White matter degeneration in aging drives cognitive and motor decline. Oligodendrocytes (OLs) and their precursors are central to this process. Their intrinsic aging, marked by differentiation failure, metabolic and mitochondrial deficits, and transcriptional epigenetic dysregulation, causes myelin thinning and axonal support loss. Degeneration is amplified by dysfunctional crosstalk: microglia clear debris poorly and turn inflammatory; astrocytes disrupt lipid balance and secrete inflammatory signals; vascular defects impair metabolic supply; and T cell infiltration injures OLs. We review therapies targeting OL lineage, glial networks, vascular health, and lifestyle. Positioning OLs as integrative hubs of white matter integrity offers new strategies to maintain brain function during aging.

AIM:The aim of this study is to evaluate the efficacy and safety of blood-activating and stasis-removing Chinese patent medicines (BASR-CPMs) during the perioperative period of percutaneous coronary intervention (PCI) for myocardial infarction (MI). METHODS:We searched eight databases (PubMed, Embase, the Cochrane Library, Web of Science, CNKI, WanFang Data, SinoMed, and VIP) from database inception to February 15, 2025, for randomized controlled trials (RCTs) comparing standard care plus BASR-CPMs versus standard care alone (or with other BASR-CPMs) in MI patients undergoing PCI. A Bayesian network meta-analysis was conducted to estimate relative effects. Primary outcomes included major adverse cardiovascular events (MACE) and major adverse cardiac and cerebrovascular events (MACCE), while key secondary outcomes included thrombolysis in MI (TIMI) grade 3 flow, angina, and bleeding events. Risk of bias was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool. The certainty of evidence was evaluated using the GRADE framework. A protocol of the systematic review and network meta-analysis was registered with PROSPERO (CRD420251048208). RESULTS:We included 160 RCTs (21,147 participants) evaluating 25 BASR-CPMs. Regarding hard clinical endpoints, no BASR-CPMs differed significantly from standard care for MACE or MACCE at any time point. For example, Tongxinluo capsule showed no significant reduction in MACE at 1 month (relative risk [RR] 0.62, 95% credible interval [CrI] 0.11 to 1.70; low certainty). Tongxinluo capsule may improve TIMI grade 3 flow immediately after PCI (RR = 1.12, 95% CrI: 1.04-1.26; low certainty) and at 3 months (RR = 1.47, 95% CrI: 1.10-1.98; moderate certainty). Danhong injection (RR = 1.15, 95% CrI: 1.02-1.31) and Shexiang Baoxin pill (RR = 1.15, 95% CrI: 1.02-1.30) may also improve TIMI grade 3 flow immediately after PCI (moderate certainty). For reducing angina incidence at 1 and 6 months, Tongxinluo, Danhong, Salvianolate injection, Shexiang Baoxin, Guanxin Shutong, and Shexiang Tongxin dripping pill showed potential benefits (low to high certainty). Most interventions did not increase bleeding risk, and Tongxinluo possibly reduced adverse effects (low certainty). CONCLUSIONS:Exploratory findings suggest that BASR-CPMs, notably Tongxinluo, Danhong, and Shexiang Baoxin, improve immediate reperfusion and reduce angina recurrence post-PCI in MI patients. These intermediate benefits do not translate into reductions in hard clinical outcomes. Further rigorous RCTs are needed to confirm their long-term impact on MACE and MACCE.

