Heart failure is increasingly prevalent in terms of mortality and morbidity worldwide, with myocardial infarction (MI) being a significant contributor. This work presents lisinopril (LN) and tannic acid (TA)-loaded nanoparticles (LNTA NPs), tailored for the pathological features of acute MI. The particle diameter of TA NPs was 325 nm with a polydispersity index of 0.002. Consequently, a fucoidan (Fu)/collagen (Col) hydrogel (HGL) exhibiting favorable mechanical and biological properties has been developed, with LNTA NPs integrated into the HGL-LNTA, resulting in several synergistic therapeutic effects. The incorporation of Fu enhanced the injectability and mechanical strength of the HGL, while endowing the Col material with anticoagulant characteristics vital for prospective clinical applications as cardiovascular biomaterials. LNTA NPs decreased the production of reactive oxygen species (ROS) and enhanced the activities of superoxide dismutase (SOD), glutathione (GSH), and glutathione peroxidase (GPx). The LNTA NPs, administered directly to the infarct site, not only provide mechanical support but also significantly restore cardiac function (***p < 0.001) and protect myocardial tissue by scavenging ROS and alleviating inflammation. Collectively, our results have validated the superior therapeutic efficacy of HGL-LNTA in treating MI patients, positioning it as a promising strategy for MI management.

Atrial fibrillation (AF) remains a leading driver of stroke and heart failure, yet timely diagnosis is frequently hindered by its asymptomatic nature and the limitations of current screening methods. This study aimed to develop and validate a highly accurate, interpretable, and scalable machine learning (ML) framework—TabPFN—for AF detection using standard 12-lead electrocardiogram (ECG)-derived features. To this end, we conducted a dual-center temporal validation study utilizing 248,324 ECG records across three distinct datasets: an internal cohort (n = 220,327), an external validation cohort (n = 6,181), and a temporal validation cohort (n = 21,816). The TabPFN model was trained on 12 clinical ECG features, such as PR interval, Paxis, and QTc, and compared against eight other ML architectures, including ensemble learning and neural networks. Model interpretability was established using SHAP (SHapley Additive exPlanations) to quantify feature contributions, and the framework was deployed via a web-based clinical interface. Results indicated that the TabPFN model demonstrated superior diagnostic efficacy, achieving an area under the receiver operating characteristic curve (AUROC) of 0.9711 in the internal cohort, 0.9797 in the external cohort, and 0.9766 in the temporal validation cohort. It outperformed traditional logistic regression (AUC 0.8687) and maintained a remarkably low Brier score (0.0474), indicating excellent calibration. Furthermore, SHAP analysis identified the PR interval and Paxis as the primary diagnostic drivers, revealing non-linear associations and physiological “inflection points” for AF presence, while decision curve analysis confirmed a high net benefit for clinical screening across all cohorts. In conclusion, by leveraging a Prior-Data Fitted approach (TabPFN) on standardized ECG features, we established a robust framework that matches the performance of complex deep-learning models while maintaining high interpretability and computational efficiency. This scalable tool, accessible via a web-based platform, bridges the gap between “black-box” AI and clinical practice, offering a practical solution for population-wide AF screening and the reduction of cardiovascular morbidity

