Chronic Alcohol Consumption Alters Home-Cage Behaviors and Responses to Ethologically Relevant Predator Tasks in Mice
Bibliographic record
Abstract
Abstract Alcohol use disorders (AUD) are the most prevalent substance use disorders worldwide. Considering recent reports indicating an increase in alcohol use particularly in females, it is vital to understand how alcohol history impacts behavior. Animal model research on withdrawal-associated affective states tends to focus on males, forced alcohol paradigms, and a few traditional anxiety/stress tests. While this has been essential, heavy alcohol use triggers adverse withdrawal-related affective states that can influence how people respond to a large variety of life events and stressors. To this end, we show that behaviors in the home-cage, open field, looming disc, and robogator predator threat task, which vary in task demand and intensity, are altered in mice with a history of voluntary alcohol consumption. In alcohol-exposed males, behaviors in the home cage, a low anxiety baseline environment, suggest increased vigilance/exploration. However, in the open field and robogator task, which induce heightened arousal and task demands, a more hesitant/avoidant phenotype is seen. Female alcohol mice show no behavioral alterations in the home cage and open field test, however, in the looming disc task, which mimics an overhead advancing predator and forces a behavioral choice, we see greater escape responses compared to water controls, indicative of active stress coping behaviors. This suggests females may begin to show alcohol-induced alterations as task demands increase. To date, few drugs have advanced past clinical trials for the treatment of AUD, and those that have are predominately used in life-threatening situations only. No treatments exist for ameliorating negative withdrawal related states, which could aid in harm reduction related to heavy alcohol use. Understanding how withdrawal alters a variety of behavioral responses that are linked to stress coping can widen our understanding of alcohol abuse and lead us closer to better therapeutics to help individuals with AUD.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".