Molecular Diagnosis, Prevalence and Importance of Zoonotic Vector-Borne Pathogens in Cuban Shelter Dogs—A Preliminary Study
Bibliographic record
Abstract
The present study aimed to determine the prevalence of zoonotic vector-borne pathogens, including Anaplasma platys, Anaplasma phagocytophilum, Borrelia burgdorferi sensu lato, Ehrlichia canis and Rickettsia spp. in shelter dogs from Cuba. Blood samples were collected from 100 shelter dogs and examined by molecular methods. Overall, 85 (85%; 95% CI: 77.88–92.12) dogs tested positive for at least one vector-borne pathogen using species-specific qPCR assays. Among the positive samples, E. canis was the most prevalent 62% (95% CI: 52.32–71.68), followed by A. platys 40% (95% CI: 30.23–49.77) and Rickettsia felis 27% (95% CI: 18.15–35.85), whereas 36% (95% CI: 26.43–45.57) showed co-infections. All samples were negative for A. phagocytophilum and B. burgdorferi s.l. The presence of 248 Rhipicephalus sanguineus ticks collected from the dogs was not statistically associated with the occurrence of infections. Thrombocytopenia was the most frequent haematological alteration found in PCR-positive dogs; it was statistically associated with the presence of E. canis, as well as co-infections (p < 0.05). The phylogenetic analyses of A. platys and E. canis based on 16S rRNA, groEL and gltA genes showed a low genetic diversity between Cuban strains. The present study demonstrates the high prevalence of vector-borne pathogens with zoonotic potential in shelter dogs from Cuba.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".