Alcohol exposure during late ovine gestation alters fetal liver iron homeostasis without apparent dysmorphology
Bibliographic record
Abstract
High levels of alcohol (ethanol) exposure during fetal life can affect liver development and can increase susceptibility to infection after birth. Our aim was to determine the effects of a moderate level of ethanol exposure in late gestation on the morphology, iron status, and inflammatory status of the ovine fetal liver. Pregnant ewes were chronically catheterized at 91 days of gestation (DG; term ~145 DG) for daily intravenous infusion of ethanol (0.75 g/kg maternal body wt; n = 8) or saline (n = 7) over 1 h from 95 to 133 DG. At necropsy (134 DG), fetal livers were collected for analysis. Liver weight, general liver morphology, hepatic cell proliferation and apoptosis, perivascular collagen deposition, and interleukin (IL)-1β, IL-6, or IL-8 mRNA levels were not different between groups. However, ethanol exposure led to significant decreases in hepatic content of ferric iron and gene expression of the iron-regulating hormone hepcidin and tumor necrosis factor (TNF)-α (all P < 0.05). In the placenta, there was no difference in transferrin receptor, divalent metal transporter 1, and ferritin mRNA levels; however, ferroportin mRNA levels were increased in ethanol-exposed animals (P < 0.05), and ferroportin protein tended to be increased (P = 0.054). Plasma iron concentration was not different between control and ethanol-exposed groups; control fetuses had significantly higher iron concentrations than their mothers, whereas maternal and fetal iron concentrations were similar in ethanol-exposed animals. We conclude that daily ethanol exposure during the third-trimester-equivalent in sheep does not alter fetal liver morphology; however, decreased fetal liver ferric iron content and altered hepcidin and ferroportin gene expression indicate that iron homeostasis is altered.
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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 | 0.001 |
| 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".