Juliana Costa

Ms. Juliana Costa


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
21 September 2025 in Microorganisms
Verified
Journal Article
Open access
PDF file
JCJuliana Costa
Juliana Costa
ASAna Rita Maia Teixeira Silva
Ana Rita Maia Teixeira Silva
Filipe SampaioFilipe Sampaio
Filipe Sampaio
Ana Patrícia AlvesAna Patrícia Alves
Ana Patrícia Alves
HSHugo Silva
Hugo Silva
Ricardo Manuel Vinagre LopesRicardo Manuel Vinagre Lopes
Ricardo Manuel Vinagre Lopes
Leishmania infantum is the causative agent of canine leishmaniosis (CanL), a zoonotic disease of considerable clinical and epidemiological concern. Quantification of parasite load is valuable for clinical management, particularly in low-parasite-load cases. This pilot study evaluated the correlation between cytological and molecular techniques in bone marrow samples from dogs clinically affected with leishmaniosis. Amastigotes were quantified by two independent observers using light microscopy, and the same samples were analysed by real-time polymerase chain reaction (qPCR) employing Leishmania spp. specific commercial primers. Inter-observer agreement was moderate according to Cohen’s kappa (κ = 0.47) and substantial according to the intraclass correlation coefficient (ICC = 0.63), respectively, confirming measurement reproducibility. A very strong inverse correlation was found between parasite counts and qPCR cycle threshold (Ct) values (Spearman’s ρ = −0.89; p < 0.001). Furthermore, a robust logarithmic relationship (amastigotes/μL = 10(−0.158 × Ct + 7.61); R2 = 0.99994) was established allowing direct estimation of in vivo parasite concentration from molecular data. These preliminary findings suggest that qPCR can serve as a reliable, semi-quantitative tool, offering higher sensitivity in subclinical infections. The integration of molecular quantification with cytological methods enhances diagnostic accuracy and supports personalised therapeutic decision-making, advancing clinical management of CanL in a One Health context.