A Synthetic Model for the Inhibition of Glutathione Peroxidase by Antiarthritic Gold Compounds

In this paper, inhibition of the glutathione peroxidase activity of two synthetic organoselenium compounds, bis[2-(N,N-dimethylamino)benzyl]diselenide (5) and bis[2-(N,N-dimethylamino)benzyl]selenide (9), by gold(I) thioglucose (1), chloro(triethylphosphine)gold(I), chloro(trimethylphosphine)gold(I), and chloro(triphenylphosphine)gold(I) is described. The inhibition is found to be competitive with respect to a peroxide (H2O2) substrate and noncompetitive with respect to a thiol (PhSH) cosubstrate. The diselenide 5 reacts with PhSH to produce the corresponding selenol (6), which upon treatment with 1 equiv of gold(I) chlorides produces the corresponding gold selenolate complexes 11−13. However, the addition of 1 equiv of selenol 6 to complexes 11−13 leads to the formation of bis-selenolate complex 14 by ligand displacement reactions involving the elimination of phosphine ligands. The phosphine ligands eliminated from these reactions are further converted to the corresponding phosphine oxides (R3PO) and selenides (R3PSe). In addition to the replacement of the phosphine ligand by selenol 6, an interchange between two different phosphine ligands is also observed. For example, the reaction of complex 11 having a trimethylphosphine ligand with triphenylphosphine produces complex 13 by phosphine interchange reactions via the formation of intermediates 15 and 16. The reactivity of selenol 6 toward gold(I) phosphines is found to be similar to that of selenocysteine.

Hybrid Materials Combining Photoactive 2,3-Didecyloxy Anthracene Physical Gels and Gold Nanoparticles

Organic/inorganic hybrid gels have been developed in order to control the three-dimensional structure of photoactive nanofibers and metallic nanoparticles (NPs). These materials are prepared by simultaneous self-assembly of the 2,3-didecyloxyanthracene (DDOA) gelator and of thiol-capped gold nanoparticles (AuNPs). TEM and fluorescence measurements show that alkane-thiol capped AuNPs are homogeneously dispersed and tightly attached to the thermoreversible fibrillar network formed by the organogelator in n-butanol or n-decanol. Rheology and thermal stability measurements reveal moreover that the mechanical and thermal stabilities of the DDOA organogels are not significantly altered and that they remain strong, viscoelastic materials. The hybrid materials display a variable absorbance in the visible range because of the AuNPs, whereas the strong luminescence of the DDOA nanofibers is efficiently quenched by micromolar amounts of AuNPs. Besides, we obtained hybrid aerogels using supercritical CO2. These arc very low-density porous materials showing fibrillar networks oil which fluorinated gold NPs arc dispersed. These hybrid materials are of high interest because of their tunable optical properties and are under investigation for efficient light scattering.

Properties of the gold related acceptor level in silicon

The apparent thermal activation energy of 0.56 eV and the electron thermal capture cross section of 2.0 × 10-16 cm2 are measured for the gold related acceptor level in p+ nn+ silicon diodes by isothermal current transient and DLTS techniques. Using the emission and capture rate data and a degeneracy ratio of 2, the energy separation of the trap level from the conduction band is calculated and found to have the same temperature dependence as the band gap indicating that the acceptor level is pinned with respect to the valence band a t Ev + 0.637 eV.

Phthalocyanine macrocycle as stabilizer for gold and silver nanoparticles

A one-step process was used for the preparation of gold and silver nanoparticles stabilized by an aminophthalocyanine macrocycle. The resultant nanoparticles were characterized by absorption spectra, infrared spectroscopy, scanning electron microscopy and transmission electron microscopy. The nanoparticles were found to possess relatively narrow size distribution. The gold nanoparticles have an average diameter of similar to 2 nm, while silver particles have 4-5 nm. Preliminary studies on fluorescence and surface enhanced Raman spectroscopy were carried out using these nanoparticles. Fluorescence studies indicate that gold nanoparticles do not quench the fluorescence, while silver nanoparticles do. The stabilized nanoparticles showed enhancement of the Raman signals, thus revealing that they are good substrates for surface enhanced Raman scattering studies.

Inferring neuronal network connectivity from spike data: A temporal data mining approach

Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent d evelopments in electrophysiology and imaging allow one to simultaneously record activities of hundreds of neurons. Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem. This task involves finding significant temporal patterns from vast amounts of symbolic time series data. In this paper we show that the frequent episode mining methods from the field of temporal data mining can be very useful in this context. In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal patterns in such data. Here we show that, using the set of discovered frequent episodes from multi-neuronal data, one can infer different types of connectivity patterns in the neural system that generated it. For this purpose, we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under these temporal constraints. Through extensive simulation studies we demonstrate that these methods are useful for unearthing patterns of neuronal network connectivity.

Microbial aspects of acid generation and bioremediation with relevance to indian mining

The role of Acidithiobacillus group of bacteria in acid generation and heavy metal dissolution was studied with relevance to some Indian mines. Microorganisms implicated in acid generation such as Acidithiobacillus Acidithicibacillus thiooxidans and Leptospirillum ferrooxidans were isolated from abandoned mines, waste rocks and tailing dumps. Arsenite oxidizing Thiomonas and Bacillus group of bacteria were isolated and their ability to oxidize As (111) to As (V) established. Mine isolated Sulfate reducing bacteria were used to remove dissolved copper, zinc, iron and arsenic from solutions.

