A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Texture analysis based on maximum contrast walker

Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.

Role of Halogen Bonds in Thyroid Hormone Receptor Selectivity: Pharmacophore-Based 3D-QSSR Studies

Most physiological effects of thyroid hormones are mediated by the two thyroid hormone receptor subtypes, TR alpha and TR beta. Several pharmacological effects mediated by TR beta might be beneficial in important medical conditions such as obesity, hypercholesterolemia and diabetes, and selective TR beta activation may elicit these effects while maintaining an acceptable safety profile, To understand the molecular determinants of affinity and subtype selectivity of TR ligands, we have successfully employed a ligand- and structure-guided pharmacophore-based approach to obtain the molecular alignment of a large series of thyromimetics. Statistically reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models were obtained using the comparative molecular field analysis (CoMFA) method, and the visual analyses of the contour maps drew attention to a number of possible opportunities for the development of analogs with improved affinity and selectivity. Furthermore, the 3D-QSSR analysis allowed the identification of a novel and previously unmentioned halogen bond, bringing new insights to the mechanism of activity and selectivity of thyromimetics.

Fragment-Based QSAR and Molecular Modeling Studies on a Series of Discodermolide Analogs as Microtubule-Stabilizing Anticancer Agents

Inhibition of microtubule function is an attractive rational approach to anticancer therapy. Although taxanes are the most prominent among the microtubule-stabilizers, their clinical toxicity, poor pharmacokinetic properties, and resistance have stimulated the search for new antitumor agents having the same mechanism of action. Discodermolide is an example of nontaxane natural product that has the same mechanism of action, demonstrating superior antitumor efficacy and therapeutic index. The extraordinary chemical and biological properties have qualified discodermolide as a lead structure for the design of novel anticancer agents with optimized therapeutic properties. In the present work, we have employed a specialized fragment-based method to develop robust quantitative structure - activity relationship models for a series of synthetic discodermolide analogs. The generated molecular recognition patterns were combined with three-dimensional molecular modeling studies as a fundamental step on the path to understanding the molecular basis of drug-receptor interactions within this important series of potent antitumoral agents.

VSImG: A high frame rate bitmap based display system for neuroscience research

This paper describes a visual stimulus generator (VSImG) capable of displaying a gray-scale, 256 x 256 x 8 bitmap image with a frame rate of 500 Hz using a boustrophedonic scanning technique. It is designed for experiments with motion-sensitive neurons of the fly`s visual system, where the flicker fusion frequency of the photoreceptors can reach up to 500 Hz. Devices with such a high frame rate are not commercially available, but are required, if sensory systems with high flicker fusion frequency are to be studied. The implemented hardware approach gives us complete real-time control of the displacement sequence and provides all the signals needed to drive an electrostatic deflection display. With the use of analog signals, very small high-resolution displacements, not limited by the image`s pixel size can be obtained. Very slow image displacements with visually imperceptible steps can also be generated. This can be of interest for other vision research experiments. Two different stimulus files can be used simultaneously, allowing the system to generate X-Y displacements on one display or independent movements on two displays as long as they share the same bitmap image. (C) 2011 Elsevier B.V. All rights reserved.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

Discovery of New Inhibitors of Schistosoma mansoni PNP by Pharmacophore-Based Virtual Screening

Schistosomiasis is considered the second most important tropical parasitic disease, with severe socioeconomic consequences for millions of people worldwide. Schistosoma monsoni, one of the causative agents of human schistosomiasis, is unable to synthesize purine nucleotides de novo, which makes the enzymes of the purine salvage pathway important targets for antischistosomal drug development. In the present work, we describe the development of a pharmacophore model for ligands of S. mansoni purine nucleoside phosphorylase (SmPNP) as well as a pharmacophore-based virtual screening approach, which resulted in the identification of three thioxothiazolidinones (1-3) with substantial in vitro inhibitory activity against SmPNP. Synthesis, biochemical evaluation, and structure activity relationship investigations led to the successful development of a small set of thioxothiazolidinone derivatives harboring a novel chemical scaffold as new competitive inhibitors of SmPNP at the low-micromolar range. Seven compounds were identified with IC(50) values below 100 mu M. The most potent inhibitors 7, 10, and 17 with 1050 of 2, 18, and 38 mu M, respectively, could represent new potential lead compounds for further development of the therapy of schistosomiasis.

A WAVELET-BASED SPEAKER VERIFICATION ALGORITHM

This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

Formalization of an architectural model for exception handling coordination based on CA action concepts

Architectures based on Coordinated Atomic action (CA action) concepts have been used to build concurrent fault-tolerant systems. This conceptual model combines concurrent exception handling with action nesting to provide a general mechanism for both enclosing interactions among system components and coordinating forward error recovery measures. This article presents an architectural model to guide the formal specification of concurrent fault-tolerant systems. This architecture provides built-in Communicating Sequential Processes (CSPs) and predefined channels to coordinate exception handling of the user-defined components. Hence some safety properties concerning action scoping and concurrent exception handling can be proved by using the FDR (Failure Divergence Refinement) verification tool. As a result, a formal and general architecture supporting software fault tolerance is ready to be used and proved as users define components with normal and exceptional behaviors. (C) 2010 Elsevier B.V. All rights reserved.

A logic-based agent that plans for extended reachability goals

Planning to reach a goal is an essential capability for rational agents. In general, a goal specifies a condition to be achieved at the end of the plan execution. In this article, we introduce nondeterministic planning for extended reachability goals (i.e., goals that also specify a condition to be preserved during the plan execution). We show that, when this kind of goal is considered, the temporal logic CTL turns out to be inadequate to formalize plan synthesis and plan validation algorithms. This is mainly due to the fact that the CTL`s semantics cannot discern among the various actions that produce state transitions. To overcome this limitation, we propose a new temporal logic called alpha-CTL. Then, based on this new logic, we implement a planner capable of synthesizing reliable plans for extended reachability goals, as a side effect of model checking.

A fast and robust statistical test based on likelihood ratio with Bartlett correction to identify Granger causality between gene sets

We propose a likelihood ratio test ( LRT) with Bartlett correction in order to identify Granger causality between sets of time series gene expression data. The performance of the proposed test is compared to a previously published bootstrapbased approach. LRT is shown to be significantly faster and statistically powerful even within non- Normal distributions. An R package named gGranger containing an implementation for both Granger causality identification tests is also provided.

Computer-Assisted Approach to Structural Elucidation of Lignans

This paper reports an expert system (SISTEMAT) developed for structural determination of diverse chemical classes of natural products, including lignans, based mainly on 13C NMR and 1H NMR data of these compounds. The system is composed of five programs that analyze specific data of a lignan and shows a skeleton probability for the compound. At the end of analyses, the results are grouped, the global probability is computed, and the most probable skeleton is exhibited to the user. SISTEMAT was able to properly predict the skeletons of 80% of the 30 lignans tested, demonstrating its advantage during the structural elucidation course in a short period of time.