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Record W4401993046 · doi:10.1016/j.vaccine.2024.126254

Vaccination with a Lawsonia intracellularis subunit water in oil emulsion vaccine mitigated some disease parameters but failed to affect shedding

2024· article· en· W4401993046 on OpenAlexaff
Kezia R. Fourie, Alison Jeffery, Dylan Chand, Pooja Choudhary, Siew Hon Ng, Haoming Liu, Donaldson Magloire, Zahed Khatooni, Emil M. Berberov, Heather L. Wilson

Bibliographic record

VenueVaccine · 2024
Typearticle
Languageen
FieldVeterinary
TopicVeterinary medicine and infectious diseases
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLawsonia intracellularisVaccinationImmunogenicityAntigenMedicineVirologyImmune systemImmunologyBiology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.020
GPT teacher head0.288
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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