Extracellular matrix proteases contribute to progression of pelvic organ prolapse in mice and humans
Bibliographic record
Abstract
Pelvic organ prolapse (POP) is a common condition affecting almost half of women over the age of 50. The molecular and cellular mechanisms underlying this condition, however, remain poorly understood. Here we have reported that fibulin-5, an integrin-binding matricellular protein that is essential for elastic fiber assembly, regulated the activity of MMP-9 to maintain integrity of the vaginal wall and prevented development of POP. In murine vaginal stromal cells, fibulin-5 inhibited the β1 integrin-dependent, fibronectin-mediated upregulation of MMP-9. Mice in which the integrin-binding motif was mutated to an integrin-disrupting motif (Fbln5RGE/RGE) exhibited upregulation of MMP-9 in vaginal tissues. In contrast to fibulin-5 knockouts (Fbln5-/-), Fbln5RGE/RGE mice were able to form intact elastic fibers and did not exhibit POP. However, treatment of mice with β-aminopropionitrile (BAPN), an inhibitor of matrix cross-linking enzymes, induced subclinical POP. Conversely, deletion of Mmp9 in Fbln5-/- mice significantly attenuated POP by increasing elastic fiber density and improving collagen fibrils. Vaginal tissue samples from pre- and postmenopausal women with POP also displayed significantly increased levels of MMP-9. These results suggest that POP is an acquired disorder of extracellular matrix and that therapies targeting matrix proteases may be successful for preventing or ameliorating POP in women.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".