Intranasal HD-Ad-FS vaccine induces systemic and airway mucosal immunities against SARS-CoV-2 and systemic immunity against SARS-CoV-2 variants in mice and hamsters
Bibliographic record
Abstract
The outbreak of coronavirus disease 19 (COVID-19) has highlighted the demand for vaccines that are safe and effective in inducing systemic and airway mucosal immunity against the aerosol transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we developed a novel helper-dependent adenoviral vector-based COVID-19 mucosal vaccine encoding a full-length SARS-CoV-2 spike protein (HD-Ad-FS). Through intranasal immunization (single-dose and prime-boost regimens), we demonstrated that the HD-Ad-FS was immunogenic and elicited potent systemic and airway mucosal protection in BALB/c mice, transgenic ACE2 (hACE2) mice, and hamsters. We detected high titers of neutralizing antibodies (NAbs) in sera and bronchoalveolar lavages (BALs) in the vaccinated animals. High levels of spike-specific secretory IgA (sIgA) and IgG were induced in the airway of the vaccinated animals. The single-dose HD-Ad-FS elicited a strong immune response and protected animals from SARS-CoV-2 infection. In addition, the prime-boost vaccination induced cross-reactive serum NAbs against variants of concern (VOCs; Beta, Delta, and Omicron). After challenge, VOC infectious viral particles were at undetectable or minimal levels in the lower airway. Our findings highlight the potential of airway delivery of HD-Ad-FS as a safe and effective vaccine platform for generating mucosal protection against SARS-CoV-2 and its VOCs.
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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".