Adjuvant screening of the Senecavirus A inactivated vaccine in mice and evaluation of its immunogenicity in pigs
Bibliographic record
Abstract
BACKGROUND: Senecavirus A (SVA) causes an emerging vesicular disease (VD) with clinical symptoms indistinguishable from other vesicular diseases, including vesicular stomatitis (VS), foot-and-mouth disease (FMD), and swine vesicular disease (SVD). Currently, SVA outbreaks have been reported in Canada, the U.S.A, Brazil, Thailand, Vietnam, Colombia, and China. Based on the experience of prevention and control of FMDV, vaccines are the best means to prevent SVA transmission. RESULTS: After preparing an SVA inactivated vaccine (CH-GX-01-2019), we evaluated the immunogenicity of the SVA inactivated vaccine mixed with Imject® Alum (SVA + AL) or Montanide ISA 201 (SVA + 201) adjuvant in mice, as well as the immunogenicity of the SVA inactivated vaccine combined with Montanide ISA 201 adjuvant in post-weaned pigs. The results of the mouse experiment showed that the immune effects in the SVA + 201 group were superior to that in the SVA + AL group. Results from pigs immunized with SVA inactivated vaccine combined with Montanide ISA 201 showed that the immune effects were largely consistent between the SVA-H group (200 µg) and SVA-L group (50 µg); the viral load in tissues and blood was significantly reduced and no clinical symptoms occurred in the vaccinated pigs. CONCLUSIONS: Montanide ISA 201 is a better adjuvant choice than the Imject® Alum adjuvant in the SVA inactivated vaccine preparation, and the CH-GX-01-2019 SVA inactivated vaccine can provide effective protection for pigs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".