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.

Natural products biological screening and ligand-based virtual screening for the discovery of new antileishmanial agents

In the course of our research program to discover novel antileishmanial agents, a biological screening of natural products against Leishmania major promastigotes allowed the identification of a furoquinoline alkaloid (1) and a furanocoumarin (2) as new hits. Subsequently, an integrated ligand-based virtual screening approach was employed to search for new antileishmanial compounds using these naturally occurring molecules as templates. Fourteen out of 40 compounds selected from a database of about 800,000 compounds (extracted from ZINC, a free database for virtual screening) were experimentally confirmed to possess significant in vitro antileishmanial properties. The application of ligand-based virtual screening as a complementary approach to experimental natural product screening was a useful strategy to facilitate the identification of new promising lead candidates.

Immobilization of lutetium bisphthalocyanine in nanostructured biomimetic sensors using the LbL technique for phenol detection

This study describes the development of amperometric sensors based on poly(allylamine hydrochloride) (PAH) and lutetium bisphthalocyanine (LuPc(2)) films assembled using the Layer-by-Layer (LbL) technique. The films have been used as modified electrodes for catechol quantification. Electrochemical measurements have been employed to investigate the catalytic properties of the LuPc(2) immobilized in the LbL films. By chronoamperometry, the sensors present excellent sensitivity (20 nA mu M(-1)) in a wide linear range (R(2) = 0.994) up to 900 mu M and limit of detection (s/n = 3) of 37.5 x 10(-8) M for catechol. The sensors have good reproducibility and can be used at least for ten times. The work potential is +0.3 V vs. saturated calomel electrode (SCE). In voltammetry measurements, the calibration curve shows a good linearity (R(2) = 0.992) in the range of catechol up to 500 mu M with a sensitivity of 90 nA mu M(-1) and LD of 8 mu M. (C) 2011 Elsevier B.V. All rights reserved.

Wavelet-based dynamic time warping

Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an optimized version of the DTW I hat is based on the Discrete Wavelet Transform (DWT). (C) 2008 Elsevier B.V. All rights reserved.

Wavelet-based cepstrum calculation

In this paper we present a new wavelet-based algorithm for low-cost computation of the cepstrum. It can be used for real time precise pitch determination in automatic speech and speaker recognition systems. Many wavelet families are examined to determine the one that works best. The results confirm the efficacy and accuracy of the proposed technique for pitch extraction. (C) 2008 Elsevier B.V. All rights reserved.

PARALLEL ALGORITHMS FOR MAXIMAL CLIQUES IN CIRCLE GRAPHS AND UNRESTRICTED DEPTH SEARCH

We present parallel algorithms on the BSP/CGM model, with p processors, to count and generate all the maximal cliques of a circle graph with n vertices and m edges. To count the number of all the maximal cliques, without actually generating them, our algorithm requires O(log p) communication rounds with O(nm/p) local computation time. We also present an algorithm to generate the first maximal clique in O(log p) communication rounds with O(nm/p) local computation, and to generate each one of the subsequent maximal cliques this algorithm requires O(log p) communication rounds with O(m/p) local computation. The maximal cliques generation algorithm is based on generating all maximal paths in a directed acyclic graph, and we present an algorithm for this problem that uses O(log p) communication rounds with O(m/p) local computation for each maximal path. We also show that the presented algorithms can be extended to the CREW PRAM model.

Generating segmented meshes from textured color images

This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion to extract features from the training data. The W-operator is built into the local error estimation used by Imesh to choose the mesh vertices. Furthermore, the W-operator also enables to assign a label to the triangles during the mesh construction, thus allowing to obtain a segmented mesh at the end of the process. The presented results show that the combination of W-operators with Imesh gives rise to a texture classification-based triangle mesh generation framework that outperforms pixel based methods. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.

New hydrazine sensors based on electropolymerized meso-tetra (4-sulphonatephenyl)porphyrinate manganese (III)/silver nanomaterial

A new electrocatalytic active porphyrin nanocomposite material was obtained by electropolymerization of meso-tetra(4-sulphonatephenyl) porphyrinate manganese(III) complex (MnTPPS) in alkaline solutions containing sub-micromolar concentrations of silver chloride. The modified glassy carbon electrodes efficiently oxidize hydrazine at 10 mV versus Ag/AgCl, dramatically decreasing the overpotential of conventional carbon electrodes. The analytical characteristics of this amperometric sensor coupled with batch injection analysis (BIA) technique were explored. Wide linear dynamic range (2.5 x 10(-7) to 2.5 x 10(-4) mol L-1), good repeatability (R.S.D. = 0.84%, n = 30) and low detection (3.1 x 10(-8) mol L-1) and quantification (1.0 x 10(-7) mol L-1) limits, as well as very fast sampling frequency (60 determinations per hour) were achieved. (c) 2007 Elsevier B.V. All rights reserved.

