Prenatal Exposure to Maternal Hyperhomocysteinemia and Allele‐Specific Methylation and Expression of <i>H19</i> / <i>Igf2</i>
Bibliographic record
Abstract
Epigenetic processes may play a role in the metabolic programming associated with prenatal exposure to maternal dietary factors. The goal of this study was to determine the effect of prenatal exposure to maternal hyperhomocysteinemia (HHcy) on allele‐specific methylation and expression of genomically imprinted H19 and Igf2 . The H19 gene is located in close proximity to Igf2 with expression of H19 and Igf2 regulated by the methylation status of a differentially methylated domain (DMD). Female C57BL/6J mice with ( Cbs +/−) and without ( Cbs +/+) heterozygous targeted disruption of the gene for cystathionine‐β‐synthase were mated with male Cast/EiJ mice and fed a control or high methionine/low folate diet to induce HHcy (HH) during pregnancy. The F1 hybrid offspring mice were then challenged with the HH diet or control diet from weaning for 1 month. Mice exposed in utero to maternal HHcy and challenged with the HH diet post weaning had higher plasma total homocysteine than mice not exposed in utero to maternal HHcy but challenged with the HH diet post weaning (12.66±2.7 μM vs 6.99±0.9). This was accompanied by lower (p<0.05) methylation of liver H19 DMD on both the maternal and paternal alleles and higher H19 and lower Igf2 transcript levels in liver. These findings show that prenatal exposure to maternal HHcy results in tissue‐specific changes in H19 / Igf2 methylation and expression.
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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) | 0.000 | 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".