The nature of services inflation in Brazil: 1999-2014

sem informaçãoEste artigo tem como objetivo analisar a dinâmica da inflação de serviços no Brasil. Para isso, procurou-se identificar os elementos constitutivos do Índice Nacional de Preços ao Consumidor Amplo passíveis de serem classificados como serviços desde 1999 e271199231sem informaçãosem informaçãosem informaçã

One More Piece in the VACV Ecological Puzzle: Could Peridomestic Rodents Be the Link between Wildlife and Bovine Vaccinia Outbreaks in Brazil?

BACKGROUND: Despite the fact that smallpox eradication was declared by the World Health Organization (WHO) in 1980, other poxviruses have emerged and re-emerged, with significant public health and economic impacts. Vaccinia virus (VACV), a poxvirus used during the WHO smallpox vaccination campaign, has been involved in zoonotic infections in Brazilian rural areas (Bovine Vaccinia outbreaks - BV), affecting dairy cattle and milkers. Little is known about VACV's natural hosts and its epidemiological and ecological characteristics. Although VACV was isolated and/or serologically detected in Brazilian wild animals, the link between wildlife and farms has not yet been elucidated. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we describe for the first time, to our knowledge, the isolation of a VACV (Mariana virus - MARV) from a mouse during a BV outbreak. Genetic data, in association with biological assays, showed that this isolate was the same etiological agent causing exanthematic lesions observed in the cattle and human inhabitants of a particular BV-affected area. Phylogenetic analysis grouped MARV with other VACV isolated during BV outbreaks. CONCLUSION/SIGNIFICANCE: These data provide new biological and epidemiological information on VACV and lead to an interesting question: could peridomestic rodents be the link between wildlife and BV outbreaks

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