Discoidin Domain Receptor 1 Is Activated Independently of β1 Integrin
Bibliographic record
Abstract
Various types of collagen have been identified as potential ligands for the two mammalian discoidin domain receptor (DDR) tyrosine kinases, DDR1 and DDR2. It is presently unclear whether collagen-induced DDR receptor activation, which occurs with very slow kinetics, involves additional proteins with kinase activity or membrane-anchored proteins serving as coreceptors. In particular, the role of the collagen-binding integrins alpha(1)beta(1) or alpha(2)beta(1) in the DDR activation process is undefined. Here, we provide three lines of evidence suggesting that DDR1 signaling is distinct from integrin activation. First we demonstrate that the enzymatic activity of DDR1 is essential for receptor tyrosine phosphorylation. Collagen-induced DDR receptor autophosphorylation can be blocked either by a dominant negative mutant or by a preparation of recombinant extracellular domain. Second, we show DDR1 signals independent of the epidermal growth factor (EGF) receptor. In cells that endogenously express both DDR1 and the EGF receptor, stimulation with EGF does not induce DDR activation. Third, we detected full DDR1 activation after collagen stimulation in cells that have been treated with blocking antibodies for alpha(2)beta(1) integrin or in cells with a targeted deletion of the beta(1) integrin gene. Finally, we show that overexpression of dominant negative DDR1 in the myoblast cell line C2C12 blocks cellular differentiation and the formation of myofibers.
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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 | 0.001 |
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".