Infection of porcine colon explants with “Brachyspira hampsonii” leads to increased epithelial necrosis and catarrhal exudate
Bibliographic record
Abstract
Mucohemorrhagic diarrhea in pigs caused by Brachyspira spp. has a global distribution, and an economic impact on affected farms due to poor performance of animals. Demonstrations that "Brachyspira hampsonii" is pathogenic have been achieved using in vivo animal models, but a critical knowledge gap exists regarding the pathogenic mechanisms employed by Brachyspira. Here, we used in vitro organ culture of porcine colon to investigate interactions between "B. hampsonii" and explants during the first 12 h of contact. Explants were either inoculated with "B. hampsonii" or sterile culture broth. Responses to infection were evaluated by optical microscopy and quantitative PCR. Significantly greater numbers of necrotic crypt cells and thicker catarrhal exudate were observed on infected explants compared to controls. Spirochaetes were observed in the mucus layer, in contact with necrotic exfoliated cells, in crypts and the lamina propria. Statistical differences were observed in mRNA levels between inoculated and control explants for IL-1α, TNF-α and ZO-1 using a Bayesian analysis, but not observed using the ΔΔCq method. These results provide a demonstration of a porcine colon explant model for investigating interactions of Brachyspira with its host and show that initial effects on the host are observed within the first 12 h of contact.
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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) | 0.001 | 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 | 0.001 |
| 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".