Objective To develop an artificial intelligence (AI)-driven lung cancer database by structuring and standardizing clinical data, enabling advanced data mining for lung cancer research, and providing high-quality data for real-world studies. Methods Building on the extensive clinical data resources of the Department of Thoracic Surgery at Peking Union Medical College Hospital, this study utilized machine learning techniques, particularly natural language processing (NLP), to automatically process unstructured data from electronic medical records, examination reports, and pathology reports, converting them into structured formats. Data governance and automated cleaning methods were employed to ensure data integrity and consistency. Results As of September 2024, the database included comprehensive data from 18 811 patients, encompassing inpatient and outpatient records, examination and pathology reports, physician orders, and follow-up information, creating a well-structured, multi-dimensional dataset with rich variables. The database’s real-time querying and multi-layer filtering functions enabled researchers to efficiently retrieve study data that meet specific criteria, significantly enhancing data processing speed and advancing research progress. In a real-world application exploring the prognosis of non-small cell lung cancer, the database facilitated the rapid analysis of prognostic factors. Research findings indicated that factors such as tumor staging and comorbidities had a significant impact on patient survival rates, further demonstrating the database’s value in clinical big data mining. Conclusion The AI-driven lung cancer database enhances data management and analysis efficiency, providing strong support for large-scale clinical research, retrospective studies, and disease management. With the ongoing integration of large language models and multi-modal data, the database’s precision and analytical capabilities are expected to improve further, providing stronger support for big data mining and real-world research of lung cancer.

GPR126, also known as ADGRG6, is one of the most deeply studied aGPCRs. Initially, GPR126 was thought to be a receptor associated with muscle development and was primarily expressed in the muscular and skeletal systems. With the deepening of research, it was found that GPR126 is expressed in multiple mammalian tissues and organs, and is involved in many biological processes such as embryonic development, nervous system development, and extracellular matrix interactions. Compared with other aGPCRs proteins, GPR126 has a longer N-terminal domain, which can bind to ligands one-to-one and one-to-many. Its N-terminus contains five domains, a CUB (complement C1r/C1s, Uegf, Bmp1) domain, a PTX (Pentraxin) domain, a SEA (Sperm protein, Enterokinase, and Agrin) domain, a hormone binding (HormR) domain, and a conserved GAIN domain. The GAIN domain has a self-shearing function, which is essential for the maturation, stability, transport and function of aGPCRs. Different SEA domains constitute different GPR126 isomers, which can regulate the activation and closure of downstream signaling pathways through conformational changes. GPR126 has a typical aGPCRs seven-transmembrane helical structure, which can be coupled to Gs and Gi, causing cAMP to up- or down-regulation, mediating transmembrane signaling and participating in the regulation of cell proliferation, differentiation and migration. GPR126 is activated in a tethered-stalk peptide agonism or orthosteric agonism, which is mainly manifested by self-proteolysis or conformational changes in the GAIN domain, which mediates the rapid activation or closure of downstream pathways by tethered agonists. In addition to the tethered short stem peptide activation mode, GPR126 also has another allosteric agonism or tunable agonism mode, which is specifically expressed as the GAIN domain does not have self-shearing function in the physiological state, NTF and CTF always maintain the binding state, and the NTF binds to the ligand to cause conformational changes of the receptor, which somehow transmits signals to the GAIN domain in a spatial structure. The GAIN domain can cause the 7TM domain to produce an activated or inhibited signal for signal transduction, For example, type IV collagen interacts with the CUB and PTX domains of GPR126 to activate GPR126 downstream signal transduction. GPR126 has homology of 51.6%-86.9% among different species, with 10 conserved regions between different species, which can be traced back to the oldest metazoans as well as unicellular animals.In terms of diseases, GPR126 dysfunction involves the pathological process of bone, myelin, embryo and other related diseases, and is also closely related to the occurrence and development of malignant tumors such as breast cancer and colon cancer. However, the biological function of GPR126 in various diseases and its potential as a therapeutic target still needs further research. This paper focuses on the structure, interspecies differences and conservatism, signal transduction and biological functions of GPR126, which provides ideas and references for future research on GPR126.

