421 research outputs found

    Glioblastoma and glioblastoma stem cells are dependent on functional MTH1

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    Glioblastoma multiforme (GBM) is an aggressive form of brain cancer with poor prognosis. Cancer cells are characterized by a specific redox environment that adjusts metabolism to its specific needs and allows the tumor to grow and metastasize. As a consequence, cancer cells and especially GBM cells suffer from elevated oxidative pressure which requires antioxidant-defense and other sanitation enzymes to be upregulated. MTH1, which degrades oxidized nucleotides, is one of these defense enzymes and represents a promising cancer target. We found MTH1 expression levels elevated and correlated with GBM aggressiveness and discovered that siRNA knock-down or inhibition of MTH1 with small molecules efficiently reduced viability of patient-derived GBM cultures. The effect of MTH1 loss on GBM viability was likely mediated through incorporation of oxidized nucleotides and subsequent DNA damage. We revealed that MTH1 inhibition targets GBM independent of aggressiveness as well as potently kills putative GBM stem cells in vitro. We used an orthotopic zebrafish model to confirm our results in vivo and light-sheet microscopy to follow the effect of MTH1 inhibition in GBM in real time. In conclusion, MTH1 represents a promising target for GBM therapy and MTH1 inhibitors may also be effective in patients that suffer from recurring disease

    Epilogue: the new frontiers of behavioral research on the interrelationships between ICT, activities, time use and mobility

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    © 2018, Springer Science+Business Media, LLC, part of Springer Nature. This special issue is a product of the international symposium on “ICT, Activities, Time Use and Travel” that was hosted by Nanjing University from 16 to 18 July 2016. The symposium brought together leading scholars from all over the world to congregate with Chinese scholars and students and to share and discuss the research frontiers at this nexus. It was motivated by a recognition of the changing goals and scope of Information and Communications Technology (ICT) research in conjunction with the development of new ICTs and the emergence of new ICT-enabled behaviors. Consequently, the symposium and later this special issue have drawn together significant scholarly contributions that provide new behavioral insights as well as new theoretical and methodological advances. The symposium culminated in three roundtable panel discussions addressing the following cross-cutting themes: (1) time use while travelling (led by Glenn Lyons); (2) ICT and travel behavior (led by Pat Mokhtarian); and (3) Big Data, activities and urban space (led by Eran Ben-Elia). In this epilogue to the special issue we offer a distillation of these discussions

    Designing visual analytics methods for massive collections of movement data

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    Exploration and analysis of large data sets cannot be carried out using purely visual means but require the involvement of database technologies, computerized data processing, and computational analysis methods. An appropriate combination of these technologies and methods with visualization may facilitate synergetic work of computer and human whereby the unique capabilities of each “partner” can be utilized. We suggest a systematic approach to defining what methods and techniques, and what ways of linking them, can appropriately support such a work. The main idea is that software tools prepare and visualize the data so that the human analyst can detect various types of patterns by looking at the visual displays. To facilitate the detection of patterns, we must understand what types of patterns may exist in the data (or, more exactly, in the underlying phenomenon). This study focuses on data describing movements of multiple discrete entities that change their positions in space while preserving their integrity and identity. We define the possible types of patterns in such movement data on the basis of an abstract model of the data as a mathematical function that maps entities and times onto spatial positions. Then, we look for data transformations, computations, and visualization techniques that can facilitate the detection of these types of patterns and are suitable for very large data sets – possibly too large for a computer's memory. Under such constraints, visualization is applied to data that have previously been aggregated and generalized by means of database operations and/or computational techniques

    Measuring regional creative capacity: A literature review for rural-specific approaches

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    Recent theories on regional creative capacity often focus on urban regions without taking into account rural regions. In addition, the application of such analyses to rural regions may lead to misrepresentation or misunderstanding of rural creative capacity. Against this background, the aim of the present study is to integrate the existing literature on different components of creative capacity, namely, knowledge, innovation, entrepreneurship and networks, in order to build a more comprehensive framework for rural creative capacity and its evaluation. In the light of the perspective from the empirical literature review on the evaluation of creative capacity in rural regions, various empirical measurements seem to misrepresent or underestimate the creative capacity of rural regions. Therefore, there is a clear need to use the locality in relation to its dynamics, i.e. tacit knowledge, cultural heritage and social and physical environment as the main and basic measurement unit for creative capacity analysis. 2010 Taylor & Francis

    The intellectual structure and substance of the knowledge utilization field: A longitudinal author co-citation analysis, 1945 to 2004

