Frontiers in Cardiovascular Medicine

Introduction Percutaneous coronary intervention (PCI) is a widely adopted strategy for managing coronary artery disease (CAD), leading to improved survival rates, particularly in developing countries. However, the increased survival of these patients imposes a substantial burden on long-term management, especially at the primary healthcare level. Recently, the hemoglobin-to-red cell distribution width ratio (HRR) has emerged as a potentially valuable prognostic biomarker for post-PCI patients. Despite its accessibility and cost-effectiveness, HRR has not been extensively investigated in resource-limited settings. Aim This study aimed to evaluate the prognostic value of the HRR in predicting 3-year major adverse cardiovascular events (MACE) among patients undergoing PCI who were managed at the primary healthcare level. Methods We conducted a multicenter prospective cohort study in Vietnam. A total of 626 post-PCI patients were ultimately included in the final analysis. The study commenced in October 2019 and concluded in October 2025. The association between HRR and 3-year MACE was evaluated using Cox proportional hazards regression models. Results The MACE incidence decreased progressively across the ascending HRR quartiles (p < 0.001). According to the unadjusted Cox model, each unit increase in HRR was associated with a lower risk of MACE (HR = 0.756; 95% CI, 0.703-0.814; p < 0.001). This association persisted after adjustment for age, sex, comorbidities (Model I: HR = 0.810; 95%CI: 0.750-0.878; p < 0.001). HRR outperformed its individual components, hemoglobin and red cell distribution width. Subgroup analyses confirmed the consistency of the association across clinically relevant strata. Calibration and decision-curve analyses further suggested acceptable risk estimation and potential clinical utility of HRR for 3-year MACE risk stratification. In the discriminative analysis for predicting 3-year MACE, the HRR had the highest area under the curve outperforming other inflammation-based indices. Conclusion A lower HRR was independently associated with a greater 3-year MACE risk in post-PCI patients. HRR outperforms commonly used leukocyte- and platelet-derived indices, highlighting its potential utility as a simple, cost-effective prognostic marker in resource-constrained healthcare settings.

Introduction Whartons jelly-derived mesenchymal stem cells (WJ-MSCs) have emerged as a promising regenerative strategy for ischemic heart disease because of their immunomodulatory, angiogenic, and antifibrotic properties. This pilot randomized trial evaluated the safety, feasibility, and exploratory efficacy of intramyocardial WJ-MSC administration combined with an extracellular matrix (ECM) patch in patients with ischemic cardiomyopathy undergoing coronary artery bypass grafting (CABG). Methods In this randomized, controlled pilot trial, 28 patients with ischemic cardiomyopathy, left ventricular ejection fraction (LVEF) <40%, and viable myocardium on cardiac magnetic resonance imaging (MRI) were assigned to receive intramyocardial WJ-MSC injections plus an extracellular matrix (ECM) patch or a placebo patch. Patients were followed for 12 months with echocardiography, cardiac MRI, Holter monitoring, functional assessment, and quality-of-life evaluation. Results Among 44 screened patients, 28 were randomized (16 to WJ-MSC and 12 to control). At 12 months, echocardiography showed a greater improvement in LVEF in the WJ-MSC group than in the control group (8% vs. 0%, p=0.045). Myocardial fibrosis decreased by 32% in both groups. Cardiac MRI demonstrated improvement in both groups, with numerically greater gains in LVEF and larger reductions in fibrosis in the WJ-MSC arm, although between-group differences were not statistically significant. No significant between-group differences were observed in ventricular arrhythmias or serious adverse events. Two non-cardiac postoperative deaths occurred in the WJ-MSC group. Conclusions Intramyocardial WJ-MSC administration combined with an ECM patch during CABG appears feasible and safe, with signals of functional improvement. Larger, adequately powered trials are needed to confirm efficacy and long-term safety.

