Supplementation with (6<i>S</i>)-5-methyltetrahydrofolic acid appears as effective as folic acid in maintaining maternal folate status while reducing unmetabolised folic acid in maternal plasma: a randomised trial of pregnant women in Canada
Bibliographic record
Abstract
Abstract Folic acid supplementation is recommended during pregnancy to support healthy fetal development; (6S)-5-methyltetrahydrofolic acid ((6S)-5-MTHF) is available in some commercial prenatal vitamins as an alternative to folic acid, but its effect on blood folate status during pregnancy is unknown. To address this, we randomised sixty pregnant individuals at 8–21 weeks’ gestation to 0·6 mg/d folic acid or (6S)-5-MTHF × 16 weeks. Fasting blood specimens were collected at baseline and after 16 weeks (endline). Erythrocyte and serum folate were quantified via microbiological assay (as globally recommended) and plasma unmetabolised folic acid (UMFA) via LC-MS/MS. Differences in biochemical folate markers between groups were explored using multivariable linear/quantile regression, adjusting for baseline concentrations, dietary folate intake and gestational weeks. At endline (n 54), the mean values and standard deviations (or median, inter-quartile range) of erythrocyte folate, serum folate and plasma UMFA (nmol/l) in those supplemented with (6S)-5-MTHF v. folic acid, respectively, were 1826 (sd 471) and 1998 (sd 421); 70 (sd 13) and 78 (sd 17); 0·5 (0·4, 0·8) and 1·3 (0·9, 2·1). In regression analyses, erythrocyte and serum folate did not differ by treatment group; however, concentrations of plasma UMFA in pregnancy were 0·6 nmol/l higher (95 % CI 0·2, 1·1) in those supplementing with folic acid as compared with (6S)-5-MTHF. In conclusion, supplementation with (6S)-5-MTHF may reduce plasma UMFA by ∼50 % as compared with supplementation with folic acid, the biological relevance of which is unclear. As folate is currently available for purchase in both forms, the impact of circulating maternal UMFA on perinatal outcomes needs to be determined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".