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Record W4411243088 · doi:10.3390/antiox14060720

Role of Redox-Induced Protein Modifications in Spermatozoa in Health and Disease

2025· review· en· W4411243088 on OpenAlexafffund
Chika Onochie, Keturah Evi, Cristián O’Flaherty

Bibliographic record

VenueAntioxidants · 2025
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsCapacitationOxidative stressAcrosome reactionOxidative phosphorylationInfertilityCell biologyRedoxMotilitySpermMale infertilityBiologyChemistryBiochemistryGenetics

Abstract

fetched live from OpenAlex

Male infertility contributes to approximately half of all infertility cases, with most cases associated with oxidative stress. Spermatozoa depend on finely tuned redox signaling for critical processes such as capacitation, motility, and fertilization competence; however, their unique structural and metabolic features render them particularly vulnerable to oxidative damage. Reversible oxidative modifications regulate enzymatic activity, signaling cascades, and structural stability, supporting normal sperm function, whereas irreversible oxidative damage impairs motility, acrosome reaction, and DNA integrity, contributing to male infertility. The intricate balance between physiological redox signaling and pathological oxidative stress demonstrates the potential of redox modifications as biomarkers for infertility diagnosis and as targets for antioxidant-based therapeutic interventions. This review explores the role of redox-induced protein modifications in sperm function, focusing on thiol oxidation, S-nitrosylation, sulfhydration, glutathionylation, CoAlation, and protein carbonylation. By uncovering the mechanisms of these redox modifications, we provide a framework for their modulation in the development of targeted redox interventions to improve male fertility.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.900
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.036
GPT teacher head0.339
Teacher spread0.303 · 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 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

Citations10
Published2025
Admission routes2
Has abstractyes

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