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Record W2114353148 · doi:10.4049/jimmunol.172.12.7548

Bap29/31 Influences the Intracellular Traffic of MHC Class I Molecules

2004· article· en· W2114353148 on OpenAlexaff
Marie-Ève Paquet, Myrna F. Cohen-Doyle, Gordon C. Shore, David B. Williams

Bibliographic record

VenueThe Journal of Immunology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsMHC class IEndoplasmic reticulumTransporter associated with antigen processingColocalizationCell biologyCD74Golgi apparatusBeta-2 microglobulinBiologyMajor histocompatibility complexReceptorIntracellularC-C chemokine receptor type 7CalnexinChemistryBiochemistryGeneChemokine receptorImmunologyChemokine

Abstract

fetched live from OpenAlex

In this study, we examine the role of the putative cargo receptor B cell-associated protein (Bap)29/31 in the export of MHC class I molecules out of the endoplasmic reticulum (ER). We show that Bap31 binds to two allotypes of mouse class I molecules, with the interaction initiated at the time of H chain association with beta(2)-microglobulin and maintained until the class I molecule has left the ER. We also show that Bap31 is part of the peptide-loading complex, although is not required for its formation. Bap31 binds not only to class I molecules, but can bind to tapasin in the absence of class I. Consistent with an important role in recruiting class I molecules to transport vesicles, we show that in the absence of Bap29/31, there is a loss of class I colocalization with mSec31 (p137), a component of mammalian coat protein complex II coats. This observation is also associated with a delay in class I traffic from ER to Golgi. Our results are consistent with the view that class I molecules are largely recruited to ER exit sites by Bap29/31, and that Bap29/31 is a cargo receptor for MHC class I molecules.

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)0.000
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 score0.020
Threshold uncertainty score0.231

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.210
Teacher spread0.203 · 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

Citations95
Published2004
Admission routes1
Has abstractyes

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