Coronary heart disease (CHD) is the leading cause of cardiovascular mortality worldwide, and its management requires patients to make complex, preference-sensitive treatment decisions. Decisional conflict is common in this population and adversely affects treatment adherence and outcomes, yet its association with eHealth literacy and the underlying psychological mechanisms remain unclear.

This study examined the association between eHealth literacy and decisional conflict in patients with CHD, tested the chain-mediating roles of cyberchondria and psychological inflexibility, and identified latent profiles of eHealth literacy.

A cross-sectional design was employed, and patients with CHD were recruited from tertiary Grade A hospitals. The survey battery comprised the eHealth Literacy Scale, the Decisional Conflict Scale, the Cyberchondria Severity Scale, the psychological inflexibility subscale of the Multidimensional Psychological Flexibility Inventory, and requisite demographic items.

eHealth literacy was significantly and negatively associated with decisional conflict, and this association was mediated by cyberchondria and psychological inflexibility. From a person-centered perspective, two latent subgroups of eHealth literacy were identified: a high eHealth literacy profile and a low eHealth literacy profile. One-way analysis of variance indicated that the optimal latent profiles differed significantly in decisional conflict, cyberchondria, and psychological inflexibility.

This study not only helps identify priority targets for interventions addressing decisional conflict in patients with CHD, but also elucidates the psychological pathways through which eHealth literacy shapes treatment decision-making, thereby informing heterogeneity-informed, tailored clinical interventions.

To systematically investigate the associations of macro-environmental exposures-specifically, county-level access to exercise opportunities (ATEO)-and population-level physical inactivity (PI) with overall and subtype-specific cardiovascular-kidney-metabolic (CKM) mortality across the United States, and to explore the heterogeneity of these associations across distinct sociodemographic and geographic subgroups.

We conducted a county-level ecological study using 2014-2019 data from CDC WONDER for CKM mortality and from County Health Rankings for physical activity measures. County-level age-adjusted CKM mortality rates were compared across quartiles of access to exercise opportunities and physical inactivity, with stratification by sex, race, and urbanization. Rate ratios (RRs) for CKM mortality and its three components (cardiovascular, kidney, and metabolic) were estimated using quasi-Poisson generalized linear models, with adjustment for year only (Model 1) or for comprehensive demographic and socioeconomic covariates (Model 2).

A clear geographic gradient emerged: counties in the South had the least exercise access, the highest inactivity levels, and the greatest CKM mortality burden. Greater access to exercise opportunities was inversely associated with total CKM mortality [Q4 vs. Q1, RR,0.89 (0.87-0.90)], but this benefit was not uniform across CKM components-while cardiovascular mortality decreased with better access (RR, 0.89), diabetes and renal failure mortality showed unexpectedly higher rates in high-access counties. Regarding physical inactivity, higher levels were associated with an overall elevation in total CKM mortality [Q4 vs. Q1, RR 1.23 (1.22-1.25)], primarily driven by cardiovascular disease (RR 1.24). However, the associations with the other two components were less consistent: diabetes mortality showed a modest increase (RR 1.23) but with a non-monotonic gradient across quartiles, while renal failure mortality unexpectedly decreased in the highest inactivity quartile. These general patterns were observed across most demographic and geographic subgroups, although the effect magnitudes varied by sex, race, and urbanization.

Our findings demonstrate that limited access to exercise opportunities and higher physical inactivity are associated with elevated total CKM mortality, with cardiovascular disease being the predominant driver. While the associations with diabetes and renal failure showed some heterogeneity, these results support population-wide efforts to reduce physical inactivity and targeted environmental investments in underserved communities as potential strategies to alleviate the combined burden of cardiovascular, diabetic, and renal mortality.

The triglyceride-glucose (TyG) index is gaining considerable attention as an emerging marker of metabolic syndrome. The TyG index is strongly associated with atherosclerosis and cardiovascular disease development. However, the impact of the TyG index on the functional outcome at discharge of patients receiving standardized treatment and its variability in different types of stroke have not been fully elucidated.

Baseline data, neurological scale scores, and laboratory indicators were retrospectively collected from ischemic stroke patients at Lianyungang Second People's Hospital and Lianyungang First People's Hospital. Patients were categorized into good and poor functional outcome groups based on the modified Rankin Scale (mRS) score at discharge. A logistic regression model was used to evaluate the relationship between the TyG index and functional outcome at discharge of patients with atherosclerotic and cardioembolic stroke.

