Determination of binding geometry of DNA-adduct systems through induced circular dichroism

Many molecules (adducts) bound to DNA are postulated to intercalate between successive DNA base pairs. Linear dichroism (LD) has been used to yield information about the angular orientation of the adduct relative to the helix axis, but cannot probe the orientation within the plane perpendicular to this axis. A model is presented in this paper which predicts that the degree of alignment relative to a DNA fixed axis in this plane may be directly probed through the sign of the circular dichroism (CD) induced in an adduct transition of known polarization. Comparison with experimental data suggests that the method can complement LD studies in giving detailed information about the binding geometry.     

Construction of the Pharmacophore Model of Glycogen Synthase Kinase-3 Inhibitors

A three dimensional pharmacophore model has been generated for glycogen synthase kinase-3 （GSK-3） inhibitots. A dataset consisting of 89 compounds was selected on the basis of the information content of the structures and activity data as required by the CATALYST system. The optimum model with four features （one hydrogen-bond acceptor unit, one ring aromatic unit, and two hydrophobic aromatic units） was selected with a good correlation coefficient （0.95）. This model is able to predict the activity of other known GSK-3 inhibitors not included in the model generation, and can be further used to identify structurally diverse compounds with desired biological activity by virtual screening.     

Chemometric Methods for the Study of Toxic Metals on the Growth of Plants: Use of Experimental Design and Response Surface Methodology

Abstract

Chemometrics is a recent discipline concerned, principally, with the application of mathematics and statistics to laboratory systems. One way in which the chemometrician can aid the environmental analytical chemist is via planned experimental designs. In this paper the importance of experimental design is illustrated and the main considerations prior to experimentation, namely, degrees of freedom, analytical errors, coding and modelling, are outlined. This is exemplified by a study of the influence of potentially toxic heavy metals on the growth of barley seedlings. Undesigned univariate experiments suggest that Tl is probably more toxic than Cd. A three factor central composite design is reported, to study the relative toxicities of Tl, Cd and Pb and also of Tl, Fe and Zn. The paper exemplifies how much information can be obtained from the resultant experimental response data. Multilinear regression can be employed to produce a quadratic model: this can be interpreted graphically by reconstructed univariate response curves and 3-dimensional response surfaces. Analysis of variance is a statistical method for computing how well the model has been fitted, taking into account analytical errors. With the aid of modern graphical computing, a variety of confidence intervals can be displayed for both univariate and bivariate responses. The usefulness of the design can be visualised by displaying leverage over and outside the experimental region. Finally future trends in multivariate response methodology are discussed.     

Understanding hERG inhibition with QSAR models based on a one-dimensional molecular representation

Blockage of the potassium channel encoded by the human ether-a-go-go related gene (hERG) is well understood to be the root cause of the cardio-toxicity of numerous approved and investigational drugs. As such, a cascade of in vitro and in vivo assays have been developed to filter compounds with hERG inhibitory activity. Quantitative structure activity relationship (QSAR) models are used at the very earliest part of this cascade to eliminate compounds that are likely to have this undesirable activity prior to synthesis. Here a new QSAR technique based on the one-dimensional representation is described in the context of the development of a model to predict hERG inhibition. The model is shown to perform close to the limits of the quality of the data used for model building. In order to make optimal use of the available data, a general robust mathematical scheme was developed and is described to simultaneously incorporate quantitative data, such as IC50 = 50 nM, and qualitative data, such as inactive or IC50 > 30 μM into QSAR models without discarding any experimental information.     

Prediction of ion channel activity using binary kernel discrimination

Voltage-gated ion channels are a diverse family of pharmaceutically important membrane proteins for which limited 3D information is available. A number of virtual screening tools have been used to assist with the discovery of new leads and with the analysis of screening results. One such tool, and the subject of this paper, is binary kernel discrimination (BKD), a machine-learning approach that has recently been applied to applications in chemoinformatics. It uses a training set of compounds, for which both structural and qualitative activity data are known, to produce a model that can then be used to rank another set of compounds in order of likely activity. Here, we report the use of BKD to build models for the prediction of five different ion channel targets using two types of activity data. The results obtained suggest that the approach provides an effective way of prioritizing compounds for acquisition and testing.     

