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Record W2062139818 · doi:10.1038/aja.2010.182

Antioxidant therapy in male infertility: fact or fiction?

2011· review· en· W2062139818 on OpenAlexaff
Armand Zini, Naif Alhathal

Bibliographic record

VenueAsian Journal of Andrology · 2011
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
Fundersnot available
KeywordsSpermAntioxidantMale infertilityReactive oxygen speciesAndrologySemenDNA damageInfertilitySemen analysisMedicineBiologyPregnancyBiochemistryDNAGenetics

Abstract

fetched live from OpenAlex

Infertile men have higher levels of semen reactive oxygen species (ROS) than do fertile men. High levels of semen ROS can cause sperm dysfunction, sperm DNA damage and reduced male reproductive potential. This observation has led clinicians to treat infertile men with antioxidant supplements. The purpose of this article is to discuss the rationale for antioxidant therapy in infertile men and to evaluate the data on the efficacy of dietary and in vitro antioxidant preparations on sperm function and DNA damage. To date, most clinical studies suggest that dietary antioxidant supplements are beneficial in terms of improving sperm function and DNA integrity. However, the exact mechanism of action of dietary antioxidants and the optimal dietary supplement have not been established. Moreover, most of the clinical studies are small and few have evaluated pregnancy rates. A beneficial effect of in vitro antioxidant supplements in protecting spermatozoa from exogenous oxidants has been demonstrated in most studies; however, the effect of these antioxidants in protecting sperm from endogenous ROS, gentle sperm processing and cryopreservation has not been established conclusively.

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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.076
GPT teacher head0.341
Teacher spread0.265 · 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

Citations129
Published2011
Admission routes1
Has abstractyes

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