Matrix Metalloproteinases in Endometrial Breakdown and Repair: Functional Significance in a Mouse Model1
Bibliographic record
Abstract
Considerable correlative evidence suggests an important role for matrix metalloproteinases (MMPs) in menstruation, a process which occurs naturally in very few species. In this study, MMP expression was examined in a mouse model of endometrial breakdown and repair and the functional importance of MMPs determined. In the model, progesterone support was withdrawn from mice in which endometrial decidualization had been induced; 24 h later, endometrial breakdown was complete, and the entire decidual zone had been shed. Re-epithelialization had occurred by 36 h, and the endometrium had undergone extensive restoration toward a predecidualized state by 48 h. Immunoreactive MMP9 and MMP7 colocalized with leukocyte subsets, particularly neutrophils, whereas MMP13 staining was always extracellular. MMP3 and MMP7 were abundant during re-epithelialization in close proximity to newly reforming epithelium. The functional importance of MMPs in these processes was examined using two MMP inhibitors, doxycycline and batimistat. Both inhibitors effectively reduced MMP activity, as assessed by in situ zymography, but did not have significant effects on endometrial breakdown or repair. This study demonstrates that although MMPs are present in abundance during endometrial breakdown and repair in this mouse model, they are not the key mediators of these processes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".