Objectives: Myocardial infarction (MI) is linked to high mortality, which highlights the need for early diagnosis and intervention to prevent heart failure. N6-methyladenosine (m6A) methylation of ribonucleic acid (RNA) influences endothelial dysfunction and MI. Here, the effects and associated mechanisms of fat mass and obesity-associated gene (FTO) on vascular endothelial cell (EC) function, as well as myocardial damage in mice following MI were investigated. Material and Methods: A human umbilical vein EC (HUVEC) model of oxygen-glucose deprivation (OGD) as well as a mouse MI model were used to detect MI-induced endothelial and myocardial damage. EC function was examined using cell-counting-kit-8, wound healing, migration, and tube formation assays. Methylated RNA immunoprecipitation (MeRIP) sequencing and RNA sequencing were utilized to analyze the m6A modifications and RNA expression patterns in control and FTO-overexpressing ECs following OGD. FTO and ATP-binding cassette subfamily F member 1 (ABCF1) levels were evaluated using western blotting. The relationship between FTO and ABCF1 was determined using RNA immunoprecipitation-quantitative polymerase chain reaction (RIPqPCR), MeRIP-qPCR, and RNA stability assays. Echocardiography and Masson's trichrome and hematoxylineosin staining were used to measure myocardial injury. Results: FTO expression was reduced in infarcted myocardial tissue and OGD-induced HUVECs (P < 0.01). Functionally, FTO overexpression improved the impaired function of OGD-treated HUVECs and restored myocardial function in MI mice (P < 0.01). Mechanistically, FTO reduced m6A methylation of ABCF1 mRNA and raised ABCF1 levels in OGD-treated HUVECs (P < 0.01). Conclusion: Taken together, our study revealed that FTO overexpression restored OGD-induced endothelial dysfunction and myocardial pathological injury after MI. FTO increased ABCF1 expression in OGD-treated HUVECs through an m6A-dependent mechanism. These findings offer new insights into mitigating EC dysfunction and myocardial injury after MI.

IntroductionTraditional transseptal puncture (TSP) relies on x-ray imaging and anatomical landmarks, which poses challenges in patients with atrial structural variations or overweight. Furthermore, emerging interventional techniques demand precise puncture site localization. This feasibility study evaluates the safety and efficacy of a novel biplane positioning method guided by left atrial (LA) 3D-CT reconstruction for TSP.MethodsA retrospective analysis included 100 atrial fibrillation patients undergoing radiofrequency catheter ablation (RFCA) between July 2023 and March 2024. Preoperative LA-enhanced CT scans were performed to reconstruct 3D models. Key measurements included vertebral height (H), horizontal distance (X) from the target puncture point (O) to the anterior spine edge at 45° right anterior oblique (RAO) view, and vertical distance (Y) between O and the great cardiac vein. Intraoperative biplane localization integrated CT-derived ratios (X/H, Y/H) with fluoroscopy. Statistical analyses compared outcomes across LA size subgroups.ResultsAll patients achieved successful TSP without complications (e.g., cardiac tamponade, thromboembolism). The mean X/H and Y/H ratios were 0.8 ± 0.2 and 0.5 ± 0.1, respectively. Patients with larger LA diameters (≥50 mm) exhibited significantly greater X values (16.8 ± 3.3 mm vs. 13.6 ± 4.2 mm, P = 0.034). In 17 patients with unclear LA posterior borders on fluoroscopy (mean BMI 27.2 ± 3.5 vs. 24.9 ± 3.2 in others, P = 0.009), the method ensured safe puncture. The mean distance from the puncture site to the right inferior pulmonary vein was 24.2 ± 5.5 mm.DiscussionThe LA 3D-CT-guided biplane positioning method demonstrates feasibility, accuracy, and safety for TSP in atrial fibrillation patients, including those with enlarged atria, structural anomalies, or overweight. The protocol is feasible within a limited, single-center cohort.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has rapidly evolved into a pressing global health issue, exacting a formidable and escalating toll on public disease burden. Insulin resistance (IR) serves as a shared pathophysiological pathway for MASLD and cardiometabolic dysfunction. However, the associations between IR surrogate indices, cardiometabolic disease (CMD) and major adverse cardiovascular events (MACE) in MASLD, particularly the comparative predictive performance of these indicators, have yet to be fully elucidated. This large-scale prospective study incorporated 127,195 and 149,402 individuals with MASLD from UK Biobank in CMD and MACE cohort, respectively. Kaplan–Meier analysis was employed to estimate CMD and MACE risks across different IR indices quartiles. Cox regression model and restricted cubic splines (RCS) curve were performed to investigate the associations between IR-related indices, CMD and MACE in MASLD, with threshold effect analysis detecting potential inflection points upon observed nonlinear relationships. Additionally, receiver operating characteristic (ROC) analysis and Harrell’s C-index, along with net reclassification index (NRI) and integrated discrimination improvement (IDI), were utilized to compare the predictive capability of estimated glucose disposal rate (eGDR) and other IR indices. Furthermore, subgroup and sensitivity analysis were conducted to validate the robustness of primary findings. During a median follow-up time of 13.67 and 13.92 years, 29,089 CMD (22.87

