Assessment of a Vesicular Stomatitis Virus–Based Vaccine by Use of the Mouse Model of Ebola Virus Hemorrhagic Fever
Bibliographic record
Abstract
BACKGROUND: In humans and nonhuman primates, Ebola virus causes a virulent viral hemorrhagic fever for which no licensed vaccines or therapeutic drugs exist. In the present study, we used the mouse model for Ebola hemorrhagic fever to assess the safety and efficacy of a vaccine based on a live attenuated vesicular stomatitis virus expressing the Zaire ebolavirus (ZEBOV) glycoprotein. METHODS: Healthy mice were given the vaccine in various doses, decreasing from 2 x 10(4) to 2 plaque-forming units (pfu), with both systemic and mucosal vaccination routes used. Mice were challenged with 10(3) to 10(6) lethal doses of mouse-adapted ZEBOV. Severely immunocompromised mice were injected with 2 x 10(5) pfu, which is 10 times greater than the immunization dose normally used, to test vaccine safety. RESULTS: Two plaque-forming units of the vaccine protected against lethal challenge, and mucosal immunization was found to be as protective as systemic injection. The replicating vaccine was never detected in the immunized animals, nor were there clinical signs after immunization. Immunization of severely immunocompromised mice with 200,000 pfu of vaccine resulted in no clinical symptoms. CONCLUSIONS: Our data suggest that the vaccine is highly potent and safe and that it very rapidly induces "sterile" immunity in mice. The potential for mucosal delivery, if confirmed in nonhuman primates, makes it an excellent candidate for mass immunization during outbreaks or in the event of intentional release.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".