Intranasal immunization with a proteosome-adjuvanted SARS-CoV-2 spike protein-based vaccine is immunogenic and efficacious in mice and hamsters
Bibliographic record
Abstract
With the persistence of the SARS-CoV-2 pandemic and the emergence of novel variants, the development of novel vaccine formulations with enhanced immunogenicity profiles could help reduce disease burden in the future. Intranasally delivered vaccines offer a new modality to prevent SARS-CoV-2 infections through the induction of protective immune responses at the mucosal surface where viral entry occurs. Herein, we evaluated a novel protein subunit vaccine formulation containing a resistin-trimerized prefusion Spike antigen (SmT1v3) and a proteosome-based mucosal adjuvant (BDX301) formulated to enable intranasal immunization. In mice, the formulation induced robust antigen-specific IgG and IgA titers, in the blood and lungs, respectively. In addition, the formulations were highly efficacious in a hamster challenge model, reducing viral load and body weight loss. In both models, the serum antibodies had strong neutralizing activity, preventing the cellular binding of the viral Spike protein based on the ancestral reference strain, the Beta (B.1.351) and Delta (B.1.617.2) variants of concern. As such, this intranasal vaccine formulation warrants further development as a novel SARS-CoV-2 vaccine.
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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 | 0.000 | 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".