BACKGROUND:Rheumatoid arthritis is a chronic autoimmune disease.Early diagnosis is crucial for preventing disease progression and for effective treatment.Therefore,it is of significance to investigate the diagnostic characteristics and immune cell infiltration of rheumatoid arthritis. OBJECTIVE:Based on the Gene Expression Omnibus(GEO)database,to screen potential diagnostic markers of rheumatoid arthritis using machine learning algorithms and to investigate the relationship between the diagnostic characteristics of rheumatoid arthritis and immune cell infiltration in this pathology. METHODS:The gene expression datasets of synovial tissues related to rheumatoid arthritis were obtained from the GEO database.The data sets were merged using a batch effect removal method.Differential expression analysis and functional correlation analysis of genes were performed using R software.Bioinformatics analysis and three machine learning algorithms were used for the extraction of disease signature genes,and key genes related to rheumatoid arthritis were screened.Furthermore,we analyzed immune cell infiltration on all differentially expressed genes to examine the inflammatory state of rheumatoid arthritis and investigate the correlation between their diagnostic characteristics and infiltrating immune cells. RESULTS AND CONCLUSION:In both rheumatoid arthritis and normal synovial tissues,we identified 179 differentially expressed genes,with 124 genes up-regulated and 55 genes down-regulated.Enrichment analysis revealed a significant correlation between rheumatoid arthritis and immune response.Three machine learning algorithms identified LRRC15 and MICB as potential biomarkers of rheumatoid arthritis.LRRC15(area under the curve=0.964,95%confidence interval:0.924-0.992)and MICB(area under the curve=0.961,95%confidence interval:0.923-0.990)demonstrated strong diagnostic performance on the validation dataset.The infiltration of 13 types of immune cells was altered,with macrophages being the most affected.In rheumatoid arthritis,the majority of proinflammatory pathways in immune cell function were activated.Immunocorrelation analysis revealed that LRRC15 and MICB had the strongest correlation with M1 macrophages.To conclude,this study identified LRRC15 and MICB as potential diagnostic markers for rheumatoid arthritis,with strong diagnostic performance and significant correlation with immune cell infiltration.Machine learning and bioinformatics analysis deepened the understanding of immune infiltration in rheumatoid arthritis and provided new ideas for the diagnosis and treatment of rheumatoid arthritis.

Objective:To evaluate the clinical outcomes of combined complete preservation of chordal structure mitral valve replacement (C-MVR) with total anatomical arterial myocardial revascularization (TACR) in coronary patients with moderate-to-severe or severe ischemic mitral regurgitation (IMR).Methods:This is a retrospective multi-center case series study. Data were retrospectively collected from 127 patients with coronary artery disease with moderate to severe or severe IMR who received TACR with C-MVR from July 2015 to April 2024 in 13 hospitals in China. There were 90 males and 37 females, aged (56.5±10.7) years (range: 33 to 74 years). Perioperative data and follow-up data including left ventricular ejection fraction, left ventricular end-diastolic diameter, and patency rate of arterial grafts of patients were collected. Comparisons were made using paired sample t-test or χ2 test. Results:In this cohort of 127 patients, 67 underwent concurrent tricuspid valve repair. During surgery, 113 grafts of the left internal mammary artery (LIMA), 127 grafts of the left radial artery, 80 grafts of the right radial artery, and 110 grafts of the right internal mammary artery (RIMA) were harvested. The number of the distal anastomosis was 4.2±0.4 (range: 3 to 5). The aortic cross-clamp time and cardiopulmonary bypass time were (97.5±23.4) minutes (range: 90 to 161 minutes) and (145.4±19.2) minutes (range: 101 to 210 minutes), respectively. There was one operative death. Intraoperative placement of an intra-aortic balloon pump was performed in 21 patients to improve the left ventricular ejection. No sternal ischemic occurred. All patients completed follow-up, with a mean follow-up period of (64.3±7.5) months (range: 4 to 110 months). No major cerebrovascular events occurred during the follow-up period, and all patients survived. Left ventricular ejection fraction improved postoperatively (55.0%±5.3% vs. 41.0%±15.3%, t=17.23, P<0.01). The proportion of patients with New York Heart Association functional class ≤2 increased postoperatively (23.6% (30/127) vs. 87.3% (110/126), χ2=103.77, P<0.01). The proportion of patients with Canadian Cardiovascular Society Angina Classification ≤3 decreased postoperatively (4.8% (6/126) vs. 78.7% (100/127), χ2=142.19, P<0.01). The left ventricular end-diastolic diameter decreased postoperatively ((5.70±4.50) cm vs. (6.10±0.23) cm, t=12.15, P<0.01). Coronary multi-detector computed tomography angiography (MDCTA) follow-up was conducted for (60.5±11.7) months (range: 6 to 109 months) postoperatively. MDCTA confirmed the patency rates of the grafts: 96.4% (108/112) for the LIMA grafts, 88.9% (112/126) for the left radial artery grafts, 93.7% (74/79) for the right radial artery grafts, and 90.9% (100/110) for the free RIMA grafts. No significant differences in graft patency rates were observed between the arterial grafts ( χ2=5.24, P=0.155). Conclusion:The results of this multi-centre study demonstrate satisfactory mid-term results of C-MVR with TACR for the treatment of coronary artery disease with moderate to severe or severe IMR.

