In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.

Objective To explore the relationship between blood glucose variability, disease severity and prognosis of the patients with acute pancreatitis. Methods Total of 242 patients with acute pancreatitis admitted to the department of emergency from January 2019 to December 2019 were enrolled. The organ failure was evaluated according to Marshall's score, the severity of the disease was evaluated according to Atlanta's score, and the blood glucose indexes of three groups of patients with mild acute pancreatitis, moderate severe acute pancreatitis and severe acute pancreatitis were compared within seven days after admission. The relationship between blood glucose index and disease severity in different patients with acute pancreatitis was analyzed. Taking whether a puncture was performed at admission, whether the patient was admitted to the intensive care unit (ICU), and whether the patient died as endpoint events as classification factors, the relationship between blood glucose indicators and disease prognosis of patients with acute pancreatitis was analyzed using the One-Way ANOVA, Kruskal-Wallis test, Mann-Whitney U test, receiver operating characteristic curve (ROC curve), etc. Results Of the 242 patients, 70 cases (28.9%) were mild acute pancreatitis, 71 cases (29.3%) with moderate severe acute pancreatitis, 101 cases (41.7%) with severe acute pancreatitis. There was no statistically significant difference in the coefficient of variation of blood glucose among the three groups within 7 days of admission. The mean, standard deviation, maximum, minimum value and difference between maximum and minimum value of venous blood glucose in severe acute pancreatitis group were higher than those in moderate severe acute pancreatitis group, while those in moderate severe acute pancreatitis group were higher than those in mild acute pancreatitis group. The mean value of blood glucose of invasive operation group (IOP) (n=55) was higher than that of non-invasive operation (NOP) group(n=187). Conclusions The blood glucose level and fluctuation range of patients with acute pancreatitis within seven days after admission, are of great significance for the judgment of the severity and prognosis of the disease.

Objective To explore the feasibility of a deep learning model based on early fundus lesions without manual segmentation in pan-retinal images for predicting diabetic kidney disease(DKD)and evaluating the enhancing effects of different binocular fusion strategies.Methods A retrospective cohort of 353 patients with type 2 diabetes mellitus(T2DM)admitted to the Endocrinology Department of Jiangdu People's Hospital Affiliated to Yangzhou University between December 2022 and March 2024 was analyzed.Patients were divided into DKD(n=114)and non-diabetic kidney disease(NDKD)(n=239)group based on the presence of DKD.First,a U-Net-based pre-trained automatic segmentation model was developed to process panoramic fundus retinal images.Subsequently,left and right eye deep learning models were constructed using ResNet152 under a five-fold cross-validation framework(70%training,30%validation).Three binocular fusion strategies were implemented:result fusion,feature fusion,and image fusion models.Model performance was evaluated using the area under the receiver operating characteristic(ROC)curve(AUC).DeLong test was used to compare AUC differences among models,while net reclassification index(NRI)and decision curve analysis(DCA)were used to assess clinical utility.Results Six prediction models were developed:clinical parameter model,left fundus model,right fundus model,binocular image fusion model,binocular result fusion model,and binocular feature fusion model.The Transformer-based binocular feature fusion model achieved the highest AUC in both training and validation sets(0.864 and 0.658,respectively).DeLong tests revealed significant AUC superiority of the Transformer model over the other five models in the training set(all P<0.001),though no significant differences were observed in the validation set(all P>0.05).NRI analysis showed negative values for all comparisons with the Transformer model(training set:-0.255,-0.244,-0.289,-0.426,-0.163;validation set:-0.060,-0.016,-0.028,-0.105,-0.033,respectively),indicating its optimal predictive performance.DCA further demonstrated greater net benefit for the Transformer-based fusion model.Conclusions The deep learning model constructed using early fundus lesions without manual segmentation in pan-retinal images can predict DKD.The Transformer-based fusion strategy present the best performance,providing a novel approach for further optimization and development of tools to predict DKD in the future.

