Characterization of the adverse effects of nicotine on placental development: in vivo and in vitro studies
Bibliographic record
Abstract
In utero exposure to nicotine is associated with increased risk of numerous adverse fetal and neonatal outcomes, which suggests that it acts directly to affect placental development and the establishment of the fetomaternal circulation (FC). This study used both in vivo [Wistar rats treated with 1 mg/kg nicotine from 2 wk prior to mating until gestational day (GD) 15] and in vitro (RCHO-1 cell line; treated with 10(-9) to 10(-3)M nicotine) models to examine the effects of nicotine on these pathways. At GD 15, control and treated placentas were examined for the impact of nicotine on 1) trophoblast invasion, proliferation, and degree of hypoxia, 2) labyrinth vascularization, 3) expression of key genes of placental development, and 4) expression of placental angiogenic factors. The RCHO-1 cell line was used to determine the direct effects of nicotine on trophoblast differentiation. Our in vivo experiments show that nicotine inhibits trophoblast interstitial invasion, increases placental hypoxia, downregulates labyrinth vascularization as well as key transcription factors Hand1 and GCM1, and decreases local and circulating EG-VEGF, a key placental angiogenic factor. The in vitro experiments confirmed the inhibitory effects of nicotine on the trophoblast migration, invasion, and differentiation processes and demonstrated that those effects are most likely due to a dysregulation in the expression of nicotine receptors and a decrease in MMP9 activity. Taken together, these data suggest that adverse effects of maternal smoking on pregnancy outcome are due in part to direct and endocrine effects of nicotine on the main processes of placental development and establishment of FC.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".