Deletion of natriuretic peptide receptor C alleviates adipose tissue inflammation in hypercholesterolemic Apolipoprotein E knockout mice is a research paper published in Journal of Cellular and Molecular Medicine (2021). On theSindex it has a DataRank of 0.480. It has been cited 11 times, with 9 citing works in its 1-hop citation network.
AbstractThe inflammation of adipose tissue is one of the most common secondary pathological changes in atherosclerosis, which in turn influences the process of atherosclerosis. Natriuretic peptides have been revealed important effect in regulating adipose metabolism. However, the relationship between natriuretic peptide receptor C and inflammation of adipose tissue in atherosclerosis remains unknown. This study aims to explore the effect natriuretic peptide receptor C exerts on the regulation of the adipose inflammation in atherosclerotic mice induced by western‐type diet and its overlying mechanisms. To clarify the importance of NPRC of adipose inflammation in atherosclerotic mice, NPRC expression was measured in mice fed with chow diet and western‐type diet for 12 weeks and we found a considerable increase in adipose tissue of atherosclerotic mice. Global NPRC knockout in mice was bred onto ApoE−/− mice to generate NPRC−/−ApoE−/− mice, which displayed remarked increase in browning of white adipose tissue and lipolysis of adipose tissue and decrease in adipose inflammation manifested by decreased macrophage invasion to form less CLS (crown‐like structure), reduced oxidative stress and alleviated expression of TNFα, IL‐6, IL‐1β and MCP1, but increased expression of adiponectin in adipose tissue. Moreover, our study showed that white adipose tissue browning in NPRC−/−ApoE−/− atherosclerotic mice was associated with decreased inflammatory response through cAMP/PKA signalling activation. These results identify NPRC as a novel regulator for adipose inflammation in atherosclerotic mice by modulating white adipose tissue browning.
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Base Score Contribution
0.373
From this paper's citation signal
Citation Network Contribution
0.107
From 8 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 78% comes from its base citations and 22% from the citation network (8 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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