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.

BackgroundNon-suicidal self-injury （NSSI） behavior among adolescents has become a global public health concern. Anxiety and depression are considered key factors influencing NSSI behavior， while social support may play a protective role in alleviating emotional and behavioral issues. However， existing research has primarily focused on the direct impact of individual factors on NSSI behavior， with insufficient exploration of the combined effects of anxiety， depression and social support. ObjectiveTo investigate the direct effect of anxiety on NSSI， the mediating role of depression and the moderating role of social support in relationship between anxiety and NSSI behavior， thus to provide references for the prevention and intervention of NSSI behavior among adolescents. MethodsIn February 2022， a total of 40 820 students in grades 7 to 12 across 10 middle schools in a district of Chengdu were selected as participants， and they were assessed using Generalized Anxiety Disorder Scale-7 item （GAD-7）， Patient's Health Questionnaire Depression Scale-9 item （PHQ-9）， Social Support Scale for Urban Students （SSSUS） and Adolescent Self-Harm Scale （ASHS）. Pearson correlation analysis was conducted to examine the correlations between scale scores among adolescents with NSSI behaviors. Mediation and moderation analyses were performed using Process 3.5 in SPSS， and the significance was tested with bootstrapping. The interaction was visualized by using simple slope analysis. ResultsAmong 34 534 （84.60%） valid respondents， 542 adolescents （1.57%） reported engaging in NSSI behavior. Significant differences in gender， GAD-7 scores， PHQ-9 scores， and SSSUS scores were observed between NSSI behavior group and non-NSSI group （χ²/t=62.889， 71.120， 94.365， -41.464， P<0.01）.Adolesents with NSSI showed positive correlations between GAD-7 scores and both ASHS and PHQ-9 scores （r=0.158， 0.166， P<0.01）. PHQ-9 scores were positively correlated with ASHS scores （r=0.364， P<0.01）， but negatively correlated with SSSUS scores （r=-0.290， P<0.01）. SSSUS scores were negatively correlated with ASHS scores （r=-0.247， P<0.01）. Depression partially mediated the relationship between anxiety and NSSI behavior， with an effect size of 0.544 （95% CI： 0.162~0.944）， accounting for 35.79% of the total effect. Social support moderated the relationship between depression and NSSI bahavior， with an effect value of -0.082 （95% CI： -0.135~-0.029）. ConclusionAnxiety not only directly influences NSSI bahavior among adolescents， also indirectly exacerbates it through depression， while social support mitigates the impact of depression on NSSI behavior. ［Funded by Youth Project of National Natural Science Foundation of China （number， 82401812）； Project of Health Commission of Sichuan Province （number， 24LCYJPT18）］

With the development of science and technology worldwide, the blooming of artificial intelligence (AI) and big data has brought new opportunities and challenges to the promotion of the research capacity of professional master's students in oncology. The construction of the new medical education in China aims to cultivate high-level medical talents with comprehensive multidisciplinary skills and innovative abilities to flexibly solve complex problems at the frontier of medicine. In this context, professional master's students in oncology, who are facing problems such as low scientific research output and uneven quality and needing improving scientific research literacy, have been required to develop into compound talents with both clinical and research prowess. To cultivate and promote the research capacity of professional master's students in oncology, the key steps include accelerating the construction of AI education and databases, highlighting the cultivation of their scientific research capacity, implementing and fostering the cultivation of innovative ability and scientific research thinking, piloting joint cultivation models by engineering universities and medical universities, emphasizing the construction of the curriculum and teacher team for oncology, piloting the multidisciplinary mode and COME mode, and establishing a multidisciplinary cooperation network.

Objective To develop a rehabilitation exercise program for the patients with osteoporotic vertebral compression fractures.Methods An online search was performed across both Chinese and English databases and websites to retrieve literature on rehabilitation exercises and related therapeutic measures for patients with osteoporotic vertebral compression fractures.Two researchers independently screened the retrieved literature,evaluated the quality,and extracted relevant evidence.Semi-structured interviews were conducted among 15 patients at various rehabilitation phases about the requirements of rehabilitation.A preliminary exercise program was developed and verified for the validity and feasibility using Delphi method.Results A rehabilitation exercise program was formulated.The program included five periods of preoperative period,bedridden period after surgery,ambulation period(1 week after surgery),weeks 2-8 after surgery and weeks 9-12 after surgery covering six domains of exercise type,exercise items,exercise duration,exercise frequency,exercise intensity and exercise safety.The response rate and effective rate over the two rounds of expert consultation were both 100.00%,with an authority coefficient of 0.94.The Kendall's W coefficients for secondary indicators in the two rounds of expert consultation were 0.184 and 0.334,respectively(both P<0.001).Conclusion The exercise program developed in this study for the patients with osteoporotic vertebral compression fractures is scientifically reliable and reasonable.The two features of continuity and staged characteristics in rehabilitation process are fully considered,thereby it offers a guidance for clinical healthcare professionals as well as the patients in development of practical and effective rehabilitation exercise plans.

