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Record W2789244789 · doi:10.1002/jlb.2mir0917-383r

On taking the STING out of immune activation

2018· review· en· W2789244789 on OpenAlexafffund
Andra Banete, Kyle Seaver, Devyani Bakshi, Katrina Gee, Sameh Basta

Bibliographic record

VenueJournal of Leukocyte Biology · 2018
Typereview
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsStingStimulator of interferon genesBiologyInterferonImmune systemIRF3Innate immune systemImmunologySignal transductionImmunityInterferon regulatory factorsInterferon type ITranscription factorSignal transducing adaptor proteinCytotoxic T cellIRF7Cell biologyCancer researchGeneGenetics

Abstract

fetched live from OpenAlex

Nearly a decade ago, an endoplasmic reticulum (ER) adaptor protein called stimulator of interferon genes (STING) was found to be critical in the induction of type I IFN production in response to DNA virus infection. STING functions by sensing cytoplasmic DNA and activates key transcription factors, including IFN regulatory factor (IRF)-3 and IRF7, to initiate type I IFN expression. Type I IFNs are vital in immunity against viral infections and can influence cancer cell proliferation, migration, and apoptosis. Several studies have shown that STING activation results in potent antitumor activity by generating strong tumor-specific cytotoxic T-cell responses. Moreover, compared with wild-type, STING-knockout mice show greater susceptibility to viral infections. In this review, we discuss the importance of STING signaling during the induction of immune responses, especially those associated with type I IFN in viral infections and tumor immunity. Furthermore, we highlight recent data that unravel how the STING signaling pathway can be negatively regulated.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.087
GPT teacher head0.372
Teacher spread0.286 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2018
Admission routes2
Has abstractyes

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