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Post-Exercise Protein Ingestion Increases Whole Body Leucine Balance in a Dose-Dependent Manner in Healthy Children

2016· article· en· W2461831278 on OpenAlexaff
Kimberly A. Volterman, Daniel R. Moore, Peter Breithaupt, Elizabeth Offord‐Cavin, Leonidas G. Karagounis, Brian W. Timmons

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsLeucineIngestionChemistryEndocrinologyInternal medicineAnimal scienceMealProtein metabolismNitrogen balanceMetabolismMedicineAmino acidBiochemistryBiology

Abstract

fetched live from OpenAlex

PURPOSE: Post-exercise protein ingestion increases whole body protein balance in healthy children early in recovery (i.e., 9 h), although the optimal single meal protein dose has yet to be determined. Therefore, we employed, for the first time in active children, a primed constant [13C]leucine infusion to determine with greater accuracy and time resolution the effect of variable protein ingestion on post-exercise whole body leucine metabolism. METHODS: Thirty-five active children (26 males; 9-13 y, 44.9 ± 10.6 kg; means ± SD) underwent a 5-day adaptation diet (0.95 g protein·kg-1·d-1) before performing an acute bout of exercise (3x20min cycling) with concurrent primed constant infusion of [13C]leucine. After exercise, participants consumed an isoenergetic (140 kcal) carbohydrate beverage containing a variable amount of milk-protein [0g, CONT; 5g, LP; 10g, MP; and 15 g, HP] enriched with [2H3]leucine to a level of 4 % of beverage leucine content (assuming 10% leucine content of protein). Blood and breath samples were taken over 3h of recovery to determine whole body leucine oxidation (LeuOX) and net balance (LeuBAL). RESULTS: Total leucine intake (drink + infusion) was: 6.2 ± 0.2 mg·kg-1 (CONT); 18.4 ± 2.5 mg·kg-1 (LP); 29.0 ± 4.2 mg·kg-1 (MP); 40.8 ± 8.8 mg·kg-1 (HP). LeuBAL showed a main effect for condition [HP (24.2 ± 8.2 mg·kg-1) > MP (11.6 ± 4.3 mg·kg-1) > LP (5.7 ± 1.9 mg·kg-1) > CONT (-3.0 ± 1.7 mg·kg-1); all P < 0.01], with all conditions different from zero (all P < 0.001). Linear correlation (r2=0.69, P < 0.001) indicated LeuBAL became positive at ~10 mg·kg-1 leucine intake. Bi-phase regression analyses (r2=0.68) revealed LeuOX reached a plateau at ~34 mg·kg-1·3h-1 leucine intake, which could suggest leucine intakes above this level represented a nutrient overload in our population over the 3h post-exercise period. CONCLUSION: During the 3h post-exercise recovery period, LeuBAL (a surrogate for net protein balance) was negative in the absence of protein ingestion. Consumption of high quality protein increased LeuBAL in a dose-dependent manner; however, 5-10g may be optimal to promote post-exercise whole body protein recovery as an apparent saturation in the oxidative disposal of leucine suggests leucine intakes above ~34mg/kg in healthy children may provide no further benefit. Study funded by Nestec Ltd.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.253
Teacher spread0.247 · 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
Published2016
Admission routes1
Has abstractyes

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