Genetic Selection for High and Low Alcohol Consumption in a Limited‐Access Paradigm
Bibliographic record
Abstract
BACKGROUND: Several rat lines have been bred for their differences in alcohol consumption based on a continuous-access paradigm in which alcohol solution is available 24 hr/day. The limited-access paradigm (LAP), in which access to alcohol solution is restricted to a short period per day, however, has been used extensively to investigate the neurochemical mechanisms underlying alcohol consumption. There is evidence of possible differences in genetic determination of alcohol drinking in a continuous- versus limited-access condition. For these reasons, selective breeding for high- and low-alcohol consumption (HARF and LARF, respectively) based on a LAP was conducted. METHODS: N/Nih rats were used as the breeding stock. A within-family breeding procedure was used to develop HARF and LARF lines with 10 families per line. Access to alcohol solution was restricted to 20 min/day. Alcohol was provided as 3%, 6% and 12% w/v solutions. Average intake of alcohol during the 12% phase was used as the selection criterion. Inbreeding began in the seventh generation. RESULTS: After the sixth generation of selection, rats from the HARF line consumed an average of 1.2 g/kg, whereas rats from the LARF line consumed an average of 0.6 g/kg of alcohol during the 20-min access period. Alcohol consumption remained stable over the next eight generations of inbreeding. In the continuous-access-drinking paradigm, the HARF and LARF rats consumed an average of 5.5 to 7.0 g/kg and 1.0 to 2.0 g/kg of alcohol per day respectively. An estimated heritability of 0.25 was obtained. CONCLUSIONS: These findings indicate that alcohol drinking in the LAP is influenced by genetic factors. Differences in alcohol drinking in the LAP also generalize to continuous access drinking. These rat lines will be very useful for investigations into the genetic and neurochemical mechanisms underlying alcohol drinking.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".