murcia, Spain.

Clinical Study on the Treatment of Severe Radiation-Induced Lung Injury after IMRT for Lung Cancer with Different Doses of Methylprednisolone Combined with N-Acetylcysteine

Xuelin Zhang¹’^*, Wei Gao², Shiyu Zhuo¹, Weichun Guo¹

¹ Department of Oncology, The Second Affiliated Hospital of Hebei North University, Zhangjiakou 075100, Hebei, China

² Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Hebei North University, Zhangjiakou 075100, Hebei, China

Objective: Lung cancer is the malignant tumor with the highest mortality rate in China. Radiation-induced lung injury (RILI) limits the efficacy of radiotherapy for lung cancer and affects the prognosis of patients. This work aims to explore the clinical efficacy of different doses of methylprednisolone combined with N-acetylcysteine in the treatment of severe RILI after intensity-modulated radiotherapy (IMRT) for lung cancer.

Methods: According to the random number table method, 120 patients with severe RILI (RTOG/EORTC grade ≥ 3) after IMRT for lung cancer who were admitted to our hospital from January 2023 to June 2025 were divided into two groups, with 60 cases in each group. Both groups were given basic supportive treatment (oxygen inhalation, cough suppression, preventive anti-infection, etc.) and oral N-acetylcysteine tablets (0.6g, bid). On this basis, the control group was given the standard dose of methylprednisolone (1.0mg/kg/d), while the observation group was given a higher dose of methylprednisolone (2.0mg/kg/d). The treatment course was 14 days, and the dosage was gradually reduced according to the disease gradient. The clinical efficacy, pulmonary function indicators [forced vital capacity (FVC), carbon monoxide diffusion capacity (DLCO)], and serum inflammatory factors [transforming growth factor-β1 (TGF-β1), interleukin-6 (IL-6)] levels of the two groups were compared.

Results: After treatment, the clinical total effective rate of the observation group was significantly higher than that of the control group (P<0.05). Moreover, after treatment, both groups showed significant increases in FVC and DLCO compared with before treatment (P<0.05), and the increase in the observation group was more significant (P<0.05). After treatment, the serum levels of TGF-β1 and IL-6 in both groups were significantly lower than those before treatment (P<0.05), and the decrease in the observation group was more significant (P<0.05). There was no statistically significant difference in adverse reactions between the two groups (P>0.05), and the adverse reactions were all mild to moderate. After symptomatic treatment, they were relieved, and no serious adverse events occurred.

Conclusion: This work compared the clinical efficacy of methylprednisolone combined with NAC at equal doses in the treatment of severe RILI after IMRT for lung cancer. The results indicated that high-dose methylprednisolone significantly improved the overall clinical prognosis of patients with severe RILI and had greater advantages in alleviating alveolar inflammation and restoring gas exchange. In summary, for patients with severe RILI after IMRT for lung cancer, the treatment regimen of 2.0 mg/kg/d methylprednisolone combined with N-acetylcysteine can more effectively suppress the inflammatory storm, improve pulmonary function, and maintain controllable safety under close monitoring and symptomatic support.

Corresponding Author: Xuelin Zhang, Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Hebei North University, Zhangjiakou 075100, Hebei, China

Author Index

The number next to the author indicates the page number.

