Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

Bat-Inspired Optimization Approach for the Brushless DC Wheel Motor Problem

This paper presents a metaheuristic algorithm inspired in evolutionary computation and swarm intelligence concepts and fundamentals of echolocation of micro bats. The aim is to optimize the mono and multiobjective optimization problems related to the brushless DC wheel motor problems, which has 5 design parameters and 6 constraints for the mono-objective problem and 2 objectives, 5 design parameters, and 5 constraints for multiobjective version. Furthermore, results are compared with other optimization approaches proposed in the recent literature, showing the feasibility of this newly introduced technique to high nonlinear problems in electromagnetics.

On estimating the basic reproduction number in distinct stages of a contagious disease spreading

In epidemiology, the basic reproduction number R-0 is usually defined as the average number of new infections caused by a single infective individual introduced into a completely susceptible population. According to this definition. R-0 is related to the initial stage of the spreading of a contagious disease. However, from epidemiological models based on ordinary differential equations (ODE), R-0 is commonly derived from a linear stability analysis and interpreted as a bifurcation parameter: typically, when R-0 >1, the contagious disease tends to persist in the population because the endemic stationary solution is asymptotically stable: when R-0 <1, the corresponding pathogen tends to naturally disappear because the disease-free stationary solution is asymptotically stable. Here we intend to answer the following question: Do these two different approaches for calculating R-0 give the same numerical values? In other words, is the number of secondary infections caused by a unique sick individual equal to the threshold obtained from stability analysis of steady states of ODE? For finding the answer, we use a susceptibleinfective-recovered (SIR) model described in terms of ODE and also in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. The values of R-0 obtained from both approaches are compared, showing good agreement. (C) 2012 Elsevier B.V. All rights reserved.

Numerical simulation of anisotropic polymeric foams

This paper shows in detail the modelling of anisotropic polymeric foam under compression and tension loadings, including discussions on isotropic material models and the entire procedure to calibrate the parameters involved. First, specimens of poly(vinyl chloride) (PVC) foam were investigated through experimental analyses in order to understand the mechanical behavior of this anisotropic material. Then, isotropic material models available in the commercial software Abaqus (TM) were investigated in order to verify their ability to model anisotropic foams and how the parameters involved can influence the results. Due to anisotropy, it is possible to obtain different values for the same parameter in the calibration process. The obtained set of parameters are used to calibrate the model according to the application of the structure. The models investigated showed minor and major limitations to simulate the mechanical behavior of anisotropic PVC foams under compression, tension and multi-axial loadings. Results show that the calibration process and the choice of the material model applied to the polymeric foam can provide good quantitative results and save project time. Results also indicate what kind and order of error one will get if certain choices are made throughout the modelling process. Finally, even though the developed calibration procedure is applied to specific PVC foam, it still outlines a very broad drill to analyze other anisotropic cellular materials.

Numerical simulation of drop impact and jet buckling problems using the eXtended Pom-Pom model

This work presents numerical simulations of two fluid flow problems involving moving free surfaces: the impacting drop and fluid jet buckling. The viscoelastic model used in these simulations is the eXtended Pom-Pom (XPP) model. To validate the code, numerical predictions of the drop impact problem for Newtonian and Oldroyd-B fluids are presented and compared with other methods. In particular, a benchmark on numerical simulations for a XPP drop impacting on a rigid plate is performed for a wide range of the relevant parameters. Finally, to provide an additional application of free surface flows of XPP fluids, the viscous jet buckling problem is simulated and discussed. (C) 2011 Elsevier B.V. All rights reserved.

Repertoire, Genealogy and Genomic Organization of Cruzipain and Homologous Genes in Trypanosoma cruzi, T. cruzi-Like and Other Trypanosome Species

Trypanosoma cruzi, the agent of Chagas disease, is a complex of genetically diverse isolates highly phylogenetically related to T. cruzi-like species, Trypanosoma cruzi marinkellei and Trypanosoma dionisii, all sharing morphology of blood and culture forms and development within cells. However, they differ in hosts, vectors and pathogenicity: T. cruzi is a human pathogen infective to virtually all mammals whilst the other two species are non-pathogenic and bat restricted. Previous studies suggest that variations in expression levels and genetic diversity of cruzipain, the major isoform of cathepsin L-like (CATL) enzymes of T. cruzi, correlate with levels of cellular invasion, differentiation, virulence and pathogenicity of distinct strains. In this study, we compared 80 sequences of genes encoding cruzipain from 25 T. cruzi isolates representative of all discrete typing units (DTUs TcI-TcVI) and the new genotype Tcbat and 10 sequences of homologous genes from other species. The catalytic domain repertoires diverged according to DTUs and trypanosome species. Relatively homogeneous sequences are found within and among isolates of the same DTU except TcV and TcVI, which displayed sequences unique or identical to those of TcII and TcIII, supporting their origin from the hybridization between these two DTUs. In network genealogies, sequences from T. cruzi clustered tightly together and closer to T. c. marinkellei than to T. dionisii and largely differed from homologues of T. rangeli and T. b. brucei. Here, analysis of isolates representative of the overall biological and genetic diversity of T. cruzi and closest T. cruzi-like species evidenced DTU- and species-specific polymorphisms corroborating phylogenetic relationships inferred with other genes. Comparison of both phylogenetically close and distant trypanosomes is valuable to understand host-parasite interactions, virulence and pathogenicity. Our findings corroborate cruzipain as valuable target for drugs, vaccine, diagnostic and genotyping approaches.

How far can we go in simplifying biomonitoring assessments? An integrated analysis of taxonomic surrogacy, taxonomic sufficiency and numerical resolution in a megadiverse region

The need for biodiversity conservation is increasing at a rate much faster than the acquisition of knowledge of biodiversity, such as descriptions of new species and mapping species distributions. As global changes are winning the race against the acquisition of knowledge, many researchers resort to the use of surrogate groups to aid in conservation decisions. Reductions in taxonomic and numerical resolution are also desirable, because they could allow more rapid the acquisition of knowledge while requiring less effort, if little important information is lost. In this study, we evaluated the congruence among 22 taxonomic groups sampled in a tropical forest in the Amazon basin. Our aim was to evaluate if any of these groups could be used as surrogates for the others in monitoring programs. We also evaluated if the taxonomic or numerical resolution of possible surrogates could be reduced without greatly reducing the overall congruence. Congruence among plant groups was high, whereas the congruence among most animal groups was very low, except for anurans in which congruence values were only slightly lower than for plants. Liana (Bignoniaceae) was the group with highest congruence, even using genera presence-absence data. The congruence among groups was related to environmental factors, specifically the clay and phosphorous contents of soil. Several groups showed strong spatial clumping, but this was unrelated to the congruence among groups. The high degree of congruence of lianas with the other groups suggests that it may be a reasonable surrogate group, mainly for the other plant groups analyzed, if soil data are not available. Although lianas are difficult to count and identify, the number of studies on the ecology of lianas is increasing. Most of these studies have concluded that lianas are increasing in abundance in tropical forests. In addition to the high congruence, lianas are worth monitoring in their own right because they are sensitive to global warming and the increasing frequency and severity of droughts in tropical regions. Our findings suggest that the use of data on surrogate groups with relatively low taxonomic and numerical resolutions can be a reliable shortcut for biodiversity assessments, especially in megadiverse areas with high rates of habitat conversion, where the lack of biodiversity knowledge is pervasive. (c) 2012 Elsevier Ltd. All rights reserved.