ArticleTropical medicine and infectious disease2024
Standardization and Evaluation of the LAMP Technique for the Diagnosis of Canine Visceral Leishmaniasis in Conjunctival Swab Samples Using DNA Extracted by a Silica Column and Boiling.
Article in Tropical medicine and infectious disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Detection of Leishmania infantum DNA in captive wild mammals from an urban zoo in a visceral leishmaniasis-endemic area of Brazil.PLoS neglected tropical diseases · 2026Article
- A Non-Invasive Diagnostic Platform for Canine Leishmaniasis Using VOC Analysis and Distributed Veterinary Infrastructure.Veterinary sciences · 2025Article
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14 authors.
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Abstract
The diagnosis of canine visceral leishmaniasis (CVL) presents a challenge due to a variety of non-specific clinical signs. The available tests have low sensitivity. This study aimed to standardize and evaluate the loop-mediated isothermal amplification technique with K26 target (K26-LAMP) for diagnosis of CVL in conjunctival swab (CS) DNA samples extracted through a silica column commercial kit (SW-kit) and boiling (SW-DB) and to compare sensitivity with conventional PCR (kDNA-cPCR) and quantitative real-time PCR (18S-qPCR). Clinical samples of CSs were collected from 54 dogs after reactive serology tests. Positive parasitological and/or histological tests were used as inclusion criteria for a sensitivity analysis. A total of 79.2% (43/54) of dogs without clinical signs or with mild, moderate, or severe clinical signs were included in the study. The sensitivity results of K26-LAMP, kDNA-cPCR, and 18S-qPCR were 72.1%, 81.4%, and 80.5% with the SW-kit and 97.2%, 95.2%, and 57.1% with SW-DB, respectively. In all techniques, the proportion of positives was higher in the group with severe clinical disease, with statistically significant differences in the K26-LAMP and 18S-qPCR techniques being seen with the SW-kit. The results obtained with LAMP for CS samples are promising and its performance is similar to other techniques.
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