Maternal Distress and Offspring Neurodevelopment: Challenges and Opportunities for Pre-clinical Research Models
Bibliographic record
Abstract
Pre-natal exposure to acute maternal trauma or chronic maternal distress can confer increased risk for psychiatric disorders in later life. Acute maternal trauma is the result of unforeseen environmental or personal catastrophes, while chronic maternal distress is associated with anxiety or depression. Animal studies investigating the effects of pre-natal stress have largely used brief stress exposures during pregnancy to identify critical periods of fetal vulnerability, a paradigm which holds face validity to acute maternal trauma in humans. While understanding these effects is undoubtably important, the literature suggests maternal stress in humans is typically chronic and persistent from pre-conception through gestation. In this review, we provide evidence to this effect and suggest a realignment of current animal models to recapitulate this chronicity. We also consider candidate mediators, moderators and mechanisms of maternal distress, and suggest a wider breadth of research is needed, along with the incorporation of advanced -omics technologies, in order to understand the neurodevelopmental etiology of psychiatric risk.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".