Journal of Cardiovascular Translational Research最新文献

Ischemic heart disease is a leading cause of global morbidity and mortality, yet early diagnosis and targeted therapies remain limited. Exosomes, small extracellular vesicles carrying nucleic acids, proteins, and lipids, mediate intercellular communication and show promise for diagnostic and therapeutic use due to their stability, biocompatibility, and targeted delivery. Circulating exosomal profiles reflect myocardial pathology, enabling early detection, risk stratification, and monitoring. Exosomes from mesenchymal stem cells, immune cells, endothelial cells, and other stem cells exert cardioprotective effects. This review summarizes advances in exosome-based diagnostics and therapies and highlights their potential as biomarkers and innovative treatments.

This study aims to integrate lesion-specific pericoronary adipose tissue (PCAT) radiomics analysis with existing clinical and imaging methods under the guidance of CT-derived fractional flow reserve (CT-FFR), to develop and validate an interpretable machine learning (ML) prediction model for patients with type 2 diabetes complicated by coronary artery disease (CAD). The performance of ML algorithms across different predictive models was compared using the area under the receiver operating characteristic curve (AUC). In the validation cohort, the XGBoost algorithm within the combined model achieved an AUC value of 0.908, outperforming the best algorithm in the traditional model (AUC = 0.834) and radiomics model (AUC = 0.840). Meanwhile, the Shapley algorithm highlights the additional incremental value of radiomic features. Our model enhances the predictive ability and provides clinicians with a comprehensive tool, facilitating early intervention for high-risk individuals and proactive secondary prevention strategies, which may potentially improve clinical outcomes.

Coronary obstruction following transcatheter aortic valve-in-valve implantation (VIV-TAVI) carries a high mortality risk. This in-vitro study assessed coronary perfusion in a high-risk VIV-TAVI scenario. A patient deemed at high-risk and treated with preventive Chimney stenting was selected as case study. A 3D-printed aortic root model was fabricated from pre-operative imaging and used to replicate the patient's VIV-TAVI setting. A CoreValve-Evolut-23 was implanted within a Trifecta-19 at five depths, with commissural alignment and 60° misalignment, to explore procedural variability and associated risk margins. The model was tested in a pulsatile mock loop with a coronary perfusion simulator. Flow and pressure were recorded pre- and post-VIV-TAVI under physiological conditions. Across all tested configurations, VIV-TAVI didn't significantly impair left or right coronary flows. The recommended depth optimized hemodynamic valve performance. Findings suggest refining coronary obstruction risk stratification in VIV-TAVI to improve decision-making regarding preventive interventions.

Acute coronary syndrome, driven by vulnerable plaque (VP) instability, is a major cause of cardiovascular mortality. Current diagnostic methods for VPs are limited by invasiveness or low specificity, highlighting the need for non-invasive biomarkers. Using single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from coronary artery disease (CAD) patients with VPs and controls, we identified circulating T cell-platelet aggregates (TPAs) significantly enriched in VP patients and linked to plaque instability via pro-inflammatory pathways. Through high dimensional weighted gene co-expression network analysis, we discovered TPAs' hub genes and demonstrated their role in plaque destabilization. Furthermore, employing machine learning, including Boruta, least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), we screened for five blood biomarkers that can serve as diagnostic indicators for VPs. Our study demonstrates that TPAs are critically involved in VPs formation. Furthermore, we identified EPHB6, STAT1, RPL23, IKZF3 and AHCY as potential circulating biomarkers for non-invasive detection of VPs.

Three-dimensional (3D) printing has rapidly evolved as a transformative technology in cardiovascular medicine, offering capabilities for anatomical modelling, surgical planning, and the development of biocompatible implants. This review synthesizes evidence from peer-reviewed studies to provide a comprehensive overview of 3D printing technologies, materials, and their clinical applications in cardiovascular fields, including myocardial tissue engineering, valve replacement, and vascular modelling. Emphasis is placed on patient-specific modelling, integration of bio-printing technologies, and recent clinical demonstrations of improved surgical precision and reduced implant rejection. Drawing on 28 primary sources, this review identifies current benefits and challenges of 3D printing in cardiovascular care, highlights emerging trends, and proposes future directions for research and clinical translation.

