Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

The technology of xenogeneic organ transplantation, as one of the core strategies to address the current contradiction between the supply and demand of transplant organs, has achieved significant breakthroughs from basic research to clinical application driven by factors such as the innovation of gene modification technology, the injection of research capital and the expansion of clinical trials, especially with the first actual clinical application of a pig heart-to-human transplant. China is also at the forefront of this field. This article intends to summarize the international research trends of xenogeneic organ transplantation (including financial support, the evolution of research stages and global clinical trial cases), and analyze the evolution and optimization of xenogeneic transplantation immunosuppression schemes, as well as the breakthroughs and unresolved scientific issues in current key clinical application technologies. The aim is to comprehensively present the progress of this field from basic research to clinical transformation, and provide references for promoting the rapid development of China's xenogeneic transplantation technology and subsequent clinical transformation and research directions.

As a pivotal strategy to alleviate the shortage of organ donors, xenotransplantation has achieved remarkable advances in both pre-clinical and clinical studies in recent years, driven by continuous optimization of gene modification techniques and immunosuppressive regimens. Nevertheless, clinical translation still confronts formidable challenges, including rejection and heightened infection risks, which severely compromise long-term graft survival. Consequently, the role of immunosuppressive regimens in xenotransplantation has become increasingly prominent. This article summarizes the mechanisms underlying xenogeneic immune rejection, the latest developments in immunosuppressive regimens, cutting-edge strategies for inducing immune tolerance and the major hurdles facing clinical xenotransplantation. It delves into potential optimization strategies and directions for future clinical research, aiming to offer theoretical insights and practical guidance for the safe and effective application of clinical xenotransplantation.

Objective: To investigate the prevalence of comorbidity of myopia, and overweight and obesity among primary and middle school students in Yanqing District, Beijing Municipality, so as to provide the evidence for \prevention and control of comorbidity. Methods: In September from 2020 to 2024, a stratified cluster sampling method was adopted annually to select primary, junior high school, senior high school, and vocational high school students in Yanqing District as survey subjects. Myopia was screened based on Screening Protocol for Myopia in Children and Adolescents. Height an weight were measured, and overweight and obesity were determined using the Screening for overweight and Obesity in School-Age Children and Adolescents. Results: A total of 9 883 individuals were surveyed, including 5 219 primary school students (52.81%), 2 486 junior high school students (25.15%), and 2 178 senior high school / vocational high school students (22.04%). There were 5 154 boys (52.15%) and 4 729 girls (47.85%). From 2020 to 2024, the numbers of primary and middle school students in Yanqing District with myopia, overweight, and obesity were 4 426, 1 897, and 3 164, respectively, with detection rates of 44.78%, 19.19%, and 32.01%. The detection rates of myopia, overweight, and obesity showed an increasing trend with the elevation of school stage (all P<0.05). The detection rate of myopia was higher in girls than in boys, while the detection rate of obesity was lower in girls than in boys (all P<0.05). There were 2 588 individuals with both myopia and overweight/obesity, representing a detection rate of 26.19%, which showed an increasing trend (P<0.05), rising from 25.04% in 2020 to 34.41% in 2024. The detection rates of comorbidity of myopia, and overweight and obesity among primary school, junior high school, and senior high school / vocational high school students were 13.22%, 36.93%, and 45.00%, respectively, showing an increasing trend with the elevation of school stage (P<0.05). The difference between genders was not statistically significant (P>0.05). Conclusions The detection rates of comorbidity of myopia, and overweight and obesity among primary and middle school students in Yanqing District is relatively high and shows an upward trend, with students in higher school stage being the key target group for prevention and control. It is recommended to strengthen health education on the co-prevention of multiple health issues and implement differentiated interventions based on school stages.

