Effect of timing of energy and carbohydrate replacement on post-exercise insulin action
Bibliographic record
Abstract
The nutritional environment surrounding an exercise bout modulates post-exercise insulin action. The purpose of this study was to determine how timing energy and carbohydrate replacement proximate to an exercise bout influences exercise-enhanced insulin action. To create an appropriate baseline, sensitivity to insulin was reduced in 9 healthy young men (n=6) and women (n=3) by 2 days of energy surplus and detraining. Then, insulin action (glucose uptake per unit plasma insulin) was assessed by stable isotope dilution during a continuous glucose infusion 12 h after a standardized meal under 4 conditions. In 3 conditions, the meal replaced the energy and carbohydrate expended during an exercise bout (62.9+/-2.8 min cycle ergometry at 65% VO2 peak followed by ten 30 s sprints). The meal was given before (Pre), immediately after (ImmPost), or 3 h after exercise (Delay). The 4th condition was a no-exercise control (Control). Data were analyzed using linear mixed-effects models with planned contrasts. Relative to Control, insulin action increased by 22% in Pre (p=0.05), 44% in ImmPost (p<0.01), and 19% in Delay (p=0.09). Non-oxidative disposal was higher, and oxidative disposal was lower in ImmPost relative to Control and Pre (p<0.05). Hepatic glucose production was suppressed by the infusion to a greater extent in Pre and Delay (76.9%+/-8.8% and 81.2%+/-4.7%) compared with ImmPost (64.7%+/-10.0%). A bout of exercise enhances insulin action even when expended energy and carbohydrate are replaced. Further, timing of energy and carbohydrate consumption subtly modulates the effectiveness of exercise to enhance insulin action.
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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".