The Impact of Maternal Folates on Brain Development and Function after Birth
Bibliographic record
Abstract
Folate is vital for biological processes within the body, including DNA synthesis, DNA repair, and methylation reactions that metabolize homocysteine. The role of folate is particularly important in pregnancy, where there is rapid cellular and tissue growth. Maternal folate deficiencies secondary to inadequate dietary supplementation are known to produce defects in the neural tube and spinal cord, yet the exact mechanism of folate in neurodevelopment is unknown. The consequences of maternal folate deficiency on offspring brain development and function beyond gestation are not well defined. The objective of this review is to investigate the role of folate deficiency in offspring neurodevelopment, and the complications that arise post-gestation. This was accomplished through a comprehensive review of the data presented in both clinical and preclinical studies. Evidence supports that folate deficiency is associated with altered offspring neurodevelopment, including smaller total brain volume, altered cortical thickness and cerebral white matter, altered neurogenesis, and neuronal apoptosis. Some of these changes have been associated with altered brain function in offspring with memory, motor function, language skills, and psychological issues. This review of literature also presents potential mechanisms of folate deficiency in neurodevelopment with altered metabolism, neuroinflammation, epigenetic modification through DNA methylation, and a genetic deficiency in one-carbon metabolism.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".