975 resultados para PROTEIN NETWORKS
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3D in vitro model systems that are able to mimic the in vivo microenvironment are now highly sought after in cancer research. Antheraea mylitta silk fibroin protein matrices were investigated as potential biomaterial for in vitro tumor modeling. We compared the characteristics of MDA-MB-231 cells on A. mylitta, Bombyx mori silk matrices, Matrigel, and tissue culture plates. The attachment and morphology of the MDA-MB-231 cell line on A. mylitta silk matrices was found to be better than on B. mori matrices and comparable to Matrigel and tissue culture plates. The cells grown in all 3D cultures showed more MMP-9 activity, indicating a more invasive potential. In comparison to B. mori fibroin, A. mylitta fibroin not only provided better cell adhesion, but also improved cell viability and proliferation. Yield coefficient of glucose consumed to lactate produced by cells on 3D A. mylitta fibroin was found to be similar to that of cancer cells in vivo. LNCaP prostate cancer cells were also cultured on 3D A. mylitta fibroin and they grew as clumps in long term culture. The results indicate that A. mylitta fibroin scaffold can provide an easily manipulated microenvironment system to investigate individual factors such as growth factors and signaling peptides, as well as evaluation of anticancer drugs.
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We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.
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Internationally the railway industry is facing a severe shortage of engineers with high level, relevant, profession and technical knowledge and abilities, in particular amongst engineers involved in the design, construction and maintenance of railway infrastructure. A unique graduate level program has been created to meet that global need via a fully online, distance education format. The development and operation of this Master of Engineering degree is proposed as a model of the process needed for the industry-relevance, flexible delivery, international networking, and professional development required for a successful graduate engineering program in the 21st century. In particular, the paper demonstrates how a mix of new and more familiar technologies are utilised through a variety of tasks to overcome the huge distances and multiple time zones that separate the participants across a growing number of countries, successfully achieving close and sustained interaction amongst the participants and railway experts.
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As the world’s rural populations continue to migrate from farmland to sprawling cities, transport networks form an impenetrable maze within which monocultures of urban form erupt from the spaces in‐between. These urban monocultures are as problematic to human activity in cities as cropping monocultures are to ecosystems in regional landscapes. In China, the speed of urbanisation is exacerbating the production of mono‐functional private and public spaces. Edges are tightly controlled. Barriers and management practices at these boundaries are discouraging the formation of new synergistic relationships, critical in the long‐term stability of ecosystems that host urban habitats. Some urban planners, engineers, urban designers, architects and landscape architects have recognised these shortcomings in contemporary Chinese cities. The ideology of sustainability, while critically debated, is bringing together thinking people in these and other professions under the umbrella of an ecological ethic. This essay aims to apply landscape ecology theory, a conceptual framework used by many professionals involved in land development processes, to a concept being developed by BAU International called Networks Cities: a city with its various land uses arranged in nets of continuity, adjacency, and superposition. It will consider six lesser‐known concepts in relation to creating enhanced human activity along (un)structured edges between proposed nets and suggest new frontiers that might be challenged in an eco‐city. Ecological theory suggests that sustaining biodiversity in regions and landscapes depends on habitat distribution patterns. Flora and fauna biologists have long studied edge habitats and have been confounded by the paradox that maximising the breadth of edges is detrimental to specialist species but favourable to generalist species. Generalist species of plants and animals tolerate frequent change in the landscape, frequenting two or more habitats for their survival. Specialist species are less tolerant of change, having specific habitat requirements during their life cycle. Protecting species richness then may be at odds with increasing mixed habitats or mixed‐use zones that are dynamic places where diverse activities occur. Forman (1995) in his book Land Mosaics however argues that these two objectives of land use management are entirely compatible. He postulates that an edge may be comprised of many small patches, corridors or convoluting boundaries of large patches. Many ecocentrists now consider humans to be just another species inhabiting the ecological environments of our cities. Hence habitat distribution theory may be useful in planning and designing better human habitats in a rapidly urbanising context like China. In less‐constructed environments, boundaries and edges provide important opportunities for the movement of multi‐habitat species into, along and from adjacent land use areas. For instance, invasive plants may escape into a national park from domestic gardens while wildlife may forage on garden plants in adjoining residential areas. It is at these interfaces that human interactions too flow backward and forward between land types. Spray applications of substances by farmers on cropland may disturb neighbouring homeowners while suburban residents may help themselves to farm produce on neighbouring orchards. Edge environments are some of the most dynamic and contested spaces in the landscape. Since most of us require access to at least two or three habitats diurnally, weekly, monthly or seasonally, their proximity to each other becomes critical in our attempts to improve the sustainability of our cities.
