Optimality relationships forp-cyclic SOR

Summary The optimality question for blockp-cyclic SOR iterations discussed in Young and Varga is answered under natural conditions on the spectrum of the block Jacobi matrix. In particular, it is shown that repartitioning a blockp-cyclic matrix into a blockq-cyclic form,q, results in asymptotically faster SOR convergence for the same amount of work per iteration. As a consequence block 2-cyclic SOR is optimal under these conditions.Research supported in part by the US Air Force under Grant no. AFOSR-88-0285 and the National Science Foundation under grant no. DMS-85-21154 Present address: Boeing Computer Services, P.O. Box 24346, MS 7L-21, Seattle, WA 98124-0346, USA     

Role of Enterobactin and Intracellular Iron in Cell Lethality During Near-UV Irradiation in Escherichia coli

Abstract— In Escherichia coli, fur mutants that constitutively express their native iron chelating agent, enterobactin, are significantly more sensitive to near-UV radiation (NUV) than wild type. An entA mutant, which is incapable of synthesizing enterobactin, is equal to wild type in resistance to NUV irradiation. However, the addition of Fe⁺³ enterobactin but not Al⁺¹ enterobactin to entA cell suspensions just prior to irradiation results in an increased sensitivity to NUV irradiation. A fes mutant, which is unable to reduce and release iron from enterobactin, is significantly more sensitive to NUV irradiation than wild type. The addition of nontoxic levels of H₂O₂ (5 μ M ) just prior to irradiation significantly increases sensitivity of both fur and fes mutants. These results suggest that one mechanism by which NUV irradiation leads to cell lethality is by creating a transient iron overload, producing very favorable conditions for the production of highly deleterious free radicals through a variety of mechanisms that lead to oxidative stress and DNA damage including lethal and mutagenic lesions. These results are consistent with the hypothesis that enterobactin is an endogenous chromophore for NUV and contributes to cell lethality via the destruction of its ligand, releasing Fe⁺² into the cytoplasm to catalyze the production of highly reactive hydroxyl radicals and other toxic oxygen species via the Haber-Weiss reaction.     

Aggregation-fragmentation in a model of DNA-mediated colloidal assembly

We present results from an off-lattice Monte Carlo simulation of DNA-mediated colloidal assembly. In this simulation, the aggregation-fragmentation of a binary mixture of DNA-coated colloidal particles is studied through a simplified model of base-pair hybridization. Bonding between monomers is modeled as a simple temperature-sensitive A/B-type interaction, where type A and B monomers can bond to only the opposite type (no A/A or B/B attachments are allowed). The actual chemistry of base-pair hybridization is not included in the model. The morphological structures of the clusters formed as well as the kinetics of growth are analyzed in our 2D simulations. The fractal dimension and kinetic growth exponents for clusters formed near the DNA "melting" temperature agree with those seen previously for 2D diffusion-limited cluster aggregation (DLCA) models. The clusters appear more compact, exhibiting signs of local order at intermediate temperature values. At higher temperatures, the formation of large clusters is not favorable under the action of temperature-dependent fragmentation, and the system eventually reaches a steady state as a collection of small aggregates. The temperature profile for this dissolution of the colloidal assembly is sharp, indicating that the selective hybridization process provides a highly sensitive measurement tool. At high temperatures, we analyze the steady-state behavior of the average cluster size in terms of an aggregation-fragmentation model.     

Classification of gasoline data obtained by gas chromatography using a piecewise alignment algorithm combined with feature selection and principal component analysis

