268 research outputs found

    Caracterização Nutricional de Branquilho (Sebastiania Commersoniana Baillon Smith & Downs - Euphorbiaceae), Cultivado em Solo Contaminado por Petróleo.

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    O estudo foi desenvolvido um ano após o vazamento de petróleo na Refinaria Presidente Getúlio Vargas (PR) às margens do rio Iguaçu, Região Metropolitana de Curitiba - PR com o objetivo de avaliar o efeito da contaminação do solo no teor de macro, micronutrientes e Al de mudas de branquilho, espécie nativa da região e utilizada para recuperação de áreas degradadas. Mudas foram plantadas à campo em solo contaminado, não-contaminado e biorremediado e em casa de vegetação em solo contaminado, não- contaminado, com e sem adubação. Folhas e caules foram analisadas após 15 meses no campo e 11 meses em casa de vegetação. A contaminação parece ter causado uma redução do teor de K e um aumento de Mg e Fe das folhas. Nos caules foram observadas reduções significativas nos teores de Ca, Fe e Al, no tratamento com solo contaminado. No experimento em casa de vegetação, a adição de adubo dificultou a análise dos resultados. No solo contaminado as folhas apresentaram menores teores de Mg. Os teores de Mn e Zn, foram maiores no solo contaminado sem adubação. Nos caules os teores de N foram maiores no solo contaminado adubado, os de Fe no solo contaminado com e sem adubação e para os teores de Mn e Al foi difícil estabelecer um padrão. Os resultados observados podem também estar relacionados ao efeito da grande variabilidade nas características morfológicas, químicas e físicas dos solos do complexo ambiente de várzea estudado

    RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing's sarcoma

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    <p>Abstract</p> <p>Background</p> <p>Ewing's sarcomas are aggressive musculoskeletal tumors occurring most frequently in the long and flat bones as a solitary lesion mostly during the teen-age years of life. With current treatments, significant number of patients relapse and survival is poor for those with metastatic disease. As part of novel target discovery in Ewing's sarcoma, we applied RNAi mediated phenotypic profiling to identify kinase targets involved in growth and survival of Ewing's sarcoma cells.</p> <p>Results</p> <p>Four Ewing's sarcoma cell lines TC-32, TC-71, SK-ES-1 and RD-ES were tested in high throughput-RNAi screens using a siRNA library targeting 572 kinases. Knockdown of 25 siRNAs reduced the growth of all four Ewing's sarcoma cell lines in replicate screens. Of these, 16 siRNA were specific and reduced proliferation of Ewing's sarcoma cells as compared to normal fibroblasts. Secondary validation and preliminary mechanistic studies highlighted the kinases STK10 and TNK2 as having important roles in growth and survival of Ewing's sarcoma cells. Furthermore, knockdown of STK10 and TNK2 by siRNA showed increased apoptosis.</p> <p>Conclusion</p> <p>In summary, RNAi-based phenotypic profiling proved to be a powerful gene target discovery strategy, leading to successful identification and validation of STK10 and TNK2 as two novel potential therapeutic targets for Ewing's sarcoma.</p

    RPPAML/RIMS: A metadata format and an information management system for reverse phase protein arrays

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    <p>Abstract</p> <p>Background</p> <p>Reverse Phase Protein Arrays (RPPA) are convenient assay platforms to investigate the presence of biomarkers in tissue lysates. As with other high-throughput technologies, substantial amounts of analytical data are generated. Over 1000 samples may be printed on a single nitrocellulose slide. Up to 100 different proteins may be assessed using immunoperoxidase or immunoflorescence techniques in order to determine relative amounts of protein expression in the samples of interest.</p> <p>Results</p> <p>In this report an RPPA Information Management System (RIMS) is described and made available with open source software. In order to implement the proposed system, we propose a metadata format known as reverse phase protein array markup language (RPPAML). RPPAML would enable researchers to describe, document and disseminate RPPA data. The complexity of the data structure needed to describe the results and the graphic tools necessary to visualize them require a software deployment distributed between a client and a server application. This was achieved without sacrificing interoperability between individual deployments through the use of an open source semantic database, S3DB. This data service backbone is available to multiple client side applications that can also access other server side deployments. The RIMS platform was designed to interoperate with other data analysis and data visualization tools such as Cytoscape.</p> <p>Conclusion</p> <p>The proposed RPPAML data format hopes to standardize RPPA data. Standardization of data would result in diverse client applications being able to operate on the same set of data. Additionally, having data in a standard format would enable data dissemination and data analysis.</p

