TRADE-OFF BETWEEN IMMUNE STIMULATION AND EXPRESSION OF STORAGE PROTEIN GENES

Proteins stored in insect hemolymph may serve (is a source of amino acids and energy for metabolism, and development. The expression of the main storage proteins was assessed in bacterial-challenged honey bees using real-time (RT)-PCH and Western blot.. After ensuring that. the immune system had, been activated by measuring the ensuing expression (, the innate immune response genes, defensin-1 (def-1) and prophenoloxidase (pro PO), we verified the expression of four genes encoding storage proteins. The levels of vitellogenin (vg) mRNA and of the respective protein. were significantly lowered in bees injected with bacteria or water only (injury). An equivalent response was observed in orally-infected bees. The levels of apolipophorin II/I (apoLP-II/I) and hexamerin (hex 70a) mRNAs did not significantly change, but levels of Hex 70a protein subunit showed a substantial decay after bacterial challenge or injury. Infection also caused a strong reduction in the levels of apoLP-III transcripts. Our findings are consistent with a down-regulation, of the express and accumulation of storage proteins as a consequence of activation of the immune system, suggesting that this phenomenon. represents a strategy to redirect resources to combat injury or infection. (C) 2009 Wiley Periodicals, Inc.

Argon ion laser and halogen lamp activation of a dark and light resin composite: microhardness after long-term storage

The objective of this study was to evaluate in vitro light activation of the nano-filled resin composite Vita shade A1 and A3 with a halogen lamp (QTH) and argon ion laser by Knoop microhardness profile. Materials and methods: Specimens of nanofilled composite resin (Z350-3 M-ESPE) Vita shade A1 and A3 were prepared with a single increment inserted in 2.0-mm-thick and 3-mm diameter disc-shaped Teflon mold. The light activation was performed with QTH for 20 s (with an intensity of approximately 1,000 mW/cm(2) and 700 mW/cm(2)) and argon ion laser for 10 s (with a power of 150 mW and 200 mW). Knoop microhardness test was performed after 24 h and 6 months. The specimens were divided into the 16 experimental groups (n = 10), according to the factors under study: photoactivation form, resin shade, and storage time. Knoop microhardness data was analyzed by a factorial ANOVA and TukeyA ` s tests at the 0.05 level of significance. Results: Argon ion laser was not able to photo-activate the darker shade of the nanofilled resin composite evaluated but when used with 200 mW it can be as effective as QTH to photo-activate the lighter shade with only 50% of the time exposure. After 6 months storage, an increase in the means of Knoop microhardness values were observed. Conclusions: Light-activation significantly influenced the Knoop microhardness values for the darker nanofilled resin composite.

Influence of curing protocol on selected properties of light-curing polymers: Degree of conversion, volume contraction, elastic modulus, and glass transition temperature

Objectives. The purpose of this study was to investigate the effect of light-curing protocol on degree of conversion (DC), volume contraction (C), elastic modulus (E), and glass transition temperature (T(g)) as measured on a model polymer. It was a further aim to correlate the measured values with each other. Methods. Different light-curing protocols were used in order to investigate the influence of energy density (ED), power density (PD), and mode of cure on the properties. The modes of cure were continuous, pulse-delay, and stepped irradiation. DC was measured by Raman micro-spectroscopy. C was determined by pycnometry and a density column. E was measured by a dynamic mechanical analyzer (DMA), and T(g) was measured by differential scanning calorimetry (DSC). Data were submitted to two-and three-way ANOVA, and linear regression analyses. Results. ED, PD, and mode of cure influenced DC, C, E, and T(g) of the polymer. A significant positive correlation was found between ED and DC (r = 0.58), ED and E (r = 0.51), and ED and T(g) (r = 0.44). Taken together, ED and PD were significantly related to DC and E. The regression coefficient was positive for ED and negative for PD. Significant positive correlations were detected between DC and C (r = 0.54), DC and E (r = 0.61), and DC and T(g) (r = 0.53). Comparisons between continuous and pulse-delay modes of cure showed significant influence of mode of cure: pulse-delay curing resulted in decreased DC, decreased C, and decreased T(g). Influence of mode of cure, when comparing continuous and step modes of cure, was more ambiguous. A complex relationship exists between curing protocol, microstructure of the resin and the investigated properties. The overall performance of a composite is thus indirectly affected by the curing protocol adopted, and the desired reduction of C may be in fact a consequence of the decrease in DC. (C) 2009 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

A comparison of low-storage strategies for spectral analysis in dissipative systems: filter diagonalisation in the Lanczos representation and harmonic inversion of the Chebychev-order-domain autocorrelation function

We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.

Lanczos subspace filter diagonalization: Homogeneous recursive filtering and a low-storage method for the calculation of matrix elements

We develop a new iterative filter diagonalization (FD) scheme based on Lanczos subspaces and demonstrate its application to the calculation of bound-state and resonance eigenvalues. The new scheme combines the Lanczos three-term vector recursion for the generation of a tridiagonal representation of the Hamiltonian with a three-term scalar recursion to generate filtered states within the Lanczos representation. Eigenstates in the energy windows of interest can then be obtained by solving a small generalized eigenvalue problem in the subspace spanned by the filtered states. The scalar filtering recursion is based on the homogeneous eigenvalue equation of the tridiagonal representation of the Hamiltonian, and is simpler and more efficient than our previous quasi-minimum-residual filter diagonalization (QMRFD) scheme (H. G. Yu and S. C. Smith, Chem. Phys. Lett., 1998, 283, 69), which was based on solving for the action of the Green operator via an inhomogeneous equation. A low-storage method for the construction of Hamiltonian and overlap matrix elements in the filtered-basis representation is devised, in which contributions to the matrix elements are computed simultaneously as the recursion proceeds, allowing coefficients of the filtered states to be discarded once their contribution has been evaluated. Application to the HO2 system shows that the new scheme is highly efficient and can generate eigenvalues with the same numerical accuracy as the basic Lanczos algorithm.