Objective To describe and analyze the current status,changing trend and influencing factors of the disease burden of cervical,endometrial and ovarian cancer in China from 1990 to 2021.Methods Data on incidence,mortality,disability-adjusted life year(DALY),and other indicators for cervical,endometrial and ovarian cancer were collected from the 2021 Global Burden of Disease database.Joinpoint regression models were used to analyze time trends,and age-period-cohort(APC)models assessed their impact on incidence and mortality.Spearman correlation analysis was performed to evaluate the relationship between the sociodemographic index(SDI)and the cancer indicators.Finally,the attributable risk factors for the disease burden were analyzed.Results From 1990 to 2021,age-standardized incidence rates of cervical and endometrial cancers in China significantly increased,while ovarian cancer showed no significant change.Age-standardized mortality,DALY,and years of life lost due to premature death(YLL)decreased significantly.The disease burden was heavier in middle-aged and older groups.APC model indicated an increase in cervical cancer incidence and a decrease in mortality over time.Furthermore,the incidence risks of cervical and endometrial cancers were elevated in successive birth cohorts,whereas a lower risk was observed for ovarian cancer.Correlation analysis showed significant associations between cancer incidence and mortality with SDI.Obesity has significantly contributed to the disease burden of common gynecologic cancers in China.Conclusion Mortality rates of cervical,endometrial and ovarian cancer have declined,while the incidence of cervical and endometrial cancers has significantly increased.The trends in incidence and mortality are influenced by age,period and cohort effects.Future efforts should focus on controlling risk factors like obesity to reduce the disease burden.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Spermatogenesis is a fundamental process that requires a tightly controlled epigenetic event in spermatogonial stem cells (SSCs). The mechanisms underlying the transition from SSCs to sperm are largely unknown. Most studies utilize gene knockout mice to explain the mechanisms. However, the production of genetically engineered mice is costly and time-consuming. In this study, we presented a convenient research strategy using an RNA interference (RNAi) and testicular transplantation approach. Histone H3 lysine 9 (H3K9) methylation was dynamically regulated during spermatogenesis. As Jumonji domain-containing protein 1A (JMJD1A) and Jumonji domain-containing protein 2C (JMJD2C) demethylases catalyze histone H3 lysine 9 dimethylation (H3K9me2), we firstly analyzed the expression profile of the two demethylases and then investigated their function. Using the convenient research strategy, we showed that normal spermatogenesis is disrupted due to the downregulated expression of both demethylases. These results suggest that this strategy might be a simple and alternative approach for analyzing spermatogenesis relative to the gene knockout mice strategy.
Spermatogenesis/physiology* ; Animals ; Male ; Mice ; Epigenesis, Genetic ; Jumonji Domain-Containing Histone Demethylases/metabolism* ; Histones/metabolism* ; RNA Interference ; Testis/metabolism* ; Methylation ; Mice, Knockout ; Histone Demethylases

Extensive studies have identified potential adverse effects on semen quality of obesity, based on body mass index, but the association between body fat distribution, a more relevant indicator for obesity, and semen quality remains less clear. We conducted a longitudinal study of 4304 sperm donors from the Guangdong Provincial Human Sperm Bank (Guangzhou, China) during 2017-2021. A body composition analyzer was used to measure total and local body fat percentage for each participant. Generalized estimating equations were employed to assess the association between body fat percentage and sperm count, motility, and morphology. We estimated that each 10% increase in total body fat percentage (estimated change [95% confidence interval, 95% CI]) was significantly associated with a 0.18 × 10 6 (0.09 × 10 6 -0.27 × 10 6 ) ml and 12.21 × 10 6 (4.52 × 10 6 -19.91 × 10 6 ) reduction in semen volume and total sperm count, respectively. Categorical analyses and exposure-response curves showed that the association of body fat distribution with semen volume and total sperm count was stronger at higher body fat percentages. In addition, the association still held among normal weight and overweight participants. We observed similar associations for upper limb, trunk, and lower limb body fact distributions. In conclusion, we found that a higher body fat distribution was significantly associated with lower semen quality (especially semen volume) even in men with a normal weight. These findings provide useful clues in exploring body fat as a risk factor for semen quality decline and add to evidence for improving semen quality for those who are expected to conceive.
Humans ; Male ; Adult ; Semen Analysis ; China ; Body Fat Distribution ; Longitudinal Studies ; Sperm Count ; Sperm Motility ; Body Mass Index ; Tissue Donors ; Obesity/complications* ; Spermatozoa ; Young Adult ; Middle Aged ; East Asian People

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

The prelimbic cortex (PL) plays a critical role in processing both the sensory and affective components of pain. However, the underlying molecular mechanisms remain poorly understood. In this study, we observed a reduction in hyperpolarization-activated cation current (I_h) in layer V pyramidal neurons of the contralateral PL in a mouse model of spared nerve injury (SNI). The expression of hyperpolarization-activated cyclic nucleotide-gated 2 (HCN2) channels was also decreased in the contralateral PL. Conversely, microinjection of fisetin, a partial agonist of HCN2, produced both analgesic and anxiolytic effects. Additionally, we found that cyclin-dependent kinase 5 (CDK5) was activated in the contralateral PL, where it formed a complex with HCN2 and phosphorylated its C-terminus. Knockdown of CDK5 restored HCN2 expression and alleviated both pain hypersensitivity and anxiety-like behaviors. Collectively, these results indicate that CDK5-mediated dysfunction of HCN2 in the PL underlies nerve injury-induced mechanical hypersensitivity and anxiety.
Animals ; Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels/metabolism* ; Hyperalgesia/metabolism* ; Cyclin-Dependent Kinase 5/metabolism* ; Neuralgia/metabolism* ; Male ; Anxiety/metabolism* ; Mice ; Potassium Channels/metabolism* ; Mice, Inbred C57BL ; Disease Models, Animal ; Pyramidal Cells/metabolism*

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.