OBJECTIVE To establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

OBJECTIVE To investigate the antidepressant effect and underlying mechanism of total triterpenes from Poriae Cutis （PCTT）. METHODS UPLC-Q-TOF-MS technology was adopted to analyze the chemical constituents of PCTT. Network pharmacology was applied to screen the antidepressant active ingredients， key targets and signaling pathways of PCTT， and molecular docking was performed to verify the binding capacity between potential active ingredients and core targets. In animal experiment， mice were intragastrically administered PCTT at doses of 80， 160 and 320 mg/kg for 14 consecutive days. Lipopolysaccharide was used to establish an acute depression mouse model. Subsequently， behavioral assays were conducted. The levels of serum inflammatory factors， hippocampal neurotransmitters and brain-derived neurotrophic factor （BDNF） were detected. Western blot and qPCR assays were adopted to validate the antidepressant mechanism of PCTT. RESULTS A total of 101 chemical constituents were identified in PCTT. Network pharmacology screened out 10 potential active ingredients （including poriacosone B， poriacosone A， pachymic acid， etc.）， six core targets [including tumor necrosis factor （TNF）， peroxisome proliferator-activated receptor， caspase-3， etc.]， as well as multiple signaling pathways including TNF and interleukin-17 （IL-17）. All 10 potential active ingredients exhibited strong binding affinity to the six core targets. Animal experimental results demonstrated that 320 mg/kg PCTT markedly increased the movement distance and movement speed of depression model mice （P＜0.05）， and shortened immobility time in tail suspension test and forced swimming test （P＜0.05）. PCTT reduced serum levels of IL-6， IL-1β and TNF-α， decreased hippocampal glutamate level； it also downregulated the relative mRNA expression of TNF-α， tumor necrosis factor receptor-2 （TNFR2）， phosphoinositide 3-kinase （PI3K） and protein kinase B （AKT）， as well as TNFR2 protein expression and the ratios of phosphorylated-PI3K/PI3K，phosphorylated-AKT/AKT in the prefrontal cortex. Meanwhile， PCTT elevated the levels of 5- hydroxytryptamine， dopamine and BDNF in the hippocampus. CONCLUSIONS PCTT exerts antidepressant effects possibly by regulating the TNF-α/PI3K/AKT signaling pathway to downregulate the expression of pro-inflammatory factors， thereby modulating the release of neurotransmitters and BDNF.

