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Abstract Hypertrophic cardiomyopathy (HCM) is considered a primary disorder of the sarcomere resulting in unexplained left ventricular hypertrophy but the paradoxical association of nonmyocyte phenotypes such as fibrosis, mitral valve anomalies and microvascular occlusion is unexplained. To understand the interplay between cardiomyocyte and nonmyocyte cell types in human HCM, single nuclei RNA-sequencing was performed on myectomy specimens from HCM patients with left ventricular outflow tract obstruction and control samples from donor hearts free of cardiovascular disease. Clustering analysis based on gene expression patterns identified a total of 34 distinct cell populations, which were classified into 10 different cell types based on marker gene expression. Differential gene expression analysis comparing HCM to Normal datasets revealed differences in sarcomere and extracellular matrix gene expression. Analysis of expressed ligand-receptor pairs across multiple cell types indicated profound alteration in HCM intercellular communication, particularly between cardiomyocytes and fibroblasts, fibroblasts and lymphocytes and involving integrin β1 and its multiple extracellular matrix (ECM) cognate ligands. These findings provide a paradigm for how sarcomere dysfunction is associated with reduced cardiomyocyte secretion of ECM ligands, altered fibroblast ligand-receptor interactions with other cell types and increased fibroblast to lymphocyte signaling, which can further alter the ECM composition and promote nonmyocyte phenotypes.
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Bridging social and ecological science to create spatially explicit models of human-caused mortality of carnivores
Abstract Research indicates that human-caused mortality (HCM) is a key factor limiting numerous large carnivore populations. However, efforts to represent HCM in spatially explicit models have generally been limited in scope—often relying on proxies, such as road or human density. Yet such efforts fail to distinguish different sources of HCM, which can arise from different antecedent processes. We offer a systems-based conceptual framework for understanding the antecedents of HCMs that is grounded in theory from the social and behavioral sciences. Specifically, we first explain how HCMs are usefully distinguished into four types (e.g., accidental, harvest, illicit, control actions), then discuss how these different types tend to be driven by different sets of psychological and sociopolitical processes. We contend that improvements in understanding the spatial variation in HCMs would rise from more explicit attention to the various antecedent processes that precede each mortality type.
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- Award ID(s):
- 2317537
- PAR ID:
- 10586268
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Ambio
- Volume:
- 54
- Issue:
- 9
- ISSN:
- 0044-7447
- Format(s):
- Medium: X Size: p. 1479-1490
- Size(s):
- p. 1479-1490
- Sponsoring Org:
- National Science Foundation
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