A synthetic consensus anti–spike protein DNA vaccine induces protective immunity against Middle East respiratory syndrome coronavirus in nonhuman primates
Bibliographic record
Abstract
First identified in 2012, Middle East respiratory syndrome (MERS) is caused by an emerging human coronavirus, which is distinct from the severe acute respiratory syndrome coronavirus (SARS-CoV), and represents a novel member of the lineage C betacoronoviruses. Since its identification, MERS coronavirus (MERS-CoV) has been linked to more than 1372 infections manifesting with severe morbidity and, often, mortality (about 495 deaths) in the Arabian Peninsula, Europe, and, most recently, the United States. Human-to-human transmission has been documented, with nosocomial transmission appearing to be an important route of infection. The recent increase in cases of MERS in the Middle East coupled with the lack of approved antiviral therapies or vaccines to treat or prevent this infection are causes for concern. We report on the development of a synthetic DNA vaccine against MERS-CoV. An optimized DNA vaccine encoding the MERS spike protein induced potent cellular immunity and antigen-specific neutralizing antibodies in mice, macaques, and camels. Vaccinated rhesus macaques seroconverted rapidly and exhibited high levels of virus-neutralizing activity. Upon MERS viral challenge, all of the monkeys in the control-vaccinated group developed characteristic disease, including pneumonia. Vaccinated macaques were protected and failed to demonstrate any clinical or radiographic signs of pneumonia. These studies demonstrate that a consensus MERS spike protein synthetic DNA vaccine can induce protective responses against viral challenge, indicating that this strategy may have value as a possible vaccine modality against this emerging pathogen.
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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".