Isolation and partial characterization of sheep plasma α1-mucoprotein

1. 1. Sheep plasma α1-mucoprotein was isolated in an electrophoretically homogeneous state by a combination of ammonium sulphate saturation, isoelectric precipitation and preparative agar electrophoresis in a yield of approx. 150 mg/l of plasma. 2. 2. The mucoprotein was water-soluble, non-coagulable on heating at 100°, not precipitable by 1.8 M perchloric acid, 10% trichloroacetic acid but precipitable by saturated ammonium sulphate solution, 0.6 M sulfosalicylic acid and 5% phosphotungstic acid in 2 N HCl. It had E1 cm1 % value of 9.57 at 278 mμ in water, refractive-index index increment 1.9·10-4 (g/l) in water, isoelectric point at pH 4.45 (sodium acetate-acetic acid buffer) and was homogeneous in pH range 4.0-11.5 but at pH values 2.6 and 3.5 showed some dissociation. 3. 3. The mucoprotein had the following chemical composition: Nitrogen, 12.4%; polypeptide, 77.4%; total hexose (only mannose and galactose), 7.1%; fucose, 1.0%; glucosamine, 4.9% and sialic acid, 4.8%. It had no N-terminal amino acid.

Isolation of Salmonella typhimurium mutants affecting the plaque morphology of phage P22

Salmonella typhimurium mutants affecting the plaque morphology of P22 and other phages have been isolated. Using one such bacterial mutant phage mutants making turbid plaques have been isolated.

A new approach for fault location identification in transmission system using stability analysis and SVMs

This paper presents a new approach to the location of fault in the high voltage power transmission system using Support Vector Machines (SVMs). A knowledge base is developed using transient stability studies for apparent impedance swing trajectory in the R-X plane. SVM technique is applied to identify the fault location in the system. Results are presented on sample 3-power station, a 9-bus system illustrate the implementation of the proposed method.

Neural network approach for fault location in unbalanced distribution networks with limited measurements

This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.

Isolation and characterization of a gonadotropin receptor binding inhibitor from porcine follicular fluid

The presence of a gonadotropin receptor binding inhibitor in pooled porcine follicular fluid has been demonstrated. Porcine follicular fluid fractionation on DE-32 at near neutral pH, followed by a cation exchange chromatography on SPC-50 and Cibacron blue affinity chromatography, yielded a partially purified gonadotropin receptor binding inhibitor (GI-4). The partially purified GI binding inhibitor inhibited the binding of both 125I labelled hFSH and hCG to rat ovarian receptor preparation. SDS electrophoresis of radioiodinated partially purified GI followed by autoradiography made it possible to identify the binding component as a protein of molecular weight of 80000. Subjecting 125I labelled GI-4 to chromatography on Sephadex G-100 helped obtain a homogeneous material, Gl-5. The 125I labelled GI-5 exhibited in its binding to ovarian membrane preparations characteristics typical of a ligand-receptor interaction such as saturability, sensitivity to reaction conditions as time, ligand and receptor concentrations and finally displaceability by unlabelled inhibitor as well as FSH and hCG in a dose dependent manner. This material could bind ovarian receptors for both FSH and LH, its binding being inhibited by added FSH or hCG in a dose dependent manner.

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.

Isoselenocyanates derived from Boc/Z-amino acids: synthesis, isolation,characterization, and application to the efficient synthesis of unsymmetrical selenoureas and selenoureidopeptidomimetics

Isoselenocyanates derived from Boc/Z-amino acids are prepared by the reaction of the corresponding isonitriles with selenium powder in presence of triethylamine at reflux. The utility of these new classes of isoselenocyanates in the preparation of selenoureidodipeptidomimetics possessing both amino as well as carboxy termini has been accomplished. The H-1 NMR analysis confirmed that the protocol involving the conversion of isonitriles to isoselenocyanates and their use as coupling agents in assembling selenour-eido derivatives is free from racemization. (C) 2010 Elsevier Ltd. All rights reserved.

Isolation Of A Cytokinin-Binding Protein From Cucumis-Sativus Cotyledons

A cytokinin-binding protein which exists as monomer and dimer was isolated from cucumber (Cucumis sativus L. var Guntur) cotyledons by affinity chromatography on AH-Sepharose-pi6 Ap /s> column. The protein bound to [3H]-N6-(Δ2-isopentenyl) adenosine trialcohol. On Sephadex G-50 chromatography it gave 2 peaks corresponding to molecular weight 4000 and 8000 daltons. On sodium dodecyl sulphate-polyacrylamide gel electrophoresis, it gave only one band with an apparent molecular weight of 4000 daltons.

Rapid isolation of lysyl-tRNA synthetase from rat liver

The high molecular weight aminoacyl-tRNA synthetase complex (the 24S complex) was isolated from rat liver by ultracentrifugation. The lysyl-tRNA synthetase (E.C. 6.1.1.6) was selectively dissociated by hydrophobic interaction chromatography on 1,6 diaminohexyl agarose followed by hydroxylapatite chromatography and DEAE chromatography. The lysyl-tRNA synthetase dissociated from the 24S synthetase complex was purified approximately to 2700 fold with 14% yield.

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.

Chemical approaches of penicillin allergy—III Isolation of the penicillin-free carrier receptor protein (CRP) on a polymeric 7-deoxy penicillin analogue template and its role in penicillin immunogeneses in rabbit and man

Specific penicillin-carrier receptor proteins (CRP) have been isolated from the sera of penicillin allergic rabbits and human subjects in the unconjugated native state in electrophoretically homogeneous form by employing a synthetic polymeric affinity template containing the 7-deoxy analogue of penicillin G. The synthesis of the 7-deoxy analogue has been described. In this affinity system the antipenicillin-antibody is desorbed by 0·9M thiourea and the CRP in 8M urea. The CRP after incubation with penicillin is converted into the full-fledged antigen. Studies on the origin of CRP and the nature of antibody as well as comparative studies on the properties of the rabbit antibody and those of antibodies elicited by a BSA-BPO conjugate are reported.