Effect of sleep restriction, with or without prior evening exercise, on morning postprandial lipemia
Bibliographic record
Abstract
Sleep restriction (SR) impairs postprandial glycemia following a high-glucose challenge and exercise improves it, but their combined impact on postprandial lipemia in response to a high-fat challenge remains unknown. This project investigated whether one night of SR impairs morning postprandial lipemia and if prior evening exercise influences the response. We hypothesized SR would induce an exaggerated postprandial lipemic response to a high-fat morning challenge and that prior evening exercise would fully or partially ameliorate these impairments. In 10 sedentary individuals with overweight or obesity (females: 4, age: 28.1 ± 3.8 years, body mass index: 30.4 ± 2.2 kg/m2), we compared the effects of one night of SR (4 h) to normal sleep (8 h), with and without prior moderate-intensity aerobic exercise (45 min, 65% VO2max), on postprandial lipemia and satiety following a standardized high-fat morning challenge (4 h). Spline regression was used to compare differences in the time course of the blood-based outcomes between exercise and sleep conditions. No significant differences were observed in fasting or 2 h concentrations of glucose, insulin, non-esterified fatty acids, or triglyceride, areas under the curves, indexes of metabolism, or satiety between conditions. However, exercise had an interaction between the spline term and exercise and sleep conditions ( p < 0.001) for glucose, insulin, non-esterified fatty acids, and triglycerides during the high-fat challenge. The findings indicate that one night of SR has minimal effects on morning postprandial lipemia, irrespective of previous aerobic exercise. Notably, exercise reduced triglyceride concentrations in the latter half of the testing period, although this effect was abolished during SR conditions. Clinical trial #: NCT05713370.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".