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Record W1833382316 · doi:10.2746/042516409x479603

Nutritional aspects of post exercise skeletal muscle glycogen synthesis in horses: A comparative review

2010· review· en· W1833382316 on OpenAlexaff
Amanda P. Waller, Michael I. Lindinger

Bibliographic record

VenueEquine Veterinary Journal · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSkeletal muscleGlycogenHorseMedicineInternal medicinePhysical medicine and rehabilitationEndocrinologyBiology

Abstract

fetched live from OpenAlex

Carbohydrate (CHO) stored in the form of skeletal muscle glycogen is the main energy source for glycolytic and oxidative ATP production during vigorous exercise in mammals. In man, horse and dog both short-term high intensity and prolonged submaximal exercise deplete muscle glycogen. In horses, however, muscle glycogen synthesis is 2-3-fold slower than in man and rat, even when a diet high in soluble CHO is fed. There appear to be significant differences in CHO and glycogen metabolism between horses and other mammals, and it is becoming increasingly clear that many conclusions drawn from human exercise physiology do not apply to horses. This review aims to provide a comprehensive, comparative summary of the research on muscle glycogen synthesis in horse, man and rodent. Species differences in CHO uptake and utilisation are examined and the issues with feeding high soluble CHO diets to horses are discussed. Alternative feeding strategies, including protein and long and short chain fatty acid supplementation and the importance of rehydration, are explored.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.050
GPT teacher head0.344
Teacher spread0.294 · 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 designNot applicable
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

Citations36
Published2010
Admission routes1
Has abstractyes

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