Characterization of the Fecal Bacterial Microbiota of Healthy and Diarrheic Dairy Calves
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Neonatal diarrhea accounts for more than 50% of total deaths in dairy calves. Few population-based studies of cattle have investigated how the microbiota is impacted during diarrhea. OBJECTIVES: To characterize the fecal microbiota and predict the functional potential of the microbial communities in healthy and diarrheic calves. METHODS: Fifteen diarrheic calves between the ages of 1 and 30 days and 15 age-matched healthy control calves were enrolled from 2 dairy farms. The Illumina MiSeq sequencer was used for high-throughput sequencing of the V4 region of the 16S rRNA gene (Illumina, San Diego, CA). RESULTS: Significant differences in community membership and structure were identified among healthy calves from different farms. Differences in community membership and structure also were identified between healthy and diarrheic calves within each farm. Based on linear discriminant analysis effect size (LEfSe), the genera Bifidobacterium, Megamonas, and a genus of the family Bifidobacteriaceae were associated with health at farm 1, whereas Lachnospiraceae incertae sedis, Dietzia and an unclassified genus of the family Veillonellaceae were significantly associated with health at farm 2. The Phylogenetic Investigation of Communities Reconstruction of Unobserved States (PICRUSt) analysis indicated that diarrheic calves had decreased abundances of genes responsible for metabolism of various vitamins, amino acids, and carbohydrate. CLINICAL RELEVANCE: The fecal microbiota of healthy dairy calves appeared to be farm specific as were the changes observed during diarrhea. The differences in microbiota structure and membership between healthy and diarrheic calves suggest that dysbiosis can occur in diarrheic calves and it is associated with changes in predictive metagenomic function.
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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 it