Assessment of energy savings related to sustainable solutions improving summer comfort

Estágio realizado na Armines - École des Mines de Paris e orientado pelo Prof. Jérôme AdnotTese de mestrado integrado. Engenharia Mecânica. Faculdade de Engenharia. Universidade do Porto. 200

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

The Genome of Anopheles darlingi, the main neotropical malaria vector

Anopheles darlingi is the principal neotropical malaria vector, responsible for more than a million cases of malaria per year on the American continent. Anopheles darlingi diverged from the African and Asian malaria vectors ∼100 million years ago (mya) and successfully adapted to the New World environment. Here we present an annotated reference A. darlingi genome, sequenced from a wild population of males and females collected in the Brazilian Amazon. A total of 10 481 predicted protein-coding genes were annotated, 72% of which have their closest counterpart in Anopheles gambiae and 21% have highest similarity with other mosquito species. In spite of a long period of divergent evolution, conserved gene synteny was observed between A. darlingi and A. gambiae. More than 10 million single nucleotide polymorphisms and short indels with potential use as genetic markers were identified. Transposable elements correspond to 2.3% of the A. darlingi genome. Genes associated with hematophagy, immunity and insecticide resistance, directly involved in vectorhuman and vectorparasite interactions, were identified and discussed. This study represents the first effort to sequence the genome of a neotropical malaria vector, and opens a new window through which we can contemplate the evolutionary history of anopheline mosquitoes. It also provides valuable information that may lead to novel strategies to reduce malaria transmission on the South American continent. The A. darlingi genome is accessible at www.labinfo.lncc.br/index.php/anopheles- darlingi. © 2013 The Author(s)

Cytokine profiles associated with acute COVID-19 and long COVID-19 syndrome

National Council for Scientific and Technological Development (CNPQ #401235/2020-3); Fundação Amazônia de Amparo a Estudos e Pesquisa do Pará (FAPESPA #005/2020 and #006/2020) and Secretaria de Estado de Ciência, Tecnologia e Educação Profissional e Tecnológica (#09/2021).Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Belém, PA, Brazil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Belém, PA, Brazil.Hospital Adventista de Belém. Belém, PA, Brazil.Hospital Adventista de Belém. Belém, PA, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Laboratório de Pesquisas Básicas em Malária. Ananindeua, PA, Brasil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Belém, PA, Brazil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Belém, PA, Brazil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Belém, PA, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade do Estado do Pará. Instituto de Ciências Biológicas e da Saúde. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.The duration and severity of COVID-19 are related to age, comorbidities, and cytokine synthesis. This study evaluated the impact of these factors on patients with clinical presentations of COVID-19 in a Brazilian cohort. A total of 317 patients diagnosed with COVID-19 were included; cases were distributed according to clinical status as severe (n=91), moderate (n=56) and mild (n=170). Of these patients, 92 had acute COVID-19 at sample collection, 90 had already recovered from COVID-19 without sequelae, and 135 had sequelae (long COVID syndrome). In the acute COVID-19 group, patients with the severe form had higher IL-6 levels (p=0.0260). In the post-COVID-19 group, there was no significant difference in cytokine levels between groups with different clinical conditions. In the acute COVID-19 group, younger patients had higher levels of TNF-alpha, and patients without comorbidities had higher levels of TNF-alpha, IL-4 and IL-2 (p<0.05). In contrast, patients over age 60 with comorbidities had higher levels of IL-6. In the post-COVID-19 group, subjects with long COVID-19 had higher levels of IL-17 and IL-2 (p<0.05), and subjects without sequelae had higher levels of IL-10, IL-6 and IL- 4 (p<0.05). Our results suggest that advanced age, comorbidities and elevated serum IL-6 levels are associated with severe COVID-19 and are good markers to differentiate severe from mild cases. Furthermore, high serum levels of IL-17 and IL-2 and low levels of IL-4 and IL-10 appear to constitute a cytokine profile of long COVID-19, and these markers are potential targets for COVID-19 treatment and prevention strategies

Ano IX, número 19

Espaço e Economia: Revista Brasileira de Geografia Econômica, além dos artigos em fluxo contínuo, inclui nesta edição o Dossiê Oeste Metropolitano do Rio de Janeiro, organizado pelos professores Marcio Rufino Silva, Denise de Alcantara, Leandro Dias de Oliveira e André Santos da Rocha (PPGGEO e PPGDT-UFRRJ)

AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest

The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive data set of inventories of mammal, bird, and reptile species ever assembled for the area. The complete data set comprises 154,123 records of 317 species (185 birds, 119 mammals, and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname, and Venezuela). The most frequently recorded species per taxa were: mammals: Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles: Tupinambis teguixin (716 records). The information detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change, and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when using its data in publications and we also request that researchers and educators inform us of how they are using these data