Tamoxifen and ICI 182,780 negatively influenced cardiac cell growth via an estrogen receptor-independent mechanism
Bibliographic record
Abstract
BACKGROUND: Recent studies have demonstrated that selective estrogen receptor modulators (SERMs) reduced identifiable risk factors implicated in cardiovascular disease. Despite this observation, the direct effect of SERMs on cardiac cell growth remains unexplored. METHODS: Neonatal rat cardiac myocytes (CM) and fibroblasts (CF) were exposed to either the partial estrogen receptor agonist/antagonist 4-OH tamoxifen (e.g., SERM) or the pure estrogen receptor antagonist ICI 182,780 and the effect on DNA synthesis, cell cycle protein expression and extracellular signal-regulated kinase (ERK1/2) phosphorylation were assessed. RESULTS: The treatment of CM and CF with either 4-OH tamoxifen or ICI 182,780 decreased DNA synthesis in the absence of apoptosis via an estrogen receptor-independent pathway. In CM and CF, 4-OH tamoxifen and ICI 182,780 treatment reduced proliferating cell nuclear antigen protein expression and concomitantly increased p27Kip1. 4-OH Tamoxifen and ICI 182,780 treatment increased ERK1/2 phosphorylation in CM and CF, and ERK1/2 kinase (MEK)-dependent inhibition of ERK1/2 activation attenuated ICI 182,780-mediated suppression of DNA synthesis. CONCLUSION: These data are the first to describe cardiac cells as novel targets of SERMs and ICI 182,780, and highlight the role of the ERK1/2 pathway in the suppression of DNA synthesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".