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The question posed in this chapter is: To what extent does current education theory and practice prepare graduates for the creative economy? We first define what we mean by the term creative economy, explain why we think it is a significant point of focus, derive its key features, describe the human capital requirements of these features, and then discuss whether current education theory and practice are producing these human capital requirements. The term creative economy can be critiqued as a shibboleth, but as a high level metaphor, it nevertheless has value in directing us away from certain sorts of economic activity and toward other kinds. Much economic activity is in no way creative. If I have a monopoly on some valued resource, I do not need to be creative. Other forms of economic activity are intensely creative. If I have no valued resources, I must create something that is valued. At its simplest and yet most profound, the idea of a creative economy suggests a capacity to compete based on engaging in a gainful activity that is different from everyone else’s, rather than pursuing the same endeavor more competitively than everyone else. The ability to differentiate on novelty is key to the concept of creative economy and key to our analysis of education for this economy. Therefore, we follow Potts and Cunningham (2008, p. 18) and Potts, Cunningham, Hartley, and Ormerod (2008) in their discussion of the economic significance of the creative industries and see the creative economy not as a sector but as a set of economic processes that act on the economy as a whole to invigorate innovation based growth. We see the creative economy as suffused with all industry rather than as a sector in its own right. These economic processes are essentially concerned with the production of new ideas that ultimately become new products, service, industry sectors, or, in some cases, process or product innovations in older sectors. Therefore, our starting point is that modern economies depend on innovation, and we see the core of innovation as new knowledge of some kind. We commence with some observations about innovation.
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The explosion in use of online social networks is an important phenomenon that provides a new set of entrepreneurial opportunities. Emerging musicians have been among the first to exploit this new market opportunity – and indeed, many have used it successfully. A recent study Carter (2009) reveals that artists who earned the most returns had an online presence on multiple social online sites and services such as MySpace and Facebook. These web pages are leveraged to build fan bases and develop different types of revenue streams. Yet, little is currently known about discovery or exploitation of such opportunities.
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This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.
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Large mysticete whales represent a unique challenge for chemical risk assessment. Few epidemiological investigations are possible due to the low incidence of adult stranding events. Similarly their often extreme life-history adaptations of prolonged migration and fasting challenge exposure assumptions. Molecular biomarkers offer the potential to complement information yielded through tissue chemical analysis, as well as providing evidence of a molecular response to chemical exposure. In this study we confirm the presence of cytochrome P450 reductase (CPR) and cytochrome P450 isoenzyme 1A1 (CYP1A1) in epidermal tissue of southern hemisphere humpback whales (Megaptera novaeangliae). The detection of CYP1A1 in the integument of the humpback whale affords the opportunity for further quantitative non-destructive investigations of enzyme activity as a function of chemical stress.
