The selective anandamide transport inhibitor VDM11 attenuates reinstatement of nicotine seeking behaviour, but does not affect nicotine intake
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The endocannabinoid system appears to play a pivotal role in mediating the rewarding and reinforcing effects of nicotine. Recent studies have shown that the inhibition of fatty acid amide hydrolase (FAAH) attenuates reinstatement of nicotine-seeking induced by nicotine priming and nicotine-associated cues. FAAH hydrolyses the endogenous endocannabinoid anandamide, as well as other non-cannabinoid ligands such as oleoylethanolamide (OEA) and palmitoylethanolamide (PEA). As OEA and PEA can attenuate both nicotine-taking and nicotine-seeking behaviour, the specific role of anandamide remains unclear. In this study, we have tested the selective anadamide uptake inhibitor, VDM11, which elevates anandamide levels without affecting levels of OEA/PEA, on nicotine-taking and nicotine-seeking behaviour. EXPERIMENTAL APPROACH: We used a nicotine intravenous self-administration model in rats to assess the effect of VDM11, given i.p., on nicotine taking using fixed and progressive ratio schedules of reinforcement as well as on reinstatement of nicotine-seeking induced by nicotine priming and nicotine-associated cues. KEY RESULTS: VDM11 did not affect levels of responding for nicotine under fixed-ratio and progressive-ratio schedules of reinforcement. In contrast, VDM11 dose-dependently attenuated reinstatement of nicotine-seeking behaviour induced by nicotine-associated cues and nicotine priming. CONCLUSIONS AND IMPLICATIONS: These results indicate that ligands elevating anandamide levels could have therapeutic value for preventing relapse into nicotine-seeking behaviour and should be tested in humans trying to quit smoking.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".