ObjectiveTo evaluate the safety and clinical utilization of traditional Chinese medicine （TCM） formula granules based on real-world data， and to provide evidence for their rational clinical use. MethodsA multicenter， prospective， open-label， observational centralized monitoring study was conducted. Participants who received TCM formula granules in 293 medical institutions throughout China from February 5th， 2020 to May 20th， 2025 were consecutively enrolled. The year of data collection was used as the stratification factor. Demographic characteristics （including sex， age， and concomitant medication use）， information on TCM formula granule use （including mean prescribed dosage and inappropriate use）， and adverse event（AE）/adverse drug reaction（ADR） occurrence and related factors were collected and statistically analyzed. ResultsA total of 42 011 participants were included in the safety set （SS）， with a mean age of （38.34±22.30） years， including 18 693 males and 23 318 females. Among them， 3519 participants （8.38%） had a history of or concomitant diseases. The three most common comorbidities were hypertension （1189 cases， 33.79%）， diabetes mellitus （850 cases， 24.15%）， and coronary heart disease （471 cases， 13.38%）. The top three diagnostic categories were respiratory， thoracic， and mediastinal diseases （7008 cases， 16.68%）， infectious and parasitic diseases （6591 cases， 15.69%）， and gastrointestinal diseases （4580 cases， 10.90%）.Among 41 961 participants with available concomitant medication data， 3332（7.94%） received concomitant medications， and western medicines were the most commonly used concomitant medications （2819 cases， 6.72%）. The mean prescribed dosage of TCM formula granules （expressed as the equivalent dosage of crude herbal pieces） was （158.23±104.86） g in 2020， （131.70±65.84） g in 2021， （130.62±59.96） g in 2022， （86.74±50.61） g in 2023， （118.59±52.01） g in 2024， and （134.38±49.43） g in 2025. The five most frequently prescribed toxic herbs were Kuxingren （Semen Armeniacae Amarum， 2746 cases， 6.54%）， Xixin （Radix et Rhizoma Asari， 2193 cases， 5.22%）， processed Kuxingren （862 cases， 2.05%）， Baiqucai （Herba Chelidonii， 747 cases， 1.78%）， and Wuzhuyu （Fructus Evodiae， 645 cases， 1.54%）. Prescriptions involving incompatible combinations of the "eighteen antagonisms" and the "nineteen mutual inhibitions" were most frequently observed in 2020 （54 cases， 0.503%）， and then decreased markedly， remaining at zero or an extremely low level thereafter. The overall incidence of adverse drug reactions （ADRs） associated with TCM formula granules was 0.057% （24 cases）， indicating a rare occurrence. The annual incidence was 0.028% （3 cases） in 2020， 0 in both 2021 and 2022， 0.065% （5 cases） in 2023， 0.158% （15 cases） in 2024， and 0.226% （1 case） in 2025. Among the 24 patients who experienced ADRs， 15 had inappropriate medication use.Five of the 24 patients used toxic herbs， and all five had inappropriate medication. Multivariate logistic regression analysis showed that no history of drug-related adverse reactions ［OR=0.053， 95%CI（0.006， 0.465）］ and no concomitant medication ［OR=0.315， 95%CI（0.109， 0.911）］ were associated with a lower risk of ADRs. ConclusionTCM formula granules are widely used in clinical practice and exhibit a favorable overall safety. Greater attention should be paid to people with a history of drug-related adverse reactions and those receiving concomitant medications to further improve medication safety.

Objective: To investigate the health literacy level and its influencing factors among the elderly in Shunyi District, Beijing Municipality, so as to provide the evidence for developing health literacy intervention measures and improving the elderly's health literacy level. Methods: From September to November 2024, permanent residents aged ≥60 years in Shunyi District were selected by a multi-stage random sampling method combined with probability proportionate to size sampling method. The Chinese Elderly Health Literacy Questionnaire was used to conduct face-to-face surveys on basic information, health status, and health literacy. The health literacy level of the elderly was analyzed. Multivariable logistic regression model and decision tree model were used to analyze the influencing factors for health literacy level of the elderly. Results: There were 285 males (47.50%) and 315 females (52.50%). The mean age was (68.91±7.38) years. The health literacy level of the elderly was 14.33%. The literacy levels of basic concepts, basic knowledge, and basic skills were 43.33%, 5.33%, and 50.83%, respectively. The literacy levels of scientific aging concept, intrinsic capacity and geriatric syndromes, healthy lifestyle, information acquisition and self-care, health service utilization and chronic disease management, and safety and first aid were 52.33%, 7.17%, 51.83%, 58.83%, 72.00%, and 4.33%, respectively. Multivariable logistic regression analysis showed that educational level (high school/technical secondary school/technical school and above, OR=2.376, 95%CI: 1.020-5.532), monthly household income per capita (1 000-<3 500 yuan, OR=2.973, 95%CI: 1.349-6.555), residence (urban, OR=3.836, 95%CI: 2.071-7.105), and health attention (relatively concerned, OR=4.164, 95%CI: 1.779-9.742) were influencing factors for health literacy level of the elderly. Decision tree model results showed that educational level, monthly household income per capita, residence, and health attention were influencing factors for health literacy level of the elderly, with residence being the main influencing factor. Elderly people living in urban areas, relatively concerned about health, and with high school/technical secondary school/technical school and above educational level had higher health literacy level (40.00%). Conclusions The health literacy level of the elderly in Shunyi District is mainly affected by educational level, monthly household income per capita, residence, and health attention. It is recommended to focus on rural elderly with lower educational level, monthly household income per capita, and health attention.