A total of 854 patients were included in the analysis, including 712 patients with large artery atherosclerotic (LAA) and 142 patients with cardioembolism (CE). Subgroup comparisons based on different discharge-level functional outcomes showed that the TyG index of the 187 patients in the poor functional outcome at discharge group was higher than that of patients in the good functional outcome group (8.98 vs. 8.69). The restricted cubic curve revealed a nonlinear association between the TyG index and discharge-level functional outcome among LAA stroke patients (for nonlinearity, p = 0.026). Multivariate logistic regression showed that the TyG-Q2 and TyG-Q3 groups were not associated with discharge-level functional outcome compared with the TyG-Q1 group, and the TyG-Q4 group was a risk factor for the occurrence of poor functional in the LAA group (odds ratio (OR) = 2.63, 95% confidence interval (CI) = 1.52-4.55). After adjusting for age, National Institute of Health Stroke Scale (NIHSS) score at admission, glucose, diastolic blood pressure, uric acid, and low-density lipoprotein, the TyG-Q4 group remained a risk factor for the occurrence of poor functional outcome at discharge in the LAA group (OR = 2.38, 95% CI = 1.03-5.51). However, the TyG index did not correlate with functional outcome at discharge in the CE group. Of note, this negative CE subgroup result should be interpreted cautiously due to the limited sample size and insufficient endpoint events, which may cause inadequate statistical power and false-negative outcomes; thus, the potential predictive value of the TyG index for discharge-level functional outcome in CE stroke cannot be excluded.

The TyG index was identified as a risk factor for poor functional outcome at discharge in LAA stroke but was not correlated with the functional outcome at discharge of CE stroke. Considering the limited sample size and insufficient statistical power of the CE subgroup, this negative result should not be over-interpreted, and large-scale clinical studies are required to further explore the potential prognostic value of the TyG index in cardioembolic stroke.

To develop and validate machine learning models for predicting severe intraventricular hemorrhage (SIVH) in preterm infants using only prenatal and intrapartum variables, and to identify the optimal model.

This multicenter retrospective cohort study included preterm infants (gestational age ≤34 weeks) who required noninvasive or invasive respiratory support, using data from the Jiangsu Neonatal Respiratory Failure Collaborative Network (2019-2021). Data were split 7:3 into training and validation sets. Eight machine learning algorithms were compared. Performance was assessed by area under the curve (AUC), calibration, and decision curve analysis. An independent cohort served for temporal validation.

Among 3,320 infants, the incidence of SIVH was 6.66%. Six predictors were identified: gestational age, birth weight, endotracheal intubation in the delivery room, chest compressions in the delivery room, surfactant administration in the delivery room, and chorioamnionitis. In the training set, logistic regression achieved the highest mean AUC based on 10-fold cross-validation. Bootstrap internal validation of the LR model yielded a corrected AUC of 0.809. In the independent hold-out validation set, the LR model again demonstrated the best discriminative ability among the eight algorithms (AUC: 0.804), with satisfactory calibration and favorable net benefit. Sensitivity analyses showed that the LR model maintained robust performance in temporal validation using an independent cohort (AUC: 0.822) and across geographic subgroups (AUC range: 0.729-0.885). An online interactive tool was also developed to facilitate clinical application.

A LR model using six readily available perinatal variables provides good discrimination and calibration for predicting SIVH in preterm infants, enabling immediate risk stratification at birth for SIVH occurring during the neonatal hospitalization period.

Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor is standard for patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI), yet real-world comparisons of ticagrelor and prasugrel remain limited. We evaluated their relative effectiveness and safety using the TriNetX Global Collaborative Network (2010-2024). Adult ACS patients receiving prasugrel or ticagrelor within 24 h post-PCI were included. The primary endpoint was a 1-year composite of all-cause mortality, myocardial infarction (MI), and cerebral infarction; secondary endpoints included individual components, major bleeding, and repeat revascularization. Propensity score matching balanced baseline characteristics, with subgroup and sensitivity analyses assessing robustness. Among 14,895 matched pairs (n = 29,790) from 126,273 patients, prasugrel was associated with lower risk of the composite endpoint (HR 0.641; 95% CI 0.613-0.671), all-cause mortality (HR 0.557; 95% CI 0.487-0.637), and MI (HR 0.648; 95% CI 0.616-0.680), without increased bleeding (HR 0.945; 95% CI 0.824-1.084). Repeat revascularization was higher with prasugrel (HR 1.791; 95% CI 1.639-1.957). Effects were consistent across subgroups. In this real-world setting, prasugrel demonstrated superior effectiveness over ticagrelor in reducing mortality and ischemic events without increasing the risk of bleeding, although higher rates of repeat revascularization warrant further study. These findings support prasugrel as a potentially preferred P2Y12 inhibitor in selected ACS patients undergoing PCI.

