Increased vitamin intake during pregnancy by rats alters lipid metabolism in the offspring at 12 weeks post‐weaning
Bibliographic record
Abstract
Increased vitamin intake during pregnancy results in epigenetic modification of gene expression in the offspring. We hypothesized that increased non‐toxic vitamin intake during pregnancy by rats would alter regulation of lipid metabolism in newborns. Two groups of female Wistar rats were fed the AIN‐93G diet containing either the regular vitamin (RV) or 10‐fold higher vitamin (HV) mix during pregnancy. Pups from each dam group were weaned to a diet containing either the regular (R) or 1/3 the recommended amount of vitamins (deficient, D), and sacrificed at 12 wks post‐weaning. High vitamin intake during pregnancy adversely affected liver and adipose fatty acid (FA) profiles when pups were weaned to a control healthy diet, but favorably influenced pups weaned to a vitamin deficient diet. Females were more affected by the maternal diet than males. Concentration (mg/g tissue) of several FA products of de novo synthesis in liver and adipose of pups fed the R diet and born to HV dams were reduced, resulting in increased percent composition of saturated FAs and reduced composition of mono‐ and polyunsaturated FAs (P<0.05). Pups weaned to the D diet and born to dams fed the RV diet had lower (P<0.05) concentrations of all FAs measured, relative to pups weaned to the R diet. In those born to HV dams, the decline in FA concentrations in liver and adipose was attenuated (P<0.05). The results show that vitamin supplementation during pregnancy altered FA metabolism in the offspring, possibly through epigenetic modification of gene expression. The changes observed in HV offspring are similar to the changes observed in insulin resistant rats and offspring of protein restricted dams, suggesting that high intake of vitamins during pregnancy may predispose the offspring towards insulin resistance. Supported by CIHR.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".