Beyond contract compliance: Common problems found during validation of radioanalytical data

In the United States today, legally defensible data is needed for environmental assessments, waste characterization, and dose assessments. A closer look at the raw data and interpretation of the results can reveal other problems that affect the data usability based on the project data quality objectives. The common problems include the following: incomplete sample dissolution, loss of volatile radionuclides during sample preparation, difficulties in aliquot subsampling during sample preparation, lack of a sample-specific chemical recovery mechanisms, use of an inappropriate sample-specific chemical recovery mechanism, not using enough of the sample-specific chemical recovery mechanism to obtain sufficient counting statistics for the recovery result, gamma-spectrometry misidentification, use of incorrect abundances or intensities, and incomplete separation of isotopes prior to alpha-spectroscopy analysis. These problems can result in the estimation or rejection of the results. Although most of these problems can be avoided, no improvement in their frequency has been noticed over time. This paper is written in an attempt to call attention to the typical problems in hopes that the contract laboratories as well as the government laboratories will review their practices to avoid these problems.     

Bias analysis of proficiency testing programme results

A proficiency testing programme might involve a great number of participating laboratories coming from different countries or regions, and normally they analysed the same test materials using their own routine analytical methods. Hence, the results of a proficiency testing programme may contain valuable information which could serve purposes other than just performance evaluation. This study attempted to extract information from the results of a proficiency testing programme for the purposes of educating the participating laboratories as suggested by ISO/IEC 17043. The “bias analysis” approach introduced in this study was based on the statistical model of measurement and the nature of bias in chemical analysis. With this approach, the participating laboratories could estimate the bias associated with different settings of experimental conditions according to the statistics of subset distribution of the reported results from the participating laboratories. This would be useful for them to review the analytical procedures they used and modify their methods if needed. The approach was applied to the analysis of data obtained from a number of past proficiency testing programmes, and the findings were discussed in this paper.     

Minimum value assured by a method to determine gold in alloys by using laser-induced breakdown spectroscopy and partial least-squares calibration model

A procedure for estimating the minimum value assured by an analytical method has been developed. It is applied to the determination of gold in jewellery alloys by means of a recently proposed spectroscopy technique. The laser-induced breakdown spectroscopic data of 17 gold alloys, with gold concentration ranging between 50 and 100% were used as calibration set for carrying out the partial least-squares regression (PLS). Ninety alloys, with known gold concentration, were used to evaluate the method’s accuracy. Finally, the minimum guaranteed value of the gold content was analysed, taking into account the values for gold hallmark in Spanish regulations.     

The determination of organochlorine compounds and petroleum hydrocarbons in a seaweed sample: results of a world-wide intercomparison exercise

A seaweed sample (Fucus sp.) was prepared, homogenised and distributed to laboratories worldwide as the IAEA-140 intercomparison material for the analysis of organochlorine compounds and petroleum hydrocarbons. A total of 80 laboratories from 51 countries reported results for this sample. The data sets reported by laboratories were evaluated statistically and the mean concentration values could be computed with 95% confidence limits for a large number of analytes. The accuracy of the analytical performance of each laboratory has been introduced by using Z-scores. The spread of results reported generally indicates that the accurate determination of many persistent organic pollutants, such as hexachlorobenzene, lindane, Aroclors or fluoranthene, is still difficult for many laboratories. The final results of this intercomparison exercise enable individual participants to assess their performance and, where necessary, to introduce appropriate modifications in their analytical procedures. Furthermore, as a series of statistical criteria was fulfilled for a number of compounds, the sample IAEA-140 can now be used as a reference material for quality control in the determination of chlorinated compounds and petroleum hydrocarbons in environmental samples.     

Using Bayes methods and mixture models in inter-laboratory studies with outliers

Inter-laboratory studies (especially so-called key comparisons) are conducted to evaluate both national and international equivalence of measurement. In these studies, a reference value of some measurand (the quantity intended to be measured) is developed and results for all laboratories are compared to this single value. How to determine the reference value is not completely obvious if there are observations and/or laboratories that could be considered outliers. Since ignoring results from one or more participating laboratories is untenable in practical terms, developing methods that are robust to the possibility that a small fraction of the laboratories produces observations unlike those from the others is critical. This paper outlines two Bayesian methods of analyzing inter-laboratory data that have been proposed in the literature and suggests three modifications of one that are more robust to outliers. A simulation study is conducted to compare the five methods.     

