The effect of exercise intensity and excess postexercise oxygen consumption on postprandial blood lipids in physically inactive men
Bibliographic record
Abstract
Reductions in postprandial lipemia have been observed following aerobic exercise of sufficient energy expenditure. Increased excess postexercise oxygen consumption (EPOC) has been documented when comparing high- versus low-intensity exercise. The contribution of EPOC energy expenditure to alterations in postprandial lipemia has not been determined. The purpose of this study was to evaluate the effects of low- and high-intensity exercise on postprandial lipemia in healthy, sedentary, overweight and obese men (age, 43 ± 10 years; peak oxygen consumption, 31.1 ± 7.5 mL·kg−1·min−1; body mass index, 31.8 ± 4.5 kg/m2) and to determine the contribution of EPOC to reductions in postprandial lipemia. Participants completed 4 conditions: nonexercise control, low-intensity exercise at 40%–50% oxygen uptake reserve (LI), high-intensity exercise at 70%–80% oxygen uptake reserve (HI), and HI plus EPOC re-feeding (HI+EERM), where the difference in EPOC energy expenditure between LI and HI was re-fed in the form of a sports nutrition bar (Premier Nutrition Corp., Emeryville, Calif., USA). Two hours following exercise participants ingested a high-fat (1010 kcals, 99 g sat fat) test meal. Blood samples were obtained before exercise, before the test meal, and at 2, 4, and 6 h postprandially. Triglyceride incremental area under the curve was significantly reduced following LI, HI, and HI+EERM when compared with nonexercise control (p < 0.05) with no differences between the exercise conditions (p > 0.05). In conclusions, prior LI and HI exercise equally attenuated postprandial triglyceride responses to the test meal. The extra energy expended during EPOC does not contribute significantly to exercise energy expenditure or to reductions in postprandial lipemia in overweight men.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".