Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.

Objective:To explore the structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

Objective To investigate the clinical efficacy of recombinant human granulocyte-macrophage colony-stimulating factor(rhGM-CSF)combined with bifidobacterium in the treatment of oral mucositis after chemotherapy.Methods A total of 60 post-chemotherapy patients with oral mucositis admitted to Ganzhou Cancer Hospital of Jiangxi Province from January 2023 to December 2024 were selected as subjects,the patients were divided into observation group(n=30)and control group(n=30)by using a randomized digital table method.The control group received rhGM-CSF mouthwash treatment,while the observation group was additionally administered bifidobacterium-lactobacillus triple live capsules orally.Clinical efficacy,symptom scores,inflammatory factor levels,oral microbiota indicators,and treatment safety were evaluated after 2 weeks of treatment.Results After treatment,the total effective rate in observation group was significantly higher than that in control group(P＜0.05).Post-treatment evaluations showed that patients in observation group exhibited lower scores for edema,congestion,and ulceration,along with reduced pain visual analog scores and decreased levels of inflammatory markers including Toll-like receptor 4,lectin-3,and interleukin-8,the difference were statistically significant(P＜0.05).After treatment,the oral microecological flora of patients in observation group,including lactic acid bacteria and bifidobacterium,were higher than that of control group,while porphyromonas gingivalis and fusetella were lower than that of control group,the difference were statistically significant(P＜0.05).Conclusion The clinical effect of rhGM-CSF combined with bifidobacterium in the treatment of oral mucositis after chemotherapy was significant,which could reduce various symptoms of patients,inhibit inflammatory factors,improve oral microecology,and have good safety.

Objective To analyze the differences in bone serum protein between patients with osteoporosis accompanied by obstructive sleep apnea syndrome(OSAS)and those with osteoporosis only using proteomics.Methods A total of 80 osteoporosis patients who attended our hospital between June 2022 and June 2024 were enrolled.Based on their polysomnography results,the participants were divided into an OSAS and osteoporosis comorbidity(OSAS-osteoporosis)group(n=42)and an osteoporosis only group(n=38).Propensity score matching was applied to incorporate covariates in logistic regression so that the individual characteristics of the two groups of patients were generally balanced.Following the matching procedure,a final cohort of 20 matched pairs was obtained and subsequently utilized for further analysis.The mass spectrum was obtained using laser desorption ionization mass spectrometry.Principal component analysis(PCA)was performed to assess differences in metabolic patterns between groups.Partial least squares discriminant analysis(PLS-DA)and orthogonal PLS-DA(OPLS-DA)were employed for further data analysis.Variable importance in projection(VIP)scores of each substance were calculated with OPLS-DA to screen the metabolites showing inter-group differences.Heatmaps were generated to visualize metabolic profile differences between the OSAS-osteoporosis group and the osteoporosis group.Enrichment pathway analysis was conducted on the differential identified metabolites.Results After propensity score matching,individual characteristics between the groups were well balanced.Mass spectrometry revealed significant differences between the OSAS-osteoporosis and osteoporosis groups.In the PCA score plot,the separation trend of the two groups was not significant.The PLS-DA score plot showed a discernible separation trend,with R2 and Q2 lower than those of the corresponding results of the real model,confirming the reliability of the model.OPLS-DA showed that the total R2X of the model was 0.635,R2Y was 0.879,and O2Y was 0.728,showing obvious separation trends between the two groups.A total of 16 differential metabolites were identified,including stearyl-oleyl-glycerol phosphate choline,phosphate choline,L-histidine,erucamide,2'-deoxyuridine,1-palmitoyl glycerol,thymine,tyramine,L-pyroglutamic acid,L-glutamic acid,myristate,glycerol-3-phosphate,caprylic acid,pregnenolone,L-arginine,D-4-hydroxyphenylglycine,and isobutyric acid.Heatmaps showed significant differences in metabolic profiles between the OSAS-osteoporosis group and the osteoporosis group.Pathway enrichment analysis showed that 27 metabolic pathways were involved.27 metabolic pathways.Under the conditions of P<0.05 and pathway impact>0.2,the three most significant metabolic pathways identified included mainly alanine,aspartate,and glutamate metabolism,arginine biosynthesis,and histidine metabolism.Conclusion Significant differences were observed in the metabolic profiles between patients with both OSAS and osteoporosis and those with osteoporosis alone.

