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

Aspectos anatomopatológicos das neoplasias malignas renais: Anatomopathological aspects of malignant renal neoplasms

As neoplasias renais correspondem ao crescimento exacerbado de células tumorais no interior dos rins, classificadas como benignas ou malignas. Neste estudo será abordado sobre as neoplasias malignas renais, a qual correspondem a maior prevalência e são representadas pelo carcinoma de células renais e o tumor de Wilms, com a finalidade de descrever a respeito dos aspectos anatomopatológicos, disseminando informações para o diagnóstico e manejo precoce. O carcinoma de células renais é mais prevalente no sexo masculino, indivíduos mais velhos, geralmente assintomático, contribuindo para o diagnóstico tardio junto a existência de metástases e terapêutica irresponsiva. Não se trata de uma doença genética, sendo o caráter esporádico o predominante, neste contexto os fatores de risco, sobretudo o tabagismo em seguida de obesidade hemodiálise e doenças genéticas são potenciais desencadeantes da enfermidade. Os exames complementares associado a clínica, junto ao acompanhamento eleva a possibilidade de identificação antes de avanços metastáticos. O tumor de Wilms é típico de crianças, acometendo um ou ambos os rins, normalmente com alguma anomalia genética, sendo os sinais inespecíficos, mas sempre manifestando massa palpável e dor abdominal, a qual os métodos de imagem confirmam o diagnóstico e estimam o prognóstico deste. Neste contexto, elucida-se a transcendência que os aspectos anatomopatológicos das neoplasias malignas renais oferecem para a diagnose precoce, devido a escassez e inespecificidafe das manifestações clínicas. Logo, a junção do perfil de cada neoplasia abordado conduz ao manejo adequado e reduz a incidência de tratamentos agressivos e irresponsivos

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

sCD163 levels as a biomarker of disease severity in leprosy and visceral leishmaniasis

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2018-04-05T13:29:54Z No. of bitstreams: 1 Silva LR sCD163 levels as a biomarker of disease....pdf: 1813439 bytes, checksum: 61b593e582b8cc501964a9d141747a1a (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2018-04-05T13:58:17Z (GMT) No. of bitstreams: 1 Silva LR sCD163 levels as a biomarker of disease....pdf: 1813439 bytes, checksum: 61b593e582b8cc501964a9d141747a1a (MD5)Made available in DSpace on 2018-04-05T13:58:17Z (GMT). No. of bitstreams: 1 Silva LR sCD163 levels as a biomarker of disease....pdf: 1813439 bytes, checksum: 61b593e582b8cc501964a9d141747a1a (MD5) Previous issue date: 2017Fundação de Apoio à Pesquisa e à Inovação Tecnológica do Estado de Sergipe (FAPITEC - http://www.fapitec.se.gov.br/)/SE/FUNTEC/Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Grants: CNPq n.12/2009, Processo n. 019.203.02712/2009-8 (ARJ).Universidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, Brasil / Universidade Federal de Sergipe. Departamento de Educação em Saúde de Lagarto. Lagarto, SE, BrasilUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, Brasil / Universidade Federal de Sergipe. Departamento de Educação em Saúde de Lagarto. Lagarto, SE, BrasilUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, Brasil / Universidade Federal de Sergipe. Departamento de Educação em Saúde de Lagarto. Lagarto, SE, BrasilUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, BrasilUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, BrasilUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, BrasilUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, Brasil / Universidade Federal de Sergipe. Departamento de Educação em Saúde de Lagarto. Lagarto, SE, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilUniversidade de São Paulo. Faculdade de Medicina de Ribeirão Preto. Departamento de Bioquímica e Imunologia. Ribeirão Preto, SP, BrasilHoward University. Department of Biology. Washington, DC, USAInfectious Diseases Research Institute. Seattle, WA, USAInfectious Diseases Research Institute. Seattle, WA, USAUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, BrasilUniversidade Federal de Sergipe. Hospital Universitário. Laboratório de Biologia Molecular. Aracaju, SE, BrasilCD163, receptor for the haptoglobin-hemoglobin complex, is expressed on monocytes/macrophages and neutrophils. A soluble form of CD163 (sCD163) has been associated with the M2 macrophage phenotype, and M2 macrophages have been shown to down-modulate inflammatory responses. In particular, previous studies have shown that M2 is closely associated with the most severe clinical presentation of leprosy (i.e. lepromatous leprosy (LL)), as well as tuberculosis. We hypothesized that sCD163 correlates with severity of diseases caused by intracellular pathogens

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora