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Record W2734997369 · doi:10.3390/nu9070735

Whey Protein Supplementation Enhances Whole Body Protein Metabolism and Performance Recovery after Resistance Exercise: A Double-Blind Crossover Study

2017· article· en· W2734997369 on OpenAlexafffund
Daniel W. D. West, Sidney Abou Sawan, Michael Mazzulla, Eric Williamson, Daniel R. Moore

Bibliographic record

VenueNutrients · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Toronto
FundersMitacs
KeywordsCrossover studyWhey proteinResistance trainingMetabolismMedicineProtein metabolismEndocrinologyInternal medicineFood scienceChemistryPlacebo

Abstract

fetched live from OpenAlex

No study has concurrently measured changes in free-living whole body protein metabolism and exercise performance during recovery from an acute bout of resistance exercise. We aimed to determine if whey protein ingestion enhances whole body net protein balance and recovery of exercise performance during overnight (10 h) and 24 h recovery after whole body resistance exercise in trained men. In a double-blind crossover design, 12 trained men (76 ± 8 kg, 24 ± 4 years old, 14% ± 5% body fat; means ± standard deviation (SD)) performed resistance exercise in the evening prior to consuming either 25 g of whey protein (PRO; MuscleTech 100% Whey) or an energy-matched placebo (CHO) immediately post-exercise (0 h), and again the following morning (~10 h of recovery). A third randomized trial, completed by the same participants, involving no exercise and no supplement served as a rested control trial (Rest). Participants ingested [15N]glycine to determine whole body protein kinetics and net protein balance over 10 and 24 h of recovery. Performance was assessed pre-exercise and at 0, 10, and 24 h of recovery using a battery of tests. Net protein balance tended to improve in PRO (P = 0.064; effect size (ES) = 0.61, PRO vs. CHO) during overnight recovery. Over 24 h, net balance was enhanced in PRO (P = 0.036) but not in CHO (P = 0.84; ES = 0.69, PRO vs. CHO), which was mediated primarily by a reduction in protein breakdown (PRO < CHO; P < 0.01. Exercise decreased repetitions to failure (REP), maximal strength (MVC), peak and mean power, and countermovement jump performance (CMJ) at 0 h (all P < 0.05 vs. Pre). At 10 h, there were small-to-moderate effects for enhanced recovery of the MVC (ES = 0.56), mean power (ES = 0.49), and CMJ variables (ES: 0.27–0.49) in PRO. At 24 h, protein supplementation improved MVC (ES = 0.76), REP (ES = 0.44), and peak power (ES = 0.55). In conclusion, whey protein supplementation enhances whole body anabolism, and may improve acute recovery of exercise performance after a strenuous bout of resistance exercise.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.014
GPT teacher head0.281
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations104
Published2017
Admission routes2
Has abstractyes

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