Comparative genomics of canine-isolated Leishmania (Leishmania) amazonensis from an endemic focus of visceral leishmaniasis in Governador Valadares, southeastern Brazil.

Leishmaniasis is a highly diverse group of diseases caused by kinetoplastid of the genus Leishmania. These parasites are taxonomically diverse, with human pathogenic species separated into two subgenera according to their development site inside the alimentary tract of the sand fly insect vector. The disease encompasses a variable spectrum of clinical manifestations with tegumentary or visceral symptoms. Among the causative species in Brazil, Leishmania (Leishmania) amazonensis is an important etiological agent of human cutaneous leishmaniasis that accounts for more than 8% of all cases in endemic regions. L. (L.) amazonensis is generally found in the north and northeast regions of Brazil. Here, we report the first isolation of L. (L.) amazonensis from dogs with clinical manifestations of visceral leishmaniasis in Governador Valadares, an endemic focus in the southeastern Brazilian State of Minas Gerais where L. (L.) infantum is also endemic. These isolates were characterized in terms of SNPs, chromosome and gene copy number variations, confirming that they are closely related to a previously sequenced isolate obtained in 1973 from the typical Northern range of this species. The results presented in this article will increase our knowledge of L. (L.) amazonensis-specific adaptations to infection, parasite survival and the transmission of this Amazonian species in a new endemic area of Brazil

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Comparison of serological assays for the diagnosis of canine visceral leishmaniasis in animals presenting different clinical manifestations.

Three serological methods, indirect fluorescent immunoassay (IFI), enzyme-linked immunosorbent assay (ELISA) and direct agglutination test (DAT) that are commonly employed in the diagnosis of canine visceral leishmaniasis (CVL), have been assessed. A total of 234 domestic dogs, drawn from an area in the municipality of Belo Horizonte, Minas Gerais, Brazil, endemic for visceral leishmaniasis, were submitted to clinical and parasitological examinations and serological assay. Sera collected from confirmed non-infected dogs (n = 20), and from dogs with other parasitic diseases including Trypanosoma cruzi ( n = 7), Leishmania braziliensis ( n = 5), Toxoplasma gondii ( n = 5) and Ehrlichia canis ( n = 3), were also included in the study. IFI presented a lower sensitivity (72%) than ELISA (95%), although the specificities of these assays were low (52 and 64%, respectively) and both exhibited cross-reactivity with sera from dogs infected with T. cruzi , L. braziliensis and E. canis. In contrast, DAT exhibited a high sensitivity (93%) and a high specificity (95%) and cross-reacted with only one serum sample derived from anE. canis-infected dog. The reproducibilities of the ELISA and DAT assays were excellent, whilst that of IFI was considered to be acceptable. The results produced by ELISA and DAT were in complete agreement, those between ELISA and IFI were at an acceptable level of agreement, whilst the concurrence between the IFI and DAT results were either acceptable or poor depending on the clinical conditions of the group of dogs examined. Since there is no readily accessible method for the diagnosis of CVL that offers 100% specificity and sensitivity, the choice of technique employed must depend on the aim of the investigation