Adverse Placental Effect of Formic Acid on hCG Secretion Is Mitigated by Folic Acid
Bibliographic record
Abstract
AIMS: Formic acid has recently been detected in maternal blood and umbilical cord blood of infants born to alcohol abusing mothers. This toxic metabolite of methanol requires folate for detoxification. We hypothesized that formic acid produced in the maternal circulation will transfer across the placenta and will be toxic to the placenta. Our objectives were, first, to determine whether formic acid transfers across the human placenta and whether it is toxic to the placenta and second, to determine whether folate can decrease transplacental transfer of formic acid and mitigate toxicity. METHODS: Dual perfusion of a single placental lobule ex vivo was used to characterize the transfer of formic acid across the placenta. After a 1-h control period, formic acid (2 mM) was introduced into the maternal circulation with (n = 4) or without folate (1 µM) (n = 4) and was allowed to equilibrate for 3 h. RESULTS: Formic acid transferred rapidly from the maternal to the fetal circulation, and transfer was not altered with the addition of folate. Compared with the control period, there was a significant decrease in hCG secretion (P = 0.03) after addition of formic acid. The addition of folic acid to the perfusate mitigated the decrease in hCG. CONCLUSIONS: Formic acid rapidly transfers across the placenta and thus has the potential to be toxic to the developing fetus. Formic acid decreases hCG secretion in the placenta, which may alter steroidogenesis and differentiation of the cytotrophoblasts, and this adverse effect can be mitigated by folate.
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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) | 0.000 | 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) | 0.001 | 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".