Signaling Mechanism for Discoidin Domain Receptor 1 Mediated Smooth Muscle Cell Migration
Bibliographic record
Abstract
Discoidin domain receptors (DDRs) are membrane receptor tyrosine kinases for collagens. Our previous studies have shown that DDR1 is important in regulating smooth muscle cell (SMC) proliferation and migration leading to intimal thickening following vascular injury. In order to study the underlying mechanism, we looked at mitogen activated protein kinase (MAPK) signaling in response to DDR1 activation. SMCs harvested from DDR1 +/+ , DDR1 −/ − mice, and DDR1 +/+ SMCs with overexpression of human DDR1b (O/hDDR1b) were used for the studies. Tyrosine phosphorylation of DDR1 was detected in O/hDDR1b cells upon type I collagen stimulation, with a peak at 4 h. In O/hDDR1b cells, ERK1/2 was activated upon type I collagen stimulation, starting at 4 h and sustained to 16 h. By contrast in DDR1 +/+ cells, ERK1/2 activation was delayed to 16 h, and in DDR1 −/ − cells ERK1/2 was not activated. P38K was activated in O/hDDR1b cells in response to type I collagen stimulation, starting at 90 min and sustained to 16 h. Delayed activation of p38K (at 16 h) was observed in both DDR1 +/+ and DDR1 −/ − cells. We conclude that activation of ERK1/2 but not P38K is dependent upon the DDR1. We also determined the role of Src in DDR1 mediated MAPK activation. We showed association of Src with activated DDR1. Src inhibitor PP2 inhibited type I collagen induced tyrosine phosphorylation of DDR1. PP2 also significantly reduced DDR1‐dependent ERK1/2 activation, but not DDR1‐independent p38K activation. In conclusion, in SMCs activation of DDR1 by type I collagen drives downstream ERK1/2 activation in a mechanism which is possibly through binding to and regulating DDR1 tyrosine phosphorylation. Future studies will be focused on linking the above DDR1 initiated signaling pathway to SMC cell proliferation and migration.
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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) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".