Prospects for a vaccine against malaria [Commentary]

No Abstract

Kunjin virus replicon vectors for human immunodeficiency virus vaccine development

We have previously demonstrated the ability of the vaccine vectors based on replicon RNA of the Australian flavivirus Kunjin (KUN) to induce protective antiviral and anticancer CD8(+) T-cell responses using murine polyepitope as a model immunogen (I. Anraku, T. J. Harvey, R. Linedale, J. Gardner, D. Harrich, A. Suhrbier, and A. A. Khromykh, J. Virol. 76:3791-3799, 2002). Here we showed that immunization of BALB/c mice with KUN replicons encoding HIV-1 Gag antigen resulted in induction of both Gag-specific antibody and protective Gag-specific CD8(+) T-cell responses. Two immunizations with KUNgag replicons in the form of virus-like particles (VLPs) induced anti-Gag antibodies with titers of greater than or equal to1:10,000. Immunization with KUNgag replicons delivered as plasmid DNA, naked RNA, or VLPs induced potent Gag-specific CD8(+) T-cell responses, with one immunization of KUNgag VLPs inducing 4.5-fold-more CD8(+) T cells than the number induced after immunization with recombinant vaccinia virus carrying the gag gene (rVVgag). Two immunizations with KUNgag VLPs also provided significant protection against challenge with rVVgag. Importantly, KUN replicon VLP vaccinations induced long-lasting immune responses with CD8(+) T cells able to secrete gamma interferon and to mediate protection 6 to 10 months after immunization. These results illustrate the potential value of the KUN replicon vectors for human immunodeficiency virus vaccine design.

DNA vaccine coding for the full-length infectious Kunjin virus RNA protects mice against the New York strain of West Nile virus

A plasmid DNA directing transcription of the infectious full-length RNA genome of Kunjin (KUN) virus in vivo from a mammalian expression promoter was used to vaccinate mice intramuscularly. The KUN viral cDNA encoded in the plasmid contained the mutation in the NS1 protein (Pro-250 to Leu) previously shown to attenuate KUN virus in weanling mice. KUN virus was isolated from the blood of immunized mice 3-4 days after DNA inoculation, demonstrating that infectious RNA was being transcribed in vivo; however, no symptoms of virus-induced disease were observed. By 19 days postimmunization, neutralizing antibody was detected in the serum of immunized animals. On challenge with lethal doses of the virulent New York strain of West Nile (WN) or wild-type KUN virus intracerebrally or intraperitoneally, mice immunized with as little as 0.1-1 mug of KUN plasmid DNA were solidly protected against disease. This finding correlated with neutralization data in vitro showing that serum from KUN DNA-immunized mice neutralized KUN and WN,viruses with similar efficiencies. The results demonstrate that delivery of an attenuated but replicating KUN virus via a plasmid DNA vector may provide an effective vaccination strategy against virulent strains of WN virus.

Immunogenicity of recombinant HBsAg/HCV particles in mice pre-immunised with hepatitis B virus-specific vaccine

Due to their spatial structure virus-like particles (VLPs) generally induce effective immune responses. VLPs derived from the small envelope protein (HBsAg-S) of hepatitis B virus (HBV) comprise the HBV vaccine. Modified HBsAs-S VLPs, carrying the immunodominant hypervariable region (HVR1) of the hepatitis C virus (HCV) envelope protein E2 within the exposed 'a'-determinant region (HBsAg/HVR1-VLPs), elicited HVR1-specific antibodies in mice. A high percentage of the human population is positive for anti-HBsAg antibodies (anti-HBs), either through vaccination or natural infection. We, therefore, determined if pre-existing anti-HBs could influence immunisation with modified VLPs. Mice were immunised with a commercial HBV vaccine, monitored to ensure an anti-HBs response, then immunised with HBsAg/HVR1-VLPs. The resulting anti-HVR1 antibody titre was similar in mice with or without pre-existing anti-HBs. This suggests that HBsAg/HVR1-VLPs induce a primary immune response to HVR1 in anti-HBs positive mice and, hence, they may be used successfully in individuals already immunised with the HBV vaccine. (C) 2003 Elsevier Science Ltd. All rights reserved.

