MétaCan
Menu
Back to cohort
Record W2109197060 · doi:10.1189/jlb.0907650

Antiviral NK cell responses in HIV infection: I. NK cell receptor genes as determinants of HIV resistance and progression to AIDS

2008· review· en· W2109197060 on OpenAlexafffund
Alexandre Iannello, Olfa Débbeche, Suzanne Samarani, Ali Ahmad

Bibliographic record

VenueJournal of Leukocyte Biology · 2008
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsBiologyMajor histocompatibility complexImmune systemMHC class IImmunologyInnate immune systemAntigenVirusVirologyReceptorGenetics

Abstract

fetched live from OpenAlex

NK cells play an important role in controlling viral infections. They can kill virus-infected cells directly as well as indirectly via antibody-dependent, cell-mediated cytotoxicity. They need no prior sensitization and expansion for this killing. NK cells are also considered as important regulators of antiviral immune responses. They do so by secreting a multitude of soluble mediators and by directly interacting with other immune cells, e.g., dendritic cells. NK cells do not possess a single well-defined receptor to recognize antigens on target cells. Instead, they express an array of inhibitory and activating receptors and coreceptors, which bind to their cognate ligands expressed on the surface of target cells. These ligands include classical and nonclassical MHC class I antigens, MHC-like proteins, and a variety of other self- and virus-derived molecules. They may be expressed constitutively and/or de novo on the surface of virus-infected cells. NK cell receptors (NKRs) of the killer-cell Ig-like receptor (KIR) family, like their MHC class I ligands, are highly polymorphic. Several recent studies suggest that epistatic interactions between certain KIR and MHC class I genes may determine innate resistance of the host to viral infections, including HIV. In the first part of this review article, we provide an overview of the current state of knowledge of NK cell immunobiology and describe how NKR genes, alone and in combination with HLA genes, may determine genetic resistance/susceptibilty to HIV infection and the development of AIDS in humans.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.026
GPT teacher head0.324
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations94
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Leukocyte BiologySame topicImmune Cell Function and InteractionFrench-language works237,207