ObjectiveTo investigate whether photoreceptor-specific knockout of lanosterol synthase （Lss） induces age-related retinal degeneration and to elucidate the underlying molecular mechanisms. MethodsPhotoreceptor-specific Lss knockout mice （Lss^flox/flox； Rho-Cre， CKO） models were established. Retinal structure and function were assessed at 1， 4， and 8 months of age using fundus photography， optical coherence tomography （OCT）， scotopic electroretinogram （ERG） and hematoxylin and eosin （HE） staining. The mouse photoreceptor cell line 661W served as an in vitro model. Lss was knocked down via siRNA， followed by analyses including Seahorse XF mitochondrial stress test， JC-1， MitoSOX Red and DCFH-DA probes to evaluate mitochondrial function and oxidative stress， glycolytic rate assay for glycolysis ability， RT-qPCR for inflammatory factors， γH2AX immunofluorescence for double-strand DNA damage detection， and transcriptome sequencing to identify differentially expressed genes and enriched pathways. ResultsCompared with controls， 1-month-old CKO mice showed no abnormalities. Mild fundus lesions appeared at 4 months. By 8 months， CKO mice exhibited significant thinning of the outer nuclear layer， disorganization of the inner/outer segment structure， and markedly reduced amplitudes of the dark-adapted ERG a- and b-waves （P<0.05）. Transcriptome analysis revealed 1 842 differentially expressed genes （826 up-regulated， 1 016 down-regulated）， with Lss being the most significantly downregulated gene； these genes significantly enriched in sterol biosynthesis， oxidative phosphorylation， aerobic electron transport chain， and ATP synthesis （P<0.05）. In 661W cells， knockdown of Lss significantly reduced mitochondrial basal respiration （P=0.006）， ATP production （P=0.015）， maximal respiration （P<0.001）， and spare respiratory capacity （P<0.001）， while basal glycolysis （P=0.005） and compensatory glycolysis （P=0.028） were increased. These changes were accompanied by mitochondrial membrane potential depolarization （P<0.001）， elevated mitochondrial reactive oxygen species （ROS） levels （P<0.001）， and increased total ROS levels （P=0.013）. Additionally， the mRNA expression of inflammatory factors， including Ccl2 （P=0.004）， Ccl5 （P=0.012）， Cxcl1 （P<0.001）， Cxcl5 （P<0.000 1）， Tgfb （P=0.008）， Hgf （P<0.000 1） and Mmp3 （P=0.003） was significantly upregulated. Moreover， γH2AX fluorescence intensity was increased （P=0.002）. ConclusionsPhotoreceptor-specific Lss deficiency induces mitochondrial dysfunction， oxidative stress and cellular inflammation， ultimately leading to age-dependent retinal degeneration. This study provides novel mechanistic insights and potential therapeutic targets for hereditary and age-related retinal degenerative diseases.

Objective:To analyze the clinical characteristics, distribution of Mycoplasma and bacteria, and risk factors associated with long-term urinary tract infection (UTI) in patients after kidney transplantation (KT).Methods:A retrospective case-control study was conducted involving a total of 402 inpatients who underwent KT and were suspected of having UTI from January 1, 2023 to July 31, 2024 at Zhabei Central Hospital in the Jing′an District, Shanghai. Pathogen distribution including Mycoplasma and bacteria, was assessed through cultures of midstream urine samples using specialized medium. The patients were categorized into three groups: the bacterial infection group (67 cases), Mycoplasma infection group (56 cases) and non-UTI group (288 cases). Subsequently, the infection group was further divided into sub-groups according to the time after transplantation. Renal function indexes and urine microalbumin (U-mALB) at the time of infections were measured, and the clinical data of inpatients were collected. Risk factors associated with urinary Mycoplasma and bacterial infections were identified using both univariate comparison methods and multivariate logistic regression analysis.Results:Among the 402 KT recipients, 56 patients were found to have Mycoplasma isolated, resulting in an infection rate of 13.9%. Additionally, Ureaplasma spp. Was identified in 11.4% (46/402) patients. About 16.7% (67/402) patients exhibited with bacteria infection, and the most common pathogens were Escherichia coli (27/402, 6.7%), followed by Klebsiella pneumoniae (10/402, 2.5%) and Enterococcus faecalis (10/402, 2.5%). There was significant difference about the infection rate of Mycoplasma among the different periods after transplantation ( P<0.05): 1-<5 years at 26.8%(11/41), 5-<10 years at 15.8%(18/114), 10-<20 years at 11.6%(22/190), above 20 years at 8.8%(5/57). Monofactorial analysis showed that gender (χ 2=8.21, P=0.004), age (χ 2=3.96, P=0.001), post-transplant duration (χ 2=2.83, P=0.005) and U-mALB level (χ 2=3.06, P=0.002) were associated risk factors for Mycoplasma infection ( P<0.05). For bacterial infections, significant associations were found with gender (χ 2=9.41, P=0.003), concomitant diabetes mellitus (χ 2=4.42, P=0.035), blood urea nitrogen (Z=2.68, P=0.007), creatinine (Z=2.81, P=0.005), cystatin C ( Z=3.87, P=0.001), estimated glomerular filtration rate (Z=3.83, P=0.001) and U-mALB level ( Z=3.33, P=0.001). Multivariate logistic regression analysis showed that female ( OR=2.81, 95% CI 1.49-5.31, P=0.001) and younger age( OR=0.95, 95% CI 0.92-0.98, P=0.001) were independent risk factors for Mycoplasma infections ( P<0.05). Female( OR=2.98, 95% CI 1.58-5.64, P=0.001) and concurrent diabetes mellitus ( OR=2.06, 95% CI 1.12-3.76, P=0.019) were the independent risk factors of bacterial infections in KT recipients ( P<0.05). Conclusion:The incidence of Ureaplasma spp. And gram-negative bacteria in UTI is relatively high among patients who have undergone long-term kidney transplantation. Notably, the highest infection rate of Mycoplasma occurs within the first 1 to 5 years post-transplantation. Female and younger age are high-risk factors for Mycoplasma UTIs, while female and concurrent diabetes are the high-risk factors for bacterial UTI.

