Cattle Immunized with a Recombinant Subunit Vaccine Formulation Exhibits a Trend towards Protection against Histophilus somni Bacterial Challenge
Bibliographic record
Abstract
Histophilosis, a mucosal and septicemic infection of cattle is caused by the Gram negative pathogen Histophilus somni (H. somni). As existing vaccines against H. somni infection have shown to be of limited efficacy, we used a reverse vaccinology approach to identify new vaccine candidates. Three groups (B, C, D) of cattle were immunized with subunit vaccines and a control group (group A) was vaccinated with adjuvant alone. All four groups were challenged with H. somni. The results demonstrate that there was no significant difference in clinical signs, joint lesions, weight change or rectal temperature between any of the vaccinated groups (B,C,D) vs the control group A. However, the trend to protection was greatest for group C vaccinates. The group C vaccine was a pool of six recombinant proteins. Serum antibody responses determined using ELISA showed significantly higher titers for group C, with P values ranging from < 0.0148 to < 0.0002, than group A. Even though serum antibody titers in group B (5 out of 6 antigens) and group D were significantly higher compared to group A, they exerted less of a trend towards protection. In conclusion, the vaccine used in group C exhibits a trend towards protective immunity in cattle and would be a good candidate for further analysis to determine which proteins were responsible for the trend towards protection.
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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 | 0.001 |
| 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".