High adsorption capacity and excellent selectivity are two crucial criteria for solid-phase extraction adsorbents to be effectively applied in the separation and purification of proteins. Herein, a novel flower-like microsphere structure grafted with poly(ethylene glycol) diamine (NH2-PEG-NH2) were proposed for the high selective isolation and superior adsorption capacity of bovine hemoglobin. This flower-like microsphere adsorbent, abbreviated as ZnO@PDA@PEG, was formed via self-polymerization of dopamine on the ZnO microspheres surface and substantially modified with poly(ethylene glycol) diamine through the Michael reaction, which provides numerous binding sites for promoting a superior adsorption capacity of 50,745.9 mg g-1 toward bovine hemoglobin. Moreover, this adsorbent exhibited favorable adsorption selectivity toward bovine hemoglobin by reducing the nonspecific adsorption by virtue of the unique steric hindrance effect of poly(ethylene glycol) diamine. The adsorbed bovine hemoglobin was easily collected by using 0.5% sodium dodecyl sulfate with a recovery rate of 87.9%. Circular dichroism spectra indicated no conformational change for bovine hemoglobin during the adsorption-elution process. Finally, ZnO@PDA@PEG demonstrated outstanding separation performance toward bovine hemoglobin from the complex bovine whole blood sample, successfully addressing the critical challenge of nonspecific adsorption during the selective isolation of target proteins from real-world biological matrices.

OBJECTIVE:To evaluate harms reporting practices in placebo-controlled randomized clinical trials (RCTs) of Chinese herbal medicine (CHM) formulas published in Quartile 1 (Q1) English-language and Tier-1 Chinese journals. METHODS:This systematic survey evaluated harms reporting in CHM formula RCTs. We systematically identified eligible RCTs published in English-language journals Q1 (2024 Journal Citation Reports) and Chinese Tier-1 journals (2023 Traditional Chinese Medicine ranking). Two reviewers independently evaluated harms reporting using items derived from the CONSORT Extension for Harms (CONSORT Harms) recommendations and CHM formula-specific reporting elements. RESULTS:Among 96 eligible RCTs (49 English Q1; 47 Chinese Tier-1), only 19.8% (n = 19) of trials had a published protocol, with a significantly higher proportion in English Q1 journals (p < 0.001). Only one trial explicitly reported adherence to the CONSORT Harms extension (2004 or 2022). Syndrome differentiation was significantly more frequent in Chinese Tier-1 journals than in English Q1 journals (76.6% vs. 38.8%, p < 0.001). Sixty-seven percent of studies (n = 64) did not report methods for assessing the relationship between harms and interventions, and 15.6% (n = 15) relied solely on clinical judgment. Eighty percent of studies (n = 77) did not report statistical methods for harms analysis. In the results section, 62% (n = 59) did not present harms data in tables. CONCLUSIONS:Harms reporting in CHM formula RCTs remains inadequate. Routine adoption of the CONSORT Harms framework, together with CHM formula-specific harms reporting elements, is needed to improve transparency and facilitate the interpretation of harms data in CHM formula research.

Traditional Chinese medicine (TCM) faces persistent gaps between evidence generation and clinical use. Building on Qian Xuesen's theory of open complex giant systems (OCGSs) and its qualitative-to-quantitative metasynthesis, we advance a complex-systems evidence framework tailored to TCM's hallmarks: a holistic perspective and pattern-based diagnosis and therapy. The framework integrates systems science, artificial intelligence, and allied disciplines to coordinate qualitative and quantitative approaches and to align macro-level effectiveness evaluation with micro-level mechanistic inquiry. It organizes multi-source evidence into a four-phase loop-production, differentiation, application, and validation: (1) standardizes evidence production; (2) conducts integrated evaluation along the disease-pattern-formula axis; (3) supports individualized effectiveness evaluation and decision-making; and (4) uses real-world feedback to verify and refine evidence. By linking clinical phenotypes, pathways, and outcomes into an evidence chain, the framework is intended to improve clinical decision quality and accelerate translational research. Beyond TCM, it offers a generalizable model for complex interventions acting on complex human systems, positioning TCM research for international scientific dialogue and modernization.

