Prenatal antidepressant exposure and sex differences in neonatal corpus callosum microstructure
Bibliographic record
Abstract
Prenatal exposure to selective serotonin reuptake inhibitor (SSRI) antidepressants may influence white matter (WM) development, as previous studies report widespread microstructural alterations and reduced interhemispheric connectivity in SSRI-exposed infants. In rodents, perinatal SSRIs had sex-specific disruptions in corpus callosum (CC) axon architecture and connectivity; yet it is unknown whether SSRI-related brain outcomes in humans are sex specific. In this study, the neonate CC was selected as a region-of-interest to investigate whether prenatal SSRI exposure has sex-specific effects on early WM microstructure. On postnatal day 7, diffusion tensor imaging was used to assess WM microstructure in SSRI-exposed (n = 24; 12 male) and nonexposed (n = 48; 28 male) term-born neonates. Fractional anisotropy was extracted from CC voxels and a multivariate discriminant analysis was used to identify latent patterns differing between neonates grouped by SSRI-exposure and sex. Analysis revealed localized variations in CC fractional anisotropy that significantly discriminated neonate groups and correctly predicted group membership with an 82% accuracy. Such effects were identified across three dimensions, representing sex differences in SSRI-exposed neonates (genu, splenium), SSRI-related effects independent of sex (genu-to-rostral body), and sex differences in nonexposed neonates (isthmus-splenium, posterior midbody). Our findings suggest that CC microstructure may have a sex-specific, localized, developmental sensitivity to prenatal SSRI exposure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".