Dopamine D3 Receptor Is Necessary for Ethanol Consumption: An Approach with Buspirone
Bibliographic record
Abstract
Mesolimbic dopamine (DA) controls drug- and alcohol-seeking behavior, but the role of specific DA receptor subtypes is unclear. We tested the hypothesis that D3R gene deletion or the D3R pharmacological blockade inhibits ethanol preference in mice. D3R-deficient mice (D3R(-/-)) and their wild-type (WT) littermates, treated or not with the D3R antagonists SB277011A and U99194A, were tested in a long-term free choice ethanol-drinking (two-bottle choice) and in a binge-like ethanol-drinking paradigm (drinking in the dark, DID). The selectivity of the D3R antagonists was further assessed by molecular modeling. Ethanol intake was negligible in D3R(-/-) and robust in WT both in the two-bottle choice and DID paradigms. Treatment with D3R antagonists inhibited ethanol intake in WT but was ineffective in D3R(-/-) mice. Ethanol intake increased the expression of RACK1 and brain-derived neurotrophic factor (BDNF) in both WT and D3R(-/-); in WT there was also a robust overexpression of D3R. Thus, increased expression of D3R associated with activation of RACK1/BDNF seems to operate as a reinforcing mechanism in voluntary ethanol intake. Indeed, blockade of the BDNF pathway by the TrkB selective antagonist ANA-12 reversed chronic stable ethanol intake and strongly decreased the striatal expression of D3R. Finally, we evaluated buspirone, an approved drug for anxiety disorders endowed with D3R antagonist activity (confirmed by molecular modeling analysis), that resulted effective in inhibiting ethanol intake. Thus, DA signaling via D3R is essential for ethanol-related reward and consumption and may represent a novel therapeutic target for weaning.
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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) | 0.001 | 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".