Objective:To evaluate the clinical outcomes of combined complete preservation of chordal structure mitral valve replacement (C-MVR) with total anatomical arterial myocardial revascularization (TACR) in coronary patients with moderate-to-severe or severe ischemic mitral regurgitation (IMR).Methods:This is a retrospective multi-center case series study. Data were retrospectively collected from 127 patients with coronary artery disease with moderate to severe or severe IMR who received TACR with C-MVR from July 2015 to April 2024 in 13 hospitals in China. There were 90 males and 37 females, aged (56.5±10.7) years (range: 33 to 74 years). Perioperative data and follow-up data including left ventricular ejection fraction, left ventricular end-diastolic diameter, and patency rate of arterial grafts of patients were collected. Comparisons were made using paired sample t-test or χ2 test. Results:In this cohort of 127 patients, 67 underwent concurrent tricuspid valve repair. During surgery, 113 grafts of the left internal mammary artery (LIMA), 127 grafts of the left radial artery, 80 grafts of the right radial artery, and 110 grafts of the right internal mammary artery (RIMA) were harvested. The number of the distal anastomosis was 4.2±0.4 (range: 3 to 5). The aortic cross-clamp time and cardiopulmonary bypass time were (97.5±23.4) minutes (range: 90 to 161 minutes) and (145.4±19.2) minutes (range: 101 to 210 minutes), respectively. There was one operative death. Intraoperative placement of an intra-aortic balloon pump was performed in 21 patients to improve the left ventricular ejection. No sternal ischemic occurred. All patients completed follow-up, with a mean follow-up period of (64.3±7.5) months (range: 4 to 110 months). No major cerebrovascular events occurred during the follow-up period, and all patients survived. Left ventricular ejection fraction improved postoperatively (55.0%±5.3% vs. 41.0%±15.3%, t=17.23, P<0.01). The proportion of patients with New York Heart Association functional class ≤2 increased postoperatively (23.6% (30/127) vs. 87.3% (110/126), χ2=103.77, P<0.01). The proportion of patients with Canadian Cardiovascular Society Angina Classification ≤3 decreased postoperatively (4.8% (6/126) vs. 78.7% (100/127), χ2=142.19, P<0.01). The left ventricular end-diastolic diameter decreased postoperatively ((5.70±4.50) cm vs. (6.10±0.23) cm, t=12.15, P<0.01). Coronary multi-detector computed tomography angiography (MDCTA) follow-up was conducted for (60.5±11.7) months (range: 6 to 109 months) postoperatively. MDCTA confirmed the patency rates of the grafts: 96.4% (108/112) for the LIMA grafts, 88.9% (112/126) for the left radial artery grafts, 93.7% (74/79) for the right radial artery grafts, and 90.9% (100/110) for the free RIMA grafts. No significant differences in graft patency rates were observed between the arterial grafts ( χ2=5.24, P=0.155). Conclusion:The results of this multi-centre study demonstrate satisfactory mid-term results of C-MVR with TACR for the treatment of coronary artery disease with moderate to severe or severe IMR.

