Macrophage Migration Inhibitory Factor Antagonist Blocks the Development of Endometriosis In Vivo
Bibliographic record
Abstract
Endometriosis, a disease of reproductive age women, is a major cause of infertility, menstrual disorders and pelvic pain. Little is known about its etiopathology, but chronic pelvic inflammation is a common feature in affected women. Beside symptomatic treatment of endometriosis-associated pain, only two main suboptimal therapeutic approaches (hormonal and invasive surgery) are generally recommended to patients and no specific targeted treatment is available. Our studies led to the detection of a marked increase in the expression of macrophage migration inhibitory factor (MIF) in the eutopic endometrium, the peripheral blood and the peritoneal fluid of women with endometriosis, and in early, vascularized and active endometriotic lesions. Herein, we developed a treatment model of endometriosis, where human endometrial tissue was first allowed to implant into the peritoneal cavity of nude mice, to assess in vivo the effect of a specific antagonist of MIF (ISO-1) on the progression of endometriosis and evaluate its efficacy as a potential therapeutic tool. Administration of ISO-1 led to a significant decline of the number, size and in situ dissemination of endometriotic lesions. We further showed that ISO-1 may act by significantly inhibiting cell adhesion, tissue remodeling, angiogenesis and inflammation as well as by altering the balance of pro- and anti-apoptotic factors. Actually, mice treatment with ISO-1 significantly reduced the expression of cell adhesion receptors αv and ß3 integrins (P<0.05), matrix metalloproteinases (MMP) 2 and 9 (P<0.05), vascular endothelial cell growth factor (VEGF) (P<0.01), interleukin 8 (IL8) (P<0.05), cyclooxygenease (COX)2 (P<0.001) and the anti-apoptotic protein Bcl2 (P<0.01), but significantly induced the expression of Bax (P<0.05), a potent pro-apoptotic protein. These data provide evidence that specific inhibition of MIF alters endometriotic tissue growth and progression in vivo and may represent a promising potential therapeutic avenue.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".