A Formação do Currículo ma Era Globalizada: Por uma Crítica à Construção do Ensino Hegemônico no Brasil

Trabalho de Conclusão de Curso apresentado ao Instituto Latino-Americano de Tecnologia, Infraestrutura e Território da Universidade Federal da Integração Latino-Americana, como requisito parcial à obtenção do título de licenciado em Geografia - Licenciatura.A presente pesquisa visa promover reflexões sobre a globalização e suas implicações na padronização curricular a partir do século XX e início do século XXI. Tendo como recorte temporal o período iminente à Segunda Guerra Mundial, destaca a mudança de paradigma dos currículos escolares que, neste momento, passaram a ser guiados em direção à construção de uma identidade global. A construção dessa identidade global acontece atrelada a outros fatores essenciais, que são a homogeneização e isomorfismo das categorias curriculares a nível mundial e a emergência de um modelo de sociedade também padronizado. Discutimos então, como a globalização dos currículos promove um novo arranjo organizacional que interfere diretamente na relação entre currículo e espaço escolar, pois transfere os poderes de decisão sobre a prática educativa para a escala global – onde predomina a ação de agentes econômicos internacionais – ao mesmo tempo em que mina o poder de decisão e autonomia da escala local, onde predomina a prática educativa que é estreitamente ligada ao espaço de significação dos sujeitos e da transformação social. Assim, a escola e o currículo se tornam desterritorializados, submetidos às determinações externas ao ambiente escolar e que servem, sobretudo, à lógica de acumulação do capital. A partir de uma revisão bibliográfica de alguns dos principais autores do tema, demonstramos como a globalização dos currículos infere na manutenção da racionalidade dominante, que a partir de grandes investimentos estrangeiros diretos formalizaram as principais reformas da educação brasileira das últimas décadas, implementando a desregulamentação da educação da esfera pública para a esfera privada e fazendo prevalecer as relações hegemônicas entre centro e periferia do sistema-mundo na formulação dos currículos escolares globalizados

Effects of Anti-IL-17 on Inflammation, Remodeling, and Oxidative Stress in an Experimental Model of Asthma Exacerbated by LPS

Inflammation plays a central role in the development of asthma, which is considered an allergic disease with a classic Th2 inflammatory profile. However, cytokine IL-17 has been examined to better understand the pathophysiology of this disease. Severe asthmatic patients experience frequent exacerbations, leading to infection, and subsequently show altered levels of inflammation that are unlikely to be due to the Th2 immune response alone. This study estimates the effects of anti-IL-17 therapy in the pulmonary parenchyma in a murine asthma model exacerbated by LPS. BALB/c mice were sensitized with intraperitoneal ovalbumin and repeatedly exposed to inhalation with ovalbumin, followed by treatment with or without anti-IL-17. Twenty-four hours prior to the end of the 29-day experimental protocol, the two groups received LPS (0.1 mg/ml intratracheal OVA-LPS and OVA-LPS IL-17). We subsequently evaluated bronchoalveolar lavage fluid, performed a lung tissue morphometric analysis, and measured IL-6 gene expression. OVA-LPS-treated animals treated with anti-IL-17 showed decreased pulmonary inflammation, edema, oxidative stress, and extracellular matrix remodeling compared to the non-treated OVA and OVA-LPS groups (p < 0.05). The anti-IL-17 treatment also decreased the numbers of dendritic cells, FOXP3, NF-kappa B, and Rho kinase 1-and 2-positive cells compared to the non-treated OVA and OVA-LPS groups (p < 0.05). In conclusion, these data suggest that inhibition of IL-17 is a promising therapeutic avenue, even in exacerbated asthmatic patients, and significantly contributes to the control of Th1/Th2/Th17 inflammation, chemokine expression, extracellular matrix remodeling, and oxidative stress in a murine experimental asthma model exacerbated by LPS.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)National Council of Scientific and the Technological Development (CNPq)Laboratory of Medical InvestigationsUniv Sao Paulo, Sch Med, Dept Med Sci, Sao Paulo, Brazil|Hosp Sirio Libanes, Sao Paulo, BrazilUniv Fed Sao Paulo, Inst Biomed Sci, Dept Biol Sci, Sao Paulo, BrazilUniv Fed Sao Paulo, Dept Biol Sci, Sao Paulo, BrazilUniv Fed Sao Paulo, Inst Biomed Sci, Dept Biol Sci, Sao Paulo, BrazilUniv Fed Sao Paulo, Dept Biol Sci, Sao Paulo, BrazilFAPESP: 2013/17944-1Laboratory of Medical Investigations: LIM-20 FMUSPWeb of Scienc

Protective Effects of Anti-IL17 on Acute Lung Injury Induced by LPS in Mice

Introduction: T helper 17 (Th17) has been implicated in a variety of inflammatory lung and immune system diseases. However, little is known about the expression and biological role of IL-17 in acute lung injury (ALI). We investigated the mechanisms involved in the effect of anti-IL17 in a model of lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice.Methods: Mice were pre-treated with anti-IL17, 1h before saline/LPS intratracheal administration alongside non-treated controls and levels of exhaled nitric oxide (eNO), cytokine expression, extracellular matrix remodeling and oxidative stress, as well as immune cell counts in bronchoalveolar lavage fluid (BALF), and respiratory mechanics were assessed in lung tissue.Results: LPS instillation led to an increase in multiple cytokines, proteases, nuclear factor-κB, and Forkhead box P3 (FOXP3), eNO and regulators of the actomyosin cytoskeleton, the number of CD4+ and iNOS-positive cells as well as the number of neutrophils and macrophages in BALF, resistance and elastance of the respiratory system, ARG-1 gene expression, collagen fibers, and actin and 8-iso-PGF2α volume fractions. Pre-treatment with anti-IL17 led to a significant reduction in the level of all assessed factors.Conclusions: Anti-IL17 can protect the lungs from the inflammatory effects of LPS-induced ALI, primarily mediated by the reduced expression of cytokines and oxidative stress. This suggests that further studies using anti-IL17 in a treatment regime would be highly worthwhile

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

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

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others