Functional characteristics of alpha adrenergic and endothelinergic receptors in pressurized rat mesenteric veins
Bibliographic record
Abstract
Increasing transmural pressure can alter the functional role of post-junctional receptor subtypes. Under conditions of changing transmural pressure, we investigated the relative contributions of alpha adrenergic (α-ARs) and endothelinergic receptors to norepinephrine (NE) and endothelin (ET-1) contractile responses, respectively, in third-order rat mesenteric small veins (MSV) and arteries (MSA). NE, phenylephrine (PE), clonidine, and ET-1 concentration-response curves were constructed in the absence and presence of α-adrenergic and ET-1 receptor antagonists, respectively. MSV were more sensitive to NE, PE, and ET-1 compared with MSA. The sensitivity of MSV to NE was higher than that to PE. Phentolamine (α1-AR/α2-AR antagonist) and prazosin (α1-AR antagonist) completely abolished NE responses. Yohimbine (α2-AR antagonist) reduced NE and clonidine contractile responses in MSV. Clonidine contractile responses were reduced by prazosin in MSA. In MSA and MSV, BQ-610 (ET(A) receptor antagonist) but not BQ-788 (ET(B) receptor antagonist) reduced ET-1 contractile responses. Combined application of BQ-610 and BQ-788 caused further reduction in ET-1 concentration-response curves obtained in MSV. These results suggest that in addition to α1-ARs and ET(A) receptors, α2-ARs and ET(B) receptors also mediate NE and ET-1 contractile responses in MSV, respectively, with no change in the participation of these receptors as transmural pressure is increased.
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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".