Since Ephedra Herba (ephedra) and its major alkaloid ephedrine were prohibited as dietary supplements due to their adverse effects on the cardiovascular and central nervous system (CNS), most studies have focused on their amphetamine-like effects and neurotoxicity. However, ephedra also has a long history of use in the treatment of various CNS diseases (known as "Zhong Feng" syndrome) according to two thousand years of traditional Chinese medicine (TCM) records. Pharmacokinetic reports have also demonstrated that alkaloids of ephedra can quickly penetrate the blood-brain barrier (BBB) once absorbed into the blood and there are multiple alkaloids derived from ephedra which have been identified as natural sympathomimetic drugs. These drugs are capable of interfering with several types of neurotransmitter, and have an especially potent effect on monoamine neurotransmitters. The effects of ephedra on CNS therefore remain both contradictory and confusing. In this review, we summarized the available evidence of pharmacology and toxicology of ephedra and ephedrine on CNS, and aimed to clarify their effects. Given the unmet need for more efficient treatments of neurological disorders, ephedra is potentially valuable herbal medicine which may provide a promising avenue for development of treatments and encourage further drug research and development (R&D).

Background: Core outcome sets (COS) are minimum sets of outcomes that should be measured and reported in all clinical trials in specific areas of health or health care. COS use is recommended by the Cochrane Handbook. Although research has shown that the uptake of COS in Cochrane systematic reviews (SRs) is low, it has improved. Chinese researchers published a large number of SRs each year, however, the uptake of COS in SRs conducted by Chinese researchers is unclear. Methods: Four diseases (lung cancer, ischemic stroke, type 2 diabetes mellitus, and knee osteoarthritis) have with high-quality COS and are among the top 25 causes of disability-adjusted life-years (DALYs) in China. We will search SRs led by authors from China, published in Chinese- or English-language journals. We will assess the overlap in scope between SRs and COS as well as the extent of overlap between the COS outcomes and the SR outcomes. Then we will conduct an online survey to identify the knowledge and perceptions of COS among authors of included SRs. We will conduct qualitative interviews of systematic reviewers who complete the online survey until is saturation reached. Discussion: Understanding systematic reviewers’ knowledge and perceptions of COS may help the future dissemination and implementation of COS among systematic reviewers in China.

BackgroundAnthracycline-induced cardiotoxicity is a major factor affecting the long-term prognosis of cancer patients. Atrial arrhythmias, as common manifestations of cardiotoxicity, significantly impair quality of life and may compromise the effectiveness of anticancer therapy, representing a significant clinical challenge. Wenxin Keli (WXKL), a traditional Chinese medicine formulation with the effects of replenishing qi, nourishing yin, and promoting blood circulation, has demonstrated potential anti-arrhythmic benefits. However, high-quality evidence supporting its application in the field of cardio-oncology remains limited. This study aims to systematically evaluate the efficacy and safety of WXKL in patients with anthracycline-induced atrial arrhythmias.MethodsThis is a multicenter, randomized, double-blind, placebo-controlled clinical trial. A total of 152 eligible participants will be enrolled and randomly assigned to receive either WXKL or placebo for 3 months, followed by a 3-month follow-up period. The primary outcome is the proportion of patients free from atrial arrhythmias at 3 months, defined as the absence of atrial fibrillation (AF) episodes lasting ≥30 s or premature atrial contractions (PACs) ≥100 beats per 24 h on Holter monitoring. Secondary outcomes include AF burden, PACs count, echocardiographic parameters, cardiac biomarkers (cTnI and NT-proBNP), quality of life (FACT-G), functional status (ECOG), clinical symptom scores, and anxiety scores (SAS) at 3 and 6 months, as well as safety assessments.DiscussionThis study is designed to provide high-level clinical evidence for the use of WXKL in the treatment of anthracycline-induced atrial arrhythmias. By incorporating both PACs and AF as a composite endpoint, the study aims to more comprehensively capture the overall burden and dynamic progression of atrial arrhythmias, and to inform cardio-protective strategies during cancer therapy.Trial registration:http://itmctr.ccebtcm.org.cn/zh-CN, International Traditional Medicine Clinical Trial Registry Platform, ITMCTR2025000704.

