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Record W2100872495 · doi:10.1186/1743-422x-7-41

Antibody dependent enhancement of frog virus 3 infection

2010· article· en· W2100872495 on OpenAlexafffund
Heather E. Eaton, Emily Penny, Craig R. Brunetti

Bibliographic record

VenueVirology Journal · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyVirologyAntibodyVirusAntibody-dependent enhancementImmunologyViral replication

Abstract

fetched live from OpenAlex

BACKGROUND: Viruses included in the family Iridoviridae are large, icosahedral, dsDNA viruses that are subdivided into 5 genera. Frog virus 3 (FV3) is the type species of the genus Ranavirus and the best studied iridovirus at the molecular level. Typically, antibodies directed against a virus act to neutralize the virus and limit infection. Antibody dependent enhancement occurs when viral antibodies enhance infectivity of the virus rather than neutralize it. RESULTS: Here we show that anti-FV3 serum present at the time of FV3 infection enhances infectivity of the virus in two non-immune teleost cell lines. We found that antibody dependent enhancement of FV3 was dependent on the Fc portion of anti-FV3 antibodies but not related to complement. Furthermore, the presence of anti-FV3 serum during an FV3 infection in a non-immune mammalian cell line resulted in neutralization of the virus. Our results suggest that a cell surface receptor specific to teleost cell lines is responsible for the enhancement. CONCLUSIONS: This report represents the first evidence of antibody dependent enhancement in iridoviruses. The data suggests that anti-FV3 serum can either neutralize or enhance viral infection and that enhancement is related to a novel antibody dependent enhancement pathway found in teleosts that is Fc dependent.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.251
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 designBench or experimental
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

Citations6
Published2010
Admission routes2
Has abstractyes

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