Minimal whey protein with carbohydrate stimulates muscle protein synthesis following resistance exercise in young men.
Bibliographic record
Abstract
Whey protein is a supplemental protein source used by athletes, particularly those aiming to gain muscle mass; however, direct evidence for its efficacy in stimulating muscle protein synthesis (MPS) is lacking. We aimed to determine the impact of consuming whey protein on skeletal muscle protein turnover in the post-exercise period. Eight healthy young men (BMI = 26.8±0.9; age = 21±1) participated in a double-blind randomized cross-over trial in which they performed a unilateral leg resistance exercise workout – EX – (4 sets of knee extensions and 4 sets of leg press – 8–10 reps per set), such that the other leg was not exercised and acted as a rested (RE) comparator. After exercise subjects consumed either an isocaloric whey protein plus carbohydrate beverage (10g whey and 21g fructose) – WHEY – or a carbohydrate beverage containing fructose and maltodextrin (21g and 10g, respectively) – CHO. Subjects received pulse-tracer injections of L[ring-2H5]phenylalanine and L-[15N]phenylalanine to measure MPS. Exercise stimulated a rise in MPS only in the WHEY-EX leg, which was greater than MPS in the WHEY-RE leg and also the CHO-EX leg (all P<0.01). We conclude that a small dose (10g) of whey protein with carbohydrate (21g) can stimulate a rise in MPS after resistance exercise which, overtime, would be supportive of a net muscle protein accrual and hypertrophy. Supported by the US National Dairy Council.
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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) | 0.001 | 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".