OBJECTIVE:To investigate the association between long-term exposure to air pollution and the risk of microvascular complications in individuals with diabetes, and provide the evidence to inform environmental strategies for prevention. METHODS:The data were collected from UK Biobank cohort (n = 9,671). Kaplan-Meier curves and log-rank tests were used to compare cumulative incidence across exposure groups. Cox proportional hazards models were employed to evaluate the associations between air pollutant exposure and the development of microvascular complications, with adjusting for demographic, clinical, and biochemical covariates. Stratified and sensitivity analyses were conducted to assess the robustness of the findings. Additionally, restricted cubic splines were used to explore potential nonlinear relationships between pollutant concentrations and complication risk. RESULTS:With a median follow-up time of 12.4 years, 2,104 participants (21.8%) developed microvascular complications. The Kaplan-Meier analysis demonstrated early divergence in cumulative incidence curves, suggesting an early impact of air pollution exposure on vascular outcomes. After multivariable adjustment, higher levels of air pollution exposure were significantly associated with increased risk of microvascular complications in patients with diabetes. Compared to the lowest quartile, participants in the highest quartile of exposure had elevated risks (NO2: HR = 1.27, 95% CI: 1.12-1.45; PM10: HR = 1.44, 95% CI: 1.27-1.64). These associations remained consistent across stratified and sensitivity analyses. CONCLUSION:Long-term exposure to air pollutants, particularly NO2 and PM10, is associated with an increased risk of microvascular complications among individuals with diabetes. The observed risk appears to be persistent and may begin at relatively low exposure levels, underscoring the need for preventive strategies targeting environmental risk factors.

Gut microbiota and their metabolites are essential for a wide range of human physiological processes, including inflammation, immunity, and homeostasis. The intricate interplay between gut microbiota and the host immune system profoundly influences both the therapeutic response and the immune-related adverse events (irAEs) in cancer patients undergoing immune checkpoint inhibitors (ICIs) therapy. Prior evidence has established the rationale for modulating the gut microbiota to improve the incidence and prognosis of ICI-associated myocarditis. In the future, we may prevent or treat ICI-associated myocarditis by regulating the gut microbiota through methods such as microbiota transplantation, antibiotic regimens, or probiotic supplements. But there is still a considerable distance between research and clinical practice.

This study aimed to develop and validate the magnetocardiography (MCG)-integrated nomogram to improve CAD prediction in patients with normal ECGs. This prospective cohort study enrolled 421 patients undergoing coronary angiography at the Fourth Affiliated Hospital of Soochow University. Participants with normal resting ECGs were included. Clinical data encompassed demographics, vital signs, laboratory/imaging results, comorbidities, and echocardiographic indices. Magnetocardiography (MCG) recordings were acquired via the Cardiomox MCG-9 system under electromagnetic shielding. Nomogram development integrated LASSO-regularized logistic regression to select predictors. Key MCG parameters and conventional biomarkers were incorporated into the nomogram’s graphical scoring system. Model performance was evaluated through AUC, calibration, and clinical utility (decision curve analysis). Analyses used R v4.2.2 and MSTATA v3.1, with p < 0.05 for significance. The nomogram achieved moderate efficacy, with an area under the curve (AUC) of 0.777 (95

