Understanding the molecular mechanisms underlying multi-drug resistance (MDR) is one of the major challenges in current cancer research. A phenomenon which is common to both intrinsic and acquired resistance, is the aberrant alteration of gene expression in drug-resistant cancers. Although such dysregulation depends on many possible causes, an epigenetic characterization is considered a main driver. Recent studies have suggested a direct role for epigenetic inactivation of genes in determining tumor chemo-sensitivity. We investigated the effects of the inhibition of DNA methyltransferase (DNMT) and hystone deacethylase (HDAC), considered to reverse the epigenetic aberrations and lead to the re-expression of de novo methylated genes in MDR osteosarcoma (OS) cells. Based on our analysis of the HosDXR150 cell line, we found that in order to reduce cell proliferation, co-treatment of MDR OS cells with DNMT (5-Aza-dC, DAC) and HDAC (Trichostatin A, TSA) inhibitors is more effective than relying on each treatment alone. In re-expressing epigenetically silenced genes induced by treatments, a very specific regulation takes place which suggests that methylation and de-acetylation have occurred either separately or simultaneously to determine MDR OS phenotype. In particular, functional relationships have been reported after measuring differential gene expression, indicating that MDR OS cells acquired growth and survival advantage by simultaneous epigenetic inactivation of both multiple p53-independent apoptotic signals and osteoblast differentiation pathways. Furthermore, co-treatment results more efficient in inducing the re-expression of some main pathways according to the computed enrichment, thus emphasizing its potential towards representing an effective therapeutic option for MDR OS.
Demographic growth in urban areas means that modern cities face challenges in ensuring a steady supply of water and electricity, smart transport, livable space, better health services, and citizens’ safety. Advances in sensing, communication, and digital technologies promise to mitigate these challenges. Hence, many smart cities have taken a new step in moving away from internal information technology (IT) infrastructure to utility-supplied IT delivered over The Internet. The benefit of this move is to manage The vast amounts of data generated by The various city systems, including water and electricity systems, The waste management system, transportation system, public space management systems, health and education systems, and many more. Furthermore, many smart city applications are time-sensitive and need to quickly analyze data to react promptly to The various events occurring in a city. The new and emerging paradigms of edge and fog computing promise to address big data storage and analysis in The field of smart cities. Here, we review existing service delivery models in smart cities and present our perspective on adopting these two emerging paradigms. We specifically describe The design of a fog-based data pipeline to address The issues of latency and network bandwidth required by time-sensitive smart city applications.
Cloud service providers typically compose their services from a number of elementary services, which are developed in-house or built by third-party providers. Personalization of composite services in mobile environments is an interesting and challenging issue to address, given the opportunity to factor-in diverse user preferences and the plethora of mobile devices at use in multiple contexts. This work proposes a framework to address personalization in mobile cloud-service provisioning. Service personalization and adaptation may be considered at different levels, including the user profile, the mobile device in use, the context of the user and the composition specification. The user's mobile device and external services are typical sources of context information, used in our proposed algorithm to elicit context-aware services. The selection process is guided by quality-of-context criteria that combine cloudservice provider requirements and user preferences. Hence, the paper proposes an integrated framework for enhancing personalized mobile cloud-services, based on a composition approach that adapts context information using a common model of service metadata specification.
Cities around the world are expanding dramatically, with urban population growth reaching nearly 2.5 billion people in urban areas and road traffic growth exceeding 1.2 billion cars by 2050. The economic contribution of the transport sector represents 5% of the GDP in Europe and costs an average of US $482.05 billion in the United States. These figures indicate the rapid rise of industrial cities and the urgent need to move from traditional cities to smart cities. This article provides a survey of different approaches and technologies such as intelligent transportation systems (ITS) that leverage communication technologies to help maintain road users safe while driving, as well as support autonomous mobility through the optimization of control systems. The role of ITS is strengthened when combined with accurate artificial intelligence models that are built to optimize urban planning, analyze crowd behavior and predict traffic conditions. AI-driven ITS is becoming possible thanks to the existence of a large volume of mobility data generated by billions of users through their use of new technologies and online social media. The optimization of urban planning enhances vehicle routing capabilities and solves traffic congestion problems, as discussed in this paper. From an ecological perspective, we discuss the measures and incentives provided to foster the use of mobility systems. We also underline the role of the political will in promoting open data in the transport sector, considered as an essential ingredient for developing technological solutions necessary for cities to become healthier and more sustainable.
GOBASE is a relational database containing integrated sequence, RNA secondary structure and biochemical and taxonomic information about organelles. GOBASE release 6 (summer 2002) contains over 130 000 mitochondrial sequences, an increase of 37% over the previous release, and more than 30 000 chloroplast sequences in a new auxiliary database. To handle this flood of new data, we have designed and implemented GOpop, a Java system for population and verification of the database. We have also implemented a more powerful and flexible user interface using the PHP programming language. http://megasun.bch.umontreal.ca/gobase/gobase.html.
The initial specifications of Web Services cope with the issues of service publishing and service discovery but not with the issue of service selection. Service discovery, handled by UDDI and WSDL, alone is not sufficient to find the most appropriate server that can deliver customers' required quality of service (QoS). In this paper, we consider a broker-based approach to provide QoS support in Web Services and deal with the selection issue. The broker may implement various selection policies that can range from static policies to dynamic ones, which take into account the current state of servers. Besides, Servers may deliver different levels of service to their customers. We model this QoS broker-based scheme by a multi-class queuing model and we study its performance with a probabilistic splitting policy for server selection.
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