Advancing age increases sperm chromatin damage and impairs fertility in peroxiredoxin 6 null mice
Bibliographic record
Abstract
Due to socioeconomic factors, more couples are choosing to delay conception than ever. Increasing average maternal and paternal age in developed countries over the past 40 years has raised the question of how aging affects reproductive success of males and females. Since oxidative stress in the male reproductive tract increases with age, we investigated the impact of advanced paternal age on the integrity of sperm nucleus and reproductive success of males by using a Prdx6(-/-) mouse model. We compared sperm motility, cytoplasmic droplet retention sperm chromatin quality and reproductive outcomes of young (2-month-old), adult (8-month-old), and old (20-month-old) Prdx6(-/-) males with their age-matched wild type (WT) controls. Absence of PRDX6 caused age-dependent impairment of sperm motility and sperm maturation and increased sperm DNA fragmentation and oxidation as well as decreased sperm DNA compaction and protamination. Litter size, total number of litters and total number of pups per male were significantly lower in Prdx6(-/-) males compared to WT controls. These abnormal reproductive outcomes were severely affected by age in Prdx6(-/-) males. In conclusion, the advanced paternal age affects sperm chromatin integrity and fertility more severely in the absence of PRDX6, suggesting a protective role of PRDX6 in age-associated decline in the sperm quality and fertility in mice.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".