New insights about functional and cross-reactive properties of antibodies generated against recombinant TbpBs of Haemophilus parasuis
Bibliographic record
Abstract
Vaccines have become fundamental in the control and elimination of Glässer Disease, a systemic disease of pigs caused by Haemophilus parasuis. The classic vaccines available for prevention of this infection were developed without a robust knowledge about host immunological mechanisms. In this study, we demonstrated the presence of cross-reactive epitopes on both the N-lobe and C-lobe of variants of transferrin binding protein B (TbpBs) expressed on the surface of 6 virulent serovars of H. parasuis. Antibodies against TbpB-derived antigens were capable of increasing the phagocytic capacity of neutrophils and were also capable of blocking porcine transferrin from binding to TbpB. Surprisingly, none of the pig or mice antisera from animals immunized with TbpB-derived antigens mixed with Montanide IMS 2215 VG PR adjuvant were able to activate the classical complement pathway (CCP). In contrast, antisera from mice immunized with TbpB-derived antigens adjuvanted with Freund's adjuvants or Montanide Gel 01 were able to activate the CCP and kill H. parasuis. Our results demonstrate that the type of adjuvant can modulate the functional response induced by TbpB-derived antigens. Based on these results, we propose that a properly formulated TbpB-based vaccine may elicit a functional protective antibody response with broad cross-reactivity against heterologous strains of H. parasuis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".