Maternal Nicotine Exposure Induces Congenital Heart Defects in the Offspring of Mice
Bibliographic record
Abstract
Background and Purpose : Congenital heart defects (CHDs) are the most prevalent birth defect, and maternal cigarette smoking is a known risk factor. Nicotine replacement therapies are recommended to pregnant women who smoke to aid in smoking cessation, as this alternative is thought to be safer compared to cigarette smoking. However, these products contain nicotine, and the safety of nicotine on the developing heart is not well known. We examined the effects of maternal nicotine exposure (MNE) during pregnancy on fetal heart development in mice. Experimental Approach : C57BL/6 female mice were treated with nicotine at 1.5 mg/kg/day using subcutaneous osmotic pumps and bred with normal male mice. The effects of MNE on fetal hearts were analyzed. Key Results : MNE resulted in CHDs and hypoplastic coronary arteries in fetal mice at significant incidences of 43% and 31%, respectively. CHDs included septal defects, atrioventricular septal defects, double outlet right ventricles, thickened aortic and pulmonary valves, isolated hypoplastic left ventricles, and ventricular hypertrophy. Moreover, MNE resulted in altered gene expression of key cardiogenic regulators and higher levels of oxidative stress in the embryonic hearts. Fetal heart epicardial epithelial-to-mesenchymal transition (EMT) was lower with MNE. Conclusions and Implications : MNE results in a higher incidence of congenital heart defects and coronary artery defects. These findings provide insight into the dangers of nicotine replacement therapy to fetuses during pregnancy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".