UV index experimental values during the years 2000 and 2001 from the Spanish broadband UV-B radiometric network

An analysis is made of experimental ultraviolet erythemal solar radiation data measured during the years 2000 and 2001 by the Spanish UV-B radiation evaluation and prediction network. This network consists of 16 Robertson-Berger type pyranometers for evaluating solar erythemal radiation and five Brewer spectroradiometers for evaluating the stratospheric ozone. On the basis of these data the Ultraviolet Index (UVI) was evaluated for the measuring stations that are located either in coastal regions or in the more densely populated regions inland on the Iberian Peninsula. It has been checked that in most cases the maximum irradiance values corresponded to solar noon, although there were exceptions that could be explained by cloudiness. The maximum experimental values of the UVI were around 9 during the summer, though frequently passing this value at the inland measurement stations. The annual accumulated dose of irradiation on a horizontal plane has also been studied, as well as the evolution through the year in units of energy, standard erythemal doses and minimum erythemal doses, according to different phototypes.     

Creep loading response and complete loading–unloading investigation of industrial anti-vibration systems

This article presents engineering approaches to evaluate creep loading response and a complete loading–unloading procedure for rubber components used as anti-vibration applications. A damage function for creep loading and a rebound resilience function for mechanical unloading are introduced into hyperelastic models independently. Hence, a hyperelastic model can be extended for both creep and unloading evaluations. A typical rubber product and a dumbbell specimen were selected to validate the proposed approaches. It has been demonstrated that the predictions offered by the new models are consistent with the experimental data. In addition, a loading procedure using the same final value, with and without involving unloading, prior to a creep test can produce different results. The proposed approach can capture this phenomenon which was observed in the literature. The proposed approach can also be easily incorporated into commercial finite element software (e.g., Abaqus). It is demonstrated that the proposed method may be used for anti-vibration products at an appropriate design stage.     

Platinum-group element concentrations in BCR-723: a quantitative review of published analyses

BCR-723 is the only environmental certified reference material for platinum-group elements (PGEs) Pt, Pd and Rh. It has been an integral component of quality control/quality assurance procedures in environmental laboratories measuring PGEs, since 2001. Here, we present an extensive quantitative review of the published PGEs measured in BCR-723, since its introduction. A statistical examination of concentrations, measurement precision and accuracy for 25 studies is presented. Measurement typically starts with an aqua regia digestion, followed by some form of pre-concentration or separation procedure, and quantitation by ICP-MS. Use of a sample mass below the recommended value of 100 mg has been shown to produce biased results for acid-based digestions or with laser ablation. Platinum is the most precisely and accurately measured PGE in BCR-723, followed by Rh, and finally by Pd. Literature precision data for all autocatalyst PGEs did not differ significantly (α = 0.05) from those obtained by the original laboratories used to certify BCR-723. Measurement accuracies for the literature tabulated PGE data did not differ significantly from zero, indicating an overall lack of directional bias. These results should be encouraging to the analytical community, but further advancements, especially for Pd quantification are required.     

Pesticide analysis in ground water. Statistical evaluation of certification data of a multicomponent reference material

21 laboratories participated in the certification of a multicomponent ampouled reference material containing 24 pesticides. This paper describes the statistical analysis of the unbalanced data set returned by the participants in the certification. The simplest method of certification is achieved when laboratories report all the required data. In practice, however, with complex analytical methods such as multicomponent analyses of organic compounds, laboratories are not able to report all the required data. The response for each determinand in the material has been modelled in a three-factor nested model. For computational comfort the model has been rephrased into a general linear model. The statistical problems with unbalanced data are discussed in relation to ISO 5725 and ISO Guide 35. Tests for homogeneity are exact and uninfluenced by the unbalance in data. Unbalanced data cause dependencies between mean squares above the second lowest level of the model, thus exact hypothesis testing is not possible at higher levels. Approximate tests for variation between rounds and laboratories has been constructed by means of Satterthwaite’s formula [1]. A graphical plot of deviances from certified values has been applied to illustrate laboratory performance.     

