Non-Synonymous Single Nucleotide Polymorphisms in the P2X Receptor Genes: Association with Diseases,Impact on Receptor Functions and Potential Use as Diagnosis Biomarkers

P2X receptors are Ca²⁺-permeable cationic channels in the cell membranes, where they play an important role in mediating a diversity of physiological and pathophysiological functions of extracellular ATP. Mammalian cells express seven P2X receptor genes. Single nucleotide polymorphisms (SNPs) are widespread in the P2RX genes encoding the human P2X receptors, particularly the human P2X7 receptor. This article will provide an overview of the non-synonymous SNPs (NS-SNPs) that have been associated with or implicated in altering the susceptibility to pathologies or disease conditions, and discuss the consequences of the mutations resulting from such NS-SNPs on the receptor functions. Disease-associated NS-SNPs in the P2RX genes have been valuable in understanding the disease etiology and the receptor function, and are promising as biomarkers to be used for the diagnosis and development of stratified therapeutics.     

Chemical Composition and Surface Properties of Paper Mill Sludge and their Impact on High Density Polyethylene (HDPE) Composites

A comparative study was conducted using paper mill sludge from three different pulping processes at two primary sludge (PS) to secondary sludge (SS) ratios to better understand the role of PS and SS in the development of wood/high-density polyethylene (HDPE) composite properties. Sludge samples from a thermomechanical (TMP), chemico-thermomechanical (CTMP), and Kraft pulping process were used at three proportions (20, 30, and 40%) to produce different composites. Pulp and combined sludge samples were characterized by conventional chemical analysis and FTIR spectroscopy. FTIR spectroscopy enabled the characterization of the inorganic content in the sludge. Results showed that the variation in composite properties according to sludge type could be explained by the chemical composition, regardless of pulping process or SS:PS ratio. Ash and cellulose content were the dominant factors in explaining the composite mechanical properties, and nitrogen content, although low, was the dominant factor in explaining composite toughness.     

Spatially homogeneous gelation in liquid composite molding

On‐line mixing of the resin with its curing agents prior to injection into a mold is a common industrial technique for fabricating composite parts. For vinyl‐ester resins that cure via free radical polymerization, the concentrations of retarder, accelerator, and initiator are pre‐selected and cannot be changed during the injection. Hence, the resin that enters the mold the earliest has cured longer than the resin that enters the mold later, since the gel time for the resin is the same, owing to the fixed ratio of the curing agents. This approach leads to inhomogeneous cure of the resin and consequently to longer residence time of the resin in the mold. It requires an additional 50 to 75 percent of the filling time before a part can be de‐molded. In this study, it is shown that by adjusting the concentration of curing agents during the injection, a more homogeneous gel time throughout the mold can be achieved. The time to de‐mold is reduced to 18‐24 percent of the filling time. Sensors that measure the conductivity of the resin were used to detect the location and monitor the cure of vinyl‐ester. This approach could be extended to other resin systems to control the spatial curing of the resin in the mold.     

Toward simple control for complex, autonomous robotic applications: combining discrete and rhythmic motor primitives

Vertebrates are able to quickly adapt to new environments in a very robust, seemingly effortless way. To explain both this adaptivity and robustness, a very promising perspective in neurosciences is the modular approach to movement generation: Movements results from combinations of a finite set of stable motor primitives organized at the spinal level. In this article we apply this concept of modular generation of movements to the control of robots with a high number of degrees of freedom, an issue that is challenging notably because planning complex, multidimensional trajectories in time-varying environments is a laborious and costly process. We thus propose to decrease the complexity of the planning phase through the use of a combination of discrete and rhythmic motor primitives, leading to the decoupling of the planning phase (i.e. the choice of behavior) and the actual trajectory generation. Such implementation eases the control of, and the switch between, different behaviors by reducing the dimensionality of the high-level commands. Moreover, since the motor primitives are generated by dynamical systems, the trajectories can be smoothly modulated, either by high-level commands to change the current behavior or by sensory feedback information to adapt to environmental constraints. In order to show the generality of our approach, we apply the framework to interactive drumming and infant crawling in a humanoid robot. These experiments illustrate the simplicity of the control architecture in terms of planning, the integration of different types of feedback (vision and contact) and the capacity of autonomously switching between different behaviors (crawling and simple reaching).     

Using Kestrel and XMPP to Support the STAR Experiment in the Cloud

This paper presents the results and experiences of adapting and improving the Many-Task Computing (MTC) framework Kestrel for use with bag of tasks applications and the STAR experiment in particular. Kestrel is a lightweight, highly available job scheduling framework for Virtual Organization Clusters (VOCs) constructed in the cloud. Kestrel uses the Extensible Message and Presence Protocol (XMPP) for increasing MTC platform scalability and mitigating faults in Wide Area Network (WAN) communications. Kestrel’s architecture is based upon pilot job frameworks used extensively in Grid computing, with fault-tolerant communications inspired by command-and-control botnets. The extensibility of XMPP has allowed development of protocols for identifying manager nodes, discovering the capabilities of worker agents, and for distributing tasks. Presence notifications provided by XMPP allow Kestrel to monitor the global state of the pool and to perform task dispatching based on worker availability. Since its inception, Kestrel has been modified based on its performance managing operational scientific workloads from the STAR group at Brookhaven National Laboratories. STAR provided a virtual machine image with applications for simulating proton collisions using PYTHIA and GEANT3. A Kestrel-based Virtual Organization Cluster, created on top of Clemson University’s Palmetto cluster, CERN, and Amazon EC2, was able to provide over 400,000 CPU hours of computation over the course of a month using an average of 800 virtual machine instances every day, generating nearly seven terabytes of data and the largest PYTHIA production run that STAR has achieved to date.     

