Cellular and Humoral Immunogenicity of a Candidate DNA Vaccine Expressing SARS-CoV-2 Spike Subunit 1
Bibliographic record
Abstract
The urgent need for effective, safe and equitably accessible vaccines to tackle the ongoing spread of COVID-19 led researchers to generate vaccine candidates targeting varieties of immunogens of SARS-CoV-2. Because of its crucial role in mediating binding and entry to host cell and its proven safety profile, the subunit 1 (S1) of the spike protein represents an attractive immunogen for vaccine development. Here, we developed and assessed the immunogenicity of a DNA vaccine encoding the SARS-CoV-2 S1. Following in vitro confirmation and characterization, the humoral and cellular immune responses of our vaccine candidate (pVAX-S1) was evaluated in BALB/c mice using two different doses, 25 µg and 50 µg. Our data showed high levels of SARS-CoV-2 specific IgG and neutralizing antibodies in mice immunized with three doses of pVAX-S1. Analysis of the induced IgG subclasses showed a Th1-polarized immune response, as demonstrated by the significant elevation of spike-specific IgG2a and IgG2b, compared to IgG1. Furthermore, we found that the immunization of mice with three doses of 50 µg of pVAX-S1 could elicit significant memory CD4+ and CD8+ T cell responses. Taken together, our data indicate that pVAX-S1 is immunogenic and safe in mice and is worthy of further preclinical and clinical evaluation.
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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".