Platelet growth factor induces smooth muscle migration through an integrin linked kinase‐dependent pathway
Bibliographic record
Abstract
Integrin linked kinase (ILK) is a cytoplasmic interactor of integrin receptors regulating cell survival, spreading, and contraction. In this study we aimed to evaluate the role of ILK in regulating smooth muscle cell (SMCs) migration, an important event during the development of atherosclerotic plaque and coronary artery disease. Primary mouse SMCs were cultured in the presence or absence of platelet growth factor (PDGF) and various specific inhibitors. Cell lysates were used for kinase and Western blot assays. Cell migration was measured using colorimetric migration or wound healing assays utilizing fluorescent imaging. Our study showed that PDGF could activate ILK, Akt, and Erk in SMCs without any effect on focal adhesion kinase and α‐paxillin. ILK inhibition had no effect on PDGF‐induced Akt and Erk activation, indicating that their activation is through an ILK‐independent pathway. Inhibition of ILK, PI3K/Akt, and Erk1/2 decreased SMCs migration, signifying the cooperation between these signaling pathways in regulating SMC migration. To our knowledge, this is the first report of a regulatory role for ILK in SMCs migration, which is independent from Akt and Erk1/2 pathways, and conveys new insights in our efforts to establish a novel therapeutic target for treatment of coronary artery occlusion. This work was supported by the Canadian Diabetes Association & the Michael Smith Foundation for Health Research.
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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".