Thymic stromal lymphopoietin contributes to endometriotic lesion proliferation and disease-associated inflammation
Bibliographic record
Abstract
Endometriosis is a chronic disorder in which endometrial-like tissue presents outside the uterus. Patients with endometriosis have been shown to exhibit aberrant immune responses within the lesion microenvironment and in circulation which contribute to the development of endometriosis. Thymic stromal lymphopoietin (TSLP) is an alarmin involved in cell proliferation and the induction of T helper 2 (Th2) inflammation in various diseases, such as asthma, atopic dermatitis, and pancreatic and breast cancer. Recent studies have detected TSLP within endometriotic lesions and shown that its concentrations are elevated in the peritoneal fluid of patients compared with control subjects. However, its role in disease pathophysiology remains unclear. Here, we compared TSLP messenger RNA and protein expression between patient eutopic endometrium, endometriotic lesions, and control endometrial samples. We also assessed its effect on the proliferation and apoptosis of human endometriosis-representative cell lines, as well as on lesion development and inflammation in a mouse model of the disease. We demonstrated that TSLP expression was elevated in the stroma of patient endometriotic lesions compared with control endometrial samples. In cell lines, TSLP treatment reduced the apoptosis of endometrial stromal cells and promoted the proliferation of THP-1 cells. In mice induced with endometriosis, TSLP treatment induced a Th2 immune response within the lesion microenvironment, and led to TSLP receptor modulation in macrophages, dendritic cells, and CD4+ T cells. Furthermore, treatment increased murine endometriotic lesion proliferation. Overall, these results suggest that TSLP modulates the endometriotic lesion microenvironment and promotes a Th2 immune response that could support lesion development.
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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) | 0.001 | 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".