Nck Adapters Are Involved in the Formation of Dorsal Ruffles, Cell Migration, and Rho Signaling Downstream of the Platelet-derived Growth Factor β Receptor
Bibliographic record
Abstract
The SH3 and SH2 domain-containing adapter proteins Nck1 and Nck2 are known to function downstream of activated tyrosine kinase receptors, such as the platelet-derived growth factor (PDGF) receptors. The SH2 domain of Nck1 binds to phosphorylated tyrosine residue 751 in PDGFbeta receptor and has been suggested to have a role in the PDGF-induced mobilization of the actin filament system. Because Tyr-751 is a site for additional receptor interactors, it has been difficult to discriminate the signaling from Nck from signaling via other molecules. For this reason we have used mouse embryonic fibroblasts derived from mice in which the genes for Nck1 and Nck2 have been inactivated by gene targeting (knock-out (KO) cells). The mutant cells had a reduced ability to form edge ruffles in response to PDGF, and the presence of Nck was obligatory for the formation of dorsal ruffles. In addition, the KO cells had a reduced chemotactic and migratory potential. Importantly, KO cells had reduced cell attachment properties and a reduced ability to form focal adhesions in response to serum stimulation. Moreover, signaling involving the Rho GTPases was defective in KO cells. In summary, our observations suggest that the Nck adapters are needed for signaling to Rho GTPases and actin dynamics downstream of the PDGFbeta receptor.
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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".