This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Cancer stands as a significant global public health challenge,and cancer screening serves as a pivotal strategy for reducing its mortality.Presently,only a limited number of cancer types have appropriate screening methods available.Traditional single-cancer screen-ing approaches are fraught with limitations,including invasiveness,low accuracy,and poor patient compliance.Multi-cancer early detection(MCED)leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA,cell-free RNA,proteins,and metabolites in blood and other bodily fluids.This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage,showcasing immense potential for improving existing can-cer screening strategies.This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED,biomarker selection and detection technologies,the criteria for cancer type selection,research design and clinical utility evaluation,as well as implementation path-ways.The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED,thereby facilitating the continuous optimization of cancer screening strategies.

Objective To explore the expression pattern and molecular function of ubiquitin-like containing PHD and RING finger domains 1(UHRF1)gene in soft tissue sarcoma(STS),as well as its correlation with clinical characteristics and prognosis of STS.Methods RNA data and related clinical data of 263 STS tissues were obtained from Cancer Genome Atlas(TCGA).Wilcoxon rank-sum test was used to analyze correlation between two groups of data;Spearman correlation coefficient analyzed the top 35 co-expressed genes positively and negatively correlated with UHRF1 expression in STS database,ggplot2 statistical package displayed co-expressed gene heatmap,Pearson correlation coefficient showed correlation between UHRF1 expression and expression of the top 10 genes in the heatmap;different UHRF1 gene expression groups in STS were analyzed using DESeq2 package,ggplot2 package was used to draw volcano plots,gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyzed differentially expressed genes(DEGs)and protein functions,ggplot2 package for visualization,and cluster Profiler package for statistical analysis;STRING web was used to establish PPI network of DEGs,and the MCC algorithm in CytoHubba of Cytoscape was used to analyze hub genes.Results In STS,UHRF1 gene was significantly correlated with its histological type(liposarcoma 22.2％,synovial sarcoma 3.8％,leiomyosarcoma 40.7％,malignant peripheral nerve sheath tumor 3.8％,myxofibrosarcoma 9.6％,pleomorphic sarcoma 19.9％,P=0.001),tumor necrosis(none 38.8％,focal necrosis 20.8％,moderate necrosis 33.8％,extensive necrosis 6.6％,P=0.010),and tumor metastasis(no metastasis 67％,metastasis 33％,P＜0.001).In different clinical subgroups(age,gender,histological type,residual tumor,tumor necrosis,tumor depth,margin status,tumor multifocality,radiotherapy),high expression of UHRF1 led to poor prognosis of overall survival(OS),disease-specific survival(DSS),and progression-free interval(PFI);Three prognostic factors above were simultaneously shortened in the following five subgroups:namely residual tumor R0 and R1,tumor necrosis extensive,focal and moderate,tumor depth deep,positive margin status,tumor without multifocality.Analysis of the top 10 co-expressed genes associated with UHRF1 expression revealed that the associated positive genes were PAGE5,LINC01425,LCEP3,SERPINB7,AC074031.1,LCE3A,LCE2A,PAGE2B,MYF5,and AC037486.1(P＜0.05);the associated negative genes were CDH19,CSN1S1,TAC3,AC103563.7,SAA1,CHST8,PRLHR,MIR202HG,IGHV1-24,and ART4(P＜0.05).A total of 3 029 DEGs of UHRF1 in STS were obtained with a threshold of|log2 fold-change(FC)|＞1.0 and adjusted P value＜0.05,in which 1 228 genes were up-regulated and 1 801 genes were down-regulated;GO enrichment analyed primary biological processes(BP),original cellular components(CC),and original molecular functions(MF),and KEGG enrichment analyed signaling pathways.A total of 343 DEGs including 133 up-regulated genes and 210 down-regulated genes,were obtained with a threshold of|log2 fold-change(FC)|＞2.0 and adjusted P value＜0.05.The top 10 hub genes were analyzed.The top 3 hub genes were GCG,SST and SHH,respectively.Conclusion UHRF1 is significantly correlated with histological type,tumor necrosis,metastasis,OS,DSS,and PFI events in STS.In co expressed genes model and molecular functions of related positive and negative genes involved in multiple biological processes;The network of differentially expressed genes and protein product interactions involved in mechanisms of occurrence and development of the disease,and provided new ideas for in-depth researches on STS.

