Bacterial species associated with bovine digital dermatitis of Finnish dairy cows using 16S rRNA amplicon sequencing and Treponema species-specific 4-plex real-time PCR
Bibliographic record
Abstract
Bovine digital dermatitis (DD) is a widespread polybacterial skin disorder affecting dairy and beef cattle, leading to significant animal welfare and economic problems worldwide. The disease primarily affects the hind feet skin, causing painful inflammation between the heel bulbs and resulting in lameness. This study investigated the bacterial compositions in different DD lesion stages and in healthy skin biopsy samples from 151 dairy cows on 36 Finnish farms. The lesions were first classified into six categories, including healthy skin (M0) and samples from different DD lesion stages (M1-M4.1). Additionally, 13 healthy skin samples (M0HH) from cows in low DD (<5 %) prevalence herds served as controls. Bacterial profiling using 16S rRNA gene sequencing revealed the presence of three dominant phyla in active DD lesions: Firmicutes (39 %), Bacteroidota (31 %), and Spirochaetota (24 %), and altogether 11 Treponema species were detected. Real-time PCR was used to verify the presence of four common pathogenic considered species ( T. phagedenis , T. denticola, T. medium and T. pedis ), but only T. phagedenis , T. denticola were detected . This study indicated that DD is a polybacterial disease, with Treponema species abundant in active DD lesions. A higher Treponema count in Western Finland was associated with larger and more severe DD lesions, emphasizing the need for targeted and effective control measures in this region. ● A shift in bacterial compositions during the DD progression was observed. ● The most common bacterial phyla in active DD lesions were Firmicutes (39 %), Bacteroidota (31 %), and Spirocaetota (24 %). ● Abundance of Treponema species was significantly increased in active DD lesions. ● The diversity of pathogenic Treponema species in DD lesions at Finnish dairy farms was low. ● Active DD lesions in Western Finland showed the highest diversity of Treponema .
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".