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Record W2965360666 · doi:10.3390/v11080688

Probing Morbillivirus Antisera Neutralization Using Functional Chimerism between Measles Virus and Canine Distemper Virus Envelope Glycoproteins

2019· article· en· W2965360666 on OpenAlexfundno aff
Miguel Ángel Muñoz-Alía, Stephen J. Russell

Bibliographic record

VenueViruses · 2019
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsnot available
FundersDalhousie UniversityMayo Clinic
KeywordsCanine distemperMeasles virusVirologyMorbillivirusBiologyVirusNeutralizationNeutralizing antibodyGlycoproteinAntiserumMononegaviralesParamyxoviridaeAntibodyMeaslesMolecular biologyVaccinationViral diseaseImmunology

Abstract

fetched live from OpenAlex

Measles virus (MeV) is monotypic. Live virus challenge provokes a broadly protective humoral immune response that neutralizes all known measles genotypes. The two surface glycoproteins, H and F, mediate virus attachment and entry, respectively, and neutralizing antibodies to H are considered the main correlate of protection. Herein, we made improvements to the MeV reverse genetics system and generated a panel of recombinant MeVs in which the globular head domain or stalk region of the H glycoprotein or the entire F protein, or both, were substituted with the corresponding protein domains from canine distemper virus (CDV), a closely related morbillivirus that resists neutralization by measles-immune sera. The viruses were tested for sensitivity to human or guinea pig neutralizing anti-MeV antisera and to ferret anti-CDV antisera. Virus neutralization was mediated by antibodies to both H and F proteins, with H being immunodominant in the case of MeV and F being so in the case of CDV. Additionally, the globular head domains of both MeV and CDV H proteins were immunodominant over their stalk regions. These data shed further light on the factors constraining the evolution of new morbillivirus serotypes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

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)0.0010.000

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 head0.055
GPT teacher head0.291
Teacher spread0.236 · 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 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

Citations20
Published2019
Admission routes1
Has abstractyes

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