Background:Myocardial ischemia-reperfusion injury (MIRI) remains a major clinical challenge in the management of acute myocardial infarction. Ginsenoside Rg1, a bioactive component from Panax ginseng, exhibits cardioprotective properties but suffers from poor bioavailability and limited tissue targeting. Methods:We designed a novel DNA nanocarrier, Rg1@pTDN, by loading Rg1 onto a tetrahedral DNA nanostructure (TDN) modified with the myocardial-targeting peptide CREKA. The physicochemical characteristics of Rg1@pTDN were evaluated by DLS, zeta potential analysis, AFM, and gel electrophoresis. Biodistribution, biosafety, and cellular uptake were assessed in vitro and in vivo. Cardioprotective efficacy was evaluated in a murine MIRI model and a H/R injury cell model. Mechanistic studies focused on oxidative stress and endoplasmic reticulum (ER) stress pathways. Results:Rg1@pTDN exhibited uniform nanoscale structure, high Rg1 loading efficiency, and good colloidal stability. In vivo imaging revealed preferential accumulation in cardiac tissue following intravenous administration. Rg1@pTDN was well tolerated and improved survival, cardiac function, and myocardial histology in MIRI mice. It significantly reduced serum CK-MB concentrations and oxidative stress markers (MDA), while increasing antioxidant enzyme activities (SOD, GSH-Px). In vitro, Rg1@pTDN suppressed ROS accumulation and H/R-induced apoptosis in H9c2 cells. Furthermore, Rg1@pTDN alleviated H/R-induced ER stress, as shown by decreased GRP78 and CHOP mRNA expression and reduced phosphorylated PERK and CHOP protein levels. Conclusion:Rg1@pTDN represents a promising nanotherapeutic strategy for myocardial ischemia-reperfusion injury through targeted delivery and dual inhibition of oxidative and ER stress. This DNA-based platform offers a versatile approach for enhancing the efficacy of natural compounds in cardiovascular disease.

Data has emerged as a premier,novel factor of production and the central engine driving the growth of the digital economy.The empowerment of Traditional Chinese Medicine(TCM)with data elements to foster new quality productive forces is an intrinsic prerequisite for the high-quality development of both the TCM discipline and its associated industries.This integration is poised to play a pivotal role in catalyzing systemic transformations in TCM's scientific research paradigms and clinical models,upgrading the traditional TCM industry,and nurturing a host of emerging and future-oriented industrial sectors.As a novel form of data infrastructure,the Trusted Data Space(TDS)serves as a critical vehicle for facilitating the unimpeded circulation of data resources.In this context,constructing a Trusted Data Space for Traditional Chinese Medicine(TCM-TDS)to empower the inheritance and innovation of TCM through data elements holds profound contemporary significance. In the digital era,data is a core asset,and its effective utilization defines advanced productive forces.For TCM,a field rich with empirical knowledge,this digital transformation presents an unprecedented opportunity to shift from experience-based practices to evidence-based,data-driven methodologies.This transition allows for the validation of traditional theories with modern scientific rigor,bridging historical wisdom with contemporary data analytics,thereby enhancing the precision,personalization,and efficacy of diagnostics and treatments.A TDS provides the foundational governance,legal,and technical framework for this shift,enabling secure and sovereign data sharing among research institutions,hospitals,and enterprises.It addresses the critical need to dismantle data silos and foster a collaborative ecosystem for innovation,which is especially crucial given the sensitive nature of medical data and the need for patient privacy. This paper elaborates on the construction pathway for a TCM-TDS,detailing its foundational infrastructure,functional architecture,and the associated technical and business workflows.The objective is to formulate a replicable and scalable construction model for the TCM sector that can support the demands of a nationally integrated data market and promote the value of TCM data as a key economic asset.The discussion outlines a detailed pathway,including the physical and virtualized resources for data handling,and the essential modules for data governance,identity management,and access control,ensuring a robust and secure operational environment for all participants. Furthermore,this paper proposes several developmental countermeasures and recommendations for the application of the TCM-TDS.These include fostering institutional and mechanistic innovations,developing high-quality datasets and enhancing the underlying data infrastructure,advancing theoretical and technological innovations in digital and smart TCM,and leveraging diverse application scenarios—from drug discovery to personalized health management—to drive the formation of a comprehensive TCM data ecosystem and promote industrial development.The successful implementation of the TCM-TDS will ultimately depend on this multi-faceted approach,cultivating a vibrant ecosystem that spurs new avenues for industrial growth and contributes significantly to societal well-being and public health.

