Waking levels of salivary biomarkers are altered following sleep in a lab with no further increase associated with simulated night-time noise exposure
Bibliographic record
Abstract
The goals of this study were twofold. First, we assessed if waking salivary hormone profiles are altered by nighttime noise exposure in a laboratory environment. Second, we evaluated the potential influence that sleeping in the lab in itself may have had on salivary biomarkers, by comparing results obtained following sleep at home. Twelve adults (7 males, 5 females) between 19-25 yrs slept at home and in a sleep laboratory. Subjects provided six saliva samples during waking hours on the day prior to sleep in the lab, on both days after sleeping in the lab and on the day following the resumption of sleep at home. Following one night of adaptation, subjects were exposed throughout the 2nd night to simulated backup alarms that consisted of trains of 5 consecutive 500 ms duration audible tones. The time between the onset of each tone was 1 s and the time between trains (offset to onset) was 15 to 20 s. When compared to home conditions, cortisol and melatonin levels were higher following sleep in the laboratory 30 minutes after awakening. However, no significant differences were noted for any salivary biomarker between the 1st and 2nd night in the sleep lab, suggesting that these endpoints were not influenced by exposure to noise on the 2nd night. Waking profiles of alpha-amylase were not influenced by where the subjects slept. Subjective reports of sleep disturbance following sleep in the lab were also obtained. For most of the day there was no apparent influence of the laboratory noise exposure. However, subjects did report more sleepiness during the evening (8 pm) following the 2nd night in the laboratory. In general, overall sleep quality was rated slightly higher upon awakening from sleep at home. Factors that might have contributed to the observations in this study are discussed, including those related to the potentially non-representative sample.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".