16 research outputs found

    Freqüência Alélica e Ausência de Distúrbio de Segregação no Locus da Distrofia Miotônica em Indivíduos Normais

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    A Distrofia Miotônica de Steinert (DM) é uma doença autossômica dominante neuromuscular progressiva, causada por uma expansão da repetição CTG no locus DMPK do cromossomo humano 19q13.3. O número de repetições nos alelos normais varia de 5 a 37, enquanto que nos pacientes com DM, este número é sempre superior a 50. O tamanho da expansão está correlacionado à gravidade clínica e à idade de apresentação dos sintomas da doença. Pacientes com 50 a 150 cópias da repetição apresentam a forma mínima da doença, podendo ter apenas catarata como único sintoma. Os pacientes com 100 a 1000 repetições apresentam a forma clássica e pacientes que apresentam mais de 2000 cópias possuem a forma congênita. Baseados em 182 trios (mãefilho-suposto pai) com probabilidade de paternidade superior a 99,99%, foram estimadas freqüências gênicas e genotípicas, parâmetros de interesse forense e verificada a possibilidade de ocorrencia de desvio meiótico. Fenótipos estão em Equilíbrio de Hardy-Weinberg (P = 0,2653); o perfil de freqüências alélicas mostrou-se semelhante ao de populações européias e africanas, mas diferentes da população Asiática. Nossos achados não confirmam a existência de desvio meiótico

    Identifying common and specific microRNAs expressed in peripheral blood mononuclear cell of type 1, type 2, and gestational diabetes mellitus patients

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    Abstract\ud \ud \ud \ud Background\ud Regardless the regulatory function of microRNAs (miRNA), their differential expression pattern has been used to define miRNA signatures and to disclose disease biomarkers. To address the question of whether patients presenting the different types of diabetes mellitus could be distinguished on the basis of their miRNA and mRNA expression profiling, we obtained peripheral blood mononuclear cell (PBMC) RNAs from 7 type 1 (T1D), 7 type 2 (T2D), and 6 gestational diabetes (GDM) patients, which were hybridized to Agilent miRNA and mRNA microarrays. Data quantification and quality control were obtained using the Feature Extraction software, and data distribution was normalized using quantile function implemented in the Aroma light package. Differentially expressed miRNAs/mRNAs were identified using Rank products, comparing T1DxGDM, T2DxGDM and T1DxT2D. Hierarchical clustering was performed using the average linkage criterion with Pearson uncentered distance as metrics.\ud \ud \ud \ud Results\ud The use of the same microarrays platform permitted the identification of sets of shared or specific miRNAs/mRNA interaction for each type of diabetes. Nine miRNAs (hsa-miR-126, hsa-miR-1307, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-144, hsa-miR-199a-5p, hsa-miR-27a, hsa-miR-29b, and hsa-miR-342-3p) were shared among T1D, T2D and GDM, and additional specific miRNAs were identified for T1D (20 miRNAs), T2D (14) and GDM (19) patients. ROC curves allowed the identification of specific and relevant (greater AUC values) miRNAs for each type of diabetes, including: i) hsa-miR-1274a, hsa-miR-1274b and hsa-let-7f for T1D; ii) hsa-miR-222, hsa-miR-30e and hsa-miR-140-3p for T2D, and iii) hsa-miR-181a and hsa-miR-1268 for GDM. Many of these miRNAs targeted mRNAs associated with diabetes pathogenesis.\ud \ud \ud \ud Conclusions\ud These results indicate that PBMC can be used as reporter cells to characterize the miRNA expression profiling disclosed by the different diabetes mellitus manifestations. Shared miRNAs may characterize diabetes as a metabolic and inflammatory disorder, whereas specific miRNAs may represent biological markers for each type of diabetes, deserving further attention.This study was funded by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP - (FAPESP #2008/56594-8, FAPESP #2010/05622-1, FAPESP #210/00932-2, FAPESP #2010/12069-7), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq # 563731/2010-9), and NAP-DIN (Núcleo de Apoio à Pesquisa em Doenças Inflamatórias)

    Transcriptional profiles of the human pathogenic fungus paracoccidioides brasiliensis in mycelium and yeast cells

