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Quercetin Enhances Endurance Capacity via Antioxidant Activity and Size of Muscle Fibre Type 1

2012· article· en· W3149988789 on OpenAlexvenueno aff
Leelayuwat, S. Laddawan, Yupaporn Kanpetta, M. Benja, D. Wongpan, Orathai Tunkamnerdthai, Jintanaporn Wattanathorn, Supaporn Muchimapura, Junichiro Yamauchi

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2012
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsnot available
Fundersnot available
KeywordsQuercetinMalondialdehydeVitamin CEndurance trainingAntioxidantSuperoxide dismutaseChemistryAntioxidant capacityBody weightVitaminVitamin EInternal medicineEndocrinologyFood scienceAnimal scienceBiochemistryMedicineBiology

Abstract

fetched live from OpenAlex

This study aimed to examine effects of quercetin on 1) endurance capacity 2) malondialdehyde (MDA) and superoxide dismutase (SOD) activity in skeletal muscle and 3) muscle fibre density and size in mice after an intense exercise. There were 5 groups: control, vitamin C (250 mg/kg body weight), quercetin 150, 300, and 450 mg/kg body weight respectively once a day for 28 days. Endurance capacity was measured by exhaustive swimming exercise test which was done 24-h after swimming at high intensity. Then muscles were analyzed for MDA, SOD activity, and muscle fibre density and size. After the 28-day treatment, endurance time in vitamin C and quercetin treated groups at dose of 150 mg/kg body weight were longer than the vehicle group (p

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.066
GPT teacher head0.370
Teacher spread0.304 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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