A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

Electrochemical Functionalization of a Gold Electrode with Redox-Active Self-Assembled Monolayer for Electroanalytical Application

The electrochemical functionalization of a Au electrode with a redox-active monolayer and the electroanalytical applications of the functionalized electrode are described. Reaction of the electrochemically derived o-quinone on the self-assembled monolayer (SAM) of 6-mercaptopurine (MPU) on a Au electrode gives a redox-active 4-(6-mercapto-purin-9-yl)benzene-1,2-diol (MPBD) self-assembly under optimized conditions. Electrochemical quartz crystal microbalance technique has been employed to follow the functionalization of the electrode in real time. Electrochemically derived o-quinone reacts at the N(9) position of the self-assembled MPU in neutral pH. Raman spectral measurement confirms the reaction of o-quinone on MPU self-assembly. MPBD shows a well-defined reversible redox response, characteristic of a surface-confined redox mediator at 0.21 V in neutral pH. The anodic peak potential (Epa) of MPBD shifts by −60 mV while changing the solution pH by 1 unit, indicating that the redox reaction involves two electrons and two protons. The surface coverage (Γ) of MPBD was 7.2 ± 0.3 × 10-12 mol/cm2. The apparent heterogeneous rate constant (ksapp) for MPBD was 268 ± 6 s-1. MPBD efficiently mediates the oxidation of nicotinamide adenine dinucleotide (NADH) and ascorbate (AA). A large decrease in the overpotential and significant increase in the peak current with respect to the unmodified electrode has been observed. Surface-confined MPBD has been successfully used for the amperometric sensing of NADH and AA in neutral pH at the nanomolar level.

Modeling of formation of gold nanoparticles by citrate method

Properties of nanoparticles are size dependent, and a model to predict particle size is of importance. Gold nanoparticles are commonly synthesized by reducing tetrachloroauric acid with trisodium citrate, a method pioneered by Turkevich et al (Discuss. Faraday Soc. 1951, 11, 55). Data from several investigators that used this method show that when the ratio of initial concentrations of citrate to gold is varied from 0.4 to similar to 2, the final mean size of the particles formed varies by a factor of 7, while subsequent increases in the ratio hardly have any effect on the size. In this paper, a model is developed to explain this widely varying dependence. The steps that lead to the formation of particles are as follows: reduction of Au3+ in solution, disproportionation of Au+ to gold atoms and their nucleation, growth by disproportionation on particle surface, and coagulation. Oxidation of citrate results in the formation of dicarboxy acetone, which aids nucleation but also decomposes into side products. A detailed kinetic model is developed on the basis of these steps and is combined with population balance to predict particle-size distribution. The model shows that, unlike the usual balance between nucleation and growth that determines the particle size, it is the balance between rate of nucleation and degradation of dicarboxy acetone that determines the particle size in the citrate process. It is this feature that is able to explain the unusual dependence of the mean particle size on the ratio of citrate to gold salt concentration. It is also found that coagulation plays an important role in determining the particle size at high concentrations of citrate.

Small-angle x-ray scattering study of the aggregation of gold nanoparticles during formation at the toluene-water interface

We report the results of an in situ small-angle x-ray scattering (SAXS) study of the aggregation of gold nanoparticles formed by an interfacial reaction at the toluene-water interface. The SAXS data provide a direct evidence for aggregate formation of nanoparticles having 1.3 nm gold core and an organic shell that gives a core-core separation of about 2.5 nm. Furthermore, the nanoparticles do not occupy all the cites of 13-member cluster. This occupancy decreases with reaction time and indicate reorganization of the clusters that generates planner disklike structures. A gradual increase in fractal dimension from 1.82 to 2.05 also indicate compactification of cluster aggregation with reaction time, the final exponent being close to 2 expected for disklike aggregates.

Hybrid learning scheme for data mining applications

Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

Hybrid learning scheme for data mining applications

Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

Electrochemical reduction of oxygen on gold and boron-doped diamond electrodes in ambient temperature, molten acetamide-urea-ammonium nitrate eutectic melt

The electrochemical reduction of oxygen has been studied on gold, boron-doped diamond (BDD) and glassy carbon (GC) electrodes in a ternary eutectic mixture of acetamide (CH3CONH2), urea (NH2CONH2) and ammonium nitrate (NH4NO3). Cyclic voltammetry (CV), differential pulse voltammetry (DPV), chronoamperometry and rotating disk electrode (RDE) voltammetry techniques have been employed to follow oxygen reduction reaction (ORR). The mechanism for the electrochemical reduction of oxygen on polycrystalline gold involves 2-step. 2-electron pathways of O-2 to H2O2 and further reduction of H2O2 to H2O. The first 2-electron reduction of O-2 to H2O2 passes through superoxide intermediate by 1-electron reduction of oxygen. Kinetic results suggest that the initial 1-electron reduction of oxygen to HO2 is the rate-determining step of ORR on gold surfaces. The chronoamperometric and ROE studies show a potential dependent change in the number of electrons on gold electrode. The oxygen reduction reaction on boron-doped diamond (BOO) seems to proceed via a direct 4-electron process. The reduction of oxygen on the glassy carbon (GC) electrode is a single step, irreversible, diffusion limited 2-electron reduction process to peroxide. (C) 2010 Elsevier Ltd. All rights reserved.