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Record W1524049020 · doi:10.4049/jimmunol.178.1.235

Functional Polymorphism of the KIR3DL1/S1 Receptor on Human NK Cells

2007· article· en· W1524049020 on OpenAlexaff
Geraldine M. O’Connor, Kieran J. Guinan, Rodat T. Cunningham, Derek Middleton, Peter Parham, Clair M. Gardiner

Bibliographic record

VenueThe Journal of Immunology · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsTrinity College
Fundersnot available
KeywordsReceptorBiologyAlleleHuman leukocyte antigenCell biologyEpitopeImmunologyMolecular biologyGeneticsGeneAntibodyAntigen

Abstract

fetched live from OpenAlex

NK cells express both inhibitory and activatory receptors that allow them to recognize target cells through HLA class I Ag expression. KIR3DL1 is a receptor that recognizes the HLA-Bw4 public epitope of HLA-B alleles. We demonstrate that polymorphism within the KIR3DL1 receptor has functional consequences in terms of NK cell recognition of target. Inhibitory alleles of KIR3DL1 differ in their ability to recognize HLA-Bw4 ligand, and a consistent hierarchy of ligand reactivity can be defined. KIR3DS1, which segregates as an allele of KIR3DL1, has a short cytoplasmic tail characteristic of activatory receptors. Because it is very similar to KIR3DL1 in the extracellular domains, it has been assumed that KIR3DS1 will recognize a HLA-Bw4 ligand. In this study, we demonstrate that KIR3DS1 is expressed as a protein at the cell surface of NK cells, where it is recognized by the Z27 Ab. Using this Ab, we found that KIR3DS1 is expressed on a higher percentage of NK cells in KIR3DS1 homozygous compared with heterozygous donors. In contrast to the inhibitory KIR3DL1 allotypes, KIR3DS1 did not recognize HLA-Bw4 on EBV-transformed cell lines.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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)0.0030.001

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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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 designObservational
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

Citations161
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of ImmunologySame topicImmune Cell Function and InteractionFrench-language works237,207