Circadian Variation of Sleep During the Follicular and Luteal Phases of the Menstrual Cycle
Bibliographic record
Abstract
STUDY OBJECTIVES: Women experience insomnia more frequently than men. Menstrual cycle changes in reproductive hormones and circadian rhythms may contribute to sleep disruptions. Our aim, therefore, was to clarify the interaction between menstrual and circadian processes as it affects sleep. DESIGN: Participants entered the laboratory during the mid-follicular (MF) and mid-luteal (ML) phases of their menstrual cycle for an ultra-rapid sleep-wake cycle (URSW) procedure, consisting of 36 cycles of 60-min wake episodes alternating with 60-min nap opportunities. This procedure concluded with an ad libitum nap episode. SETTING: Time-isolation suite. PARTICIPANTS: Eight unmedicated, physically and mentally healthy females with regular ovulatory menstrual cycles. INTERVENTIONS: N/A. MEASUREMENTS: Polysomnographic sleep from nocturnal sleep episodes and 60-min naps; subjective alertness; core body temperature (CBT); salivary melatonin; urinary estradiol; and urinary progesterone. RESULTS: Increased CBT values at night and decreased CBT amplitude were observed during ML compared to MF. Circadian phase of CBT and the circadian melatonin profile were unaffected by menstrual phase. All analyzed sleep parameters showed a circadian variation throughout the URSW procedure, with no menstrual phase differences observed for most, including slow wave sleep (SWS). The circadian variation of REM sleep duration, however, was sensitive to menstrual phase, with reduced REM sleep during ML at circadian phase 0 degrees and 30 degrees. CONCLUSIONS: Moderate but significant changes in REM sleep across the menstrual and circadian cycles were observed. These results support an interaction between circadian and menstrual processes in the regulation of REM 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 | 0.001 |
| 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 | 0.000 |
| 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".