Investigating the effects of valproic acid on placental epigenetic modifications and development in the CD-1 mouse model
Bibliographic record
Abstract
Gestational exposure to the anticonvulsant drug valproic acid (VPA) is associated with congenital malformations and neurodevelopmental disorders through its action as a histone deacetylase inhibitor. VPA can elicit placental toxicity and affect placental growth and development. The objective of this study was to evaluate the impact of maternal exposure to VPA on the mouse placenta following exposure on gestational day (GD) 13 since previous studies have shown that mice exposed at this time during gestation give birth to offspring with an autism spectrum disorder-like phenotype. We exposed CD-1 dams to a teratogenic dose (600 mg/kg) of VPA or saline on GD13 and assessed fetoplacental growth and development on GD18. We evaluated epigenetic modifications, including acetylated histone H4 (H4ac), methylated H3K4 (H3K4me2) using immunohistochemistry, and global DNA methylation in the placenta at 1, 3, and 24 h following maternal exposure on GD13. In utero exposure to VPA on GD13 significantly decreased placental weight and increased fetal resorptions. Moreover, VPA significantly increased the staining intensity of histone H4 acetylation and H3K4 di-methylation across the placenta at 1 and 3 h post maternal dose. Our results also demonstrate that VPA significantly decreased global DNA methylation levels in placental tissue. These results show that gestational exposure to VPA interferes with placental growth and elicits epigenetic modifications, which may play a vital role in VPA-induced developmental toxicity.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".