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Record W4283015250 · doi:10.1016/j.jesf.2022.06.001

Potential harms of supplementation with high doses of antioxidants in athletes

2022· review· en· W4283015250 on OpenAlexaff
Shunchang Li, Babatunde Fasipe, Ismail Laher

Bibliographic record

VenueJournal of Exercise Science & Fitness · 2022
Typereview
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of British Columbia
FundersNational Natural Science Foundation of China
KeywordsOxidative stressAntioxidantAthletesReactive oxygen speciesMitochondrial biogenesisHormesisMedicineHealth benefitsPhysiologyInternal medicineChemistryMitochondrionPhysical therapyBiochemistryTraditional medicine

Abstract

fetched live from OpenAlex

in athletes, causing some athletes to consume antioxidants in the erroneous belief that this will counteract the damaging effects of ROS. There is currently no convincing evidence to support the benefits of antioxidant supplementation in acute physical exercise and exercise training. On the contrary, exogenous antioxidants prevent some physiological functions of free radicals that are needed for cell signaling, causing higher dosages of antioxidants to hamper or prevent performance-enhancing and health-promoting training adaptation such as mitochondrial biogenesis, skeletal and cardiac muscle hypertrophy, and improved insulin sensitivity. However, there remains the perception that antioxidants can counterbalance oxidative stress and benefit exercise adaptation and performance in athletes. It is likely that the negative effects of high doses of antioxidant supplementation exceed their potential benefits. We discuss some proposed pathways of potential side effects of exogenous antioxidant supplementation in athletes.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.044
GPT teacher head0.363
Teacher spread0.319 · 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

Citations71
Published2022
Admission routes1
Has abstractyes

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