BackgroundCardiovascular disease risk is higher in men than in women. Although sex differences in aortic wall adaptation following antihypertensive treatment have been reported in acute hypertension models, the response after gradually developing hypertension, which mimics human essential hypertension, remains unclear. This study investigated sex differences in aortic wall adaptation following acute blood pressure reduction after gradually developing hypertension. MethodSeventeen-week-old spontaneously hypertensive rats (SHRs) were assigned to the Hypertensive group or the antihypertensive (Reversal) group (N = 5/sex each). The Reversal group received the antihypertensive drug captopril for 4 weeks to maintain systolic blood pressure below 130 mmHg. Age-matched Wistar Kyoto rats (N = 3/sex) served as normotensive (Normal) group. After the experimental period, arterial wall thickness, circumferential wall stress, smooth muscle cell phenotype, and histological changes were evaluated. ResultsAntihypertensive treatment significantly reduced systolic blood pressure in both sexes. Both male and female SHRs exhibited elevated circumferential wall stress during the gradual development of hypertension. In females, antihypertensive treatment significantly reduced medial thickness compared with the Hypertensive group, whereas males showed no reduction. Circumferential wall stress in female Reversal group did not differ significantly from either the Hypertensive or Normal group, whereas males exhibited a significant reduction in circumferential wall stress compared with the Hypertensive group. Furthermore, the reduced collagen area fraction in the Hypertensive group returned to the normotensive levels only in females following antihypertensive treatment. ConclusionThese findings indicate that vascular remodeling induced by gradually developing hypertension is more effectively reversed by antihypertensive treatment in females than in males.

Objective To analyze the associations between cardiorespiratory fitness (CRF) indicators and cardiovascular health, assessed through the Life's Essential 8 (LE8) score, in individuals with coronary artery disease (CAD). Patients and methods This cross-sectional study included individuals (aged 50-75 years) with stable CAD were enrolled in the Heart-Brain randomized controlled trial (NCT06214624) from April 2022 to June 2024. Participants underwent a cardiopulmonary exercise test until volitional exhaustion. CRF indicators included peak oxygen consumption (VO2peak), time to exhaustion (TTE), ventilatory anaerobic threshold (VAT), peak oxygen pulse, 60-s heart rate recovery (HRrec) and oxygen uptake efficiency slope (OUES). LE8 score (range 0-100) was calculated as the unweighted average of 8 variables: physical activity, sleep, diet, nicotine exposure, glucose, lipids, body mass index, and blood pressure, as defined by the American Heart Association. We used linear regression models adjusted for sex, age, and education. Results 102 individuals were included (21 females). VO2peak ({beta}std=0.67, P<.001) and TTE ({beta}std=0.64, P<.001) showed strong positive associations with LE8 total score, followed by VAT ({beta}std=0.43, P<.001) and HRrec ({beta}std=0.26, P=.01). No associations were found for OUES ({beta}std=-0.08, P=.54) and peak oxygen pulse ({beta}std=-0.05, P=.72). Conclusion Maximal and submaximal indicators of CRF were positively associated with LE8 in individuals with CAD, yet maximal indicators showed the strongest associations. Notably, TTE demonstrated a similar strength of association with LE8 as VO2peak. These findings have important clinical and research implications as they support TTE as a simpler (than the gold-standard VO2peak), yet informative, marker of cardiovascular health in individuals with CAD.

Background: Cardiovascular diseases (CVD) remain the leading global cause of mortality, responsible for approximately 31% of all deaths worldwide in 2021. Traditional risk calculators, including Framingham, ASCVD, SCORE, and SCORE2, have long constituted the cornerstone of primary prevention strategies; however, they were derived predominantly from high-income European and North American populations, thereby limiting their predictive accuracy in diverse epidemiological contexts, particularly among Hispanic/Latino communities. Machine learning (ML) offers an alternative to capture the non-linear interactions inherent in biomedical data. Objective: The present study develops and validates ML-based models for cardiovascular mortality prediction using the National Health and Nutrition Examination Survey (NHANES) 1999-2018 dataset, and systematically compares their discriminative performance against eleven conventional clinical CVD risk calculators. Materials and Methods: A dedicated software platform, "CardioPrediQ," was designed to integrate multiple CVD calculators with ML-based risk assessment. A cohort of 12,847 participants with 16 predictor variables was derived from NHANES. Six algorithms (Logistic Regression, Cox Proportional Hazards, Gradient Boosting, AdaBoost, Random Forest, and Extra Trees) were trained in combination with six class-balancing strategies, yielding 36 model configurations. All models were trained on a stratified 70/30 split and calibrated using the Saerens prior probability adjustment method. Performance was evaluated using AUC-ROC, sensitivity, specificity, F1-score, and a weighted composite score. DeLong's test was employed to assess the statistical significance of AUC differences between the best-performing ML model and each conventional calculator. Results: Gradient Boosting with 2:1 oversampling and Saerens calibration achieved the best overall performance (AUC = 0.8934; composite score = 0.7904), outperforming all traditional calculators in composite ranking. The top six positions were occupied exclusively by ML and statistical models. The mean age of cardiovascular decedents was 67.43 years compared with 47.74 years among survivors. DeLong's test confirmed statistical superiority over six traditional CVD calculators (p < 0.05), whereas the difference against the top-performing calculators (ASCVD, HEARTS Caribbean, ASCVD Colombia, SCORE2, HEARTS North America) did not reach statistical significance. Age dominated feature importance at 41.2% relative weight, followed by systolic blood pressure (18.7%). Saerens calibration reduced the Brier score from 0.1286 to 0.1158, substantially improving probability calibration. Conclusions: ML models demonstrated superior composite performance over traditional calculators. The statistical equivalence with the highest-performing conventional calculators in the NHANES cohort is context-dependent and validates the methodological pipeline. The CardioPrediQ platform addresses the critical need for integrated, scalable CVD risk assessment tools, which is particularly relevant for Latin American populations where calculator validation remains limited. These findings support the integration of calibrated ML-based risk prediction into clinical practice while underscoring the importance of probability calibration for informed clinical decision-making.

