LAR protein tyrosine phosphatase regulates focal adhesions through CDK1
Bibliographic record
Abstract
Focal adhesions are complex multi-molecular structures that link the actin cytoskeleton to the extracellular matrix through integrin adhesion receptors and play a key role in regulation of many cellular functions. LAR (also known as PTPRF) is a receptor protein tyrosine phosphatase that regulates PDGF signalling and localises to focal adhesions. We have observed that loss of LAR phosphatase activity in mouse embryonic fibroblasts results in reduced numbers of focal adhesions and decreased adhesion to fibronectin. To understand how LAR regulates cell adhesion we used phosphoproteomic data, comparing global phosphorylation events in wild-type and LAR phosphatase-deficient cells, to analyse differential kinase activity. Kinase prediction analysis of LAR-regulated phosphosites identified a node of cytoskeleton- and adhesion-related proteins centred on cyclin-dependent kinase-1 (CDK1). We found that loss of LAR activity resulted in reduced activity of CDK1, and that CDK1 activity was required for LAR-mediated focal adhesion complex formation. We also established that LAR regulates CDK1 activity through c-Abl and Akt family proteins. In summary, we have identified a new role for a receptor protein tyrosine phosphatase in regulating CDK1 activity and hence cell adhesion to the extracellular matrix.
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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".