Valproic Acid Induces the Hyperacetylation of P53, Expression of P53 Target Genes, and Markers of the Intrinsic Apoptotic Pathway in Midorganogenesis Murine Limbs
Bibliographic record
Abstract
In utero exposure to valproic acid (VPA), an anticonvulsant and histone deacetylase inhibitor (HDACi), increases the risk of congenital malformations. Although the mechanisms leading to the teratogenicity of VPA remain unsolved, several HDAC inhibitors increase cell death in cancer cell lines and embryonic tissues. Moreover, P53, the master regulator of apoptosis, is an established HDAC target. The purpose of this study was to investigate the effects of VPA on P53 signaling and markers of apoptosis during midorganogenesis in vitro limb development. Timed-pregnant CD1 mice (gestation day 12) were euthanized; embryonic forelimbs were excised and cultured in vitro for 3, 6, 12, or 24 hr in the presence or absence of VPA or valpromide (VPD), a non-HDACi analog of VPA. Quantitative RT-PCR and Western blots were used to assess the expression of candidate genes and proteins involved in P53 signaling and apoptosis. P53 hyperacetylation and a decrease (Survivin/Birc5 and Bcl2) or an increase (p21/Cdkn1a) in the expression of p53 target genes was observed only in VPA-exposed limbs. VPA exposure also triggered an increase in markers of apoptosis and DNA damage; the concentrations of cleaved caspase 9 and caspase 3, cleaved-poly (ADP-ribose) polymerase, and γ-H2AX were increased in VPA-exposed limbs. VPD treatment caused a small but significant increase in cleaved caspase 3. Thus, in vitro exposure to an HDACi such as VPA leads to P53 hyperacetylation, enhances the expression of P53 target genes, and triggers an increase in apoptosis that may contribute to teratogenicity.
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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".