Adding protein to a carbohydrate drink increases skeletal muscle protein synthesis during recovery from prolonged aerobic exercise
Bibliographic record
Abstract
Protein (PRO) ingestion with carbohydrate (CHO) during recovery from prolonged exercise may promote muscle glycogen synthesis; however, an additional benefit may be an increase in muscle protein synthesis. This study used stable isotope tracer methodology to examine the effect of CHO or CHO+PRO ingestion on mixed skeletal muscle protein fractional synthetic rates (FSR) following prolonged exercise. Six men (22±1 yr) performed 2 h of cycle exercise to reduce body CHO stores. Following exercise, subjects ingested either a CHO+PRO drink (1.2g CHO + 0.4g PRO/kg/h), an iso‐CHO drink (L‐CHO: 1.2g CHO/kg/h) or an iso‐energetic CHO drink (H‐CHO: 1.6g CHO/kg/h) every 15 min for 3 h. Subjects completed all trials in random order, separated by 1 wk. Prior to each trial, subjects received a primed constant infusion of L‐[ring‐ 2 H 5 ]‐phenylalanine (Phe) and muscle FSR was determined from biopsies (v lateralis) obtained at 0 and 4 h of recovery. Analysis of variance revealed that muscle FSR was higher in the CHO+PRO trial (0.088±0.008 %/h) compared to both CHO trials (L‐CHO: 0.066±0.006, H‐CHO: 0.060±0.007; p<0.05). We conclude that adding PRO to a CHO drink increases muscle protein synthesis during recovery from prolonged exercise compared to CHO alone. The higher FSR during recovery may promote the muscle adaptive response to training by facilitating synthesis of new proteins stimulated by exercise. Supported by NSERC, Canada.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".