Preparation and characterization of monoclonal antibodies against pathogenic Stenotrophomonas maltophilia in fish.
Bibliographic record
Abstract
BALB/c mice were immunized with Stenotrophomonas maltophilia ina ctivated by formalin.The hybridoma cell lines consistently secreting monoclonal antibodies(McAbs)against pathogenic S.maltophilia in fish were obtained through cell fusion.The specificity of the McAbs was analysed by an indirect ELISA.Then the subtypes were identified,the titer and relative affinity were measured,and its specifici ty was analyzed.Examination were made to identify the antigen epitope of McAbs by combining expe rimental site and indirect ELISA with lipopolysaccharides(LPS)of S.mal tophilia.In results,from over hundreds of positive hybridomas which secreted anti-S.maltophilia McAbs,eight strains of hybridomas were screened out,and designated as 1C3,1C6,4H8,3D9,2B11,3G3,2H11 and 1B8,respectively.The subtypes of the McAbs were IgG2a,IgG2b,IgG3 and IgM,respectively.The titers of these McAbs produced by ascites fluid were higher than 10-6.The McAbs had high relativ e affinity.The eight strains of McAbs targeted different antigen epitope:only 2B 11 targeted the LPS of S.maltophilia,while the others targeted t he non-LPS sites of S.maltophilia.In conclusion,eight specific McAbs against S.maltophilia were ob tained successfully,which might be very useful for further studies of the patho genesis and early diagnosis of S.maltophilia in aquaculture.
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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) | 0.001 | 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 | 0.000 | 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".