ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

BACKGROUND:Multiple studies have confirmed that mitogen-activated protein kinase(MAPK)signaling pathway is involved in cell proliferation,and microRNA(miR)is involved in the occurrence and development of hypertrophic scars.Therefore,the role of miR-27a-3p and MAPK signaling pathways in pathological scar formation has been further explored. OBJECTIVE:To explore the effect of miR-27a-3p on the proliferation of human hypertrophic scar fibroblasts through the MAPK signaling pathway. METHODS:The primary fibroblasts were isolated and collected from the skin samples.The primary fibroblasts were observed by inverted microscope and verified by immunofluorescence.The relative expression level of miR-27a-3p in tissues was detected by qRT-PCR.The target genes of hsa-miR-27a-3p were predicted using the database,and then the predicted target genes were enriched by gene ontology function analysis and biological pathway enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes.There were seven groups:blank control,negative control,miR-27a-3p mimic,miR-27a-3p inhibitor,miR-27a-3p mimic+p38 MAPK inhibitor,miR-27a-3p mimic+extracellular regulated protein kinase inhibitor,miR-27a-3p mimic+c-Jun N-terminal kinase inhibitor.Western blot was used to detect the levels of extracellular regulated protein kinase,c-Jun N-terminal kinase inhibitor.and p38 kinase and their phosphorylation levels.Cell counting kit-8 and EdU were used to detect cell proliferation. RESULTS AND CONCLUSION:Compared with normal skin fibroblasts,hypertrophic scar fibroblasts had stronger proliferative activity(P<0.05)and faster proliferation level(P<0.001).Compared with normal skin,miR-27a-3p was highly expressed in hypertrophic scars(P<0.001).Compared with the negative control group,overexpression of miR-27a-3p could promote cell proliferation activity(P<0.001)and proliferation levels(P<0.001).Compared with the negative control group,knockdown of miR-27a-3p could inhibit the proliferation activity(P<0.05)and proliferation levels(P<0.001).Compared with the negative control group,overexpression of miR-27a-3p promoted the phosphorylated levels of extracellular regulated protein kinase,c-Jun N-terminal kinase,and p38 mitogen-activated protein kinase(P<0.05).Compared with the negative control group,knockdown of miR-27a-3p inhibited the phosphorylated levels of extracellular regulated protein kinase,c-Jun N-terminal kinase,and p38 MAPK(P<0.05).Compared with the miR-27a-3p mimic group,specific inhibitors of extracellular regulated protein kinase,c-Jun N-terminal kinase,and p38 MAPK reversed the effects of miR-27a-3p on the proliferative activity(P<0.01)and proliferation level(P<0.001)of fibroblasts.To conclude,these results suggest that miR-27a-3p promotes the proliferation of human hypertrophic scar fibroblasts by activating the MAPK signaling pathway.

Objective:To explore the relationship between monocyte-lymphocyte ratio(MLR),modified Glasgow prognostic score(mGPS)and the prognosis of patients with advanced gastric cancer after radical gastrectomy.Methods:A retrospective analysis was conducted on the data of 106 patients with advanced gastric cancer who underwent radical gastrectomy in our hospital from April 2018 to April 2021,the patients were followed up for 3 years after the operation.MLR and mGPS scores of patients with different clinical characteristics were compared.The Kaplan-Meier method was used to analyze the survival differences of patients in different MLR and mGPS groups,and the survival curves were plotted.The Cox regression model was used to analyze variables such as clinical characteristics,laboratory indicators,MLR and mGPS scores,and to screen out the independent factors affecting the prognosis of patients.The receiver operating characteristic(ROC)curve was constructed to evaluate the efficacy of MLR,mGPS scores and their combination in predicting poor prognosis efficiency of patients,and the area under the curve(AUC),sensitivity and specificity were calculated.Results:MLR and mGPS scores were correlated with tumor TNM stage,degree of differentiation,tumor diameter,lymph node metastasis and postoperative chemotherapy(P＜0.05).The 3-year survival rates of the MLR ≥0.3 group and mGPS ≥ 1 group were 45.20％and 50.00％respectively,which were much lower than those in the low MLR group and mGPS group(78.40％and 82.40％,P＜0.05).The survival rate in the high-risk group(MLR ≥0.3 and mGPS ≥ 1)was 29.41％,significantly lower than those in the medium and low-risk groups(P＜0.05).Cox multivariate analysis showed that high clinical stage,lymph node metastasis,high degree of differentiation,high MLR and high mGPS scores were independent risk factors affecting the prognosis of patients.ROC curve showed that the AUC of MLR and mGPS scores alone in predicting poor prognosis of patients was 0.756 and 0.842,respectively,the AUC of combination detection the two was 0.909,the predictive efficacy of the combination detection was significantly better than that of the single detection.Conclusion:Elevated MLR and mGPS scores can be used as independent prognostic indicators after advanced gastric cancer,the combination in predicting is helpful to provide a more accurate basis for clinical prognosis assessment.

