Augmented Angiogenic Factors Expression via FP Signaling Pathways in Peritoneal Endometriosis
Bibliographic record
Abstract
Angiogenesis is required for ectopic endometrial tissue growth. Our previous studies showed that prostaglandin F2α (PGF2α) biosynthetic enzymes and receptor were markedly elevated in endometriotic lesions and that PGF2α is a potent angiogenic factor in endothelial cells. We sought to determine whether or not the F-prostanoid receptor modulates angiogenesis in ectopic stromal cells. Release of angiogenic factors by ectopic endometrial stromal cell primary cultures stimulated with PGF2αand exposed to agents that target PGF2α signaling was assessed. The study was conducted in an immunology laboratory at the Centre Hospitalier Universitaire (Québec City) medical research center. Women found to have peritoneal endometriosis during laparoscopy were included in this study. Prostaglandin E2, PGF2α, vascular endothelial cell growth factor, and CXC chemokine ligand 8 mRNA and protein; FP prostanoid receptor expression. PGF2α markedly up-regulated prostaglandin E2, CXC chemokine ligand 8 and vascular endothelial cell growth factor secretion in endometriotic cells. This effect was suppressed in the presence of a specific F-prostanoid antagonist (AL8810) and its signaling pathway was dependent on F-prostanoid receptor variant. PGF2α can exert its proliferative and angiogenic activities either directly by stimulating endothelial cell proliferation, migration and angiogenesis through F-prostanoid receptor, or indirectly, by stimulating endometriotic stromal cells to produce potent angiogenic factors through either receptor variant. These results show for the first time that PGF2α exerts an angiogenic effect on ectopic stromal cells, inducing the secretion of major angiogenic factors via different F-prostanoid signaling pathways. This study suggests a new interpretation of the mechanism underlying endometriosis development involving PGF2α in endometriosis-associated angio-inflammatory changes.
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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 | 0.000 |
| 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 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".