Induction of protective immune responses against a lethal Zika virus challenge post-vaccination with a dual serotype of recombinant vesicular stomatitis virus carrying the genetically modified Zika virus E protein gene
Bibliographic record
Abstract
The development of a vaccine to prevent Zika virus (ZIKV) infection has been one of the priorities in infectious disease research in recent years. There have been numerous attempts to develop an effective vaccine against ZIKV. It is imperative to choose the safest and the most effective ZIKV vaccine from all candidate vaccines to control this infection globally. We have employed a dual serotype of prime-boost recombinant vesicular stomatitis virus (VSV) vaccine strategy, to develop a ZIKV vaccine candidate, using a type 1 IFN-receptor knock-out ( Ifnar −/− ) mouse model for challenge studies. Prime vaccination with an attenuated recombinant VSV Indiana serotype (rVSV Ind ) carrying a genetically modified ZIKV envelope (E) protein gene followed by boost vaccination with attenuated recombinant VSV New Jersey serotype (rVSV NJ ) carrying the same E gene induced robust adaptive immune responses. In particular, rVSV carrying the ZIKV E gene with the honeybee melittin signal peptide (msp) at the N terminus and VSV G protein transmembrane domain and cytoplasmic tail (Gtc) at the C terminus of the E gene induced strong protective immune responses. This vaccine regimen induced highly potent neutralizing antibodies and T cell responses in the absence of an adjuvant and protected Ifnar -/- mice from a lethal dose of the ZIKV challenge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".