Whey Protein Supplementation Enhances Whole Body Protein Metabolism and Recovery of Performance after Resistance Exercise: A Double‐blind Crossover Study
Bibliographic record
Abstract
Post‐exercise protein consumption enhances muscle and whole body anabolism for up to 24h by providing amino acids to support increased rates of protein synthesis. However, little research has addressed if high quality protein consumption may concomitantly facilitate the acute recovery of exercise performance. We aimed to determine if a whey protein supplement enhances whole body net protein balance during overnight and 24h recovery and whether supplementation supported greater recovery of exercise performance over this same period. In a double‐blind crossover design, 12 healthy resistance‐trained men (76 ± 8 kg, 24 ± 4 y, 14 ± 5% body fat; means ± SD) performed a strenuous bout of whole body resistance exercise in the evening prior to consuming either 25g of MuscleTech 100% Whey protein (REx+PRO) or an energy‐matched placebo (REx+CHO) immediately after exercise as well as the following morning (i.e., after 10h recovery). A third randomized trial involving no exercise or supplement served as a control trial (Rest). Participants ingested 2 mg [ 15 N]glycine/kg to determine whole body nitrogen turnover, protein synthesis, breakdown, and net balance over 10 and 24h of recovery. Exercise performance was assessed before and immediately, 10h, and 24h after exercise using the following tests: i) knee extension repetitions‐to‐failure (REP) and maximal isometric strength (MVC); ii) peak (PP) and mean (MP) anaerobic power via Wingate, and; iii) countermovement jump as an indicator of neuromuscular fatigue. Data were analyzed using two‐way repeated measures ANOVA and, using Cohen's d effect size (ES), by calculating the Probability of REx+PRO Superiority (PS) versus REx+CHO (50% = no effect). There was a trend ( P = 0.064; ES = 0.61; PS = 67%) toward an effect of condition on net protein balance during 10‐h overnight recovery. Over 24h, net protein balance was enhanced in REx+PRO ( P = 0.036 vs. Rest; ES = 0.69; PS = 69%) but not in REx+CHO ( P = 0.84 vs. Rest), which was mediated primarily through a reduction in protein breakdown (REx+PRO < REx+CHO; P < 0.01). Exercise decreased REP, MVC, PP, MP, and CMJ in post‐testing (all P < 0.05, Pre vs. Post). At 10h recovery, REx+PRO tended to enhance recovery of MVC (ES = 0.56; PS = 65%), MP (ES = 0.49; PS = 64%), and markers of neuromuscular function including jump height (ES = 0.49; PS = 64%), peak velocity (ES = 0.27; PS = 58%) and kinetic energy at take‐off (ES = 0.30; PS = 58%). At 24h, potential benefits to neuromuscular fatigue were negligible (ES for CMJ variables = −0.09 to −0.38; PS = 41–49%) whereas protein supplementation appeared to be beneficial for the recovery of MVC (ES = 1.15; PS = 79%), REP (ES = 0.44; PS = 62%), and PP (ES = 0.55; PS = 65%). There was no correlation between recovery in performance tests and whole body net balance at 10 or 24h (all P > 0.05, r < 0.3). In conclusion, whey protein supplementation enhances whole body net protein balance after an acute bout of whole body resistance exercise. The improvement in select exercise tasks suggests whey protein supplementation enhances the rate of performance recovery in trained young men. Support or Funding Information Supported by Iovate Health Sciences Int. and Mitacs
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".