Is fetal brain monoamine oxidase inhibition the missing link between maternal smoking and conduct disorders?
Bibliographic record
Abstract
Smoking is the leading cause of preventable illness in the world today. Prenatal cigarette smoke exposure (PCSE) is a particularly insidious form because so many of its associated health effects befall the unborn child and produce behavioural outcomes that manifest themselves only years later. Among these are the associations between PCSE and conduct disorders, which have been mostly ascribed to the deleterious effects of nicotine on the fetal brain. Here we hypothesize that inhibition of brain monoamine oxidase (MAO) during fetal brain development, secondary to maternal cigarette smoking and in addition to nicotine, is a likely contributor to this association. MAOs play a central role in monoaminergic balance in the brain, and their inhibition during fetal development - but not during adult life - is known to result in an aggressive phenotype in laboratory animals. This paper provides theoretical and experimental support for the notion that cigarette smoke-induced inhibition of MAO in the fetal brain, particularly when it occurs in combination with polymorphisms in the MAOA gene that lead to lower enzyme concentration in the brain, may result in brain morphologic and functional changes that enhance the risk of irritability, poor self-control and aggression in the offspring. It also encourages research to evaluate whether the interaction of smoking exposure during fetal development and MAOA genotype increases the risk for conduct disorder over that incurred by mere fetal exposure to tobacco smoke.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".