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Record W2989621866 · doi:10.3389/fmicb.2019.02627

A Tug of War: DNA-Sensing Antiviral Innate Immunity and Herpes Simplex Virus Type I Infection

2019· review· en· W2989621866 on OpenAlexaff
Yingying Lin, Chunfu Zheng

Bibliographic record

VenueFrontiers in Microbiology · 2019
Typereview
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsUniversity of Calgary
FundersFujian Medical UniversityNatural Science Foundation of Fujian ProvinceNational Natural Science Foundation of China
KeywordsInnate immune systemHerpes simplex virusImmune systemBiologyPattern recognition receptorVirologyVirusImmunologyInterferonImmunityDNA virusGeneGeneticsGenome

Abstract

fetched live from OpenAlex

Cytosolic DNA sensors are the most recently described class of pattern recognition receptors (PRRs), which induce the production of type I interferons (IFN-I) and trigger the induction of a rapid and efficient innate immune response. Herpes simplex virus type I (HSV-1), a typical DNA virus, has displayed the ability to manipulate and evade host antiviral innate immune responses. Therefore, with an aim to highlight IFN-I-mediated innate immune response in a battle against viral infection, we have summarized the current understandings of DNA-sensing signal pathways and the most recent findings on the molecular mechanisms utilized by HSV-1 to counteract antiviral immune responses. A comprehensive understanding of the interplay between HSV-1 and host early antiviral immune responses will contribute to the development of novel therapies and vaccines in the future.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.034
GPT teacher head0.324
Teacher spread0.290 · 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 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

Citations52
Published2019
Admission routes1
Has abstractyes

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