BackgroundAtherosclerosis is a chronic vascular disease driven by inflammation, vascular smooth muscle cells (VSMCs) phenotypic switching, metabolic dysregulation, and mitochondrial dysfunction. Idebenone, a coenzyme Q10 analogue with mitochondrial protective activity, may have anti-atherosclerotic potential, but its vascular mechanism remains unclear.PurposeThis study aimed to determine whether idebenone attenuates atherosclerosis by regulating PKM2-mediated metabolic reprogramming and the mitochondrial-Hippo/YAP axis in VSMCs.MethodsApoE-/- mice fed a high-fat diet and ox-LDL-stimulated MOVAS cells were used to evaluate the anti-atherosclerotic effects of idebenone. Histological staining, Western blot, mitochondrial functional analyses, network pharmacology, transcriptomics, proteomics, and external dataset validation were performed. PKM2 knockdown/overexpression and the MST1/2 inhibitor XMU-MP-1 were used in VSMCs for mechanistic validation.ResultsIdebenone dose-dependently reduced atherosclerotic plaque burden, vascular inflammation, and mitochondrial ultrastructural injury without primarily relying on lipid lowering. In VSMCs, idebenone suppressed ox-LDL-induced phenotypic switching, lipid accumulation, proliferation, and migration. Integrated bioinformatics and proteomics identified PKM/PKM2 as a key idebenone-responsive metabolic node associated with atherosclerotic progression. Mechanistically, idebenone inhibited ox-LDL-induced PKM2, HK2, and LDHA upregulation, restored NAD+/NADH balance and ATP production, reduced mitochondrial ROS, preserved mitochondrial membrane potential, and suppressed mtDNA release. PKM2 silencing mimicked, whereas PKM2 overexpression weakened the protective effects of idebenone. Idebenone also restored Hippo pathway activity and reduced YAP nuclear translocation. MST1/2 inhibitor XMU-MP-1 partially reversed its protective effects.ConclusionIdebenone attenuates atherosclerosis by suppressing PKM2-mediated metabolic reprogramming and restoring mitochondrial–Hippo/YAP homeostasis in VSMCs. These findings support idebenone as a promising metabolic and mitochondrial-targeted candidate for further preclinical anti-atherosclerotic research.

Finerenone, a novel non-steroidal mineralocorticoid receptor antagonist, has demonstrated significant efficacy in the management of myocardial infarction (MI). However, its direct cytoprotective effects on cardiomyocytes and vascular endothelial cells remain unclear. This study was performed to evaluate the cardioprotective and vasoprotective effects of finerenone following MI and to elucidate its underlying mechanisms. An in vitro oxygen-glucose deprivation (OGD) model was utilized to mimic ischemic conditions. H9C2 rat cardiomyoblasts and human umbilical vein endothelial cells were employed to assess the protective effects of finerenone. For in vivo assessment, a murine model of MI was established and treated with oral finerenone for 28 consecutive days. Cardioprotective outcomes were evaluated through electrocardiography, echocardiography, serum biochemical markers, histopathological analyses, and protein expression profiling. Finerenone significantly improved the viability of cardiomyocytes and endothelial cells subjected to OGD, reduced autophagosome accumulation by enhancing autophagosome degradation, inhibited apoptosis, and promoted endothelial cell migration and tube formation capacity. In vivo, finerenone improved cardiac function parameters, reduced serum levels of myocardial enzyme profiles and brain natriuretic peptides, decreased myocardial infarct size, enhanced left ventricular function, and alleviated myocardial inflammation, fibrosis and apoptosis. Mechanistically, finerenone downregulated the expression of ATG5 and apoptosis-related molecules in myocardial tissue, while enhancing the expression of Ang and VEGF involved in angiogenesis. Finerenone confers significant cardioprotection by inhibiting autophagy, apoptosis, and enhancing angiogenesis in both cardiomyocytes and vascular endothelial cells. These findings provide experimental evidence for the clinical utility of finerenone for secondary prevention after MI.

