Characterization of the vasorelaxation to methanandamide in rat gastric arteries
Bibliographic record
Abstract
In the present study, the relaxant effect of the cannabinoid methanandamide was explored in rat gastric arteries. Since in some vessels cannabinoids have been shown to release calcitonin gene-related peptide (CGRP) from perivascular nerves, the influence of methanandamide was compared with that of exogenous CGRP. Methanandamide and CGRP elicited concentration-dependent, endothelium-independent relaxations. Methanandamide-induced relaxations were unaffected by the CB1 receptor antagonist AM251, the CB2 receptor antagonists AM630 and SR144528, and combined pre-exposure to AM251 and SR144528. Pre-exposure to O-1918, an antagonist of a novel nonCB1/nonCB2 cannabinoid receptor, did not influence the relaxations to methanandamide. Capsaicin or capsazepine treatment slightly inhibited methanandamide-induced relaxations. Preincubation with 30 mmol/L extracellular K+ or 3 mmol/L TEA had no significant effect on the responses elicited by methanandamide, but reduced CGRP-induced relaxations. Relaxation to 10(-5) mol/L methanandamide was significantly blunted by Bay K8644 and by preincubation with nifedipine. Furthermore, 10(-5) mol/L methanandamide significantly inhibited CaCl2-induced contractions in norepinephrine-stimulated vessels previously depleted of intra- and extracellular Ca2+. Finally, preincubation with 10(-5) mol/L methanandamide almost completely abolished high K+-induced contractions. These findings suggest that the vasorelaxant action of methanandamide in rat gastric arteries is not mediated by stimulation of known cannabinoid receptors and only partly related to stimulation of TRPV1 receptors on perivascular nerves. At high concentrations, methanandamide might induce relaxation by reducing calcium entry into the smooth muscle cells.
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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".