Background: The saphenous vein (SV) remains the most widely used graft in coronary artery bypass grafting (CABG). However, graft failure over the years has compromised long-term outcomes. Preservation of the vascular endothelium is fundamental for vein graft patency, and hydrogen sulfide (H2S) a protective gasotransmitter, plays a significant role in vascular homeostasis. This study evaluated how different intraoperative preservation solutions modulate H2S-synthesizing enzymes and endothelial integrity. Methods: SV segments from 20 CABG patients were subdivided into five groups: Control (immediate fixation), normal saline (NS; 0.9% NaCl), autologous heparinized arterial blood (AHB), histidine-tryptophan-ketoglutarate (HTK) solution, and a damage group (no solution for 30 minutes). Structural integrity was evaluated by measuring endothelial coverage using light microscopy, and the expression of eNOS, CD31, and H2S pathway enzymes (CSE, CBS, and 3-MPST) was assessed by immunofluorescence (IF) and confocal microscopy to determine mean fluorescence intensity (MFI). Results: LM analysis revealed that AHB (89.66% {+/-} 3.02) and HTK (88.72% {+/-} 3.07) preserved endothelial coverage significantly better than NS (78.06% {+/-} 4.48) and the Damage Group (76.82% {+/-} 4.90; p < 0.001). In IF, all interventions reduced eNOS and CD31 expression compared to the control, but AHB and HTK maintained significantly higher levels than NS (p < 0.001). All three H2S-producing enzymes were detected in the GSV endothelium, with CSE being the most expressed isoform. The use of NS caused a marked depletion of these enzymes, while AHB and HTK showed specific superiority in preserving H2S synthesizing enzymes. Conclusions: The choice of preservation solution significantly affects endothelial integrity and the modulation of enzymatic H2S synthesis. NS proved to be deleterious to the endothelium, whereas AHB and HTK better preserved vascular structure and function, suggesting their clinical superiority for the preparation of venous grafts during CABG.

Background: Epicardial adipose tissue (EAT) is a metabolically active fat depot adjacent to the myocardium and the coronary arteries that can be non-invasively assessed by cardiovascular magnetic resonance (CMR). Increased EAT volume quantified by CMR has been linked to adverse cardiac remodeling, atrial fibrillation, coronary artery disease, and heart failure. Among CMR techniques, isotropic three-dimensional (3D) Dixon imaging at 1.3 x 1.3 x 1.3 mm3 resolution was developed to improve tissue characterization, providing fat-water signal separation for precise volumetric EAT assessment. However, manual segmentation of 3D datasets is highly time-consuming. For integration into clinical and research CMR workflows, reliable and fast automated segmentation is needed. Purpose: To develop and evaluate an automated deep-learning-based pipeline for ventricular EAT quantification based on isotropic 3D Dixon CMR acquisitions. Methods: An nnU-Net model was trained on 165 3D Dixon CMR cases encompassing healthy individuals and patients with underlying cardiovascular disease. The model was trained using all four Dixon phase images (opposed-phase, in-phase, fat-phase, water-phase). Manual 3D ventricular EAT segmentations served as the ground truth for training and evaluation. Performance was evaluated in 30 independent cases using Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), volumetric agreement, Pearson correlation, intraclass correlation (ICC), and Bland-Altman analysis. Model performance was benchmarked against interobserver and intraobserver variability. Results: Automated segmentation achieved a mean DSC of 0.896 {+/-} 0.039 and HD95 of 1.84 {+/-} 0.93 mm versus ground truth. Volumetric agreement with ground truth was high (r = 0.984, ICC = 0.988, p < 0.001; mean bias -0.70 mL, limits of agreement (LoA) [-10.31, 8.90] mL), exceeding interobserver agreement (bias -25.24 mL, LoA [-42.81, -7.66] mL) and comparable to intraobserver reproducibility (bias 2.72 mL, LoA [-8.73, 14.17] mL). Automated segmentation required less than one minute per case compared to 58.4 {+/-} 7.9 minutes for manual segmentation. Two of 30 cases (6.7%) required minor manual correction, both less than five minutes. Conclusion: Fully automated nnU-Net-based ventricular EAT segmentation from isotropic 3D Dixon CMR achieves accuracy comparable to intraobserver reproducibility while significantly reducing post-processing time. The approach may facilitate large-scale and longitudinal EAT quantification in CMR-based research workflows.

