Facile preparation and some applications of an affinity matrix with a cleavable connector arm containing a disulfide bond

A versatile affinity matrix in which the ligand of interest is linked to the matrix through a connector arm containing a disulfide bond is described. It can be synthesized from any amino-substituted matrix by successive reaction with 2-imino-thio-lane, 5, 5'-dithiobis(2-nitrobenzoic acid), and a thiol derivative of the ligand of choice. The repertoire of ligands can be significantly increased by the appropriate use of avidin-biotin bridges. After adsorption of the material to be fractionated, elution can be effected by reducing the disulfide bond in the connector arm with dithiothreitol. Examples of the preparation and use of various affinity matrices based on amino-substituted Sepharose 6MB are given. One involves the immobilization of the Fab' fragment of a monoclonal antibody against Aspergillus oryzae β-galactosidase and the specific binding of that enzyme to the resulting immunoaffinity matrix. Another involves the immobilization of N-biotinyl-2-thioethylamine followed by complex formation with avidin. The resulting avidin-substituted matrix was used for the selective adsorption and subsequent recovery of mouse hybridoma cells producing anti-avidin antibodies. By further complexing the avidin-substituted matrix with appropriate biotinylated antigens, it should be possible to fractionate cells producing antibodies against a variety of antigens.

Agents Based Algorithms for Design Parameter Estimation in Contaminant Transport Inverse Problems

A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

Detection of multiple source locations using a glowworm metaphor with applications to collective robotics

This paper presents a glowworm swarm based algorithm that finds solutions to optimization of multiple optima continuous functions. The algorithm is a variant of a well known ant-colony optimization (ACO) technique, but with several significant modifications. Similar to how each moving region in the ACO technique is associated with a pheromone value, the agents in our algorithm carry a luminescence quantity along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luminescence and have a circular sensor range. The glowworms depend on a local-decision domain to compute their movements. Simulations demonstrate the efficacy of the proposed glowworm based algorithm in capturing multiple optima of a multimodal function. The above optimization scenario solves problems where a collection of autonomous robots is used to form a mobile sensor network. In particular, we address the problem of detecting multiple sources of a general nutrient profile that is distributed spatially on a two dimensional workspace using multiple robots.

Purification and properties of an inhibitor for nicotinamide-adenine dinucleotidase from Mycobacterium tuberculosis H37Rv

The excess of free inhibitor for the enzyme NADase present in the crude cell-free extracts of Mycobacterium tuberculosis H37Rv has been purified by chromatography on a DEAE-cellulose column and adsorption and elution from alumina Cγ-gel. Some of the properties of the purified inhibitor have been studied and attempts have been made to elucidate the nature of combination between the enzyme and the inhibitor. The purified inhibitor may be glycoprotein in nature, and considerable loss in the activity of the inhibitor preparations could be brought about by trypsin digestion. The inhibitor was specific for the enzymes from M. tuberculosis H37Rv or H37Ra and could be stored for at least 6 months in the frozen state below 0 ° without any significant loss in activity. The inhibition was noncompetitive with respect to the substrates, and the enzyme-inhibitor complex formed was undissociable.

Purification and properties of an inhibitor for nicotinamide-adenine dinucleotidase from Mycobacterium tuberculosis H37Rv

The excess of free inhibitor for the enzyme NADase present in the crude cell-free extracts of Mycobacterium tuberculosis H37Rv has been purified by chromatography on a DEAE-cellulose column and adsorption and elution from alumina Cγ-gel. Some of the properties of the purified inhibitor have been studied and attempts have been made to elucidate the nature of combination between the enzyme and the inhibitor. The purified inhibitor may be glycoprotein in nature, and considerable loss in the activity of the inhibitor preparations could be brought about by trypsin digestion. The inhibitor was specific for the enzymes from M. tuberculosis H37Rv or H37Ra and could be stored for at least 6 months in the frozen state below 0 ° without any significant loss in activity. The inhibition was noncompetitive with respect to the substrates, and the enzyme-inhibitor complex formed was undissociable.

