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Record W2340544773 · doi:10.2527/2005.8313_supple32x

Role of dietary energy source in the expression of chronic exertional myopathies in horses

2005· article· en· W2340544773 on OpenAlexaff
Raymond J. Geor

Bibliographic record

VenueJournal of Animal Science · 2005
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGlycogenInternal medicineCarbohydrateMyopathyEndocrinologyMuscle disorderPolysaccharideDiabetes mellitusOxidative stressPathophysiologyChemistryFood scienceMedicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Muscle disorders characterized by the development of pain and stiffness during and after exercise (exertional rhabdomyolysis, ER) are common in horses. Two heritable forms of chronic ER have been identified: 1) polysaccharide storage myopathy (PSSM), a condition characterized in quarter horses and related breeds, but also reported to occur in other breeds; and 2) recurrent exertional rhabdomyolysis (RER) in Thoroughbreds. Although the pathophysiology of PSSM and RER are different, there is epidemiological and experimental evidence that feeding diets rich in hydrolyzable carbohydrates (starch and simple sugars) enhances the phenotypic expression of both disorders. The PSSM is characterized by increased insulin sensitivity, excessive muscle glycogen storage, and the accumulation of amylase-resistant polysaccharide in muscle. The feeding of concentrates rich in hydrolyzable carbohydrates may enhance disease expression by increasing the quantity of glucose available for muscle glycogen synthesis. On the other hand, diets rich in starches and simples sugars may increase clinical expression of RER via enhancement of stress and anxiety, factors known to increase the risk of ER in horses with RER. A decrease in the frequency and severity of ER has been observed when horses with PSSM and RER are fed diets with reduced DE from hydrolyzable carbohydrates (<10 to 15% of total diet) and increased DE from fat (15 to 20%) and other energy sources, such as beet pulp and soybean hulls.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.056
GPT teacher head0.363
Teacher spread0.308 · 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

Citations5
Published2005
Admission routes1
Has abstractyes

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