Objective To propose a lung artery segmentation method that integrates shape and position prior knowledge, aiming to solve the issues of inaccurate segmentation caused by the high similarity and small size differences between the lung arteries and surrounding tissues in CT images. Methods Based on the three-dimensional U-Net network architecture and relying on the PARSE 2022 database image data, shape and position prior knowledge was introduced to design feature extraction and fusion strategies to enhance the ability of lung artery segmentation. The data of the patients were divided into three groups: a training set, a validation set, and a test set. The performance metrics for evaluating the model included Dice Similarity Coefficient (DSC), sensitivity, accuracy, and Hausdorff distance (HD95). Results The study included lung artery imaging data from 203 patients, including 100 patients in the training set, 30 patients in the validation set, and 73 patients in the test set. Through the backbone network, a rough segmentation of the lung arteries was performed to obtain a complete vascular structure; the branch network integrating shape and position information was used to extract features of small pulmonary arteries, reducing interference from the pulmonary artery trunk and left and right pulmonary arteries. Experimental results showed that the segmentation model based on shape and position prior knowledge had a higher DSC (82.81%±3.20% vs. 80.47%±3.17% vs. 80.36%±3.43%), sensitivity (85.30%±8.04% vs. 80.95%±6.89% vs. 82.82%±7.29%), and accuracy (81.63%±7.53% vs. 81.19%±8.35% vs. 79.36%±8.98%) compared to traditional three-dimensional U-Net and V-Net methods. HD95 could reach (9.52±4.29) mm, which was 6.05 mm shorter than traditional methods, showing excellent performance in segmentation boundaries. Conclusion The lung artery segmentation method based on shape and position prior knowledge can achieve precise segmentation of lung artery vessels and has potential application value in tasks such as bronchoscopy or percutaneous puncture surgery navigation.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Objective To explore the application of artificial intelligence (AI) in the standardized training of thoracic surgery residents, specifically in enhancing clinical skills and anatomical understanding through AI-assisted lung nodule identification and lung segment anatomy teaching. Methods Thoracic surgery residents undergoing standardized training at Peking Union Medical College Hospital from September 2023 to September 2024 were selected. They were randomly assigned to a trial group and a control group using a random number table. The trial group used AI-assisted three-dimensional reconstruction technology for lung nodule identification, while the control group used conventional chest CT images. After basic teaching and self-practice, the ability to identify lung nodules on the same patient CT images was evaluated, and feedback was collected through questionnaires. Results A total of 72 residents participated in the study, including 30 (41.7%) males and 42 (58.3%) females, with an average age of (24.0±3.0) years. The trial group showed significantly better overall diagnostic accuracy for lung nodules (91.9% vs. 73.3%) and lung segment identification (100.0% vs. 83.70%) compared to the control group, and the reading time was significantly shorter [ (118.5±10.5) s vs. (332.1±20.2) s, P<0.01]. Questionnaire results indicated that 94.4% of the residents had a positive attitude toward AI technology, and 91.7% believed that it improved diagnostic accuracy. Conclusion AI-assisted teaching significantly improves thoracic surgery residents’ ability to read images and clinical thinking, providing a new direction for the reform of standardized training.

OBJECTIVE To construct the drug utilization evaluation criteria for Dezocine injection， so as to provide reference for the rational drug use in medical institutions. METHODS On the basis of evidence methodology， relevant guidelines/expert consensus， systematic reviews/meta-analysis were consulted； the evaluation criteria framework for Dezocine injection was established after screening evidence. Delphi method was employed， whereby 28 clinicians and clinical pharmacists from secondary and above-level medical institutions across eight provinces， including Tianjin， Beijing and Shandong， were selected to participate in two rounds of questionnaire surveys. The final indicators were determined based on the experts’ enthusiasm coefficient， authority coefficient， and degree of coordination. RESULTS The effective recovery rate of questionnaire was 100% in the first round and 92.86% in the second round； expert authority coefficient was 0.82 in the first round and 0.81 in the second round； the coordination degree of experts in the first round was 0.29， and in the second round was 0.31 （P＜0.001）. Drug utilization evaluation standard system for Dezocine injection was formed finally， including three dimensions of medication indications， medication process and medication results， with a total of 11 first-level indicators （such as indications， usage and dosage） and 33 second-level indicators （such as labor analgesia and the management of severe pain following major or moderate surgeries combined with other analgesic drugs）. The average importance scores for each indicator ranged from 4.08 to 5.00 points， with an overall average score of 4.61 points and coefficient of variation ranging from 0 to 0.19. CONCLUSIONS The drug utilization evaluation criteria for Dezocine injection established based on evidence-based methodology and Delphi method is authoritative and scientific， which provides a reference for subsequent evaluation of the rationality of clinical medication.

Based on current national policies, regulations, standards, relevant literature, and departmental experience regarding the protection against radionuclides in China, this study provides a brief overview of key issues in the management of hospital wards for patients with internal radionuclide contamination. The discussion covers the detection of internal contamination, general requirements for internal radionuclide contamination wards, and inpatient management. In addition, the study explores in depth the daily responsibilities, protective measures, and management protocols for both healthcare staff and patients within such wards. This article summarizes a framework for the construction of internal radionuclide contamination wards, along with specific plans and detailed role-based guidelines. These results provide a reference for the management of hospital wards for patients with internal radionuclide contamination.