Chronic prenatal ethanol exposure increases adiposity and disrupts pancreatic morphology in adult guinea pig offspring
Bibliographic record
Abstract
BACKGROUND: Ethanol consumption during pregnancy can lead to a range of adverse developmental outcomes in children, termed fetal alcohol spectrum disorder (FASD). Central nervous system injury is a debilitating and widely studied manifestation of chronic prenatal ethanol exposure (CPEE). However, CPEE can also cause structural and functional deficits in metabolic pathways in offspring. OBJECTIVES AND METHODS: This study tested the hypothesis that CPEE increases whole-body adiposity and disrupts pancreatic structure in guinea pig offspring. Pregnant guinea pigs received ethanol (4 g kg(-1) maternal body weight per day) or isocaloric-sucrose/pair-feeding (control) for 5 days per week throughout gestation. RESULTS: Male and female CPEE offspring demonstrated growth restriction at birth, followed by a rapid period of catch-up growth before weaning (postnatal day (PD) 1-7). Whole-body magnetic resonance imaging (MRI) in young adult offspring (PD100-140) revealed increased visceral and subcutaneous adiposity produced by CPEE. At the time of killing (PD150-200), CPEE offspring also had increased pancreatic adipocyte area and decreased β-cell insulin-like immunopositive area, suggesting reduced insulin production and/or secretion from pancreatic islets. CONCLUSION: CPEE causes increased adiposity and pancreatic dysmorphology in offspring, which may signify increased risk for the development of metabolic syndrome and type 2 diabetes mellitus.
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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 | 0.001 | 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) | 0.002 | 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".