The multifunctional Ca<sup>2+</sup>/calmodulin-dependent kinase II regulates vascular smooth muscle migration through matrix metalloproteinase 9
Bibliographic record
Abstract
The multifunctional CaMKII has been implicated in vascular smooth muscle cell (VSMC) migration, but little is known regarding its downstream targets that mediate migration. Here, we examined whether CaMKII regulates migration through modulation of matrix metalloproteinase 9 (MMP9). Using CaMKIIδ(-/-) mice as a model system, we evaluated migration and MMP9 regulation in vitro and in vivo. After ligation of the common carotid artery, CaMKII was activated in the neointima as determined by oxidation and autophosphorylation. We found that MMP9 was robustly expressed in the neointima and adventitia of carotid-ligated wild-type (WT) mice but was barely detectable in CaMKIIδ(-/-) mice. The perimeter of the external elastic lamina, a correlate of migration-related outward remodeling, was increased in WT but not in CaMKIIδ(-/-) mice. Migration induced by serum, platelet-derived growth factor, and tumor necrosis factor-α (TNF-α) was significantly decreased in CaMKIIδ(-/-) as compared with WT VSMCs, but migration was rescued with adenoviral overexpression of MMP9 in CaMKIIδ(-/-) VSMCs. Likewise, overexpression of CaMKIIδ in CaMKIIδ(-/-) VSMCs increased migration, whereas an oxidation-resistant mutant of CaMKIIδ did not. TNF-α strongly induced CaMKII oxidation and autophosphorylation as well as MMP9 activity, mRNA, and protein levels in WT, but not in CaMKIIδ(-/-) VSMC. Surprisingly, TNF-α strongly induced MMP9 promoter activity in WT and CaMKIIδ(-/-) VSMC. However, the MMP9 mRNA stability was significantly decreased in CaMKIIδ(-/-) VSMC. Our data demonstrate that CaMKII promotes VSMC migration through posttranscriptional regulation of MMP9 and suggest that CaMKII effects on MMP9 expression may be a therapeutic pathway in vascular injury.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".