Novel Ehrlichia canis genogroup in dogs with canine ehrlichiosis in Cuba
Bibliographic record
Abstract
BACKGROUND: Canine monocytic ehrlichiosis (CME) is caused by the tick-borne pathogen Ehrlichia canis, an obligate intracellular Gram-negative bacterium of the family Anaplasmataceae with tropism for canine monocytes and macrophages. The trp36 gene, which encodes for the major immunoreactive protein TRP36 in E. canis, has been successfully used to characterize the genetic diversity of this pathogen in different regions of the world. Based on trp36 sequence analysis, four E. canis genogroups, United States (US), Taiwan (TWN), Brazil (BR) and Costa Rica (CR), have been identified. The aim of this study was to characterize the genetic diversity of E. canis in Cuba based on the trp36 gene. METHODS: Whole blood samples (n = 8) were collected from dogs found to be infested with the tick vector Rhipicephalus sanguineus sensu lato (s.l.) and/or presenting clinical signs and symptoms of CME. Total DNA was extracted from the blood samples and trp36 fragments were amplified by PCR. Nucleotide and protein sequences were compared using alignments and phylogenetic analysis. RESULTS: Four of the trp36 sequences obtained (n = 8) fall within the phylogenetic cluster grouping the US genogroup E. canis strains. The other E. canis trp36 sequences formed a separate and well-supported clade (94% bootstrap value) that is phylogenetically distant from the other major groups and thus represents a new genogroup, herein designated as the 'Cuba (CUB) genogroup'. Notably, dogs infected with the CUB genogroup presented frequent hemorrhagic lesions. CONCLUSIONS: The results of this study suggest that genetic diversification of E. canis in Cuba is associated with the emergence of E. canis strains with increased virulence.
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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 | 0.001 | 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".