GPER (GPR30): A Nongenomic Receptor (GPCR) for Steroid Hormones with Implications for Cardiovascular Disease and Cancer
Bibliographic record
Abstract
Although the rapid effects of steroids, such as estrogen and aldosterone, were postulated originally to be nongenomic, it is now appreciated that activation of such signaling pathways via a steroid-acting G protein-coupled receptor, the G protein estrogen receptor (GPER), has important transcription-dependent outcomes in the regulation of cell growth and programmed cell death secondary to GPER-regulated second-messenger pathways. GPER is expressed ubiquitously and has diverse biological effects, including regulation of endocrine, immune, neuronal, and cardiovascular functions. Perhaps the most biologically important consequences of GPER activation are the regulation of cell growth, migration, and apoptotic cell death. These cell growth regulatory effects, important in cancer biology, are also relevant in the regulation of cardiac and vascular hypertrophy and in the response to ischemia. This review provides a summary of relevant findings of the impact of GPER regulation by either estradiol or aldosterone in in vitro model systems and extends those findings to in vivo studies of direct clinical relevance for development of GPER-directed agents for treatment of cancer and cardiovascular diseases associated with cellular proliferation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".