RhoA inhibition activates MMP‐2 via a PI3K dependent mechanism.
Bibliographic record
Abstract
Basement membrane and interstitial matrix proteolysis are critical early steps in the angiogenic process, and require matrix metalloproteinase (MMP) activation. Skeletal muscle endothelial cells cultured as a monolayer on type I collagen exhibit high levels of stress fibre polymerization and low levels of MMP activity, indicative of a quiescent state. Depolymerization of stress fibres by RhoA inhibition with 10 μM H1152, an inhibitor of Rho kinase, increased cortical actin and MMP‐2 activation. We investigated the effect of RhoA inhibition on the localization of membrane type‐1 (MT1)‐MMP, the activator of MMP‐2, and found that H1152 treatment increased cell surface MT1‐MMP and caused MT1‐MMP localization to areas of strong cortical actin staining. Cortical actin polymerization is hypothesized to involve PI3K and we found that phospho‐AKT levels increased as early as 30 min post H1152 exposure and remained elevated for more than 2 hrs. Pretreatment with 10 μM LY294009, an inhibitor of PI3K, abolished the increase in active MMP‐2 observed with H1152 treatment alone. These results indicate that inhibition of RhoA, through a PI3K dependent mechanism, increases cell surface MT1‐MMP and localizes it to areas of cortical actin polymerization, which facilitates activation of MMP‐2. Funded by NSERC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".