Reconstruction of molecular networks involved in citokine-induced myotubes atrophy integrating microRNA and mRNA expression

Pós-graduação em Ciências Biológicas (Genética) - IBB

Chicken skeletal muscle-associated macroarray for gene discovery

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactions

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

Semi-synthetic minimal cells: Biochemical, physical, and technological aspects

The construction of synthetic cells is one of the major goals of bioengineering. The most successful approach consists in the encapsulation of biochemical materials (DNA, RNA, enzymes, etc.) inside lipid vesicles (liposomes), mimicking a cell structure. In this contribution, that also aims at introducing the reader to 'chemical synthetic biology,' we describe the current state of the art of 'semi-synthetic minimal cells' (SSMCs), namely, cell-like structures containing the minimal number of biological compounds that are required to reconstruct a function of interest. We will first describe how the concept of the minimal cell was originated and its relation with the theory of autopoiesis, then we review the most advanced results focused on genetic/metabolic networks inside liposomes. Next, we emphasize that relevance of physical aspects (too often neglected) that impact on the solute entrapment process, and finally we discuss new technological trends in SSMC research that will probably allow their future use in biotechnology. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.

Hopf bifurcation in the full repressilator equations

In this paper, we prove that the full repressilator equations in dimension six undergo a supercritical Hopf bifurcation.

Regulation of cardiac microRNAs induced by aerobic exercise training during heart failure

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

Short-term planning of electric power distribution networks using multiobjective genetic algorithim

The high active and reactive power level demanded by the distribution systems, the growth of consuming centers, and the long lines of the distribution systems result in voltage variations in the busses compromising the quality of energy supplied. To ensure the energy quality supplied in the distribution system short-term planning, some devices and actions are used to implement an effective control of voltage, reactive power, and power factor of the network. Among these devices and actions are the voltage regulators (VRs) and capacitor banks (CBs), as well as exchanging the conductors sizes of distribution lines. This paper presents a methodology based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II) for optimized allocation of VRs, CBs, and exchange of conductors in radial distribution systems. The Multiobjective Genetic Algorithm (MGA) is aided by an inference process developed using fuzzy logic, which applies specialized knowledge to achieve the reduction of the search space for the allocation of CBs and VRs.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

Balancing immunity and tolerance: genetic footprint of natural selection in the transcriptional regulatory region of HLA-G

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effects of polymorphic microsatellites in the regulatory region of IGF1 and GHR on growth and carcass traits in beef cattle

Growth hormone (GH), insulin-like growth factors 1 and 2 (IGF1 and IGF2) and their associated binding proteins and transmembrane receptors (GHR, IGF1R and IGF2R) play an important role in the physiology of mammalian growth. The objectives of the present study were to estimate the allele and genotype frequencies of microsatellite markers located in the 5'-regulatory region of the IGF1 and GHR genes in beef cattle belonging to different genetic groups and to determine effects of these markers on growth and carcass traits in these animals under an intensive production system. For this purpose, genotyping was performed on 384 bulls including 79 Nellore, 30 Canchim (5/8 Charolais + 3/8 Zebu) and 275 crossbred animals originating from crosses of Simmental (1/2 Simmental, n = 30) and Angus (1/2 Angus, n = 245) sires with Nellore females. The effects of substituting L allele for S allele of GHR microsatellite across Nellore, Canchim and 1/2 Angus were significant for weight gain and body weight (P < 0.05). The IGF1 microsatellite allele substitutions of 229 for 225 within Nellore group and of 225 for 229 within 1/2 Angus were not significant for any of the traits.

Gene flow networks among American Aedes aegypti populations

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Optimal capacitor placement in radial distribution networks

The capacitor placement (replacement) problem for radial distribution networks determines capacitor types, sizes, locations and control schemes. Optimal capacitor placement is a hard combinatorial problem that can be formulated as a mixed integer nonlinear program. Since this is a NP complete problem (Non Polynomial time) the solution approach uses a combinatorial search algorithm. The paper proposes a hybrid method drawn upon the Tabu Search approach, extended with features taken from other combinatorial approaches such as genetic algorithms and simulated annealing, and from practical heuristic approaches. The proposed method has been tested in a range of networks available in the literature with superior results regarding both quality and cost of solutions.

Location and contract pricing of distributed generation using a genetic algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.

Variation of genetic expression during development, revealed by esterase patterns in Aedes aegypti (Diptera, Culicidae)

Polyacrylamide gel electrophoresis was used to analyze esterase patterns during development of Aedes aegypti from the cities of Marília and São José do Rio Preto (SJRP), Brazil. The zymograms showed a total of 23 esterase bands, 22 of which were in the specimens from Marília and 19 in those from SJRP. These esterase bands were considered to be the product of 23 alleles distributed tentatively in eight genetic loci. Most of the alleles were developmentally regulated. The larval stage expressed the greatest number of them (19 alleles, from the eight loci, in Marília; and 17 alleles, from seven loci, in SJRP). The pupal stage expressed 10 alleles from seven loci, in both populations, and the adult stage expressed 8 alleles from five and six loci in SJRP and Marília, respectively. Some alleles that were active in every stage were developmentally controlled at the level of expression (amount of product). A single allele was constitutively and highly expressed, in larvae, pupae, and adults, in both populations. Differences in esterase synthesis among stages are probably due to regulatory mechanisms acting in agreement with the requirements of a variable number of processes in which esterases are involved. The larval stage is the most active in developmental processes and shows very intense intake of food and very high mobility. These features may demand increased esterase production at that stage. Comparison of the two populations examined showed (besides the existence of alleles that they do not share) that they exhibit differences in the control of expression of other alleles. Such findings may reflect genetic differences between founders in each population, but the possibility of involvement of the intensive use of insecticides in SJRP is also discussed.