Objective To develop a rehabilitation exercise program for the patients with osteoporotic vertebral compression fractures.Methods An online search was performed across both Chinese and English databases and websites to retrieve literature on rehabilitation exercises and related therapeutic measures for patients with osteoporotic vertebral compression fractures.Two researchers independently screened the retrieved literature,evaluated the quality,and extracted relevant evidence.Semi-structured interviews were conducted among 15 patients at various rehabilitation phases about the requirements of rehabilitation.A preliminary exercise program was developed and verified for the validity and feasibility using Delphi method.Results A rehabilitation exercise program was formulated.The program included five periods of preoperative period,bedridden period after surgery,ambulation period(1 week after surgery),weeks 2-8 after surgery and weeks 9-12 after surgery covering six domains of exercise type,exercise items,exercise duration,exercise frequency,exercise intensity and exercise safety.The response rate and effective rate over the two rounds of expert consultation were both 100.00%,with an authority coefficient of 0.94.The Kendall's W coefficients for secondary indicators in the two rounds of expert consultation were 0.184 and 0.334,respectively(both P<0.001).Conclusion The exercise program developed in this study for the patients with osteoporotic vertebral compression fractures is scientifically reliable and reasonable.The two features of continuity and staged characteristics in rehabilitation process are fully considered,thereby it offers a guidance for clinical healthcare professionals as well as the patients in development of practical and effective rehabilitation exercise plans.

With the development of science and technology worldwide, the blooming of artificial intelligence (AI) and big data has brought new opportunities and challenges to the promotion of the research capacity of professional master's students in oncology. The construction of the new medical education in China aims to cultivate high-level medical talents with comprehensive multidisciplinary skills and innovative abilities to flexibly solve complex problems at the frontier of medicine. In this context, professional master's students in oncology, who are facing problems such as low scientific research output and uneven quality and needing improving scientific research literacy, have been required to develop into compound talents with both clinical and research prowess. To cultivate and promote the research capacity of professional master's students in oncology, the key steps include accelerating the construction of AI education and databases, highlighting the cultivation of their scientific research capacity, implementing and fostering the cultivation of innovative ability and scientific research thinking, piloting joint cultivation models by engineering universities and medical universities, emphasizing the construction of the curriculum and teacher team for oncology, piloting the multidisciplinary mode and COME mode, and establishing a multidisciplinary cooperation network.

Objective Clinical medical record data associated with hepatitis B-related acute-on-chronic liver failure(HBV-ACLF)generally have small sample sizes and a class imbalance.However,most machine learning models are designed based on balanced data and lack interpretability.This study aimed to propose a traditional Chinese medicine(TCM)diagnostic model for HBV-ACLF based on the TCM syndrome differentiation and treatment theory,which is clini-cally interpretable and highly accurate. Methods We collected medical records from 261 patients diagnosed with HBV-ACLF,includ-ing three syndromes:Yang jaundice(214 cases),Yang-Yin jaundice(41 cases),and Yin jaun-dice(6 cases).To avoid overfitting of the machine learning model,we excluded the cases of Yin jaundice.After data standardization and cleaning,we obtained 255 relevant medical records of Yang jaundice and Yang-Yin jaundice.To address the class imbalance issue,we employed the oversampling method and five machine learning methods,including logistic regression(LR),support vector machine(SVM),decision tree(DT),random forest(RF),and extreme gradient boosting(XGBoost)to construct the syndrome diagnosis models.This study used precision,F1 score,the area under the receiver operating characteristic(ROC)curve(AUC),and accuracy as model evaluation metrics.The model with the best classification per-formance was selected to extract the diagnostic rule,and its clinical significance was thor-oughly analyzed.Furthermore,we proposed a novel multiple-round stable rule extraction(MRSRE)method to obtain a stable rule set of features that can exhibit the model's clinical in-terpretability. Results The precision of the five machine learning models built using oversampled balanced data exceeded 0.90.Among these models,the accuracy of RF classification of syndrome types was 0.92,and the mean F1 scores of the two categories of Yang jaundice and Yang-Yin jaun-dice were 0.93 and 0.94,respectively.Additionally,the AUC was 0.98.The extraction rules of the RF syndrome differentiation model based on the MRSRE method revealed that the com-mon features of Yang jaundice and Yang-Yin jaundice were wiry pulse,yellowing of the urine,skin,and eyes,normal tongue body,healthy sublingual vessel,nausea,oil loathing,and poor appetite.The main features of Yang jaundice were a red tongue body and thickened sublin-gual vessels,whereas those of Yang-Yin jaundice were a dark tongue body,pale white tongue body,white tongue coating,lack of strength,slippery pulse,light red tongue body,slimy tongue coating,and abdominal distension.This is aligned with the classifications made by TCM experts based on TCM syndrome differentiation and treatment theory. Conclusion Our model can be utilized for differentiating HBV-ACLF syndromes,which has the potential to be applied to generate other clinically interpretable models with high accura-cy on clinical data characterized by small sample sizes and a class imbalance.

