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Record W2025080754 · doi:10.1002/eji.200323351

Signaling through HLA‐DR induces PKCβ‐dependent B cell death outside rafts

2003· article· en· W2025080754 on OpenAlexaff
Wenyan Guo, Jean‐Gabriel Castaigne, Nuala Mooney, Dominique Charron, Reem Al‐Daccak

Bibliographic record

VenueEuropean Journal of Immunology · 2003
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsCentre hospitalier de l'Université LavalUniversité Laval
Fundersnot available
KeywordsCell biologyLYNLipid raftProgrammed cell deathProtein kinase CBiologySignal transductionProto-oncogene tyrosine-protein kinase SrcApoptosisGenetics

Abstract

fetched live from OpenAlex

Signals through HLA-DR molecules contribute to optimal activation of antigen-presenting cells (APC) during T cell/APC interactions participating in the generation of productive interactions, and to the induction of APC death, which has been postulated to play a role in the termination of the immune response. To understand how these molecules accommodate both cellular responses, we studied the not yet well-defined signaling events and the biochemical requirements for HLA-DR-mediated death. We demonstrate that in B cells the HLA-DR-activated protein kinase C (PKC) beta is required for HLA-DR-mediated death whereas the HLA-DR-activated Src family of PTK is redundant. In contrast to HLA-DR-mediated activation of Src kinase Lyn, the aggregation of HLA-DR molecules in lipid rafts is not required for HLA-DR-mediated PKC beta activation nor for the induction of cell death. Indeed, the bulk of HLA-DR-activated PKC beta reside outside rafts. This is the first report showing that HLA-DR-induced PKC beta activation is essential for the induction of B cell death via HLA-DR, and that these HLA-DR-mediated events do not require the integrity of rafts.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.003

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 head0.024
GPT teacher head0.231
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

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

Citations26
Published2003
Admission routes1
Has abstractyes

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