Mitigating the detrimental developmental impact of early fetal alcohol exposure using a maternal methyl donor‐enriched diet
Bibliographic record
Abstract
Fetal alcohol exposure at any stage of pregnancy can lead to fetal alcohol spectrum disorder (FASD), a group of life-long conditions characterized by congenital malformations, as well as cognitive, behavioral, and emotional impairments. The teratogenic effects of alcohol have long been publicized; yet fetal alcohol exposure is one of the most common preventable causes of birth defects. Currently, alcohol abstinence during pregnancy is the best and only way to prevent FASD. However, alcohol consumption remains astoundingly prevalent among pregnant women; therefore, additional measures need to be made available to help protect the developing embryo before irreparable damage is done. Maternal nutritional interventions using methyl donors have been investigated as potential preventative measures to mitigate the adverse effects of fetal alcohol exposure. Here, we show that a single acute preimplantation (E2.5; 8-cell stage) fetal alcohol exposure (2 × 2.5 g/kg ethanol with a 2h interval) in mice leads to long-term FASD-like morphological phenotypes (e.g. growth restriction, brain malformations, skeletal delays) in late-gestation embryos (E18.5) and demonstrate that supplementing the maternal diet with a combination of four methyl donor nutrients, folic acid, choline, betaine, and vitamin B12, prior to conception and throughout gestation effectively reduces the incidence and severity of alcohol-induced morphological defects without altering DNA methylation status of imprinting control regions and regulation of associated imprinted genes. This study clearly supports that preimplantation embryos are vulnerable to the teratogenic effects of alcohol, emphasizes the dangers of maternal alcohol consumption during early gestation, and provides a potential proactive maternal nutritional intervention to minimize FASD progression, reinforcing the importance of adequate preconception and prenatal nutrition.
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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".