Background: Left ventricular (LV) remodeling is associated with impaired cardiac function and future cardiovascular disease (CVD). Current remodeling definitions use broad categorizations based on hypertrophy and mean wall thickness. Cardiac magnetic resonance (CMR) imaging provides detailed characterization of regional myocardial wall properties, which may enhance sex-specific cardiovascular disease (CVD) risk stratification. Objectives: We aimed to identify detailed LV remodeling patterns, their associations with CVD risk, and their clinical predictors. Methods: LV wall thickness data were obtained by CMR in three independent population-based cohorts (SHIP-TREND-0, n=931; SHIP-START-2, n=490; KORA-FF4, n=368). Sex-specific remodeling patterns were identified by k-means clustering and associated with established CVD risk scores and incident morbidity and all-cause mortality. Bootstrapped multinomial regression with LASSO regularization was used to select relevant clinical predictors of remodeling patterns. Results: The sample comprised 991 men (mean age 52.9 years, prevalent CVD 7.8%) and 798 women (52.5 years, 2%). Four remodeling clusters were found for men and women, respectively. For a subset of these clusters, significant associations with an increased CVD risk were found, e.g. in women, the high-risk cluster was associated with a 10.6 (95% confidence interval: 8.9, 12.3) percentage point increase in the 10-year Framingham Risk Score. Associations were independent of blood pressure and myocardial mass. Only in women, associations were also independent of average wall thickness and LV concentricity. Variable selection identified distinct clinical predictors of remodeling patterns. Conclusion: Particularly in women, regional LV wall thickness patterns detect unfavorable cardiac remodeling and might improve CVD risk stratification beyond existing strategies. Automated implementation during image acquisition and integration with shape-based models may facilitate clinical application.

Background and Aims: Epicardial adipose tissue (EAT) has emerged as an important cardiovascular biomarker that reflects both inflammatory and cardiometabolic risk. EAT volume and density vary significantly across populations, yet there is a lack of multicenter studies investigating the predictive value of population-specific EAT percentiles. Methods: In this multicenter study, we retrospectively analyzed low-dose computed tomography correction scans from 42,842 patients undergoing myocardial perfusion imaging. A derivation cohort of 15,082 patients was used to establish sex- and age-specific nomograms for EAT density and EAT volume indexed to body surface area. Percentile-based thresholds were tested for outcome prediction in a validation cohort of 27,760 patients. For clinical implementation, we developed an online EAT percentile calculator. Results: Percentile curves demonstrated increased BSA-indexed EAT volume and decreasing EAT density with age. Over a median follow-up of 3.6 years (IQR: 1.83 - 5.14), 4,956 patients experienced a nonfatal myocardial infarction or death. In multivariable Cox models, patients above the 95th sex- and age-specific percentile had significantly worse outcomes for BSA- indexed EAT volume [adjusted hazard ratio 1.30, 95% CI: 1.14 - 1.49, p < 0.001] and EAT density [adjusted hazard ratio 1.7, 95% CI: 1.51 - 1.92, p<0.001] when compared to patients below the 50th percentile (p<0.001). Conclusion: Age- and sex-specific EAT percentiles provide a clinically interpretable framework for contextualizing automated EAT measurements and identifying patients at increased cardiovascular risk. EAT density was a stronger prognostic marker and identified elevated risk even among patients with normal BMI, supporting its potential to provide information beyond conventional anthropometric assessment.

