The acute effects of light on murine sleep during the dark phase: importance of melanopsin for maintenance of light‐induced sleep
Bibliographic record
Abstract
Light exerts a direct effect on sleep and wakefulness in nocturnal and diurnal animals, with a light pulse during the dark phase suppressing locomotor activity and promoting sleep in the former. In the present study, we investigated this direct effect of light on various sleep parameters by exposing mice to a broad range of illuminances (0.2-200 μW/cm(2) ; equivalent to 1-1000 lux) for 1 h during the dark phase (zeitgeber time 13-14). Fitting the data with a three-parameter log model indicated that ~0.1 μW/cm(2) can generate half the sleep response observed at 200 μW/cm(2). We observed decreases in total sleep time during the 1 h following the end of the light pulse. Light reduced the latency to sleep from ~30 min in darkness (baseline) to ~10 min at the highest intensity, although this effect was invariant across the light intensities used. We then assessed the role of melanopsin during the rapid transition from wakefulness to sleep at the onset of a light pulse and the maintenance of sleep with a 6-h 20 μW/cm(2) light pulse. Even though the melanopsin knockout mice had robust induction of sleep (~35 min) during the first hour of the pulse, it was not maintained. Total sleep decreased by almost 65% by the third hour in comparison with the first hour of the pulse in mice lacking melanopsin, whereas only an 8% decrease was observed in wild-type mice. Collectively, our findings highlight the selective effects of light on murine sleep, and suggest that melanopsin-based photoreception is primarily involved in sustaining light-induced sleep.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".