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.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Soy is a vital source of plant carbohydrates.However,it poses significant allergenic risks,particularly to young children and animals.Among the various proteins in soy,β-conglycinin,which con-stitutes approximately 30％of total soy carbohydrates,is a primary allergen.Undigested β-conglycinin can lead to intestinal damage by inhibiting cell growth,disrupting the cytoskeleton,and inducing apopto-sis.It can also enter the lymphatic and circulatory systems,triggering allergic reactions.Conventional ELISA methods for detecting β-conglycinin rely on polyclonal or monoclonal antibodies,which are limited by their large molecular weight,difficulty in accessing the protein core,and sensitivity to acidic and bas-ic conditions.To address these limitations,this study aimed to develop nanobodies(Nbs)against β-con-glycinin.Nbs,derived from the variable regions of heavy-chain antibodies found in camelids,have a mo-lecular weight approximately one-tenth that of conventional antibodies.They offer advantages such as small size,stable structure,high specificity,and strong affinity.A female alpacas was immunized five times using β-conglycinin,which showed a heavy chain antibody potency of 1∶16 000 by ELISA.Pe-ripheral blood lymphocytes were subsequently isolated and total RNA was extracted.The variable region of the heavy-chain antibody was amplified via PCR,and recombinant plasmids were constructed and transformed into the E.coli competency strain ER2738.The resulting library contained about 3.5×108 CFU/mL,which increased to 1.15×1012 PFU/mL after phage rescue,with a 100％Nbs gene insertion rate,indicating high diversity.Its Nbs phage output was significantly enriched by four rounds of solid-phase elution with an enrichment rate of 155.9.Four rounds of solid-phase panning yielded 35 positive clones,all of which shared the same amino acid sequence upon sequencing.The selected Nb was ex-pressed in a prokaryotic system,and its binding ability to β-conglycinin was confirmed using Western blotting and ELISA.The results demonstrated excellent specificity and affinity.This research lays the groundwork for developing a rapid and efficient detection method for β-conglycinin using Nbs,potentially enhancing food safety and allergen management.

This paper summarizes the progress of theoretical research and practice of One Health in China,and discusses the paradigm of One Health governance to improve the prevention and control of infectious diseases in China and the world,and provide an example for the improvement of the public health system.In particular,China has long history to apply the concept of One Health in the national schistosomiasis control programmes and patriotic health campaigns,which were not only focusing on human health,but also emphasizing the sustainable development of animal health and ecological environment.At the same time,the application of tools such as system dynamics model,eDNA technology,One Health economic assessment and global One Health index(GOHI)in the field of disease control and environmental health provides technical support for the concept of One Health.Despite the challenges of practical application of these tools,the One Health concept will play a greater role in providing sustainable solutions for human-animal-environmental health by strengthening interdisciplinary collaboration,improving standardization protocols and promoting inter-national cooperation.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Soy is a vital source of plant carbohydrates.However,it poses significant allergenic risks,particularly to young children and animals.Among the various proteins in soy,β-conglycinin,which con-stitutes approximately 30％of total soy carbohydrates,is a primary allergen.Undigested β-conglycinin can lead to intestinal damage by inhibiting cell growth,disrupting the cytoskeleton,and inducing apopto-sis.It can also enter the lymphatic and circulatory systems,triggering allergic reactions.Conventional ELISA methods for detecting β-conglycinin rely on polyclonal or monoclonal antibodies,which are limited by their large molecular weight,difficulty in accessing the protein core,and sensitivity to acidic and bas-ic conditions.To address these limitations,this study aimed to develop nanobodies(Nbs)against β-con-glycinin.Nbs,derived from the variable regions of heavy-chain antibodies found in camelids,have a mo-lecular weight approximately one-tenth that of conventional antibodies.They offer advantages such as small size,stable structure,high specificity,and strong affinity.A female alpacas was immunized five times using β-conglycinin,which showed a heavy chain antibody potency of 1∶16 000 by ELISA.Pe-ripheral blood lymphocytes were subsequently isolated and total RNA was extracted.The variable region of the heavy-chain antibody was amplified via PCR,and recombinant plasmids were constructed and transformed into the E.coli competency strain ER2738.The resulting library contained about 3.5×108 CFU/mL,which increased to 1.15×1012 PFU/mL after phage rescue,with a 100％Nbs gene insertion rate,indicating high diversity.Its Nbs phage output was significantly enriched by four rounds of solid-phase elution with an enrichment rate of 155.9.Four rounds of solid-phase panning yielded 35 positive clones,all of which shared the same amino acid sequence upon sequencing.The selected Nb was ex-pressed in a prokaryotic system,and its binding ability to β-conglycinin was confirmed using Western blotting and ELISA.The results demonstrated excellent specificity and affinity.This research lays the groundwork for developing a rapid and efficient detection method for β-conglycinin using Nbs,potentially enhancing food safety and allergen management.

