Estrogen mediates inflammatory role of mast cells in endometriosis pathophysiology
Bibliographic record
Abstract
Endometriosis is an estrogen dependent, chronic inflammatory disease characterized by the growth of endometrial lining outside of the uterus. Mast cells have emerged as key players in regulating not only allergic responses but also other mechanisms such as angiogenesis, fibrosis, and pain. The influence of estrogen on mast cell function has also been recognized as a potential factor driving disease pathophysiology in number of allergic and chronic inflammatory conditions. However, precise information is lacking on the cross talk between endocrine and immune factors within the endometriotic lesions and whether that contributes to the involvement of mast cells with disease pathophysiology. In this study, we observed a significant increase in mast cell numbers within endometriotic lesions compared to matched eutopic endometrium from the same patients. Compared to eutopic endometrium, endometriotic lesions had significantly higher levels of stem cell factor (SCF), a potent growth factor critical for mast cell expansion, differentiation, and survival for tissue resident mast cells. Targeted mRNA Q-PCR array revealed that the endometriotic lesions harbour microenvironment (upregulation of CPA3, VCAM1, CCL2, CMA1, CCR1, and KITLG) that is conducive to mast cells recruitment and subsequent differentiation. To examine cross-talk of mast cells within the endometriotic lesion microenvironment, endometriotic epithelial cells (12Z) and endometrial stromal cells (hESC) incubated with mast cell-conditioned media showed significantly increased production of pro-inflammatory and chemokinetic cytokines. To further understand the impact of estrogen on mast cells in endometriosis, we induced endometriosis in C57BL/6 mice. Mature mast cells were significantly higher in peritoneal fluid of estrogen-treated mice compared to untreated mice within the sham operated groups. Mouse endometriotic lesion tissue revealed several genes (qRT-PCR) relevant in mast cell biology significantly upregulated in the estrogen treated, endometriosis-induced group compared to control endometrium. The endometriotic lesions from estrogen treated mice also had significantly higher density of Alcian blue stained mast cells compared to untreated lesions or control endometrium. Collectively, these findings suggest that endometriotic lesions provide a microenvironment necessary for recruitment and differentiation of mast cells. In turn, mast cells potentially release pro-inflammatory mediators that contribute to chronic pelvic pain and endometriosis disease progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".