6 research outputs found

    MISTIC2: Comprehensive server to study coevolution in protein families

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    Correlated mutations between residue pairs in evolutionarily related proteins arise from constraints needed to maintain a functional and stable protein. Identifying these inter-related positions narrows down the search for structurally or functionally important sites. MISTIC is a server designed to assist users to calculate covariation in protein families and provide them with an interactive tool to visualize the results. Here, we present MISTIC2, an update to the previous server, that allows to calculate four covariation methods (MIp, mfDCA, plmDCA and gaussianDCA). The results visualization framework has been reworked for improved performance, compatibility and user experience. It includes a circos representation of the information contained in the alignment, an interactive covariation network, a 3D structure viewer and a sequence logo. Others components provide additional information such as residue annotations, a roc curve for assessing contact prediction, data tables and different ways of filtering the data and exporting figures. Comparison of different methods is easily done and scores combination is also possible. A newly implemented web service allows users to access MISTIC2 programmatically using an API to calculate covariation and retrieve results. MISTIC2 is available at: https://mistic2.leloir.org.ar.Fil: Colell, Eloy A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Iserte, Javier Alonso. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Marino Buslje, Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentin

    Mappatura delle professioni culturali emergenti e loro percorsi formativi

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    La ricerca, commissionata dalla Fondazione Compagnia di San Paolo, ha avuto come territorio di riferimento il Piemonte, la Liguria e la Valle d’Aosta, regioni d'azione della Fondazione. La ricerca ha mirato a produrre tre output: - una mappatura delle professioni culturali, con particolare focus sulle emergenti; - una mappatura dell’offerta formativa ad oggi; - la definizione delle competenze necessarie nel settore culturale sul medio - lungo periodo. L’obiettivo generale della ricerca è stato quindi quello di costruire un quadro del lavoro e delle professioni culturali, con una particolare attenzione a quelle emergenti e di approfondire le caratteristiche dei percorsi formativi ad esse collegati. Tali obiettivi generali, sono stati poi declinati nei seguenti obiettivi specifici: - la ricognizione delle definizioni di “professione culturale”; - un approfondimento e un’analisi delle caratteristiche delle figure professionali presenti ed emergenti nel settore con un’attenzione sia all’individuazione delle competenze necessarie sia alle caratteristiche e alle condizioni dei lavoratori, alle loro traiettorie e identità; - un approfondimento e un’analisi dell’o erta formativa esistente (formale e non formale), nonché l’individuazione di fabbisogni formativi e di eventuali gap tra l’attuale o erta e le figure professionali e competenze nel prossimo triennio. Nella ricerca è stato assunto come angolo di osservazione privilegiato il punto di vista dei principali protagonisti del mondo culturale nelle tre regioni in cui opera la Fondazione Compagnia di S. Paolo (Piemonte, Liguria e Valle d’Aosta). In particolare sono stati coinvolti gli enti beneficiari e proponenti dell’attività istituzionale ed erogativa della Compagnia di San Paolo - Obiettivo Cultura, le società fornitrici della Fondazione e i loro lavoratori e alcuni esperti del mondo della cultura

    Grand Challenges in global eye health: a global prioritisation process using Delphi method

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    Background: We undertook a Grand Challenges in Global Eye Health prioritisation exercise to identify the key issues that must be addressed to improve eye health in the context of an ageing population, to eliminate persistent inequities in health-care access, and to mitigate widespread resource limitations. Methods: Drawing on methods used in previous Grand Challenges studies, we used a multi-step recruitment strategy to assemble a diverse panel of individuals from a range of disciplines relevant to global eye health from all regions globally to participate in a three-round, online, Delphi-like, prioritisation process to nominate and rank challenges in global eye health. Through this process, we developed both global and regional priority lists. Findings: Between Sept 1 and Dec 12, 2019, 470 individuals complete round 1 of the process, of whom 336 completed all three rounds (round 2 between Feb 26 and March 18, 2020, and round 3 between April 2 and April 25, 2020) 156 (46%) of 336 were women, 180 (54%) were men. The proportion of participants who worked in each region ranged from 104 (31%) in sub-Saharan Africa to 21 (6%) in central Europe, eastern Europe, and in central Asia. Of 85 unique challenges identified after round 1, 16 challenges were prioritised at the global level; six focused on detection and treatment of conditions (cataract, refractive error, glaucoma, diabetic retinopathy, services for children and screening for early detection), two focused on addressing shortages in human resource capacity, five on other health service and policy factors (including strengthening policies, integration, health information systems, and budget allocation), and three on improving access to care and promoting equity. Interpretation: This list of Grand Challenges serves as a starting point for immediate action by funders to guide investment in research and innovation in eye health. It challenges researchers, clinicians, and policy makers to build collaborations to address specific challenges. Funding: The Queen Elizabeth Diamond Jubilee Trust, Moorfields Eye Charity, National Institute for Health Research Moorfields Biomedical Research Centre, Wellcome Trust, Sightsavers, The Fred Hollows Foundation, The Seva Foundation, British Council for the Prevention of Blindness, and Christian Blind Mission. Translations: For the French, Spanish, Chinese, Portuguese, Arabic and Persian translations of the abstract see Supplementary Materials section.</p

    A global metagenomic map of urban microbiomes and antimicrobial resistance

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    We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.
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