Automated home-cage-like monitoring for assessing innate behaviors in a murine hangover model
Abstract The prevalence of alcohol consumption among the younger generation remains alarmingly high. A hangover is a common short-term consequence observed after consuming alcohol. To effectively study alcohol-induced hangovers, reliable and translational animal models, along with appropriate testin...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-13334-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract The prevalence of alcohol consumption among the younger generation remains alarmingly high. A hangover is a common short-term consequence observed after consuming alcohol. To effectively study alcohol-induced hangovers, reliable and translational animal models, along with appropriate testing methods, are required. While several testing approaches have been used in hangover-induced mice, they often fail to assess innate behaviors comprehensively and are limited by short observation periods. Although existing studies have developed methods to assess hangover-related behaviors in rodents, few have focused on innate behaviors. This study aimed to establish a model for assessing the innate behaviors of hangover-induced mice using automated home-cage-like behavioral monitoring. Mice were intraperitoneally injected with ethanol at doses of 3, 2, or 1 g/kg, followed by behavioral assessments, including exploratory actions and long-term home-cage-like behaviors during both day and night phases. Results showed a significant reduction in mobile behaviors (climbing, locomotion, rearing), speed, and distance traveled, along with increased immobility in both exploratory and long-term home-cage-like assessments. Furthermore, there was a significant decrease in exploratory behaviors and long-term home-cage-like activities, which were linked to hangover symptoms. This study provides a preliminary approach for assessing hangover behaviors in mice using automated behavioral monitoring, ensuring improved animal welfare, optimised timing, and extended assessment durations. Hence, we propose automated home-cage-like behavioral assessment as an exploratory model for evaluating hangover behaviors in mice, which may serve as a useful tool for future research on the therapeutic efficacy of anti-hangover compounds. |
|---|---|
| ISSN: | 2045-2322 |