In Vitro Study of Mechanisms Underlying the Developmental Effects of Bisphenol A Using Human Fetal Lung Fibroblasts
Bibliographic record
Abstract
Both experimental and/or epidemiological studies suggest that prenatal exposure to bisphenol A (BPA) may delay fetal lung development and maturation and increase the susceptibility to childhood respiratory disease.However, the underlying mechanisms remain to be elucidated.In our study with cultured human fetal lung fibroblasts (HFLF), we demonstrated that 24 h exposure to 1 and 100 µM BPA increased nuclear expression of GPR30, at 100 μM, also increased cytoplasmic expression of ERβ and release of GDF-15, as well as decreased release of IL-6, ET-1, and IP-10 through suppression of NFκB phosphorylation, with no effects on cell viability.By performing global gene expression and pathway analyses, we identified molecular pathways, gene networks, and key molecules that were affected by 100, but not 0.01 and 1, µM BPA in HFLF.Using multiple genomic and proteomic tools, we confirmed these changes at both gene and protein levels.Our data suggest that 100 μM BPA increased CYP1B1 and HSD17B14 gene and protein expression and release of endogenous estradiol, which was associated with increased ROS production and DNA double strand breaks, upregulation of genes and/or proteins in steroid synthesis and metabolism, and activation of Nrf2-regulated stress response pathways.In addition, BPA also activated ATM-p53 signaling pathway, resulting in increased cell cycle arrest at G1 phase, senescence, and autophagy in HFLF.Fetal lung development and maturation requires paracrine interaction between fetal lung alveolar type II epithelial cells and fibroblasts.The results from our studies suggest that prenatal exposure to BPA at high enough concentrations may affect fetal lung development and maturation, by altering the release of developmental, immune, and hormonal modulators from fetal lung fibroblasts, and thereby affecting susceptibility to childhood respiratory disease.
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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) | 0.000 | 0.001 |
| 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 | 0.001 |
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".