Skin Temperature Rhythms in Humans Respond to Changes in the Timing of Sleep and Light
Bibliographic record
Abstract
Body temperature is known to vary with circadian phase and to be influenced by factors that can mask its circadian expression. We wanted to test whether skin temperature rhythms were sensitive to an abrupt shift of the sleep schedule and to the resetting effects of light. Nineteen healthy subjects spent 6 days in time isolation and underwent a simulated night-shift procedure. They were assigned to either a control group ( n = 10) or bright light group ( n = 9) and measurements were taken under a baseline day-oriented schedule and during the 4 th cycle of a night-oriented schedule. In the bright light group, participants were exposed to a 3-cycle 8-h exposure of ~6,500 lux at night, while the control group remained in dim light conditions (~3 lux). Skin temperature was recorded in 10 and 4 participants from the control and bright light groups, respectively. We found significant circadian rhythms of plasma melatonin, core body temperature (CBT), and skin temperature at baseline for both groups ( p < 0.001 for all). Rhythms of melatonin, CBT, and skin temperature following night shifts were significantly phase delayed by about 7 to 9 h ( p < 0.05) in response to bright light at night, whereas there was no shift in the control group. In addition, we found that at bedtime melatonin does not consistently increase before the increase in distal skin temperature and subsequent decrease in CBT, in contrast to what has been previously reported. The present study shows that, in constant posture conditions, skin temperature rhythms have an evoked component sensitive to abrupt changes in the timing of sleep. They also comprise an endogenous component that is sensitive to the resetting effects of bright light exposure. These results have applications for the determination of circadian phase, as skin temperature is less intrusive than rectal temperature recordings.
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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".