Production and characterization of monoclonal antibodies against shope fibroma virus superoxide dismutase and glutathione-s-transferase.
Bibliographic record
Abstract
PURPOSE: The superoxide dismutase (SOD) like proteins encoded by Leporipoxviruses play a role in regulating the redox status of infected cells. The biological function of these proteins is unclear. Why poxviruses encode these proteins are still unknown. Exploiting standard hybridoma techniques, we developed a monoclonal antibody (MAb) against shope fibroma virus superoxide dismutase (sfvSOD) to be used in diagnostics and as tools to understand the role of SOD-like proteins in pathogenesis. METHODS: Hybridoma cell fusion technology was used for production of MAbs. Balb/c mice were immunized with sfvSOD-GST fusion protein. Hybridoma clones were screened using indirect enzyme linked immunosorbent assay (ELISA). Specificity and reactivity of the MAbs were determined by Western blot analysis (WBA) and indirect ELISA. Protein G affinity chromatography was used for the purification of MAbs. RESULTS: Two stable hybridoma clones producing MAbs against the two domains of the fusion protein were obtained. The anti-GST (glutathione-s-transferase) and anti-sfvSOD MAbs were found to react specifically with GST and sfvSOD proteins respectively, in addition to the sfvSOD-GST fusion protein. Isotypes of these MAbs were identified as IgG2b heavy chain and k light chain. CONCLUSION: The anti-sfvSOD MAb (P115.SOD MAb) has been successfully used in studying the enzymatic and biochemical properties of a SOD homolog encoded by sfv. We also developed a strong anti-GST MAb which was also cloned and characterized P115.GST MAb. The anti-GST MAb might be useful in analyzing GST fusion proteins and in immunoaffinity chromatography purification of GST fusion proteins.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
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".