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.

Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

This study analyzed the burden and trends in enteric infections in China from 1990 to 2021 from a One Health perspec-tive.Data on mortality associated with enteric infections were extracted from the 2021 Global Burden of Disease(GBD)database.The analysis focused on assessing the mortality rates of enteric infectious diseases attributed to various etiologies and risk factors,along with the age and sex distribution,from 1990 to 2021.Average annual percentage change(AAPC)was used to assess the total changes in disease burden.The age-standardized mortality rate of intestinal infections in China decreased from 9.642/100 000 in 1990 to 0.439/100 000 in 2021,with an AAPC of-57.103%(95%CI:-57.118%to-57.088%).In 2021,Rotavirus,Norovirus,and Crypto-sporidium were the top three etiologies contributing to disease burden,with mortality rates of 1.020/100 000,0.040/100 000 and 0.079/100 000,respectively.A significant variation in etiology distribution was observed across age groups:Rotavirus,Shigella,and Crypto-sporidium dominated among children under 5 years of age,whereas Cryptosporidium,Norovirus,and Clostridioides difficile were more prevalent in older populations.Risk factor analysis indicated that unsafe water sources and poor sanitation accounted for 73.394%of all enteric disease-related deaths.In conclusion,the burden of enteric infections in China markedly declined from 1990 to 2021,and sig-nificant variations in the etiological spectrum and disease burden were observed across age groups.The persistent effects of unsafe wa-ter sources and poor sanitation underscore the need for targeted interventions to further decrease the burden of these diseases.Our find-ings highlight the success of public health interventions in decreasing the burden of enteric infections in China,while emphasizing the need for targeted measures to address disparities in high-risk populations and improve environmental sanitation.

With the improvement in the accuracy and portability of three-dimensional facial imaging de-vices,and the rapid development of medical image recognition technology in artificial intelligence,the analysis and automatic recognition of three-dimensional facial characteristics of diseases have been widely applied in multiple fields such as endocrine metabolic disorders,chronic respiratory diseases,neuromuscular diseases,ge-netic syndromes,and plastic surgery.We aim to systematically review and summarize the current research status and development trends of three-dimensional facial photogrammetry and image analysis techniques in disease di-agnosis,assessment of prognosis and treatment efficacy,in order to provide references and insights for scientific research and clinical applications of this field.

Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challenges related to data standardization,completeness,and accuracy,primarily due to the decen-tralized distribution of TCM resources.To address these issues,we developed a platform for TCM knowledge discovery(TCMKD,https://cbcb.cdutcm.edu.cn/TCMKD/).Seven types of data,including syndromes,formulas,Chinese patent drugs(CPDs),Chinese medicinal materials(CMMs),ingredients,targets,and diseases,were manually proofread and consolidated within TCMKD.To strengthen the integration of TCM with modern medicine,TCMKD employs analytical methods such as TCM data mining,enrichment analysis,and network localization and separation.These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights.In addition to its analytical capabilities,a quick question and answer(Q&A)system is also embedded within TCMKD to query the database efficiently,thereby improving the interactivity of the platform.The platform also provides a TCM text annotation tool,offering a simple and efficient method for TCM text mining.Overall,TCMKD not only has the potential to become a pivotal repository for TCM,delving into the pharmaco-logical foundations of TCM treatments,but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems,extending beyond just TCM.

This study was aimed at exploring novel auxiliary diagnostic biomarkers for brucellosis and their potential miR-NA-mRNA regulatory networks.High-throughput sequencing was used to compare miRNA expression differences in serum ex-osomes between patients with brucellosis and healthy controls.Subsequently,RT-qPCR was used to validate the expression of significantly upregulated exosomal miRNAs.The diagnostic value of these miRNAs was assessed with ROC curves,and bioin-formatics analyses were performed to investigate the potential roles of the miRNAs in brucellosis infection.The ROC curve a-nalysis indicated that the area under the curve for exosomal hsa-miR-11400(P＜0.05),hsa-miR-199a-5p(P＜0.05),and hsa-miR-148a-5p(P＜0.05)was 0.79,0.81,and 0.74,respectively.A total of 465 differentially expressed miRNAs and their tar-get genes were predicted,including 25 immune-related target genes,most of which were closely associated with cancer-related proteoglycans,NF-kappa B signaling pathways,and IL-17 signaling pathways.The constructed differentially expressed gene network indicated that the immune genes PLXNA2,IL17RA,PRKCA,CD22,ACVR1B,and CBL might be regulated by hsa-miR-199a-5p and hsa-miR-148a-5p.These findings suggest that exosomal miRNAs might serve as auxiliary diagnostic indicators for brucellosis.Our exosomal miRNA-mRNA regulatory network provides new insights into the pathogenesis and treatment of brucellosis.