BackgroundMyocardial infarction (MI) poses a formidable health challenge, frequently necessitating management through percutaneous coronary intervention (PCI). However, PCI comes with potential complications that can impact patient outcomes. Traditional Chinese medicine (TCM), particularly the utilization of Chinese patent medicines with blood-activating and stasis-resolving properties, offers another approach to enhance PCI efficacy and improve patient quality of life. The aim of this study is to assess the comparative efficacy and safety of blood activating and stasis removing Chinese patent medicines for the perioperative period of PCI for MI.MethodsThis systematic review and network meta-analysis will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search strategy will be implemented across seven electronic databases to identify relevant studies. Eligible studies will be limited to randomized controlled trials that compare any Chinese patent medicine (added to standard care) with standard care or another treatment in patients in the perioperative period of PCI after MI. Two independent reviewers will screen all retrieved citations, extract pertinent data, and assess the risk of bias. We will conduct Bayesian random-effects network meta-analysis and network meta-regression. To elucidate whether the intervention has an important impact on certain outcomes within the perioperative period of PCI for MI, we will conduct a patient values and preferences survey to determine the minimum important difference for outcomes. We will assess the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework.DiscussionThis study will provide new insights into the efficacy and safety of blood activating and stasis removing Chinese patent medicines for the perioperative period of PCI for MI patients, providing help for future clinical practice and research.Ethics and disseminationEthical approval is not required for this review. The findings will be disseminated through publication in a peer-reviewed academic journal, presentations at scientific conferences, and outreach via various media platforms.

The combined use of traditional Chinese and Western medicines is a distinctive and widely adopted medical practice in China, particularly in the management of chronic diseases and the treatment of major illnesses. However, fundamental differences in chemical composition, pharmacological mechanisms, and theoretical frameworks introduce distinctive safety challenges, characterized by latent risks, mechanistic complexity, and interindividual variability. Conventional safety evaluation paradigms, largely developed for single-drug scenarios, are inadequate to support accurate risk identification and evidence-based decision-making in this context, particularly under conditions of polypharmacy and long-term exposure. From a clinically driven perspective, this study systematically examines the key challenges in evaluating the safety of combined Chinese and Western medication and analyzes the principal features of associated adverse reactions. These include delayed and nonspecific clinical manifestations that complicate early recognition; multi-level interaction mechanisms involving both pharmacokinetic and pharmacodynamic processes; and marked heterogeneity arising from patient-specific factors, comorbidities, genetic susceptibility, and TCM syndrome differentiation. In addition, inconsistencies in data quality, underreporting in routine clinical documentation, and variability in outcome definitions further hinder robust signal interpretation. Collectively, these factors impede early detection, causal attribution, and effective risk stratification in clinical practice, while also limiting the reproducibility, comparability, and external validity of existing evidence. To address these limitations, we propose a clinically oriented, digital intelligence-driven safety evaluation framework designed to align regulatory science with real-world clinical needs. The framework is structured as a system encompassing four interconnected core components: intelligent prediction, risk identification, mechanistic validation, and digital decision-making. Intelligent prediction integrates artificial intelligence techniques with multi-source heterogeneous data to enable proactive risk screening prior to treatment initiation and to support stratified patient selection. Risk identification leverages real-world data sources, including electronic health records and spontaneous reporting systems, to detect safety signals. Mechanistic validation combines network pharmacology and experimental models to elucidate the biological basis of adverse drug interactions and to analyze causal pathways underlying observed clinical signals, thereby bridging the gap between clinical evidence and mechanism. Digital decision-making incorporates advanced technologies such as digital twins and knowledge graphs to translate population-level evidence into individualized risk prediction, dynamic monitoring, and real-time clinical decision support, ultimately improving precision in medication management. By integrating data-driven analytics with mechanism-based experimentation, this framework establishes a translational pathway linking risk prediction, evidence generation, mechanistic interpretation, and clinical application. It enables continuous evidence updating, dynamic risk monitoring across treatment cycles, and personalized intervention strategies that evolve with accumulating data. Overall, this study proposes a novel methodological paradigm for the safety evaluation of combined Chinese and Western medication. It provides theoretical support for advancing regulatory science in TCM and offers practical guidance for improving clinical safety management. Furthermore, it lays the foundation for the future development of intelligent pharmacovigilance systems capable of supporting precision medicine in complex therapeutic contexts.

