Catalase can protect spermatozoa of FSH receptor knock‐out mice against oxidant‐induced DNA damage in vitro
Bibliographic record
Abstract
The aetiology of sperm DNA damage is likely multi-factorial with abnormal compaction of nuclear DNA, abortive apoptosis and oxidative stress implicated as potential causes of DNA damage. The objective of this study was to evaluate DNA damage in spermatozoa from wild-type (WT) and FSH receptor knock-out (FORKO) mice, compare the relative susceptibility of spermatozoa from these animals to oxidative DNA damage, and examine the protective effect of the antioxidant catalase on sperm DNA damage. Epididymal spermatozoa from FORKO mice (n = 5) and WT controls (n = 5) were extracted and incubated with or without catalase. Sperm DNA damage was assessed immediately after epididymal extraction (time 0 control) and following 2-h incubation at 37 °C. DNA damage was measured by the sperm chromatin structure assay and the results expressed as the %DNA fragmentation index or %DFI. Freshly retrieved epididymal spermatozoa from WT mice had a significantly lower mean (±SD) %DFI than that of FORKO mice (2.7 ± 1.8 vs. 6.4 ± 2.9%, p < 0.05). Prolonged (2-h) incubation of FORKO mice spermatozoa resulted in a significant increase in %DFI compared with the time 0 control (17.9 ± 9.2% vs. 6.4 ± 2.9%, respectively, p < 0.05) and the addition of catalase protected these spermatozoa from DNA damage (9.8 ± 4.1 vs. 17.9 ± 9.2%, respectively, p < 0.05). However, incubation of WT mice spermatozoa did not increase %DFI significantly (5.8 ± 5.0 vs. 2.7 ± 1.8, respectively, p > 0.05) and the addition of catalase (vs. no catalase) did not result in a significant reduction in %DFI (5.8 ± 5.0 vs. 7.7 ± 6.5%, respectively, p > 0.05). These data indicate that catalase may protect sperm nuclear DNA from oxidative stress in vitro. The data also demonstrate the differential susceptibility of WT and FORKO mice spermatozoa to oxidative stress.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".