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Record W2065492838 · doi:10.1097/jes.0b013e3181f4bb2a

Carbohydrate Availability and Training Adaptation

2010· review· en· W2065492838 on OpenAlexaff
Martin J. Gibala

Bibliographic record

VenueExercise and Sport Sciences Reviews · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGlycogenAthletesEndurance trainingStrength trainingAdaptive responseMedicineSports nutritionAdaptation (eye)Physical medicine and rehabilitationExercise physiologyPhysical therapyPsychologyInternal medicineBiology

Abstract

fetched live from OpenAlex

It is well known that nutrition can influence the acute and chronic response to exercise, including athletic performance and training-induced adaptations in skeletal muscle. One classic example is the positive relationship between carbohydrate intake, muscle glycogen content, and endurance exercise capacity. Leading sports nutrition experts continue to advocate that athletes who partake in activities that are heavily reliant on glycogen for energy ingest sufficient amounts of carbohydrate before, during, and after exercise (1). The general premise for this recommendation is that habitual training in a chronic high-carbohydrate state will maximize the training impulse and optimize performance. However, a long-standing unresolved question is whether it is a lack or a surplus of substrate that triggers the adaptive response to exercise. In this issue of Exercise and Sport Sciences Reviews, Drs. John A. Hawley and Louise M. Burke review the evidence from recent studies that have investigated whether selected markers of endurance training adaptation are enhanced to a greater extent when individuals commence periodic training sessions with low compared with normal or high carbohydrate availability (4). Several years ago, Danish researchers (3) published an intriguing study that reported greater increases in the maximal activities of oxidative enzymes and exercise time to fatigue when one leg was trained twice per day (with restricted carbohydrate intake between sessions) as compared with the contralateral leg that trained once daily. Given the unique experimental design, the original study authors were careful to note the limitations of their work, cautioning, "Coaches and athletes should be careful not to draw practical consequences of the present study with regard to training regimens." Nonetheless, the article coined the term "train low, compete high," a catchphrase borrowed from altitude physiology that Hawley and Burke (4) argue has become widely used in athletic circles (and scientific literature) to describe a range of practices other than the original protocol, with the potential for confusion owing to misunderstood terminology. For example, it is often overlooked that in the original study by Hansen et al. (3), only half of the training sessions were initiated with low muscle glycogen. Hawley and Burke (4) observe that there are many ways of manipulating carbohydrate availability, and their considerate review highlights subtle differences in various experimental designs that are important to properly evaluate the evidence for and against "training low." A periodic train-low approach may indeed offer a time-efficient method to augment adaptations, even in athletes who are already highly trained (5). Using a nutritional manipulation similar to Hansen et al. (3), but with a more applied research design that simulated the usual practice of competitive athletes, Yeo et al. (5) showed that cyclists who trained twice a day on alternate days experienced greater increases in mitochondrial enzymes and whole-body fat oxidation compared with a group that trained once daily. The mechanisms responsible for the enhanced skeletal muscle oxidative capacity under conditions of restricted carbohydrate intake remain largely elusive, but recent evidence points to several nutrient-sensitive signaling molecules that may be involved in the adaptive response (2). A conundrum highlighted by Hawley and Burke is that, despite the changes in "mechanistic" variables that should in theory enhance exercise performance (e.g., increased phosphorylation state of signaling molecules and/or the expression of proteins involved in mitochondrial biogenesis), there is a mismatch in many studies in that whole-body functional outcomes (e.g., changes in training capacity or measures of performance) remain unchanged. The authors propose several explanations for this disconnect, noting we have inadequate knowledge of underlying adaptive mechanisms as well as surprisingly little knowledge about glycogen utilization during the training sessions typically undertaken by competitive athletes or how their current real-world training and dietary practices interact to influence performance.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.072
GPT teacher head0.328
Teacher spread0.256 · 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 designOther design
Domainnot available
GenreReview

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

Citations2
Published2010
Admission routes1
Has abstractyes

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