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.

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."

AIM To investigate the effects of Wenfei Jiangzhuo Formula on mitochondrial function of Aβ25-35-induced BV-2 cells.METHODS In the establishment of cell model of Alzheimer's disease(AD)using Aβ25-35 on the BV-2 cells,the optimal concentration and time point of Aβ25-35 intervention were determined;and the groups for the intervention of LFHP-1c group(inhibitor)or the serum containing Wenfei Jiangzhuo Formula were set up.The detection of the optimal intervention concentration and time point by CCK-8 assay;the observation of cell migration and apoptosis by Transwell assay and Hoechst 33342 staining;the detection of the positive expressions of PGAM5 and Drp1 by immunofluorescence;and the detection of cellular PGAM5,Drp1,OPA1,and Mfn1/2 mRNA and protein expressions by RT-qPCR and Western blot were conducted.RESULTS The best AD cell model was established by 48 h exposure to 5 μmol/L of Aβ25-35,and most active cell viability was achieved with the 48 h use of serum containing 20％Wenfei Jiangzhuo Formula.Compared with the control group,the model group displayed decreased number of cell migration,more bright blue positive apoptotic cells,increased number of PGAM5 and Drp1 positive cells and their mRNA and protein expressions(P＜0.05);and decreased mRNA and protein expressions of OPA1 and Mfn1/2(P＜0.05).Compared with the model group,the groups intervened with the medicines shared increased number of cell migration,less bright blue positive apoptotic cells,decreased number of PGAM5 and Drp1 positive cells and their mRNA and protein expressions(P＜0.05);and elevated OPA1 and Mfn1/2 mRNA and protein expressions(P＜0.05).CONCLUSION Wenfei Jiangzhuo Formula exerts cerebroprotective effects to improve cognition by reducing cell damage and improving the balance of mitochondrial homeostasis through PGAM5-Drp1 axis in AD model.

Objective:This study aims to analyze the trends,hotspots,and interrelations in research on retroperito-neal tumors through bibliometric methods,providing the latest scientific information support for clinicians and research-ers.Methods:Data were sourced from the SCI-expanded database of the Web of Science Core Collection,covering the period from 2004 to 2023.Statistical analysis and visualization of the number of publications,total citations,average citations per article,countries,institutions,journals,and keywords were conducted using Microsoft Excel 2019,VOS-viewer,and CiteSpace.Results:A total of 6,842 relevant articles were retrieved,with a total of 113 753 citations and an average of 16.63 citations per article.The number of publications had been increasing annually,peaking in 2022.The United States,China,and Japan are the major research countries,with the United States contributing the most.Memo-rial Sloan Kettering Cancer Center and the University of Texas MD Anderson Cancer Center are the leading research in-stitutions.The journal with the most publications was the Cureus Journal of Medical Science.Gronchi Alessandro was the most prolific author.The ain keywords were"Management","Surgery",and"Tumor",and the most cited papers focus on surgery and multicenter studies.Conclusion:Research on retroperitoneal tumors is increasing annually,with hot-spots focusing on treatment methods and prognosis analysis.The United States is the main contributor to this field,with significant international collaboration.Future research should further explore the pathogenesis of retroperitoneal tumors and more effective treatment strategies.

Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]

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 investigate lymph node metastasis(LNM)in the prostatic anterior fat pad(PAFP)of PCa patients after robot-assisted radical prostatectomy(RARP),and analyze the clinicopathological features and prognosis of LNM in the PAFP.Methods:We retrospectively analyzed the clinicopathological data on 1 003 cases of PCa treated by RARP in the Department of Urolo-gy of PLA General Hospital from January 2017 to December 2022.All the patients underwent routine removal of the PAFP during RARP and pathological examination,with the results of all the specimens examined and reported by pathologists.Based on the pres-ence and locations of LNM,we grouped the patients for statistical analysis,compared the clinicopathological features between different groups using the Student's t,Mann-Whitney U and Chi-square tests,and conducted survival analyses using the Kaplan-Meier and Log-rank methods and survival curves generated by Rstudio.Results:Lymph nodes were detected in 77(7.7％)of the 1 003 PAFP samples,and LNM in 11(14.3％)of the 77 cases,with a positive rate of 1.1％(11/1 003).Of the 11 positive cases,9 were found in the upgraded pathological N stage,and the other 2 complicated by pelvic LNM.The patients with postoperative pathological stage≥T3 constituted a significantly higher proportion in the PAFP LNM than in the non-PAFP LNM group(81.8％[9/11]vs 36.2％[359/992],P=0.005),and so did the cases with Gleason score ≥8(87.5％[7/8]vs 35.5％[279/786],P=0.009).No statisti-cally significant differences were observed in the clinicopathological features and biochemical recurrence-free survival between the pa-tients with PAFP LNM only and those with pelvic LNM only.Conclusion:The PAFP is a potential route to LNM,and patients with LNM in the PAFP are characterized by poor pathological features.There is no statistically significant difference in biochemical recur-rence-free survival between the patients with PAFP LNM only and those with pelvic LNM only.Routine removal of the PAFP and inde-pendent pathological examination of the specimen during RARP is of great clinical significance.

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 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.

Objective To evaluate the prognosis and safety of patients with advanced pancreatic ductal adenocarcinoma(PDAC)who received I-125 seed implantation in treatment with anti-PD-1 monoclonal antibody+chemotherapy.Methods A retrospective analysis was conducted on patients with stage Ⅳ metastatic PDAC who received anti-PD-1 combined chemotherapy treatment at Yixing Hospital,Jiangsu University from Jan 2021 to Jun 2023.Patients were divided into two groups based on whether they received I-125 seed implantation:the I-125 seed implantation+anti-PD-1 monoclonal antibody+Chemotherapy group(IPC group)and the anti-PD-1 monoclonal antibody+chemotherapy group(PC group).The follow-up period ranged from 2 to 24 months,with a median follow-up time of 9 months.The prognosis of patients was analysed in combination with peripheral blood biomarkers.The peripheral lymphocyte subsets of patients in different treatment groups were preliminarily analysed by flow cytometry.Results A total of 13 patients were included,with 5 in the IPC group and 8 in the PC group.Progression-free survival(PFS)and overall survival(OS)in the IPC group were significantly longer than those in the PC group.The treatment in the IPC group was relatively safe,adverse reactions were controllable.The neutrophil-lymphocyte ratio(NLR)and CD4/CD8 ratio indicated that the prognosis of the IPC patients was better.The levels of regulatory T cells(Treg)and active regulatory T cells(aTreg)cells in the IPC patients were reduced after treatment compared with those of the PC patients.Conclusion The addition of I-125 seed implantation can improve the prognosis of patients with advanced PDAC who receive anti-PD-1 monoclonal antibody+chemotherapy,the post-treatment levels of patients'circulating aTreg cells are reduced,and the combination therapy has good safety.