Genetic diversity of Siberian bovine coronavirus isolates (Coronaviridae: Coronavirinae: <i>Betacoronavirus-1: Bovine-Like coronaviruses</i>)
Bibliographic record
Abstract
INTRODUCTION: Bovine coronaviruses (BCoVs) are causative agents of diarrhea, respiratory diseases in calves and winter cow dysentery. The study of genetic diversity of these viruses is topical issue. The purpose of the research is studying the genetic diversity of BCoV isolates circulating among dairy cattle in Siberia. MATERIALS AND METHODS: Specimens used in this study were collected from animals that died or was forcedly slaughtered before the start of the study. The target for amplification were nucleotide sequences of S and N gene regions. RESULTS: Based on the results of RT-PCR testing, virus genome was present in 16.3% of samples from calves with diarrheal syndrome and in 9.9% with respiratory syndrome. The nucleotide sequences of S gene region were determined for 18 isolates, and N gene sequences - for 12 isolates. Based on S gene, isolates were divided into two clades each containing two subclades. First subclade of first clade (European line) included 11 isolates. Second one included classic strains Quebec and Mebus, strains from Europe, USA and Korea, but none of sequences from this study belonged to this subclade. 6 isolates belonged to first subclade of second clade (American-Asian line). Second subclade (mixed line) included one isolate. N gene sequences formed two clades, one of them included two subclades. First subclade included 3 isolates (American-Asian line), and second subclade (mixed) included one isolate. Second clade (mixed) included 8 sequences. No differences in phylogenetic grouping between intestinal and respiratory isolates, as well as according to their geographic origin were identified. CONCLUSION: The studied population of BCoV isolates is heterogeneous. Nucleotide sequence analysis is a useful tool for studying molecular epidemiology of BCoV. It can be beneficial for choice of vaccines to be used in a particular geographic region.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".