Impact of Maternal Folate Deficiencies on Early Neurological Development: A Narrative Review
Bibliographic record
Abstract
Context Folates are B-vitamins that cannot be generated de novo and are therefore obtained from the diet. In the brain, these vitamins are involved in nucleotide synthesis, DNA repair, lipid metabolism, methylation and neurotransmitter synthesis. It is well established that adequate levels of maternal folates are required for closure of the neural tube within the first month of pregnancy, however, it is not clear whether maternal folates are needed throughout pregnancy for brain development and whether they influence offspring neurological function after birth. The aim of this review is to outline current literature from epidemiological and animal model studies that shows maternal supplementation of folates throughout pregnancy does indeed affect offspring neurological function after birth. Evidence Acquisition A Medline search was performed using the following mesh terms, maternal-fetal exchange, folic acid, offspring neurologic manifestations, methylenetetrahydrofolate reductase (MTHFR), embryology, and behavior. Results The studies described in the present review have reported that maternal deficiencies in folates during pregnancy result in changes in behavior as well as in blood and brain tissue in offspring, including altered methylation, including reduced levels of the global methyl donor S-adenosylmethionine (SAM), and increased levels of oxidative stress. Conclusions The data summarized here outlines the importance of adequate levels of folates throughout pregnancy to facilitate appropriate neurological development of offspring after birth.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".