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Record W4244437344 · doi:10.1242/jeb.02468

BENEFICIAL BLUEBERRIES

2006· article· en· W4244437344 on OpenAlexaff
Jonathan A. W. Stecyk

Bibliographic record

VenueJournal of Experimental Biology · 2006
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOxidative stressAntioxidantReactive oxygen speciesOxidative damagePolyphenolOxidative phosphorylationChemistryDNA damageMedicinePhysiologyFood scienceBiochemistryDNA

Abstract

fetched live from OpenAlex

Exercise is commonly viewed to be beneficial for one's health. However, you may be surprised to learn that exercise can be detrimental too. Previous study in mammals, including humans, has shown strenuous exercise to produce free radicals, which increase the presence of reactive oxygen species that induce oxidative damage in cells and tissues. Specifically, reactive oxygen species have been shown to play an important role in the etiology of numerous serious ailments such as cancer, Alzheimer's disease and heart disease.Nevertheless, there may be a simple way to continue exercising without suffering the consequences of the associated oxidative damage. Numerous fruits contain antioxidant compounds such as polyphenols and flavanoids that have been shown to protect against oxidative stress by functioning as reducing agents, singlet oxygen quenchers, and helpers in the repair of damaged DNA bases or protein amino acids. Thus, maintaining a diet supplemented with fruits high in antioxidant compounds could potentially serve to sustain the body's antioxidant levels and prevent exercise-induced oxidative damage.Kriya Dunlap and associates at the University of Alaska Fairbanks were interested in determining whether a diet supplemented with a fruit high in antioxidant compounds would indeed elevate an animal's total antioxidant power and protect against oxidative muscle damage associated with exercise. As such,Dunlap's team devised an experiment to investigate whether supplementing the diet of Alaskan huskie (Canis lupus familiaris) sled dogs with blueberries would prevent oxidative muscle damage in these animals following strenuous exercise. The team maintained two groups of 12 dogs for two months with minimal exercise on either (1) a normal dog food diet or (2) a supplemented diet in which 2% of the daily food intake was blueberries. At the end of the two-month acclimation period, both groups of dogs were exercised on two consecutive days for 30 min each day at 70% of their \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\dot{V}}_{\mathrm{O}_{2}}\) \end{document} max. Blood samples were taken prior to, immediately following and 24 and 48 h post-exercise for measurements of plasma creatine kinase and isoprostane-indicators of muscle damage - and total antioxidant power. Measurements were compared to a control group of dogs that were fed a normal dog food diet over the two-month adaptation period but were not exercised at its conclusion.The team found that supplementing the diet of young healthy sled dogs with blueberries failed to attenuate the muscle damage associated with the exercise regime. Both groups of exercised dogs exhibited a slight, but not unusual,amount of muscle damage following exercise. However, the blueberry-fed dogs did have a greater total amount of antioxidants present in blood plasma immediately post-exercise, but not at 24 or 48 h following exercise. From this finding, Dunlop's team surmise that the blueberry-fed dogs had the potential to be better protected against the deleterious effects of oxidative stress. Thus, it appears the old saying holds true, `you are what you eat'!

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.333
Teacher spread0.312 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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