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 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 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.

Background/Aims: The pathophysiology of refractory gastroesophageal reflux disease (RGERD), which differs from proton pump inhibitor dependent gastroesophageal reflux disease (DGERD), remains incompletely elucidated. This study aims to compare esophageal motility patterns, transdiaphragmatic pressure gradients (TPG), and reflux profiles between RGERD and DGERD patients, and to delineate dynamic pressure gradient-esophagogastric junction (EGJ) interactions in these patients. Methods: In this retrospective study, 274 patients who underwent 24-hour impedance-pH monitoring and high-resolution manometry, along with an assessment of proton pump inhibitor responsiveness, were classified as RGERD (32.5%), DGERD (54.4%), or non-GERD (13.1%). Clinical characteristics, TPG, esophageal motility, and reflux metrics were compared between RGERD and DGERD patients. Subgroup analysis excluding hiatal hernia (HH) was conducted to investigate the pathophysiology of RGERD. Results: The RGERD group exhibited a significantly higher proportion of chest pain compared to the DGERD group. Regarding reflux profiles, RGERD patients without HH (RGERDHH- group) experienced increased weakly acidic reflux (P < 0.001) and prolonged bolus exposure (P = 0.006) compared to their counterparts (DGERDHH- group). Mechanistically, the RGERDHH- group showed reduced lower esophageal sphincter basal pressure (P = 0.010) and EGJ contractile integral (P = 0.005). Notably, following a wet-swallow, the RGERDHH- group experienced the significant elevation in gastric pressure and TPG. Correlation analyses revealed weakly acidic reflux and bolus exposure were positively correlated with gastric pressure variation, and inversely correlated with lower esophageal sphincter basal pressure. Conclusions Transient gastric pressure elevation and compromised EGJ barrier function drive weakly acidic reflux and esophageal bolus exposure. This pressure gradient-barrier mismatch underpins the refractoriness of RGERD.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher among individuals with inflammatory bowel disease (IBD) than in the general population. Emerging evidence indicates that the development of MASLD in patients with IBD may occur independently of traditional metabolic risk factors, suggesting a unique pathophysiological mechanism distinct from conventional MASLD pathways. Bile acids (BAs), which act as critical signaling molecules in enterohepatic circulation, play an essential role in maintaining gastrointestinal homeostasis through bidirectional gut–liver axis communication. These molecules are increasingly recognized as pivotal regulators in the progression of both MASLD and IBD. While previous studies have characterized the dynamics of BA in blood or fecal samples under both conditions, a comprehensive understanding of their metabolic profiles and the associated interactions within the gut–liver axis is still lacking. This review synthesizes current evidence from studies employing BA metabolomics to investigate IBD and MASLD. By focusing on BA signatures, we summarize conserved alterations between these two conditions and their potential mechanisms of disease progression. Our review advances understanding of BA-mediated pathways in IBD and MASLD, providing a foundation for assessing their roles in contributing to the pathogenesis of MASLD in patients with IBD.

Objective To analyze the status of willingness to participate in health science popularization (HSP) and its influencing factors among medical workers in Guangdong Province. Methods A total of 462 medical workers in Guangdong Province were recruited as the study subjects using a stratified convenience sampling method. The Questionnaire on Influencing Factors of Willingness to Participate in Health Science Popularization, developed by the research team, was used to investigate their willingness to participate in HSP and related variables, including previous communication experience, attitude, moral belief, descriptive norm, injunctive norm, self-efficacy, and social support. Hierarchical regression analysis was used to identify the influencing factors of willingness to participate in HSP. Results The median and 25^th and 75^th percentiles score of willingness to participate in HSP was 4.0 (3.8, 4.5), indicating a moderately high level of willingness. The HSP participation willingness score was positively correlated with scores for previous communication experience, attitude, moral belief, descriptive norm, injunctive norm, self-efficacy, and social support (Spearman correlation coefficients were 0.513, 0.384, 0.507, 0.533, 0.463, 0.556, and 0.435, respectively; all P<0.01). Hierarchical regression analysis showed that previous communication experience, moral belief, descriptive norm and self-efficacy positively predicted willingness to participate in HSP (all P<0.05). Medical workers in the non-Pearl River Delta region had lower willingness than those in the Pearl River Delta region for HSP participation (P<0.05). Conclusion There is still room for improving willingness for HSP participation among healthcare professionals in Guangdong Province. It is recommended to enhance self-efficacy through communication skills training, strengthen professional ethics education, foster a positive peer engagement atmosphere, and intensify resource support and capacity building for HSP in the non-Pearl River Delta region, to improve HSP participation willingness among medical workers in Guangdong Province.