ARF1 and ARF6 are dispensable for Crk-dependent epithelial-mesenchymal-like transitions.
Bibliographic record
Abstract
BACKGROUND: Activation of the Met receptor tyrosine kinase through its ligand, hepatocyte growth factor (HGF), promotes an epithelial-mesenchymal transition and cell dispersal. However, little is known about the HGF-dependent signals that regulate these events. HGF stimulation of epithelial cell colonies leads to the enhanced recruitment of the CrkII and CrkL adapter proteins to Met-dependent signaling complexes. Overexpression of Crk adapter proteins in MDCK cells promotes spreading and loss of adherens junctions, events regulated by HGF. We recently demonstrated that the overexpression of CrkII promotes the formation of a multi-molecular complex containing CrkII, Paxillin and GIT-2, an ARF-GAP. MATERIALS AND METHODS: To determine the possible role of ARF1 and ARF6 in Crk- and HGF-dependent cell spreading, dominant negative mutants of ARF1 or ARF6 were microinjected into MDCK cells. RESULTS: We report that MDCK cell lines overexpressing CrkII display reduced ARF6 but not ARF1 activity. While both ARF1 and ARF6 are required for the spreading of MDCK cells stimulated with HGF, ARF1 and ARF6 activity is dispensable for the spreading of cells microinjected with Crk. CONCLUSION: We propose that Crk adapter proteins may act downstream of ARF1 and ARF6 to promote cell spreading or rely on different pathways to enhance cell spreading.
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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) | 0.002 | 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".