Impact of mothers' early life exposure to low or high folate on progeny outcome and DNA methylation patterns
Bibliographic record
Abstract
Abstract The dynamic patterning of DNA and histone methylation during oocyte development presents a potentially susceptible time for epigenetic disruption due to early life environmental exposure of future mothers. We investigated whether maternal exposure to folic acid deficient and supplemented diets starting in utero could affect oocytes and cause adverse developmental and epigenetic effects in next generation progeny. Female BALB/c mice (F0) were placed on one of four amino acid defined diets for 4 weeks before pregnancy and throughout gestation and lactation: folic acid control (rodent recommended daily intake; Ctrl), 7-fold folic acid deficient, 10-fold folic acid supplemented or 20-fold folic acid supplemented diets. F1 female pups were weaned onto Ctrl diets, mated to produce the F2 generation and the F2 offspring were examined at E18.5 for developmental and epigenetic abnormalities. Resorption rates were increased and litter sizes decreased amongst F2 E18.5-day litters in the 20-fold folic acid supplemented group. Increases in abnormal embryo outcomes were observed in all three folic acid deficient and supplemented groups. Subtle genome-wide DNA methylation alterations were found in the placentas and brains of F2 offspring in the 7-fold folic acid deficient , 10-fold folic acid supplemented and 20-fold folic acid supplemented groups; in contrast, global and imprinted gene methylation were not affected. The findings show that early life female environmental exposures to both low and high folate prior to oocyte maturation can compromise oocyte quality, adversely affecting offspring of the next generation, in part by altering DNA methylation patterns.
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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 | 0.000 |
| 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".