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Record W2083120131 · doi:10.1586/erv.10.119

Effective control of viral infections by the adaptive immune system requires assistance from innate immunity

2010· letter· en· W2083120131 on OpenAlexaff
Nicole G. Barra, Amy Gillgrass, Ali A. Ashkar

Bibliographic record

VenueExpert Review of Vaccines · 2010
Typeletter
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInnate immune systemAcquired immune systemIntrinsic immunityLymphocytic choriomeningitisBiologyVirologyImmunityImmune systemImmunologyViral replicationVirusAdoptive cell transferT cellCD8

Abstract

fetched live from OpenAlex

Evaluation of: Nakayama Y, Plisch EH, Sullivan JM et al. Role of PKR and type I IFNs in viral control during primary and secondary infection. PLoS Pathog. 6(6), e1000966 (2010). During acute viral infections, innate antiviral immunity has been extensively studied for its ability to inhibit and/or control viral replication while priming the adaptive immune system. Recently, these processes have been studied for their role in assisting adaptive immunity to effectively clear or control viral rechallenge. The paper under evaluation introduces the concept that functional innate immune mechanisms such as dsRNA-activated protein kinase (PKR) and type I interferons are critical in controlling viral replication during secondary lymphocyte choriomeningitis virus infection. Elegant adoptive transfer studies revealed that during lymphocyte choriomeningitis virus secondary infections, dependence of viral control relied on expression of these innate factors in virally infected cells and not in adaptive immune T cells. Such findings illustrate that functional adaptive responses are less effective in providing protection against reinfections in the absence of innate mechanisms. This demonstrates the importance of intact innate mechanisms when considering effective vaccine strategies.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.715
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.254
Teacher spread0.246 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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