Comparative Effect of Danazol and a GnRH Agonist on Monocyte Chemotactic Protein‐1 Expression by Endometriotic Cells
Bibliographic record
Abstract
PROBLEM: Endometriosis is associated with a chronic inflammatory process, and the increased number of activated peritoneal macrophages is one of the major hallmarks of this process. The medical treatment of the disease, which is based on the creation of an hypoestrogenic milieu unfavorable to the growth of endometriotic lesions, is often associated with a reduced peritoneal inflammation. The aim of this study was to investigate the ability of current therapeutic agents to modulate, through a direct mechanism, the expression by endometriotic cells of monocyte chemotactic protein-1 (MCP-1), a chemokine endowed with the potent faculty of recruiting and activating macrophages. METHOD OF STUDY: Cells were stimulated with interleukin-1 beta (IL-1beta) to induce MCP-1 expression. MCP-1 protein secretion and mRNA steady-state levels were evaluated by ELISA and northern blot, respectively. RESULTS: Our results show that danazol concentrations (10(-7) -10(-5) M), taking into account the therapeutic levels found in the plasma of treated patients, inhibited MCP-1 protein and mRNA steady-state levels in endometriotic cells, whereas buserelin acetate (0.1-10 ng/mL), a GnRH agonist, had no significant effect. Dexamethasone, an anti-inflammatory glucocorticoid, used at concentrations varying between 10(-12) and 10(-6) M, also displayed a dose-dependent inhibitory action. CONCLUSIONS: These results put into prominence the capability of danazol to directly inhibit the expression of a potent monocyte chemotactic and activating factor by ectopic endometrial cells shedding more light on the mechanisms underlying the clinical effects of hormonal therapeutic agents used in the treatment of endometriosis.
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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 | 0.000 |
| 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".