Objective To establish an animal model of hand,foot,and mouth disease(HFMD)in Syrian hamsters coinfected with coxsackievirus A6(CVA6)and coxsackievirus B1(CVB1).Methods 42 Syrian hamsters were divided into a CVA6 infection group,CVB1 infection group,CVA6 and CVB1 coinfection group and control group.A HFMD model was established by nasal instillation of virus solution and phosphate-buffered saline.Clinical and physiological indicators and detoxification status were monitored and recorded for 15 d,and animals were selected on day 7(D7)after infection for histopathology and viral antigen and nucleic acid testing.Results Hamsters in the single-infection and coinfection groups showed clinical symptoms similar to human HFMD.White blood cell,neutrophil,and lymphocyte result were characteristic of viral infection.Both viral nucleic acids were detected in throat swabs,feces,blood,and tissues and both viruses were isolated from fecal samples.Pathological damage and positive co-localization of CVA6 and CVB1 viral antigen proteins and nucleic acids were found in brain and other tissues.Conclusions Nasal instillation of a CVA6 and CVB1 mixture can successfully coinfect Syrian hamsters,replicate herpes infection similar to human HFMD,and cause pathological viral myocarditis and encephalitis damage.The result showed that the coinfection group was more seriously affected than the single-infection group,with worse clinical symptoms,increased viral replication,and obvious tissue pathological damage.This study provides a reference for further basic and clinical research into human enterovirus coinfection.

With the rapid development of artificial intelligence(AI),how to digitize the teaching of Medical Immunology is a new challenge posed by the times and education.This study is based on the advanced teaching model of Medical Immunology,which includes lectures-PAD class-flipped classrooms-expert lecture.By introducing knowledge mapping and AI teaching assistant into the entire learning process,the students not only deepen their understanding of the knowledge system of Medical Immunology,but also ex-ercise their ability to apply immunological knowledge to solve practical clinical problems,enhance their self-learning ability,expres-sion ability,communication ability,on-site performance ability,and cultivate a spirit of unity,cooperation,and exploration.The practice of empowering Medical Immunology teaching with digital intelligence achieves the integration of theory and application,the linkage between in class and out of class teaching,the connection between commonalities and individualities,and the union of abili-ties and qualities in Medical Immunology teaching.It also provides practical basis for exploring the implementation path of digital intel-ligence empowerment in Medical Immunology teaching.

With the rapid advancement of artificial intelligence (AI) technology, particularly breakthroughs in large models, AI applications in healthcare are becoming increasingly widespread.Ophthalmology, as a critical branch of medicine, has emerged as a clinical specialty with comprehensive AI research and applications, especially in the AI-driven analysis of ophthalmic imaging.Currently, AI in ophthalmology is undergoing profound transformation driven by large model technology.AI large models, with their robust data comprehension and multimodal interaction capabilities, offer new possibilities for the diagnosis, treatment, and health education of ophthalmic diseases, powerfully propelling the evolution of current AI paradigms in ophthalmology.This article explores the novel opportunities brought by the extensive application of AI large models in ophthalmic research and practice, and provides recommendations for ophthalmologists and insights for industry development.

