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Record W2998413545 · doi:10.1089/ars.2019.7985

Antioxidant Enzymes and Male Fertility: Lessons from Knockout Models

2019· review· en· W2998413545 on OpenAlexafffund
Eleonora Scarlata, Cristián O’Flaherty

Bibliographic record

VenueAntioxidants and Redox Signaling · 2019
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsAntioxidantSpermatozoonReactive oxygen speciesBiologyKnockout mouseOxidative stressSpermCell biologyLipid peroxidationCapacitationDNA damageGeneticsBiochemistryDNAGene

Abstract

fetched live from OpenAlex

Significance: Spermatozoa are very sensitive to high levels of reactive oxygen species (ROS) due to the limited antioxidant systems present in these terminal cells. However, tight regulation of ROS levels must be ensured to accomplish the unique goal of the spermatozoon, that is, the transfer of the paternal genome into the mature oocyte during the fertilization process. Thus, it is essential that the restricted antioxidant enzymatic systems are active for sperm function. Recent Advances: Oxidative stress is associated with low sperm quality. High levels of ROS in spermatozoa produce oxidation of lipids, proteins, and DNA that lead to lipid peroxidation, oxidation of essential structural proteins and enzymes, and mutations due to oxidation of DNA. Critical Issues: In this study, we described the available knockout mouse models that helped to better understand the role of different antioxidant enzymes in male fertility. We focused mainly on those studies that directly explore the effects of the lack of these enzymes in male fertility and included information when existing knockout mouse models produced for other purposes were used. Special attention was given in this review to the consequences of the absence of antioxidant enzymes on sperm quality and fertility of aging males from the knockout models. Future Directions: Further studies using novel mouse models lacking different antioxidants and their combinations are essential to understand the consequences of high levels of ROS in aging testes, epididymes, spermatozoa, and embryo development to produce a healthy baby.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.086
GPT teacher head0.333
Teacher spread0.247 · 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.

Study designOther design
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

Citations42
Published2019
Admission routes2
Has abstractyes

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