PAR-2 elicits afferent arteriolar vasodilation by NO-dependent and NO-independent actions
Bibliographic record
Abstract
Proteinase-activated receptors (PARs) are a novel class of G protein-coupled receptors that respond to signals through endogenous proteinases. PAR activation involves enzymatic cleavage of the extracellular NH(2)-terminal domain and unmasking of a new NH(2) terminus, which serves as an anchored ligand to activate the receptor. At least four PAR subtypes have been identified. In the present study, we used the in vitro perfused hydronephrotic rat kidney to examine the effects of activating PAR-2 on the afferent arteriole. The synthetic peptide SLIGRL-NH(2), which corresponds to the exposed ligand sequence and selectively activates PAR-2, did not alter basal afferent arteriolar diameter but caused a concentration-dependent vasodilation (3-30 microM) of arterioles preconstricted by angiotensin II (0.1 nM). A modified peptide sequence (LSIGRL-NH(2), inactive at PAR-2) had no effect. This vasodilation was characterized by an initial transient component followed by a smaller sustained response. A similar pattern of vasodilation was seen when SLIGRL-NH(2) was administered to isolated perfused normal rat kidney. The sustained component of the PAR-2-induced afferent arteriolar vasodilation was eliminated by nitric oxide (NO) synthase inhibition (100 microM nitro-L-arginine methyl ester). In contrast, the transient vasodilation persisted under these conditions. This transient response was not observed when afferent arterioles were preconstricted with elevated KCl, suggesting involvement of an endothelium-derived hyperpolarizing factor. Finally, RT-PCR revealed the presence of PAR-2 mRNA in isolated afferent arterioles. These findings indicate that PAR-2 is expressed in the afferent arteriole and that its activation elicits afferent arteriolar vasodilation by NO-dependent and NO-independent mechanisms.
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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) | 0.001 | 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".