47 resultados para wet storage


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BACKGROUND: The quality of platelet concentrates (PCs) is primarily determined in vitro by selective methods (e.g., pH, aggregometry), which provide only limited information on certain platelet (PLT) characteristics. In contrast, proteomic technologies provide a comprehensive overview of the PLT proteome. High interassay variability, however, limits meaningful assessment of samples taken from the same product over time or before and after processing. STUDY DESIGN AND METHODS: Differential in-gel electrophoresis (DIGE) and mass spectrometry were applied to analyze changes in the PLT proteome during storage of PCs. RESULTS: DIGE provides a comprehensive and reproducible overview of the cytoplasmic PLT proteome (median standard deviation of protein spot intensities, 5%-9%). Although 97 percent of cytosolic PLT proteins remained unchanged over a 9-day storage period, septin 2 showed characteristic alterations that preceded by several days more widespread alterations affecting numerous other proteins. Also beta-actin and gelsolin are potential marker proteins for changes in the PLT proteome. Interestingly septin 2 and gelsolin are affected during apoptosis, indicating that apoptosis in PCs may have an impact on PLT storage. CONCLUSION: DIGE is a tool for comprehensively assessing the impact of storage on the global proteome profile of therapeutic PCs. Most of the changes detected are in high-abundance PLT proteins.

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The role of platelets as inflammatory cells is demonstrated by the fact that they can release many growth factors and inflammatory mediators, including chemokines, when they are activated. The best known platelet chemokine family members are platelet factor 4 (PF4) and beta-thromboglobulin (beta-TG), which are synthesized in megakaryocytes, stored as preformed proteins in alpha-granules and released from activated platelets. However, platelets also contain many other chemokines such as interleukin-8 (IL-8), growth-regulating oncogene-alpha(GRO-alpha), epithelial neutrophil-activating protein 78 (ENA-78), regulated on activation normal T expressed and secreted (RANTES), macrophage inflammatory protein-1alpha (MIP-1alpha), and monocyte chemotactic protein-3 (MCP-3). They also express chemokine receptors such as CCR4, CXCR4, CCR1 and CCR3. Platelet activation is a feature of many inflammatory diseases such as heparin-induced thrombocytopenia, acquired immunodeficiency syndrome, and congestive heart failure. Substantial amounts of PF4, beta-TG and RANTES are released from platelets on activation, which may occur during storage. Although very few data are available on the in vivo effects of transfused chemokines, it has been suggested that the high incidence of adverse reactions often observed after platelet transfusions may be attributed to the chemokines present in the plasma of stored platelet concentrates.

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Plant diversity has been shown to influence the water cycle of forest ecosystems by differences in water consumption and the associated effects on groundwater recharge. However, the effects of biodiversity on soil water fluxes remain poorly understood for native tree species plantations in the tropics. Therefore, we estimated soil water fluxes and assessed the effects of tree species and diversity on these fluxes in an experimental native tree species plantation in Sardinilla (Panama). The study was conducted during the wet season 2008 on plots of monocultures and mixtures of three or six tree species. Rainfall and soil water content were measured and evapotranspiration was estimated with the Penman-Monteith equation. Soil water fluxes were estimated using a simple soil water budget model considering water input, output, and soil water and groundwater storage changes and in addition, were simulated using the physically based one-dimensional water flow model Hydrus-1D. In general, the Hydrus simulation did not reflect the observed pressure heads, in that modeled pressure heads were higher compared to measured ones. On the other hand, the results of the water balance equation (WBE) reproduced observed water use patterns well. In monocultures, the downward fluxes through the 200 cm-depth plane were highest below Hura crepitans (6.13 mm day−1) and lowest below Luehea seemannii (5.18 mm day−1). The average seepage rate in monocultures (±SE) was 5.66 ± 0.18 mm day−1, and therefore, significantly higher than below six-species mixtures (5.49 ± 0.04 mm day−1) according to overyielding analyses. The three-species mixtures had an average seepage rate of 5.63 ± 0.12 mm day−1 and their values did not differ significantly from the average values of the corresponding species in monocultures. Seepage rates were driven by the transpiration of the varying biomass among the plots (r = 0.61, p = 0.017). Thus, a mixture of trees with different growth rates resulted in moderate seepage rates compared to monocultures of either fast growing or slow growing tree species. Our results demonstrate that tree-species specific biomass production and tree diversity are important controls of seepage rates in the Sardinilla plantation during the wet season.

