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Record W2118519438 · doi:10.1099/vir.0.006833-0

Alpha interferon as an adenovirus-vectored vaccine adjuvant and antiviral in Venezuelan equine encephalitis virus infection

2009· article· en· W2118519438 on OpenAlexaff
Lyn M. O’Brien, Stuart D. Perkins, Amanda Williams, Lin Eastaugh, Amanda Phelps, Josh Wu, R.J. Phillpotts

Bibliographic record

VenueJournal of General Virology · 2009
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsVirologyVenezuelan equine encephalitis virusBiologyAlphavirusAdjuvantVirusInterferonAntibodyImmune systemViral vectorEncephalitisAdenoviridaeAlpha interferonImmunologyRecombinant DNA

Abstract

fetched live from OpenAlex

There are no widely available vaccines or antiviral drugs capable of protecting against infection with Venezuelan equine encephalitis virus (VEEV), although an adenovirus vector expressing VEEV structural proteins protects mice from challenge with VEEV and is potentially a vaccine suitable for human use. This work examines whether alpha interferon (IFN-alpha) could act as an adjuvant for the adenovirus-based vaccine. IFN-alpha was either expressed by a plasmid linked to the adenovirus vaccine or encoded by a separate adenovirus vector administered as a mixture with the vaccine. In contrast to previous reports with other vaccines, the presence of IFN-alpha reduced the antibody response to VEEV. When IFN-alpha was encoded by adenovirus, the lack of a VEEV-specific response was accompanied by an increase in the immune response to the adenovirus vector. IFN-alpha also plays a direct role in defence against virus infection, inducing the expression of a large number of antiviral proteins. Adenovirus-delivered IFN-alpha protected mice from VEEV disease when administered 24 h prior to challenge, but not when administered 6 h post-challenge, suggesting that up to 24 h is required for the development of the IFN-mediated antiviral response.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.613

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)0.0000.000

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 head0.010
GPT teacher head0.300
Teacher spread0.291 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations34
Published2009
Admission routes1
Has abstractyes

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