Predominance of Distal Skin Temperature Changes at Sleep Onset across Menstrual and Circadian Phases
Bibliographic record
Abstract
Menstrual cycle-associated changes in reproductive hormones affect body temperature in women. We aimed to characterize the interaction between the menstrual, circadian, and scheduled sleep-wake cycles on body temperature regulation. Eight females entered the laboratory during the midfollicular (MF) and midluteal (ML) phases of their menstrual cycle for an ultradian sleep-wake cycle procedure, consisting of 36 cycles of 60-minute wake episodes alternating with 60-minute nap opportunities, in constant bed-rest conditions. Core body temperature (CBT) and distal skin temperature (DT) were recorded and used to calculate a distal-core gradient (DCG). Melatonin, sleep, and subjective sleepiness were also recorded. The circadian variation of DT and DCG was not affected by menstrual phase. DT and DCG showed rapid, large nap episode-dependent increases, whereas CBT showed slower, smaller nap episode-dependent decreases. DCG values were significantly reduced for most of the wake episode in an overall 60-minute wake/60-minute nap cycle during ML compared to MF, but these differences were eliminated at the wake-to-nap lights-out transition. Nap episode-dependent decreases in CBT were further modulated as a function of both circadian and menstrual factors, with nap episode-dependent deceases occurring more prominently during the late afternoon/evening in ML, whereas nap episode-dependent DT and DCG increases were not significantly affected by menstrual phase but only circadian phase. Circadian rhythms of melatonin secretion, DT, and DCG were significantly phase-advanced relative to CBT and sleep propensity rhythms. This study explored how the thermoregulatory system is influenced by an interaction between circadian phase and vigilance state and how this is further modulated by the menstrual cycle. Current results agree with the thermophysiological cascade model of sleep and indicate that despite increased CBT during ML, heat loss mechanisms are maintained at a similar level during nap episodes, which may allow for comparable circadian sleep propensity rhythms between menstrual phases.
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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 | 0.000 |
| 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".