Gestational exposure to valproic acid upregulates total Stat3 protein expression while downregulating phosphorylated Stat3 in CD‐1 mouse embryos with neural tube defects
Bibliographic record
Abstract
Valproic acid (VPA), a widely prescribed antiepileptic drug and an effective treatment for psychiatric disorders, is teratogenic causing neural tube defects (NTDs) and other defects in the exposed embryo. Signal transducer and activator of transcription 3 (Stat3) is a transcription factor that is activated via tyrosine phosphorylation. Stat3, as well as its active form (pYStat3), is expressed during neural tube closure in murine development. This study investigated the effects of in utero VPA exposure on embryonic Stat3 mRNA and protein expression during the critical period of neural tube closure in CD-1 mouse embryos. Following the exposure of CD-1 pregnant mice to the teratogenic dose of 400 mg/kg VPA or saline on gestational day (GD) 9, embryos were harvested at 1, 3, 6, or 24 hr and on GD13. Stat3 mRNA levels remained unchanged at all time points. Total Stat3 protein levels were significantly (p < .05) increased in GD9 embryos at 1 and 6 hr post-exposure and in GD13 exposed nonexencephalic and exencephalic embryo heads. In contrast, phosphorylated Stat3 levels were significantly (p < .05) downregulated in GD9 embryos at the 3 and 6 hr time points with an overall trend of downregulation in the GD10 and GD13 groups. Total and phosphorylated Stat3 protein levels remained unchanged in nuclear extracts of the exposed nonexencephalic and exencephalic GD13 embryo heads. The reported significant downregulation of phosphorylated Stat3 levels suggests its possible role in VPA-induced NTDs in mouse embryos.
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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".