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

Clinical and epidemiology evaluation of Aids-infected patients hospitalized between 2011 and 2016 in the Santos region of Brazil

Abstract INTRODUCTION: We assessed the clinical-epidemiological profile of acquired immune deficiency syndrome (AIDS) patients in the Santos region (São Paulo state) with the highest AIDS prevalence in Brazil. METHODS Information was extracted from records of 409 AIDS-infected patients hospitalized between 2011 and 2016. RESULTS: Human immunodeficiency virus (HIV) was diagnosed in 24.7% of patients during admission, and 39.6% of already diagnosed patients received highly active antiretroviral therapy (HAART) irregularly. The mortality rate was 19.1%, and the main secondary manifestations were neurotoxoplasmosis and tuberculosis. CONCLUSIONS: AIDS patients in the Santos region had high rates of late diagnosis and low treatment adherence

Núcleos de Ensino da Unesp: artigos 2013: volume 2: metodologias de ensino e a apropriação de conhecimento pelos alunos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Núcleos de Ensino da Unesp: artigos 2013: volume 2: metodologias de ensino e a apropriação de conhecimento pelos alunos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP