Deprenyl Enhances the Teratogenicity of Hydroxyurea in Organogenesis Stage Mouse Embryos
Bibliographic record
Abstract
Hydroxyurea, an antineoplastic drug, is a model teratogen. The administration of hydroxyurea to CD1 mice on gestation day 9 induces oxidative stress, increasing the formation of 4-hydroxy-2-nonenal adducts to redox-sensitive proteins such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in the caudal region of the embryo. GAPDH catalytic activity is reduced, and its translocation into the nucleus is increased. Because the nuclear translocation of GAPDH is associated with oxidative stress-induced cell death, we hypothesized that this translocation plays a role in mediating the teratogenicity of hydroxyurea. Deprenyl (also known as selegiline), a drug used as a neuroprotectant in Parkinson's disease, inhibits the nuclear translocation of GAPDH. Hence, timed pregnant CD1 mice were treated with deprenyl (10mg/kg) on gestation day 9 followed by the administration of hydroxyurea (400 or 600mg/kg). Deprenyl treatment significantly decreased the hydroxyurea-induced nuclear translocation of GAPDH in the caudal lumbosacral somites. Deprenyl enhanced hydroxyurea-mediated caudal malformations, inducing specifically limb reduction, digit anomalies, tail defects, and lumbosacral vertebral abnormalities. Deprenyl did not augment the hydroxyurea-induced inhibition of glycolysis or alter the ratio of oxidized to reduced glutathione. However, it did dramatically increase cleaved caspase-3 in embryos. These data suggest that nuclear GAPDH plays an important, region-specific, role in teratogen-exposed embryos. Deprenyl exacerbated the developmental outcome of hydroxyurea exposure by a mechanism that is independent of oxidative stress. Although the administration of deprenyl alone did not affect pregnancy outcome, this drug may have adverse consequences when combined with exposures that increase the risk of malformations.
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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".