Intralitter Variability Influences the Developmental Impact of Valproic Acid Exposure in CD‐1 Mice
Bibliographic record
Abstract
Valproic acid (VPA) is an antiepileptic and mood-stabilizing drug that causes teratogenic effects, including neural tube defects (NTDs), when taken during pregnancy. Although animal models are widely used to study VPA teratogenicity, most rely on litter means, which overlook variability within the litter. In litter-bearing species like mice, fetal development can vary by sex, uterine horn location, and intrauterine position. This study examined whether these intralitter variables affect fetal and placental outcomes following VPA exposure. Pregnant CD-1 mice received a subcutaneous injection of saline (vehicle control), 400 mg/kg, or 600 mg/kg VPA on gestational day (GD) 9 and were euthanized on GD 18. Fetuses and placentas were collected, weighed, and stratified by exposure, NTD status, sex, uterine horn location, and intrauterine position. Fetal and placental weights were normalized to maternal weight gain and live litter size or the number of live fetuses in each uterine horn. VPA exposure produced a clear dose-dependent effect, with 600 mg/kg significantly increasing postimplantation losses and NTD frequency. These effects were further influenced by intralitter variables, particularly sex and uterine horn location. Fetal weight increased at 400 mg/kg VPA but was unchanged at 600 mg/kg, while placental weight decreased and placental efficiency increased at both doses, suggesting possible compensatory adaptations. At 600 mg/kg VPA, sex differences in placental weight and efficiency were lost, and fetuses in the left uterine horn were significantly lighter than those in the right, indicating location-dependent susceptibility. Intrauterine position did not significantly affect outcomes. These findings demonstrate that intralitter variables influence fetal and placental responses to VPA and underscore the need to account for these factors to improve the translational relevance of developmental toxicology studies.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".