Suppression of acute and anticipatory nausea by peripherally restricted fatty acid amide hydrolase inhibitor in animal models: role of PPARα and CB<sub>1</sub> receptors
Bibliographic record
Abstract
Background and Purpose Effective treatments of nausea are limited. In this study we evaluated the ability of the peripherally restricted fatty acid amide hydrolase (FAAH) inhibitor, URB937, to suppress acute and anticipatory nausea in rats and examined the pharmacological mechanism of this effect. Experimental Approach We investigated the potential of URB937 (administered i.p.) to reduce the establishment of lithium chloride‐induced conditioned gaping (model of acute nausea) and to reduce the expression of contextually‐elicited conditioned gaping (model of anticipatory nausea) in rats. The role of CB1 receptors, CB2 receptors and PPARα in the anti‐nausea effect of URB937 was examined. The potential of URB937 to suppress FAAH activity in tissue collected from the area postrema (AP), prefrontal cortex (PFC), liver and duodenum and to elevate levels of FAAH substrates – anandamide (AEA), N‐oleoylethanolamide (OEO) and N‐palmitoylethanolamide (PEA) – in the AP was also evaluated. Key Results URB937 reduced acute nausea by a PPARα‐dependent mechanism and reduced anticipatory nausea by a CB1 receptor‐dependent mechanism. The PPARα agonist, GW7647, similarly attenuated acute nausea. URB937 reduced FAAH activity in the liver and the duodenum but not in the PFC. In addition, URB937 reduced FAAH activity and elevated levels of fatty‐acid ethanolamides in the AP, a brain region that is not protected by the blood–brain barrier. Conclusions and Implications The anti‐nausea action of URB937 may occur in the AP and may involve PPARα to suppress acute nausea and CB1 receptors to suppress anticipatory nausea.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".