Objective:In the context of China's cardiovascular disease(CVD)high-risk population screening and intervention project,this study systematically evaluates the applicability of the EQ-5D-5L and SF-6Dv2 instruments among individuals at high risk of CVD.Methods:Convergent validity was assessed using Spearman's correlation coefficient.Measurement agreement was evaluated through intraclass correlation coefficients(ICC)and Bland-Altman plots.Factors influencing utility differences were explored using multiple linear regression analysis.Kruskal-Wallis test and t-test were used to examine discriminant validity.Sensitivity was compared by effect size(ES),relative efficiency(RE),and the area under the receiver operating characteristic curve(ROC-AUC).Floor and ceiling effects were also compared.Results:Among 5,415 individuals at high risk of CVD,the two instruments showed moderate overall correlation and acceptable convergent validity,but dimension-specific correlations were weak,and measurement consistency was low(ICC=0.367).Both instruments effectively distinguished different health states,yet the SF-6Dv2 demonstrated superior sensitivity and a milder ceiling effect.Conclusion:When measuring the health utility value of CVD patients,scale selection should be cautious,especially for high-risk groups,and SF-6Dv2 is more appropriate.

Aim To investigate the effect of chrysoeriol on pulmonary vascular remodeling in pulmonary hyper-tension by animal experiments combined with cell ex-periments,and to explore its potential therapeutic tar-gets by network pharmacology.Methods The target of chrysoeriol was collected in Targetnet,SEA and SwissTargetPrediction database.Pulmonary arterial hy-pertension(PAH)targets were collected in the Dis-GeNET and GeneCards databases,and PPI network map was drawn in the STRING database,and key tar-gets were screened.The GO and KEGG pathway en-richment analysis was carried out through DAVID data-base and Weishengxing platform.AutoDock software was used for molecular docking of key core targets.The PAH model of rats was constructed,and the pulmo-nary hemodynamics and vascular remodeling were de-tected by echocardiography,HE and Masson staining.Primary pulmonary smooth muscle cells were extracted,and the effects of drugs on pathway proteins were de-tected in vitro.Results The results of network phar-macology showed that chrysoeriol exerted therapeutic effects on pulmonary hypertension by affecting key tar-gets such as AKT1,SRC,EGFR,MMP9 and gsk3 β,and signaling pathways such as EGFR and PI3K-AKT.Molecular docking showed that chrysoeriol had good binding ability with 5 key target genes.Animal experi-ments showed that the pulmonary hemodynamic func-tion of PAH rats was significantly improved after ad-ministration of chrysoeriol.The remodeling of small pulmonary arteries was significantly reduced.Cell ex-periments showed that chrysoeriol could inhibit the ex-pression of proliferation,migration and phenotypic transformation genes.Conclusion Chrysoeriol may play a role in the treatment of pulmonary hypertension through multiple targets.

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.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To explore the structural equation model to explore the levels of work-related musculoskeletal disorders (WMSDs) and various risk factors in the feet and ankle of China's occupational population, providing scientific basis for for preventing WMSDs in feet and ankles.Methods:Data of 73497 national occupational epidemiological cases were selected from June 2018 to December 2023 used the Chinese version of the Electronic Questionnaire on Musculoskeletal Disorders. The adverse ergonomic factors and their source classification standard and confirmatory factor analysis were used to investigate foot and ankle WMSDs and their related risk factors (including individual factors, work organization, work posture, work type, fatigue, etc.) in key occupational groups in China, and structural equation model hypothesis, fitting, verification, and path and intermediary effect analysis were carried out. The model fit evaluation indexes included Chi-square specific degrees of freedom ( χ2/ df), gauge fit index (NFI), Tucker Lewis index (TLI), goodness of Fit index (GFI), adjusted Goodness of Fit index (AGFI) and approximate root mean square error (RMSEA) . Results:A total of 73497 occupational workers were surveyed, with local muscle fatigue and WMSDs incidence rates in the feet and ankles being 17.17% and 12.06%, respectively. The fitting index of the adjusted structural equation model basically meets the standard (GFI=1, AGFI=1, RMESA=0.042, NFI=0.716, TLI=0.663). The top three factors affecting feet and ankle WMSDs are feet and ankle muscle fatigue, work type, and work organization, with standardized path coefficients of 0.221, 0.105, and 0.095, respectively. The top two factors affecting feet and ankle muscle fatigue are work organization and work type, with standardized path coefficients of 0.548 and 0.383, respectively. Feet and ankle muscle fatigue, work type, work organization, and work posture have a direct effect on feet and ankle WMSDs, with effect values of 0.221, 0.105, 0.095, and 0.077, respectively. The organization and type of work can also have indirect effects through feet and ankle muscle fatigue, with effect values of 0.121 and 0.084, respectively.Conclusion:Feet and ankle muscle fatigue has a direct impact on WMSDs, and plays a mediating role between ankle and ankle WMSDs caused by work organization and work type. Feet and ankle muscle fatigue is an important pathway leading to feet and ankle WMSDs. It is recommended that employers and managers detect job fatigue early and take corresponding prevention and intervention measures, which can play a key role in preventing feet and ankle WMSDs.

Objective:To explore the structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."