The amino acid selected for generating mutant TbpB antigens defective in binding transferrin can compromise the in vivo protective capacity
Bibliographic record
Abstract
Haemophilus parasuis is the causative agent of the Glässer's disease (GD), one of the most important bacterial diseases that affect young pigs worldwide. GD prevention based on vaccination is a major concern due to the limited cross-protection conferred by the inactivated whole cell vaccines used currently. In this study, vaccines based on two mutant recombinant proteins derived from transferrin binding protein B of H. parasuis (Y167A-TbpB and W176A-TbpB) were formulated and evaluated in terms of protection against lethal challenge using a serovar 7 (SV7) H. parasuis in a high susceptibility pig model. Our results showed that H. parasuis strain 174 (SV7) is highly virulent in conventional and colostrum-deprived pigs. The Y167A-TbpB and W176A-TbpB antigens were immunogenic in pigs, however, differences in terms of antigenicity and functional immune response were observed. In regard to protection, animals immunized with Y167A-TbpB antigen displayed 80% survival whereas the W176A-TbpB protein was not protective. In conjunction with previous studies, our results demonstrate, (a) the importance of testing engineered antigens in an in vivo pig challenge model, and, (b) that the Y167A-TbpB antigen is a promising antigen for developing a broad-spectrum vaccine against H. parasuis infection.
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) | 0.000 | 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".