Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

OBJECTIVE To analyze and identify the metabolites of pirtobrutinib （PTN） in rats， and clarify the possible metabolic pathways of PTN in rats. METHODS Six rats were intragastrically administered with 10 mg/kg PTN suspension. Blood samples were collected from the rats 30 minutes before administration and at 0.25， 0.5， 1， 2， 4， 6， 8， 12， 24 hours after administration. Urine and feces samples were collected 12 hours before administration and 24 hours after administration. UHPLC- Orbitrap Exploris 240 system combined with Compound Discoverer 3.0 and Xcalibur 2.0 software were adopted for structural identification and metabolic pathway analysis of PTN metabolites in rat plasma， urine， and feces. RESULTS A total of 29 PTN metabolites were identified， including 17， 19 and 22 metabolites in plasma， urine and feces， respectively. The metabolic pathways of PTN mainly included oxidation， sulfation， glucuronidation， etc.， and its metabolites were mostly combination products of two or more different metabolic forms. In detail， a total of 26 metabolites were associated with phase Ⅰ metabolic reactions （14 oxidation metabolites， 9 reduction/dehydrogenation metabolites， 8 demethylation metabolites， and 5 hydrolysis metabolites）. Meanwhile， a total of 20 products were involved in phase Ⅱ metabolites （14 sulfation metabolites and 8 glucuronic acid binding metabolites）. CONCLUSIONS PTN exhibits a diverse range of metabolites in rat fecal samples， with the primary metabolic pathways being oxidation， sulfation， glucuronidation， and others.

Real-world study (RWS), based on multi-source data from real medical environments, is gradually becoming an important supplement to traditional randomized controlled trials, and its application in the field of transfusion medicine is becoming increasingly widespread. This article systematically reviews the definition and methodological system of RWS, examines its application cases in clinical blood transfusion research, and discusses the advantages, limitations, and future research directions of RWS, aiming to provide a reference for evidence-based research in blood transfusion medicine.

Real-world study (RWS), based on multi-source data from real medical environments, is gradually becoming an important supplement to traditional randomized controlled trials, and its application in the field of transfusion medicine is becoming increasingly widespread. This article systematically reviews the definition and methodological system of RWS, examines its application cases in clinical blood transfusion research, and discusses the advantages, limitations, and future research directions of RWS, aiming to provide a reference for evidence-based research in blood transfusion medicine.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Nicotinamide adenine dinucleotide (NAD⁺) is a central and pleiotropic metabolite involved in multiple cellular energy metabolism, such as cell signaling, DNA repair, protein modifications, and so on. Evidence suggests that NAD⁺ levels decline with age, obesity, and hypertension, which are all significant CVD risk factors. In addition, the therapeutic elevation of NAD⁺ levels reduces chronic low-grade inflammation, reactivates autophagy and mitochondrial biogenesis, and enhances antioxidation and metabolism in vascular cells of humans with vascular disorders. In preclinical animal models, NAD⁺ boosting also extends the health span, prevents metabolic syndrome, and decreases blood pressure. Moreover, NAD⁺ storage by genetic, pharmacological, or natural dietary NAD⁺-increasing strategies has recently been shown to be effective in improving the pathophysiology of cardiac and vascular health in different animal models and humans. Here, we discuss NAD⁺-related mechanisms pivotal for vascular health and summarize recent research on NAD⁺ and its association with vascular health and disease, including hypertension, atherosclerosis, and coronary artery disease. This review also assesses various NAD⁺ precursors for their clinical efficacy and the efficiency of NAD⁺ elevation in the prevention or treatment of major CVDs, potentially guiding new therapeutic strategies.
Humans ; Cardiovascular Diseases/physiopathology* ; NAD/metabolism* ; Animals ; Hypertension/metabolism*

The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans ; Sarcopenia/physiopathology* ; Obesity/physiopathology* ; Aging/physiology* ; Autophagy/physiology* ; Insulin Resistance ; Comorbidity ; Vitamin D/metabolism* ; Gonadal Steroid Hormones/metabolism* ; Gastrointestinal Microbiome ; Mitochondria ; MicroRNAs

To develop a milestone-based evaluation system for the core "knowledge and skills" competency of neurology residents that is tailored to China's medical context, so as to provide precise guidance for their training and assessment.

