Antioxidant Enzymes and Male Fertility: Lessons from Knockout Models
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".