Objective To identify immune cell-related biomarkers in lung adenocarcinoma (LUAD) using weighted gene co-expression network analysis (WGCNA). Methods Based on data from The Cancer Genome Atlas (TCGA) database, a gene co-expression network was constructed for the TCGA-LUAD dataset using the "WGCNA" R package, and genes were clustered into different modules. Concurrently, the Estimation of STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm was applied to the tumor samples in the TCGA-LUAD dataset. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to evaluate the biological functions of genes within the most significantly correlated module. Candidate hub genes from the key module were intersected with a protein-protein interaction (PPI) network to identify the final hub genes. The prognostic performance of these hub genes and their correlation with immune cell infiltration were validated using Kaplan-Meier curves and the Tumor IMmune Estimation Resource (TIMER) algorithm. Finally, a multivariate Cox regression analysis was conducted on the identified hub genes to construct a prognostic risk model. Results In the co-expression network, the brown module was found to be highly correlated with the ImmuneScore, StromalScore, and ESTIMATE Score. Five immune-related hub genes were identified: CD53, PLEK, SPI1, IL10RA, and C3AR1. Enrichment analysis of the brown module revealed that its genes were primarily enriched in GO terms such as "regulation of innate immune response" and KEGG pathways like the "NF-kappa B signaling pathway". Furthermore, the expression levels of these five hub genes were significantly and positively correlated with the infiltration abundance of various immune cells. The immune relevance of the model was validated by the Immunophenoscore (IPS) and the Tumor Immune Dysfunction and Exclusion (TIDE) score. Moreover, the established RiskScore demonstrated significant potential in predicting the response to immunotherapy. Conclusion These five immune-related key genes may serve as novel and effective potential therapeutic targets for LUAD immunotherapy, facilitating the development of personalized diagnosis and treatment strategies for patients with LUAD.

This consensus focuses on the clinical application of domestic ultra-high-definition (UHD) medical endoscopes in cardiovascular surgery, addressing their clinical value, key technical aspects, and strategies for broader implementation. It traces the evolution of domestic endoscopic platforms from high-resolution imaging toward integrated advanced functionalities such as fluorescence imaging, three-dimensional visualization, and intelligent assistance. The document outlines standardized procedural steps and perioperative management pathways for minimally invasive endoscopic cardiovascular surgery and summarizes specific application scenarios and technical considerations in congenital heart disease, valvular disorders, coronary artery disease, arrhythmias, and cardiac tumors. Furthermore, recommendations are provided regarding professional training, multicenter collaboration, the establishment of clinical evaluation systems, and coordinated policy-industry support to promote standardized adoption and high-quality dissemination of domestic medical devices. Based on available evidence and expert agreement, 16 consensus statements are presented, aiming to offer authoritative and actionable guidance for clinical practice.

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease. As a critical component of surgical repair, reconstruction of the right ventricular outflow tract (RVOT) serves as a primary determinant of postoperative hemodynamics and long-term prognosis. With advancements in surgical techniques, early postoperative survival rates for TOF have significantly improved, shifting clinical focus toward addressing long-term complications such as right ventricular dysfunction and reduced exercise tolerance. However, challenges persist regarding optimal timing of surgery in relation to adverse long-term outcomes, balancing RVOT reconstruction strategies, and selecting appropriate repair materials for RVOT reconstruction, with a lack of unified high-level evidence-based guidelines. To address these issues and standardize the application of radical corrective surgery for TOF to better serve patients, the National Society for Congenital Heart Diseases has systematically reviewed existing high-level evidence. Consequently, we have registered and formulated the "Protocol for Chinese expert consensus on right ventricular outflow tract reconstruction in tetralogy of Fallot (2026 edition)", which details the methodology and development process of this upcoming consensus.

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease. Right ventricular outflow tract (RVOT) reconstruction, as the core technical step of radical surgery, plays a decisive role in postoperative hemodynamics and long-term quality of life. With the substantial improvement in early survival after TOF repair, clinical focus has progressively shifted toward the prevention and management of late complications, including right ventricular dysfunction, impaired exercise capacity, and the need for reintervention. However, RVOT reconstruction strategies and the selection of repair materials remain controversial. To standardize the clinical practice of definitive TOF repair, the National Society for Congenital Heart Diseases developed this expert consensus, focusing on three domains: postoperative outcomes after TOF repair, RVOT reconstruction strategies, and the reconstructive materials.