Objective To develop the Ego Depletion Scale for Type 2 Diabetes Patients and evaluate its reliability and validity,and to provide a specific assessment tool for evaluating ego-depletion in self-management.Methods Guided by the self-control strength model,the initial scale was constructed through literature review,semi-structured interviews,2 rounds of expert consultation,and a pilot survey.A convenience sampling method was employed to recruit 460 patients with Type 2 Diabetes from the endocrinology department of a tertiary hospital in Wuhan,Hubei Province,between April and July 2024.They were randomly divided into 2 subsets for exploratory factor analysis and confirmatory factor analysis.Results A total of 451 valid questionnaires were collected.Exploratory factor analysis extracted 6 common factors,with a cumulative variance contribution of 73.231％.In confirmatory factor analysis,an item was deleted due to failing to meet the standardized loading value criterion.The revised Ego Depletion Scale for Type 2 Diabetes Patients comprised 6 dimensions and 22 items.The total Cronbach's α coefficient was 0.911;split-half reliability was 0.744;the content validity index was 0.860.Correlation coefficients between the total score and scores of each dimension of the scale and the total score of the Self-Regulatory Fatigue Scale ranged from 0.558 to 0.946(P＜0.001).Conclusion The scale exhibits robust reliability and validity,serving as a scientifically instrument for assessing ego depletion in patients with Type 2 Diabetes.

Purpose To explore the diagnostic efficacy of texture analysis in grading multiple ligament injuries of the knee Joint.Materials and Methods MRI images of 203 patients with knee injuries in the Second Affiliated Hospital of Shantou University School of Medicine from June 2018 to September 2020 were retrospectively collected,and then graded the injuries of multiple ligaments.Extraction of texture features and discriminant analysis were accomplished by MaZda software.Spearman correlation analysis and LASSO penalized Logistic regression analysis were used to further explore the differential diagnostic efficacy of each texture parameter for grading knee ligament injuries.Results(1)MaZda software was found to have the highest diagnostic efficacy for patellar ligament injury grading by using different texture feature screening methods in combination with discriminant analysis.Non-linear discriminant analysis had the lowest misclassification rate of 4.43%.(2)The texture parameters that were ultimately included in the analysis of the subjects'work characteristic curves appeared more frequently in the gray level co-occurrence matrix and the run length matrix.(3)The area under the curve of the texture parameters finally included in the analysis were 0.870-0.975,0.772-0.912,0.836-0.929 and 0.766-0.920,respectively in patellar ligament,anterior cruciate ligament,posterior cruciate ligament and lateral collateral ligament for the diagnosis of knee ligament injury grading.The diagnostic efficacy for patellar ligament injury grading was the highest,which was consistent with the lowest misclassification rate for patellar ligament in the discriminant analysis of texture features.And the texture parameters ultimately included in patellar ligament were all highly correlated with its injury grading.Conclusion The texture analysis technique has high diagnostic efficacy for grading knee ligament injuries,and can provide a more accurate diagnostic imaging basis for the clinic.

Objective:To systematically evaluate the current status of research on the development of indicators for entrustable professional activities (EPAs) of residents in China.Methods:We searched the China National Knowledge Infrastructure, Wanfang Data, Airiti Library, PubMed, Embase, and Web of Science databases for literature on the development of EPA indicators for residents in China published between January 1, 2005 and February 28, 2025. Two researchers independently screened the literature and extracted data, followed by descriptive analysis. The quality of the studies was assessed using the Joanna Briggs Institute critical appraisal tool for expert opinion. Quantitative data were presented as medians (ranges) and qualitative data were presented as frequencies (percentages).Results:A total of eight articles were included, in which two general EPA indicator systems and six specialty-specific EPA indicator systems were developed for residents. The overall quality of the research was high, with the main shortcomings related to the methods used in the process of constructing the consensus indicators. The number of experts recruited ranged from 22 to 45, with 100.00% response rate, high authority coefficients (0.820-0.914), and high coordination coefficients (0.157-0.741). Most of the studies used literature reviews as one source for the indicator pool (8 studies, 100.00%), employed the Delphi method to reach consensus (6 studies, 75.00%), and provided inclusion criteria for the indicators (7 studies, 87.50%). However, only one study (12.50%) explored the practical application of the developed indicators, and none of the studies set indicator weights or conducted quality assessments. The number of EPA indicators developed ranged from 10 to 38 per study. The reporting of EPA indicators was included in most studies regarding titles (8 studies, 100.00%) and the expected levels of entrustment at various stages of training (6 studies, 75.00%), but the reporting on other aspects was lacking. Among the specialty-specific EPA indicators, 38.39% overlapped with the general EPAs indicators.Conclusions:The research on the development of EPA indicators for residents in China is still in its early stages, and there is room for improvement in methodological quality and reporting coverage. There is partial overlap between specialty-specific and general EPA indicators, failing to fully reflect the unique characteristics of different specialties.

