Hyperpolarization of murine small caliber mesenteric arteries by activation of endothelial proteinase-activated receptor 2
Bibliographic record
Abstract
Activation of endothelial proteinase-activated receptor 2 (PAR-2) relaxes vascular smooth muscle (VSM) and causes hypotension by nitric oxide (NO)-prostanoid-dependent and -independent mechanisms. We investigated whether endothelium-dependent hyperpolarization of VSM was the mechanism whereby resistance caliber arteries vasodilated independently of NO. VSM membrane potentials and isometric tension were measured concurrently to correlate the electrophysiological and mechanical changes in murine small caliber mesenteric arteries. In uncontracted arteries, the PAR-2 agonist, SLIGRL-NH2 (0.1 to 10 micromol/L), hyperpolarized the VSM membrane potential only in endothelium-intact arterial preparations. This response was unaltered by treatment of arteries with inhibitors of NO synthases (L-NAME), soluble guanylyl cyclase (ODQ), and cyclooxygenases (indomethacin). L-NAME, ODQ, and indomethacin also failed to inhibit SLIGRL-NH2-induced hyperpolarization and of cirazoline-contracted mesenteric arteries. However, in blood vessels that were depolarized and contracted with 30 mmol/L KCl, the effects of the SLIGRL-NH2 on membrane potential and tension were not observed. SLIGRL-NH2-induced hyperpolarization and relaxation was inhibited completely by the combination of apamin plus charybdotoxin, but only partially inhibited after treatment with the combination of barium plus ouabain, suggesting an important role for SKCa and IKCa channels and a lesser role for Kir channels and Na+/K+ ATPases in the hyperpolarization response. We concluded that activation of endothelial PAR-2 hyperpolarized the vascular smooth muscle (VSM) cells of small caliber arteries, without requiring the activation of NO synthases, cyclooxygenases, or soluble guanylyl cyclase. Indeed, this hyperpolarization may be a primary mechanism for PAR-2-induced hypotension in vivo.
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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".