Chronic heart failure （CHF） is a complex clinical syndrome caused by ventricular dysfunction， with mitochondrial energy metabolism disorder being a critical factor in disease progression. Heart-Yang deficiency syndrome， as the core pathogenesis of CHF， persists throughout the disease course. Insufficiency of heart-Yang leads to weakened warming and propelling functions， resulting in the accumulation of phlegm-fluid， blood stasis， and dampness. This eventually causes Qi stagnation with phlegm obstruction and blood stasis with water retention， forming a vicious cycle that exacerbates disease progression. According to the theory of reinforcing Yang， the clinical experience of the traditional Chinese medicine （TCM） master Tang Zuxuan in treating CHF with heart-Yang deficiency syndrome， and achievements from molecular biological studies， this study innovatively proposes an integrated research framework of "TCM syndrome differentiation and staging-mitochondrial metabolism mechanisms-intervention with Yang-reinforcing prescriptions" which is characterized by the integration of traditional Chinese and Western medicine. Heart-Yang deficiency syndrome is classified into mild （Stage Ⅰ-Ⅱ）， severe （Stage Ⅲ）， and critical （Stage Ⅳ） stages. The study elucidates the precise correlations between the pathogenesis of each stage and mitochondrial metabolism disorders from theoretical， pathophysiological， and therapeutic perspectives. The mild stage is characterized by impaired biogenesis and substrate-utilization imbalance， corresponding to heart-Yang deficiency and phlegm-fluid aggregation. Linggui Zhugantang and similar prescriptions can significantly improve the expression of peroxisome proliferator-activated receptor gamma co-activator-1α（PGC-1α）/silent information regulator 2 homolog 1 （SIRT1） and ATPase activity. The severe stage centers on oxidative stress and structural damage， reflecting Yang deficiency with water overflow and phlegm-blood stasis intermingling. At this stage， Zhenwu Tang and Qiangxin Tang can effectively mitigate oxidative stress damage， increase adenosine triphosphate （ATP） content， and repair mitochondrial structure. The critical stage arises from calcium overload and mitochondrial disintegration， leading to the collapse of Yin-Yang equilibrium. At this stage， Yang-restoring and crisis-resolving prescriptions such as Fuling Sini Tang and Qili Qiangxin capsules can inhibit abnormal opening of the mitochondrial permeability transition pore （MPTP）， reduce cardiomyocyte apoptosis rate， and protect mitochondrial function. By summarizing the characteristics of mitochondrial energy metabolism disorders at different stages of CHF， this study explores the application of the theory of reinforcing Yang in treating heart-Yang deficiency syndrome and provides new insights for the clinical diagnosis and treatment of CHF.

ObjectiveTo establish a new noninvasive， simple， and convenient clinical predictive model by identifying independent predictive factors for rebleeding after endoscopic therapy in cirrhotic patients with esophagogastric variceal bleeding （EGVB）， and to provide a basis for individualized risk assessment and development of clinical intervention strategies. MethodsCirrhotic patients with EGVB who were diagnosed and treated in The First Affiliated Hospital of Xi’an Medical University from September 2018 to October 2023 were enrolled as subjects， and according to whether the patient experienced rebleeding within 1 year after endoscopic therapy， they were divided into rebleeding group with 93 patients and non-rebleeding group with 84 patients. Clinical data were collected and analyzed. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. A Logistic model was established based on the results of the univariate and multivariate analyses， and the receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the accuracy of the model. R software was used to visualize the model by plotting a nomogram， and the Bootstrap method was used for internal validation of the model. ResultsThe multivariate analysis showed that red blood cell count （RBC）， cholinesterase （ChE）， alkaline phosphatase （ALP）， albumin （Alb）， thrombin time （TT）， portal vein trunk diameter， sequential therapy， and primary prevention were independent predictive factors for rebleeding. Based on the results of the multivariate analysis， a logistic model was established as logit（P）=-0.805-1.978×（RBC）+0.001×（ChE）-0.020×（ALP）-0.314×（Alb）+0.567×（TT）+0.428×（portal vein trunk diameter）-2.303×［sequential therapy （yes=1， no=0）］-2.368×［primary prevention （yes=1， no=0）］. The logistic model （AUC=0.928， 95% confidence interval ［CI］： 0.893—0.964， P<0.001） had a better performance in predicting rebleeding than MELD score （AUC=0.603， 95%CI： 0.520—0.687， P=0.003）， Child-Pugh class （AUC=0.650， 95%CI： 0.578—0.722， P=0.001）， and FIB-4 index （AUC=0.587， 95%CI： 0.503—0.671， P=0.045）. The model had an optimal cut-off value of 0.607， a sensitivity of 0.817， and a specificity of 0.817. Internal validation confirmed that the model had good predictive performance and accuracy. ConclusionSequential therapy， implementation of primary prevention， an increase in RBC， and an increase in Alb are protective factors against rebleeding， while prolonged TT and widened main portal vein diameter are risk factors. The logistic model based on these independent predictive factors can predict rebleeding and thus holds promise for clinical application.

