ObjectiveThis paper aims to investigate and evaluate the staged efficacy and safety of the representative empirical prescription of the “Zhu Ke Jiao” theory， Qijia Rougan prescription， combined with entecavir in the treatment of hepatic fibrosis in chronic hepatitis B. MethodsA multicenter randomized controlled clinical study was conducted， and 101 patients diagnosed with chronic hepatitis B-related hepatic fibrosis （CHB-HF） who met the diagnosis and inclusion criteria were randomly assigned to an observation group （Qijia Rougan prescription + entecavir） and a control group （entecavir）. The treatment duration was 24 weeks. Liver stiffness measurement （LSM）， fibrosis-4 index （FIB-4）， portal vein diameter， hepatitis B serology， biochemical indicators， hepatic fibrosis markers in serum ［hyaluronic acid （HA）， laminin （LN）， procollagen Ⅲ peptide （PⅢP）， and type Ⅳ collagen （Ⅳ-C）］， and traditional Chinese medicine syndrome scores were used as efficacy evaluation indicators. Efficacy assessments and explorations of different staged subgroups of Qijia Rougan prescription were conducted according to LSM values based on the Metavir pathological staging standard. ResultsA total of 98 cases were included for statistical analysis， with 49 cases in the observation group and 49 in the control group. The general data of the patients in both groups were comparable. Compared with the same group before treatment， the observation group showed a significant reduction in LSM and FIB-4 （P<0.01）， as well as notable improvements in LN， Ⅳ-C， and various TCM syndrome scores （P<0.05， P<0.01）. When compared to the control group after treatment， the observation group demonstrated significant improvements in LSM， FIB-4， and various TCM syndrome score indicators （P<0.05， P<0.01）， indicating that the observation group performed better than the control group. Subgroup analysis of the regression of hepatic fibrosis stages showed that compared to the same group before treatment， the observation group had better improvement in regression of stages F2 and F3 （P<0.05）. When compared to the control group after treatment， the observation group exhibited superior improvement in regression of stage F3 （P<0.05）. No adverse events occurred in either group during the treatment period. ConclusionCompared with entecavir alone， the combination of Qijia Rougan prescription and entecavir significantly improves the degree of hepatic fibrosis and clinical TCM symptoms in patients. The optimal intervention period is primarily during stage F3， which is a potential “interception” point of the “Zhu Ke Jiao” theory.

The chronicity of infectious diseases is an important field in the collaborative research of traditional Chinese and Western medicine. The warm disease theory of pathogen invading nutrient and blood aspects in traditional Chinese medicine （TCM） takes the struggle between healthy Qi and pathogenic Qi and cementation of Yin as the core pathogenesis， providing a unique theoretical framework for explaining the common pathology of infectious chronic diseases. This theory originated from Yin-Yang interaction in the Internal Classic and was enriched with WU Youke's theory of intruding pathogen interacting and lingering in blood vessels and YE Tianshi's theory of long-term illness entering collaterals. Combining the theory with modern medical knowledge， our team has condensed the dynamic pathogenesis model of deficiency （nutrient and blood aspects） and excess （pathogen） interacting in the blood collaterals of Yin aspect， the core feature of which is the four-dimensional interactions of cause （pathogen characteristics）， location （three Yin locations of diseases）， nature （deficiency and excess）， and potential （transmission trend）. The common pathology of infectious chronic diseases is reflected in interactions. That is， the interactions between nutrient and blood deficiency （immune exhaustion and metabolic disorder） and pathogen excess （pathogen persistence and fibrous hyperplasia） in the liver collaterals （Jueyin）， kidney collaterals （Shaoyin）， lung collaterals （Taiyin） and other blood collaterals of Yin aspect form the pathological damage characterized by immune inflammatory response-continuous tissue damage with excessive repair. Taking the inheritance and innovative development of classics as the main line， this paper systematically discusses the scientific connotation of the theory of pathogen invading nutrient and blood aspects and the paths of inheritance and innovation and clarifies the original significance of this theory in the chronic development of infectious diseases. Furthermore， taking clinical diseases as an example， this paper reflects the guiding value of this classical theory in the modern diagnosis and treatment of infectious diseases with integrated traditional Chinese and Western medicine and the application potential of this theory in solving complex medical problems through the construction of the innovative paradigm of precise diagnosis and treatment with integrated traditional Chinese and Western medicine.

