Increased Vulnerability to Nicotine Self-Administration and Relapse in Alcohol-Naive Offspring of Rats Selectively Bred for High Alcohol Intake
Bibliographic record
Abstract
The prevalence of smoking in human alcoholics is substantially higher than in the general population, and results from twin studies suggest that a shared genetic vulnerability underlies alcohol and nicotine addiction. Here, we directly tested this hypothesis by examining nicotine-taking behavior in alcohol-naive offspring of alcohol-preferring (P) rats and alcohol-nonpreferring (NP) rats that had been selectively bred for high and low alcohol intake. The self-administration of intravenous nicotine (0.015-0.060 mg/kg per infusion) in P rats was more than twice than that of NP rats. Nicotine seeking induced by reexposure to nicotine cues in extinction tests was also substantially greater in P rats than in NP rats. In a subsequent relapse test, priming nicotine injections reinstated drug seeking in P rats but not NP rats. P rats also self-administered higher amounts of oral sucrose (1-20%) than NP rats, a finding consistent with previous reports. In contrast, self-administration of intravenous cocaine (0.1875-1.125 mg/kg per infusion) was remarkably similar in the P and NP rats; however, P-NP differences in cocaine seeking emerged in subsequent extinction and cocaine priming-induced reinstatement tests. In both cases, lever responding was higher in P rats than in NP rats. Thus, alcohol-naive offspring of rats genetically selected for high alcohol intake are highly susceptible to nicotine self-administration and relapse, and this susceptibility is not likely caused by general reward deficits in NP rats. The present findings provide experimental evidence for the hypothesis that a shared genetic determinant accounts for the co-abuse of nicotine and alcohol.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".