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Archaeal transcription utilizes a complex multisubunit RNA polymerase and the basal transcription factors TBP and TF(II)B, closely resembling its eukaryal counterpart. We have uncovered a tight physical and functional interaction between RNA polymerase and the single-stranded DNA-binding protein SSB in Sulfolobus solfataricus. SSB stimulates transcription from promoters in vitro under TBP-limiting conditions and supports transcription in the absence of TBP. SSB also rescues transcription from repression by reconstituted chromatin. We demonstrate the potential for promoter melting by SSB, suggesting a plausible basis for the stimulation of transcription. This stimulation requires both the single-stranded DNA-binding domain and the acidic C-terminal tail of the SSB. The tail forms a stable interaction with RNA polymerase. These data reveal an unexpected role for single-stranded DNA-binding proteins in transcription in archaea.
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Single-strand DNA (ssDNA)-binding proteins (SSBs) are ubiquitous and essential for a wide variety of DNA metabolic processes, including DNA replication, recombination, DNA damage detection and repair1. SSBs have multiple roles in binding and sequestering ssDNA, detecting DNA damage, stimulating nucleases, helicases and strand-exchange proteins, activating transcription and mediating protein–protein interactions. In eukaryotes, the major SSB, replication protein A (RPA), is a heterotrimer1. Here we describe a second human SSB (hSSB1), with a domain organization closer to the archaeal SSB than to RPA. Ataxia telangiectasia mutated (ATM) kinase phosphorylates hSSB1 in response to DNA double-strand breaks (DSBs). This phosphorylation event is required for DNA damage-induced stabilization of hSSB1. Upon induction of DNA damage, hSSB1 accumulates in the nucleus and forms distinct foci independent of cell-cycle phase. These foci co-localize with other known repair proteins. In contrast to RPA, hSSB1 does not localize to replication foci in S-phase cells and hSSB1 deficiency does not influence S-phase progression. Depletion of hSSB1 abrogates the cellular response to DSBs, including activation of ATM and phosphorylation of ATM targets after ionizing radiation. Cells deficient in hSSB1 exhibit increased radiosensitivity, defective checkpoint activation and enhanced genomic instability coupled with a diminished capacity for DNA repair. These findings establish that hSSB1 influences diverse endpoints in the cellular DNA damage response.
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Optimal scheduling of voltage regulators (VRs), fixed and switched capacitors and voltage on customer side of transformer (VCT) along with the optimal allocaton of VRs and capacitors are performed using a hybrid optimisation method based on discrete particle swarm optimisation and genetic algorithm. Direct optimisation of the tap position is not appropriate since in general the high voltage (HV) side voltage is not known. Therefore, the tap setting can be determined give the optimal VCT once the HV side voltage is known. The objective function is composed of the distribution line loss cost, the peak power loss cost and capacitors' and VRs' capital, operation and maintenance costs. The constraints are limits on bus voltage and feeder current along with VR taps. The bus voltage should be maintained within the standard level and the feeder current should not exceed the feeder-rated current. The taps are to adjust the output voltage of VRs between 90 and 110% of their input voltages. For validation of the proposed method, the 18-bus IEEE system is used. The results are compared with prior publications to illustrate the benefit of the employed technique. The results also show that the lowest cost planning for voltage profile will be achieved if a combination of capacitors, VRs and VCTs is considered.
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PROBLEM Chlamydia trachomatis is a significant worldwide health problem, and the often-asymptomatic disease can result in infertility. To develop a successful vaccine, a complete understanding of the immune response to chlamydial infection and development of genital tract pathology is required. METHOD OF STUDY We utilized the murine genital model of chlamydial infection. Mice were immunized with chlamydial major outer membrane protein, and vaginal lavage was assessed for the presence of neutralizing antibodies. These samples were then pre-incubated with Chlamydia muridarum and administered to the vaginal vaults of immune-competent female BALB/c mice to determine the effect on infection. RESULTS The administration of C. muridarum in conjunction with neutralizing antibodies reduced the numbers of mice infected, but a surprising finding was that this accelerated the development of severe oviduct pathology. CONCLUSION Antibodies play an under-recognized role in chlamydial infection and pathology development, which possibly involves interaction with Th1 immunity.
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Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.