DNA Based Vaccine Expressing SARS-CoV-2 Spike-CD40L Fusion Protein Confers Protection Against Challenge in a Syrian Hamster Model
Bibliographic record
Abstract
SARS-CoV-2 infections present a tremendous threat to public health. Safe and efficacious vaccines are the most effective means in preventing the infections. A variety of vaccines have demonstrated excellent efficacy and safety around the globe. Yet, development of alternative forms of vaccines remains beneficial, particularly those with simpler production processes, less stringent storage conditions, and the capability of being used in heterologous prime/boost regimens which have shown improved efficacy against many diseases. Here we reported a novel DNA vaccine comprised of the SARS-CoV-2 spike protein fused with CD40 ligand (CD40L) serving as both a targeting ligand and molecular adjuvant. A single intramuscular injection in Syrian hamsters induced significant neutralizing antibodies 3-weeks after vaccination, with a boost substantially improving immune responses. Moreover, the vaccine also reduced weight loss and suppressed viral replication in the lungs and nasal turbinates of challenged animals. Finally, the incorporation of CD40L into the DNA vaccine was shown to reduce lung pathology more effectively than the DNA vaccine devoid of CD40L. These results collectively indicate that this DNA vaccine candidate could be further explored because of its efficacy and known safety profile.
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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 | 0.000 | 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".