ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

Myopic traction maculopathy(MTM)is a common vision-threatening complication in patients with high myopia. With the global increase in high myopia, the prevalence of MTM has been rising worldwide, leading to a growing burden of disease, economic costs,and social impact. The emergence and development of optical coherence tomography(OCT)have provided robust technical support for the staging of MTM. Based on the evolving understanding of its pathological mechanisms and natural course, various staging systems have been proposed and applied in clinical practice, offering crucial guidance for the personalized management of MTM patients. Additionally, innovations and refinements in surgical techniques and materials, such as pars plana vitrectomy(PPV), posterior scleral reinforcement, and macular buckling(MB), have expanded the therapeutic options for MTM. This article systematically reviews the staging systems and treatment strategies for MTM, focusing on the role of OCT-based staging in guiding individualized treatment plans. It also summarizes the current evidence on the efficacy and safety of existing and emerging surgical approaches, including PPV, MB, and their combined procedures. The review further proposes that future research should focus on developing predictive models integrating multimodal data to clarify surgical timing and indications, as well as conducting large-scale, multicenter randomized controlled trials to explore the selection of PPV, MB, or combined surgeries. The review aims to discuss personalized treatment for MTM, providing theoretical foundations and practical directions for optimizing clinical management and improving patient prognosis for MTM patients.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

Objective: To analyze the time-related factors influencing daily blood donation attendance at fixed donation sites in Nanjing and the heterogeneity among sites, and to provide evidence for optimizing site layout and operational management. Methods: Based on daily attendance data from 17 fixed donation sites in Nanjing for the full year of 2025, matched with contemporaneous meteorological and air quality data, a two-stage negative binomial generalized linear mixed model (NB-GLMM) was constructed. In the second stage, site-level static characteristics (number of scenic spots, daily operating hours, number of shopping malls, public transport stops, hospitals, universities, and residential buildings) were additionally incorporated. Model comparison was performed using Akaike information criterion (AIC). Significance of random effects was tested by likelihood ratio test, and site-specific random effects were extracted using empirical Bayes estimation. Robustness of the results was verified through residual diagnostics and multiple sensitivity analyses. Results: The first-stage model showed that rainfall was associated with lower attendance (IRR=0.943, P<0.001); holidays were associated with higher attendance (IRR=1.162, P<0.001); Saturdays and Sundays showed higher attendance than Mondays, with the strongest association on Sundays (IRR=1.195, P<0.001). Temperature exhibited a non-linear relationship (linear term P=0.051, quadratic term P=0.036). The joint results of the linear and quadratic terms for temperature suggested a nonlinear relationship between attendance and temperature. After introducing static characteristics in the second stage, the number of scenic spots (IRR=1.372, P=0.008) and daily operating hours (IRR=1.823, P<0.001) were found to be positively associated with attendance, while the numbers of shopping malls, public transport stops, hospitals, universities, and residential buildings showed no significant effects. Conclusion: Daily blood donation attendance at fixed sites in Nanjing is influenced by multiple factors including weather, day of the week, holidays, and site surroundings. Substantial heterogeneity exists among different sites; extended operating hours and more nearby scenic spots are associated with increased attendance.

Objective To investigate the impact of county-level"Unified ECG Network"construction on the treatment efficiency and clinical outcomes of patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A retrospective analysis was conducted on the clinical data of STEMI patients from Beichuan County and Yanting County in Mianyang City,and Jiange County in Guangyuan City,Sichuan Province,during the 18 months before(128 cases)and 18 months after(187 cases)the establishment of the"Unified ECG Network."Differences in demographic characteristics,treatment efficiency,therapeutic methods,and clinical outcomes between the two groups were compared.Results There was no statistically significant difference in general demographic characteristics between the two groups(all P＞0.05).Compared with the pre-construction group,the post-construction group showed significantly shorter times in initial ECG completion[5(3,7)min vs.6(4,8)min],initial ECG diagnosis[3(2,4)min vs.5(2,6)min],first medical contact to preliminary diagnosis[10(9,12)min vs.13(11,15)min],network hospital door-in-door-out time[21(19,23)min vs.26(23,30)min],and first medical contact to wire-crossing time[(94.82±11.87)min vs.(107.97±18.39)min](allP＜0.001).The proportion of patients bypassing the emergency department and coronary care unit significantly increased(64.17％vs.32.81％,P＜0.001).The proportion of patients undergoing emergency percutaneous coronary intervention significantly increased(72.73％vs.51.56％,P＜0.001),while the proportions of thrombolytic therapy and non-reperfusion therapy significantly decreased(both P＜0.05).Additionally,in-hospital mortality rate,Killip class≥Ⅱ proportion,incidence of major adverse cardiovascular events,and average length of hospital stay were all significantly reduced(all P＜0.05).There were no statistically significant differences among the three county-level chest pain centers in terms of major treatment efficiency,therapeutic strategies,or clinical outcomes(all P＞0.05).Conclusions The construction of the county-level"Unified ECG Network"can significantly improve the treatment efficiency of STEMI patients,optimize reperfusion therapy strategies,improve clinical outcomes,and demonstrate substantial clinical promotion value.

Objective To develop and validate a fast Monte Carlo(MC)-based patient-specific quality assurance(PSQA)tool using the treatment log files that is suitable to be used in the online adaptive radiotherapy for pencil beam scanning proton therapy(PBSPT-ART).Methods The proposed tool first used the delivery log file of a PBSPT plan to reversely reconstruct the PBSPT(rPBSPT)plan,and then used an in-house developed graphic processing unit(GPU)-accelerated virtual particle MC(VPMC)dose engine to calculate the dose distribution of the rPBSPT plan.The rPBSPT dose calculated by VPMC was then compared to the rPBSPT dose calculated by another independent MC dose engine(MCsquare),using 3D gamma analysis to verify the accuracy of VPMC calculation.As a demonstration of the feasibility of developed log file-based PSQA,the VPMC calculated dose of the rPBSPT plan was compared to the pre-delivery second check dose of the corresponding PBSPT plan calculated by MCsquare,using 3D gamma analysis.3D gamma analysis employes a criterion of 2 mm/2%/10%.Twenty patients with different disease sites were representatively selected to validate the efficiency and accuracy of the tool.Results The average calculation time of a rPBSPT plan by VPMC was(5.88±4.00)s in the accuracy verification.Compared to MCsquare,the passing rate of the 3D gamma analysis was 99.47%±0.72%.In the proposed PSQA tool demonstration,the passing rate of comparing the VPMC calculated rPBSPT dose to MCsquare calculated second check dose of the corresponding PBSPT plan was 98.91%±0.92%.Conclusion The accuracy and efficiency of the tool can meet the requirements of PSQA in the online PBSPT-ART workflow.

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.

The minor purchasing process and mode of some hospital were introduced,and the implementation of the hospital's minor purchasing projects in the past year was analyzed.The causes for high failure rate of purchasing were pointed out including long interval between project creation and procurement,unreasonable demand presentation,insufficient demand demonstration and lack of active participation of suppliers.Some suggestions were put forward such as timely adjustment of demands,strengthening of demand demonstration,improvement of supplier motivation and enhancement of procurement process management,which were of great significance for increasing the success rate of minor purchasing of the hospital.[Chinese Medical Equipment Journal,2025,46(8):91-95]