Effect of some organic acids on leaf phosphatase from French beans

1. The common organic acids inhibited leaf phosphatase activity, This effect is mostly due to the hydroxyl groups in them. 2. The less common organic acids, which have only carboxyl groups, did not show any marked inhibitory action on phosphatase activity. 3. The less common organic acids eluted the leaf phosphatase after adsorption on aluminacγ gel to a greater extent than the more common organic acids. 4. The second elution of the purified enzyme from the aluminacγ gel was not possible with the organic acids as it was adsorbed on the gel.

A study of the purification and properties of tryptophan synthetase of Bengal gram (Cicer arietinum)

Active preparations of tryptophan synthetase were obtained from Bengal gram (Cicer arietinum) by the following procedure: (1) precipitation of inactive materials by manganous sulfate, (2) Adsorption of impurities on Alumina Cγ, (3) Adsorption of tryptophan synthetase on tricalcium phosphate gel, removal of inert protein from the gel by treatment with phosphate buffer (pH 7.2), and selective elution of the enzyme by 0.15 M phosphate buffer pH 7.2 containing 10% ammonium sulfate and 10−3 M serine. A 220-fold purification of the enzyme with 44% recovery of the activity was achieved. The pH optimum, effect of temperature, and substrate concentration and other properties of the purified enzyme have been studied in detail. Only the Image -isomer of serine takes part in the reaction. The Km values for indole, Image -serine, and Image -serine were calculated to be 0.66, 4.1, and 8.6 × 10−4 M, respectively. A kinetic study of the inhibition of tryptophan synthetase by indole-propionic acid has shown that it is of a competitive type. It has been demonstrated for the first time that 4-nitro-salicylaldehyde can replace pyridoxal phosphate as a coenzyme for the tryptophan synthetase reaction.

A colorimetric method for determination of pyrocatechol and related substances

A colorimetric assay for the quantitative determination of catecholic compounds was developed. The method was based on the observation that a red color was formed when nitrite was added to a solution containing pyrocatechol and sodium tungstate. Aromatic amines interfere with the reaction but this could be overcome by the addition of formaldehyde. When interfering substances are present along with pyrocatechol, it can be readily separated by paper chromatography and estimated after elution from the filter paper.

Oxidation of catechol in plants : III. Purification and properties of the diphenylene dioxide 2,3-quinone-forming enzyme system from Tecoma leaves

In attempting to determine the nature of the enzyme system mediating the conversion of catechol to diphenylenedioxide 2,3-quinone, in Tecoma leaves, further purification of the enzyme was undertaken. The crude enzyme from Tecoma leaves was processed further by protamine sulfate precipitation, positive adsorption on tricalcium phosphate gel, and elution and chromatography on DEAE-Sephadex. This procedure yielded a 120-fold purified enzyme which stoichiometrically converted catechol to diphenylenedioxide 2,3-quinone. The purity of the enzyme system was assessed by polyacrylamide gel electrophoresis. The approximate molecular weight of the enzyme was assessed as 200,000 by gel filtration on Sephadex G-150. The enzyme functioned optimally at pH 7.1 and at 35 °C. The Km for catechol was determined as 4 × 10−4 Image . The enzyme did not oxidize o-dihydric phenols other than catechol and it did not exhibit any activity toward monohydric and trihydric phenols and flavonoids. Copper-chelating agents did not inhibit the enzyme activity. Copper could not be detected in the purified enzyme preparations. The purified enzyme was not affected by extensive dialysis against copper-complexing agents. It did not show any peroxidase activity and it was not inhibited by catalase. Hydrogen peroxide formation could not be detected during the catalytic reaction. The enzymatic conversion of catechol to diphenylenedioxide 2,3-quinone by the purified Tecoma leaf enzyme was suppressed by such reducing agents as GSH and cysteamine. The purified enzyme was not sensitive to carbon monoxide. It was not inhibited by thiol inhibitors. The Tecoma leaf was found to be localized in the soluble fraction of the cell. Treatment of the purified enzyme with acid, alkali, and urea led to the progressive denaturation of the enzyme.