Objective:To investigate the current status of Chinese-foreign cooperative education programs for medical majors, and to discuss the potential problems and development trends of this field.Methods:Related data were collected from the information platform of Chinese-Foreign Cooperation in Running Schools by Ministry of Education of the People's Republic of China, and the characteristics of Chinese-foreign cooperative education programs for medical majors were extracted for analysis. Categorical data were expressed as frequency (percentage), and continuous data were expressed as mean±standard deviation.Results:A total of 83 Chinese-foreign cooperative education programs for medical majors were included in the study, accounting for only 3.45% (83/2 406) of all programs. Chinese partners in these cooperative programs were mainly from East China (41 programs, 49.40%), while foreign partners were mainly from Europe (39 programs, 46.99%). The mean duration of these programs was (3.61±0.88) years, with an enrollment of (87.08±35.52) students. Most of the students were included in National General Higher Education Enrollment Plan (79 programs, 95.18%), and the main majors included nursing (39 programs, 46.99%), medical technology (19 programs, 22.89%), and clinical medicine (11 programs, 13.25%), with the main enrollment level of junior college (45 programs, 54.22%). Chinese partners in the cooperative programs mainly issued academic certificate (45 programs, 54.22%) or academic certificate plus degree certificate (36 programs, 43.37%), while most foreign partners did not issue such certificates (44 programs, 53.01%).Conclusions:There are several problems in Chinese-foreign cooperative education programs for medical majors, such as a limited number of programs, a significant regional difference, an imbalanced distribution of specialties, a low level of education, and inconsistency in issuance of certificates, which still requires further improvement and standardization. However, there are also high-level and high-quality programs for reference.

Objective:To systematically evaluate the home care needs of the disabled elderly in China, to provide a reference for developing home care services oriented to the needs of the elderly.Methods:Qualitative studies on the need for home care services for the disabled elderly in China were electronically searched in PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, VIP, WanFang Data, and China Biology Medicine disc. The search time limit was from the tstablishment of the database to March 9, 2024. The methodological quality of the included literature was evaluated using the quality evaluation criteria for qualitative research (2016) of the Joanna Briggs Institute Evidence-Based Health Care Center. The results of the qualitative study were analyzed using the convergent integration method.Results:A total of 12 articles were included, and 43 outcomes were distilled, summarized to form eight new categories, and synthesized to produce two outcomes, including medical care and rehabilitation needs (professional nursing needs, rehabilitation and exercise needs, health guidance needs, and psychological guidance needs), and supportive needs (policy support needs, home environment needs, service resource needs, and life care needs) .Conclusions:Disabled elderly have multifaceted needs for home care. It is recommended that a multidisciplinary team be formed and a multi-pronged integrated care model be adopted to meet the needs of the disabled elderly living at home.

Objective To develop the Ego Depletion Scale for Type 2 Diabetes Patients and evaluate its reliability and validity,and to provide a specific assessment tool for evaluating ego-depletion in self-management.Methods Guided by the self-control strength model,the initial scale was constructed through literature review,semi-structured interviews,2 rounds of expert consultation,and a pilot survey.A convenience sampling method was employed to recruit 460 patients with Type 2 Diabetes from the endocrinology department of a tertiary hospital in Wuhan,Hubei Province,between April and July 2024.They were randomly divided into 2 subsets for exploratory factor analysis and confirmatory factor analysis.Results A total of 451 valid questionnaires were collected.Exploratory factor analysis extracted 6 common factors,with a cumulative variance contribution of 73.231％.In confirmatory factor analysis,an item was deleted due to failing to meet the standardized loading value criterion.The revised Ego Depletion Scale for Type 2 Diabetes Patients comprised 6 dimensions and 22 items.The total Cronbach's α coefficient was 0.911;split-half reliability was 0.744;the content validity index was 0.860.Correlation coefficients between the total score and scores of each dimension of the scale and the total score of the Self-Regulatory Fatigue Scale ranged from 0.558 to 0.946(P＜0.001).Conclusion The scale exhibits robust reliability and validity,serving as a scientifically instrument for assessing ego depletion in patients with Type 2 Diabetes.