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 establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

Objective To investigate the association between school bullying and comorbidity of overweight/obesity and depressive symptoms in middle school students, and to provide a basis for formulating intervention strategies for the prevention and control of common diseases and comorbidities among students. Methods In September 2023, a stratified cluster random sampling method was employed to select junior high school, high school, and vocational high school students in 103 districts and counties across 17 cities (prefectures) in Hubei Province. A questionnaire survey was conducted on these students regarding school bullying and depressive symptoms, and physical measurements of height and weight were taken. The association between school bullying and comorbidity of overweight/obesity and depressive symptoms was analyzed using a logistic regression model. Results A total of 99 921 middle school students aged 11-19 years old were included in the study. The detection rate of overweight/obesity was 29.39%, the detection rate of depressive symptoms was 31.15%, and the detection rate of comorbidity of overweight/obesity and depressive symptoms was 9.15%. Among all students, 24.12% reported experiencing school bullying. Multivariate logistic regression analysis showed that experiencing school bullying was positively associated with the comorbidity of overweight/obesity and depressive symptoms among middle school students (OR = 2.692, 95% CI: 2.571-2.817, P < 0.001). Stratified analysis results showed that both male and female students who experienced school bullying were more likely to have comorbidity of overweight/obesity and depressive symptoms (OR values were 2.756 for males and 2.594 for females; P values were both < 0.001). Students in all educational stages who experienced school bullying had an increased risk of comorbidity of overweight/obesity and depressive symptoms (OR values were 2.739 for junior high, 2.676 for senior high, and 2.378 for vocational high; P values were all < 0.001). Conclusion The comorbidity of overweight/obesity and depressive symptoms among middle school students is widespread, and there is a significant association between school bullying and comorbidity of overweight/obesity and depressive symptoms. It is necessary to strengthen the prevention and control of school bullying to promote the healthy physical and mental development of adolescents.

OBJECTIVE To investigate the antidepressant effect and underlying mechanism of total triterpenes from Poriae Cutis （PCTT）. METHODS UPLC-Q-TOF-MS technology was adopted to analyze the chemical constituents of PCTT. Network pharmacology was applied to screen the antidepressant active ingredients， key targets and signaling pathways of PCTT， and molecular docking was performed to verify the binding capacity between potential active ingredients and core targets. In animal experiment， mice were intragastrically administered PCTT at doses of 80， 160 and 320 mg/kg for 14 consecutive days. Lipopolysaccharide was used to establish an acute depression mouse model. Subsequently， behavioral assays were conducted. The levels of serum inflammatory factors， hippocampal neurotransmitters and brain-derived neurotrophic factor （BDNF） were detected. Western blot and qPCR assays were adopted to validate the antidepressant mechanism of PCTT. RESULTS A total of 101 chemical constituents were identified in PCTT. Network pharmacology screened out 10 potential active ingredients （including poriacosone B， poriacosone A， pachymic acid， etc.）， six core targets [including tumor necrosis factor （TNF）， peroxisome proliferator-activated receptor， caspase-3， etc.]， as well as multiple signaling pathways including TNF and interleukin-17 （IL-17）. All 10 potential active ingredients exhibited strong binding affinity to the six core targets. Animal experimental results demonstrated that 320 mg/kg PCTT markedly increased the movement distance and movement speed of depression model mice （P＜0.05）， and shortened immobility time in tail suspension test and forced swimming test （P＜0.05）. PCTT reduced serum levels of IL-6， IL-1β and TNF-α， decreased hippocampal glutamate level； it also downregulated the relative mRNA expression of TNF-α， tumor necrosis factor receptor-2 （TNFR2）， phosphoinositide 3-kinase （PI3K） and protein kinase B （AKT）， as well as TNFR2 protein expression and the ratios of phosphorylated-PI3K/PI3K，phosphorylated-AKT/AKT in the prefrontal cortex. Meanwhile， PCTT elevated the levels of 5- hydroxytryptamine， dopamine and BDNF in the hippocampus. CONCLUSIONS PCTT exerts antidepressant effects possibly by regulating the TNF-α/PI3K/AKT signaling pathway to downregulate the expression of pro-inflammatory factors， thereby modulating the release of neurotransmitters and BDNF.

Plants of the Isodon genus are an important source of terpenoids， with their constituents exhibiting rich structural diversity and remarkable biological activities （such as anticancer， antimicrobial， and anti-inflammatory properties）， demonstrating significant potential in the field of immunomodulation. This review summarizes recent advances in the immunomodulatory mechanisms， development and application of terpenoid compounds from the Isodon genus. It has been found that these compounds can modulate key inflammatory signaling pathways， such as nuclear factor-kappa B （NF-κB） and mitogen-activated protein kinases （MAPKs）， thereby blocking the cascade amplification of inflammatory factors， alleviating chronic inflammatory responses， and correcting immune dysregulation. Additionally， they can influence the polarization direction of macrophages and dynamically regulate the balance among different functional subsets of T cells， restoring immune homeostasis. Their clinical translation faces multiple challenges， including poor druggability， a lack of systematic safety data， the absence of precise pharmacodynamic biomarkers， complexities in clinical trial design， and unclear industrialization pathways.

OBJECTIVE: This study examines the sequential mediating roles of body pain and self-reported health in the association between sleep duration and self-reported life satisfaction among elderly Chinese adults. METHODS: Data from the fifth wave of the China Health and Retirement Longitudinal Survey (CHARLS) were used to analyse the relationships between sleep duration and body pain, self-reported health, and life satisfaction through logistic regression and Restricted Cubic Spline (RCS) analyses. The sequential mediation effects of body pain and self-reported health status were examined via chain mediation analysis. RESULTS: Logistic regression analysis showed that sleeping fewer than 6 hours or 6-7 hours was linked to higher risks of body pain, poor health, and dissatisfaction with life compared to sleeping 7-8 hours (all P < 0.05). Additionally, those sleeping more than 9 hours also had increased risks of poor health and dissatisfaction with life compared to those sleeping 7-8 hours (all P < 0.05). Chain mediation analysis showed that body pain and self-reported health status sequentially mediated 46.15% of the association between sleep duration and life satisfaction. CONCLUSION Body pain and self-reported health may shape the relationship between sleep duration and life satisfaction in elderly Chinese adults.
Humans ; Male ; Female ; Aged ; Personal Satisfaction ; Sleep ; Health Status ; Self Report ; China ; Middle Aged ; Longitudinal Studies ; Pain/psychology* ; Sleep Duration