BACKGROUND:Left Ventricular Remodeling (LVR) in hypertension involves both structural and electrophysiological alterations. Magnetocardiography (MCG) non-invasively measures cardiac magnetic fields, potentially reflecting these changes. This study aimed to explore the association between MCG parameters and established Echocardiographic (ECHO) indices of concentric left ventricular remodeling in hypertensive patients. METHODS:In this cross-sectional study, 220 hypertensive patients underwent both ECHO and 9-channel MCG. Patients were categorized based on ECHO into Non-LVR (n = 105) and concentric remodeling groups (n = 115). Fifteen MCG parameters derived from the QRS complex and R-wave were analyzed. Correlations between MCG and ECHO parameters (Left Ventricular Mass Index [LVMI], Interventricular Septal thickness [IVSd], Left Ventricular Posterior Wall thickness [LVPWd], Relative Wall Thickness [RWT]) were assessed. A multivariate associative model combining selected MCG parameters was developed in a 70% subset (n = 154), and its association with ECHO-defined concentric structural phenotype was tested in a separate 30% validation subset (n = 66). RESULTS:After rigorous correction for multiple testing, several MCG parameters demonstrated statistically significant correlations with specific ECHO indices. The maximum current moment of the QRS complex (QRS_MCM) showed positive correlations with IVSd (r = 0.388, p < 0.00083), LVPWd (r = 0.333, p < 0.00083), and RWT (r = 0.392, p < 0.00083). The relative timing parameters QRS_CA ratio and QRS_FMA ratio exhibited significant positive correlations with both IVSd and RWT (r = 0.299-0.339, all p < 0.00083). Patients in the ECHO-defined concentric remodeling group exhibited a distinct MCG profile characterized by increased current moments, altered current angles, and higher depolarization timing ratios compared to the Non-LVR group. The multivariate associative model, incorporating QRS_MCM, R_CA, QRS_CA ratio, and QRS_FMA ratio, showed a strong association with concentric structural phenotype in the development set (AUC = 0.887, 95% CI 0.832-0.942). Critically, this association remained robust and significant when the model was applied to the independent validation set (AUC = 0.856, 95% CI 0.763-0.948). The internal validation confirmed the stability of this associative pattern, though the model is not intended for clinical diagnostic use. CONCLUSION:Specific magnetocardiographic parameters, particularly those reflecting the global strength of ventricular depolarization (QRS_MCM) and the relative timing of electrical events within the cardiac cycle, are significantly and robustly associated with echocardiographic indices of concentric left ventricular remodeling in hypertension. These cross-sectional findings establish a measurable link between MCG-based electrophysiological features and concentric structural alterations in hypertensive patients. Further prospective studies are needed to explore the temporal relationship between electrical and structural remodeling and to determine whether MCG offers insights beyond those obtainable from simpler, more widely available tools such as the ECG.

The albumin-bilirubin (ALBI) score, a liver function indicator, has a not fully established prognostic association with acute myocardial infarction (AMI) mortality. Our study sought to investigate the adjusted association of the ALBI score with all-cause mortality (ACM) in this population. We analyzed the first eligible ICU stay of adults with AMI in MIMIC-IV. ALBI was modeled continuously and using three prespecified grades (Grade 1 ≤ − 2.60, Grade 2 > − 2.60 to ≤ − 1.39, and Grade 3 > − 1.39). Kaplan–Meier curves, Cox models, restricted cubic splines (RCS), receiver-operating-characteristic (ROC) analyses, paired DeLong tests, and incremental discrimination metrics were used for 30-, 90-, 180-, and 360-day ACM. Five random-forest multiple imputations were analyzed and pooled with Rubin’s rules. Global and term-specific proportional-hazards assumptions were tested using scaled Schoenfeld residuals in each completed dataset. Repeated ALBI-specific violations were handled using ALBI × log(time/30 days) interactions, with separate Grade 2 and Grade 3 time interactions in categorical models. Binary RCS-derived high-versus-low ALBI propensity-score matching (PSM) was conducted as a sensitivity analysis. Among 3,153 critically ill AMI patients, 605, 2,059, and 489 were classified as Grade 1, Grade 2, and Grade 3, respectively. In fully adjusted Model 3 including SOFA, continuous ALBI had fixed-effect HRs of 1.43, 1.42, and 1.47 for 30-, 90-, and 180-day ACM. For 360-day ACM, exposure-specific time-varying models yielded day-360 h of 1.18 (0.98–1.43) for continuous ALBI and 1.21 (0.81–1.83) for Grade 3 versus Grade 1. ALBI AUCs were 0.677, 0.674, 0.677, and 0.668, while SOFA+ALBI AUCs were 0.746, 0.736, 0.730, and 0.715. The corresponding SOFA+ALBI versus SOFA ΔAUCs were 0.015, 0.018, 0.021, and 0.020. Continuous NRI and IDI indicated incremental discrimination, but the magnitude was modest. In matched Model 1 Cox analyses, binary RCS-derived high-versus-low ALBI PSM yielded HRs of 1.22, 1.25, 1.31, and 1.30 across the four endpoints. In this single-center retrospective cohort, higher ALBI was associated with higher 30-, 90-, and 180-day ACM, whereas 360-day associations were reported as time-specific estimates because the ALBI-specific proportional-hazards assumption was not met. ALBI showed limited incremental discrimination beyond SOFA. These findings do not establish causality or clinical utility and require external validation.