Evidence-based medicine (EBM), formalized in the 1990s, has redefined clinical practice by advocating the integration of research evidence, clinical expertise, and patient values. This paradigm has introduced methodological rigor through randomized controlled trials (RCTs) to establish causality, systematic reviews to synthesize findings, and the GRADE approach to evaluate evidence based on risk of bias, inconsistency, indirectness, imprecision, and publication bias. These advancements have shaped clinical guidelines, reduced practice variability, and influenced medical education toward evidence-based inquiry. Despite its contributions, EBM faces challenges in the evolving landscape of modern medicine. The lengthy process of evidence generation, often requiring years for trials and guideline updates, limits responsiveness to emerging health needs, as observed during the COVID-19 pandemic. The external validity of RCT results is constrained by strict inclusion criteria, posing difficulties in applying findings to diverse patient populations with comorbidities. Additionally, the siloed nature of evidence complicates comprehensive care for multifactorial conditions, while the annual influx of over one million medical publications overwhelms traditional synthesis methods. Artificial intelligence (AI) presents a promising avenue to address these issues, leveraging capabilities in processing heterogeneous data. Natural language processing may enhance literature analysis, machine learning could identify patterns in complex datasets, and causal inference might improve the reliability of observational data insights. These technologies hold potential to accelerate evidence development and tailor it to individual needs. This paper proposes digital intelligent evidence-based medicine (i-EBM) as a conceptual evolution of EBM, designed for the AI era. i-EBM envisions a three-layered framework. The data foundation layer aims to integrate structured evidence from RCTs, domain knowledge such as biomedical ontologies and traditional Chinese medicine principles, and multi- modal patient data, including electronic health records, genomics, and wearable device outputs. Knowledge graphs are proposed to link these elements into a unified, computable knowledge network. The intelligent processing layer seeks to apply AI for evidence retrieval, data extraction, quality assessment, and synthesis, potentially using large language models to assist these processes. The knowledge service layer intends to provide dynamic guidelines and individualized predictions, supported by ongoing human-machine collaboration to ensure clinical relevance and ethical considerations. i-EBM has the potential to mitigate EBM's limitations by facilitating real-time evidence updates, reducing knowledge fragmentation through integrated data, and offering personalized decision support. For instance, it may support precision medicine by connecting diverse data sources, with applications possibly extending to fields like oncology or traditional Chinese medicine. Future research could explore autonomous AI systems, optimized clinical workflows, and governance frameworks to address data privacy, bias, and global standardization. In conclusion, i-EBM offers a theoretical framework to extend EBM principles, harnessing AI's potential alongside human expertise to advance medical research and practice. Meanwhile, for issues such as the quantitative study of the complex intervention characteristics and syndrome differentiation patterns of traditional Chinese medicine, i-EBM can provide methodological support in data integration, pattern recognition, and causal inference, offering potential tools and insights for uncovering the intrinsic regularities of TCM evidence and optimizing its evaluative framework.

