Cdc42 and RhoA have opposing roles in regulating membrane type 1-matrix metalloproteinase localization and matrix metalloproteinase-2 activation
Bibliographic record
Abstract
Proteolysis of the basement membrane and interstitial matrix occurs early in the angiogenic process and requires matrix metalloproteinase (MMP) activity. Skeletal muscle microvascular endothelial cells exhibit robust actin stress fibers, low levels of membrane type 1 (MT1)-MMP expression, and minimal MMP-2 activation. Depolymerization of the actin cytoskeleton increases MT1-MMP expression and MMP-2 activation. Rho family GTPases are regulators of actin cytoskeleton dynamics, and their activity can be modulated in response to angiogenic stimuli such as vascular endothelial growth factor (VEGF). Therefore, we investigated their roles in MMP-2 and MT1-MMP production. Endothelial cells treated with H1152 [an inhibitor of Rho kinase (ROCK)] induced stress fiber depolymerization and an increase in cortical actin. Both MMP-2 and MT1-MMP mRNA increased, which translated into greater MMP-2 protein production and activation. ROCK inhibition rapidly increased cell surface localization of MT1-MMP and increased PI3K activity, which was required for MMP-2 activation. Constitutively active Cdc42 increased cortical actin polymerization, phosphatidylinositol 3-kinase activity, MT1-MMP cell surface localization, and MMP-2 activation similarly to inhibition of ROCK. Activation of Cdc42 was sufficient to decrease RhoA activity. Capillary sprout formation in a three-dimensional collagen matrix was increased in cultures treated with RhoAN19 or Cdc42QL and, conversely, decreased in cultures treated with dominant negative Cdc42N17. VEGF stimulation also induced activation of Cdc42 while inhibiting RhoA activity. Furthermore, VEGF-dependent activation of MMP-2 was reduced by inhibition of Cdc42. These results suggest that Cdc42 and RhoA have opposing roles in regulating cell surface localization of MT1-MMP and MMP-2 activation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".