Real-time behavioral monitoring of C57BL/6J mice during reproductive cycle
Bibliographic record
Abstract
Introduction The present study aims to identify differences in behavioral profiles in post-pubertal C57BL/6J males and female mice across distinct phases of the reproductive cycle in a home cage environment. Methods To reduce human bias, we used an automated behavioral analysis system HomeCageScan from CleverSys Inc. Mice were monitored continuously, and resulting data were summarized across 24-h, light, and dark cycles. Behavioral activities of each period were analyzed using hierarchical clustering, factor analysis, and principal component analysis. Results Females exhibited higher levels of physically demanding activities, including ambulatory and exploratory movements, particularly during estrus and metestrus, with estrus showing up to 30% more activity than males. In contrast, males consistently engaged in more sleep-related behaviors across all phases, with significantly higher engagement during the light cycle compared to females in proestrus and estrus ( p < 0.0001); the extent of this sex difference was greater during proestrus and estrus than in metestrus and diestrus ( p < 0.01). Notably, distinct patterns of sleep fragmentation were observed, with females experiencing greater disruptions during the light cycle, while males showed similar disruptions during the dark cycle. Feeding and resourcing behaviors were highest in males, showing up to 20% increase compared to cycling females, as well as significantly engaging in habituation-related behaviors such as feeding and digging. Interphase differences were observed within females, such as a significant increase of habituation-related activities during estrus compared to proestrus and diestrus ( p < 0.05), while during the dark cycle, these activities peaked during the diestrus phase ( p < 0.05). Female mice in the metestrus phase exhibited more sleep-related behaviors than those in proestrus. Discussion Our study has revealed prevalent behavioral differences due to sex, and inter-phase variations by employing a continuous monitoring approach designed to reduce bias. This methodology ensures a comprehensive understanding of natural behavioral patterns and strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".