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Record W3107417040 · doi:10.3389/fimmu.2020.606456

Type I Interferon (IFN)-Regulated Activation of Canonical and Non-Canonical Signaling Pathways

2020· review· en· W3107417040 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Immunology · 2020
Typereview
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
FundersNational Cancer InstituteNational Institutes of Health
KeywordsSignal transductionBiologyJAK-STAT signaling pathwaystatInterferonTranscription factorTranscription (linguistics)Translation (biology)Computational biologyNon canonicalCell biologyGeneGeneticsMessenger RNASTAT3Tyrosine kinase

Abstract

fetched live from OpenAlex

For several decades there has been accumulating evidence implicating type I interferons (IFNs) as key elements of the immune response. Therapeutic approaches incorporating different recombinant type I IFN proteins have been successfully employed to treat a diverse group of diseases with significant and positive outcomes. The biological activities of type I IFNs are consequences of signaling events occurring in the cytoplasm and nucleus of cells. Biochemical events involving JAK/STAT proteins that control transcriptional activation of IFN-stimulated genes (ISGs) were the first to be identified and are referred to as "canonical" signaling. Subsequent identification of JAK/STAT-independent signaling pathways, critical for ISG transcription and/or mRNA translation, are denoted as "non-canonical" or "non-classical" pathways. In this review, we summarize these signaling cascades and discuss recent developments in the field, specifically as they relate to the biological and clinical implications of engagement of both canonical and non-canonical pathways.

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.

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 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 score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.039
GPT teacher head0.303
Teacher spread0.264 · 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