PGE2-induced migration of human brain endothelial cell is mediated though protein kinase A in cooperation of EP receptors
Bibliographic record
Abstract
Abstract PGE2 plays a critical role in angiogenesis, ischemic, and neuro-inflammatory disorders of the brain, which breakdown the blood-brain barrier (BBB). However, the effects of PGE2 on human brain endothelial cell (HBECs) migration, a key process in the angiogenic response and BBB stability, are not well defined. In this study, we investigated the mechanism of PGE2 in HBECs migration in vitro. Here we showed that PGE2 stimulated migration of HBECs in a dose-time and matrix-dependent manner, evaluated by the Boyden chamber assay, but other prostanoids failed to do so. PGE2 receptor (EP2; butaprost), EP3 (sulprostone), and EP4 (PGE1-OH) receptor agonists stimulated HBECs migration, but the silencing of EP significantly attenuated this effect. EP1 agonist (11-trinor PGE1) had no effect on HBECs migration on silencing of the EP1 receptor. We further showed that PGE2 stimulated cAMP production and activated protein kinase A (PKA), whereas pretreatment with the adenyl cyclase inhibitor (dideoxyadenosine; 1 μM) or PKA inhibitors, H89 (0.5 μM)/PKAI (1 μM), completely abrogated PGE2-induced migration. Furthermore, silencing of the EP2/EP4 receptors significantly inhibited PGE2-induced cAMP and PKA activation, whereas EP3 receptor silencing failed to do so. These results suggest that PGE2 regulates HBEC migration via cooperation of EP2, EP3, and EP4 receptors. Coupling of PGE2 to these receptors resulted in increased production of cAMP, which regulates HBEC migration via PKA pathway. The elucidation of molecular events involved is critical for the development of targeted strategies to treat cerebrovascular diseases associated with dysregulated angiogenesis.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".