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.

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 investigate the feasibility and safety of bedside transesophageal echocardiography(TEE)-guided atrial septostomy in patients undergoing extracorporeal membrane oxygenation(ECMO)support.Methods Eight patients(2 females and 6 males)who developed pulmonary edema during VA-ECMO treatment between January 2020 and October 2024 were enrolled.All patients underwent bedside TEE-guided atrial septal puncture,followed by gradual balloon dilation using an Inoue balloon(diameter:18-24 mm).The endpoint for dilation was defined as mean left atrial pressure＜15 mmHg.Post-procedure evaluation included assessment of the septal defect size,mean left atrial pressure,and improvement in bilateral pulmonary edema.Results The mean age of all 8 patients was(43.50±16.84)years old.Atrial septostomy was successfully performed in all patients.The mean balloon dilation diameter was(22.75±2.68)mm,resulting in a mean septal defect size of(6.31±0.37)mm.The mean left atrial pressure significantly decreased from(26.63±1.77)mmHg pre-procedure to(12.75±1.28)mmHg post-procedure(P＜0.001).All patients demonstrated marked improvement in bilateral pulmonary edema,and six patients also showed a significant reduction in the severity of mitral regurgitation following the procedure.No procedure-related complications were observed.Conclusions Bedside TEE-guided atrial septostomy is safe and effective for reducing left heart loading during ECMO support and improving pulmonary edema.

China has become the country with the highest global burden of heart failure(HF).Despite the widespread use of prognostic-improving medications today,the mortality rate of HF remains high,reaching 13.7％at one year-particularly among patients with heart failure with reduced ejection fraction(HFrEF).HF interventional device therapy(structural intervention)targets the structural factors underlying HF,including atrial pressure,ventricular remodeling,and valvular intervention.It leverages the heart's intrinsic physiological properties and pathological progression mechanisms to deliver treatments through interventions without external active forces,achieving anatomical or functional repair.This field has emerged as a rapidly growing area and plays an increasingly critical role in HF management.This article provides a comprehensive review and summary of the latest advancements in HF and cardiomyopathy interventional therapy over the past year.It covers various novel technologies and products currently in the research phase,aiming to provide an in-depth analysis of the current status and future directions of HF interventional therapy,and further advance the development of this discipline.

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]

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Radiation‐induced lung injury (RILI) is one of the common and serious complications in chest cancer patients after undergoing radiotherapy. In recent years, gut microbiota has garnered attention as a research hotspot. Multiple studies found that it has preventive and therapeutic effects on RILI. It can exert its effects through various mechanisms including the regulation of the immune system, the gut‐lung axis and its own metabolites, etc. In this article, the mechanism of RILI was elucidated and the protective mechanism of gut microbiota against RILI was comprehensively analyzed, providing new insights for the prevention and treatment of RILI in clinical practice and offering new methods to improve patient prognosis and enhance the quality of life.

Objective To investigate the expression characteristics and clinical diagnostic value of programmed death receptor 1(PD-1)and its corresponding ligand(PD-L1)in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD).Methods One hundred and sixty COPD patients who visited Dongzhimen Hospital of Beijing University of Chinese Medicine from April 2024 to November 2024 were included and divided into an acute exacerbation group of 100 cases and a stable group of 60 cases according to the severity of the disease.Additionally,40 healthy volunteers during the same period were recruited as the control group.The general clinical data of the patients were collected.Chronic Obstructive Pulmonary Disease Assessment Test(CAT)and Modified Medical Research Council Dyspnea Questionnaire(mMRC)Scale were used to test the severity of the disease;respiratory function testing was performed and fasting venous blood was collected for serum PD-1 and PD-L1 testing.Pearson correlation was used to analyze the correlation between serum PD-1,PD-L1,CAT,and mMRC,and multiple logistic regression analysis to identify the influencing factors of AECOPD.Receiver operating characteristic(ROC)curve was drawn to evaluate the diagnostic value of serum PD-1 and PD-L1 level for AECOPD.Results Serum PD-1 level in the stable COPD group and AECOPD group was significantly increased compared with that in the control group,while serum PD-L1 level was significantly decreased,showing statistical significance(P<0.05);The level of PD-1 gradually increased with the grading of lung function and the deterioration of AECOPD,with statistical significance(P<0.05);Pearson correlation showed that serum PD-1 level was positively correlated with CAT scores in COPD patients,while negatively with CAT scores,showing statistical significance(P<0.05);Multiple logistic regression analysis showed that elevated levels of serum inter-leukin-6(IL-6),neutrophil to lymphocyte ratio(NLR),and PD-1 were risk factors for AECOPD,while elevated level of PD-L1 was protective factor for AECOPD(P<0.05);ROC curve showed that the levels of PD-1,PD-L1,IL-6,NLR,and the area under the ROC curve(AUC)for their combined prediction of AECOPD diagnosis were 0.884,0.867,0.868,0.802,and 0.995,respectively.Conclusion Serum PD-1 and PD-L1 in AECOPD patients have presented certain expression characteristics,with elevated PD-1 level while decreased PD-L1 level.Both have good clinical diagnostic value for AECOPD.

