Arvanil, anandamide and <i>N</i>‐arachidonoyl‐dopamine (NADA) inhibit emesis through cannabinoid CB1 and vanilloid TRPV1 receptors in the ferret
Bibliographic record
Abstract
Cannabinoid (CB) agonists suppress nausea and vomiting (emesis). Similarly, transient receptor potential vanilloid-1 (TRPV1) receptor agonists are anti-emetic. Arvanil, N-(3-methoxy-4-hydroxy-benzyl)-arachidonamide, is a synthetic 'hybrid' agonist of CB1 and TRPV1 receptors. Anandamide and N-arachidonoyl-dopamine (NADA) are endogenous agonists at both these receptors. We investigated if arvanil, NADA and anandamide were anti-emetic in the ferret and their mechanism of action. All compounds reduced the episodes of emesis in response to morphine 6 glucuronide. These effects were attenuated by AM251, a CB1 antagonist that was pro-emetic per se, and TRPV1 antagonists iodoresiniferatoxin and AMG 9810, which were without pro-emetic effects. Similar sensitivity to arvanil and NADA was found for prodromal signs of emesis. We analysed the distribution of TRPV1 receptors in the ferret brainstem and, for comparison, the co-localization of CB1 and TRPV1 receptors in the mouse brainstem. TRPV1 immunoreactivity was largely restricted to the nucleus of the solitary tract of the ferret, with faint labeling in the dorsal motor nucleus of the vagus and sparse distribution in the area postrema. A similar distribution of TRPV1, and its extensive co-localization with CB1, was observed in the mouse. Our findings suggest that CB1 and TRPV1 receptors in the brainstem play a major role in the control of emesis by agonists of these two receptors. While there appears to be an endogenous 'tone' of CB1 receptors inhibiting emesis, this does not seem to be the case for TRPV1 receptors, indicating that endogenously released endocannabinoids/endovanilloids inhibit emesis preferentially via CB1 receptors.
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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 | 0.000 |
| 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".