Effects of Social Defeat Stress on Sleep in Mice
Bibliographic record
Abstract
Stress plays a key role in the development of psychiatric disorders and has a negative impact on sleep integrity. In mice, chronic social defeat stress (CSDS) is an ethologically valid model of stress-related disorders but little is known about its effects on sleep regulation. Here, we investigated the immediate and long-term effects of 10 consecutive days of social defeat (SD) on vigilance states in C57Bl/6J male mice. Social behavior was assessed to identify susceptible mice, i.e., mice that develop long-lasting social avoidance, and unsusceptible mice. Sleep-wake stages in mice of both groups were analyzed by means of polysomnographic recordings at baseline, after the first, third, and tenth stress sessions and on the 5th recovery day (R5) following the 10-day CSDS. In susceptible mice, each SD session produced biphasic changes in sleep-wake states that were preserved all along 10-day CSDS. These sessions elicited a short-term enhancement of wake time while rapid eye-movement (REM) sleep was strongly inhibited. Concomitantly, delta power was increased during non REM (NREM) sleep. During the following dark period, an increase in total sleep time, as well as wake fragmentation, were observed after each analyzed SD session. Similar changes were observed in unsusceptible mice. At R5, elevated high-frequency EEG activity, as observed in insomniacs, emerged during NREM sleep in both susceptible and unsusceptible groups suggesting that CSDS impaired sleep quality. Furthermore, susceptible but not unsusceptible mice displayed stress-anticipatory arousal during recovery, a common feature of anxiety disorders. Altogether, our findings show that CSDS has profound impacts on vigilance states and further support that sleep is tightly regulated by exposure to stressful events. They also revealed that susceptibility to chronic psychological stress is associated with heightened arousal, a physiological feature of stress vulnerability.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".