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Record W2137698660 · doi:10.1182/blood-2004-08-3156

A subset of natural killer cells achieves self-tolerance without expressing inhibitory receptors specific for self-MHC molecules

2005· article· en· W2137698660 on OpenAlexaff
Nadine Fernandez, Emmanuel Treiner, Russell E. Vance, A. M. Jamieson, Suzanne Lemieux, David H. Raulet

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Institute of Allergy and Infectious Diseases
KeywordsBiologyMajor histocompatibility complexCell biologyCD1MHC class IReceptorSelf ToleranceNatural killer cellNatural killer T cellInterleukin 12Cytotoxic T cellJanus kinase 3ImmunologyImmune systemT cellIn vitroBiochemistry

Abstract

fetched live from OpenAlex

It is widely believed that self-tolerance of natural killer (NK) cells occurs because each NK cell expresses at least one inhibitory receptor specific for a host major histocompatibility complex (MHC) class I molecule. Here we report that some NK cells lack all known self-MHC-specific inhibitory receptors, yet are nevertheless self-tolerant. These NK cells exhibit a normal cell surface phenotype and some functional activity. However, they respond poorly to class I-deficient normal cells, tumor cells, or cross-linking of stimulatory receptors, suggesting that self-tolerance is established by dampening stimulatory signaling. Thus, self-tolerance of NK cells in normal animals can occur independently of MHC-mediated inhibition, and hyporesponsiveness plays a role in self-tolerance of NK cells, as also proposed for B and T cells.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations561
Published2005
Admission routes1
Has abstractyes

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