Determination of carbaryl in tomato ""in natura"" using an amperometric biosensor based on the inhibition of acetylcholinesterase activity

This work reports the utilization of two methodologies for carbaryl determination in tomatoes. The measurements were carried out using an amperometric biosensor technique based on the inhibition of acetylcholinesterase activity due to carbaryl adsorption and a HPLC procedure. The electrochemical experiments were performed in 0.1 mol L-1 phosphate buffer solutions at pH 7.4 with an incubation time of 8 min. The analytical curve obtained in pure solutions showed excellent linearity in the 5.0 x 10(-5) to 75 x 10(-5) mol L-1 range, with the limit of detection at 0.4 x 10(-3) gL(-1). The application of such a methodology in tomato samples involved solely liquidising the samples, which were spiked with 6.0 x 10(-6) and 5.0 x 10(-5) mol L-1 carbaryl. Recovery in such samples presented values of 99.0 and 92.4%, respectively. In order to obtain a comparison, HPLC experiments were also conducted under similar conditions. However, the tomato samples have to be manipulated by an extraction procedure (MSPD), which yielded much lower recovery values (78.3 and 84.8%, respectively). On the other hand, the detection limit obtained was much lower than that for the biosensor, i.e., 3.2 x 10(-6) g L-1. Finally, the biosensor methodology was employed to analyze carbaryl directly inside the tomato, without any previous manipulation. In this case, the biosensor was immersed in the tomato pulp, which had previously been spiked with the pesticide for 8 min, removed and inserted in the electrochemical cell. A recovery of 83.4% was obtained, showing very low interference of the matrix constituents. (C) 2007 Elsevier B.V. All rights reserved.

A simple and sensitive detection of diquat herbicide using a dental amalgam electrode A comparison using the chromatographic technique

This paper describes the use of a dental amalgam electrode (DAE) to evaluate the electrochemical behaviour and to develop an electroanalytical procedure for determination of diquat herbicide in natural water and potato samples. The work was based on the square wave voltammetry responses of diquat, which presented two well-defined and reversible reduction peaks, at -0.56 V (peak 1) and -1.00V (peak 2). The experimental and voltammetric parameters were optimised, and the analytical curves were constructed and compared to similar curves performed by high performance liquid chromatography coupled to ultraviolet-visible spectrophotometric detector (HPLC/UV-vis). The responses were directly proportional to diquat concentration in a large interval of concentration, and the calculated detection limits were very similar, around 10 mu g L(-1) (10 ppb) for voltammetric and chromatographic experiments. These values were lower than the maximum residue limit established for natural water by the Brazilian Environmental Agency. The recovery percentages in pure electrolyte, natural water and potato samples showed values from 70% to 130%, demonstrating that the voltammetric methodology proposed is suitable for determining any contamination by diquat in different samples, minimising the toxic residues due to the use of liquid mercury or the adsorptive process relative to use of other solid surfaces. (C) 2009 Published by Elsevier B.V.

Integration of Ligand- and Target-Based Virtual Screening for the Discovery of Cruzain Inhibitors

A myriad of methods are available for virtual screening of small organic compound databases. In this study we have successfully applied a quantitative model of consensus measurements, using a combination of 3D similarity searches (ROCS and EON), Hologram Quantitative Structure Activity Relationships (HQSAR) and docking (FRED, FlexX, Glide and AutoDock Vina), to retrieve cruzain inhibitors from collected databases. All methods were assessed individually and then combined in a Ligand-Based Virtual Screening (LBVS) and Target-Based Virtual Screening (TBVS) consensus scoring, using Receiving Operating Characteristic (ROC) curves to evaluate their performance. Three consensus strategies were used: scaled-rank-by-number, rank-by-rank and rank-by-vote, with the most thriving the scaled-rank-by-number strategy, considering that the stiff ROC curve appeared to be satisfactory in every way to indicate a higher enrichment power at early retrieval of active compounds from the database. The ligand-based method provided access to a robust and predictive HQSAR model that was developed to show superior discrimination between active and inactive compounds, which was also better than ROCS and EON procedures. Overall, the integration of fast computational techniques based on ligand and target structures resulted in a more efficient retrieval of cruzain inhibitors with desired pharmacological profiles that may be useful to advance the discovery of new trypanocidal agents.

Road Sign Recognition based onInvariant Features using SupportVector Machine

Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

Modeling and illustrating requirement prioritization in public e-service development from a value-based perspective

A major problem in e-service development is the prioritization of the requirements of different stakeholders. The main stakeholders are governments and their citizens, all of whom have different and sometimes conflicting requirements. In this paper, the prioritization problem is addressed by combining a value-based approach with an illustration technique. This paper examines the following research question: How can multiple stakeholder requirements be illustrated from a value-based perspective in order to be prioritizable? We used an e-service development case taken from a Swedish municipality to elaborate on our approach. Our contributions are: 1) a model of the relevant domains for requirement prioritization for government, citizens, technology, finances and laws and regulations; and 2) a requirement fulfillment analysis tool (RFA) that consists of a requirement-goal-value matrix (RGV), and a calculation and illustration module (CIM). The model reduces cognitive load, helps developers to focus on value fulfillment in e-service development and supports them in the formulation of requirements. It also offers an input to public policy makers, should they aim to target values in the design of e-services.

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.