Search for cytotoxic agents in multiple Laurencia complex seaweed species (Ceramiales, Rhodophyta) harvested from the Atlantic Ocean with emphasis on the Brazilian State of Espírito Santo

The development of new anti-cancer drugs of algal origin represents one of the least explored frontiers in medicinal chemistry. In this regard, the diversity of micro- and macroalgae found in Brazilian coastal waters can be viewed as a largely untapped natural resource. In this report, we describe a comparative study on the cytotoxic properties of extracts obtained from the Laurencia complex: Laurencia aldingensis, L. catarinensis, L. dendroidea, L. intricata, L. translucida, L. sp, and Palisada flagellifera. All of these species were collected in the coastal waters of the State of Espírito Santo, Brazil. Four out of the twelve samples initially investigated were found to show significant levels of toxicity towards a model tumor cell line (human uterine sarcoma, MES-SA). The highest levels of cytotoxicity were typically associated with non-polar (hexane) algal extracts, while the lowest levels of cytotoxicity were found with the corresponding polar (methanol) extracts. In this report, we also describe a biological model currently in development that will not only facilitate the search for new anti-cancer drug candidates of algal origin, but also permit the identification of compounds capable of inducing the destruction of multi-drug resistant tumors with greater efficiency than the pharmaceuticals currently in clinical use.

Multidisciplinary optimization of a catamaran's hydrofoil design with dynamic response surface and distributive processing

This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.

A novel mutation in the glycogen synthase 2 gene in a child with glycogen storage disease type 0

Background: Glycogen storage disease type 0 is an autosomal recessive disease presenting in infancy or early childhood and characterized by ketotic hypoglycemia after prolonged fasting and postprandial hyperglycemia and hyperlactatemia. Sixteen different mutations have been identified to date in the gene which encodes hepatic glycogen synthase, resulting in reduction of glycogen storage in the liver. Case Presentation: Biochemical evaluation as well as direct sequencing of exons and exon-intron boundary regions of the GYS2 gene were performed in a patient presenting fasting hypoglycemia and postprandial hyperglycemia and her parents. The patient was found to be compound heterozygous for one previously reported nonsense mutation (c. 736 C>T; R243X) and a novel frameshift mutation (966_967delGA/insC) which introduces a stop codon 21 aminoacids downstream from the site of the mutation that presumably leads to loss of 51% of the COOH-terminal part of the protein. The glycemia and lactatemia of the parents after an oral glucose tolerance test were evaluated to investigate a possible impact of the carrier status on the metabolic profile. The mother, who presented a positive family history of type 2 diabetes, was classified as glucose intolerant and the father, who did not exhibit metabolic changes after the glucose overload, had an antecedent history of hypoglycemia after moderate alcohol ingestion. Conclusion: The current results expand the spectrum of known mutations in GYS2 and suggest that haploinsufficiency could explain metabolic abnormalities in heterozygous carriers in presence of predisposing conditions.

249 TP53 mutation has high prevalence and is correlated with larger and poorly differentiated HCC in Brazilian patients

Background: Ser-249 TP53 mutation (249(Ser)) is a molecular evidence for aflatoxin-related carcinogenesis in Hepatocellular Carcinoma (HCC) and it is frequent in some African and Asian regions, but it is unusual in Western countries. HBV has been claimed to add a synergic effect on genesis of this particular mutation with aflatoxin. The aim of this study was to investigate the frequency of 249Ser mutation in HCC from patients in Brazil. Methods: We studied 74 HCC formalin fixed paraffin blocks samples of patients whom underwent surgical resection in Brazil. 249Ser mutation was analyzed by RFLP and DNA sequencing. HBV DNA presence was determined by Real-Time PCR. Results: 249Ser mutation was found in 21/74 (28%) samples while HBV DNA was detected in 13/74 (16%). 249Ser mutation was detected in 21/74 samples by RFLP assay, of which 14 were confirmed by 249Ser mutant-specific PCR, and 12 by nucleic acid sequencing. All HCC cases with p53-249ser mutation displayed also wild-type p53 sequences. Poorly differentiated HCC was more likely to have 249Ser mutation (OR = 2.415, 95% CI = 1.001 - 5.824, p = 0.05). The mean size of 249Ser HCC tumor was 9.4 cm versus 5.5 cm on wild type HCC (p = 0.012). HBV DNA detection was not related to 249Ser mutation. Conclusion: Our results indicate that 249Ser mutation is a HCC important factor of carcinogenesis in Brazil and it is associated to large and poorly differentiated tumors.

A novel COL1A1 gene-splicing mutation (c. 1875+1G > C) in a Brazilian patient with osteogenesis imperfecta

Osteogenesis imperfecta is a heterogeneous genetic disorder characterized by bone fragility and deformity, recurrent fractures, blue sclera, short stature, and dentinogenesis imperfecta. Most cases are caused by mutations in COL1A1 and COL1A2 genes. We present a novel splicing mutation in the COL1A1 gene (c. 1875+ 1G>C) in a 16-year-old Brazilian boy diagnosed as a type III osteogenesis imperfecta patient. This splicing mutation and its association with clinical phenotypes will be submitted to the reference database of COL1A1 mutations, which has no other description of this mutation.

