Integrin linked kinase (ILK) expression and function in vascular smooth muscle cells
Bibliographic record
Abstract
Vascular smooth muscle cell (SMC) migration and proliferation contribute to arterial wound repair and thickening of the intimal layer in atherosclerosis, restenosis and transplant vascular disease. These processes are influenced by cell adhesion to molecules present in the extracellular matrix, and regulated by the integrin family of cell-surface matrix receptors. An important signaling molecule acting downstream of integrin receptors is integrin-linked kinase (ILK), a serine/threonine kinase and scaffolding protein. ILK has been implicated in cancer cell growth and survival through modulation of downstream targets, notably Akt and glycogen synthase kinase-3beta (GSK3beta). Evidence also exists to establish ILK as a molecular adaptor protein linking integrins to the actin cytoskeleton and regulating actin polymerization, and this function may not necessarily depend upon the kinase activity of ILK. ILK has been implicated in anchorage-independent growth, cell cycle progression, epithelial-mesenchymal transition (EMT), invasion and migration. In addition, ILK has been shown to be involved in vascular development, tumor angiogenesis and cardiac hypertrophy. Despite the documented involvement of integrin signaling in vascular pathologies, the function of ILK has not been well characterized in the SMC response to vascular injury. This brief review summarizes and puts into context the current literature on ILK expression and function in the vascular smooth muscle cell.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".