Background: Stability of the atherosclerotic plaque in coronary artery disease (CAD) is determined by features such as total plaque burden and necrotic core volume. Since invasive procedures are required to evaluate plaque stability, we tested whether the peripheral blood mononuclear cell (PBMC) microRNA (miR) signature could correlate with measures of plaque stability and thus serve as a non-invasive biomarker. Method: Patients from two distinct geographical locations in India were recruited to the study (Site 1: CAD=19, non-CAD=5; Site 2: CAD=12, non-CAD=7) and underwent invasive intravascular ultrasound with virtual histology to assess plaque burden and necrotic core volume. RNA from PBMCs of these patients was subjected to unbiased sequencing. Differential miR expression evaluated by DESeq2 and assessed for co-relationship with plaque stability. miR target gene prediction was performed using multiple databases, and Enrichr was used for enrichment analysis. Results: Unbiased RNA sequencing identified miR-664a-3p to be significantly downregulated in CAD patients from both sites (Site 1: log2FC=-1.02, p=0.0033 & Site 2: log2FC=-1.04, p=0.0007). miR-664a-3p expression was inversely correlated with plaque burden and necrotic core volume. Receiver operating characteristic (ROC) analysis of miR-664a-3p showed significant discriminative performance in the CAD cohort, with AUC values of 0.842 (Site 1) and 0.881 (Site 2). miR664a-3p target prediction and pathway enrichment analysis revealed selective enrichment of inflammatory signaling pathways, such as IL-17 and TNF, suggesting an association between PBMC pro-inflammatory response and plaque vulnerability. Conclusion: miR-664a-3p is downregulated in CAD patients and inversely correlates with measures of plaque stability, with potential as a biomarker for identifying patients at risk of CAD progression and plaque instability. Keywords: Coronary artery disease, peripheral blood mononuclear cells (PBMCs), microRNA, atherosclerotic plaque, necrotic core, plaque burden, biomarkers.

Background: ST-elevation myocardial infarction (STEMI) remains a major cause of global mortality. While troponin is the gold-standard biomarker for myocardial injury, a subset of patients presents with troponin levels below the clinical "rule-in" threshold upon hospital admission. The long-term prognostic significance of these initial "low-troponin" presentations in a large-scale population remains insufficiently characterized. Methods: We conducted a retrospective multicenter cohort study using the "KINERET" database, analyzing 8,394 patients diagnosed with STEMI who underwent percutaneous coronary intervention (PCI) at four academic medical centers in Israel between 2016 and 2023. Patients were stratified into two groups based on ESC rule-in criteria for high-sensitivity cardiac troponin (hs-cTn) at admission: a High trop group (above rule-in cutoff) and a Low trop group (below rule-in cutoff). The primary outcome was all-cause mortality at 5 years. Results: Of the 8,394 patients (mean age 68.3{+/-}13.3 years; 76% male), 36.5% (n=3,064) presented with troponin levels below the rule-in cutoff. Patients in the High trop group were older and had a higher prevalence of comorbidities, including heart failure (46.7% vs. 28.7%) and chronic kidney disease (13.9% vs. 9%). The Low trop group demonstrated significantly higher survival rates at both 1 year (92.9% vs. 84.0%, p<0.001) and 5 years (85.7% vs. 75.0%, p<0.001). After adjusting for age, sex, and comorbidities in a multivariate Cox regression model, initially elevated troponin remained a robust independent predictor of 5-year mortality (HR 1.15, 95% CI 1.14-1.16, p<0.001), alongside age >75, female sex, and chronic kidney disease. Conclusions: STEMI patients presenting with initial troponin levels below the diagnostic rule-in threshold have a significantly better short- and long-term prognosis compared to those with early troponin elevation. Moreover, admission troponin levels serve as a powerful predictor of 5-year mortality and may be used as an independent prognostic factor following STEMI.

Left ventricular ejection fraction (LVEF) guides diagnosis and treatment across cardiovascular disease, yet cardiac magnetic resonance (CMR), the reference standard, is frequently unavailable in middle-income settings. In this study we determined optimal cut-off values of global longitudinal strain (GLS) and speckle-tracking-derived LVEF for detecting CMR-defined reduced LVEF, compared their diagnostic accuracy, and reported sensitivity, specificity, likelihood ratios, and predictive values. We believe the work is a good fit for PLOS ONE as a methodologically rigorous, hypothesis-generating diagnostic-accuracy study of potential value for settings with limited access to advanced imaging. It is reported following the STARD 2015 guideline (included as Supporting Information) and includes a QUADAS-2 assessment and internal validation of the derived thresholds. In the interest of full transparency, we wish to disclose that this manuscript is a secondary analysis of a patient cohort previously reported by our group in a concordance study among Simpson-derived LVEF, GLS, and CMR-derived LVEF (Herrera-Escandon A, et al. Arq Bras Cardiol Imagem Cardiovasc. 2026;39(2):e20250102). The present study addresses a distinct research question, namely the diagnostic accuracy and optimal cut-off of these echocardiographic markers against a dichotomized CMR reference standard, that was not examined in that report, and it is cited and discussed accordingly in the manuscript. No figures, tables, or text have been reproduced from the prior publication. We make this overlap explicit in accordance with ICMJE recommendations on overlapping publications and are happy to provide the prior article to the editorial office.

