Contributions of T helper 9 cells in endometriosis-associated inflammation and lesion growth
Bibliographic record
Abstract
Endometriosis is an inflammatory gynecologic disease characterized by ectopic growth of endometrial-like tissue, resulting in pelvic pain and infertility. T-helper 9 (Th9) cells play a known role in various chronic inflammatory diseases. Despite parallels between endometriosis and Th9-driven diseases, their role in endometriosis has not been extensively explored. We investigated Th9 cell involvement in endometriosis pathophysiology using human tissue samples, in vitro experiments with human-derived Th9 cells, and in vivo experiments to shed insight on the impact of adoptively transferred Th9 cells in our established syngeneic endometriosis mouse model. Immunohistochemistry of a tissue microarray revealed significantly increased IL-9-positive cells in patient lesions compared to control endometrium. Human CD4+ Th cells purified from peripheral blood mononuclear cells treated with Th9-driving growth factors produced significantly altered proinflammatory mediators (increased IL-5 and IL-17F; decreased IL-8) in response to estrogen stimulation. Adoptive transfer of mouse Th9-like cells increased plasma IL-1α concentration and altered transcriptional profiles of several signaling pathways, including Notch and PI3K-Akt. Immunofluorescent microscopy depicted adoptively transferred Th9 cells present within mouse lesions. Furthermore, immunohistochemical analysis demonstrated reduced lesion proliferation following Th9 adoptive transfer. This study provides the first evidence that Th9 cells likely promote immune-inflammatory alterations within lesions to exacerbate disease.
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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) | 0.003 | 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".