Genetic basis for the psychostimulant effects of nicotine: a quantitative trait locus analysis in AcB/BcA recombinant congenic mice
Bibliographic record
Abstract
Genetic differences in sensitivity to nicotine have been reported in both animals and humans. The present study utilized a novel methodology to map genes involved in regulating both the psychostimulant and depressant effects of nicotine in the AcB/BcA recombinant congenic strains (RCS) of mice. Locomotor activity was measured in a computerized open-field apparatus following subcutaneous administration of saline (days 1 and 2) or nicotine on day 3. The phenotypic measures obtained from this experimental design included total basal locomotor activity, as well as total nicotine activity, nicotine difference scores, nicotine percent change and nicotine regression residual scores. The results indicated that the C57BL/6J (B6) were insensitive to nicotine over the entire dose-response curve (0.1, 0.2, 0.4 and 0.8 mg/kg). However, the 0.8-mg/kg dose of nicotine produced a significant decrease in the locomotor activity in the A/J strain and a wide and continuous range of both locomotor excitation and depression among the AcB/BcA RCS. Single-locus association analysis in the AcB RCS identified quantitative trait loci (QTL) for the psychostimulant effects of nicotine on chromosomes 11, 12, 13, 14 and 17 and one QTL for nicotine-induced depression on chromosome 11. In the BcA RCS, nicotine-induced locomotor activation was associated with seven putative regions on chromosomes 2, 7, 8, 13, 14, 16 and 17. There were no overlapping QTL and no genetic correlations between saline- and nicotine-related phenotypes in the AcB/BcA RCS. A number of putative candidate genes were in proximity to regions identified with nicotine sensitivity, including the alpha2 subunit of the nicotinic acetylcholine receptor and the dopamine D3 receptor.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".