Introduction: Diastolic pulse wave analysis provides non-invasive indices of arterial elasticity, but their associations with cardiac structure and function remain incompletely understood. Objective: To examine associations between arterial elasticity assessed by diastolic pulse wave analysis and echocardiographic measures of cardiac structure and function in a community-based cohort. Methods: A population-based cohort recruited 2816 randomly selected men and women aged 30-75 years between 2002 and 2005. A random subsample (n = 1,035) underwent echocardiography by a single senior cardiologist. Large-artery elasticity (C1) and small-artery elasticity (C2) were assessed by radial artery applanation tonometry. The analytical sample included 991 participants. Associations were examined using multivariable linear and logistic regression with sequential adjustment. The final model included sex, age, heart rate, diabetes mellitus, LDL cholesterol, body mass index, antihypertensive medication use, current smoking, alcohol intake, leisure-time physical activity, and systolic blood pressure. Results: Among 991 participants, mean age was 51 years, 488 were men, and 160 had left ventricular hypertrophy. Mean C1 was 16.0 {+/-} 5.1 mL/mmHg x 10, mean C2 was 6.9 {+/-} 3.5 mL/mmHg x 100, and mean EF was 73.4 {+/-} 8.5%. Higher C2 was associated with higher EF after systolic blood pressure adjustment ({beta} per 1-SD increase: 1.2; 95% CI: 0.5-1.9; p < 0.001). Higher C1 was associated with lower odds of left ventricular hypertrophy (OR per 1-SD increase: 0.61; 95% CI: 0.44-0.84; p = 0.003). Conclusions: Higher C2 was associated with better systolic function, whereas higher C1 was associated with lower odds of left ventricular hypertrophy.

Preeclampsia (PE) is a severe pregnancy-associated hypertensive disorder and a major contributor to maternal and perinatal morbidity and mortality. The mechanisms of PE pathogenesis are not yet understood. This paper aims to explore candidate PE-associated biomarkers and regulatory mechanisms using bioinformatics analysis of placental transcriptomic datasets. We downloaded placental transcriptomic datasetsGSE203507 and GSE148241 from GEO and investigated differentially expressed genes(DEGs) between PE and control samples. We performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO), and protein-protein interaction (PPI) analyses to characterize the potential role, disease associations, and interaction networks of the DEGs. We validated the mRNA expression patterns of candidate hub genes using two independent placental transcriptomic datasets, GSE143966 and GSE114691.We identified 263 DEGs in the discovery analysis and further obtained 150 overlapping DEGs including80 upregulated genes and 70 downregulated genes, for downstream analysis. We then identified eight candidate hub genes: OPRK1, OXGR1, HCAR3, CCR5, HCAR2, CXCL1, FPR3, and SSTR1using Meta scape software(v3.5.20260201). In the validation phase, most candidate hub genes showed broadly consistent mRNA expression trends across GSE114691 and GSE143966, while FPR3 showed weaker cross-dataset consistency. These findings provide candidate PE-associated genes and regulatory pathways for further experimental and clinical validation..

AimsTo elucidate the relationship between interstitial flow (IF) and structural changes in the aortic media during the development of aortic dissection (AD). MethodsApolipoprotein E-deficient (ApoE[-/-]) mice infused with angiotensin II (AngII) were used as an AD model, in which AD develops exclusively in the thoracoabdominal aorta but not in the thoracic aorta. To capture characteristics present prior to AD onset, the duration of AngII infusion was shortened to generate Pre-AD group. Normal C57BL/6 mice (Normal group) and ApoE(-/-) mice without AngII infusion (Control group) were also included for comparison. Thoracic and thoracoabdominal aortas were excised from all groups, and IF was measured in vitro in accordance with our previously established methods. ResultsIF velocity was generally smaller than 4 m/s across all groups; however, velocities exceeding 4 m/s was observed predominantly in the thoracoabdominal region of the Pre-AD group. Although mean IF velocity did not differ significantly among groups, the standard deviation differed significantly and was the highest in the thoracoabdominal region of the Pre-AD group. In this region, IF velocity tended to increase with more prolonged AngII administration, indicating acceleration of IF prior to AD onset. Three-dimensional internal structural microscopy revealed fragmentation of the elastic lamina (ELs) and a reduction in elastin density only in the thoracoabdominal region of the Pre-AD group. ConclusionsOur findings suggest that increased IF and EL degradation occur in parallel and together contribute to the initiation of AD.

