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Record W4386209319 · doi:10.1093/infdis/jiad345

AAV-Vectored Expression of Marburg Virus–Neutralizing Antibody MR191 Provides Complete Protection From Challenge in a Guinea Pig Model

2023· article· en· W4386209319 on OpenAlexafffund
Amira D. Rghei, Wenguang Cao, Shihua He, Jordyn A. Lopes, Nicole Zielinska, Yanlong Pei, Brad Thompson, Logan Banadyga, Sarah K. Wootton

Bibliographic record

VenueThe Journal of Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsCanada Energy RegulatorUniversity of ManitobaPublic Health Agency of CanadaUniversity of Guelph
FundersCanadian Institutes of Health ResearchPublic Health Agency of Canada
KeywordsVirologyMarburg virusGuinea pigNeutralizing antibodyAntibodyVirusBiologyMedicineImmunologyEbola virusInternal medicine

Abstract

fetched live from OpenAlex

Although there are no approved countermeasures available to prevent or treat disease caused by Marburg virus (MARV), potently neutralizing monoclonal antibodies (mAbs) derived from B cells of human survivors have been identified. One such mAb, MR191, has been shown to provide complete protection against MARV in nonhuman primates. We previously demonstrated that prophylactic administration of an adeno-associated virus (AAV) expressing MR191 protected mice from MARV. Here, we modified the AAV-MR191 coding sequence to enhance efficacy and reevaluated protection in a guinea pig model. Remarkably, 4 different variants of AAV-MR191 provided complete protection against MARV, despite administration 90 days prior to challenge. Based on superior expression kinetics, AAV-MR191-io2, was selected for evaluation in a dose-reduction experiment. The highest dose provided 100% protection, while a lower dose provided ∼88% protection. These data confirm the efficacy of AAV-mediated expression of MR191 and support the further development of this promising MARV countermeasure.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.061
GPT teacher head0.345
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2023
Admission routes2
Has abstractyes

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