Secretome-based proteomics reveals sulindac-modulated proteins released from colon cancer cells

Although experiments in rodents and human population-based studies have demonstrated the efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) such as sulindac in colorectal cancer (CRC) prevention, a detailed knowledge of the underlying mechanism of action of this drug is limited. To better understand the chemopreventitive effects of sulindac, especially early sulindac-induced apoptotic events, we used the CRC cell line LIM1215 as an experimental model, focusing on proteins secreted into the LIM1215 culture medium - i.e., the secretome. This subproteome comprises both soluble-secreted proteins and exosomes (30-100?nm diameter membrane vesicles released by several cell types). Selected secretome proteins whose expression levels were dysregulated by 1?mM sulindac treatment over 16?h were analyzed using 2-D DIGE, cytokine array, Western blotting, and MS. Overall, 150 secreted proteins were identified, many of which are implicated in molecular and cellular functions such as cell proliferation, differentiation, adhesion, invasion, angiogenesis, metastasis, and apoptosis. Our secretome-based proteomic studies have identified several secreted modulators of sulindac-induced apoptosis action (e.g., Mac-2 binding protein, Alix, 14-3-3 isoforms, profilin-1, calumenin/Cab45 precursors, and the angiogenic/tumor growth factors interleukin 8 (IL-8) and growth related oncogene (GRO-α)) that are likely to improve our understanding of the chemopreventitive action of this NSAID in CRC.     

Main-Chain Nematic Side-Chain Smectic Composite Liquid Crystalline Elastomers

A composite liquid crystalline elastomer is designed, combining main-chain and side-chain mesogenic polymers in the network, and resulting in micro-phase separated regions of nematic and smectic ordering in the macroscopically homogeneous elastomer. A range of different fractions of the components is explored, from fully nematic main-chain system, across to fully smectic side-chain elastomer. Thermal phase transitions of both phases coexisting in the material are detected by calorimetry, and the nematic/smectic structure investigated by X-ray scattering. The tensile stress–strain data reveal the key effect of such a multi-phase composite, where the nematic fraction adds ductility while the smectic fraction increases the modulus and mechanical stiffness. Varying the composition, the authors are able to optimize the mechanical properties of this material type.     

The synaptology of 2 types of neurons in the sympathetic ganglia of the frog

In 1996 the immunization of children against measles, mumps and rubella with combined vaccine Trimovax ("Pasteur Mérieux Connaught", France) was carried out in the Republic of Belarus. The reactogenicity of the vaccine was studied in 372 children. To evaluate immunological effectiveness, the sera of 324 children were used. Postvaccinal reactions of different intensity were registered in 5.6% of the children; of these, 1.3% exhibited severe reactions. Among the vaccinees, protective titers of antibodies to measles were found in 97.6% to mumps, in 93.8% and to rubella, in 96.0% of the children. Antibodies to all three components of the vaccine were present mainly in high and moderate titers. The results thus obtained indicate that, Trimovax was well tolerated and proved to be immunologically active.     

Parametric algorithms for 2-cyclic robot scheduling with interval processing times

Consider an m-machine production line for processing identical parts served by a mobile robot. The problem is to find the minimum cycle time for 2-cyclic schedules, that is, schedules in which exactly two parts enter and two parts leave the production line during each cycle. This work treats a special case of the 2-cyclic robot scheduling problem when the robot route is given and operation durations are chosen from prescribed intervals. A strongly polynomial algorithm of time complexity O(m ⁸log m) is proposed.     

Audlib: a configurable,high‐fidelity application audit mechanism

In this paper, we introduce Audlib, an extendable tool for generating security‐relevant information on Unix systems. Audlib is a wrapper environment that generates application level audit information from existing executable programs. Audlib is not a detection system, instead it is designed to supplement existing audit systems and work transparently with them. Audlib records information that is not presently available from existing kernel‐level audit sources. Here, we describe the design of the Audlib framework and the information it provides. We compare auditing the actions of a web server with Audlib to existing kernel audit sources and show that we have 2–4 times the throughput of Linux auditd and less than half the performance overhead of Solaris BSM while collecting detailed information about the server's execution. Although Audlib is focused on recording security information, this technique can be used to collect data for a wide variety of purposes including profiling, dependency analysis, and debugging. Copyright © 2010 John Wiley & Sons, Ltd.     

A Fast Explicit Operator Splitting Method for Passive Scalar Advection

The dispersal and mixing of scalar quantities such as concentrations or thermal energy are often modeled by advection-diffusion equations. Such problems arise in a wide variety of engineering, ecological and geophysical applications. In these situations a quantity such as chemical or pollutant concentration or temperature variation diffuses while being transported by the governing flow. In the passive scalar case, this flow prescribed and unaffected by the scalar. Both steady laminar and complex (chaotic, turbulent or random) time-dependent flows are of interest and such systems naturally lead to questions about the effectiveness of the stirring to disperse and mix the scalar. The development of reliable numerical methods for advection-diffusion equations is crucial for understanding their properties, both physical and mathematical. In this paper, we extend a fast explicit operator splitting method, recently proposed in (A. Chertock, A. Kurganov, G. Petrova, Int. J. Numer. Methods Fluids 59:309–332, 2009), for solving deterministic convection-diffusion equations, to the problems with random velocity fields and singular source terms. A superb performance of the method is demonstrated on several two-dimensional examples.     

Visualization of diversity in large multivariate data sets

Understanding the diversity of a set of multivariate objects is an important problem in many domains, including ecology, college admissions, investing, machine learning, and others. However, to date, very little work has been done to help users achieve this kind of understanding. Visual representation is especially appealing for this task because it offers the potential to allow users to efficiently observe the objects of interest in a direct and holistic way. Thus, in this paper, we attempt to formalize the problem of visualizing the diversity of a large (more than 1000 objects), multivariate (more than 5 attributes) data set as one worth deeper investigation by the information visualization community. In doing so, we contribute a precise definition of diversity, a set of requirements for diversity visualizations based on this definition, and a formal user study design intended to evaluate the capacity of a visual representation for communicating diversity information. Our primary contribution, however, is a visual representation, called the Diversity Map, for visualizing diversity. An evaluation of the Diversity Map using our study design shows that users can judge elements of diversity consistently and as or more accurately than when using the only other representation specifically designed to visualize diversity.     

Interleaving solving and elicitation of constraint satisfaction problems based on expected cost

We consider Constraint Satisfaction Problems in which constraints can be initially incomplete, where it is unknown whether certain tuples satisfy the constraint or not. We assume that we can determine the satisfaction of such an unknown tuple, i.e., find out whether this tuple is in the constraint or not, but doing so incurs a known cost, which may vary between tuples. We also assume that we know the probability of an unknown tuple satisfying a constraint. We define algorithms for this problem, based on backtracking search. Specifically, we consider a simple iterative algorithm based on a cost limit on the unknowns that may be determined, and a more complex algorithm that delays determining an unknown in order to estimate better whether doing so is worthwhile. We show experimentally that the more sophisticated algorithms can greatly reduce the average cost.