Objective: Through analyzing the current handling capabilities for complex cases in blood transfusion compatibility detection and the application status of artificial intelligence-assisted (AI-assisted) technologies, this study explores the establishment of an effective AI-augmented protocol for managing challenging blood transfusion compatibility detection. Methods: This research systematically analyzes, designs, and explores an AI-augmented operational workflow for resolving challenging blood transfusion compatibility detection cases. Through three representative case studies, we evaluate its effectiveness, accuracy, and efficiency in addressing real-world diagnostic challenges. Results: The AI-augmented operational model demonstrates significant efficacy in resolving complex blood transfusion compatibility challenges, including complex blood typing, antibody specificity identification, challenging cross-matching, and transfusion strategy formulation. Conclusion: AI-augmented technologies demonstrate immense potential in resolving complex blood transfusion compatibility detections. By enabling intelligent, automated, precise, and standardized solutions, they significantly enhance diagnostic accuracy and operational efficiency, which is critical for ensuring transfusion safety and advancing personalized transfusion medicine. This study delineates both the advantages and existing limitations of AI implementation, explores future developmental trajectories, and provides a theoretical framework and practical implementation pathways for deeper integration of AI in transfusion medicine.

The analysis of nano-micro nuclear particles has attracted significant attention due to the crucial role of their elemental and isotopic characteristics in tracing the origins of particulate matter and assessing its potential risks to human health and the environment.However,challenges persist in obtaining accurate and consistent element profiles and ratios for small-sized nanoparticles due to their low level and the transient nature.In this study,a high-speed digital oscilloscope was integrated with multiple collector inductively coupled plasma mass spectrometry(MC-ICP-MS)to develop a high time-resolution"Event-triggered signal capture"(ETSC)system for single particle analysis.This innovative approach enabled the analysis of element/isotope within rare earth nanoparticles at ag-fg level.The ETSC accurately recorded the complete profile of single particle,event captured by the electron multiplier with nanosecond time resolution,allowing for high-sensitivity element analysis and high-precision isotope analysis of single particles.The results demonstrated that the ETSC system could achieve quantitative analysis of ag levels of ytterbium(Yb)in 50-nm rare earth-doped particles,with a detection limit as low as 38 ag for Yb.Moreover,the isotopic precision of single particle analysis for 173/171Yb could reach 0.047(standard deviation),and the standard error for isotopic analysis of multiple particles could achieve a level of 2‰-3‰(permil)for 173/171Yb.Finally,the capability of ETSC system to analyze environmental samples was demonstrated through the analysis of doped ytterbium oxide nanoparticles.All these findings demonstrated that the ETSC provided a unique method for elemental and isotopic analysis of single nuclear particles.

Objective To investigate the distribution of the traditional Chinese medicine(TCM)constitution types in the patients with nonspecific low back pain(NLBP)and to explore the correlation of the thickness of ligamentum flavum with the age,body mass index(BMI),gender,the presence of diabetes mellitus,and the grading of hypertension.Methods Sixty patients with NLBP admitted to Guangdong Second Traditional Chinese Medicine Hospital from January 2023 to June 2023 were selected as the study subjects.The TCM constitution types of the patients were identified,the thickness of the ligamentum flavum at lumbar vertebrae 4/5 segment(L4/5)disc level was measured by computerized tomography(CT)scanning,and the patients'age,genders,TCM constitution types,BMI,the presence or absence of diabetes mellitus,and hypertension grading were recorded.Correlation analysis and linear regression analysis were used for the exploration of the relevant influencing factors for the thickness of the ligamentum flavum of patients with NLBP.Results(1)The average thickness of ligamentum flavum in the 60 patients with NLBP was(2.60±0.72)mm.(2)The TCM constitutions of NLBP patients were classified into four types,of which blood stasis constitution was the most common,accounting for 21 cases(35.0%),followed by 19 cases(31.7%)of damp-heat constitution,12 cases(20.0%)of phlegm-damp constitution,and 8 cases(13.3%)of qi deficiency constitution.(3)The results of correlation analysis showed that BMI,gender,TCM constitution type and the presence or absence of diabetes mellitus had no influence on the thickness of ligamentum flavum in NLBP patients(P＞0.05),while the age and hypertension grading had an influence on the thickness of ligamentum flavum(P＜0.01).(4)The results of linear regression analysis showed that the age had an influence on the thickness of the ligamentum flavum(b = 0.034,t = 6.282,P＜0.01),while the influence of the hypertension grading had no influence on the thickness of the ligamentum flavum(P＞0.05).Conclusion The TCM constitution type of NLBP patients is predominated by blood stasis constitution,the thickness of ligamentum flavum is significantly affected by the age,and hypertension may be a potential factor affecting the thickness of ligamentum flavum.