Epoxyeicosatrienoic acid (EET)-stimulated angiogenesis is mediated by epoxy hydroxyeicosatrienoic acids (EHETs) formed from COX-2
Bibliographic record
Abstract
Epoxyeicosatrienoic acids (EETs) are formed from the metabolism of arachidonic acid by cytochrome P450s. EETs promote angiogenesis linked to tumor growth in various cancer models that is attenuated in vivo by cyclooxygenase 2 (COX-2) inhibitors. This study further defines a role for COX-2 in mediating endothelial EET metabolism promoting angiogenesis. Using human aortic endothelial cells (HAECs), we quantified 8,9-EET-induced tube formation and cell migration as indicators of angiogenic potential in the presence and absence of a COX-2 inducer [phorbol 12,13-dibutyrate (PDBu)]. The angiogenic response to 8,9-EET in the presence of PDBu was 3-fold that elicited by 8,9-EET stabilized with a soluble epoxide hydrolase inhibitor ( t- TUCB). Contributing to this response was the COX-2 metabolite of 8,9-EET, the 11-hydroxy-8,9-EET (8,9,11-EHET), which exogenously enhanced angiogenic responses in HAECs at levels comparable to those elicited by vascular endothelial growth factor (VEGF). In contrast, the 15-hydroxy-8,9-EET isomer was also formed but inactive. The 8,9,11-EHET also promoted expression of the VEGF family of tyrosine kinase receptors. These results indicate that 8,9-EET-stimulated angiogenesis is enhanced by COX-2 metabolism in the endothelium through the formation of 8,9,11-EHET. This alternative pathway for the metabolism of 8,9-EET may be particularly important in regulating angiogenesis under circumstances in which COX-2 is induced, such as in cancer tumor growth and inflammation.
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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 | 0.000 |
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 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".