Profiling of lung SARS-CoV-2 and influenza virus infection dissects virus-specific host responses and gene signatures

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies. METHODS: Here, we use targeted transcriptomics of formalin-fixed paraffin-embedded tissue using the NanoString GeoMX platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients. RESULTS: Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the sample, within patient correlations and patient-patient variation, had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27, previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza. CONCLUSION: Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.Arutha Kulasinghe, Chin Wee Tan, Anna Flavia Ribeiro dos Santos Miggiolaro, James Monkman, Habib SadeghiRad, Dharmesh D. Bhuva, Jarbas da Silva Motta Junior, Caroline Busatta Vaz de Paula, Seigo Nagashima, Cristina Pellegrino Baena, Paulo Souza-Fonseca-Guimaraes, Lucia de Noronha, Timothy McCulloch, Gustavo Rodrigues Rossi, Caroline Cooper, Benjamin Tang, Kirsty R. Short, Melissa J. Davis, Fernando Souza-Fonseca-Guimaraes, Gabrielle T. Belz, and Ken O, Byrn

PRAPRAG: software para planejamento racional de máquinas agrícolas PRAPRAG: software for rational planning of agricultural machines

O software PRAPRAG é uma ferramenta de escolha de máquinas e implementos agrícolas que apresentam o menor custo por área ou por quantidade produzida, bem como, faz o planejamento de aquisição das máquinas para a propriedade agrícola, do ponto de vista técnico e econômico. Foi utilizada a linguagem de programação Borland Delphi 3.0 e, a partir de prospectos das máquinas e implementos, criou-se um banco de dados onde o usuário pode cadastrar e modificar suas características de uso. O software mostrou-se uma ferramenta útil e uso amigável. O software proporciona maior rapidez, segurança e confiabilidade ao processo produtivo e econômico das propriedades, na seleção e aquisição de conjuntos mecanizados agrícolas, e na determinação de custos com a mão de obra utilizada.<br>The software PRAPRAG is a tool used for choosing agricultural machines and implements that present the lowest cost per area or produced amount, as well as, to it makes the machines acquisition planning for the agricultural property, from both technical and economical points of view. It was used the programming language Borland Delphi 3.0. From the machine and implement handouts, it was created a database where the user can register and modify their characteristics of use. The software showed to be a useful and friendly tool. The software provides high speed, safety and reliability for the productive and economical process of the properties, at the selection and acquisition of agricultural systems, as well as for the determination of costs with the used labor

Search for magnetically-induced signatures in the arrival directions of ultra-high-energy cosmic rays measured at the Pierre Auger Observatory

We search for signals of magnetically-induced effects in the arrival directions of ultra-high-energy cosmic rays detected at the Pierre Auger Observatory. We apply two different methods. One is a search for sets of events that show a correlation between their arrival direction and the inverse of their energy, which would be expected if they come from the same point-like source, they have the same electric charge and their deflection is relatively small and coherent. We refer to these sets of events as "multiplets". The second method, called "thrust", is a principal axis analysis aimed to detect the elongated patterns in a region of interest. We study the sensitivity of both methods using a benchmark simulation and we apply them to data in two different searches. The first search is done assuming as source candidates a list of nearby active galactic nuclei and starburst galaxies. The second is an all-sky blind search. We report the results and we find no statistically significant features. We discuss the compatibility of these results with the indications on the mass composition inferred from data of the Pierre Auger Observatory. © 2020 IOP Publishing Ltd and Sissa Medialab