Histamine increases sphingosine kinase-1 expression and activity in the human arterial endothelial cell line EA.hy 926 by a PKC-alpha-dependent mechanism

Sphingosine 1-phosphate (S1P) is a potent mitogenic signal generated from sphingosine by the action of sphingosine kinases (SKs). In this study, we show that in the human arterial endothelial cell line EA.hy 926 histamine induces a time-dependent upregulation of the SK-1 mRNA and protein expression which is followed by increased SK-1 activity. A similar upregulation of SK-1 is also observed with the direct protein kinase C activator 12-O-tetradecanoylphorbol-13-acetate (TPA). In contrast, SK-2 activity is not affected by neither histamine nor TPA. The increased SK-1 protein expression is due to stimulated de novo synthesis since cycloheximide inhibited the delayed SK-1 protein upregulation. Moreover, the increased SK-1 mRNA expression results from an increased promoter activation by histamine and TPA. In mechanistic terms, the transcriptional upregulation of SK-1 is dependent on PKC and the extracellular signal-regulated protein kinase (ERK) cascade since staurosporine and the MEK inhibitor U0126 abolish the TPA-induced SK-1 induction. Furthermore, the histamine effect is abolished by the H1-receptor antagonist diphenhydramine, but not by the H2-receptor antagonist cimetidine. Parallel to the induction of SK-1, histamine and TPA stimulate an increased migration of endothelial cells, which is prevented by depletion of the SK-1 by small interfering RNA (siRNA). To appoint this specific cell response to a specific PKC isoenzyme, siRNA of PKC-alpha, -delta, and -epsilon were used to selectively downregulate the respective isoforms. Interestingly, only depletion of PKC-alpha leads to a complete loss of TPA- and histamine-triggered SK-1 induction and cell migration. In summary, these data show that PKC-alpha activation in endothelial cells by histamine-activated H1-receptors, or by direct PKC activators leads to a sustained upregulation of the SK-1 protein expression and activity which, in turn, is critically involved in the mechanism of endothelial cell migration.

Intra-annual radial growth and water relations of trees - implications towards a growth mechanism

There is a missing link between tree physiological and wood-anatomical knowledge which makes it impossible mechanistically to explain and predict the radial growth of individual trees from climate data. Empirical data of microclimatic factors, intra-annual growth rates, and tree-specific ratios between actual and potential transpiration (T PET−1) of trees of three species (Quercus pubescens, Pinus sylvestris, and Picea abies) at two dry sites in the central Wallis, Switzerland, were recorded from 2002 to 2004 at a 10 min resolution. This included the exceptionally hot and dry summer of 2003. These data were analysed in terms of direct (current conditions) and indirect impacts (predispositions of the past year) on growth. Rain was found to be the only factor which, to a large extent, consistently explained the radial increment for all three tree species at both sites and in the short term as well. Other factors had some explanatory power on the seasonal time-scale only. Quercus pubescens built up much of its tree ring before bud break. Pinus sylvestris and Picea abies started radial growth 1–2 weeks after Quercus pubescens and this was despite the fact that they had a high T PET−1 before budburst and radial growth started. A high T PET−1 was assumed to be related to open stomata, a very high net CO2 assimilation rate, and thus a potential carbon (C)-income for the tree. The main period of radial growth covered about 30–70% of the productive days of a year. In terms of C-allocation, these results mean that Quercus pubescens depended entirely on internal C-stores in the early phase of radial growth and that for all three species there was a long time period of C-assimilation which was not used for radial growth in above-ground wood. The results further suggest a strong dependence of radial growth on the current tree water relations and only secondarily on the C-balance. A concept is discussed which links radial growth over a feedback loop to actual tree water-relations and long-term affected C-storage to microclimate.

Topology and Link quality-aware Geographical opportunistic routing in wireless ad-hoc networks

Opportunistic routing (OR) takes advantage of the broadcast nature and spatial diversity of wireless transmission to improve the performance of wireless ad-hoc networks. Instead of using a predetermined path to send packets, OR postpones the choice of the next-hop to the receiver side, and lets the multiple receivers of a packet to coordinate and decide which one will be the forwarder. Existing OR protocols choose the next-hop forwarder based on a predefined candidate list, which is calculated using single network metrics. In this paper, we propose TLG - Topology and Link quality-aware Geographical opportunistic routing protocol. TLG uses multiple network metrics such as network topology, link quality, and geographic location to implement the coordination mechanism of OR. We compare TLG with well-known existing solutions and simulation results show that TLG outperforms others in terms of both QoS and QoE metrics.

A reliable, traffic-adaptive and energy-efficient link layer for wireless sensor networks

The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

A physiological and behavioral mechanism for leaf-herbivore induced systemic root resistance

Indirect plant-mediated interactions between herbivores are important drivers of community composition in terrestrial ecosystems. Among the most striking examples are the strong indirect interactions between spatially separated leaf- and root-feeding insects sharing a host plant. Although leaf feeders generally reduce the performance of root herbivores, little is known about the underlying systemic changes in root physiology and the associated behavioral responses of the root feeders. We investigated the consequences of maize (Zea mays) leaf infestation by Spodoptera littoralis caterpillars for the root-feeding larvae of the beetle Diabrotica virgifera virgifera, a major pest of maize. D. virgifera strongly avoided leaf-infested plants by recognizing systemic changes in soluble root components. The avoidance response occurred within 12 h and was induced by real and mimicked herbivory, but not wounding alone. Roots of leaf-infested plants showed altered patterns in soluble free and soluble conjugated phenolic acids. Biochemical inhibition and genetic manipulation of phenolic acid biosynthesis led to a complete disappearance of the avoidance response of D. virgifera. Furthermore, bioactivity-guided fractionation revealed a direct link between the avoidance response of D. virgifera and changes in soluble conjugated phenolic acids in the roots of leaf-attacked plants. Our study provides a physiological mechanism for a behavioral pattern that explains the negative effect of leaf attack on a root-feeding insect. Furthermore, it opens up the possibility to control D. virgifera in the field by genetically mimicking leaf herbivore-induced changes in root phenylpropanoid patterns.

SOP: Parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centers from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.