Folic acid supplementation in a mouse model of diabetes in pregnancy alters insulin sensitivity in female mice and beta cell mass in offspring
Bibliographic record
Abstract
Epidemiological studies have reported discrepant findings on the relationship between folic acid intake during pregnancy and risk for gestational diabetes mellitus (GDM). To begin to understand how folic acid impacts metabolic health during pregnancy, we determined the effects of excess folic acid supplementation (5× recommendation) on maternal and fetal offspring metabolic health. Using a mouse (female C57BL/6J) model of diet-induced diabetes in pregnancy (western diet) and control mice, we show that folic acid supplementation improved insulin sensitivity in the female mice fed the western diet and worsened insulin sensitivity in control mice. We found no unmetabolized folic acid in liver from supplemented mice suggesting the metabolic effects of folic acid supplementation are not due to unmetabolized folic acid. Male fetal (gestational day 18.5) offspring from folic acid supplemented dams (western and control) had greater beta cell mass and density than those from unsupplemented dams; this was not observed in female offspring. Differential sex-specific hepatic gene expression profiles were observed in the fetal offspring from supplemented dams but this differed between western and controls. Our findings suggest that folic acid supplementation affects insulin sensitivity in female mice, but is dependent on their metabolic phenotype and has sex-specific effects on offspring pancreas and liver.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".