In vitro efficacy of potentiated egg yolk powder against Campylobacter jejuni does not correlate with in vitro efficacy
Bibliographic record
Abstract
Campylobacter jejuni is a zoonotic agent responsible for the foodborne gastroenteritis campylobacteriosis. Control of C. jejuni load in the poultry primary production is recognized as an avenue to reduce human exposure to the pathogen. As for now, no commercially applicable control methods exist at the farm. Several studies tested egg yolk powders, potentiated or not against C. jejuni, as feed additives for chicken and suggested that the quantity and quality of the antibodies presence in the yolk are determinant factors for the full success of this approach. Unfortunately, data from these studies inconsistently showed a reduction of cecal C. jejuni carriage. Our first goal wwas to characterize (quantification by ELISA, agglutination test, bacterial antigen recognition profiles by Western blot, bactericidal effect by serum killing assays and C. jejuni mobility by soft agar migation) the antibodies extracted from egg yolk powders originating from different egg production protocols. Secondly, these powders were microencapsulated and recharacterized. Finally the protected powders were tested as a feed additive to destabilize C. jejuni colonization in an in vivo assay. Despite the in vitro results indicating the ability of the egg yolk powders to recognize Campylobacter and potentially alter its colonization of the chicken caecum, these results were not confirmed in the in vivo trial despite that specific caecal IgY directed toward Campylobacter were detected in the groups receiving the protected powders. More research is needed on Campylobacter in order to effectively control this pathogen at the farm.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".