A fast and objective chemometric classification method is developed and applied to the analysis of gas chromatography (GC) data from five commercial gasoline samples. The gasoline samples serve as model mixtures, whereas the focus is on the development and demonstration of the classification method. The method is based on objective retention time alignment (referred to as piecewise alignment) coupled with analysis of variance (ANOVA) feature selection prior to classification by principal component analysis (PCA) using optimal parameters. The degree-of-class-separation is used as a metric to objectively optimize the alignment and feature selection parameters using a suitable training set thereby reducing user subjectivity, as well as to indicate the success of the PCA clustering and classification. The degree-of-class-separation is calculated using Euclidean distances between the PCA scores of a subset of the replicate runs from two of the five fuel types, i.e., the training set. The unaligned training set that was directly submitted to PCA had a low degree-of-class-separation (0.4), and the PCA scores plot for the raw training set combined with the raw test set failed to correctly cluster the five sample types. After submitting the training set to piecewise alignment, the degree-of-class-separation increased (1.2), but when the same alignment parameters were applied to the training set combined with the test set, the scores plot clustering still did not yield five distinct groups. Applying feature selection to the unaligned training set increased the degree-of-class-separation (4.8), but chemical variations were still obscured by retention time variation and when the same feature selection conditions were used for the training set combined with the test set, only one of the five fuels was clustered correctly. However, piecewise alignment coupled with feature selection yielded a reasonably optimal degree-of-class-separation for the training set (9.2), and when the same alignment and ANOVA parameters were applied to the training set combined with the test set, the PCA scores plot correctly classified the gasoline fingerprints into five distinct clusters.     

Determination of methadone and its metabolites by high performance liquid chromatography following solid-phase extraction in rat plasma.

This paper describes a rapid, quantitative liquid chromatographic analysis and extraction of methadone and its two major metabolites from rat plasma, using difenoxin as the internal standard. Using a C18 column, resolution of all sample components and the internal standard is achieved with a mobile phase of 25:75 acetonitrile-0.08% diethylamine in 1000 mL water, pH 2.3, at a flow rate of 1.5 mL/min. The injection volume is 100 microL. Standards are linear over the range 25-100 ng, with a lower limit of detection for methadone of 0.25 ng. Within- and between-run coefficients of variation (CV) are 1.24% and 2.94%, respectively. Extraction of methadone and its metabolites from rat plasma uses a solid-phase extraction technique that is highly efficient. Extraction efficiencies of 90.3%, 99.6%, 85.9% and 93.8% were achieved for methadone, its primary and secondary metabolites, and difenoxin, respectively.     

Exact rotamer optimization for protein design

Computational methods play a central role in the rational design of novel proteins. The present work describes a new hybrid exact rotamer optimization (HERO) method that builds on previous dead-end elimination algorithms to yield dramatic performance enhancements. Measured on experimentally validated physical models, these improvements make it possible to perform previously intractable designs of entire protein core, surface, or boundary regions. Computational demonstrations include a full core design of the variable domains of the light and heavy chains of catalytic antibody 48G7 FAB with 74 residues and 10(128) conformations, a full core/boundary design of the beta1 domain of protein G with 25 residues and 10(53) conformations, and a full surface design of the beta1 domain of protein G with 27 residues and 10(60) conformations. In addition, a full sequence design of the beta1 domain of protein G is used to demonstrate the strong dependence of algorithm performance on the exact form of the potential function and the fidelity of the rotamer library. These results emphasize that search algorithm performance for protein design can only be meaningfully evaluated on physical models that have been subjected to experimental scrutiny. The new algorithm greatly facilitates ongoing efforts to engineer increasingly complex protein features.     

Determination of the solubility of organic compounds. II

Summary In general, solid particles liquify when they are exposed to air laden with the vapor of a liquid in which they are soluble. There are exceptions, however, which may be explained by assuming the formation of a solvate.

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Zusammenfassung Feste Teilchen verflüssigen sich im allgemeinen, wenn sie Luft ausgesetzt sind, die mit dem Dampf einer Flüssigkeit geladen ist, in der sie löslich sind. Es wurden aber Ausnahmen gefunden, die möglicherweise durch die Bildung von Solvaten erklärt werden können.

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Résumé Généralement, les particules solides se liquéfient si elles sont exposées à l'air chargé de la vapeur d'un liquide dans lequel elles sont solubles. Il existe cependant des exceptions que l'on peut expliquer en supposant la formation de solvates.

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On the occasion of the hundredth return ofFriedrich Emich's birthday.

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The authors wish to express their appreciation to ProfessorO. F. Steinbach for his suggestions and advice.