385 Unraveling the gut-liver axis in Bovine liver abscesses: Isolation and characterization of Bacteroides from hepatic lesions.
Bibliographic record
Abstract
Abstract Liver abscesses (LAs) in cattle reduce animal performance, increasing the environmental footprint of beef production and causing significant economic losses. These infections result from a translocation of opportunistic pathogens from the gastrointestinal (GI) tract into the blood stream where they can colonize the liver. The primary etiological agent of LAs is Fusobacterium necrophorum; however, recent research has found Bacteroides to be the second most prevalent bacterial group in up to 50% of LAs. Despite their beneficial role in the gut of ruminants, Bacteroides can cause severe infections when they breach the GI tract, leading to bacteremia, and the formation of abscesses in a variety of tissues. We have employed a combination of metagenomic and culture-based methods to isolate and identify the Bacteroides that are associated with liver abscesses in cattle. Two species of Bacteroides were isolated from the purulent material of liver abscesses, and whole genome sequencing conclusively identified these isolates as Bacteroides pyogenes, and a previously unknown species of Bacteroides. This analysis revealed putative virulence genes and identified distinct differences between LA-Bacteroides and most Bacteroides typically found in the GI-tract. In vivo assays have revealed insight into metabolic properties of these microbes. This data provides a critical foundation for expanding our knowledge of the potential role Bacteroides play in this process, and could contribute to the identification of novel targets for developing treatments to prevent this important production limiting disease.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".