Elastase-Dependant Live Attenuated Swine Influenza Virus Vaccine in Pigs
Bibliographic record
Abstract
Swine influenza (SI) is an acute, highly contagious, respiratory disease of swine caused by influenza A viruses.In addition, SI infections possess significant human public health concerns as they may serve as intermediate host for the generation of new pandemic viruses.Vaccination is still the primary method for the prevention and control of SI.Currently, commercially available vaccines against SI are a combination of inactivated swine influenza viruses (SIVs) with oil adjuvant.Their application induces mainly humoral immune response, which may not be protective against virus variation in the field.In contrast, application of live attenuated influenza vaccines (LAIV) mimics natural infection and induces strong, cell-mediated and humoral immunity.Furthermore, LAIV induces cross-protective immunity against different subtypes of influenza A viruses and are currently unavailable for SI.Using reverse genetics technology we generated mutant SIVs with the modified cleavage site within hemagglutinin (HA) segment.These viruses are fully dependent on the presence of human neutrophil elastase for their growth in tissue culture and are completely attenuated when administered to pigs.Furthermore, application of these live attenuated, elastase-dependent swine influenza viruses as a live vaccines resulted in the significant protective humoral (systemic and mucosal), cell-mediated and cross-reactive immunity in pigs.The purpose of this review is to provide recent advances in SIV live vaccine development by modifying the hemagglutinin cleavage site.Here, we review the design and generation of elastasedependent mutant SIV by reverse genetics; evaluation of its genetic stability and pathogenicity in pigs; evaluation of its immunogenicity and protection efficacy after intratracheal and intranasal application to diverse SIV challenges including 2009 pandemic H1N1 virus.
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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) | 0.000 | 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".