In recent years, generative artificial intelligence (AI) technologies have achieved remarkable progress in the early screening, risk prediction, disease progression assessment, and clinical trial design of glaucoma.Using advanced algorithms, such as generative adversarial networks, variational autoencoders, and diffusion models, researchers have synthesized high-quality structural images of the optic disc, macular region, and retinal nerve fiber layer, which effectively alleviates the limitations of scarce clinical imaging data and label imbalance.These methods have substantially improved the accuracy and generalization of deep learning models in visual field defect prediction, structure-function mapping, and longitudinal disease progression simulation.Meanwhile, multimodal generative approaches that integrate imaging data, visual field tests, and clinical features have facilitated individualized prediction of glaucoma progression.In addition, large language models have shown preliminary potential in ophthalmic image interpretation, clinical text information extraction, and decision support, providing new insights into intelligent ophthalmic diagnosis and treatment.However, the clinical implementation of generative AI in glaucoma faces challenges.The pathological authenticity and cross-device consistency of generated images require further validation, which may affect the reliability of early glaucoma detection.The heterogeneous characteristics of different glaucoma subtypes, such as open-angle and angle-closure glaucoma, also limit the generalization of synthetic data.Moreover, issues related to model interpretability (" black-box" nature), artifact generation, data privacy, and ethical governance remain key barriers to clinical translation.In the future, it is expected that establishing large-scale training frameworks that incorporate multicenter, multimodal, and multiethnic datasets will enhance model robustness and clinical applicability.Furthermore, generative AI may contribute to remote ophthalmic care and personalized precision therapy by enhancing low-quality image, reconstructing missing data, and simulating dynamic disease courses.This article reviews the current applications, core technologies, and challenges of generative AI in glaucoma diagnosis and management, and discusses its future directions and translational potential in clinical ophthalmology.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Objective To establish an animal model of hand,foot,and mouth disease(HFMD)in Syrian hamsters coinfected with coxsackievirus A6(CVA6)and coxsackievirus B1(CVB1).Methods 42 Syrian hamsters were divided into a CVA6 infection group,CVB1 infection group,CVA6 and CVB1 coinfection group and control group.A HFMD model was established by nasal instillation of virus solution and phosphate-buffered saline.Clinical and physiological indicators and detoxification status were monitored and recorded for 15 d,and animals were selected on day 7(D7)after infection for histopathology and viral antigen and nucleic acid testing.Results Hamsters in the single-infection and coinfection groups showed clinical symptoms similar to human HFMD.White blood cell,neutrophil,and lymphocyte result were characteristic of viral infection.Both viral nucleic acids were detected in throat swabs,feces,blood,and tissues and both viruses were isolated from fecal samples.Pathological damage and positive co-localization of CVA6 and CVB1 viral antigen proteins and nucleic acids were found in brain and other tissues.Conclusions Nasal instillation of a CVA6 and CVB1 mixture can successfully coinfect Syrian hamsters,replicate herpes infection similar to human HFMD,and cause pathological viral myocarditis and encephalitis damage.The result showed that the coinfection group was more seriously affected than the single-infection group,with worse clinical symptoms,increased viral replication,and obvious tissue pathological damage.This study provides a reference for further basic and clinical research into human enterovirus coinfection.

Background and purpose:Melanoma is a highly invasive malignant tumor originating from melanocytes,which poses a great threat to human life and health around the world,and its morbidity and mortality have been rising continuously in recent years.Telomerase and autophagy play crucial roles in cell proliferation,survival and stress response.Telomerase maintains the replication ability of cells by prolonging telomeres at the ends of chromosomes,and autophagy,as a self-degradation mechanism of cells,can not only help cells remove damaged components to promote survival,but also induce cell death under certain conditions.In the tumor environment,they are often abnormally activated or out of balance,and participate in the occurrence and development of many cancers,including melanoma.This study investigated the roles of telomerase and autophagy in melanoma progression and evaluated the potential synergistic therapeutic effects of combined application of telomerase inhibitor BIBR1532 and autophagy inhibitor chloroquine(CQ)in melanoma treatment.Methods:Malignant melanoma cells A375 were treated with telomerase inhibitor BIBR1532.The cell viability was assessed using the cell counting kit-8(CCK-8)assay,and the cell apoptosis was detected using the Annexin Ⅴ/propidium iodide(PI)double staining method.Additionally,the expressions of autophagy-related proteins LC3-Ⅱand p62 were detected by Western blot,and the changes in autophagy flux were observed using dual-tagged adenovirus transfection technology.Based on these studies,BIBR1532 and the autophagy inhibitor CQ were further applied in combination to analyze cell proliferation,apoptotic rate,changes in mitochondrial membrane potential,and cell cycle distribution,and the cloning formation experiment was used to verify the cell's proliferative capacity,thereby comprehensively evaluating the efficacy of this combined treatment strategy.Results:Telomerase inhibitor BIBR1532 at a concentration of 50 μmol/L significantly inhibited the growth of malignant melanoma cells A375 and induced apoptosis.At the same concentration,BIBR1532 upregulated the expression of the autophagy-related protein LC3-Ⅱ in A375 cells,while downregulating the expression of p62 protein.By transducing A375 cells with a dual-tagged adenovirus,it was observed that autophagy flux was significantly enhanced after treatment with BIBR1532.Furthermore,the combined application of BIBR1532(50 μmol/L)and the autophagy inhibitor CQ(20 μmol/L)significantly promoted the death of A375 cells,induced apoptosis and destruction of mitochondrial membrane potential,caused cell cycle arrest at the G2/M phase,and significantly inhibited the cell's clonogenic ability.Conclusion:Telomerase inhibitor BIBR1532 not only inhibits the proliferation of malignant melanoma cells but also activates the autophagy process in these cells,and inhibition of the autophagy response by autophagy inhibitor CQ can enhance the sensitivity of malignant melanoma cells to telomerase inhibitor BIBR1532.