Interleukin‐17A expression in endometriotic tissue and plasma samples from women with endometriosis (539.2)
Bibliographic record
Abstract
Cytokines present within the environment of endometriosis are believed to contribute to the pathogenesis of the disease by promoting inflammatory conditions surrounding the implantation of endometriotic lesions. Interleukin‐17A is a member of proinflammatory cytokines implicated in the pathogenesis of various chronic inflammatory diseases. However, its role in the disease progression of endometriosis is poorly understood. The objective of this study was to elucidate the involvement of IL‐17A in the pathogenesis of endometriosis. To investigate this, IL‐17A concentration was measured in plasma, eutopic and ectopic samples from women with endometriosis and in plasma and eutopic samples from women without endometriosis. Immunostaining for IL‐17A was conducted on eutopic and ectopic tissue sections. To elucidate biological function of IL‐17A, WST‐1 proliferation assay, cell cycle analysis with Propidium Iodide (PI) , and supernatant analysis were performed with endometrial epithelial carcinoma cells (EECCs) . Expression of IL‐17A, IL‐17RA, and IL‐17RC mRNA from EECCs and primary EECs was measured using qPCR. Flow cytometry was performed on EECCs to detect IL‐17RA expression. Results show presence of IL‐17A in plasma samples and ectopic tissue samples from women with endometriosis. Imunohistochemistry confirmed the presence of IL‐17A positive cells within both the epithelium and stroma of eutopic and ectopic tissue sections. Even though IL‐17A has shown no proliferative or apoptotic effect on EECCs, its stimulation on EECCs induced increased production of G‐CSF, VEGF, PDGF‐AA, and SDF‐1. Follow up investigation is needed to elucidate the understanding of the relationship between the presence of IL‐17A and the pathogenesis of endometriosis. Grant Funding Source : Supported by CIHR
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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 | 0.001 |
| 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 | 0.000 |
| 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".