Synthetic and natural polycations for gene therapy: State of the art and new perspectives

Currently, the major drawback of gene therapy is the gene transfection rate. The two main types of vectors that. are used in gene therapy are based on viral or non-viral gene delivery systems. There are several non-viral systems that can be used to transfer foreign genetic material into the human body. In order to do so, the DNA to be transferred must escape the processes that affect the disposition of macromolecules. These processes include the interaction with blood components, vascular endothelial cells and uptake by the reticuloendothelial system. Furthermore, the degradation of therapeutic DNA by serum nucleases is also a potential obstacle for functional delivery to the target cell. Cationic polymers have a great potential for DNA complexation and may be useful as non-viral vectors for gene therapy applications. The objective of this review was to address the state of the art in gene therapy using synthetic and natural polycations and the latest strategies to improve the efficiency of gene transfer into the cell.

HIERARCHICAL VERSUS NONHIERARCHICAL PATTERNS OF GENETIC DISTANCES AMONG POPULATIONS - A SIMULATION STUDY

A simulation study was made of the effects of mixing two evolutionary forces (natural selection and random genetic drift), combined in a single data matrix of gene frequencies, on the resulting genetic distances among populations. Twenty-one, kinds of simulated gene frequencies surfaces, for 15 populations linearly distributed over geographic space, were used to construct 21 data matrices, combining different proportions of two types of surfaces (gradients and random surfaces). These matrices were analysed by Unweighted Pair-Group Method - Arithmetic Averages (UPGMA), clustering and Principal Coordinate Analysis. The results obtained show that ordination is more accurate than UPGMA in revealing the spatial patterns in the genetic distances, in comparison with results obtained using the Mantel test comparing directly genetic and geographic distances.

Low genetic diversities of rabies virus populations within different hosts in Brazil

The low rates of nonsynonymous evolution observed in natural rabies virus (RABV) isolates are suggested to have arisen in association with the structural and functional constraints operating on the virus protein and the infection strategies employed by RABV within infected hosts to avoid strong selection by the immune response. In order to investigate the relationship between the genetic characteristics of RABV populations within hosts and the virus evolution, the present study examined the genetic heterogeneities of RABV populations within naturally infected dogs and foxes in Brazil, as well as those of bat RABV populations that were passaged once in suckling mice. Sequence analyses of complete RABV glycoprotein (G) genes showed that RABV populations within infected hosts were genetically highly homogeneous whether they were infected naturally or experimentally (nucleotide diversities of 0-0.95 x 10(-3)). In addition, amino acid mutations were randomly distributed over the entire region of the G protein, and the nonsynonymous/synonymous rate ratios (d(N)/d(S)) for the G protein gene were less than 1. These findings suggest that the low genetic diversities of RABV populations within hosts reflect the stabilizing selection operating on the virus, the infection strategies of the virus, and eventually, the evolutionary patterns of the virus. (C) 2009 Elsevier B.V. All rights reserved.

Genetic Algorithms (Binary and Real Codes) for the Optimisation of a Fermentation Process for Butanol Production

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Location and contract pricing of distributed generation using a genetic algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Defects location in power systems components through a dedicated genetic algorithm

In this work the problem of defects location in power systems is formulated through a binary linear programming (BLP) model based on alarms historical database of control and protection devices from the system control center, sets theory of minimal coverage (AI) and protection philosophy adopted by the electric utility. In this model, circuit breaker operations are compared to their expected states in a strictly mathematical manner. For solving this BLP problem, which presents a great number of decision variables, a dedicated Genetic Algorithm (GA), is proposed. Control parameters of the GA, such as crossing over and mutation rates, population size, iterations number and population diversification, are calibrated in order to obtain efficiency and robustness. Results for a test system found in literature, are presented and discussed. © 2004 IEEE.

Strong selection against hybrids at a hybrid zone in the Ensatina ring species complex and its evolutionary implications

The analysis of interactions between lineages at varying levels of genetic divergence can provide insights into the process of speciation through the accumulation of incompatible mutations. Ring species, and especially the Ensatina eschscholtzii system exemplify this approach. The plethodontid salamanders E. eschscholtzii xanthoptica and E. eschscholtzii platensis hybridize in the central Sierran foothills of California. We compared the genetic structure across two transects (southern and northern Calaveras Co.), one of which was resampled over 20 years, and examined diagnostic molecular markers (eight allozyme loci and mitochondrial DNA) and a diagnostic quantitative trait (color pattern). Key results across all studies were: (1) cline centers for all markers were coincident and the zones were narrow, with width estimates of 730 m to 2000 m; (2) cline centers at the northern Calaveras transect were coincident between 1981 and 2001, demonstrating repeatability over five generations; (3) there were very few if any putative F1s, but a relatively high number of backcrossed individuals in the central portion of transects: and (4) we found substantial linkage disequilibrium in all three studies and strong heterozygote deficit both in northern Calaveras, in 2001, and southern Calaveras. Both linkage disequilibrium and heterozygote deficit showed maximum values near the center of the zones. Using estimates of cline width and dispersal, we infer strong selection against hybrids. This is sufficient to promote accumulation of differences at loci that are neutral or under divergent selection, but would still allow for introgression of adaptive alleles. The evidence for strong but incomplete isolation across this centrally located contact is consistent with theory suggesting a gradual increase in postzygotic incompatibility between allopatric populations subject to divergent selection and reinforces the value of Ensatina as a system for the study of divergence and speciation at multiple stages. © 2005 The Society for the Study of Evolution. All rights reserved.

