Postexercise Muscle Glycogen Recovery Enhanced with a Carbohydrate-Protein Supplement
Bibliographic record
Abstract
PURPOSE: This study assessed whether liquid carbohydrate-protein (C+P) supplements, ingested early during recovery, enhance muscle glycogen resynthesis versus isoenergetic liquid carbohydrate (CHO) supplements, given early or an isoenergetic solid meal given later during recovery (PLB). METHODS: Two hours after breakfast (7.0 kcal.kg; 0.3 g.kg P, 1.2 g.kg C, 0.1 g.kg F), six male cyclists performed a 60-min time trial (AMex). Pre- and postexercise, vastus lateralis glycogen concentrations were determined using nMRS. Immediately, 1 h, and 2 h postexercise, participants ingested C+P (4.8 kcal.kg; 0.8 g.kg C, 0.4 g.kg P), CHO (4.8 kcal.kg; 1.2 g.kg C), or PLB (no energy). Four hours postexercise, a solid meal was ingested. At that time, C+P and CHO received a meal identical to breakfast, whereas PLB received 21 kcal.kg (1 g.kg P, 3.6 g.kg C, 0.3 g.kg F); energy intake during 6 h of recovery was identical among treatments. After 6 h of recovery, measurement and cycling protocols (PMex) were repeated. RESULTS: Absolute muscle glycogen utilization was 18% greater (P <or= 0.05) during AMex (C+P: -42.75+/-5.24 mmol.L; CHO: -37.08+/-7.59 mmol.L; PLB: -53.78+/-11.59 mmol.L; P=0.302) relative to PMex (C+P: -38.40+/-4.37 mmol.L; CHO: -31.16+/-3.78 mmol.L; PLB: -40.33+/-1.47 mmol.L; P=0.292), but there were no differences between groups. During 6 h of recovery, muscle glycogen resynthesis was greater in C+P (+ 28.62+/-2.10 mmol.L) versus CHO (+ 22.20+/-1.19 mmol.L, P <or= 0.05) or PLB (+18.50+/-7.67 mmol.L, P <or= 0.05). Cycling performance was similiar (P=0.282) among treatments during both AMex (C+P: 37.61+/-0.63 km; CHO: 37.03+/-0.60 km; PLB: 37.24+/-0.34 km) and PMex (C+P: 36.31+/-0.83 km; CHO: 36.38+/-0.80 km; PLB: 35.34+/-0.45 km). CONCLUSIONS: C+P supplements, given early after exercise, enhance glycogen resynthesis relative to CHO and PLB. However, this does not influence performance in this type of exercise bout.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".