Klf9 is a cardiac-enriched transcription factor of the Kruppel-like factor (Klf) family. Klf9 levels decrease during cardiac hypertrophy; however, no studies have examined its transcriptional targets or role in the progression of hypertrophy. Here, we report genome-wide differential Klf9 occupancy during cardiac hypertrophy, with a predominant enrichment at the metabolic gene promoters. Further, using conditional Klf9 knock-in mice subjected to pressure overload for 1 or 2 weeks, we show that restoring Klf9 expression initially inhibits hypertrophy but later leads to early-onset heart failure. We conclude that a decrease in Klf9 is required for metabolic adaptations that support the development of compensatory hypertrophy.

Background: Aortic stenosis (AS) is a progressive valvular disease associated with poor prognosis once symptoms develop, yet routine echocardiographic screening is impractical. While artificial intelligence (AI)-based electrocardiogram (ECG) models have shown promise for AS detection, it remains unclear whether they primarily reflect conventional left ventricular hypertrophy (LVH) voltage criteria or capture additional ECG features. Methods and Results: We developed a deep learning model using 244,816 ECGs from 51,713 patients across six academic institutions in Japan (CLIDAS database). AS labels were derived from inpatient Diagnosis Procedure Combination (DPC) codes. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.849 (95% confidence interval 0.832-0.865) in the independent test cohort, with consistent performance across institutions, sex, and age. At a threshold of 0.1, sensitivity was 79.1%, specificity was 73.9%, and negative predictive value (NPV) was 98.0%. Conventional LVH voltage criteria (Sokolow-Lyon AUC 0.706; Cornell AUC 0.692) showed lower performance, and adding them to the AI model conferred no incremental benefit (AUC 0.849 vs. 0.847). Gradient-weighted class activation mapping (Grad-CAM) revealed predominant attention around QRS complexes in limb leads, beyond regions typically assessed in LVH evaluation. Conclusions: This multicenter AI-ECG model demonstrated strong discrimination for AS and captured ECG features beyond conventional LVH voltage criteria. The high NPV supports its use as a rule-out pre-screening tool.

BackgroundQuantitative dynamic contrast-enhanced myocardial perfusion cardiovascular magnetic resonance (CMR) enables estimation of myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). These measurements require an arterial input function (AIF), which is typically derived from the left ventricular blood pool. However, the contrast agent bolus undergoes dispersion during transport through the coronary vasculature before reaching the myocardial microcirculation. This may introduce systematic and spatially heterogeneous errors in MBF and MPR estimates. PurposeThis work provides an extended segmental analysis of bolus-dispersion-induced errors in quantitative myocardial perfusion MRI using previously established computational fluid dynamics (CFD) simulations in realistic porcine coronary artery models. The focus of the present analysis is the assignment of coronary outlets to myocardial segments and the resulting segmental variability of MBF and MPR errors. MethodsRealistic three-dimensional models of the left and right coronary arteries were extracted from an ex-vivo porcine imaging cryomicrotome dataset. The models extended down to the pre-arteriolar level and included 364 outlets for the left coronary artery and 104 outlets for the right coronary artery, with an average outlet diameter of 383 {+/-} 85 {micro}m. Blood flow was simulated under rest and stress conditions using OpenFOAM. Contrast agent transport was then modeled by solving the advection-diffusion equation using a gamma-variate bolus as input. Outlet concentration-time curves were analyzed using an indicator-dilution model to estimate MBF and MPR errors. Outlets were assigned to standardized myocardial segments, and segmental averages were evaluated with respect to coronary supply territory and travel distance from the model inlet. ResultsThe simulations demonstrated marked segmental heterogeneity of volume blood flow and bolus-dispersion-induced MBF and MPR errors. Errors increased with travel distance from the coronary artery inlet and were more pronounced in regions supplied by the right coronary artery, consistent with lower flow velocities and stronger bolus dispersion. The resulting systematic errors led to underestimation of MBF and overestimation of MPR, with segmental deviations reaching up to approximately 60%. ConclusionBolus dispersion in the coronary vasculature may lead to substantial segmental and location-dependent errors in quantitative myocardial perfusion MRI. This extended analysis indicates that dispersion-related bias is not spatially uniform, but depends on coronary supply territory, travel distance, and flow conditions. These effects should be considered when interpreting regional MBF and MPR estimates, particularly as automated quantitative myocardial perfusion CMR becomes more widely used.

