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Record W2256564896 · doi:10.1083/jcb.201504137

Dynamics of the actin cytoskeleton mediates receptor cross talk: An emerging concept in tuning receptor signaling

2016· review· en· W2256564896 on OpenAlexafffund
Pieta K. Mattila, Facundo D. Batista, Bebhinn Treanor

Bibliographic record

VenueThe Journal of Cell Biology · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchAcademy of FinlandNatural Sciences and Engineering Research Council of CanadaCancer Research UK
KeywordsActin cytoskeletonCell biologyBiologyCytoskeletonReceptorSignal transductionCellGenetics

Abstract

fetched live from OpenAlex

Recent evidence implicates the actin cytoskeleton in the control of receptor signaling. This may be of particular importance in the context of immune receptors, such as the B cell receptor, where dysregulated signaling can result in autoimmunity and malignancy. Here, we discuss the role of the actin cytoskeleton in controlling receptor compartmentalization, dynamics, and clustering as a means to regulate receptor signaling through controlling the interactions with protein partners. We propose that the actin cytoskeleton is a point of integration for receptor cross talk through modulation of protein dynamics and clustering. We discuss the implication of this cross talk via the cytoskeleton for both ligand-induced and low-level constitutive (tonic) signaling necessary for immune cell survival.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.019
GPT teacher head0.321
Teacher spread0.302 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations143
Published2016
Admission routes2
Has abstractyes

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