INTRODUCTION:Dilated cardiomyopathy (DCM) is a leading cause of heart failure and remains a major clinical challenge due to its complex etiology and lack of effective targeted therapies. Sodium overload-induced necrosis, a recently described form of regulated cell death, has emerged as a novel contributor to cardiovascular injury, but its role in DCM remains poorly defined. AIMS:This study aimed to elucidate the molecular signatures of sodium overload-associated cell death and explore their diagnostic and therapeutic relevance in DCM. MATERIALS AND METHODS:We systematically integrated four publicly available transcriptomic datasets (GSE226801, GSE116250, and GSE141910) from human myocardial tissues and in vitro sodium-overload models to identify sodium overload-associated death-related genes (DRGs). Machine learning algorithms were used to screen and validate key hub genes. Experimental validation was performed in a doxorubicin-induced DCM mouse model using Western blotting, quantitative PCR, and immunohistochemistry. Drug-gene interaction analysis was conducted using the Comparative Toxicogenomics Database (CTD). KEY FINDINGS:Four hub genes-BACH2, NXPH4, CD1E, and LIF-were identified as central regulators linking sodium overload to DCM pathogenesis. A diagnostic model incorporating these genes showed robust discrimination between DCM patients and healthy controls across multiple datasets. Furthermore, abrine was identified through CTD analysis as a potential therapeutic candidate capable of simultaneously targeting all four hub genes. SIGNIFICANCE:This study uncovers a novel mechanistic link between sodium overload-induced regulated necrosis and DCM progression. The findings provide new molecular insights into cardiomyocyte death and inflammation in DCM and propose candidate biomarkers and drug targets for precision therapy.

Cardiovascular disease (CVD) poses a major global health burden. The Atherogenic Index of Plasma (AIP) and Cystatin C are novel biomarkers reflecting lipid metabolism disorders and renal/micro-inflammatory status, respectively. Their combined indicator (AIP-Cys, the product of AIP × Cystatin C) may provide improved predictive value beyond either marker alone. This study aimed to investigate the predictive role of AIP-Cys for the risk of incident CVD across different glycemic statuses: normal glucose regulation (NGR), pre-diabetes (preDM), and diabetes mellitus (DM). This study was based on the prospective China Health and Retirement Longitudinal Study (CHARLS) cohort. A total of 6,035 participants aged ≥ 45 years without a history of CVD at baseline (2011) were included. The primary exposure was baseline AIP-Cys (the product of AIP × Cystatin C), and the outcome was the first self-reported incident heart disease or stroke event during follow-up (until 2020). Glycemic status was defined based on fasting plasma glucose and glycated hemoglobin levels. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs). Restricted cubic splines and piecewise linear models were applied to analyze nonlinear relationships. Mediation and sensitivity analyses were conducted to verify the robustness of the results. During a median follow-up of 9.0 years, 651 incident CVD cases occurred. In the fully adjusted model, AIP-Cys was independently associated with CVD risk in the overall (HR per unit increase: 1.34; 95

