Vaccination with a Lawsonia intracellularis subunit water in oil emulsion vaccine mitigated some disease parameters but failed to affect shedding
Bibliographic record
Abstract
Lawsonia intracellularis is the causative agent of ileitis in swine that manifests as slower weight gain, mild or hemorrhagic diarrhea and/or death in severe cases. As an economically important swine pathogen, development of effective vaccines is important to the swine industry. In developing a subunit vaccine with three recombinant antigens - FliC, GroEL and YopN - we wanted to identify a formulation that would produce robust immune responses that reduce disease parameters associated with Lawsonia intracellularis infection. We formulated these three antigens with four adjuvants: Montanide ISA 660 VG, Montanide Gel 02 PR, Montanide IMS 1313 VG NST, and Montanide ISA 61 VG in an immunogenicity study. Groups vaccinated with formulations including Montanide ISA 660 VG or Montanide ISA 61 VG had significantly more robust immune responses than groups vaccinated with formulations including Montanide Gel 02 PR or Montanide IMS 1313 VG NST. In the challenge study, animals vaccinated with these antigens and Montanide ISA 61 VG had reduced lesion scores, reduced lesion lengths, and increased average daily gain, but no reduction in shedding relative to the control animals. This work shows that this vaccine formulation should be considered for future study in a field and performance trial.
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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".