259,390 research outputs found

    Insights into the structure and dynamics of lysyl oxidase propeptide, a flexible protein with numerous partners

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    Lysyl oxidase (LOX) catalyzes the oxidative deamination of lysine and hydroxylysine residues in collagens and elastin, which is the first step of the cross-linking of these extracellular matrix proteins. It is secreted as a proenzyme activated by bone morphogenetic protein-1, which releases the LOX catalytic domain and its bioactive N-terminal propeptide. We characterized the recombinant human propeptide by circular dichroism, dynamic light scattering, and small-angle X-ray scattering (SAXS), and showed that it is elongated, monomeric, disordered and flexible (Dmax: 11.7 nm, Rg: 3.7 nm). We generated 3D models of the propeptide by coarse-grained molecular dynamics simulations restrained by SAXS data, which were used for docking experiments. Furthermore, we have identified 17 new binding partners of the propeptide by label-free assays. They include four glycosaminoglycans (hyaluronan, chondroitin, dermatan and heparan sulfate), collagen I, cross-linking and proteolytic enzymes (lysyl oxidase-like 2, transglutaminase-2, matrix metalloproteinase-2), a proteoglycan (fibromodulin), one growth factor (Epidermal Growth Factor, EGF), and one membrane protein (tumor endothelial marker-8). This suggests new roles for the propeptide in EGF signaling pathway

    From user goals to process-based service compositions: A flexible semantic-based approach

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    International audienceComplex user's needs often require heterogeneous services to be combined together. In this paper, we explore a novel approach to enable flexible and dynamic composition of heterogeneous services for end users who are usually not familiar with technical process models. End-users are only required to model their goals and semantic reasoning is used for the composition itself. The possible service compositions are expressed in BPMN in order to be then processed by a BPMN engine. Since the composition is built on-the-fly, this approach avoids static linking of services and therefore is much more flexible

    A flexible model for dynamic linking in Java and C#

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    Dynamic linking supports flexible code deployment, allowing partially linked code to link further code on the fly, as needed. Thus, end-users enjoy the advantage of automatically receiving any updates, without any need for any explicit actions on their side, such as re-compilation, or re-linking. On the down side, two executions of a program may link in different versions of code, which in some cases causes subtle errors, and may mystify end-users. Dynamic linking in Java and C# are similar: the same linking phases are involved, soundness is based on similar ideas, and executions which do not throw linking errors give the same result. They are, however, not identical: the linking phases are combined differently, and take place in different order. Consequently, linking errors may be detected at different times by Java and C# runtime systems. We develop a non-deterministic model, which describes the behaviour of both Java and C# program executions. The nondeterminism allows us to describe the design space, to distill the similarities between the two languages, and to use one proof of soundness for both. We also prove that all execution strategies are equivalent with respect to terminating executions that do not throw link errors: they give the same results

    Visual and interactive exploration of point data

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    Point data, such as Unit Postcodes (UPC), can provide very detailed information at fine scales of resolution. For instance, socio-economic attributes are commonly assigned to UPC. Hence, they can be represented as points and observable at the postcode level. Using UPC as a common field allows the concatenation of variables from disparate data sources that can potentially support sophisticated spatial analysis. However, visualising UPC in urban areas has at least three limitations. First, at small scales UPC occurrences can be very dense making their visualisation as points difficult. On the other hand, patterns in the associated attribute values are often hardly recognisable at large scales. Secondly, UPC can be used as a common field to allow the concatenation of highly multivariate data sets with an associated postcode. Finally, socio-economic variables assigned to UPC (such as the ones used here) can be non-Normal in their distributions as a result of a large presence of zero values and high variances which constrain their analysis using traditional statistics. This paper discusses a Point Visualisation Tool (PVT), a proof-of-concept system developed to visually explore point data. Various well-known visualisation techniques were implemented to enable their interactive and dynamic interrogation. PVT provides multiple representations of point data to facilitate the understanding of the relations between attributes or variables as well as their spatial characteristics. Brushing between alternative views is used to link several representations of a single attribute, as well as to simultaneously explore more than one variable. PVT’s functionality shows how the use of visual techniques embedded in an interactive environment enable the exploration of large amounts of multivariate point data
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