A importância da Feira de Ciências na formação do aluno

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As experiências práticas correlacionando saberes.

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O objetivo da Aula Passeio no processo educativo

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A Interdisciplinaridade na construção de saberes

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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

Essential oil of Lippia sidoides and its major compound thymol: toxicity and walking response of populations of Sitophilus zeamais (Coleoptera: Curculionidae)

The maize weevil, Sitophilus zeamais (Motschulsky) (Coleoptera: Curculionidae), is the main pest of stored grains across tropical regions. An alternative strategy to the use of synthetic insecticides for the management of S. zeamais is the development of botanical insecticides based in the essential oils (EOs) from aromatic plants. In the present study, we evaluated the lethal and sublethal effects of the EO of Lippia sidoides (Cham.) and its major compounds (thymol and ρ-cymene) on different populations of S. zeamais. For this, we determined toxicity by fumigation of treatments of five populations from different Brazilian regions and assessed the lethal time and walking behavior for the most tolerant and susceptible populations. The lethal concentration required to kill 50% of S. zeamais populations ranged from 35.48 to 118.29 μL L^−1 air for EO of L. sidoides, 65.00–91.23 μL L^−1 air for thymol and 801.24 to 2188,83 μL L^−1 air for ρ-cymene. Population from Jacarezinho was the most tolerant to treatments, while population of Rio Branco was the most susceptible one. The survival of S. zeamais populations was significantly affected by treatments and ρ-cymene showed the faster action on both Jacarezinho and Rio Branco populations (LT50 = 0.3 h). The walking behavior of maize weevil showed that the EO of L. sidoides and thymol present repellent effect, however, ρ-cymene present attractive effect. Therefore, the EO of L. sidoides and its major compound thymol are promising source to develop bioinsecticides for the management of S. zeamais populations with different levels of resistance

Proteomic analysis reveals differentially expressed proteins in macrophages infected with Leishmania amazonensis or Leishmania major.

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2014-05-29T19:29:39Z No. of bitstreams: 1 Menezes JPB Proteomic analysis....pdf: 1459187 bytes, checksum: 8d7186a26071a6aedf0690a3c922fa6a (MD5)Made available in DSpace on 2014-05-29T19:29:39Z (GMT). No. of bitstreams: 1 Menezes JPB Proteomic analysis....pdf: 1459187 bytes, checksum: 8d7186a26071a6aedf0690a3c922fa6a (MD5) Previous issue date: 2013Fundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, Brasil / Federal University of Bahia. Salvador, Bahia, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, Brasil / Federal University of Bahia. Salvador, Bahia, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, Brasil / Federal University of Bahia. Salvador, Bahia, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, Brasil / Federal University of Bahia. Salvador, Bahia, BrasilCenter for the Study of Biological Complexity, Virginia Commonwealth University. Richmond, VA, USAFundação Oswaldo Cruz. Functional Genomic Laboratory. Carlos Chagas Institute (ICC). Paraná, SC, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Laboratório de Patologia e Biointervenção. Salvador, BA, BrasilCBA macrophages effectively control Leishmania major infection, yet are permissive to Leishmania amazonensis. Employing a transcriptomic approach, we previously showed the up-regulation of the genes involved in the classical pathway of macrophage activation in resistant mice. However, microarray analyses do not evaluate changes in gene expression that occur after translation. To circumvent this analytical limitation, we employed a proteomics approach to increase our understanding of the modulations that occur during infection and identify novel targets for the control of Leishmania infection. To identify proteins whose expression changes in CBA macrophages infected with L. major or L. amazonensis, protein extracts were obtained and digested and the peptides were characterized using multi-dimensional liquid chromatography coupled with tandem mass spectrometry analyses. A total of 162 proteins were selected as potentially modulated. Using biological network analyses, these proteins were classified as primarily involved in cellular metabolism and grouped into cellular development biological networks. This study is the first to use a proteomics approach to describe the protein modulations involved in cellular metabolism during the initial events of Leishmania-macrophage interaction. Based on these findings, we hypothesize that these differentially expressed proteins likely play a pivotal role in determining the course of infection