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A conserved fungal glycosyltransferase facilitates pathogenesis of plants by enabling hyphal growth on solid surfaces
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Pathogenic fungi must extend filamentous hyphae across solid surfaces to cause diseases of plants. However, the full inventory of genes which support this is incomplete and many may be currently concealed due to their essentiality for the hyphal growth form. During a random T-DNA mutagenesis screen performed on the pleomorphic wheat (Triticum aestivum) pathogen Zymoseptoria tritici, we acquired a mutant unable to extend hyphae specifically when on solid surfaces. In contrast “yeast-like” growth, and all other growth forms, were unaffected. The inability to extend surface hyphae resulted in a complete loss of virulence on plants. The affected gene encoded a predicted type 2 glycosyltransferase (ZtGT2). Analysis of >800 genomes from taxonomically diverse fungi highlighted a generally widespread, but discontinuous, distribution of ZtGT2 orthologues, and a complete absence of any similar proteins in non-filamentous ascomycete yeasts. Deletion mutants of the ZtGT2 orthologue in the taxonomically un-related fungus Fusarium graminearum were also severely impaired in hyphal growth and non-pathogenic on wheat ears. ZtGT2 expression increased during filamentous growth and electron microscopy on deletion mutants (ΔZtGT2) suggested the protein functions to maintain the outermost surface of the fungal cell wall. Despite this, adhesion to leaf surfaces was unaffected in ΔZtGT2 mutants and global RNAseq-based gene expression profiling highlighted that surface-sensing and protein secretion was also largely unaffected. However, ΔZtGT2 mutants constitutively overexpressed several transmembrane and secreted proteins, including an important LysM-domain chitin-binding virulence effector, Zt3LysM. ZtGT2 likely functions in the synthesis of a currently unknown, potentially minor but widespread, extracellular or outer cell wall polysaccharide which plays a key role in facilitating many interactions between plants and fungi by enabling hyphal growth on solid matrices
Avaliação da qualidade de vida, da dor nas costas, da funcionalidade e de alterações da coluna vertebral de estudantes de fisioterapia
O objetivo deste estudo foi avaliar a qualidade de vida, dor nas costas, funcionalidade e as alterações da coluna vertebral de estudantes de fisioterapia. Participaram 42 universitários, sendo avaliada a coluna vertebral por meio do arcômetro, a dor nas costas por meio de um questionário multidimensional de dor, a qualidade de vida por meio do questionário SF-36 e funcionalidade a partir do Roland-Morris. Foi realizada estatística descritiva e teste qui-quadrado (α=0,05). Os resultados demonstraram: prevalência de alterações nas curvaturas da coluna vertebral de 38,1%; (n=16); alta prevalência de dor nas costas (69%; n=29); baixa prevalência de comprometimento da funcionalidade (3,4%; n=1); que não há associação entre as alterações nas curvaturas da coluna vertebral e funcionalidade e dor nas costas; e que os escores dos domínios do SF-36 foram maiores que 45, exceto o domínio "dor", cujo escore aproximado foi de 35. Conclui-se que quanto menor os níveis de intensidade da dor melhor o nível de qualidade de vida
IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes.
GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach
Exploiting sparsity and equation-free architectures in complex systems
Complex systems exhibit dynamics that typically evolve on low-dimensional attractors and may have sparse representation in some optimal basis. Recently developed compressive sensing techniques exploit this sparsity for state reconstruction and/or categorical identification from limited measurements. We argue that data-driven dimensionality reduction methods integrate naturally with sparse sensing in the context of complex systems. This framework works equally well with a physical model or in an equation-free context, where data is available but the governing equations may be unknown. We demonstrate the advantages of combining these methods on three prototypical examples: classification of dynamical regimes, optimal sensor placement, and equation-free dynamic model reduction. These examples motivate the potentially transformative role that state-of-the-art data methods and machine learning can play in the analysis of complex systems
Multi-decadal variability and trends in the temperature of the northwest European continental shelf: A model-data synthesis
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High-Speed Tensile Testing of Optical Fibers— New Understanding for Reliability Prediction
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