The selective dopamine D3 receptor antagonist SB 277011-A, but not the partial agonist BP 897, blocks cue-induced reinstatement of nicotine-seeking
Bibliographic record
Abstract
The dopamine D3 receptor (DRD3) has been suggested to be involved in the mechanisms underlying stimulus-controlled drug-seeking behaviour. Ligands acting as DRD3 antagonists (SB 277011-A) or DRD3 partial agonists (BP 897) have shown some promise for reducing the influence of drug-associated cues on motivational behaviour. Here, effects of SB 277011-A and BP 897 were evaluated on cue-induced reinstatement of nicotine-seeking in rats. The effects of BP 897 on nicotine self-administration under a fixed-ratio 5 (FR5) schedule of reinforcement were also evaluated. SB 277011-A (1-10 mg/kg) was able to block cue-induced reinstatement of nicotine-seeking, indicating that DRD3 selective antagonism may be an effective approach to prevent relapse for nicotine. In contrast, BP 897 did not block the cue-induced reinstatement of nicotine-seeking or nicotine-taking under the FR5 schedule. In a control study, rats did not respond to the light stimuli without nicotine delivery, indicating that the responding for the drug-associated cues was induced by the previous pairing of light stimuli with nicotine's effects. These findings validate the role of DRD3 on reactivity to drug-associated stimuli and suggest that the DRD3 antagonist, but perhaps not the DRD3 partial agonist, could be used to prevent relapse in tobacco smokers.
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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 | 0.000 |
| 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 | 0.001 |
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".