Porcine β-defensin 5 (pBD-5) modulates the inflammatory and metabolic host intestinal response to infection
Bibliographic record
Abstract
Swine dysentery (SD) presents considerable challenges to both animal welfare and pork industry sustainability. Control and prevention of SD rely on antibiotics and non-vaccine biosecurity practices. Host defense peptides (HDPs) have emerged as promising alternatives to treat and prevent such health concern. This study investigated the effects of porcine β-defensin 5 (pBD-5) and its potential host cytotoxicity, metabolic influence, gene expression modulation and direct antimicrobial activity on Brachyspira hyodysenteriae growth in vitro. pBD-5 does not directly inhibit B. hyodysenteriae growth or significantly alters the metabolic activity or membrane integrity of host cells, indicating no significant cytotoxicity at the tested concentrations. Host transcriptome sequencing revealed a reduction in the number of differentially expressed genes in cells exposed to B. hyodysenteriae following pBD-5 treatment, when compared to the pathogen alone, suggesting an immunomodulatory effect. Pathway analysis revealed the downregulation of immune-related pathways, including IL-17, toll-like receptor (TLR), and NOD-like receptor signalling pathways, upon pBD-5 exposure. Conversely, metabolic pathways such as ribosome, protein digestion and absorption, and renin-angiotensin system were upregulated by pBD-5 treatment, hinting at a role in producing and conserving energy during the challenge. While this study offers insights into the immunomodulatory effects of pBD-5, further research is necessary to elucidate its precise mechanisms and potential applications as an alternative treatment for infectious diseases.
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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) | 0.001 | 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".