Fecal microbiota of horses with colitis and its association with laminitis and survival during hospitalization
Bibliographic record
Abstract
BACKGROUND: The association of microbiota with clinical outcomes and the taxa associated with colitis in horses remains generally unknown. OBJECTIVES: Describe the fecal microbiota of horses with colitis and investigate the association of the fecal microbiota with the development of laminitis and survival. ANIMALS: Thirty-six healthy and 55 colitis horses subdivided into laminitis (n = 15) and non-laminitis (n = 39, 1 horse with chronic laminitis was removed from this comparison) and survivors (n = 27) and nonsurvivors (n = 28). METHODS: Unmatched case-control study. The Illumina MiSeq platform targeting the V4 region of the 16S ribosomal RNA gene was used to assess the microbiota. RESULTS: The community membership (Jaccard index) and structure (Yue and Clayton index) were different (analysis of molecular variance [AMOVA]; P < .001) between healthy and colitis horses. The linear discriminant analysis effect size (LEfSe; linear discriminant analysis [LDA] >3; P < .05) and random forest analyses found Enterobacteriaceae, Lactobacillus, Streptococcus, and Enterococcus enriched in colitis horses, whereas Treponema, Faecalibacterium, Ruminococcaceae, and Lachnospiraceae were enriched in healthy horses. The community membership and structure of colitis horses with or without laminitis was (AMOVA; P > .05). Enterobacteriaceae, Streptococcus, and Lactobacillus were enriched in horses with laminitis (LDA > 3; P < .05). The community membership (AMOVA; P = .008) of surviving and nonsurviving horses was different. Nonsurviving horses had an enrichment of Enterobacteriaceae, Pseudomonas, Streptococcus, and Enterococcus (LDA >3; P < .05). CONCLUSION AND CLINICAL IMPORTANCE: Differences in the microbiota of horses with colitis that survive or do not survive are minor and, similarly, the microbiota differences in horses with colitis that do or do not develop laminitis are minor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".