Objective To explore scientific and accurate prediction methods for the incidence of hand, foot, and mouth disease in the post-pandemic era, and to address modeling challenges caused by abnormal fluctuations in case numbers from 2020 to 2023. Methods The seasonal index was used to pre-process the data. The traditional seasonal autoregressive integrated moving average (SARIMA) model, singular spectrum analysis (SSA)-ARIMA model, ARIMA-Long short-term memory (LSTM) model, and SSA-ARIMA-LSTM model were used to fit the incidence from 2013 to 2023, and the incidence of hand, foot and mouth disease in 2024 was predicted. The real data collected in 2024 were used as the test set to compare the prediction performance of the models. Results The fitting performance of the constructed models was as follows: the ARIMA model had MAE=107.50 and RMSE=144.53, the SSA-ARIMA model showed MAE=2.84 and RMSE=4.33, the ARIMA-LSTM model achieved MAE=99.46 and RMSE=131.59, and the SSA-ARIMA-LSTM model had MAE=96.35 and RMSE=132.13. In terms of prediction performance, the ARIMA model resulted in MAE=151.64 and RMSE=146.70, the SSA-ARIMA model demonstrated MAE=41.22 and RMSE=57.01, the ARIMA-LSTM model yielded MAE=220.75 and RMSE=257.89, and the SSA-ARIMA-LSTM model recorded MAE=58.83 and RMSE=72.06. Conclusion The SSA-ARIMA model has the best fitting degree and the highest prediction accuracy, and is suitable for predicting the incidence trend of hand, foot and mouth disease.

Objective To compare the performance of seasonal difference autoregressive moving average exogenous variable model (SARIMAX), backpropagation neural network (BPNN), long short-term memory network (LSTM), and various combination models in fitting and predicting the incidence of hand, foot, and mouth disease (HFMD), and to provide a reference for optimizing HFMD prediction and prevention and control decisions. Methods Taking the monthly HFMD incidence data in Changsha from 2010 to 2024 as the training set, and the monthly HFMD incidence data from January to August 2025 as the validation set, the single models, SARIMAX-BPNN, SARIMAX-LSTM and weight combination models were constructed respectively. The R², mean absolute percentage error (MAPE), mean absolute error (MAE), and root mean square error (RMSE) were used to evaluate the model fitting and prediction performance. Results Based solely on MAPE, the LSTM model showed the best fitting and prediction performance. A comprehensive analysis of multiple indicators including R², MAPE, MAE, and RMSE indicated that the combination models had superior prediction performance. Compared with the LSTM, RMSE predicted by equal weight combination, different weight combination and SARIMAX-BPNN decreased by 40.97%, 37.50%, and 25.00%, respectively, while MAPE increased by 124.84%, 96.90%, and 89.69%, respectively. The fitting effect was as follows: LSTM > unequal weight combination > equal weight combination > SARIMAX-LSTM > SARIMAX-BPNN > BPNN > SARIMAX. The prediction performance was as follows: SARIMAX-BPNN > unequal weight combination > equal weight combination > LSTM > SARIMAX-LSTM > BPNN > SARIMAX. Conclusion SARIMAX-BPNN combination or weighted combination of multiple different models are two more robust combination strategies for predicting the incidence trend of hand, foot and mouth disease in Changsha.

Intraoperative cell salvage (IOCS) has been widely applied as an important blood conservation measure in surgical operations. However, there is currently a lack of clinical practice guidelines for the implementation of IOCS in patients with malignant tumors. This report aims to provide clinicians with recommendations on the use of IOCS in patients with malignant tumors based on the review and assessment of the existed evidence. Data were derived from databases such as PubMed, Embase, the Cochrane Library and Wanfang. The guideline development team formulated recommendations based on the quality of evidence, balance of benefits and harms, patient preferences, and health economic assessments. This study constructed seven major clinical questions. The main conclusions of this guideline are as follows: 1) Compared with no perioperative allogeneic blood transfusion (NPABT), perioperative allogeneic blood transfusion (PABT) leads to a more unfavorable prognosis in cancer patients (Recommended); 2) Compared with the transfusion of allogeneic blood or no transfusion, IOCS does not lead to a more unfavorable prognosis in cancer patients (Recommended); 3) The implementation of IOCS in cancer patients is economically feasible (Recommended); 4) Leukocyte depletion filters (LDF) should be used when implementing IOCS in cancer patients (Strongly Recommended); 5) Irradiation treatment of autologous blood to be reinfused can be used when implementing IOCS in cancer patients (Recommended); 6) A careful assessment of the condition of cancer patients (meeting indications and excluding contraindications) should be conducted before implementing IOCS (Strongly Recommended); 7) Informed consent from cancer patients should be obtained when implementing IOCS, with a thorough pre-assessment of the patient's condition and the likelihood of blood loss, adherence to standardized internally audited management procedures, meeting corresponding conditions, and obtaining corresponding qualifications (Recommended). In brief, current evidence indicates that IOCS can be implemented for some malignant tumor patients who need allogeneic blood transfusion after physician full evaluation, and LDF or irradiation should be used during the implementation process.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.