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Deep geological storage of radioactive waste foresees cementitious materials as reinforcement of tunnels and as backfill. Bentonite is proposed to enclose spent fuel drums, and as drift seals. The emplacement of cementitious material next to clay material generates an enormous chemical gradient in pore water composition that drives diffusive solute transport. Laboratory studies and reactive transport modeling predict significant mineral alteration at and near interfaces, mainly resulting in a decrease of porosity in bentonite. The goal of this project is to characterize and quantify the cement/bentonite skin effects spatially and temporally in laboratory experiments. A newly developed mobile X-ray transparent core infiltration device was used, which allows performing X-ray computed tomography (CT) periodically without interrupting a running experiment. A pre-saturated cylindrical MX-80 bentonite sample (1920 kg/m3 average wet density) is subjected to a confining pressure as a constant total pressure boundary condition. The infiltration of a hyperalkaline (pH 13.4), artificial OPC (ordinary Portland cement) pore water into the bentonite plug alters the mineral assemblage over time as an advancing reaction front. The related changes in X-ray attenuation values are related to changes in phase densities, porosity and local bulk density and are tracked over time periodically by non-destructive CT scans.

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Decision making in honeybees is based on in- formation which is acquired and processed in order to make choices between two or more al- ternatives. These choices lead to the expression of optimal behaviour strategies such as floral constancy. Optimal foraging strategies such as floral constancy improve a colony’s chances of survival, however to our knowledge, there has been no research on decision making based on optimal storage strategies. Here we show, using diagnostic radioentomology, that decision mak- ing in storer bees is influenced by nectar sugar concentrations and that, within 48 hours of col- lection, honeybees workers store carbohydrates in groups of cells with similar sugar concentra- tions in a nonrandom way. This behaviour, as evidenced by patchy spatial cell distributions, would help to hasten the ripening process by reducing the distance between cells of similar sugar concentrations. Thus, colonies which ex- hibit optimal storage strategies such as these would have an evolutionary advantage and im- prove colony survival expectations over less efficient colonies and it should be plausible to select colonies that exhibit these preferred traits.

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The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN) is a EU FP7 Large-scale Integrating Project (IP) funded by the European Commission. MCN project was launched in November 2012 for the period of 36 month. In total top-tier 19 partners from industry and academia commit to jointly establish the vision of Mobile Cloud Networking, to develop a fully cloud-based mobile communication and application platform.

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Storing and recalling spiking sequences is a general problem the brain needs to solve. It is, however, unclear what type of biologically plausible learning rule is suited to learn a wide class of spatiotemporal activity patterns in a robust way. Here we consider a recurrent network of stochastic spiking neurons composed of both visible and hidden neurons. We derive a generic learning rule that is matched to the neural dynamics by minimizing an upper bound on the Kullback–Leibler divergence from the target distribution to the model distribution. The derived learning rule is consistent with spike-timing dependent plasticity in that a presynaptic spike preceding a postsynaptic spike elicits potentiation while otherwise depression emerges. Furthermore, the learning rule for synapses that target visible neurons can be matched to the recently proposed voltage-triplet rule. The learning rule for synapses that target hidden neurons is modulated by a global factor, which shares properties with astrocytes and gives rise to testable predictions.

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This paper deals with scheduling batch (i.e., discontinuous), continuous, and semicontinuous production in process industries (e.g., chemical, pharmaceutical, or metal casting industries) where intermediate storage facilities and renewable resources (processing units and manpower) of limited capacity have to be observed. First, different storage configurations typical of process industries are discussed. Second, a basic scheduling problem covering the three above production modes is presented. Third, (exact and truncated) branch-and-bound methods for the basic scheduling problem and the special case of batch scheduling are proposed and subjected to an experimental performance analysis. The solution approach presented is flexible and in principle simple, and it can (approximately) solve relatively large problem instances with sufficient accuracy.

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This paper is concerned with the modelling of storage configurations for intermediate products in process industries. Those models form the basis of algorithms for scheduling chemical production plants. Different storage capacity settings (unlimited, finite, and no intermediate storage), storage homogeneity settings (dedicated and shared storage), and storage time settings (unlimited, finite, and no wait) are considered. We discuss a classification of storage constraints in batch scheduling and show how those constraints can be integrated into a general production scheduling model that is based on the concept of cumulative resources.

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