Theory and technology of Medical Immunology are widely used in scientific research.Our teaching and research group uses experimental teaching of Medical Immunology as a platform to carry out practice of scientific research project-based experi-mental system among"5+3"integration students.By completing a mini-project research including experimental design-experimental operation-research article writing,students cultivated scientific research thinking and exercised scientific research practice ability,and generally reported that the course is very difficult,but after completing it,it is very rewarding.

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.

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.

Objective To investigate the status and influencing factors of the coexistence of multiple frailty domains in patients with chronic heart failure(CHF),and to provide a reference for formulating targeted intervention measures.Methods The patients with CHF hospitalized in the cardiovascular department of a tertiary general hospital in Tianjin from November 2021 to December 2022 were conveniently selected as the study subjects.The self-designed general information questionnaire,FRAIL scale,Montreal Cognitive Assessment(MoCA)scale,HALFT Scale,Social Support Rating Scale and Self-Rating Depression Scale were used to investigate the coexistence of physical,cognitive and social frailty in CHF patients,and single factor analysis and binary logistic regression analysis were used to analyze the influencing factors.Results A total of 275 questionnaires were issued and 269 valid questionnaires were collected.Among 269 patients with CHF,12(4.5％),67(24.9％),122(45.4％)and 68(25.3％)patients had 0,1,2 and 3 frailty domains,respectively.According to the patients with CHF whether coexists physical,cognitive,social frailty,divided into coexistence and non-coexistence group.In univariate analysis,there were statistically significant differences in education,residence,family history of cardiovascular disease,NYHA cardiac function grade,atrial fibrillation,BMI,social support score and depression score(P＜0.05).Binary logistic regression analysis showed that high education level(OR=0.567,95％CI 0.397～0.810,P=0.002)was the protective factor for multiple frailty domains in CHF patients,and atrial fibrillation(OR=1.904,95％CI 1.054～3.442,P=0.033)and depression(OR=1.038,95％CI 1.006～1.071,P=0.018)were risk factors.Conclusion The prevalence of the coexistence of multiple frailty domains in CHF patients is high.Education level,atrial fibrillation and depression are potential intervention targets for multiple frailty domains in CHF patients.Targeted intervention measures should be carried out to reduce the incidence of multiple frailty domains and to improve quality of life for CHF patients.

Objective:To compare the consistency of microarray chemiluminescent protein chip and immunoblotting in the autoantibody spectrum of patients and the diagnostic efficacy of systemic lupus erythematosus(SLE), and to explore the correlation between the detection results of protein microarray and clinical indicators and lymphocyte subsets.Methods:Serum autoantibodies in 649 samples collected between December 2023 and December 2024 in Nanjing Drum Tower Hospital were analyzed using the microarray chemiluminescent protein chip method, with 401 samples simultaneously tested by immunoblotting. Kappa coefficient assessed inter-method consistency. Diagnostic performance was compared via ROC curves. Spearman correlation analysis evaluated relationships between autoantibody levels and SLEDAI-2000 scores, clinical parameters, and lymphocyte subsets.Results:The two methods demonstrated good consistency across 14 antinuclear antibodies, with optimal agreement for anti-SSA/Ro ( Kappa=0.845, P<0.001), anti-SSB ( Kappa=0.825, P<0.001), and anti-CENP B ( Kappa=0.851, P<0.001). The protein chip method significantly improved SLE diagnostic efficacy, particularly for anti-dsDNA (AUC difference=0.291, P<0.001) and anti-Sm antibodies (AUC difference=0.295, P<0.001). Combined detection of anti-SSA/Ro and anti-nRNP/Sm antibodies achieved superior diagnostic performance (AUC=0.927). Anti-dsDNA, anti-histone, and anti-nucleosome antibodies positively correlated with SLEDAI-2000 ( r=0.408, 0410, 0.384, all P<0.001), complement ( P<0.001), and 24-hour urinary protein ( r=0.374, 0.387, 0.301, all P<0.001). Immunological analysis showed that the proportion of NK cells was generally negatively correlated with antinuclear antibodies such as anti-dsDNA ( r=-0.352, P<0.001) and anti-Sm ( r=-0.328, P<0.001) antibodies. Meanwhile, the proportion of CD8 + T cells was positively correlated with anti-nRNP/Sm ( r=0.229, P=0.002) and anti-Sm antibodies ( r=0.211, P=0.005). The proportion of CD4 + T cells was negatively correlated with anti-SSA/Ro ( r=-0.239, P<0.001), while the proportion of B cells was positively correlated with anti-dSDNA antibody ( r=0.300, P<0.001). Conclusion:The protein chip method showed strong consistency with immunoblotting for detecting 14 autoantibodies but demonstrated superior SLE diagnostic efficacy. The combined use of multiple detection methods can enhance the reliability of clinical diagnosis.