The plausibility of long-wavelength stress correlation or stress magnitude as a mechanism for precursory seismicity: Results from two simple elastic models

Observations of accelerating seismic activity prior to large earthquakes in natural fault systems have raised hopes for intermediate-term eartquake forecasting. If this phenomena does exist, then what causes it to occur? Recent theoretical work suggests that the accelerating seismic release sequence is a symptom of increasing long-wavelength stress correlation in the fault region. A more traditional explanation, based on Reid's elastic rebound theory, argues that an accelerating sequence of seismic energy release could be a consequence of increasing stress in a fault system whose stress moment release is dominated by large events. Both of these theories are examined using two discrete models of seismicity: a Burridge-Knopoff block-slider model and an elastic continuum based model. Both models display an accelerating release of seismic energy prior to large simulated earthquakes. In both models there is a correlation between the rate of seismic energy release with the total root-mean-squared stress and the level of long-wavelength stress correlation. Furthermore, both models exhibit a systematic increase in the number of large events at high stress and high long-wavelength stress correlation levels. These results suggest that either explanation is plausible for the accelerating moment release in the models examined. A statistical model based on the Burridge-Knopoff block-slider is constructed which indicates that stress alone is sufficient to produce accelerating release of seismic energy with time prior to a large earthquake.

Patterns of lipid storage and mobilisation in the female green sea turtle (Chelonia mydas)

Reproductive data from southern Queensland indicate that vitellogenesis in female Chelonia mydas takes approximately 8 months and is followed by a migration to a breeding area. At Heron Island, females lay multiple clutches over approximately 3 months. To investigate how females mobilise and store lipid during the breeding season we collected plasma, yolk, and fat tissue samples from females at a variety of stages during the nesting season. In breeding females, concentrations of plasma triglyceride increased seasonally. They reached peak concentrations during vitellogenesis and courtship, remained high throughout the nesting season, and then declined to a nadir after the last clutch. Plasma protein concentration increased throughout the breeding season, peaking following the last clutch for the season. Yolk lipids were highest during courtship and were similar throughout the nesting season, suggesting that uptake of lipid by ovarian follicles is completed prior to the beginning of the nesting season. Plasma triglyceride decreases in females with prolonged periods of unsuccessful nesting, and total lipid levels in adipose tissue and follicle yolks were significantly lower in atretic females. It appears that: (1) endogenous energy reserves can be reduced by stochastic environmental events (such as those reducing nesting success), and (2) a metabolic shift signalling the end of the nesting season is characterised by a drop in plasma triglycerides and slight increase in total plasma protein.

The peroxisome proliferator-activated receptor beta/delta agonist, GW501516, regulates the expression of genes involved in lipid catabolism and energy uncoupling in skeletal muscle cells

Lipid homeostasis is controlled by the peroxisome proliferator-activated receptors (PPARalpha, -beta/delta, and -gamma) that function as fatty acid-dependent DNA-binding proteins that regulate lipid metabolism. In vitro and in vivo genetic and pharmacological studies have demonstrated PPARalpha regulates lipid catabolism. In contrast, PPARgamma regulates the conflicting process of lipid storage. However, relatively little is known about PPARbeta/delta in the context of target tissues, target genes, lipid homeostasis, and functional overlap with PPARalpha and -gamma. PPARbeta/delta, a very low-density lipoprotein sensor, is abundantly expressed in skeletal muscle, a major mass peripheral tissue that accounts for approximately 40% of total body weight. Skeletal muscle is a metabolically active tissue, and a primary site of glucose metabolism, fatty acid oxidation, and cholesterol efflux. Consequently, it has a significant role in insulin sensitivity, the blood-lipid profile, and lipid homeostasis. Surprisingly, the role of PPARbeta/delta in skeletal muscle has not been investigated. We utilize selective PPARalpha, -beta/delta, -gamma, and liver X receptor agonists in skeletal muscle cells to understand the functional role of PPARbeta/delta, and the complementary and/or contrasting roles of PPARs in this major mass peripheral tissue. Activation of PPARbeta/delta by GW501516 in skeletal muscle cells induces the expression of genes involved in preferential lipid utilization, beta-oxidation, cholesterol efflux, and energy uncoupling. Furthermore, we show that treatment of muscle cells with GW501516 increases apolipoprotein-A1 specific efflux of intracellular cholesterol, thus identifying this tissue as an important target of PPARbeta/delta agonists. Interestingly, fenofibrate induces genes involved in fructose uptake, and glycogen formation. In contrast, rosiglitazone-mediated activation of PPARgamma induces gene expression associated with glucose uptake, fatty acid synthesis, and lipid storage. Furthermore, we show that the PPAR-dependent reporter in the muscle carnitine palmitoyltransferase-1 promoter is directly regulated by PPARbeta/delta, and not PPARalpha in skeletal muscle cells in a PPARgamma coactivator-1-dependent manner. This study demonstrates that PPARs have distinct roles in skeletal muscle cells with respect to the regulation of lipid, carbohydrate, and energy homeostasis. Moreover, we surmise that PPARgamma/delta agonists would increase fatty acid catabolism, cholesterol efflux, and energy expenditure in muscle, and speculate selective activators of PPARbeta/delta may have therapeutic utility in the treatment of hyperlipidemia, atherosclerosis, and obesity.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.