Time-Dependent Differences in the Influence of Perivascular Adipose Tissue on Vasomotor Functions in Metabolic Syndrome
Bibliographic record
Abstract
Background: Metabolic syndrome (MetS) facilitates the development of cardiovascular disease due to atherosclerosis, which is accelerated by defects of the vascular endothelium. Vascular dysfunction in response to nitric oxide (NO) occurs in the mesenteric arteries of an animal model of MetS, SHRSP.Z- Lepr fa /IzmDmcr (SHRSP.ZF) rats. Vascular responses to vasodilators are affected by perivascular adipose tissue (PVAT) that surrounds the outsides of arteries. In this study, we assessed the role of PVAT in vascular dysfunction observed in SHRSP.ZF. Methods: To determine the effects of PVAT on vasodilators in SHRSP.ZF and control Wistar-Kyoto (WKY) rats, we used organ bath bioassay techniques to assay acetylcholine and nitroprusside-induced relaxations of isolated mesenteric arterial ring preparations with PVAT intact or removed. Results: A PVAT-mediated enhancement of relaxations induced by acetylcholine and nitroprusside occurred in SHRSP.ZF at 20 weeks of age, but not at 10 and 30 weeks, and did not occur in WKY. Furthermore, the enhancing effects of PVAT from SHRSP.ZF at 20 weeks could not be substituted by replacement with PVAT from either WKY or 30-week-old SHRSP.ZF, was inhibited by NO synthase inhibitor, and abolished by removal of the arteries' endothelium. Cyclic guanosine monophosphate (cGMP) accumulation elicited by nitroprusside was higher in SHRSP.ZF arteries with PVAT than arteries without PVAT at 20 weeks, but the enhancement of cGMP accumulation did not occur at 30 weeks. Conclusions: PVAT may regulate arterial tone by releasing diffusible vasorelaxing factor(s), which, through endothelium-derived NO production, compensates for impaired vasodilations at early stages of MetS.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".