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Record W2044153324 · doi:10.1139/h10-017

Effect of milk-based carbohydrate-protein supplement timing on the attenuation of exercise-induced muscle damage

2010· article· en· W2044153324 on OpenAlexvenueno aff
Emma Cockburn, Emma Stevenson, Philip R. Hayes, Paula Robson‐Ansley, Glyn Howatson

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsMuscle damageIngestionMedicineCreatine kinaseLimitingDelayed onset muscle sorenessInternal medicineEndocrinologyCarbohydrate

Abstract

fetched live from OpenAlex

Exercise-induced muscle damage (EIMD) leads to decrements in muscle performance and increases in intramuscular enzymes measured in the plasma, and to delayed onset of muscle soreness (DOMS), partly due to the activation of degradative pathways. It has been shown that milk-based carbohydrate-protein (CHO-P) can limit changes in markers of EIMD, possibly by attenuating protein degradation and (or) increasing protein synthesis. However, the timing of supplementation has received limited attention, and this may alter the response. This study examined the effects of acute milk-based CHO-P supplementation timing on the attenuation of EIMD. Four independent matched groups of 8 healthy males consumed milk-based CHO-P before (PRE), immediately after (POST), or 24 h after (TWENTY-FOUR) muscle-damaging exercise. Active DOMS, isokinetic muscle performance, reactive strength index (RSI), and creatine kinase (CK) were assessed immediately before and 24, 48, and 72 h after EIMD. POST and TWENTY-FOUR demonstrated a benefit in limiting changes in active DOMS, peak torque, and RSI over 48 h, compared with PRE. PRE showed a possible benefit in reducing increases in CK over 48 h and limiting changes in other variables over 72 h. Consuming milk-based CHO-P after muscle-damaging exercise is more beneficial in attenuating decreases in muscle performance and increases in active DOMS at 48 h than ingestion prior to 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.014
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.243
Teacher spread0.234 · 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 teacher head, 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".

Quick stats

Citations92
Published2010
Admission routes1
Has abstractyes

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