Background: Individuals with JAK2V617F-mutant myeloproliferative neoplasms or clonal hematopoiesis of indeterminate potential have a markedly increased risk of cardiovascular disease, yet the mechanisms by which mutant blood cells drive vascular and cardiac dysfunction remain incompletely understood. Although the thrombopoietin (TPO) receptor MPL is central to hematopoiesis and is expressed in vascular endothelial cells (ECs), its role in JAK2V617F-associated cardiovascular complications is unknown. Methods and Results: We generated chimeric mice with JAK2V617F-mutant blood cells and wild-type endothelium by bone marrow transplantation and challenged them with a high-fat/high-cholesterol diet to model cardiometabolic stress. These mice developed a distinct cardiovascular phenotype characterized by microvascular disease, increased left ventricular mass, and relatively preserved left ventricular ejection fraction. Histological analysis revealed coronary arteriole stenosis, perivascular fibrosis, reduced microvascular density, and endocardial injury, without evidence of epicardial coronary stenosis or myocardium infarction. Single-cell RNA sequencing revealed activation of inflammatory, stress-response, and endothelial-to-mesenchymal transition gene signatures in ECs, most prominently within the endocardial ECs. Immunohistochemistry identified MPL expression predominantly in endocardial ECs. TPO/MPL signaling was upregulated in endocardial ECs in mice with JAK2V617F-mutant hematopoiesis, and treatment with an anti-MPL neutralizing antibody markedly improved cardiac pathology, restored endocardial integrity, and increased coronary microvascular density despite persistent systemic inflammation. Conclusions: JAK2V617F-mutant hematopoiesis induces coronary microvascular dysfunction. Endocardial ECs represent a key cellular target under cardiometabolic stress, and endocardial MPL signaling constitutes a potential targetable pathway in JAK2V617F-associated cardiovascular disease.
Assessing nurses’ attitudes toward artificial intelligence in Kazakhstan: psychometric validation of a nine-item scale
BackgroundArtificial intelligence (AI) is increasingly integrated into healthcare, yet the attitudes and knowledge of nurses, who are the key mediators of AI implementation, remain underexplored.



