Paxillin phosphorylation at Ser273 localizes a GIT1–PIX–PAK complex and regulates adhesion and protrusion dynamics
Bibliographic record
Abstract
Continuous adhesion formation and disassembly (adhesion turnover) in the protrusions of migrating cells is regulated by unclear mechanisms. We show that p21-activated kinase (PAK)-induced phosphorylation of serine 273 in paxillin is a critical regulator of this turnover. Paxillin-S273 phosphorylation dramatically increases migration, protrusion, and adhesion turnover by increasing paxillin-GIT1 binding and promoting the localization of a GIT1-PIX-PAK signaling module near the leading edge. Mutants that interfere with the formation of this ternary module abrogate the effects of paxillin-S273 phosphorylation. PAK-dependent paxillin-S273 phosphorylation functions in a positive-feedback loop, as active PAK, active Rac, and myosin II activity are all downstream effectors of this turnover pathway. Finally, our studies led us to identify in highly motile cells a class of small adhesions that reside near the leading edge, turnover in 20-30 s, and resemble those seen with paxillin-S273 phosphorylation. These adhesions appear to be regulated by the GIT1-PIX-PAK module near the leading edge.
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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".