Search for Lorentz Invariance and CPT Violation with the MINOS Far Detector

We searched for a sidereal modulation in the MINOS far detector neutrino rate. Such a signal would be a consequence of Lorentz and CPT violation as described by the standard-model extension framework. It also would be the first detection of a perturbative effect to conventional neutrino mass oscillations. We found no evidence for this sidereal signature, and the upper limits placed on the magnitudes of the Lorentz and CPT violating coefficients describing the theory are an improvement by factors of 20-510 over the current best limits found by using the MINOS near detector.

Characterization of dynamic solid phase DNA extraction from blood with magnetically controlled silica beads

A novel solid phase extraction technique is described where DNA is bound and eluted from magnetic silica beads in a manner where efficiency is dependent on the magnetic manipulation of the beads and not on the flow of solution through a packed bed. The utility of this technique in the isolation of reasonably pure, PCR-amplifiable DNA from complex samples is shown by isolating DNA from whole human blood, and subsequently amplifying a fragment of the beta-globin gene. By effectively controlling the movement of the solid phase in the presence of a static sample, the issues associated with reproducibly packing a solid phase in a microchannel and maintaining consistent flow rates are eliminated. The technique described here is rapid, simple, and efficient, allowing for recovery of more than 60% of DNA from 0.6 mu L of blood at a concentration which is suitable for PCR amplification. In addition, the technique presented here requires inexpensive, common laboratory equipment, making it easily adopted for both clinical point-of-care applications and on-site forensic sample analysis.

Combined heuristic with fuzzy system to transmission system expansion planning

A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (C) 2010 Elsevier B.V. All rights reserved.

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

A novel multiobjective optimization algorithm based on bacterial chemotaxis

In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

A Constructive Genetic Algorithm for permutation flowshop scheduling

The general flowshop scheduling problem is a production problem where a set of n jobs have to be processed with identical flow pattern on in machines. In permutation flowshops the sequence of jobs is the same on all machines. A significant research effort has been devoted for sequencing jobs in a flowshop minimizing the makespan. This paper describes the application of a Constructive Genetic Algorithm (CGA) to makespan minimization on flowshop scheduling. The CGA was proposed recently as an alternative to traditional GA approaches, particularly, for evaluating schemata directly. The population initially formed only by schemata, evolves controlled by recombination to a population of well-adapted structures (schemata instantiation). The CGA implemented is based on the NEH classic heuristic and a local search heuristic used to define the fitness functions. The parameters of the CGA are calibrated using a Design of Experiments (DOE) approach. The computational results are compared against some other successful algorithms from the literature on Taillard`s well-known standard benchmark. The computational experience shows that this innovative CGA approach provides competitive results for flowshop scheduling; problems. (C) 2007 Elsevier Ltd. All rights reserved.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 2: shells

Following the approach developed for rods in Part 1 of this paper (Pimenta et al. in Comput. Mech. 42:715-732, 2008), this work presents a fully conserving algorithm for the integration of the equations of motion in nonlinear shell dynamics. We begin with a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, allowing for an extremely simple update of the rotational variables within the scheme. The weak form is constructed via non-orthogonal projection, the time-collocation of which ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that general hyperelastic materials (and not only materials with quadratic potentials) are permitted in a totally consistent way. Spatial discretization is performed using the finite element method and the robust performance of the scheme is demonstrated by means of numerical examples.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 1: Rods

A fully conserving algorithm is developed in this paper for the integration of the equations of motion in nonlinear rod dynamics. The starting point is a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, which results in an extremely simple update of the rotational variables. The weak form is constructed with a non-orthogonal projection corresponding to the application of the virtual power theorem. Together with an appropriate time-collocation, it ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that nonlinear hyperelastic materials (and not only materials with quadratic potentials) are permitted without any prejudice on the conservation properties. Spatial discretization is performed via the finite element method and the performance of the scheme is assessed by means of several numerical simulations.

Dynamic Design of Piezoelectric Laminated Sensors and Actuators using Topology Optimization

Sensors and actuators based on piezoelectric plates have shown increasing demand in the field of smart structures, including the development of actuators for cooling and fluid-pumping applications and transducers for novel energy-harvesting devices. This project involves the development of a topology optimization formulation for dynamic design of piezoelectric laminated plates aiming at piezoelectric sensors, actuators and energy-harvesting applications. It distributes piezoelectric material over a metallic plate in order to achieve a desired dynamic behavior with specified resonance frequencies, modes, and enhanced electromechanical coupling factor (EMCC). The finite element employs a piezoelectric plate based on the MITC formulation, which is reliable, efficient and avoids the shear locking problem. The topology optimization formulation is based on the PEMAP-P model combined with the RAMP model, where the design variables are the pseudo-densities that describe the amount of piezoelectric material at each finite element and its polarization sign. The design problem formulated aims at designing simultaneously an eigenshape, i.e., maximizing and minimizing vibration amplitudes at certain points of the structure in a given eigenmode, while tuning the eigenvalue to a desired value and also maximizing its EMCC, so that the energy conversion is maximized for that mode. The optimization problem is solved by using sequential linear programming. Through this formulation, a design with enhancing energy conversion in the low-frequency spectrum is obtained, by minimizing a set of first eigenvalues, enhancing their corresponding eigenshapes while maximizing their EMCCs, which can be considered an approach to the design of energy-harvesting devices. The implementation of the topology optimization algorithm and some results are presented to illustrate the method.

Multi-Objective Optimization Design of Tanker Ships via a Genetic Algorithm

The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies. [DOI:10.1115/1.4002740]