A nanoparticle-based COVID-19 vaccine candidate elicits broad neutralizing antibodies and protects against SARS-CoV-2 infection
Bibliographic record
Abstract
A vaccine candidate to SARS-CoV-2 was constructed by coupling the viral receptor binding domain (RBD) to the surface of the papaya mosaic virus (PapMV) nanoparticle (nano) to generate the RBD-PapMV vaccine. Immunization of mice with the coupled RBD-PapMV vaccine enhanced the antibody titers and the T-cell mediated immune response directed to the RBD antigen as compared to immunization with the non-coupled vaccine formulation (RBD + PapMV nano). Anti-RBD antibodies, generated in vaccinated animals, neutralized SARS-CoV-2 infection in vitro against the ancestral, Delta and the Omicron variants. At last, immunization of mice susceptible to the infection by SARS-CoV-2 (K18-hACE2 transgenic mice) with the RBD-PapMV vaccine induced protection to the ancestral SARS-CoV-2 infectious challenge. The induction of the broad neutralization against SARS-CoV-2 variants induced by the RBD-PapMV vaccine demonstrate the potential of the PapMV vaccine platform in the development of efficient vaccines against viral respiratory infections.
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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 | 0.000 |
| 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".