Theoretical foundations for multiple rendezvous of glowworm-inspired mobile agents with variable local-decision domains

We present the theoretical foundations for the multiple rendezvous problem involving design of local control strategies that enable groups of visibility-limited mobile agents to split into subgroups, exhibit simultaneous taxis behavior towards, and eventually rendezvous at, multiple unknown locations of interest. The theoretical results are proved under certain restricted set of assumptions. The algorithm used to solve the above problem is based on a glowworm swarm optimization (GSO) technique, developed earlier, that finds multiple optima of multimodal objective functions. The significant difference between our work and most earlier approaches to agreement problems is the use of a virtual local-decision domain by the agents in order to compute their movements. The range of the virtual domain is adaptive in nature and is bounded above by the maximum sensor/visibility range of the agent. We introduce a new decision domain update rule that enhances the rate of convergence by a factor of approximately two. We use some illustrative simulations to support the algorithmic correctness and theoretical findings of the paper.

Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources

This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

An ensemble of B-DNA dinucleotide geometries lead to characteristic nucleosomal DNA structure and provide plasticity required for gene expression

Background: A nucleosome is the fundamental repeating unit of the eukaryotic chromosome. It has been shown that the positioning of a majority of nucleosomes is primarily controlled by factors other than the intrinsic preference of the DNA sequence. One of the key questions in this context is the role, if any, that can be played by the variability of nucleosomal DNA structure. Results: In this study, we have addressed this question by analysing the variability at the dinucleotide and trinucleotide as well as longer length scales in a dataset of nucleosome X-ray crystal structures. We observe that the nucleosome structure displays remarkable local level structural versatility within the B-DNA family. The nucleosomal DNA also incorporates a large number of kinks. Conclusions: Based on our results, we propose that the local and global level versatility of B-DNA structure may be a significant factor modulating the formation of nucleosomes in the vicinity of high-plasticity genes, and in varying the probability of binding by regulatory proteins. Hence, these factors should be incorporated in the prediction algorithms and there may not be a unique `template' for predicting putative nucleosome sequences. In addition, the multimodal distribution of dinucleotide parameters for some steps and the presence of a large number of kinks in the nucleosomal DNA structure indicate that the linear elastic model, used by several algorithms to predict the energetic cost of nucleosome formation, may lead to incorrect results.

Variations in the Levels of Aminoacylation and Modified Nucleotide Content Between Total Transfer-RNAS From Chloroplasts and Etioplasts in Cucumber Cotyledons

Total tRNAs isolated from chloroplasts and etioplasts of cucumber cotyledons were compared with respect to amino acid acceptance, isoacceptor distribution and extent of modification. Aminoacylation of the tRNAs with nine different amino acids studied indicated that the relative acceptor activities of chloroplast total tRNAs for four amino acids are significantly higher than etioplast total tRNAs. Two dimensional polyacrylamide gel electrophoresis (2D-PAGE) of chloroplast total tRNAs separated at least 32 spots, while approximately 41 spots were resolved from etioplast total tRNAs. Comparison of the reversed-phase chromatography (RPC-5) profiles of chloroplast and etioplast leucyl-, lysyl-, phenylalanyl-, and valyl-tRNA species showed no qualitative differences in the elution profiles. However, leucyl-, lysyl- and valyl-tRNA species showed quantitative differences in the relative amounts of the isoaccepting species present in chloroplasts and etioplasts. The analysis of modified nucleotides of total tRNAs from the two plastid types indicated that total tRNA from etioplasts was undermodified with respect to ribothymidine, isopentenyladenosine/hydroxy-isopentenyladenosine, 1-methylguanosine and 2-o-methylguanosine. This indicates that illumination may cause de novo synthesis of chloroplast tRNA-modifying enzymes encoded for by nuclear genes leading to the formation of highly modified tRNAs in chloroplasts. Based on these results, we speculate that the observed decrease in levels of aminoacylation, variations in the relative amounts of certain isoacceptors, and differences in the electrophoretic mobilities of some extra tRNA spots in the etioplast total tRNAs as compared to chloroplast total tRNAs could be due to some partially undermodified etioplast tRNAs. Taken together, the data suggested that the light-induced transformation of etioplasts into chloroplasts is accompanied by increases in the relative levels of some functional chloroplast tRNAs by post transcriptional nucleotide modifications.