Biocidal activity of chicken defensin-9 against microbial pathogens
Bibliographic record
Abstract
In this study we identified the expression patterns of β-defensin-9 in chickens from Saudi Arabia, evaluated the antimicrobial activities of synthetic chicken β-defensin-9 (sAvBD-9) against pathogenic bacteria and fungi, and investigated the mode of action of sAvBD-9 on bacterial cells. The AvBD-9 gene of Saudi chickens encodes a polypeptide of 67 amino acids, which is highly similar to the polypeptide in duck, quail, and goose (97%, 86%, and 87%, respectively) and shares a low sequence similarity with the mammalian defensins. AvBD-9 is expressed in various organs and tissues of Saudi chickens and inhibits the growth of both Gram-negative and Gram-positive bacteria, as well as showing activity against unicellular and multicellular fungi (Aspergillus flavus, A. niger, and Candida albicans). sAvBD-9 completely inhibited the growth of both Gram-positive and Gram-negative bacterial strains as well as Candida albicans. The haemolytic effects of sAvBD-9 were limited. Morphological analysis by TEM revealed that sAvBD-9 induces shortening and swelling of Staphylococcus aureus and Shigella sonni cells, opens holes and deep craters in their envelopes, and leads to the release of their cytoplasmic content. Our data shed light on the potential applications of sAvBD-9 in the pharmaceutical industry.
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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".