The objectives were to investigate serum miR-508-3p expression in patients with acute ischemic stroke (AIS), determine its value for early diagnosis and prognosis of AIS, and preliminarily explore its underlying mechanism. A total of 131 AIS patients (case group) admitted between January 2023 and December 2024, and 125 healthy individuals (control group) were enrolled. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect serum miR-508-3p expression, and an enzyme-linked immunosorbent assay (ELISA) was conducted to assess the concentrations of IL-6, IL-1β, TNF-α, and CRP in serum samples. The clinical value of miR-508-3p was analyzed using correlation, receiver operating characteristic (ROC), and Kaplan-Meier methods. Multivariate logistic regression was used to identify independent predictors of 90-day outcome. In vitro, human brain microvascular endothelial cells (HBMECs) were subjected to OGD/R; cell viability, injury, and apoptosis were determined by CCK-8, LDH release, and flow cytometry, and the miR-508-3p/SOCS3 targeted binding was confirmed using a dual-luciferase reporter system. Serum miR-508-3p was significantly decreased in AIS patients compared with controls (p < 0.001) and negatively correlated with National Institutes of Health Stroke Scale (NIHSS) score and levels of IL-6, IL-1β, TNF-α, and CRP (all p < 0.001). ROC analysis yielded an area under the curve (AUC) of 0.8641 (95%CI: 0.8184-0.9098), with 87.79% sensitivity and 72.80% specificity. Multivariate analysis confirmed low miR-508-3p as an independent predictor of poor 90-day prognosis (OR 0.002, 95% CI 0.000-0.581, p = 0.032). In vitro, miR-508-3p overexpression enhanced HBMEC viability and reduced LDH release and apoptosis after oxygen-glucose deprivation/reoxygenation (OGD/R). Dual‑luciferase reporter assay confirmed that miR-508-3p targets the 3'UTR of SOCS3. Downregulated serum miR-508-3p is associated with AIS severity, inflammation, and poor prognosis, suggesting its diagnostic and prognostic potential. Its protective effect may involve targeting suppressor of cytokine signaling 3 (SOCS3) and alleviating brain microvascular endothelial cell injury.

This review re-evaluates the literature from a matrix-centered perspective and determines how strongly it supports versican as a regulator of myocardial renewal rather than merely a marker of tissue remodeling. The evidence is organized around molecular identity, developmental location, temporal behavior after infarction, and causal intervention. During cardiac formation, versican-rich extracellular matrices recur in cushions, valves, septal and outflow structures, where matrix hydration, cell adhesion, and proteolytic processing accompany morphogenesis. In adult injury models, versican abundance and processing change as fibroblasts, inflammatory cells, and cardiomyocytes pass through different phases of repair and provisional-matrix resolution. Experimental augmentation has been associated with more cardiomyocytes displaying cell-cycle activity, less fibrotic distortion, and better ventricular performance. Candidate mechanisms include integrin-dependent ERK1/2 and Akt signaling, retention of soluble mediators, and modification of local matrix mechanics. Versican is better interpreted as a context-dependent matrix regulator than as a stand-alone cardiomyocyte mitogen. The current data justify further preclinical work, but not direct clinical use. Translation requires identification of the active isoform or fragment, the responsible source, modifying, and target cell populations, the effective time window and clearance mechanisms, proof that cycling cardiomyocytes complete division and integrate electrically, and systematic testing for fibrosis, inflammation, vascular remodeling, and off-target proliferation.

Right-to-left shunt (RLS) has been associated with cryptogenic stroke, migraine, and other neurological conditions in which ischemic brain injury may be clinically relevant. In routine practice, however, assessment is often fragmented. Shunt presence may be documented, but shunt burden, provoked versus non-provoked patterns, anatomical complexity, and MRI-defined brain injury are not always integrated into a reproducible workflow. Here, we describe a standardized protocol for multimodal assessment of RLS-related ischemic brain injury in a clinically selected cohort. The workflow includes patient screening, exclusion of major vascular and systemic factors that could independently contribute to brain parenchymal injury, contrast-enhanced transcranial Doppler ultrasound (c-TCD) confirmation and shunt grading, brain magnetic resonance imaging (MRI) classification, transthoracic and/or transesophageal echocardiographic anatomical assessment, structured data extraction, and dataset cleaning. To improve reproducibility, the protocol also standardizes key coding steps, including shunt-grade harmonization, classification of RLS as simple or complex, and interpretation of D-dimer values reported below the assay threshold. Using this workflow, a harmonized analytic cohort of 60 RLS-positive patients was established. MRI identified 23 MRI-negative and 37 MRI-positive patients. Representative analyses showed that MRI-positive findings were more frequent in patients with greater shunt burden and more complex anatomical phenotypes. This protocol provides an operational model for incorporating c-TCD, MRI, echocardiography, and structured clinical parameters into the evaluation of MRI-defined ischemic brain injury in RLS-positive patients. It should be interpreted as a workflow for standardized multimodal phenotyping rather than as a standalone physiologic assessment of all clinically significant or hypoxemia-related RLS.

