Inhibition of anandamide hydrolysis by cyclohexyl carbamic acid 3â²-carbamoyl-3-yl ester (URB597) reverses abuse-related behavioral and neurochemical effects of nicotine in rats
Bibliographic record
Abstract
Emerging evidence suggests that the rewarding, abuse-related effects of nicotine are modulated by the endocannabinoid system of the brain. For example, pharmacological blockade or genetic deletion of cannabinoid CB1receptors can reduce or eliminate many abuse-related behavioral and neurochemical effects of nicotine. Furthermore, doses of Δ9- tetrahydrocannabinol and nicotine that are ineffective when given alone can induce conditioned place preference when given together. These previous studies have used systemically administered CB1receptor agonists and antagonists and gene deletion techniques, which affect cannabinoid CB1receptors throughout the brain. A more functionally selective way to alter endocannabinoid activity is to inhibit fatty acid amide hydrolase (FAAH), thereby magnifying and prolonging the effects of the endocannabinoid anandamide only when and where it is synthesized and released on demand. Here, we combined behavioral and neurochemical approaches to evaluate whether the FAAH inhibitor URB597 (cyclohexyl carbamic acid 3′-carbamoyl-3-yl ester) could alter the abuse-related effects of nicotine in rats. We found that URB597, at a dose (0.3 mg/kg) that had no behavioral effects by itself, prevented development of nicotine-induced conditioned place preference (CPP) and acquisition of nicotine self-administration. URB597 also reduced nicotine-induced reinstatement in both CPP and self-administration models of relapse. Furthermore, in vivo microdialysis showed that URB597 reduced nicotine-induced dopamine elevations in the nucleus accumbens shell, the terminal area of the brain's mesolimbic reward system. These findings suggest that FAAH inhibition can counteract the addictive properties of nicotine and that FAAH may serve as a new target for development of medications for treatment of tobacco dependence.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".