Compatibilization of polypropylene/polyamide 6 blends using new synthetic nanosized talc fillers: Morphology,thermal, and mechanical properties

New synthetic nanotalc and a commercially available natural fine talc (Luzenac© A3) were chosen in order to establish a comparative study in terms of their contributions on the improvement of the morphology as well as the final properties of PP/PA6 blends prepared by melt processing. At first, the TEM and SEM micrographs showed that both talc particles have a preferential affinity for the more hydrophilic polyamide 6 phase compared with the continuous PP matrix. Moreover, in both cases, the addition of talc fillers induces a significant decrease of the size of the PA6 domains but the better compatibilization efficiency was obtained in the presence of synthetic nanotalc particles. In this work, the positive change induced by the talc nanofillers on the crystallization kinetics and final morphology was highlighted. In addition, compared with natural talc, a highly level of dispersion of talc layers has been obtained with the synthetic nanotalc which is more hydrophilic. Thus, this better dispersion greatly improves the thermal stability of PP/PA6 blends and leads to better mechanical properties (+ 40% in Young's modulus). © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40453.     

Assessing regional intake fractions in North America

This paper develops the IMPACT North America model, a spatially resolved multimedia, multi-pathway, fate, exposure and effect model that includes indoor and urban compartments. IMPACT North America allows geographic differentiation of population exposure of toxic emissions for comparative risk assessment and life cycle impact assessment within U.S. and Canada. It looks at air, water, soil, sediment and vegetation media, and divides North America into several hundred zones. It is nested within a single world box to account for emissions leaving North America. It is a multi-scale model, covering three different spatial scales — indoor, urban and regional — in all zones in North America. Model results are evaluated against monitored emissions and concentrations of benzo(a)pyrene, 2,3,7,8-TCDD and mercury. Most of the chemical concentrations predicted by the model fall within two orders of magnitude of the monitored data. The model shows that urban intake fractions are one order of magnitude higher than rural intake fractions. The model application and importance is demonstrated by a case study on spatially-distributed emissions over the life cycle of diesel fuel. Depending on population densities and agricultural intensities, intake fractions can vary by eight orders of magnitudes, and even limited indoor emissions can lead to intakes comparable to those from outdoor emissions. To accurately assess these variations in intake fraction, we require the essential three original features described in the present paper: i) inclusion of the continental model within a world box for persistent pollutants, ii) addition of an urban box for short- and medium-lived substances (for grid size larger than 100 km), and iii) assess indoor emissions. This model can therefore be used to screen chemicals and assess regionalized intake fractions within North America for population-based human exposure assessment, life cycle impact assessment, and comparative risk assessment. The model can be downloaded at http://www.impactmodeling.org.     

Unexpected microgravity effect during the self-organization of silicalite-1 nanoslabs

Silicalite-1 zeolite was synthesized from clear solutions prepared from tetraethylorthosilicate, tetrapropylammonium hydroxide and water. Crystallization was performed in a unit composing 30 miniautoclaves programmed to heat to 145 or 155°C and to quench sequentially. The synthesis under microgravity condition was conducted aboard the MAXUS 4 sounding rocket. A reference experiment under normal gravity was executed using the same temperature and time profiles. The evolution of the particle size populations was determined using X-ray scattering. The microgravity condition significantly slowed aggregation but did not change the overall aggregation mechanism. Surprisingly, aggregation of the smallest entities, expected to be the least influenced by absence of convection, were most retarded under microgravity conditions. A considerable fraction of the original nanoslabs persisted even at the end of crystallization. An explanation for this unusual microgravity effect was found in the observation of strong physical interaction between groups of individual particles.     

Parameter identification of hardening laws for bulk metal forming using experimental and numerical approach

The simulative prediction of material behaviour in forming processes necessitates a precise determination of the material parameters. The present work focusses on the modelling of the isostatic part of the flow stress using a flow curve with an analytical suppression of the influence of friction and an adequate analytical law. The experimental data are obtained from isothermal upsetting tests with various upsetting ratios. The different ratios are based on a variation of the height of the sample, remaining the diameter constant. For the proposed flow stress law five parameters are identified. In order to decrease the number of function evaluations, a new reduction model method based on both analytical and sequential quadratic programming (SQP) algorithms is developed and applied to identify flow stress law parameters. A comparison with traditional SQP algorithm is also done. A 3D finite element model is built in order to simulate a side pressing test and an experimental validation is done. As numerical results fit very well experimental data, the proposed model achieves a precise prediction of the flow behaviour. The identification of the other parts of the model (i.e. dependencies on strain-rate and temperature) are conducted in further works.