Dilated cardiomyopathy (DCM)-induced heart failure (HF) remains a major global health burden, highlighting the need to identify disease-associated molecular signatures and potential therapeutic targets. In this study, we performed differential expression analysis and weighted gene co-expression network analysis (WGCNA) on the GSE141910 dataset, which identified 138 genes associated with DCM-induced HF. These were further refined to 48 candidate genes using support vector machine-recursive feature elimination (SVM-RFE). Protein-protein interaction (PPI) network analysis revealed 10 hub genes, and external validation identified four core genes—MFAP4, CCDC80, LTBP2, and COL16A1—that were consistently upregulated in DCM-induced HF. Single-cell and functional enrichment analyses indicated that these genes are predominantly expressed in cardiac fibroblasts and may contribute to myocardial fibrosis by activation of the NOTCH signaling pathway. Drug screening suggested beta-naphthoflavone as a potential therapeutic compound. In vivo validation confirmed the upregulation of the core genes through RT-qPCR, western blot, and immunohistochemistry in an isoproterenol (ISO)-induced HF mouse model. In summary, MFAP4, CCDC80, LTBP2, and COL16A1 represent disease-associated transcriptional signatures and potential therapeutic targets for DCM-induced HF, offering novel insights into disease mechanisms and treatment strategies.

BACKGROUND:The escalating prevalence of obesity has made it a critical public health concern. There is an urgent need to identify naturally derived compounds with anti-obesity potential. Britanin (BRI), a bioactive sesquiterpene lactone derived from Inula species, has shown promise in metabolic disorder management, but its anti-obesity mechanisms remain uncharacterized. OBJECTIVES:Combining animal experiments and network pharmacology analysis to explore the effect of BRI in high-fat diet-induced obesity. METHODS:C57BL/6J male mice were used for experiment. A high-fat diet (HFD)-induced obese mouse model was treated with BRI (5/15 mg/kg, i.p.) to validate lipid metabolism and weight loss. Network pharmacology identified potential targets via SwissTargetPrediction, GeneCards and OMIM databases, with molecular docking (CB-DOCK) and PPI network analysis (STRING/Cytoscape). Relevant validations were conducted based on the screened targets. Additionally, a biosafety assessment was performed. RESULTS:In-vivo, 15 mg/kg BRI reduced body weight by 18%, decreased serum TG (-45%, p<0.001), TC (-37%, p<0.001) and LDL-C (-32%, p<0.01) and reversed adipocyte hypertrophy. Thirty-nine intersection targets were identified, with MAPK1, EGFR, PTGS2, MAP2K1 and MAPK8 as top hubs (degree centrality >15). BRI exhibited strong binding affinity (-7.7 to -10.3 kcal/mol) to these targets. Mechanistically, BRI exerts its anti-obesity effects by regulating key targets within the MAPK signaling pathway, particularly MAPK1 and inhibited the PPARγ, thereby blocking adipogenesis and promoting the transition of adipose tissue. CONCLUSION:BRI may alleviate obesity by regulating the Mitogen-Activated Protein Kinase signaling pathway, providing a rationale for natural compound-based obesity therapy.

Dilated cardiomyopathy (DCM) is a progressive myocardial disorder lacking reliable molecular biomarkers for early diagnosis. Given the emerging role of protein lactylation in cardiovascular disease, we investigated lactylation-related genes (LRGs) in DCM using transcriptomic data from the GEO database. Differential gene expression and lactylation databases were integrated to identify 18 dysregulated LRGs. Using ensemble machine learning algorithms, six core LRGs (G6PD, PPP1CC, MBP, LSP1, HMGN1, HMGN2) were selected to construct a diagnostic model, which showed robust performance across five external cohorts. Unsupervised clustering revealed two molecular DCM subtypes. Immune infiltration and ssGSEA analyses suggested that core LRGs modulate immunometabolic remodeling. Single-cell RNA-seq analysis confirmed their cell-type-specific distribution, with fibroblasts identified as dominant signaling sources via CellChat analysis. Ferrostatin-1 and Resveratrol were predicted as potential therapeutic compounds targeting core genes. Validation in human and mouse myocardial tissues confirmed differential gene and protein expression. This study uncovers lactylation-driven molecular signatures in DCM and establishes a robust diagnostic model with promising translational potential. By linking lactate metabolism to immune regulation and cardiac remodeling, our findings highlight novel diagnostic markers and potential therapeutic targets for precision intervention in DCM.