Bei Deng, 20

Bin He, 26, 38

Bin Xia, 36

Chen Zhao, 28

Cheng Ji, 27

Chengkai Lai, 31

Chu Li, 22

Dongbin Lu, 17

Duanzhong Chen, 19

Duo Tang, 34

Fang Wang, 9

Feng Liang, 19

Fengnian Liu, 27

Fuchun Li, 17

Geyan Wang, 29, 41

Guangding Hou, 19

Haidan Hu, 4

Han Li, 5

Haotian Dinig, 15

Haoyuan Xu, 22

Hengying Che, 4

Hong Xu, 43

Hua Chen, 35

Huanxiu Wu, 1

Huiling Ren, 30

Huiqiao Gao, 42

Huiqin Xu, 11

Ji Liu, 40

Jiabin Zhao, 34

Jiahao Tian, 29, 41

Jiale Chen, 22

Jiale Wang, 7

Jiale Yang, 38

Jian Gao, 29, 41

Jian Li, 11

Jian Wei, 3

Jianfeng Xie, 18

Jiang Li, 22

Jianhui Li, 7

Jiankui Peng, 26, 38

Jianxin Zhang, 11

Jianzhao Cheng, 2

Jiaojiao Zhou, 19

Jiaqi Qiu, 25

Jiaqing Li, 17

Jiarui Tang, 10

Jiayu Dong, 7

Jie Ding, 15

Jie Hu, 22

Jie Zhang, 15

Jimin Zhang, 27

Jincen Cai, 15

Jing Che, 39

Jing Lin, 34

Jing Long, 27

Jingyi Chen, 3

Jinling Liu, 11

Jinzhang Wang, 18

Jose Eduardo Mate Sanchez de Val, 45

Jun Wen, 23

Kai Liu, 44

Keke Ge, 42

Kexin Ma, 11

Kezhong Lu, 22

Kun Ma, 8

Lakshmi Jeevithan, 45

Lei Zhang, 20

Li Zhong, 24

Liang Zhou, 21

Lili Xu, 3

Lili Zhang, 23

Limin Xu, 23

Lin Chen, 31

Lina Zhang, 11

Ling He, 35

Lingling Ge, 28

Liuqing Cheng, 11

Liyuan Fan, 31

Lu Zhang, 5

Luo Tian, 12

Lupei Ding, 34

Meihua Suo, 22

Meng Huang, 18

Mengyao Zhang, 39

Min Chen, 35

Mingming Zhou, 15

Mingxia He, 38

Na Liu, 39

Ning Chen, 4

Ning Hao, 6

Ning Zhao, 26

Peng Dai, 22

Peng Wu, 19

Pengcheng Lu, 21

Pengcheng Zhang, 33

Ping Chi, 20

Pu Rao, 11

Puzhu Han, 11

Qian Wang, 14

Qian Zhang, 5

Qianqian Xu, 3

Qingmei Li, 1

Qinyi Yang, 15

Qiutong Lu, 15

Quan Luo, 14

Quan Tang, 11

Quanrong Fang, 3

Ran Chen, 29, 41

Rong Wang, 22

Ruiyang Zhang, 9

Ruiyu Yang, 36

Saiyu Zhang, 13, 32

Sha Wu, 19

Shanshan Li, 20

Shidong Chu, 1

Shinan Li, 6

Shiying Cai, 35

Shiyu Zhuo, 46

Shuang Wu, 33

Shunying Zhang, 9

Shuxing Yang, 1

Sibin Tao, 17

Simei Tang, 19

Siyan Zhang, 29, 41

Siyu Tao, 41

Songyan Zhang, 31

Tao Xu, 42

Tao Zhou, 35

Teng Yuan, 42

Tian Zhang, 36

Wei Gao, 46

Wei Li, 19

Wei Xie, 20

Weichun Guo, 46

Weiying Di, 39

Wen Min, 25

Wen Zhang, 23

Wenbo Yu, 17

Wencan Li, 19

Wenhu Zhou, 4

Wenjia Li, 29, 41

Wenjing Liu, 4

Wenlong Xiu, 18

Wenqing Cao, 24

Wenqing Liu, 8

Wenqiong Xiu, 18

Wenyuan Cao, 11

Wenyuan Zeng, 27

Wenzijing Ni, 5

Xiaofeng Ye, 5

Xiaoli Chen, 28

Xiaotong Fan, 31

Xiaoya Wen, 1

Xiaoyan Li, 8

Xin Li, 11

Xinhe Xu, 26

Xinlei Huang, 17

Xinpeng Wang, 8

Xinqiang Zhang, 16

Xinrui Wu, 15

Xiuhong Li, 23

Xue Chen, 39

Xue He, 26, 38

Xuejuan Zan, 9

Xuelin Zhang, 46

Xuke Huang, 42

Yan Qin, 33

Yan Shuang, 13, 25

Yan Wen, 19

Yan Zhao, 1

Yanan Chen, 39

Yandong Mu, 31

Yang Qian, 6

Yangyang Lu, 31

Yanping Yang, 30

Yaping Chen, 31

Yarui Huo, 41

Yi Liu1, 23

Yi Sun, 3

Yibo Zhang, 27

Yifan Nie, 43

Yihao Xiao, 40

Yili Wang, 37

Yiming Feng, 40

Ying Chen, 20

Yingzhe Liu, 13, 25

Yixuan Wu, 41

Yiyun Zhang, 1

Yizi Xiao, 34

Yongdong Liu, 11

Yongmei Wen, 31

Yongqing Chou, 8

Yu Cao, 9

Yu Liu, 13, 25

Yu Ma, 23

Yuan Wei, 27

Yuan Yuan, 45

Yuan Zhao, 1

Yuansheng Dong, 22

Yuanxin Wang, 25

Yue Feng, 31

Yue Wei, 40

Yufei Yan, 3

Yuhan Chen, 29

Yuhao Chen, 41, 29

Yujie Li, 33

Yulan Kang, 18

Yun Cai, 39

Yun Jiang, 15

Yunqiong Jiang, 20

Yuxia Ma, 33

Yuxin Wang, 10

Yuzhe Ding, 34

Zhen Jiang, 5

Zhenghua Xu, 40

Zhengqi Sun, 3

Zhengqing Mao, 19

Zhengyi Pan, 8

Zhenyu Wen, 17

Zhiyong Pang, 8

Zhongchao Wang, 31

Zhongjie Mao, 22

Zihao Yan, 27

Zijun Mu, 33

Zirui Wang, 6

Ziyan Guo, 2

Ziyi Wang, 28