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Record W2036148042 · doi:10.1074/jbc.m600897200

PTP-PEST Couples Membrane Protrusion and Tail Retraction via VAV2 and p190RhoGAP

2006· article· en· W2036148042 on OpenAlexafffund
Sarita K. Sastry, Zenon Rajfur, Betty P. Liu, Jean‐François Côté, Michel L. Tremblay, Keith Burridge

Bibliographic record

VenueJournal of Biological Chemistry · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsMcGill UniversityMontreal Clinical Research Institute
FundersNational Institute of General Medical SciencesNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsRHOACell biologyRAC1CDC42BiologyMotilityGTPaseSignal transduction

Abstract

fetched live from OpenAlex

Cell motility is regulated by a balance between forward protrusion and tail retraction. These phenomena are controlled by a spatial asymmetry in signals at the front and the back of the cell. We show here that the protein-tyrosine phosphatase, PTP-PEST, is required for the coupling of protrusion and retraction during cell migration. PTP-PEST null fibroblasts, which are blocked in migration, exhibit exaggerated protrusions at the leading edge and long, unretracted tails in the rear. This altered morphology is accompanied by changes in the activity of Rho GTPases, Rac1 and RhoA, which mediate protrusion and retraction, respectively. PTP-PEST null cells exhibit enhanced Rac1 activity and decreased RhoA activity. We further show that PTP-PEST directly targets the upstream regulators of Rac1 and RhoA, VAV2 and p190RhoGAP. Moreover, we demonstrate that the activities of VAV2 and p190RhoGAP are regulated by PTP-PEST. Finally, we present evidence indicating the VAV2 can be regulated by integrin-mediated adhesion. These data suggest that PTP-PEST couples protrusion and retraction by acting on VAV2 and p190RhoGAP to reciprocally modulate the activity of Rac1 and RhoA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.226
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations67
Published2006
Admission routes2
Has abstractyes

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