Doença de Chagas em cães: revisão de literatura

A doença de Chagas é uma enfermidade endêmica nas Américas e tem como agente etiológico o protozoário flagelado Trypanosoma cruzi, que infecta uma diversidade de mamíferos e tem como vetores os insetos triatomíneos. Os cães são considerados reservatórios de importância epidemiológica devido ao seu papel de sentinela, proximidade com os seres humanos e manutenção do ciclo de transmissão em ambientes domésticos e peridomésticos. O objetivo deste trabalho foi evidenciar os aspectos clínicos e epidemiológicos da doença de Chagas em cães enfatizando a etiologia, ciclo biológico, terapêutica e profilaxia. Foi realizada uma revisão bibliográfica no banco de dados do Public Medline (PUBMED), Scientific Electronic Library (SCIELO), Biblioteca Virtual em Medicina Veterinária e Zootecnia (BVS-Vet), Biblioteca Virtual em Saúde Brasil (BVS Brasil), Elsevier, Pubvet e Oxford academy no período de 2007 a 2022. Os critérios de inclusão foram artigos publicados nos idiomas inglês e português. No Brasil, as espécies de triatomíneos apresentam ampla distribuição espacial e potencial invasor, facilitada por alterações frequentes no ambiente natural, causadas por atividades antrópicas. A infecção apresenta-se sob duas fases distintas, a fase aguda com uma miocardite ou encefalite em cães jovens e a fase crônica, uma cardiomiopatia dilatada em cães idosos. Os cães infectados geralmente apresentam uma cardiomiopatia, sendo o principal sintoma responsável pela alta morbidade e mortalidade dos animais. Os estudos apontaram que a doença é de difícil diagnóstico, em virtude de diversos fatores, dentre eles, a ausência de um teste padrão ouro, a possibilidade de reação sorológica cruzada com anticorpos para Leishmania, a ocorrência inconsistente de parasitemia e a rara detecção de amastigotas do parasita em cortes histológicos. O tratamento da doença de Chagas constitui um grande desafio, pois os medicamentos disponíveis, benznidazol (BZ) e nifurtimox (NF), apresentam eficácia limitada e efeitos colaterais graves, principalmente na fase crônica. A prevenção e o controle da doença de Chagas estão amplamente focados na redução do contato do cão com os vetores

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

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

Giant calyceal diverticulum with an extra-renal component: A case report

Calyceal diverticula are urine-filled non-secretory cavities that result from outpouchings of the kidney's calyx or pelvis. These cavities lie in the renal parenchyma and are linked to the kidney's collecting system through a narrow channel. They are generally small in size and present without symptoms. Here, we report the case of a middle-aged patient who was diagnosed, following imaging exams, with a giant calyceal diverticulum presenting with an extra-renal component, a remarkably rare finding. The patient's condition was successfully treated through excision by laparoscopic surgery

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data