Objective To develop and validate a machine learning model based on preoperative clinical characteristics, laboratory indices, and radiological features for the non-invasive prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma. Methods Preoperative data from patients with early-stage lung adenocarcinoma who underwent surgical resection at Northern Jiangsu People's Hospital between January 2020 and August 2025 were retrospectively collected. The data included clinical characteristics, laboratory indices, and radiological features. Patients were divided into a STAS-positive and a STAS-negative group based on postoperative pathological findings. The dataset was randomly split into a training set and a testing set at a 7 : 3 ratio. Feature variables were selected using the maximum relevance and minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression. Five machine learning models were constructed: logistic regression (LR), random forest (RF), support vector machine (SVM), light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The shapley additive explanations (SHAP) method was employed to interpret the optimal prediction model. Results A total of 377 patients were included, comprising 177 (46.9%) males and 200 (53.1%) females, with a mean age of (63.31±9.73) years. There were 261 patients in the training set and 116 patients in the testing set. In the training set, statistically significant differences were observed between the STAS-positive group (n=130) and STAS-negative group (n=131) across multiple features, including age, sex, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), clinical T stage, and maximum solid component diameter (P<0.05). A final set of 10 feature variables was selected by combining mRMR and LASSO regression, and five machine learning models (LR, RF, SVM, LightGBM, XGBoost) were developed. The XGBoost model demonstrated optimal performance in both the training and testing sets, achieving AUCs of 0.947 [95%CI (0.920, 0.975)] and 0.943 [95%CI (0.894, 0.993)], respectively. DCA indicated that the XGBoost model provided a high net clinical benefit across a wide range of threshold probabilities. SHAP analysis revealed that the vessel convergence sign, clinical T stage, age, consolidation-to-tumor ratio (CTR), and MLR were the features with the highest contributions to STAS prediction. Conclusion The XGBoost model effectively predicts preoperative STAS status in early-stage lung adenocarcinoma, exhibiting excellent discriminative performance and good clinical interpretability. Key predictors such as the vessel convergence sign, clinical T stage, age and CTR provide a crucial reference for preoperative risk assessment and the individualized selection of surgical strategies, ultimately benefiting patients.

Objective To investigate the causes and management strategies for lower limb ischemic necrosis following xenogeneic heterotopic heart transplantation from a multigene-edited pig to a rhesus monkey. Methods A xenogeneic heterotopic heart transplantation was performed on December 16, 2023, at the Institute of Experimental Animals of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, using a quintuple-gene-edited pig as the donor and a rhesus monkey as the recipient. On postoperative day (POD) 9, the recipient monkey underwent left lower limb amputation due to ischemic necrosis. Blood samples were collected at various time points after transplantation for analysis of hematologic parameters, liver and renal function, myocardial enzymes, and coagulation profiles. Ultrasound and computed tomography (CT) were used to evaluate anastomotic patency and cardiac structure. Immunological assays, including complement-dependent cytotoxicity (CDC) and IgG/IgM antibody detection, combined with clinical observations, were employed to assess rejection type and therapeutic response. Results The recipient monkey survived for 46 days after transplantation. Echocardiography demonstrated preserved biventricular systolic function in the recipient’s native heart, with left ventricular ejection fraction (LVEF) consistently exceeding 50%. In the donor pig heart, left ventricular endocardial thickening was noted on POD 9, followed by right ventricular endocardial thickening on POD 24, while LVEF remained around 35%. No hyperacute or acute rejection was detected immunologically. CDC positivity ranged between 3.4% and 5.1%, with IgG/IgM antibody binding trends consistent with CDC results. Following amputation, the recipient exhibited elevated inflammatory markers, coagulopathy, and reactive thrombocytosis, which later normalized. Immunohistochemical staining of the necrotic limb revealed arterial and venous thrombosis; however, no T-cell or B-cell infiltration was observed in vascular structures, thrombi, nerves, muscles, fascia, or skin tissues, with CD3 and CD20 staining both negative. Conclusion Limb ischemia after xenogeneic heart transplantation may be associated with lower extremity vascular thrombosis triggered by local trauma in the context of transplantation-induced inflammatory activation and coagulation dysfunction. While no clear lymphocyte-mediated rejection was observed, further studies are needed to explore the potential role of non-lymphocyte-mediated immune mechanisms.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

Lung cancer is the leading cause of death worldwide. With the prevalence of CT screening and early diagnosis and treatment of lung cancer in China, more and more patients with early-stage lung cancer characterized with ground-glass opacity are discovered and urgently require treatment, which poses a significant challenge to surgeons. As an emerging technology, three dimensional reconstruction technology plays a crucial auxiliary role in clinical work. This review aims to briefly introduce this technology, focusing on its latest advances in surgical applications in early lung cancer screening, malignant risk assessment, and perioperative period application and medical education.

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.