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Record W2071006115 · doi:10.1182/blood-2012-02-412593

MHC I–associated peptides preferentially derive from transcripts bearing miRNA response elements

2012· article· en· W2071006115 on OpenAlexafffund
Diana Paola Granados, Wafaa Yahyaoui, Céline M. Laumont, Tariq Daouda, Tara L. Muratore‐Schroeder, Caroline Côté, Jean‐Philippe Laverdure, Sébastien Lemieux, Pierre Thibault, Claude Perreault

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health ResearchCanada Research ChairsPfizer
KeywordsBiologyTranscriptomemicroRNABiogenesisMajor histocompatibility complexHuman leukocyte antigenComputational biologyCell biologyGeneGeneticsGene expressionAntigen

Abstract

fetched live from OpenAlex

MHC I-associated peptides (MIPs) play an essential role in normal homeostasis and diverse pathologic conditions. MIPs derive mainly from defective ribosomal products (DRiPs), a subset of nascent proteins that fail to achieve a proper conformation and the physical nature of which remains elusive. In the present study, we used high-throughput proteomic and transcriptomic methods to unravel the structure and biogenesis of MIPs presented by HLA-A and HLA-B molecules on human EBV-infected B lymphocytes from 4 patients. We found that although HLA-different subjects present distinctive MIPs derived from different proteins, these MIPs originate from proteins that are functionally interconnected and implicated in similar biologic pathways. Secondly, the MIP repertoire of human B cells showed no bias toward conserved versus polymorphic genomic sequences, were derived preferentially from abundant transcripts, and conveyed to the cell surface a cell-type-specific signature. Finally, we discovered that MIPs derive preferentially from transcripts bearing miRNA response elements. Furthermore, whereas MIPs of HLA-disparate subjects are coded by different sets of transcripts, these transcripts are regulated by mostly similar miRNAs. Our data support an emerging model in which the generation of MIPs by a transcript depends on its abundance and DRiP rate, which is regulated to a large extent by miRNAs.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.310
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.238
Teacher spread0.218 · 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.

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

Citations67
Published2012
Admission routes2
Has abstractyes

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