Intranasal administration of unadjuvanted SARS‐CoV‐2 spike antigen boosts antigen‐specific immune responses induced by parenteral protein subunit vaccine prime in mice and hamsters
Bibliographic record
Abstract
With the continued transmission of SARS-CoV-2 across widely vaccinated populations, it remains important to develop new vaccines and vaccination strategies capable of providing protective immunity and limiting the spread of disease. Heterologous prime-boost vaccination based on the selection of different vaccine formulations and administration routes for priming and booster doses presents a promising strategy for inducing broader immune responses in key systemic and respiratory mucosal compartments. Intranasal vaccination can induce mucosal immune responses at the site of SARS-CoV-2 infection; however, the lack of clinically approved mucosal adjuvants makes it difficult to induce robust immune responses with protein subunit vaccines. Herein, we evaluated the immunogenicity of heterologous prime-boost regimens in mice and hamsters based on a parenteral vaccination of the antigen in combination with sulfated lactosylarchaeol (SLA) archaeosomes, a liposome adjuvant comprised of a single semisynthetic archaeal lipid, followed by an intranasally administered unadjuvanted SARS-CoV-2 spike antigen. Intranasal administration of unadjuvanted spike to mice and hamsters increased serum spike-specific IgG titers and spike-neutralizing activity compared with nonboosted animals. Spike-specific IgA responses were also detected in the bronchoalveolar lavage fluid in the lungs of mice that received an intranasal boost. In hamsters, the intranasal boost showed high efficacy against SARS-CoV-2 infection by protecting from body weight loss and reducing viral titers in the lungs and nasal turbinate. Overall, our heterologous intramuscular prime-intranasal boost with SLA-adjuvanted and unadjuvanted spike, respectively, demonstrated the potential of protein subunit formulations to promote antigen-specific systemic and mucosal immune responses.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".