Fetal alcohol spectrum disorder predisposes to metabolic abnormalities in adulthood
Bibliographic record
Abstract
Prenatal alcohol exposure (PAE) affects at least 10% of newborns globally and leads to the development of fetal alcohol spectrum disorders (FASDs). Despite its high incidence, there is no consensus on the implications of PAE on metabolic disease risk in adults. Here, we describe a cohort of adults with FASDs that had an increased incidence of metabolic abnormalities, including type 2 diabetes, low HDL, high triglycerides, and female-specific overweight and obesity. Using a zebrafish model for PAE, we performed population studies to elucidate the metabolic disease seen in the clinical cohort. Embryonic alcohol exposure (EAE) in male zebrafish increased the propensity for diet-induced obesity and fasting hyperglycemia in adulthood. We identified several consequences of EAE that may contribute to these phenotypes, including a reduction in adult locomotor activity, alterations in visceral adipose tissue and hepatic development, and persistent diet-responsive transcriptional changes. Taken together, our findings define metabolic vulnerabilities due to EAE and provide evidence that behavioral changes and primary organ dysfunction contribute to resultant metabolic abnormalities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".