G protein‐coupled oestrogen receptor 1 (GPER1)/GPR30: a new player in cardiovascular and metabolic oestrogenic signalling
Bibliographic record
Abstract
Oestrogens are important sex hormones central to health and disease in both genders that have protective effects on the cardiovascular and metabolic systems. These hormones act in complex ways via both genomic and non‐genomic mechanisms. The genomic mechanisms are relatively well characterized, whereas the non‐genomic ones are only beginning to be explored. Two oestrogen receptors (ER), ERα and ERβ, have been described that act as nuclear transcription factors but can also associate with the plasma membrane and influence cytosolic signalling. ERα has been shown to mediate both anti‐atherogenic effects and pro‐survival effects in pancreatic β‐cells. In recent years, a third membrane‐bound ER has emerged, G protein‐coupled receptor 30 or G protein‐coupled oestrogen receptor 1 (GPER1), which mediates oestrogenic responses in cardiovascular and metabolic regulation. Both GPER1 knock‐out models and pharmacological agents are now available to study GPER1 function. These tools have revealed that GPER1 activation may have several beneficial effects in the cardiovascular system including vasorelaxation, inhibition of smooth muscle cell proliferation, and protection of the myocardium against ischaemia/reperfusion injury, and in the metabolic system including stimulation of insulin release and protection against pancreatic β‐cell apoptosis. Thus, GPER1 is emerging as a candidate therapeutic target in both cardiovascular and metabolic disease. LINKED ARTICLES This article is one of a set of reviews submitted to BJP in connection with talks given at the September 2010 meeting of the International Society of Hypertension in Vancouver, Canada. To view the other articles in this collection visit http://dx.doi.org/10.1111/j.1476‐5381.2010.01167.x , http://dx.doi.org/10.1111/j.1476‐5381.2011.01260.x and http://dx.doi.org/10.1111/j.1476‐5381.2011.01366.x
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".