Tricuspid regurgitation (TR) is a highly morbid and often untreated valvular heart disease. New devices are under development to address this unmet need, necessitating valid models to test their efficacy. Aim of this study was to assess feasibility and reliability of pulmonary artery banding (PAB) as a pathological acute model of functional TR. Eight pigs underwent right thoracotomy, with an umbilical tape placed around the main pulmonary trunk, followed by controlled reduction of the pulmonary artery lumen via a tourniquet system. No animals died during the procedure. After PAB, right ventricular (RV) mean pressure, RV basal and mid-diameter and tricuspid septo-lateral diameter significantly increased (+ 97%, + 23%, + 32%, + 20%, p < 0.01 for all). Consequently, TR was at least moderate-to-severe in all the animals and these modifications remained stable for up to one hour. PAB therefore represents a reliable, one-step model of functional TR ideal to test the efficacy of new tricuspid devices.

To develop a predictive model for optimal anastomosis sizing in TAPVC surgery, focusing on the role of pulmonary venous confluence (PVC) size. A patient-specific fluid-structure interaction (FSI) model simulated blood flow through various anastomosis sizes. Key variables included body weight, anastomosis length, and PVC size. The model's predictions were validated against postoperative echocardiographic measurements from nine TAPVC cases. A strong positive correlation was found between flow velocity and the ratio of body weight to anastomosis length and PVC circumference. Including PVC size significantly improved predictive accuracy. No significant difference was observed between predicted and measured velocities. PVC size is a critical factor for planning TAPVC surgery. Incorporating it into computational models enhances the prediction of flow dynamics and supports personalized surgical decision-making.

Chronic myocardial ischemia (CMI) is a key pathological condition in coronary artery disease (CAD), yet small animal models for CMI are limited. This study developed and characterized a CMI mouse model using ApoE-/- mice fed a high-fat diet for 3 months. Cardiac function was assessed through electrocardiography (ECG), myocardial action potential, and perfusion echocardiography. The model group exhibited elevated cholesterol, aortic lipid plaques, and T-wave flattening, correlated with atherosclerosis severity. Impaired myocardial perfusion, reduced ATP content, and accelerated inner cardiomyocyte repolarization were also observed. PET/CT scans revealed filling defects, while myocardial contractile function showed reactive suppression under CMI conditions. This model replicates CMI's pathological features, providing a valuable tool for studying CAD progression and treatment.

Hyperoside (Hyp) exhibits notable protective effects by targeting oxidative stress, ferroptosis, and apoptosis. In vivo experiments used a murine model of DOX-induced cardiotoxicity with Hyp co-treatment. Hyp co-administration mitigated doxorubicin-induced cardiac impairment in mice, demonstrated by enhanced ejection fraction (EF) and fractional shortening (FS), diminished inflammatory cell infiltration and fibrotic changes, reduced circulating levels of cardiac biomarkers including cTnT, CK, CK-MB, LDH, and LDH-1. Hyp reduced oxidative stress (lower MDA, higher SOD and GSH-Px activity), inhibited ferroptosis (decreased intracellular Fe2 + , MDA, 4-HNE, PTGS2, and ASCL4; increased GSH and Ferritin), and suppressed apoptosis (fewer TUNEL-positive cells, balanced Bax/Bcl-2). Mechanistically, Hyp activated the Nrf2/GPX4 axis: it promoted Nrf2 nuclear translocation, upregulated GPX4 expression as shown by molecular docking. These effects were abrogated by ML385, confirming Nrf2 dependence. Hyp alleviates DOX-induced cardiotoxicity via Nrf2/GPX4 activation, suppressing oxidative stress, ferroptosis, with potential as a therapeutic agent.

This study evaluated coronary computed tomography angiography (CCTA)-based computational fluid dynamics (CFD) for predicting plaque dynamics in coronary artery disease. We retrospectively analyzed 22 patients (34 lesions) with paired CCTAs (mean interval 2 years). Lesions were categorized as progression (increase in diameter stenosis ≥ 5%), stable (change within - 5% to 5%), or regression (decrease in diameter stenosis ≥ 5%). Hemodynamic indices were normalized to adjacent non-diseased segments. Logistic regression identified predictors: normalized minimum wall shear stress (odds ratio (OR) = 0.38, p < 0.001) and maximum helicity (OR = 1.44, p = 0.016) predicted progression; average vorticity (OR = 0.13, p = 0.019) and gradient oscillatory number (OR = 0.10, p = 0.001) predicted regression. Receiver operating characteristic (ROC) analysis showed good discrimination (area under the curve (AUC) = 0.78 for progression, 0.83 for regression). These noninvasive imaging- and hemodynamic-derived markers, which were independently associated with lesion progression, may enhance coronary artery disease risk stratification by identifying high-risk plaques beyond stenosis severity, thereby informing individualized follow-up and treatment.