IL-17A Contributes to the Pathogenesis of Endometriosis by Triggering Proinflammatory Cytokines and Angiogenic Growth Factors
Bibliographic record
Abstract
Endometriosis is a chronic, inflammatory disease characterized by the growth of endometrial tissue in aberrant locations outside the uterus. Neoangiogenesis or establishment of new blood supply is one of the fundamental requirements of endometriotic lesion survival in the peritoneal cavity. IL-17A is emerging as a potent angiogenic and proinflammatory cytokine involved in the pathophysiology of several chronic inflammatory diseases such as rheumatoid arthritis and psoriasis. However, sparse information is available in the context of endometriosis. In this study, we demonstrate the potential importance of IL-17A in the pathogenesis and pathophysiology of endometriosis. The data show a differential expression of IL-17A in human ectopic endometriotic lesions and matched eutopic endometrium from women with endometriosis. Importantly, surgical removal of lesions resulted in significantly reduced plasma IL-17A concentrations. Immunohistochemistry revealed localization of IL-17A primarily in the stroma of matched ectopic and eutopic tissue samples. In vitro stimulation of endometrial epithelial carcinoma cells, Ishikawa cells, and HUVECs with IL-17A revealed significant increase in angiogenic (vascular endothelial growth factor and IL-8), proinflammatory (IL-6 and IL-1β), and chemotactic cytokines (G-CSF, CXCL12, CXCL1, and CX3CL1). Furthermore, IL-17A promoted tubulogenesis of HUVECs plated on Matrigel in a dose-dependent manner. Thus, we provide the first evidence, to our knowledge, that endometriotic lesions produce IL-17A and that the removal of the lesion via laparoscopic surgery leads to the significant reduction in the systemic levels of IL-17A. Taken together, our data show a likely important role of IL-17A in promoting angiogenesis and proinflammatory environment in the peritoneal cavity for the establishment and maintenance of endometriosis lesions.
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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 | 0.001 | 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".