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Record W2493641194 · doi:10.1111/asj.12655

Fast‐to‐slow shift of muscle fiber‐type composition by dietary apple polyphenols in rats: Impact of the low‐dose supplementation

2016· article· en· W2493641194 on OpenAlexaff
Wataru Mizunoya, Shinpei Okamoto, Hideo Miyahara, Mariko Akahoshi, Takahiro Suzuki, Q. Mai‐Khoi, Hideaki Ohtsubo, Yusuke Komiya, Mulan Qahar, Toshiaki Waga, Koichi Nakazato, Yoshihide Ikeuchi, Judy E. Anderson, Ryuichi Tatsumi

Bibliographic record

VenueAnimal Science Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMyosinIsometric exerciseEndocrinologyInternal medicineHindlimbAtrophyMyoglobinLower bodyAnimal scienceChemistryLeg muscleMuscle hypertrophyMedicineAnatomyBiologyPhysical medicine and rehabilitationBiochemistry

Abstract

fetched live from OpenAlex

Our previous studies demonstrated that an 8-week intake of 5% (w/w) apple polyphenol (APP) in the diet improves muscle endurance of young-adult rats. In order to identify a lower limit of the dietary contribution of APP to the effect, the experiments were designed for lower-dose supplementation (8-week feeding of 0.5% APP in AIN-93G diet) to 12-week-old male Sprague-Dawley rats. Results clearly showed that the 0.5% APP diet significantly up-regulates slower myosin-heavy-chain (MyHC) isoform ratios (IIx and IIa relative to total MyHC) and myoglobin expression in lower hind-limb muscles examined (P < 0.05). There was a trend to increased fatigue resistance detected from measurements of relative isometric plantar-flexion force torque generated by a stimulus train delivered to the tibial nerve (F(98, 1372) = 1.246, P = 0.0574). Importantly, there was no significant difference in the animal body-phenotypes or locomotor activity shown as total moving distance in light and dark periods. Therefore, the present study encourages the notion that even low APP-intake may increase the proportions of fatigue-resistant myofibers, and has promise as a strategy for modifying performance in human sports and improving function in age-related muscle atrophy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.339
Teacher spread0.316 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

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