This study aimed to investigate the therapeutic effect of Yindan Pinggan capsules (YDPG) on intrahepatic cholestasis (IHC) through animal experiments, while utilizing network pharmacology and molecular docking techniques to explore its potential mechanisms. Initially, the therapeutic effect of YDPG on an α-naphthylisothiocyanate (ANIT)-induced IHC mouse model was assessed through liver function tests, routine blood tests, and liver pathology analysis. Subsequently, network pharmacology tools were employed to predict the active components, core targets, and signaling pathways of YDPG. Molecular docking technology was employed to verify the binding activity of key active components of YDPG with core targets, followed by protein immunoblotting to validate the key targets. Results showed that YDPG significantly improved liver function abnormalities and hepatocyte damage in IHC mice. Network pharmacology analysis revealed that 94 active components in YDPG were associated with 396 targets for the treatment of IHC, and were significantly enriched in pathways such as the phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT) signaling pathway, lipid metabolism, and bile secretion. Molecular docking results showed good binding activity between key active components of YDPG and core targets of the PI3K-AKT signaling pathway. Further protein immunoblotting confirmed that YDPG could reduce the phosphorylation levels of PI3K and AKT proteins, core targets of the PI3K-AKT pathway in liver tissue. These findings suggest that YDPG may alleviate biological processes such as oxidative stress and inflammatory responses by regulating the PI3K-AKT signaling pathway, thereby improving liver damage in IHC mice and exerting a therapeutic effect on IHC. This experiment has been approved by the Animal Experiment Ethics Committee of Jinan University (ethical approval number: IACUC-20241011-09).

Objective To develop a personalized recommendation strategy for tranexamic acid administration during the perioperative period of orthopedic surgery based on machine learning,aiming to reduce perioperative bleeding and related complications and improving clinical outcomes.Methods A total of 11 727 patients undergoing orthopedic surgery from the INSPIRE database were subjected in this study.Missing data were handled using multiple imputation methods,and relevant feature variables were screened using Boruta analysis.We constructed various machine learning models,including Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),eXtreme Gradient Boosting(XGBoost),K-Nearest Neighbors(KNN),Neural Network(NNET),Naive Bayes(NB),and Random Forest(RF),to evaluate their performance in predicting intraoperative bleeding and prolonged postoperative length of hospital stay.The optimal model was then selected and further integrated using a weighted ensemble,aiming to achieve the best prognosis by recommending usage strategies for tranexamic acid.The predictive performance of the constructed model was then verified against the testing set,and compared with the physician decision-making to complete the evaluation.Results In predicting intraoperative bleeding,the RF model achieved an area under the receiver operating characteristic curve(AUC)of 0.73,which was significantly better than other models.In predicting the prolonged postoperative length of hospital stay,the XGBoost model performed the best,with an AUC value of 0.84.Based on the above best-performing models,an ensemble strategy was implemented.The patients who followed the recommended strategy had reduced intraoperative bleeding and shorter postoperative length of hospital stay.Conclusion The use of tranexamic acid is associated with intraoperative bleeding and postoperative length of hospital stay.Personalized decision-making recommendation based on our constructed model can effectively improve the outcomes of the patients undergoing orthopedic surgery.