Distribution network reconfiguration using an efficient evolutionary algorithm

Network reconfiguration is an important tool to optimize the operating conditions of a distribution system. This is accomplished modifying the network structure of distribution feeders by changing the open/close status of sectionalizing switches. This not only reduces the power losses, but also relieves the overloading of the network components. Network reconfiguration belongs to a complex family of problems because of their combinatorial nature and multiple constraints. This paper proposes a solution to this problem, using a specialized evolutionary algorithm, with a novel codification, and a brand new way of implement the genetic operators considering the problem characteristics. The algorithm is presented and tested in a real distribution system, showing excellent results and computational efficiency. © 2007 IEEE.

Mitochondrial genome sequence of the Brazilian luminescent click beetle Pyrophorus divergens (Coleoptera: Elateridae): Mitochondrial genes utility to investigate the evolutionary history of Coleoptera and its bioluminescence

The Coleoptera order is the richest group among Metazoa, but its phylogenetics remains incompletely understood. Among Coleoptera, bioluminescence is found within the Elateroidea, but the evolution of this character remains a mystery. Mitochondrial DNA has been used extensively to reconstruct phylogenetic relationships, however, the evolution of a single gene does not always correspond to the species evolutionary history and the molecular marker choice is a key step in this type of analysis. To create a solid basis to better understand the evolutionary history of Coleoptera and its bioluminescence, we sequenced and comparatively analyzed the mitochondrial genome of the Brazilian luminescent click beetle Pyrophorus divergens (Coleoptera: Elateridae). © 2007 Elsevier B.V. All rights reserved.

Evolutionary heuristic to determine future land use

In the spatial electric load forecasting, the future land use determination is one of the most important tasks, and one of the most difficult, because of the stochastic nature of the city growth. This paper proposes a fast and efficient algorithm to find out the future land use for the vacant land in the utility service area, using ideas from knowledge extraction and evolutionary algorithms. The methodology was implemented into a full simulation software for spatial electric load forecasting, showing a high rate of success when the results are compared to information gathered from specialists. The importance of this methodology lies in the reduced set of data needed to perform the task and the simplicity for implementation, which is a great plus for most of the electric utilities without specialized tools for this planning activity. © 2008 IEEE.

A specialized genetic algorithm to solve the short term transmission network expansion planning

In this paper, the short term transmission network expansion planning (STTNEP) is solved through a specialized genetic algorithm (SGA). A complete AC model of the transmission network is used, which permits the formulation of an integrated power system transmission network expansion planning problem (real and reactive power planning). The characteristics of the proposed SGA to solve the STTNEP problem are detailed and an interior point method is employed to solve nonlinear programming problems during the solution steps of the SGA. Results of tests carried out with two electrical energy systems show the capabilities of the SGA and also the viability of using the AC model to solve the STTNEP problem. © 2009 IEEE.

Specialized genetic algorithm for transmission network expansion planning considering reliability

This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.

Presence and distribution of the endosymbiont Wolbachia among Solenopsis spp. (Hymenoptera: Formicidae) from Brazil and its evolutionary history

Wolbachia are intracellular bacteria that commonly infect arthropods. Its prevalence among ants of the genus Solenopsis is high. In the present study, the presence and distribution of these endosymbionts was examined among populations of Solenopsis spp. from Brazil. A phylogenetic analysis based on the wsp gene was conducted to infer the evolutionary history of Wolbachia infections within the populations surveyed. A high frequency of Wolbachia bacteria was observed among the genus Solenopsis, 51% of the colonies examined were infected. Incidence was higher in populations from southern Brazil. However, little genetic variability was found among different Wolbachia strains within supergroups A and B. Our findings also suggest that horizontal transmission events can occur through the social parasite S. daguerrei. © 2012 Elsevier Inc..

An enhanced genetic algorithm to solve the static and multistage transmission network expansion planning

An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1) generation of an initial population using fast, efficient heuristic algorithms, (2) better implementation of the local improvement phase and (3) efficient solution of linear programming problems (LPs). Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem. Copyright © 2012 Luis A. Gallego et al.