Objective To investigate the protective effects of secretomes released by three-dimensional cultured mesenchymal stem cells(MSCs)on neurons subjected to seawater immersion(SW)and stretch injury(SI),and to provide new insights into neuronal repair following SW combined with traumatic brain injury(TBI).Methods MSCs were cultured using the hanging drop method,and the conditioned medium(CM)containing MSCs secretomes was collected.A cellular model combining SW with SI was established using mouse hippocampal neuronal cells(HT22 cells).HT22 cells were randomly assigned to five groups:control,SI,SI+SW,SI+CM,and SI+SW+CM groups.Cell viability was assessed using the CCK-8 assay,apoptosis rate was measured by flow cytometry,cell migration ability was evaluated by scratch assay,and the expression levels of apoptosis-related proteins Bcl-2 and Bcl-2-associated protein(Bax),and ferroptosis-related proteins long-chain acyl-CoA synthetase 4(ACSL4)and cyclooxygenase-2(COX-2)were detected by Western blotting.Results Immersion in 15%seawater for 12 h significantly decreased HT22 cell viability(P<0.05).The CCK-8 assay indicated that cell viability in both the SI and SI+SW groups was significantly lower than that in control group after 12 h of treatment(P<0.05).Treatment with CM containing MSCs secretomes significantly increased cell viability in SI+CM group compared to SI group(P<0.0001),and in SI+SW+CM group compared to SI+SW group(P<0.001).Flow cytometry results revealed that the apoptosis rate in SI and SI+SW groups was significantly higher than that in control group(P<0.05 or P<0.001),while in SI+CM group was lower than that in SI group(P<0.05),and in SI+SW+CM group was lower than that in SI+SW group(P<0.05).Western blotting showed that compared to control group,SI and SI+SW groups exhibited reduced Bcl-2 expression level(P<0.01 or P<0.0001)and increased expression levels of Bax,ACSL4,and COX-2(P<0.01 or P<0.0001).Compared to SI group,the SI+CM group displayed increased Bcl-2 expression level(P<0.05)and decreased expression levels of Bax,ACSL4,and COX-2(P<0.05).Compared to SI+SW group,SI+SW+CM group exhibited increased Bcl-2 expression level(P<0.01)and decreased expression levels of Bax,ACSL4,and COX-2(P<0.01 or P<0.001).Scratch assay results demonstrated that at both 12 h and 24 h,the cell migration rate in SI and SI+SW groups was significantly lower than that in control group(P<0.01 or P<0.0001),while the migration rate in SI+CM group was significantly higher than that in SI group(P<0.0001 or P<0.01),and the migration rate in SI+SW+CM group was significantly higher than that in SI+SW group(P<0.0001).Conclusion Secretomes derived from MSCs cultured using the hanging drop method can alleviate neuronal damage caused by SW and TBI,potentially offering a therapeutic approach for SW combined with TBI.

Objective To explore the value of serum matrix metalloproteinase 7 combined with glutamyl transferase and total bile acids in the diagnosis of biliary atresia.Methods 112 children hospitalized in Kunming Children's Hospital with the cholestatic jaundice from July 2023 to September 2024 were selected as the research subjects.According to the surgical exploration,intraoperative cholangiography,liver biopsy and follow-up,the children were divided into the biliary atresia group(BA)(n=52)and non-biliary atresia group(Non-BA)(n=60)respecvely.The age,gender,serum matrix metalloproteinase 7(MMP-7),glutamyl transferase(GGT),alanine aminative aminotransferase(ALT),aspartate aminotransferase(AST),total bilirubin(TB),direct bilirubin(DB),total bile acid(TBA)and aspartate aminotransferase/platelet index(APRI)were compared between the two groups.Statistically significant indicators were included in receiver operating characteristic curve(ROC)analysis,and the area under the ROC curve(AUC)and optimal diagnostic margin(Youden index)were calculated.Results There was no significant difference in age,ALT,AST,DB,TB and APRI levels between the two groups of patients(P>0.05);There was a difference in gender composition ratio between the two groups(P=0.006);MMP-7,GGT,TBA levels in the BA group were significantly higher than those in the Non-BA group,and the difference was statistically significant(P<0.05);the AUC of MMP-7,GGT,and TBA in diagnosing BA were 0.946(95%CI 0.897～0.996),0.857(95%CI 0.789～0.926),0.654(95%CI 0.552～0.755)respectively;When the cut-off value of MMP-7 was 22.37 ng/ml,the sensitivity and specificity for diagnosing BA were 0.923 and 0.933 respectively;When the cut-off value of GGT was 151.5 U/L,the sensitivity and specificity of diagnosing BA were 0.885 and 0.733 respectively;When the cut-off value of TBA was 119.5 μmol/L,the sensitivity and specificity of diagnosing BA were 0.788 and 0.500,respectively.The AUC of MMP-7+GGT and MMP-7+TBA combined to diagnose BA were 0.971(95%CI 0.946～0.997)and 0.943(95%CI 0.889～0.996)respectively.Conclusion Serum MMP-7 has the good diagnostic value as a single indicator for diagnosing BA;MMP-7 combined with GGT is better than a single indicator for diagnosing BA;MMP-7 combined with TBA cannot improve the diagnostic efficiency.

Objective:To explore the equity and driving path of primary healthcare human resource allocation across 31 provinces in China,providing references for optimizing such allocations.Methods:Using data from the 2022 primary healthcare human resources in 31 provinces in China,the Health Resource Density Index(HRDI)was used to measure the equity of primary healthcare human resource allocation.The fuzzy-set Qualitative Comparative Analysis(fsQCA)was applied to construct configurational pathways influencing on allocation patterns.Results:In 2022,the HRDI for primary healthcare human resources in China was 2.349 0 in the East,1.198 6 in the Central region,and 0.775 2 in the West.Configurational analysis revealed three paths that promote high equity:the internal-external balance-driven model(H1),the government-led model(H2),and the economic-demand combined model(H3),with overall consistency and coverage of 0.955 and 0.794,respectively.Seven paths lead to low equity:internal-external constraint models(L1,L2),economic constraint models(L3),and demand constraint models(L4,L5,L6,L7),with overall consistency and coverage of 0.967 and 0.795,respectively.Conclusions:Significant regional disparities exist in the equity of primary healthcare human resource allocation in China.Population density is a critical factor influencing allocation equity.The collaboration of various factors contributes to enhancing the equity of primary healthcare human resources distribution.Therefore,future efforts to enhance equity should focus on promoting inter-regional mobility and resource sharing,while precisely addressing regional shortcomings to achieve high equity in primary healthcare human resource allocation.

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.