Regulation of eNOS Expression in Brain Endothelial Cells by Perinuclear EP <sub>3</sub> Receptors
Bibliographic record
Abstract
We reported upregulation of endothelial nitric oxide synthase (eNOS) by PGE(2) in tissues and presence of perinuclear PGE(2) receptors (EP). We presently studied mechanisms by which PGE(2) induces eNOS expression in cerebral microvessel endothelial cells (ECs). 16,16-Dimethyl PGE(2) and selective EP(3) receptor agonist M&B28767 increased eNOS expression in ECs and the NO-dependent vasorelaxant responses induced by substance P on cerebral microvessels. These effects could be prevented by prostaglandin transporter blocker bromcresol green and actinomycin D. EP(3) immunoreactivity was confirmed on plasma and perinuclear membrane of ECs. M&B28767 increased eNOS RNA expression in EC nuclei, and this effect was augmented by overexpression of EP(3) receptors. M&B28767 also induced increased phosphorylation of Erk-1/2 and Akt, as well as changes in membrane potential revealed by the potentiometric fluorescent dye RH421, which were prevented by iberiotoxin; perinuclear K(Ca) channels were detected, and their functionality corroborated by NS1619-induced Ca(2+) signals and nuclear membrane potential changes. Moreover, pertussis toxin, Ca(2+) chelator, and channel blockers EGTA, BAPTA, and SK&F96365, as well as K(Ca) channel blocker iberiotoxin, protein-kinase inhibitors wortmannin and PD 98059, and NF-kappaB inhibitor pyrrolidine dithiocarbamate prevented M&B28767-induced increase in Ca(2+) transients and/or eNOS expression in EC nuclei. We describe for the first time that PGE(2) through its access into cell by prostaglandin transporters induces eNOS expression by activating perinuclear EP(3) receptors coupled to pertussis toxin-sensitive G proteins, a process that depends on nuclear envelope K(Ca) channels, protein kinases, and NF-kappaB; the roles for nuclear EP(3) receptors seem different from those on plasma membrane.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".