Sex Hormones and Vascular Function
Bibliographic record
Abstract
GPER (GPR30) is an intracellular transmembrane ER that initiates many rapid non-genomic signaling events, including intracellular calcium mobilization and synthesis of phosphatidyl-inositol 3,4,5-triphosphate in the nucleus of multiple cell types.(Revankar et al, 2005).GPER has been indentified in human internal mammary arteries, saphenous veins, and contributes to vasorelaxation in arteries, although this mechanism remains to be fully understood ( Haas et al, 2009) Estrogen acts on various cell types through both genomic and non-genomic mechanisms.Genomic effects occur when estrogen binds to ERs in target tissue cell nuclei, resulting in changes in gene expression.Multiple genes in both the nuclear and mitochondrial genomes are regulated by ER and ER-.(O'Lone et al, 2007) In aortic smooth muscle cells and endothelial cells of wild-type ovariectomized mice, E2 treatment resulted in both up-and down-regulation of multiple genes involved in mitochondrial fuction.ER upregulated four clusters of genes, while ER downregulated a different set of mitochondrial genes.E2 also stimulates oxidative phosphorylation and inhibits production of superoxide and other reactive oxygen species in mitochondria.(O'Lone et al, 2007) It is hypothesized that this mechanism decreases the rate of accumulation of mitochondrial DNA mutations over a lifespan, and therefore protects against age-related disease.This notion is relevant to the development of CVD and timing of HRT initiation.(O'Lone et al, 2007) Estrogen can also trigger non-genomic events by binding to targets other than nuclear receptors, eg., cell membrane ERs.(Kelly and Levin, 2001) Non-genomic effects, such as direct activation of intracellular signaling pathways, can be rapid and do not require changes in gene expression, although the long-term consequences include altered transcription of targeted genes.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".