Preliminary evaluation of laser-induced breakdown spectroscopy for tissue classification

Laser-induced breakdown spectroscopy (LIBS) is an on-line, real-time technology that can produce immediate information about the elemental contents of tissue samples. We have previously shown that LIBS may be used to distinguish cancerous from non-cancerous tissue. In this work, we study LIBS spectra produced from chicken brain, lung, spleen, liver, kidney and skeletal muscle. Different data processing techniques were used to study if the information contained in these LIBS spectra is able to differentiate between different types of tissue samples and then identify unknown tissues. We have demonstrated a clear distinguishing between each of the known tissue types with only 21 selected analyte lines from each observed LIBS spectrum. We found that in order to produce an analytical model to work well with new sample we need to have representative training data to cover a wide range of spectral variation due to experimental or environmental changes.     

Absolute standard hydrogen electrode potential measured by reduction of aqueous nanodrops in the gas phase

In solution, half-cell potentials are measured relative to those of other half cells, thereby establishing a ladder of thermochemical values that are referenced to the standard hydrogen electrode (SHE), which is arbitrarily assigned a value of exactly 0 V. Although there has been considerable interest in, and efforts toward, establishing an absolute electrochemical half-cell potential in solution, there is no general consensus regarding the best approach to obtain this value. Here, ion-electron recombination energies resulting from electron capture by gas-phase nanodrops containing individual [M(NH3)6]3+, M = Ru, Co, Os, Cr, and Ir, and Cu2+ ions are obtained from the number of water molecules that are lost from the reduced precursors. These experimental data combined with nanodrop solvation energies estimated from Born theory and solution-phase entropies estimated from limited experimental data provide absolute reduction energies for these redox couples in bulk aqueous solution. A key advantage of this approach is that solvent effects well past two solvent shells, that are difficult to model accurately, are included in these experimental measurements. By evaluating these data relative to known solution-phase reduction potentials, an absolute value for the SHE of 4.2 +/- 0.4 V versus a free electron is obtained. Although not achieved here, the uncertainty of this method could potentially be reduced to below 0.1 V, making this an attractive method for establishing an absolute electrochemical scale that bridges solution and gas-phase redox chemistry.     

New NIST sediment SRM for inorganic analysis

NIST maintains a portfolio of more than 1300 standard reference materials (SRM), more than a third of these relating to measurements in the biological and environmental fields. As part of the continuous renewal and replacement efforts, a set of new marine sediments has been recently developed covering organic and inorganic determinations. This paper describes the steps taken in sample preparation, homogeneity assay, and analytical characterization and certification with specific emphasis on SRM 2702 inorganics in marine sediment. Neutron activation analysis showed the SRM to be highly homogeneous, opening the possibility for use with solid sampling techniques. The certificate provides certified mass fraction values for 25 elements, reference values for eight elements, and information values for 11 elements, covering most of the priority pollutants with small uncertainties of only several percent relative. The values were obtained by combining results from different laboratories and techniques using a Bayesian statistical model. An intercomparison carried out in field laboratories with the material before certification illustrates a high commutability of this SRM.Electronic Supplementary Material Supplementary material is available in the online version of this article at     

Global statistical predictor model for characteristic adsorption energy of organic vapors-solid interaction: use in dynamic process simulation

Adsorption of Volatile Organic Compounds (VOCs) is one of the best remediation techniques for controlling industrial air pollution. In this paper, a quantitative predictor model for the characteristic adsorption energy (E) of the Dubinin-Radushkevich (DR) isotherm model has been established with R(2) value of 0.94. A predictor model for characteristic adsorption energy (E) has been established by using Multiple Linear Regression (MLR) analysis in a statistical package MINITAB. The experimental value of characteristic adsorption energy was computed by modeling the isotherm equilibrium data (which contain 120 isotherms involving five VOCs and eight activated carbons at 293, 313, 333, and 353 K) with the Gauss-Newton method in a statistical package R-STAT. The MLR model has been validated with the experimental equilibrium isotherm data points, and it will be implemented in the dynamic adsorption simulation model PROSIM. By implementing this model, it predicts an enormous range of 1200 isotherm equilibrium coefficients of DR model at different temperatures such as 293, 313, 333, and 353K (each isotherm has 10 equilibrium points by changing the concentration) just by a simple MLR characteristic energy model without any experiments.