Diurnal Variation in Vascular Function: Role of Sleep
Bibliographic record
Abstract
Although vascular function is lower in the morning than afternoon, previous studies have not assessed the influence of prior sleep on this diurnal variation. The authors employed a semiconstant routine protocol to study the contribution of prior nocturnal sleep to the previously observed impairment in vascular function in the morning. Brachial artery vascular function was assessed using the flow-mediated dilation technique (FMD) in 9 healthy, physically active males (mean ± SD: 27 ± 9 yrs of age), at 08:00 and 16:00 h following, respectively, 3.29 ± .37 and 3.24 ± .57 h prior sleep estimated using actimetry. Heart rate and systolic and diastolic blood pressures were also measured. The data of the experimental sleep condition were compared with the data of the "normal" diurnal sleep condition, in which FMD measurements were obtained from 21 healthy individuals who slept only during the night, as usual, before the morning test session. The morning-afternoon difference in FMD was 1 ± 4% in the experimental sleep condition compared with 3 ± 4% in the normal sleep condition (p = .04). This difference was explained by FMD being 3 ± 3% lower in afternoon following the prior experimental sleep (p = .01). These data suggest that FMD is more dependent on the influence of supine sleep than the endogenous circadian timekeeper, in agreement with our previous finding that diurnal variation in FMD is influenced by exercise. These findings also raise the possibility of a lower homeostatic "set point" for vascular function following a period of sleep and in the absence of perturbing hemodynamic fluctuation.
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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) | 0.001 | 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".