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Record W2159751093 · doi:10.1084/jem.20050449

Regulation of natural cytotoxicity by the adaptor SAP and the Src-related kinase Fyn

2005· article· en· W2159751093 on OpenAlexaff
Coralie Bloch‐Queyrat, Marie‐Claude Fondanèche, Riyan Chen, Francis Relouzat, André Veillette, Alain Fischer, Sylvain Latour

Bibliographic record

VenueThe Journal of Experimental Medicine · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMontreal Clinical Research Institute
Fundersnot available
KeywordsFYNCytotoxicityCell biologyBiologyTyrosine kinaseReceptorSignal transducing adaptor proteinCancer researchPhosphorylationSignal transductionIn vitroBiochemistry

Abstract

fetched live from OpenAlex

SAP is an adaptor protein that is expressed in NK and T cells. It is mutated in humans who have X-linked lymphoproliferative (XLP) disease. By interacting with SLAM family receptors, SAP enables tyrosine phosphorylation signaling of these receptors by its ability to recruit the Src-related kinase, Fyn. Here, we analyzed the role of SAP in NK cell functions using the SAP-deficient mouse model. Our results showed that SAP was required for the ability of NK cells to eliminate tumor cells in vitro and in vivo. This effect strongly correlated with expression of CD48 on tumor cells, the ligand of 2B4, a SLAM-related receptor expressed in NK cells. In keeping with earlier reports that studied human NK cells, we showed that SAP was necessary for the ability of 2B4 to trigger cytotoxicity and IFN-gamma secretion. In the absence of SAP, 2B4 function was shifted toward inhibition of NK cell-mediated cytotoxicity. By analyzing mice lacking Fyn, we showed that similarly to SAP, Fyn was strictly required for 2B4 function. Taken together, these results provide evidence that the 2B4-SAP-Fyn cascade defines a potent activating pathway of natural cytotoxicity. They also could help to explain the high propensity of patients who have XLP disease to develop lymphoproliferative disorders.

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)0.001
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 score0.052
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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

Citations118
Published2005
Admission routes1
Has abstractyes

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