A third SARS-CoV-2 spike vaccination improves neutralization of variants-of-concern
Bibliographic record
Abstract
The emergence of SARS-CoV-2 variants that are more resistant to antibody-mediated neutralization pose a new hurdle in combating the COVID-19 pandemic. Although vaccines based on the original Wuhan sequence have been shown to be effective at preventing COVID-19, their efficacy is likely to be decreased against more neutralization-resistant variants-of-concern (VOC), in particular, the Beta variant originating in South Africa. We assessed, in mice, rabbits, and non-human primates, whether a third vaccination with experimental Wuhan-based Spike vaccines could alleviate this problem. Our data show that a third immunization improves neutralizing antibody titers against the variants-of-concern, Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2). After three vaccinations, the level of neutralization against Beta was similar to the level of neutralization against the original strain after two vaccinations, suggesting that simply providing a third immunization could nullify the reduced activity of current vaccines against VOC.
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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 | 0.000 |
| 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 | 0.001 | 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".