Characterization of a Bivalent Vaccine Capable of Inducing Protection Against Both Ebola and Cross-clade H5N1 Influenza in Mice
Bibliographic record
Abstract
BACKGROUND: Ebola virus (EBOV) is a lethal pathogen that causes up to 90% mortality in humans, whereas H5N1 avian influenza has a 60% fatality rate. Both viruses are considered pandemic threats. The objective was to evaluate the protective efficacy of a bivalent, recombinant vesicular stomatitis virus vaccine expressing both the A/Hanoi/30408/2005 H5N1 hemagglutinin and the EBOV glycoprotein (VSVΔG-HA-ZGP) in a lethal mouse model of infection. METHODS: Mice were vaccinated 28 days before or 30 minutes after a lethal challenge with mouse-adapted EBOV or selected H5N1 influenza viruses from clades 0, 1, and 2. Animals were monitored for weight loss and survival, in addition to humoral and cell-mediated responses after immunization. RESULTS: A single VSVΔG-HA-ZGP injection was efficacious when administered 28 days before a homologous H5N1 and/or mouse-adapted EBOV challenge, as well as a heterologous H5N1 challenge. Postexposure protection was only observed in vaccinated animals challenged with homologous H5N1 and/or mouse-adapted EBOV. Analysis of the adaptive immune response postvaccination revealed robust specific T- and B-cell responses, including a potent hemagglutinin inhibition antibody response against all H5N1 strains tested. CONCLUSIONS: The results highlight the ability of vesicular stomatitis virus-vectored vaccines to rapidly confer protection against 2 unrelated pathogens and stimulate cross-protection against H5N1 influenza viruses.
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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) | 0.001 | 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".