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Baculovirus Expression and Antigenic Characterization of Classical Swine Fever Virus E2 Proteins

2012· article· en· W2153517972 on OpenAlexafffund
Lizhong Luo, Krista Nishi, Erin MacLeod, Marta Sabara, Min Lin, K. Handel, John Pasick

Bibliographic record

VenueTransboundary and Emerging Diseases · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsCanadian Science Centre for Human and Animal Health
FundersAgriculture Funding Consortium
KeywordsMonoclonal antibodyPolyclonal antibodiesVirologyAntigenBiologyAntibodyAntiserumMolecular biologyGlycoproteinEpitopeWestern blotClassical swine feverVirusRecombinant DNAGeneImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Genes encoding a major structural glycoprotein, E2, of classical swine fever viruses (CSFV) Brescia (subgroup 1.2), Paderborn (subgroup 2.1) and Kanagawa (subgroup 3.4) were constructed by removing the transmembrane domain and adding a C-terminal 6 histidine (His) tag. All the E2 constructs were efficiently expressed in a baculovirus system as 53-kDa glycosylated proteins that were identified in Western blots by their reaction with anti-His and CSFV-specific antibodies. These proteins were used as ELISA antigens to confirm the existence of an antigenic relationship between the viruses using group-specific polyclonal antisera. Antigenic differences were identified by Western blot and ELISA reactivity of the E2 proteins with a panel of monoclonal antibodies. Specifically, one monoclonal antibody (WH303) reacted with all three proteins, two monoclonal antibodies (M1660 and M1665) reacted with only the Brescia E2 protein, and three monoclonal antibodies (M1654, M1664 and M1669) reacted equally well with only Brescia and Kanagawa E2 proteins. Therefore, antibody reactivity profiles, established using recombinant E2 proteins, could be used to quickly identify novel CSFV strains as illustrated in this report with only a limited number of monoclonal antibodies. These proteins could also have added utility in the production of monoclonal antibodies and as critical reagents in diagnostic assays.

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 score0.825
Threshold uncertainty score0.403

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 integrity0.0000.000
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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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

Citations13
Published2012
Admission routes2
Has abstractyes

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