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Record W2163586656 · doi:10.1586/14760584.2013.814871

Type I interferon regulation of natural killer cell function in primary and secondary infections

2013· review· en· W2163586656 on OpenAlexafffund
Michele L Stackaruk, Amanda J. Lee, Ali A. Ashkar

Bibliographic record

VenueExpert Review of Vaccines · 2013
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsImmunologyInterferonPriming (agriculture)BiologyInnate immune systemImmune systemInterleukin 21Interleukin 12Cell typeCellT cellCytotoxic T cellIn vitro

Abstract

fetched live from OpenAlex

The priming of natural killer (NK) cells by type I interferon (IFN) is necessary for protection against primary and secondary viral infections. However, the pathway by which type I IFN activates NK cells to elicit antiviral responses is controversial. There is evidence to suggest that type I IFN priming of NK cells occurs through both direct and indirect pathways. As with many innate mechanisms, type I IFN and NK cells also orchestrate the adaptive immune response and thus aid in protection against secondary infections. Type I IFN can shape CD4(+) T cell, B cell and humoral memory formation. In addition, long-lived NK cells can perform specific and enhanced memory-like protection in secondary infections. This review outlines the different mechanisms underlying type I IFN regulation of NK cells and how type I IFN and NK cells can be used as a therapeutic target in vaccinations.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.881
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.015
GPT teacher head0.287
Teacher spread0.272 · 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

Citations20
Published2013
Admission routes2
Has abstractyes

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