Modulatory role of baseline impulsivity on the acute and persistent effects of CB <sub>1</sub> agonism on impulsive choice
Bibliographic record
Abstract
Background: Impulsivity may be defined as a heterogeneous construct characterized by difficulties in inhibiting actions and premature decision-making. Although a high level of impulsivity is recognized as a risk factor for cannabis use disorder, the effects of cannabinoids on impulsive choices have been less explored. Aims: This study aimed to determine the acute and persistent effects of CB 1/2 agonism on impulsive choice in rats using a delay-discounting task (DDT). Methods: Trained adult male Sprague-Dawley rats were injected with either vehicle or increasing doses (0.1, 1, and 5 mg/kg) of the CB 1/2 agonist WIN 55212-2 and tested in the DDT. Results: Our results showed that the effect of WIN55212-2 correlated with baseline impulsivity and reduced impulsivity in rats classified as high impulsive, while no effect was observed in rats classified as low impulsivity. Two weeks after the last WIN55212-2 injection, the rats were injected with vehicle and re-exposed to DDT. Rats classified as high impulsive maintained a significantly high AUC log value, suggesting a long-lasting effect of WIN 55212-2. Finally, the CB 1 receptor antagonist rimonabant (1 mg/kg) reversed the effect of repeated treatment with WIN55212-2 on impulsivity in the high-impulsive population, suggesting an active role of the CB 1/2 receptor in the persistent effect of WIN55212-2. Conclusions: Our results suggest a potential benefit of CB 1/2 agonism in vulnerable subpopulations with high levels of impulsivity. To maximize therapeutic benefits and minimize potential iatrogenic effects, assessing choice impulsivity and other variables is essential, aligning with personalized medicine principles to effectively tailor interventions.
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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 | 0.001 |
| 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".