Formation of Extracellular Matrix-Digesting Invadopodia by Primary Aortic Smooth Muscle Cells
Bibliographic record
Abstract
Invasion of the subendothelial space by vascular smooth muscle cells (VSMCs) contributes to the development and progression of diverse cardiovascular diseases. In this report we show that the expression of activated versions of Src, Cdc42 and Rac1, or a kinase-dead but open form of the p21-activated kinase (PAK1), induces primary rat aorta VSMCs to form extracellular matrix-degrading actin-rich protrusions that are morphologically similar to the invadopodia formed by highly invasive tumor cells. The matrix-degrading structures are enriched in known markers for invadopodia, including cortactin and tyrosine-phosphorylated cortactin and contain the matrix metalloproteinases MMP-9 and MT1-MMP and the urokinase plasminogen activator receptor (uPAR). In contrast to other cell types, invadopodia formation in VSMCs is only weakly supported by the phorbol ester PBDu. Invadopodia formation by Src was dependent on Cdc42, Rac, and ERK, but not on p38 MAPK. Invadopodia formation induced by kinase-dead PAK1 required Src and ERK activity and a direct interaction with the exchange factor PIX. VSMCs embedded in a three-dimensional collagen matrix formed actin- and cortactin-rich extensions that penetrated through holes in the matrix, suggesting that invadopodia-like structures are formed in a three-dimensional environment.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".