Prospective study of leptospirosis and brucellosis in dogsfrom a public shelter in the municipality of Lavras, Minas Gerais State, Brazil
Bibliographic record
Abstract
ABSTRACT: The aim of this study was to assess the prevalence and incidence of canine leptospirosis and brucellosis in Parque Francisco de Assis, a shelter in Lavras, Minas Gerais State, Brazil, as well as the risk factors potentially associated with both diseases. Samples of blood, urine, and sera from all animals were collected in 2019 (n = 329) and 2020 (n = 325 dogs). DNA of Leptospira spp. (urine) and Brucella spp. (urine and blood) were searched by PCR, whereas microagglutination test (MAT) and agar gel immunodiffusion assay (AGID) were performed to identify antibodies anti-Leptospira spp. and anti-rough Brucella spp., respectively. The results showed no positive dogs in PCR for Leptospira spp.; however, a seroincidence of 9.24% was found considering MAT results, with Canicola and Autumnalis being the most common serogroups. The incidence of Brucella spp. PCR-positive animals in the 6 months was 5.62% in the urine and 11.23% in the blood samples, while AGID showed a seroincidence of 11.74% in the period. Overall, our results demonstrated the circulation of Leptospira spp. and Brucella spp. among the dogs from Parque Francisco de Assis, Lavras, Minas Gerais, Brazil, being the weight increase (1.10, 95%CI 1.00-1.21) and neutropenia (3.29, 95%CI 1.60-6.77), the risk factors associated with the occurrence of leptospirosis and brucellosis, respectively. Therefore, brucellosis was identified in the dogs of Parque Francisco de Assis, and the presence of antibodies against Leptospira spp. suggesting contact of the dogs with the pathogen, which represent a risk for the other animals and to the humans in close contact with the positive dogs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".