    O MICRO-IFC

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    Nas mãos, nas mesas, nos filtros de ar-condicionado, nas esponjas dos refeitórios, nosbebedouros, nos computadores e salas de aula, dentro do micro-ondas, nos livros da biblioteca, nassalas reservadas e fechadas, em diversos pontos podem-se encontrar microrganismos. A escola é umlocal onde pessoas vêm das mais diferentes culturas e hábitos de higiene (ou falta destes). Lavar asmãos, não tossir ou espirrar sem tapar a boca e o nariz, evitar utilizar utensílios compartilhados,sobretudo, se estiverem com aspecto de sujo, deixar portas ou janelas abertas no ambiente coletivo,tudo isso, são medidas de higiene básicas para conter o avanço das contaminações em locaispúblicos como os ambientes escolares (GUIMARÃES, 2020; FADER et.al, 2021). Há bem poucosanos atrás, o mundo viveu uma pandemia e a maioria dos locais públicos tiveram que ser esvaziadospara atender às normas de saúde e segurança. Toda uma revisão dos hábitos de higiene para evitaras contaminações eram repassados diariamente na TV e nos canais da Internet. Venceu-se umabatalha, mas a guerra continua. Os microrganismos continuam disseminados e causando doençaspelos ambientes, sobretudo, em espaços públicos como as escolas (BACHA e TOLUSSI, 2022). Ométodo científico é uma forma sistemática de trabalhar o problema em questão. Ele envolve aobservação de fenômenos naturais, a formulação de hipóteses explicativas, o teste dessas hipótesespor meio de experimentação e observação cuidadosa e a análise e interpretação dos dadosresultantes. É uma ferramenta confiável utilizada por cientistas em todas as áreas de estudo, incluindoa Microbiologia (MARKONI e LAKATOS, 2003). O objetivo desta pesquisa é envolver os alunos doprojeto na investigação por meio da microbiologia das diversas superfícies do IFC Fraiburgoanalisando a carga de microrganismos, entre fungos e bactérias, associadas aos ambientes de usocomum e abordar sobre o método científico em cima destes resultados

    Posterior Association Networks and Functional Modules Inferred from Rich Phenotypes of Gene Perturbations

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    Combinatorial gene perturbations provide rich information for a systematic exploration of genetic interactions. Despite successful applications to bacteria and yeast, the scalability of this approach remains a major challenge for higher organisms such as humans. Here, we report a novel experimental and computational framework to efficiently address this challenge by limiting the ‘search space’ for important genetic interactions. We propose to integrate rich phenotypes of multiple single gene perturbations to robustly predict functional modules, which can subsequently be subjected to further experimental investigations such as combinatorial gene silencing. We present posterior association networks (PANs) to predict functional interactions between genes estimated using a Bayesian mixture modelling approach. The major advantage of this approach over conventional hypothesis tests is that prior knowledge can be incorporated to enhance predictive power. We demonstrate in a simulation study and on biological data, that integrating complementary information greatly improves prediction accuracy. To search for significant modules, we perform hierarchical clustering with multiscale bootstrap resampling. We demonstrate the power of the proposed methodologies in applications to Ewing's sarcoma and human adult stem cells using publicly available and custom generated data, respectively. In the former application, we identify a gene module including many confirmed and highly promising therapeutic targets. Genes in the module are also significantly overrepresented in signalling pathways that are known to be critical for proliferation of Ewing's sarcoma cells. In the latter application, we predict a functional network of chromatin factors controlling epidermal stem cell fate. Further examinations using ChIP-seq, ChIP-qPCR and RT-qPCR reveal that the basis of their genetic interactions may arise from transcriptional cross regulation. A Bioconductor package implementing PAN is freely available online at http://bioconductor.org/packages/release/bioc/html/PANR.html

    Deterministic Effects Propagation Networks for reconstructing protein signaling networks from multiple interventions

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    <p>Abstract</p> <p>Background</p> <p>Modern gene perturbation techniques, like RNA interference (RNAi), enable us to study effects of targeted interventions in cells efficiently. In combination with mRNA or protein expression data this allows to gain insights into the behavior of complex biological systems.</p> <p>Results</p> <p>In this paper, we propose Deterministic Effects Propagation Networks (DEPNs) as a special Bayesian Network approach to reverse engineer signaling networks from a combination of protein expression and perturbation data. DEPNs allow to reconstruct protein networks based on combinatorial intervention effects, which are monitored via changes of the protein expression or activation over one or a few time points. Our implementation of DEPNs allows for latent network nodes (i.e. proteins without measurements) and has a built in mechanism to impute missing data. The robustness of our approach was tested on simulated data. We applied DEPNs to reconstruct the <it>ERBB </it>signaling network in <it>de novo </it>trastuzumab resistant human breast cancer cells, where protein expression was monitored on Reverse Phase Protein Arrays (RPPAs) after knockdown of network proteins using RNAi.</p> <p>Conclusion</p> <p>DEPNs offer a robust, efficient and simple approach to infer protein signaling networks from multiple interventions. The method as well as the data have been made part of the latest version of the R package "nem" available as a supplement to this paper and via the Bioconductor repository.</p
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