Objective:To analyze the death cases in Beijing municipal hospitals, identify possible medical quality issues in unexpected death cases, so as to provide a basis for medical quality management in medical institutions.Methods:A total of 432 death cases from Beijing municipal hospitals were included, and their acute physiology and chronic health status were evaluated. Based on the evaluation results and the death risk level determined by the diagnosis-related groups, an average of 10 cases were selected from each hospital. A total of 186 cases from 20 hospitals were selected for clinical diagnosis and treatment process evaluation, those cases with problems in the diagnosis and treatment process were defined as unexpected deaths.Results:According to expert judgment, 19.89% (37/186) of the examined deaths had medical quality issues. The main medical quality issues included delayed diagnosis and treatment of patient condition changes (15 cases), inadequate preoperative evaluation (12 cases), failure to consult as required(11 cases), and inadequate prevention of venous thromboembolism (7 cases).Conclusions:Medical institutions should attach importance to the analysis of death cases, address the medical quality issues in the diagnosis and treatment of unexpected death cases, continuously improve medical quality management.

A quantitative analytical method was established for 275 kinds of metabolites in plasma based on ultra-high performance liquid chromatography-triple quadrupole mass spectrometry/multiple reaction monitoring-selected ion monitoring(UHPLC-QQQ-MS/MRM-SIM)technique.Based on UHPLC-high resolution(HRMS)/full MS-parallel reaction monitoring(PRM)technique,165 kinds of lipid metabolites in plasma were qualitatively identified and quantitatively detected to address the analytical challenges of lipid isomers.This quantitative metabolomics approach was successfully applied to a rat myocardial infarction study,identifying and quantifying 372 kinds of metabolites in total.Comparative analysis with the sham-operated group revealed significant alterations in 59 kinds of plasma metabolites in myocardial infarction rats.Key metabolic pathways,which included amino acid metabolism(alanine,aspartate,and glutamate metabolism;glycine,serine,and threonine metabolism,etc.),one-carbon unit metabolism,and tricarboxylic acid cycle,were significantly disrupted.

Lymphoma is a highly heterogeneous malignancy characterized by complex molecular regulatory mechanisms that result in significant differences in aggressiveness and prognosis across its subtypes.Gene copy number alteration(CNA)analysis,an emerging technology,has become a pivotal tool in the precision re-search and management of lymphoma.By detecting DNA deletions,amplifications,and chromosomal copy number changes,CNA analysis addresses the limitations of traditional cytogenetic techniques,enhances the ac-curacy of subtype classification,and aids in evaluating tumor heterogeneity and disease progression.This re-view provides a comprehensive summary of CNA detection methods and their applications in lymphoma,with a focus on recent advancements in the field.It offers a comparative analysis of CNA detection techniques and discusses their role in precision diagnosis,subtype classification,monitoring disease progression,predicting therapeutic resistance,and assessing prognosis.Additionally,the review explores the potential applications of CNA analysis in uncovering molecular regulatory mechanisms,optimizing therapeutic strategies,and impro-ving patient survival outcomes.

Objective To explore the pathological features of bronchiolar adenoma(BA)and its specific high-resolution computed tomography(HRCT)signs,and to differentiate BA from minimally invasive adenocarcinoma(MIA)using a non-invasive preoperative method.Methods A total of 80 patients with BA and 130 patients with MIA were retrospectively selected,and the clinical information and HRCT features were compared.All cases were divided into development set and test set at a 7︰3 ratio.Logistic regression analysis was used to screen the independent predictors of MIA and construct a model.Results There were significant differences in age,lobe distribution,density,vacuole sign,tumor-related vessels number(TVN),and distance to pleura(DTP)between BA and MIA patients(P<0.05).Age,density,TVN,DTP and long diameter were identified as independent predictors of MIA.A model was constructed,with area under the curve(AUC)of 0.887 and 0.884 in the development and test sets,respectively.Conclusion The model based on HRCT morphological features of BA and MIA demonstrates superior diagnostic performance compared to individual CT morphological features.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.