Prenatal maternal depressive symptoms are associated with neonatal left amygdala microstructure in a sex‐dependent way
Bibliographic record
Abstract
Exposures to prenatal maternal depressive symptoms (PMDS) may lead to neurodevelopmental changes in the offspring in a sex-dependent way. Although a connection between PMDS and infant brain development has been established by earlier studies, the relationship between PMDS exposures measured at various prenatal stages and microstructural alterations in fundamental subcortical structures such as the amygdala remains unknown. In this study, we investigated the associations between PMDS measured during gestational weeks 14, 24 and 34 and infant amygdala microstructural properties using diffusion tensor imaging. We explored amygdala mean diffusivity (MD) alterations in response to PMDS in infants aged 11 to 54 days from birth. PMDS had no significant main effect on the amygdala MD metrics. However, there was a significant interaction effect for PMDS and infant sex in the left amygdala MD. Compared with girls, boys exposed to greater PMDS during gestational week 14 showed significantly higher left amygdala MD. These results indicate that PMDS are linked to infants' amygdala microstructure in boys. These associations may be relevant to later neuropsychiatric outcomes in the offspring. Further research is required to better understand the mechanisms underlying these associations and to develop effective interventions to counteract any potential adverse consequences.
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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 | 0.000 | 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) | 0.001 | 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".