Inhibition of monoacylglycerol lipase attenuates vomiting in <i>Suncus murinus</i> and 2‐arachidonoyl glycerol attenuates nausea in rats
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: To evaluate the role of 2-arachidonoyl glycerol (2AG) in the regulation of nausea and vomiting using animal models of vomiting and of nausea-like behaviour (conditioned gaping). EXPERIMENTAL APPROACH: Vomiting was assessed in shrews (Suncus murinus), pretreated with JZL184, a selective monoacylglycerol lipase (MAGL) inhibitor which elevates endogenous 2AG levels, 1 h before administering the emetogenic compound, LiCl. Regulation of nausea-like behaviour in rats by exogenous 2AG or its metabolite arachidonic acid (AA) was assessed, using the conditioned gaping model. The role of cannabinoid CB(1) receptors, CB(2) receptors and cyclooxygenase (COX) inhibition in suppression of vomiting or nausea-like behaviour was assessed. KEY RESULTS: JZL184 dose-dependently suppressed vomiting in shrews, an effect prevented by pretreatment with the CB(1) receptor inverse agonist/antagonist, AM251. In shrew brain tissue, JZL184 inhibited MAGL activity in vivo. In rats, 2AG suppressed LiCl-induced conditioned gaping but this effect was not prevented by AM251 or the CB(2) receptor antagonist, AM630. Instead, the COX inhibitor, indomethacin, prevented suppression of conditioned gaping by 2AG or AA. However, when rats were pretreated with a high dose of JZL184 (40 mg·kg(-1) ), suppression of gaping by 2AG was partially reversed by AM251. Suppression of conditioned gaping was not due to interference with learning because the same dose of 2AG did not modify the strength of conditioned freezing to a shock-paired tone. CONCLUSIONS AND IMPLICATIONS: Our results suggest that manipulations that elevate 2AG may have anti-emetic or anti-nausea potential. LINKED ARTICLES: This article is part of a themed section on Cannabinoids in Biology and Medicine. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2012.165.issue-8. To view Part I of Cannabinoids in Biology and Medicine visit http://dx.doi.org/10.1111/bph.2011.163.issue-7.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".