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Effects Of Leucine-Enriched Protein Supplementation On Subsequent Performance And Metabolism Following High-Intensity Cycling

2011· article· en· W2324431264 on OpenAlexaff
André R. Nelson, Stuart M. Phillips, Trent Stellingwerff, Stephen J. Bruce, Anita Thorimbert, Philipe A. Guy, Jim Clarke, Suzanne Broadbent, David S. Rowlands

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsLeucineProtein metabolismMetabolismInternal medicineEndocrinologyCarbohydrateProtein turnoverChemistryAmino acidCrossover studyValineCarbohydrate metabolismBiochemistryProtein biosynthesisBiologyMedicine

Abstract

fetched live from OpenAlex

Recently we observed that the addition of leucine with protein to high-carbohydrate recovery feeding ingested following intense cycling over 3 days led to a small enhancement in subsequent performance. It is also established that post-exercise protein feeding, both with and without added leucine, attenuates muscle damage and soreness, and can increase muscle-protein synthesis, but the metabolic consequences are largely unknown. PURPOSE: To investigate further putative mechanisms and the effects on metabolism of a post-exercise leucine-protein supplement and confirm a benefit to subsequent performance. METHODS: In a double-blind randomized crossover, 12 male cyclists ingested either a leucine/protein/carbohydrate/fat supplement (LEUPRO; respectively 7.5/20/89/22 g·h-1) or isocaloric carbohydrate/fat control (CON: 119/22 g·h-1) for 1-3 h post-exercise during a 6-day training block. Protein intake was clamped at 1.9 (LEUPRO) and 1.5 g·kg-1d∑-1 (CON). Using stable isotope methodology and LC-MS based metabolomics we determined the impact of LEUPRO on leucine turnover and amino acid metabolism. RESULTS: Following exercise, LEUPRO increased branch-chain amino acids (BCAA) in plasma (2.6-fold; 90%CL ×/÷1.1) and urine (2.8-fold; ×/÷1.2) and products of their metabolism: plasma acylcarnitine C5 (3.0-fold; ×/÷0.9) and urinary β-aminoisobutyrate (3.4-fold; ×/÷1.4). LEUPRO also increased whole-body leucine oxidation (5.6-fold; ×/÷1.1) and synthesis (4.8-fold; ×/÷1.1), and only with LEUPRO was recovery leucine balance (mean ± SD: 580 ± 215 μmol·kg-1h∑-1, control; -43 ± 24 μmol·kg-1h∑-1) and day-1 nitrogen balance (17 ± 20 mg·kg-1, control; -90 ± 44 mg·kg-1) positive. However, subsequent day 2-5 nitrogen balance was positive in CON (111 ± 86 mg·kg-1; LEUPRO: 130 ± 110 mg·kg-1). LEUPRO reduced serum creatine kinase by 21-25% (90%CL ±14%). Despite these effects, the impact of LEUPRO on sprint power was trivial (day 4: 0.4% ±1.0%; day 6: -0.3% ±1.0%). CONCLUSIONS: Despite saturation of post-exercise BCAA metabolism and apparent attenuated tissue damage, a leucine-protein supplement had a trivial effect on performance compared to control, possibly due to both treatment groups being in positive nitrogen balance. Supported by a grant from Nestec Ltd., Vevey, Switzerland.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.011
GPT teacher head0.248
Teacher spread0.236 · 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 designBench or experimental
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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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