Generation, characterization, and application in serodiagnosis of recombinant swine vesicular disease virus-like particles
Bibliographic record
Abstract
Swine vesicular disease (SVD) is a highly contagious viral disease that causes vesicular disease in pigs. The importance of the disease is due to its indistinguishable clinical signs from those of foot-and-mouth disease, which prevents international trade of swine and related products. SVD-specific antibody detection via an enzyme-linked immunosorbent assay (ELISA) is the most versatile and commonly used method for SVD surveillance and export certification. Inactivated SVD virus is the commonly used antigen in SVD-related ELISA. A recombinant SVD virus-like particle (VLP) was generated by using a Bac-to-Bac baculovirus expression system. Results of SVD-VLP analyses from electron microscopy, western blotting, immunofluorescent assay, and mass spectrometry showed that the recombinant SVD-VLP morphologically resemble authentic SVD viruses. The SVD-VLP was evaluated as a replacement for inactivated whole SVD virus in competitive and isotype-specific ELISAs for the detection of antibodies against SVD virus. The recombinant SVD-VLP assay produced results similar to those from inactivated whole virus antigen ELISA. The VLP-based ELISA results were comparable to those from the virus neutralization test for antibody detection in pigs experimentally inoculated with SVD virus. Use of the recombinant SVD-VLP is a safe and valuable alternative to using SVD virus antigen in diagnostic assays.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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".