Low muscle glycogen concentration does not suppress the anabolic response to resistance exercise
Bibliographic record
Abstract
We determined the effect of muscle glycogen concentration and postexercise nutrition on anabolic signaling and rates of myofibrillar protein synthesis after resistance exercise (REX). Sixteen young, healthy men matched for age, body mass, peak oxygen uptake (Vo(2peak)) and strength (one repetition maximum; 1RM) were randomly assigned to either a nutrient or placebo group. After 48 h diet and exercise control, subjects undertook a glycogen-depletion protocol consisting of one-leg cycling to fatigue (LOW), whereas the other leg rested (NORM). The next morning following an overnight fast, a primed, constant infusion of l-[ring-(13)C(6)] phenylalanine was commenced and subjects completed 8 sets of 5 unilateral leg press repetitions at 80% 1RM. Immediately after REX and 2 h later, subjects consumed a 500 ml bolus of a protein/CHO (20 g whey + 40 g maltodextrin) or placebo beverage. Muscle biopsies from the vastus lateralis of both legs were taken at rest and 1 and 4 h after REX. Muscle glycogen concentration was higher in the NORM than LOW at all time points in both nutrient and placebo groups (P < 0.05). Postexercise Akt-p70S6K-rpS6 phosphorylation increased in both groups with no differences between legs (P < 0.05). mTOR(Ser2448) phosphorylation in placebo increased 1 h after exercise in NORM (P < 0.05), whereas mTOR increased ~4-fold in LOW (P < 0.01) and ~11 fold in NORM with nutrient (P < 0.01; different between legs P < 0.05). Post-exercise rates of MPS were not different between NORM and LOW in nutrient (0.070 ± 0.022 vs. 0.068 ± 0.018 %/h) or placebo (0.045 ± 0.021 vs. 0.049 ± 0.017 %/h). We conclude that commencing high-intensity REX with low muscle glycogen availability does not compromise the anabolic signal and subsequent rates of MPS, at least during the early (4 h) postexercise recovery period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".