Human milk unmetabolized folic acid is increased following supplementation with synthetic folic acid as compared to (6S)-5-methyltetrahydrofolic acid
Bibliographic record
Abstract
Folic acid supplementation is recommended perinatally, but may increase unmetabolized folic acid (UMFA) in human milk; this is concerning as it is an inactive form which may be less bioavailable for the infant. "Natural" (6S)-5-methyltetrahydrofolic acid [(6S)-5-MTHF] is available as an alternative to folic acid, and may prevent the accumulation of UMFA in human milk. Pregnant women (n = 60) were enrolled at 8-21 weeks of gestation and randomized to 0.6 mg/day folic acid or (6S)-5-MTHF. At ~ 1-week postpartum, participants provided a human milk specimen. Total human milk folate (nmol/L) and concentrations of UMFA (nmol/L) were quantified via LC-MS/MS. Differences between groups were evaluated using multivariable quantile/linear regression, adjusting for dietary folate, weeks supplementing, and milk collection methods. No significant difference in total milk folate was found; however, the median milk UMFA concentration was 11 nmol/L higher in those receiving folic acid versus (6S)-5-MTHF (95% CI = 6.4-17 nmol/L), with UMFA representing 28% and 2% of total milk folate. In conclusion, the form of supplemental folate had markedly differential effects on the human milk folate profile, with folic acid increasing the mean proportion of milk UMFA by ~ 14-fold. Investigation of whether increased UMFA impacts folate-related metabolism and infant health outcomes is required.
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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) | 0.000 | 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".