5‐Aza‐2′‐Deoxycytidine Induces Alterations in Murine Spermatogenesis and Pregnancy Outcome
Bibliographic record
Abstract
Because of the ability of cytidine analogues, such as 5-aza-2'-deoxycytidine, to incorporate into DNA and lead to decreases in DNA methylation, there has recently been renewed interest in using these drugs in anticancer therapy. To determine the effects of paternal 5-aza-2'-deoxycytidine treatment on spermatogenesis and progeny outcome in the mouse and whether effects are modulated by decreased levels of the predominant DNA methyltransferase, DNMT1, adult Dnmt1(+/+) and Dnmt1-deficient (Dnmt1(c/+)) male mice were treated with 5-aza-2'-deoxycytidine for 7 weeks, which resulted in dose-dependent decreases in testicular weight, an increase in histological abnormalities, and a decline in sperm counts, with no apparent effect on androgen status. Testes of Dnmt1(c/+) mice, however, were less severely affected by 5-aza-2'-deoxycytidine than were those of wild-type mice. The exposure of Dnmt1(+/+) male mice to even low doses of 5-aza-2'-deoxycytidine followed by mating elicited significantly reduced pregnancy rates and elevated preimplantation loss in females. Dnmt1 deficiency, however, protected against such drug-induced decreases in pregnancy rate but not preimplantation loss. Altered DNA methylation or DNMT1 activity may explain such adverse effects, because treatment resulted in dose-dependent decreases in the global methylation of sperm DNA. Thus, in the mouse, paternal administration of 5-aza-2'-deoxycytidine interferes with normal male germ cell development and results in reduced fertility, whereas lowering DNMT1 levels appears to partially protect the seminiferous epithelium from deleterious drug effects.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".