Bisphenol A impacts cardiomyocyte differentiation in vitro by modulating cardiac protein expression
Bibliographic record
Abstract
introduction: Bisphenol A (BPA) is an environmental toxin commonly found in plastics and is able to mimic the actions of endogenous steroid hormones. BPA binds and activates intracellular estrogen receptors (eRα and eRβ) and estrogen related receptor γ (eRRγ), all of which are present in cardiomyocytes. however, it is unclear how BPA impacts the heart. We hypothesized that BPA modulates the expression of proteins regulating cardiac structure, energy and calcium homeostasis during cardiomyocyte differentiation in vitro. Methods: We differentiated h9C2 cells into cardiomyocytes in hormone-replete (Rm) or hormone-depleted (hD) media. We co-treated the cells with graded amounts of Bpa and pure anti-estrogen ICI 182,780, which blocks eRα and eRβ activity. Immunoblotting measured the expression of the structural protein β-myosin heavy chain (βmhC), calcium homeostasis protein sarcoendoplasmic reticulum calcium aTpase (seRCa2a), and the cardiac energy-producing protein creatine kinase (CK). results: expression of these proteins was hormone-dependent during cardiomyocyte differentiation, with expression highest in Rm media after 72 or 96 hours of differentiation. adding 10-8 m BPA to hD media increased cardiac structural (βmhC), energy (CK), and calcium homeostasis (seRCa2a) protein expression. Conversely, 10-7 m BPA added to Rm media decreased protein expression. Co-treatment with ICI 182,780 reduced Bpa-mediated induction of seRCa2a and CK expression in hD media. discussion: BPA modulates cardiac structure, calcium and energy homeostasis protein expression during cardiomyocyte differention in vitro. moreover, the data suggest that BPA mediates these changes in protein expression through activation of cardiomyocyte eRα, eRβ, or eRRγ.
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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 | 0.000 |
| 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 | 0.000 |
| 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".