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    <p>Abstract</p> <p>Background</p> <p>It has been argued that science and society are in the midst of a far-reaching renegotiation of the social contract between science and society, with society becoming a far more active partner in the creation of knowledge. On the one hand, new forms of knowledge production are emerging, and on the other, both science and society are experiencing a rapid acceleration in new forms of knowledge utilization. Concomitantly since the Second World War, the science underpinning the knowledge utilization field has had exponential growth. Few in-depth examinations of this field exist, and no comprehensive analyses have used bibliometric methods.</p> <p>Methods</p> <p>Using bibliometric analysis, specifically first author co-citation analysis, our group undertook a domain analysis of the knowledge utilization field, tracing its historical development between 1945 and 2004. Our purposes were to map the historical development of knowledge utilization as a field, and to identify the changing intellectual structure of its scientific domains. We analyzed more than 5,000 articles using citation data drawn from the Web of Science<sup>Âź</sup>. Search terms were combinations of knowledge, research, evidence, guidelines, ideas, science, innovation, technology, information theory and use, utilization, and uptake.</p> <p>Results</p> <p>We provide an overview of the intellectual structure and how it changed over six decades. The field does not become large enough to represent with a co-citation map until the mid-1960s. Our findings demonstrate vigorous growth from the mid-1960s through 2004, as well as the emergence of specialized domains reflecting distinct collectives of intellectual activity and thought. Until the mid-1980s, the major domains were focused on innovation diffusion, technology transfer, and knowledge utilization. Beginning slowly in the mid-1980s and then growing rapidly, a fourth scientific domain, evidence-based medicine, emerged. The field is dominated in all decades by one individual, Everett Rogers, and by one paradigm, innovation diffusion.</p> <p>Conclusion</p> <p>We conclude that the received view that social science disciplines are in a state where no accepted set of principles or theories guide research (<it>i.e.</it>, that they are pre-paradigmatic) could not be supported for this field. Second, we document the emergence of a new domain within the knowledge utilization field, evidence-based medicine. Third, we conclude that Everett Rogers was the dominant figure in the field and, until the emergence of evidence-based medicine, his representation of the general diffusion model was the dominant paradigm in the field.</p

    Clustering daily patterns of human activities in the city

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    Data mining and statistical learning techniques are powerful analysis tools yet to be incorporated in the domain of urban studies and transportation research. In this work, we analyze an activity-based travel survey conducted in the Chicago metropolitan area over a demographic representative sample of its population. Detailed data on activities by time of day were collected from more than 30,000 individuals (and 10,552 households) who participated in a 1-day or 2-day survey implemented from January 2007 to February 2008. We examine this large-scale data in order to explore three critical issues: (1) the inherent daily activity structure of individuals in a metropolitan area, (2) the variation of individual daily activities—how they grow and fade over time, and (3) clusters of individual behaviors and the revelation of their related socio-demographic information. We find that the population can be clustered into 8 and 7 representative groups according to their activities during weekdays and weekends, respectively. Our results enrich the traditional divisions consisting of only three groups (workers, students and non-workers) and provide clusters based on activities of different time of day. The generated clusters combined with social demographic information provide a new perspective for urban and transportation planning as well as for emergency response and spreading dynamics, by addressing when, where, and how individuals interact with places in metropolitan areas.Massachusetts Institute of Technology. Dept. of Urban Studies and PlanningUnited States. Dept. of Transportation (Region One University Transportation Center)Singapore-MIT Alliance for Research and Technolog

    A new world typology of cities and systems of cities

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    The chapter proposes an overview of global urbanization since 1950, relying on the structural and dynamic principles of the evolutionary theory of urban systems and on the observations of some of the major financial linkages connecting cities. We analyze first an overview of the state of urbanization at the world scale using statistics collected and provided for all 195 nation-states of the United Nations. We then examine the extent to which the income level and human development index of countries are correlated with the urbanization rates. Trajectories of cities underline the booming cities including many Asiatic and African cities opposed to the relative declining cities. The total weight of emerging metropolises mostly located in Southern countries passed the total population of the other groups of relatively declining cities between 1980 and 2010. It is highly critical for the urban future that the large majority of urban citizens of the world (more than 60%) will be living in these emerging cities in 2030. It will require finding adapted ways to manage urban growth and ecological transition in these developing systems. This global approach finally leads to the partition of the world we used in the book to analyze more precisely the evolution of individual national or continental urban systems
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