Avian antimicrobial peptides: in vitro and in ovo characterization and protection from early chick mortality caused by yolk sac infection
Bibliographic record
Abstract
Increasing antibiotic resistance is a matter of grave concern for consumers, public health authorities, farmers, and researchers. Antimicrobial peptides (AMPs) are emerging as novel and effective non-antibiotic tools to combat infectious diseases in poultry. In this study, we evaluated six avian AMPs including 2 truncated cathelicidins, [CATH-1(6-26) and CATH-2(1-15)], and 4 avian β-defensins (ABD1, 2, 6 and 9) for their bactericidal and immunomodulatory activities. Our findings have shown CATH-1(6-26) and ABD1 being the two most potent avian AMPs effective against Gram-positive and Gram-negative bacteria investigated in these studies. Moreover, CATH-1(6-26) inhibited LPS-induced NO production and exhibited dose-dependent cytotoxicity to HD11 cells. While, ABD1 blocked LPS-induced IL-1β gene induction and was non-toxic to HD11 cells. Importantly, in ovo administration of these AMPs demonstrated that ABD1 can offer significant protection from early chick mortality (44% less mortality in ABD1 treated group versus the control group) due to the experimental yolk sac infection caused by avian pathogenic Escherichia coli. Our data suggest that in ovo administration of ABD1 has immunomodulatory and anti-infection activity comparable with CpG ODN. Thus, ABD1 can be a significant addition to potential alternatives to antibiotics for the control of bacterial infections in young chicks.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".