Objective To conduct a bibliometric analysis of relevant literature on liver failure caused by viral hepatitis from the past five years,and to help researchers understand the current status and hotspots in this field,and to provide insights into future research trends.Methods Based on the Science Citation Index Expanded(SCI-Expanded)data from Web of Science Core Collection,visualization analysis and mapping were conducted through VOSviewer and CiteSpace software to generate visual representations of international research collaboration networks,keyword co-occurrence clustering,and keyword bursts.Results From 2019 to 2023,a total of 873 relevant literature were included,with a total citation frequency of 7 364 and an average citation frequency of 8.44.Among them,China had the highest number of publications(458 articles,52.46%)and had the most cooperation with the United States.The research hotspots of viral hepatitis induced liver failure were mainly divided into three categories:basic and clinical research on liver failure caused by non-hepatitis B virus(HBV),the pathogenesis of HBV related liver failure,and treatment and prediction models of liver failure.The keyword time overlay map and burst map showed that the research hotspots had gradually shifted from the prevention and control of new infections to the treatment and prognosis assessment of patients with chronic infection.Conclusion China is a major international research entity in liver failure caused by viral hepatitis and actively participates in international scientific collaborations.The research hotspots on liver failure caused by viral hepatitis have gradually shifted from preventing viral hepatitis infections and expanding treatment options to the treatment of chronic infection patients and prognostic prediction.

Objective:To explore the risk factors and etiological characteristics of urinary tract infection caused by urinary calculi in eastern Fujian region,in order to attract clinical attention and improve the prevention and treatment of urinary tract infection caused by urinary calculi.Methods:A total of 154 patients with urinary calculi admitted to Ningde People's Hospital(n=80)and Ningde Mindong Hospital(n=74)from November 2022 to October 2023 were selected as the main research objects.According to whether the patients had urinary tract infection,they were divided into infection group and non-infection group.The baseline data of the two groups were analyzed in detail,and the risk factors and pathogen distribution of urinary tract infection in patients with urinary calculi were analyzed.Results:There were 33 cases of urinary tract infection in 154 patients with urinary calculi,accounting for 21.43％.Univariate analysis showed that the urinary white blood cell count in the infection group was higher than that in the non-infection group,and the proportion of patients with effusion,urinary tract obstruction,calculi in the upper urinary tract,staghorn calculi,smoking history,diabetes,and urinary nitrite positive was higher than that in the uninfected group(P＜0.05).The results of binary logistic regression analysis showed that effusion,urinary tract obstruction,staghorn calculi,smoking history,diabetes,high urine white blood cell count and positive urine nitrite were independent risk factors for urinary tract infection in patients with urinary calculi(OR＞1,P＜0.05).A total of 33 strains of pathogenic bacteria were isolated from 33 patients in the infection group.Among them,23 strains(69.70％)were gram-negative bacteria,8 strains(24.24％)were gram-positive bacteria,and 2 strains(6.06％)were fungi.Among gram-negative bacteria,escherichia coli accounted for the highest proportion(48.48％),followed by klebsiella pneumoniae(9.09％).Among gram-positive bacteria,enterococcus faecalis accounted for the highest proportion(12.12％),followed by enterococcus faecium(6.06％).Candida and candida tropicalis in fungi was the same,accounted for 3.03％.Conclusion:The risk of urinary tract infection in patients with urinary calculi in eastern Fujian region is high.Effusion,urinary tract obstruction,staghorn calculi,smoking history,diabetes,high urine white blood cell count and positive urine nitrite are independent risk factors for urinary tract infection in patients with urinary calculi.The main urinary tract pathogens are gram-negative bacteria.