Background:Coronary artery disease (CAD) remains a leading cause of global mortality and disability. CAD patients face tradeoffs between antithrombotic therapy benefits and bleeding risks, underscoring the need to incorporate patient values and preferences into clinical guidelines. Establishing minimal important differences (MIDs) for patient-important outcomes supports clinical guideline development by determining the smallest change in outcomes that patients consider important. However, directly conducting patient surveys to establish MIDs presents several methodological challenges. Methods:We established a multidisciplinary working group to guide the MID investigation. Using a three-phase process, we identified key outcomes through literature review and discussion. We will develop draft health outcome descriptions by synthesizing evidence from clinical guidelines and qualitative studies, supplemented with patient interviews, and refine the drafts through iterative cognitive interviews. We then designed outcome-specific draft MID questionnaires and will employ cognitive interviews to assess clarity and comprehensibility. Discussion:This study will develop standard materials for surveying patient values and determining MIDs in Chinese CAD patients. The resulting methodology will support future investigations into patient-important outcomes and provide critical evidence for clinical guideline development.

Background: "Qi deficiency" (a pathological state where the body's vital energy (Qi) is insufficient or weakened, impairing physiological functions and diminishing the body's ability to perform daily activities, defend against illness, and maintain homeostasis) syndrome is considered a critical syndrome in traditional Chinese medicine (TCM) and is associated with poor prognosis in heart failure (HF). This study investigates the clinical, metabolic, and transcriptomic differences between heart failure patients with and without Qi deficiency syndrome. Methods: 56 heart failure patients were evaluated using a Qi deficiency syndrome scale and divided into Qi deficiency syndrome (QD) and non-Qi deficiency (non-QD) groups based on the median score. Clinical characteristics, including baseline N-terminal pro-B-type natriuretic peptide (NT-proBNP), left ventricular ejection fraction (LVEF), total diuretic use during hospitalization, and 90-day rehospitalization rates, were compared between the groups. Differentially expressed genes (DEGs) and differential metabolites were identified, followed by enrichment analyses and validation using qPCR and Western blot in AC16 cardiomyocytes. Results: QD patients exhibited significantly higher NT-proBNP levels, lower LVEF, and increased 90-day rehospitalization rates. Metabolomic profiling revealed lipid metabolism disruptions, notably in linoleic acid and phospholipid pathways. Transcriptomic analysis highlighted 17 DEGs, including CISD2, a critical mitochondrial regulator, which was downregulated in QD patients. Correlation analysis identified significant associations between DEGs (e.g., CISD2, BPGM) and lipid metabolites such as PC (16:0/P-16:0). Functional knockdown of CISD2 in AC16 cells led to upregulation of lipid oxidation enzymes ALOX15 and CYP1A2, linking CISD2 dysfunction to lipid metabolic dysregulation. Conclusion: Qi deficiency is associated with more severe heart failure symptoms, worse prognosis, and distinct metabolic and transcriptomic profiles, particularly in lipid metabolism. CISD2 emerges as a potential therapeutic target, offering new avenues for integrating molecular insights with TCM approaches to optimize HF management.

BACKGROUND:The pathological process of atherosclerotic cardiovascular disease (ASCVD) involves complex interactions between metabolic dysregulation and inflammatory responses. The stress hyperglycemia ratio (SHR) and neutrophil-to-lymphocyte ratio (NLR), as biomarkers reflecting metabolic stress and systemic inflammation respectively, have demonstrated significant value in ASCVD prognosis assessment. This study aims to investigate the predictive role of combined SHR and NLR indicators for all-cause mortality in ASCVD patients and their clinical applicability. METHODS:ASCVD patients were identified from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and National Health and Nutrition Examination Survey (NHANES) databases, stratified by SHR/NLR tertiles. Multivariable Cox regression, restricted cubic splines, time-dependent ROC, and machine learning models assessed mortality associations. RESULTS:Among 6159 patients, the highest SHR tertile showed increased mortality (NHANES: HR = 1.20, 95 % CI 1.08-1.34; MIMIC-IV: HR = 2.27, 95 % CI 1.44-3.57). The highest NLR tertile showed elevated risk (NHANES: HR = 1.56, 95 % CI 1.39-1.74; MIMIC-IV: HR = 1.61, 95 % CI 1.03-2.52). The combined high SHR/NLR group exhibited the most pronounced risk (NHANES: HR = 1.54, 95 % CI 1.35-1.77; MIMIC-IV: HR = 2.90, 95 % CI 1.70-4.93), with significantly improved predictive accuracy. CONCLUSION:The combined SHR-NLR assessment effectively quantifies combined metabolic-inflammatory injury and provides superior prognostic stratification for ASCVD patients compared to individual biomarker evaluation. These findings highlight the clinical potential of this dual-biomarker approach for enhancing risk prediction, though further prospective validation is warranted to establish its predictive utility across various patient populations.

