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The Wiskott–Aldrich syndrome protein: forging the link between actin and cell activation

2003· review· en· W1982128760 on OpenAlexaff
Karen Badour, Jinyi Zhang, Katherine A. Siminovitch

Bibliographic record

VenueImmunological Reviews · 2003
Typereview
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsWiskott–Aldrich syndrome proteinBiologyCell biologyCytoskeletonActinT-cell receptorActin cytoskeletonWiskott–Aldrich syndromeSignal transductionEffectorActin remodelingT cellImmunologyCellGeneticsImmune systemGene

Abstract

fetched live from OpenAlex

The Wiskott-Aldrich syndrome protein (WASp) has emerged as a central player in the regulation of actin remodeling in T cells. The unique domain structure of WASp and other WASp family members enables these proteins to associate with a myriad of signaling effectors and to thereby regulate the coupling of T cell antigen receptor (TCR) engagement to both cytoskeletal rearrangement and transcriptional activation. This review focuses on these biochemical properties of WASp and also on the mechanisms whereby WASp interactions with its cognate ligands influence T cell activation. Because of its capacity to shift intracellular location and thereby dictate both the timing and the spatial distribution of actin polymerization following cell stimulation, WASp is well positioned to play major regulatory roles in directing a wide range of cellular processes and signaling pathways. Further dissection of the functional and biochemical properties of WASp therefore represents a promising avenue towards defining the molecular mechanisms that convey TCR stimulatory signals to the actin cytoskeleton and integrate cytoskeletal and other signaling systems so as to evoke a biological response.

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: 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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.127
GPT teacher head0.390
Teacher spread0.262 · 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

Citations79
Published2003
Admission routes1
Has abstractyes

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