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Record W2144656400 · doi:10.1083/jcb.200705122

Rac1 and Rac2 differentially regulate actin free barbed end formation downstream of the fMLP receptor

2007· article· en· W2144656400 on OpenAlexaff
Chun Xiang Sun, Marco Magalhaes, Michael Glogauer

Bibliographic record

VenueThe Journal of Cell Biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of TorontoCanadian Institutes of Health Research
Fundersnot available
KeywordsCell biologyCofilinBiologyActinRAC1GTPaseActin cytoskeletonRac GTP-Binding ProteinsCytoskeletonSignal transductionBiochemistryCell

Abstract

fetched live from OpenAlex

Actin assembly at the leading edge of migrating cells depends on the availability of high-affinity free barbed ends (FBE) that drive actin filament elongation and subsequent membrane protrusion. We investigated the specific mechanisms through which the Rac1 and Rac2 small guanosine triphosphatases (GTPases) generate free barbed ends in neutrophils. Using neutrophils lacking either Rac1 or Rac2 and a neutrophil permeabilization model that maintains receptor signaling to the actin cytoskeleton, we assessed the mechanisms through which these two small GTPases mediate FBE generation downstream of the formyl-methionyl-leucyl-phenylalanine receptor. We demonstrate here that uncapping of existing barbed ends is mediated through Rac1, whereas cofilin- and ARP2/3-mediated FBE generation are regulated through Rac2. This unique combination of experimental tools has allowed us to identify the relative roles of uncapping (15%), cofilin severing (10%), and ARP2/3 de novo nucleation (75%) in FBE generation and the respective roles played by Rac1 and Rac2 in mediating actin dynamics.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), 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

Citations119
Published2007
Admission routes1
Has abstractyes

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