Genetically programmed retinoic acid deficiency during gastrulation phenocopies most known developmental defects due to acute prenatal alcohol exposure in FASD
Bibliographic record
Abstract
Fetal Alcohol Spectrum Disorder (FASD) arises from maternal consumption of alcohol during pregnancy affecting 2%–5% of the Western population. In Xenopus laevis studies, we showed that alcohol exposure during early gastrulation reduces retinoic acid (RA) levels at this critical embryonic stage inducing craniofacial malformations associated with Fetal Alcohol Syndrome. A genetic mouse model that induces a transient RA deficiency in the node during gastrulation is described. These mice recapitulate the phenotypes characteristic of prenatal alcohol exposure (PAE) suggesting a molecular etiology for the craniofacial malformations seen in children with FASD. Gsc+/Cyp26A1 mouse embryos have a reduced RA domain and expression in the developing frontonasal prominence region and delayed HoxA1 and HoxB1 expression at E8.5. These embryos also show aberrant neurofilament expression during cranial nerve formation at E10.5 and have significant FASD sentinel-like craniofacial phenotypes at E18.5. Gsc+/Cyp26A1 mice develop severe maxillary malocclusions in adulthood. Phenocopying the PAE-induced developmental malformations with a genetic model inducing RA deficiency during early gastrulation strongly supports the alcohol/vitamin A competition model as a major molecular etiology for the neurodevelopmental defects and craniofacial malformations seen in children with FASD.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".