Single Immunization With a Monovalent Vesicular Stomatitis Virus–Based Vaccine Protects Nonhuman Primates Against Heterologous Challenge With Bundibugyo ebolavirus
Bibliographic record
Abstract
The recombinant vesicular stomatitis virus (rVSV) vector-based monovalent vaccine platform expressing a filovirus glycoprotein has been demonstrated to provide protection from lethal challenge with Ebola (EBOV) and Marburg (MARV) viruses both prophylactically and after exposure. This platform provides protection between heterologous strains within a species; however, protection from lethal challenge between species has been largely unsuccessful. To determine whether the rVSV-EBOV vaccines have the potential to provide protection against a newly emerging, phylogenetically related species, cynomolgus macaques were vaccinated with an rVSV vaccine expressing either the glycoprotein of Zaire ebolavirus (ZEBOV) or Côte d'Ivoire ebolavirus (CIEBOV) and then challenged with Bundibugyo ebolavirus (BEBOV), which was recently proposed as a new EBOV species following an outbreak in Uganda in 2007. A single vaccination with the ZEBOV-specific vaccine provided cross-protection (75% survival) against subsequent BEBOV challenge, whereas vaccination with the CIEBOV-specific vaccine resulted in an outcome similar to mock-immunized animals (33% and 25% survival, respectively). This demonstrates that monovalent rVSV-based vaccines may be useful against a newly emerging species; however, heterologous protection across species remains challenging and may depend on enhancing the immune responses either through booster immunizations or through the inclusion of multiple immunogens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".