BACKGROUND: Chronic coronary syndromes (CCS) remain under-characterized in Latin America, where clinical profiles may differ from high-income countries. OBJECTIVE: We aim to characterize the clinical presentation, coronary anatomic profile, and pharmacologic treatment patterns of adults living with CCS using data from the Mexican Chronic Coronary Syndrome Registry (RESINCCRO). METHODS: RESINCCRO is an observational, multicenter, cross-sectional registry conducted across ~50 centers in five regions from Mexico. We included adults ([&ge;]18 years) enrolled between September 2024 and March 2025 who met 2019 ESC CCS criteria. Coronary imaging data was collected from medical records into a standardized electronic case report form. RESULTS: We enrolled 3,029 adults (men [72.5%]; mean age 67.2 {+/-} 10.7 years). Cardiometabolic comorbidities were frequent: overweight/obesity (76%), arterial hypertension (69.0%), type 2 diabetes (44.0%), and chronic kidney disease (24.2%). Persistent angina/equivalents occurred in (23.9%), of which most had Canadian Cardiovascular Society class I - II (91.2%). The mean LVEF was of 53.7 {+/-} 12.0. Cardiac rehabilitation participation was (6.2%). Median LDL-C was 70 mg/dL (IQR 51 - 95) and LDL <55 mg/dL was only 26.1%, despite high prescription of lipid-lowering therapies, including statins (93.2%), ezetimibe (24.6%), and PCSK9 inhibitors (2.4%). 60.3% had obstructive epicardial disease. CONCLUSIONS: Mexican adults with CCS exhibit high cardiometabolic burden, frequent symptoms, suboptimal LDL-C goal attainment, low rehabilitation uptake, and a substantial obstructive phenotype. These findings highlight opportunities to intensify secondary prevention, adopt mechanism-directed evaluation and therapy, and expand cardiac rehabilitation to improve CCS care in Mexico.

Congenital heart disease (CHD) comprises a diverse group of structural heart defects present at birth due to complex interactions between genetic and environmental factors. Prenatal alcohol exposure (PAE) is a known environmental factor that disrupts fetal cardiogenesis and increases the risk of CHD. However, the molecular mechanisms behind ethanol (EtOH)-induced CHD remain obscure. This study investigated the effects of EtOH on bone morphogenetic protein (BMP) signaling and transcriptomic reprograming in HL-1 cardiomyocytes. HL-1 cells were treated with varying concentrations of EtOH (25, 50, and 100 mM) for 24 h. 100 mM of EtOH exposure significantly enhanced SMAD1/5 phosphorylation and upregulated BMP-responsive genes, namely Id1, Gata4, Mef2c, and Nkx2.5. Increased histone acetyltransferase activity further validated activation of BMP signaling through histone hyperacetylation. These effects were reversed by the BMP pathway inhibitor LDN-193189, confirming pathway-specific activation. Further, transcriptome analysis following 100 mM EtOH treatment identified 3,876 differentially expressed genes. KEGG enrichment analysis revealed significant dysregulation of cardiogenic pathways, including TGF-{beta}, Hedgehog, PI3K-Akt, Notch, FoxO, and calcium signaling pathways, along with extracellular matrix-receptor interaction and focal adhesion pathways. Gene Ontology analysis highlighted disturbances in heart development, cellular differentiation, apoptosis, extracellular matrix (ECM) organization, and chromatin regulation. Network analysis identified key hub genes, viz. Kras, Fn1, Col1a1, Prkaca, Fbn1, Col6a1, Col6a2, Ccnd1, Col1a2 and Myc which are upregulated and Hsp90aa1, Mdm2, Jun, Hras, Il6, Hsp90ab1, Pdgfra, Cdkn1a, Pparg, Fos and Hspa8 are downregulated which were subsequently validated by qRT-PCR. Collectively, these findings provide novel insights into the molecular basis of EtOH-induced CHD and identify potential biomolecule candidates for future therapeutic investigation.