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Record W2243106965 · doi:10.4049/jimmunol.1501222

Antigen Specificity of Type I NKT Cells Is Governed by TCR β-Chain Diversity

2015· article· en· W2243106965 on OpenAlexaff
Garth Cameron, Daniel G. Pellicci, Adam P. Uldrich, Gurdyal S. Besra, Petr A. Illarionov, Spencer J. Williams, Nicole L. La Gruta, Jamie Rossjohn, Dale I. Godfrey

Bibliographic record

VenueThe Journal of Immunology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsT-cell receptorCD1DNatural killer T cellAntigenBiologyGlycolipidT cellMolecular biologyCell biologyChemistryImmunologyImmune system

Abstract

fetched live from OpenAlex

NKT cells recognize lipid-based Ags presented by CD1d. Type I NKT cells are often referred to as invariant owing to their mostly invariant TCR α-chain usage (Vα14-Jα18 in mice, Vα24-Jα18 in humans). However, these cells have diverse TCR β-chains, including Vβ8, Vβ7, and Vβ2 in mice and Vβ11 in humans, joined to a range of TCR Dβ and Jβ genes. In this study, we demonstrate that TCR β-chain composition can dramatically influence lipid Ag recognition in an Ag-dependent manner. Namely, the glycolipids α-glucosylceramide and isoglobotrihexosylceramide were preferentially recognized by Vβ7(+) NKT cells from mice, whereas the α-galactosylceramide analog OCH, with a truncated sphingosine chain, was preferentially recognized by Vβ8(+) NKT cells from mice. We show that the influence of the TCR β-chain is due to a combination of Vβ-, Jβ-, and CDR3β-encoded residues and that these TCRs can recapitulate the selective Ag reactivity in TCR-transduced cell lines. Similar observations were made with human NKT cells where different CDR3β-encoded residues determined Ag preference. These findings indicate that NKT TCR β-chain diversity results in differential and nonhierarchical Ag recognition by these cells, which implies that some Ags can preferentially activate type I NKT cell subsets.

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 categoriesInsufficient 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 score0.039
Threshold uncertainty score0.999

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.225
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.

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

Citations37
Published2015
Admission routes1
Has abstractyes

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