Fibrosis caused by the increase in extracellular matrix in cardiac fibroblasts plays an important role in the occurrence and development of atrial fibrillation (AF). The aim of this study was to investigate the role of hsa-miR-4443 in AF, human cardiac fibroblast (HCFB) proliferation, and extracellular matrix remodeling. TaqMan Stem-loop miRNA assay was used to measure hsa-miR-4443 expression in patients with persistent AF (n=123) and healthy controls (n=100). Patients with AF were confirmed to have atrial fibrosis by late gadolinium enhancement. At the cellular level, after hsa-miR-4443 mimic and inhibitor were transfected with HCFBs, proliferation, apoptosis, migration, and invasion were analyzed. Lastly, hsa-miR-4443-targeted gene and transforming growth factor (TGF)-β1/α-SMA/collagen pathway were evaluated by dual-luciferase reporter assay and western blot, respectively. In patients with AF, hsa-miR-4443 decreased significantly and collagen metabolism level increased significantly. Logistic regression analysis showed that low hsa-miR-4443 level was a risk factor of AF (P<0.001). The receiver operating characteristic curve revealed that hsa-miR-4443 was useful for predicting AF (area under the curve: 0.828, sensitivity: 0.71, specificity: 0.78, P<0.001). In HCFBs, hsa-miR-4443 targeted thrombospondin-1 (THBS1) and downregulated TGF-β1/α-SMA/collagen pathway. The inhibition of hsa-miR-4443 expression promoted HCFB proliferation, migration, invasion, myofibroblast differentiation, and collagen production. The significant reduction of hsa-miR-4443 can be used as a biomarker for AF. hsa-miR-4443 protected AF by targeting THBS1 and regulated TGF-β1/α-SMA/collagen pathway to inhibit HCFB proliferation and collagen synthesis.
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http://dx.doi.org/10.1590/1414-431X202010692 | DOI Listing |
Curr Oncol Rep
January 2025
Department of Radiology, Albert Einstein College of Medicine and the Montefiore Medical Center, 111 East 210Th Street, Bronx, NY, 10461, USA.
Purpose Of Review: This paper reviewed the current literature on incidence, clinical manifestations, and risk factors of Chimeric Antigen Receptor T-cell (CAR-T) cardiotoxicity.
Recent Findings: CAR-T therapy has emerged as a groundbreaking treatment for hematological malignancies since FDA approval in 2017. CAR-T therapy is however associated with a few side effects, among which cardiotoxicity is of significant concern.
Eur J Clin Invest
January 2025
Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, Liverpool, UK.
Cureus
December 2024
Internal Medicine, University of Health Sciences, Lahore, PAK.
Acute coronary syndrome (ACS) remains a major global health burden, encompassing a spectrum of conditions from unstable angina to acute myocardial infarction. Despite advancements in early detection and management, ACS is often complicated by the development of heart failure. This systematic review and meta-analysis aimed to identify factors associated with the development of heart failure following acute coronary syndrome.
View Article and Find Full Text PDFCureus
December 2024
Cardiology, Avicenna Military Hospital, Marrakesh, MAR.
Introduction Atrial fibrillation (AF), the most common cardiac arrhythmia, poses challenges in predicting thromboembolic risk. While the CHADS-VASc (congestive heart failure, hypertension, age ≥ 75 years (doubled), type 2 diabetes mellitus, previous stroke, transient ischemic attack, or thromboembolism (doubled), vascular disease, age 65-74 years, and sex category) score remains essential, its limitations include failure to identify left atrial (LA) thrombus in some patients. Transesophageal echocardiography (TEE) provides superior detection of LA thrombi and thrombogenic factors compared to transthoracic echocardiography (TTE), improving risk stratification, especially in intermediate-risk groups.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Department of Cardiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Introduction: The risk of mortality associated with cardiac arrhythmias is considerable, and their diagnosis presents significant challenges, often resulting in misdiagnosis. This situation highlights the necessity for an automated, efficient, and real-time detection method aimed at enhancing diagnostic accuracy and improving patient outcomes.
Methods: The present study is centered on the development of a portable deep learning model for the detection of arrhythmias via electrocardiogram (ECG) signals, referred to as CardioAttentionNet (CANet).
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