Therapeutic LMP1 polyepitope vaccine for EBV-assolciated Hodgkin disease and nasopharyngeal carcinoma

Development of an epitope-based vaccination strategy designed to enhance Epstein-Barr virus (EBV)-specific CD8(+) cytotoxic T lymphocytes (CTLs) is increasingly being considered as a preferred approach for the treatment of EBV-associated relapsed Hodgkin disease (HD) and nasopharyngeal carcinoma (NPC). EBV-encoded latent membrane proteins, LMP1 and LMP2, are the only target antigens available for therapeutic augmentation of CTL responses in patients with HD and NPC. Here, we describe preclinical studies using a recombinant poxvirus vaccine that encodes a polyepitope protein comprising 6 HLA A2-restricted epitopes derived from LMP1. Human cells infected with this recombinant polyepitope construct were efficiently recognized by LM1-specific CTL lines from HLAA2 healthy individuals. Furthermore, immunization of HLrA A2/K-b mice with this polyepitope vaccine consistently generated strong LMP1 -specific CTL responses to 5 of the. 6 epitopes, which were readily detected by both ex vivo and in vitro assays. More important, this polyepitope vaccine successfully reversed the outgrowth of LMP1-expressing tumors in HLA A2/Kb mice. These studies provide an important platform for the development of an LMP-based polyepitope vaccine as an immunotherapeutic tool for the treatment of EBV-associated HD and NPC. (C) 2003 by The American Society of Hematology.

Spatial variability of particle size fractions of an Oxisol cultivated with conilon coffee

Information on the spatial distribution of particle size fractions is essential for use planning and management of soils. The aim of this work to was to study the spatial variability of particle size fractions of a Typic Hapludox cultivated with conilon coffee. The soil samples were collected at depths of 0-0.20 and 0.20-0.40 m in the coffee canopy projection, totaling 109 georeferentiated points. At the depth of 0.2-0.4 m the clay fraction showed average value significantly higher, while the sand fraction showed was higher in the depth of 0-0.20 m. The silt showed no significant difference between the two depths. The particle size fractions showed medium and high spatial variability. The levels of total sand and clay have positive and negative correlation, respectively, with the altitude of the sampling points, indicating the influence of landscape configuration.

Determination of reactivity rates of silicate particle-size fractions

The efficiency of sources used for soil acidity correction depends on reactivity rate (RR) and neutralization power (NP), indicated by effective calcium carbonate (ECC). Few studies establish relative efficiency of reactivity (RER) for silicate particle-size fractions, therefore, the RER applied for lime are used. This study aimed to evaluate the reactivity of silicate materials affected by particle size throughout incubation periods in comparison to lime, and to calculate the RER for silicate particle-size fractions. Six correction sources were evaluated: three slags from distinct origins, dolomitic and calcitic lime separated into four particle-size fractions (2, 0.84, 0.30 and <0.30-mm sieves), and wollastonite, as an additional treatment. The treatments were applied to three soils with different texture classes. The dose of neutralizing material (calcium and magnesium oxides) was applied at equal quantities, and the only variation was the particle-size material. After a 90-day incubation period, the RER was calculated for each particle-size fraction, as well as the RR and ECC of each source. The neutralization of soil acidity of the same particle-size fraction for different sources showed distinct solubility and a distinct reaction between silicates and lime. The RER for slag were higher than the limits established by Brazilian legislation, indicating that the method used for limes should not be used for the slags studied here.

Probing the scalar-pseudoscalar mixing in the 125 GeV Higgs particle with current data

LHC has found hints for a Higgs particle of 125 GeV. We investigate the possibility that such a particle is a mixture of scalar and pseudoscalar states. For definiteness, we concentrate on a two-Higgs doublet model with explicit CP violation and soft Z(2) violation. Including all Higgs production mechanisms, we determine the current constraints obtained by comparing h -> yy with h -> VV*, and comment on the information which can be gained by measurements of h -> b (b) over bar. We find bounds vertical bar s(2)vertical bar less than or similar to 0.83 at one sigma, where vertical bar s(2)vertical bar = 0 (vertical bar s(2)vertical bar = 1) corresponds to a pure scalar (pure pseudoscalar) state.

Re-entrant phase behaviour of network fluids: A patchy particle model with temperature-dependent valence

We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

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.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.