Crosstalk between adipose tissue and blood vessels in cardiometabolic syndrome: implication of steroid hormone receptors (MR/GR)
Bibliographic record
Abstract
Crosstalk between adipose tissue and blood vessels is vital to vascular homeostasis and is disturbed in cardiovascular and metabolic diseases such as hypertension, diabetes and obesity. Cardiometabolic syndrome (CMS) refers to the clustering of obesity-related metabolic disorders such as insulin resistance, glucose and lipid profile alterations, hypertension and cardiovascular diseases. Mechanisms underlying these associations remain unclear. Adipose tissue associated with the vasculature [known as perivascular adipose tissue (PVAT)] has been shown to produce myriads of adipose tissue-derived substances called adipokines, including hormones, cytokines and reactive oxygen species (ROS), which actively participate in the regulation of vascular function and local inflammation by endocrine and/or paracrine mechanisms. As a result, the signaling from PVAT to the vasculature is emerging as a potential therapeutic target for obesity and diabetes-related vascular dysfunction. Accumulating evidence supports a shift in our understanding of the crucial role of elevated plasma levels of aldosterone in obesity, promoting insulin resistance and hypertension. In obesity, aldosterone/mineralocorticoid receptor (MR) signaling induces an abnormal secretion of adipokines, ROS production and systemic inflammation, which in turn contribute to impaired insulin signaling, reduced endothelial-mediated vasorelaxation, and associated cardiovascular abnormalities. Thus, aldosterone excess exerts detrimental metabolic and vascular effects that participate to the development of the CMS and its associated cardiovascular abnormalities. In this review, we focus on the physiopathological roles of corticosteroid receptors in the interplay between PVAT and the vasculature, which underlies their potential as key regulators of vascular function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".