Doxorubicin (DOX) is the most widely used anthracycline in hematologic and solid tumors, whose clinical utility is constrained by dose-dependent cumulative cardiotoxicity that can progress to chronic heart failure. Although previously attributed to overt cardiomyocyte loss, emerging evidence indicates that stress-induced premature senescence (SIPS) constitutes the dominant mechanism of chronic cardiotoxicity at clinically relevant concentrations. SIPS is defined by permanent cell cycle arrest, activation of the p53/p21 and p16/Rb tumor suppressor axes, mitochondrial dysfunction, and a senescence-associated secretory phenotype (SASP) that sustains a pro-inflammatory myocardial milieu. Nevertheless, the post-transcriptional mechanisms that govern this process remain incompletely understood.

The post-transcriptional regulation of DOX-induced SIPS was evaluated in vitro using neonatal rat ventricular myocytes (NRVMs) exposed to sublethal DOX (0.1 μM) with or without prophylactic miR-15b restoration via a synthetic mimetic to assess the p53/p21, p16, SASP, lysosomal, and mitochondrial responses. In vivo, a chronic cardiotoxicity model was established in female C57BL/6 mice receiving a cumulative dose of 30 mg/kg DOX to analyze myocardial miR-15b suppression, SIPS markers, and SASP profiles across survival cohorts.

Sublethal DOX treatment (0.1 μM) suppressed miR-15b expression by approximately 50% in NRVMs, resulting in post-transcriptional derepression of its mitochondrial target, SIRT4. This miR-15b loss triggered a multiparametric SIPS phenotype encompassing accumulation of γH2AX foci, p53/p21 and p16 activation, SASP induction (IL-6, IL-1β, Mcp-1 and Mmp13), lysosomal dysfunction (increased SA-β-Gal staining) and mitochondrial dysfunction. Prophylactic restoration of miR-15b via a synthetic mimetic selectively attenuated the p53/p21 axis, genomic damage foci, lysosomal dysfunction, mitochondrial dysfunction and SASP (IL-6 and IL-1β), without rescuing the p16/Rb pathway. In the female C57BL/6 chronic cardiotoxicity model, the cohort spontaneously stratified into animals completing the protocol (ND; 67%) and a premature death subgroup (PD; 33%). The PD subgroup exhibited the most profound myocardial miR-15b suppression and greater accumulation of SIPS markers, including γH2AX, p16, and reduced Lamin B. Notably, the SASP displayed distinct qualitative profiles between PD and ND animals, suggesting that SASP composition, rather than magnitude alone, determines the cardiotoxic outcome.

Collectively, these findings position miR-15b as a key post-transcriptional regulator of DOX-induced SIPS in the cardiomyocyte, whose sustained loss associates with cardiotoxicity severity in vivo.

Cardiovascular diseases remain a leading global health threat. Recent advances in room-temperature sensing and artificial intelligence (AI) have renewed research interest in the clinical translation of magnetocardiography (MCG) for cardiovascular diagnosis, yet the global research evolution of MCG has yet to be quantitatively characterized.

Literature from the Web of Science Core Collection and Scopus (2000-2026) was analyzed using CiteSpace, VOSviewer, and R to evaluate publication trends, knowledge networks, and evolving frontiers.

A total of 631 WoSCC and 755 Scopus articles were included. The publication trajectory exhibits a prolonged plateau followed by substantial recent growth. Germany, the United States, and China are the most prolific contributors. Keyword analysis revealed a diversification of technological and analytical themes. While early literature was strongly associated with superconducting quantum interference devices-based MCG, recent research has increasingly highlighted optically pumped magnetometers, magnetic-field control, sensor arrays, magnetic noise suppression, and AI-based signal analysis. The application landscape has broadened from physiological validation to coronary artery disease diagnosis, arrhythmia assessment, and fetal electrophysiology.

Collectively, these findings suggest that the evolution of cardiovascular MCG reflects the parallel development and interaction of sensor technologies, AI-based analysis, and emerging clinical applications. Future research should prioritize standardized protocols, scalable and robust acquisition systems, and explainable AI models to accelerate clinical implementation.