Brain volume and magnetic susceptibility differences in children and adolescents with prenatal alcohol exposure
Bibliographic record
Abstract
BACKGROUND: Prenatal alcohol exposure (PAE) can negatively affect brain development thereby increasing the risk of cognitive deficits, behavioral challenges, and mental health problems. Brain iron is important for a number of physiological processes for healthy brain development. Animal studies show that PAE reduced brain iron; however, this has not been investigated in human children with PAE. METHODS: We studied 20 children and adolescents with PAE and 44 unexposed children and adolescents aged 7.5 to 15 years. All children underwent quantitative susceptibility mapping and T1-weighted magnetic resonance imaging scans. Susceptibility and volume measurements of the caudate, putamen, pallidum, thalamus, amygdala, hippocampus, and nucleus accumbens were extracted using FreeSurfer. ANCOVAs were used to compare volume and susceptibility between groups for each region of interest, controlling for age and gender. For structures where susceptibility differed by group, we also tested for an association between intelligence quotient (IQ) and susceptibility. RESULTS: There were no significant group differences in susceptibility after multiple comparison correction, though the PAE group had higher susceptibility in the thalamus compared to unexposed participants before correction (p = 0.032, q = 0.230). There was no association between IQ and thalamus susceptibility. The PAE group had significantly lower volume in the bilateral caudate, bilateral pallidum, and left putamen. CONCLUSIONS: These findings suggest susceptibility may be altered in children and adolescents with PAE, though more research is needed. Volume reductions are consistent with previous literature and likely underlie cognitive and behavioral deficits associated with PAE.
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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 | 0.001 |
| 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) | 0.001 | 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".