ObjectiveThis paper aims to conduct the feature analysis and correlation analysis on the ocular collateral features and differential metabolites in patients with chronic hepatitis B （CHB） complicated by glucose metabolism disorder （GMD），particularly those with the damp-heat syndrome type，by integrating shadowless scleral imaging and metabolomics technologies. MethodsA total of 313 patients were recruited from the Hepatology and Endocrinology Outpatient Departments of Public Health Clinical Center of Chengdu according to the inclusion/exclusion criteria，and they were divided into a CHB group and a CHB complicated by GMD groups （damp-heat syndrome group and non-damp-heat syndrome group）. All patients underwent high-definition ocular image acquisition and feature extraction using an intelligent analysis system for shadowless scleral imaging to analyze the differences in the counting of morphological feature scores of ocular collaterals among groups. By using a digital sampling method，24 patients from each group were randomly selected，along with 20 healthy volunteers，for untargeted metabolomic analysis of peripheral serum. Differential metabolites were identified，statistically analyzed，and subjected to potential biomarker analysis and pathway enrichment. Spearman method was performed to conduct the correlation analysis on the differential ocular collateral features and differential metabolites，followed by correlation network construction. ResultsCompared with those in the CHB group，patients with CHB complicated by GMD showed significant changes in ocular collateral feature scores such as "hillock"，"blood vessels"，and "pale dusky coloration" （P<0.05）. In comparison with those in the healthy group，metabolites including N-acetylglucosamine，acetylhomoserine，and myo-inositol （AUC>0.7） were identified as potential biomarkers for the disease. Compared with those in the CHB complicated by GMD group with non-damp-heat syndrome，patients with damp-heat syndrome exhibited significant changes in feature scores of "plaques"，"yellow coloration"，"spleen"，and "gallbladder" （P<0.05）. In comparison with those in the healthy group，metabolites such as O²′-4a-cyclic tetrahydrobiopterin，theobromine，xanthurenic acid，and L-glutamic acid 5-phosphate （AUC>0.7） were identified as potential biomarkers for the damp-heat syndrome type. The Spearman correlation analysis reveals weak to moderate linear correlations between the differential scleral collateral features and metabolites. By constructing a "disease-syndrome" network of ocular diagnosis and metabolites，"xanthurenic acid-gallbladder" and "theobromine-plaque/yellow coloration" were identified as specific molecular-phenotypic correlated biomarker clusters for CHB complicated by GMD with dampness-heat syndrome. ConclusionPatients with CHB complicated by GMD demonstrate differential ocular diagnostic features and serum metabolites corresponding to disease states and dampness-heat syndrome. These objective biomarkers can guide both clinical syndrome differentiation and medication. The macro-micro integration based on ocular feature clusters and potential metabolic biomarkers offers an innovative approach to a combined traditional Chinese and Western medicine diagnosis and treatment model for this disease.

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.

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.

Chrysophanol(Chr)and physcion(Phy)are primary active ingredients of a well-known traditional Chinese medicine namely rhubarb(Chinese name:Dahuang),and their glucuronides have been revealed as the dominant forms presenting in rats after oral administration.Either Chr or Phy has two glycosylation sites,resulting in a pair of positional isomers for glucuronides of either compound(CG1&CG2 and PG1&PG2).To confirmatively identify these glucuronides,energy-resolved mass spectrometry(ER-MS)was used to pursue the fragmentation trajectories of the targeted fragment ions,and the resultant breakdown graphs that were described by the optimal collision energy(OCE)were expected to exhibit the differences of glycosidic bond cleavage between the isomers.Quantum chemical calculation was thereafter conducted to produce the bond dissociation energy(BDE)of the glycosidic bonds.The isomers were unambiguously identified through applying the positive correlation rule between OCE and BDE.Fortunately,the glucuronides of Chr and Phy in vivo were observed through liver microsomes incubationin vitro.ER-MS was utilized to collect the Gaussian-shaped breakdown graphs in response to the neutral loss of 176 Da,and the absolute values of OCE were compared between positional isomers.The results revealed that CG1(-32.31 eV)>CG2(-31.61 eV),and nonetheless,PG1(-30.00 eV)Chr-8-GluA(-48.787 kJ/mol),and nonetheless,Phy-1-GluA(-48.672 kJ/mol)