Prenatal Exposure to Ethanol and Disturbances in Hepatic One Carbon Metabolism
Bibliographic record
Abstract
Disturbances in one carbon metabolism contribute to the pathology of adult alcoholic liver disease. We hypothesize that disturbances in one carbon metabolism may contribute to the pathology associated with prenatal ethanol exposure including fetal alcohol spectrum disorder. We studied offspring at gestational age 21 days (GD 21) from female Sprague‐Dawley rats fed a liquid ethanol diet (36% energy from ethanol), a liquid control diet (maltose‐dextrin isocalorically substituted for ethanol, g/kg body wt/day of gestation), or lab chow throughout pregnancy. Liver methionine levels were higher (P< 0.05) and dimethylglycine levels lower (P<0.01) in pups exposed in utero to ethanol than in pups from lab chow‐fed dams. This was accompanied by higher (P<0.05) levels of methionineadenosyltransferase 2a ( Mat2a ), methionine synthase ( Mtr ), methylenetetrahydrofolate reductase ( Mthfr ), and cysthationine‐β‐synthase ( Cbs ) mRNA levels in liver from pups exposed in utero to ethanol than in pups from dams fed lab chow. No effects of prenatal ethanol exposure on betaine‐homocysteine methyltransferase, phosphatidylethanolamine methyltransferase, and Mat1a mRNA levels or Cbs protein levels were observed. These finding suggest that prenatal exposure to ethanol affects liver one carbon metabolism in GD21 offspring.
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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) | 0.001 | 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".