We reported previously that angiopoietin-like protein3 (ANGPTL3), a liver-specific secretory factor, increased plasma triglyceride (TG) via inhibition of lipoprotein lipase and free fatty acid (FFA) by activating adipose-lipolysis. The current study examined the regulation of Angptl3 by leptin and insulin, both of which are key players in the metabolic syndrome. Angptl3 expression and plasma ANGPTL3 levels were increased in leptin-resistant C57BL/6J(db/db) and -deficient C57BL/6J(ob/ob) mice, relative to the control. Leptin supplements decreased Angptl3 gene expression and plasma ANGPTL3 in C57BL/6J(ob/ob) mice. The changes of Angptl3 were associated with alterations of plasma TG and FFA levels. Leptin treatment directly suppressed Angptl3 gene expression in hepatocytes. Angptl3 gene expression and plasma protein levels were also increased in insulin-deficient streptozotocin-treated mice. Insulin treatment of hepatocytes decreased Angptl3 gene expression and protein secretion. Our results suggest that elevated ANGPTL3 by leptin- or insulin-resistance is attributed to increased plasma TG and FFA concentrations in obesity.
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http://dx.doi.org/10.1016/j.bbrc.2004.08.024 | DOI Listing |
Am J Clin Exp Urol
December 2024
Department of Urology, General Hospital of Northern Theater Command Shenyang 110016, Liaoning, China.
Objective: To investigate the expression of metabolism-related genes (MRGs) in kidney renal clear cell carcinoma (KIRC) and their association with patient prognosis, and to identify potential targets for intervention.
Methods: Bioinformatics methods were employed to mine the KIRC transcriptome data in The Cancer Genome Atlas Program (TCGA) database in order to identify MRGs that are aberrantly expressed in cancerous tissues. Subsequently, a prognostic risk score model was constructed and its predictive capacity was evaluated.
Prog Mol Biol Transl Sci
January 2025
Department of Microbiology, Gargi College, University of Delhi, New Delhi, India. Electronic address:
The CRISPR-Cas system has emerged as a revolutionary tool in genetic research, enabling highly precise gene editing and significantly advancing the field of cardiovascular science. This chapter provides a comprehensive overview of the latest developments in utilizing CRISPR-Cas technologies to investigate and treat heart diseases. It delves into the application of CRISPR-Cas9 for creating accurate models of complex cardiac conditions, such as hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and various arrhythmias, which are essential for understanding disease mechanisms and testing potential therapies.
View Article and Find Full Text PDFCurr Cardiol Rev
January 2025
School of Paramedics and Allied Health Sciences, Centurion University of Technology and Management, Bhubaneswar, Odisha, India.
Background: Atherosclerosis is a chronic disease caused by the accumulation of lipids, inflammatory cells, and fibrous elements in arterial walls, leading to plaque formation and cardiovascular conditions like coronary artery disease, stroke, and peripheral arterial disease. Factors like hyperlipidemia, hypertension, smoking, and diabetes contribute to its development. Diagnosis relies on imaging and biomarkers, while management includes lifestyle modifications, pharmacotherapy, and surgical interventions.
View Article and Find Full Text PDFMedicine (Baltimore)
December 2024
National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Dyslipidemia has been established as a potential risk factor for venous thromboembolism (VTE) in several observational studies. Statins and novel lipid-modifying agents are being explored for their potential in VTE prevention, encompassing deep vein thrombosis (DVT), and pulmonary embolism (PE). Nonetheless, conclusive evidence supporting the effectiveness remains uncertain.
View Article and Find Full Text PDFGenomics Inform
December 2024
Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Cells interact with each other for proper function and homeostasis. Often, co-expression of ligand-receptor pairs from the single-cell RNAseq (scRNAseq) has been used to identify interacting cell types. Recently, RNA sequencing of physically interacting multi-cells has been used to identify interacting cell types without relying on co-expression of ligand-receptor pairs.
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