Objectives:To analyze the functional movement characteristics after brace treatment for patients with adolescent idiopathic scoliosis(AIS),and to develop and validate a nomogram model to predict the risk of poor outcome.Methods:AIS patients who were treated with braces at our institution from March 2020 to March 2022 were collected as a training set,and were tested for functional movement before treatment,at initial follow-up and after treatment.The same criteria were used to collect AIS patients who underwent brace treatment in our hospital from April 2022 to August 2022 as the validation set.On the basis of whether the degree of scoliosis progression was＞5° after 1 year of treatment,the patients in the training set were divided into stable(≤5°)and progressive(＞5°)groups.Comparison of data was made between groups.Spearman corre-lation analysis was used to analyze the correlation between variables.Logistic regression model was used to screen the risk factors for poor outcomes.R software was applied to develop a nomogram prediction model.Area under curve(AUC)of receiver operating characteristic(ROC)curve and calibration curve were applied to evaluate the discrimination and accuracy of the model.Internal validation was performed with the model predicted risk values before and after training set Bootstrap self-sampling as the test variables and the actual prognosis of patients as the state variable;External validation of the model was performed after randomization of the validation set Bootstrap self-sampling.Results:A total of 102 patients with AIS were included in the training set.There were 73 cases in the stable group and 29 cases in the progressive group(range of degrees of progression:8° to 27°).The median follow-up time was 15.4 months.Both thoracic and lumbar Cobb angles decreased significantly after treatment(P＜0.05).Rotational stability and push-ups were higher at initial follow-up than before treatment,and scores on bow-step squat,hurdle striding,rotational stability,and push-ups improved after treatment(P＜0.05).There was no significant correlation between functional movement characteristics and Cobb angle(P＞0.05).Pre-treatment Cobb angle≥35°,Risser's sign≥3°,apex rotation≥degree Ⅲ,and spinal length gain≥20mm/year were independent risk factors for scoliosis progression.Lumbar spine bone density≥0.8g/cm2 and spinal flexibility≥50%were protective factors.The total value of the risk of scoliosis progression after brace treatment predicted by the nomogram model was 0.93.The AUCs before and after training set self-sampling were 0.928(95%CI:0.858-0.998)and 0.926(95%CI:0.854-0.997),respectively.The validation set included 37 patients.The external validation AUC for validation set was 0.891(95%CI:0.857-0.998).The calibration curves all showed good degree of fitting.Conclusions:Patients with AIS have poor movement patterns due to spinal restrictions.Brace treatment improves trunk stability and rotational stability,which has good corrective effects on the movement pattern.AIS patients with Cobb angle≥35°,Risser's sign≥3°,apex rotation≥degree Ⅲ,spinal length gain≥20mm/year,lumbar spine bone mineral density＜0.8g/cm2,and spinal flexibility＜50%before treatment who underwent bracing are prone to scoliosis progression.Timely warning shall be made based on the nomogram model and postural correction needs to be supplemented at appropriate time to improve the prognosis of AIS brace treatment.

Using the liquid chromatography-tandem mass spectrometry (LC-MS/MS) to determine the plasma level of Lyso-GL3 in patients with Fabry disease and to analyze the clinical application of the method.