Matrix Metalloproteinase-8 Promotes Vascular Smooth Muscle Cell Proliferation and Neointima Formation
Bibliographic record
Abstract
OBJECTIVE: We investigated the role of matrix metalloproteinase-8 (MMP8) in neointima formation and in vascular smooth muscle cell (VSMC) migration and proliferation. APPROACH AND RESULTS: After carotid artery wire injuring, MMP8(-/-)/apoE(-/-) mice had fewer proliferating cells in neointimal lesions and smaller lesion sizes. Ex vivo assays comparing VSMCs isolated from MMP8 knockout and wild-type mice showed that MMP8 knockout decreased proliferation and migration. Proteomics analysis revealed that a disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) had lower concentrations in MMP8 knockout VSMC culture media than in MMP8 wild-type VSMC culture media. Western blot, flow cytometric, and immunocytochemical analyses showed that MMP8 knockout VSMCs contained more pro-ADAM10 but less mature ADAM10, more N-cadherin, and β-catenin in the plasma membrane but less β-catenin in the nucleus and less cyclin D1. Treatment of MMP8 wild-type VSMCs with an ADAM10 inhibitor, GI254023X, or siRNA knockdown of ADAM10 in MMP8 wild-type VSMCs inhibited proliferation and migration, increased N-cadherin and β-catenin in the plasma membrane, reduced β-catenin in the nucleus, and decreased cyclin D1 expression. Incubation of MMP8 knockout VSMCs with a recombinant ADAM10 rescued the proliferative and migratory ability of MMP8 knockout VSMCs and increased cyclin D1 expression. Furthermore, immunohistochemical analyses showed colocalization of ADAM10 with VSMCs and N-cadherin, and nuclear accumulation of β-catenin in the neointima in apoE(-/-)/MMP8(+/+) mice. CONCLUSIONS: MMP8 enhances VSMC proliferation via an ADAM10, N-cadherin, and β-catenin-mediated pathway and plays an important role in neointima formation.
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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) | 0.000 | 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 | 0.000 |
| 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".