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    This work was supported by MCT, CNPq, CAPES, FUB, UFG, and FUNDECT-MS. PbGenome Network: Alda Maria T. Ferreira, Alessandra Dantas, Alessandra J. Baptista, Alexandre M. Bailão, Ana Lídia Bonato, André C. Amaral, Bruno S. Daher, Camila M. Silva, Christiane S. Costa, Clayton L. Borges, Cléber O. Soares, Cristina M. Junta, Daniel A. S. Anjos, Edans F. O. Sandes, Eduardo A. Donadi, Elza T. Sakamoto-Hojo, Flábio R. Araújo, Flávia C. Albuquerque, Gina C. Oliveira, João Ricardo M. Almeida, Juliana C. Oliveira, Kláudia G. Jorge, Larissa Fernandes, Lorena S. Derengowski, Luís Artur M. Bataus, Marcus A. M. Araújo, Marcus K. Inoue, Marlene T. De-Souza, Mauro F. Almeida, Nádia S. Parachin, Nadya S. Castro, Odair P. Martins, Patrícia L. N. Costa, Paula Sandrin-Garcia, Renata B. A. Soares, Stephano S. Mello, and Viviane C. B. ReisParacoccidioides brasiliensis is the causative agent of paracoccidioidomycosis, a disease that affects 10 million individuals in Latin America. This report depicts the results of the analysis of 6,022 assembled groups from mycelium and yeast phase expressed sequence tags, covering about 80% of the estimated genome of this dimorphic, thermo-regulated fungus. The data provide a comprehensive view of the fungal metabolism, including overexpressed transcripts, stage-specific genes, and also those that are up- or down-regulated as assessed by in silico electronic subtraction and cDNA microarrays. Also, a significant differential expression pattern in mycelium and yeast cells was detected, which was confirmed by Northern blot analysis, providing insights into differential metabolic adaptations. The overall transcriptome analysis provided information about sequences related to the cell cycle, stress response, drug resistance, and signal transduction pathways of the pathogen. Novel P. brasiliensis genes have been identified, probably corresponding to proteins that should be addressed as virulence factor candidates and potential new drug targets

    Pervasive gaps in Amazonian ecological research

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    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

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    Pervasive gaps in Amazonian ecological research

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    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

    Do monumento comemorativo à arte pública

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    In this paper we tried to define and discuss the concept of public art in light of the theoretical work that justified the creation of this subject, with reference to the main arguments that have characterized the discussion on the topic. To that end, we present a model based on a set of aesthetic and conceptual transformation that occurred in art from the second half of the twentieth century onwards, as far as the plastic formulation, and the perspective of a new understanding of the Spectator place are concerned. This also implies the recognition of old values rejection that characterized the traditional public monument and the failure of its own compositional structure. Thus it is argued that public art is inseparable from the traditional monument crisis, in that it proposes a rupture with this historical context, promoting a new awareness of its form and function. For that purpose we present several artistic projects that illustrate the theoretical and practical implications of this concept.info:eu-repo/semantics/publishedVersio

    Gene Expression Profiles in Radiation Workers Occupationally Exposed to Ionizing Radiation

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    Ionizing radiation OR) imposes risks to human health and the environment. IR at low doses and low (lose rates has the potency to initiate carcinogenesis. Genotoxic environmental agents such as IR trigger a cascade of signal transduction pathways for cellular protection. In this study, using cDNA microarray technique, we monitored the gene expression profiles in lymphocytes derived from radiation-ex posed individuals (radiation workers). Physical dosimetry records on these patients indicated that the absorbed dose ranged from 0.696 to 39.088 mSv. Gene expression analysis revealed statistically significant transcriptional changes in a total of 78 genes (21 up-regulated and 57 clown-regulated) involved in several biological processes such as ubiquitin cycle (UHRF2 and PIAS1), DNA repair (LIG3, XPA, ERCC5, RAD52, DCLRE1C), cell cycle regulation/proliferation (RHOA, CABLES2, TGFB2, IL16), and stress response (GSTP1, PPP2R5A, DUSP22). Some of the genes that showed altered expression profiles in this study call be used as biomarkers for monitoring the chronic low level exposure in humans. Additionally, alterations in gene expression patterns observed in chronically exposed radiation workers reinforces the need for defining the effective radiation dose that causes immediate genetic damage as well as the long-term effects on genomic instability, including cancer.FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo)[99/12135-9]FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo)[01/10995-2]FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo)[02/07314-6]CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico
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