Strain-Specific Monoclonal Antibodies to the E2 Protein of Classical Swine Fever Virus, Paderborn Strain
Bibliographic record
Abstract
Monoclonal antibodies (MAbs) against the E2 protein of classical swine fever virus (CSFV) are useful for diagnosis and strain characterization. A purified, baculovirus-expressed CSFV E2 protein from the Paderborn strain was formulated with a saponin adjuvant and successfully used to induce an antigen-specific immune response in mice. After cell fusion a panel, designated F92G, of 12 mouse hybridomas (5-2, 11-1, 14-1, 25-2, 28-2, 31-1, 34-1, 35-2, 37-3, 38-2, 39-1, 41-1) producing CSFV-E2 specific MAbs were selected based on their Ig subclass and secretion level (μg IgG/mL). Nine IgG 1/k, two IgG 2b/k, and one IgG 2a/k MAbs were further characterized using immunoperoxidase reactivity, ELISA, and Western blot analysis. Immunoglobulin concentration-dependent immunoperoxidase and ELISA reactivity was observed for some of the MAbs with certain antigens. In general there were several reactivity patterns exhibited by the MAbs, with CSFV strains representing different genetic subgroups (by immunoperoxidase staining) and recombinant antigens (by ELISA). It was interesting to note that in some cases the strain-specific reactivity of a MAb was dependent on the test, thereby providing a clue regarding the nature of the binding site.
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 | 0.000 | 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) | 0.002 | 0.001 |
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".