Background Artificial intelligence medical diagnostic devices (AIMDDs) show strong potential but face barriers to clinical use, emphasizing the need for rigorous clinical research. Objective We assessed current AIMDD research, key challenges, and future directions. Methods A scoping review followed Arksey and O'Malley's methodological framework and the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews guidelines. PubMed, Web of Science Core Collection, and the Cochrane Database of Systematic Reviews (January 2020–December 2024) were searched on AIMDD design, implementation, and evaluation. Two independent researchers screened and extracted data from the literature using predefined criteria. Results Ninety-seven articles met the inclusion criteria. Machine learning and deep learning approaches dominated across diverse disease fields, with oncology being the most frequent (41 %). The key challenges identified include insufficient quantity, quality, representativeness, and diversity of data; research designs that do not adequately address clinical needs; poor patient selection; poorly defined gold standards; lack of external and prospective validation; and a disconnect between validation strategies and clinical practice. Additionally, issues such as the “black box” phenomenon, overfitting, and data privacy concerns hinder clinical translation. Completeness and standardization of reporting were also found to be lacking. Conclusions Significant challenges remain in the development and clinical application of AIMDD. To facilitate their clinical translation, improvements are needed in dataset optimization, clinically driven research design, development of evaluation frameworks, enhanced interpretability, and standardized reporting and validation of algorithms.

Objective To identify the chemical constituents and blood-absorbed prototype components of Xijiasong Formula (XJS) and to elucidate its potential anti-arrhythmic mechanisms. Methods Ultra-high performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-MS/MS)was employed to identify the chemical constituents and blood-absorbed prototype components of XJS under both positive and negative ion modes. Targets of the blood-absorbed components and arrhythmia-related targets were retrieved from multiple traditional Chinese medicine and disease databases. The intersection targets were obtained to construct a “component-disease-target” network and a protein-protein interaction (PPI) network, from which key active components and core hub targets were screened. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently performed for the intersecting targets. Results A total of 132 chemical constituents were preliminarily identified from XJS, among which 17 were blood-absorbed prototype components, mainly including phenolic acids, terpenoids, flavonoids,esters, and fatty acids. Network pharmacology analysis showed that AKT serine / threonine kinase 1 (AKT1),protein kinase cAMP-activated catalytic subunit alpha (PRKACA), tumor necrosis factor (TNF), interleukin-6 (IL6), and mitogen-activated protein kinase 3 (MAPK3) were the core hub targets involved in the anti-arrhythmic effects of the formula. GO enrichment analysis suggested that the blood-absorbed components were mainly enriched in biological processes such as regulation of myocardial contraction and action potential, in cellular components such as voltage-gated ion channel complexes, and in molecular functions including ion channel activity. KEGG pathway enrichment analysis indicated that XJS exerted anti-arrhythmic effects mainly by regulating multiple key signaling pathways, including adrenergic signaling in cardiomyocytes, cyclic adenosine monophosphate / cyclic guanosine monophosphate-protein kinase G (cAMP / cGMP-PKG) signaling, mitogenactivated protein kinase (MAPK) signaling, and calcium signaling pathways. Conclusion This study preliminarily identifies the blood-absorbed prototype components of XJS and clarifies the potential core targets and key regulatory pathways underlying its anti-arrhythmic effects. These findings provide experimental evidence and theoretical support for the rational clinical application of this formula and for further investigation into its underlying mechanisms.