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Record W2167984750 · doi:10.1128/cdli.8.3.475-481.2001

Development of an Immunoglobulin M (IgM) Capture Enzyme-Linked Immunosorbent Assay for Detection of Equine and Swine IgM Antibodies to Vesicular Stomatitis Virus

2001· article· en· W2167984750 on OpenAlexaff
En‐Min Zhou, J. Riva, Alfonso Clavijo

Bibliographic record

VenueClinical and Diagnostic Laboratory Immunology · 2001
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and Retrovirus Studies
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsAntibodyVirologyVesicular stomatitis virusImmunoglobulin MVesicular StomatitisImmunoglobulin GStomatitisVirusBiologyImmunologyMedicine

Abstract

fetched live from OpenAlex

An immunoglobulin M (IgM) capture enzyme-linked immunosorbent assay (MC-ELISA) was developed for the detection of primary infection of vesicular stomatitis virus (VSV) in equine and swine sera. The test was based on the use of biotinylated sheep antibodies against equine or swine IgM molecules bound to a streptavidin-coated ELISA plate. The captured IgM antibodies were detected by application of antigens prepared from the New Jersey and the Indiana VSV serotypes (VSV-NJ and VSV-IN, respectively) and mouse polyclonal antibodies against VSV-NJ and VSV-IN. The MC-ELISA was compared to a competitive ELISA (C-ELISA) and the standard microtiter serum neutralization (MTSN) assay by testing serum samples from horses and pigs experimentally infected with VSV-NJ or VSV-IN. The MC-ELISA detected specific homologous IgM antibodies from equine and swine sera as early as 5 and 4 days postinfection (DPI), respectively, and as late as 35 DPI. The MTSN test also detected antibodies as early as 5 DPI and as late as 160 DPI. In a similar fashion, the C-ELISA detected antibodies from 6 to 7 DPI and as late as 160 DPI. These results demonstrated that the MC-ELISA is a useful test for serodiagnosis of primary VSV infection in horses and pigs.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.423
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.287
Teacher spread0.268 · 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

Citations12
Published2001
Admission routes1
Has abstractyes

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