Characterization of the bacterial fecal microbiota composition of pigs preceding the clinical signs of swine dysentery
Bibliographic record
Abstract
Swine dysentery (SD) is a worldwide production-limiting disease of growing-finishing pigs in commercial farms. The importance of the large intestinal microbiota in the swine dysentery pathogenesis has been established, but not well characterized. The objective of this study was to characterize the fecal bacterial microbiota of pigs immediately prior to developing clinical signs of swine dysentery. A total of 60 fecal samples were collected from 15 pigs with SD. Sampling times included a time point prior to SD (d0, n=15), 2 days before mucohaemorrhagic diarrhea was observed (d-2SD, n=15), 1 day before mucohaemorrhagic diarrhea was observed (d-1SD, n=15), and the day when pigs developed mucohemorragic diarrhea (MHD, n=15). Sequencing of cpn60 amplicons was used to profile the microbiome, and analyses were performed on QIIME2. Increased Chao1 index in d-1SD and MHD samples when compared to the d0 was the only change observed in alpha diversity. No differences between sampling times on beta diversity (Bray-Curtis dissimilarity) were found. Although a small sample size was investigated, differential abundance analysis revealed that Alistipes dispar and Parabacteroides gordonii were increased in MHD fecal samples when compared to d-2SD and d-1SD. It is suggested that these taxa may play a role in the pathogenesis of SD, which is known to require the presence of Brachyspira spp. and an anaerobe for severe disease development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".