Modulation of Vasomotor Function by Perivascular Adipose Tissue of Renal Artery Depends on Severity of Arterial Dysfunction to Nitric Oxide and Severity of Metabolic Parameters
Bibliographic record
Abstract
/IzmDmcr rats (SPZF), a metabolic syndrome model. We investigated and compared the effects of PVAT on the renal artery in SPZF with those on SHR/NDmcr-cp rats (CP). Renal arteries with and without PVAT were isolated from 23-week-old SPZF and CP. The effects of PVAT on acetylcholine- and nitroprusside-induced relaxation were examined using bioassays with phenylephrine-contracted arterial rings. Acetylcholine-induced relaxations without PVAT in SPZF and CP were 0.7- and 0.5-times lower in females than in males, respectively. In the presence of PVAT, acetylcholine-induced relaxations increased 1.4- and 2-times in male and female CP, respectively, but did not differ in SPZF. Nitroprusside-induced relaxation with and without PVAT was 0.7-times lower in female than in male SPZF but did not differ in CP. Angiotensin-II type-1 receptor (AT1R)/AT1R-associated protein mRNA ratios were lower in CP than in the SPZF and negatively correlated with the difference in arterial relaxation with and without PVAT. The effects of renal artery PVAT differed between the SPZF and CP groups. Higher levels of enhanced AT1R activity in SPZF PVAT may drive these differences by impairing the vascular smooth muscle responses to nitric oxide.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".