Single-dose replicating poxvirus vector-based RBD vaccine drives robust humoral and T cell immune response against SARS-CoV-2 infection
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) pandemic requires the continued development of safe, long-lasting, and efficacious vaccines for preventive responses to major outbreaks around the world, and especially in isolated and developing countries. To combat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we characterize a temperature-stable vaccine candidate (TOH-Vac1) that uses a replication-competent, attenuated vaccinia virus as a vector to express a membrane-tethered spike receptor binding domain (RBD) antigen. We evaluate the effects of dose escalation and administration routes on vaccine safety, efficacy, and immunogenicity in animal models. Our vaccine induces high levels of SARS-CoV-2 neutralizing antibodies and favorable T cell responses, while maintaining an optimal safety profile in mice and cynomolgus macaques. We demonstrate robust immune responses and protective immunity against SARS-CoV-2 variants after only a single dose. Together, these findings support further development of our novel and versatile vaccine platform as an alternative or complementary approach to current vaccines.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".