A method for screening the temperature dependence of three-dimensional crystal formation

Temperature is an important parameter controlling protein crystal growth. A new temperature-screening system (Thermo-screen) is described consisting of a gradient thermocycler fitted with a special crystallization-plate adapter onto which a 192-well sitting-drop crystallization plate can be mounted (temperature range 277-372 K; maximum temperature gradient 20 K; interval precision 0.3 K). The system allows 16 different conditions to be monitored simultaneously over a range of 12 temperatures and is well suited to conduct wide (similar to 20 K) and fine (similar to 3 K) temperature-optimization screens. It can potentially aid in the determination of temperature phase diagrams and run more complex temperature-cycling experiments for seeding and crystal growth.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

A simple method to localise pleiotropic susceptibility loci using univariate linkage analyses of correlated traits

Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.

An equivalent distributed magnetic current based FDTD method for the calculation of e-fields induced by gradient coils in MRI

This paper evaluates a low-frequency FDTD method applied to the problem of induced E-fields/eddy currents in the human body resulting from the pulsed magnetic field gradients in MRI. In this algorithm, a distributed equivalent magnetic current (DEMC) is proposed as the electromagnetic source and is obtained by quasistatic calculation of the empty coil's vector potential or measurements therein. This technique circumvents the discretizing of complicated gradient coil geometries into a mesh of Yee cells, and thereby enables any type of gradient coil modeling or other complex low frequency sources. The proposed method has been verified against an example with an analytical solution. Results are presented showing the spatial distribution of gradient-induced electric fields in a multilayered spherical phantom model and a complete body model.

What Counts Versus What Can Be Counted : The Complex Interplay of Market Orientation and Marketing Performance Measurement

Market orientation (MO) and marketing performance measurement (MPM) are two of the most widespread strategic marketing concepts among practitioners. However, some have questioned the benefits of extensive investments in MO and MPM. More importantly, little is known about which combinations of MO and MPM are optimal in ensuring high business performance. To address this research gap, the authors analyze a unique data set of 628 firms with a novel method of configurational analysis: fuzzy-set qualitative comparative analysis. In line with prior research, the authors find that MO is an important determinant of business performance. However, to reap its benefits, managers need to complement it with appropriate MPM, the level and focus of which vary across firms. For example, whereas large firms and market leaders generally benefit from comprehensive MPM, small firms may benefit from measuring marketing performance only selectively or by focusing on particular dimensions of marketing performance. The study also finds that many of the highest-performing firms do not follow any of the particular best practices identified.

Causality and synchronisation in complex systems with applications to neuroscience

This thesis presents an investigation, of synchronisation and causality, motivated by problems in computational neuroscience. The thesis addresses both theoretical and practical signal processing issues regarding the estimation of interdependence from a set of multivariate data generated by a complex underlying dynamical system. This topic is driven by a series of problems in neuroscience, which represents the principal background motive behind the material in this work. The underlying system is the human brain and the generative process of the data is based on modern electromagnetic neuroimaging methods . In this thesis, the underlying functional of the brain mechanisms are derived from the recent mathematical formalism of dynamical systems in complex networks. This is justified principally on the grounds of the complex hierarchical and multiscale nature of the brain and it offers new methods of analysis to model its emergent phenomena. A fundamental approach to study the neural activity is to investigate the connectivity pattern developed by the brain’s complex network. Three types of connectivity are important to study: 1) anatomical connectivity refering to the physical links forming the topology of the brain network; 2) effective connectivity concerning with the way the neural elements communicate with each other using the brain’s anatomical structure, through phenomena of synchronisation and information transfer; 3) functional connectivity, presenting an epistemic concept which alludes to the interdependence between data measured from the brain network. The main contribution of this thesis is to present, apply and discuss novel algorithms of functional connectivities, which are designed to extract different specific aspects of interaction between the underlying generators of the data. Firstly, a univariate statistic is developed to allow for indirect assessment of synchronisation in the local network from a single time series. This approach is useful in inferring the coupling as in a local cortical area as observed by a single measurement electrode. Secondly, different existing methods of phase synchronisation are considered from the perspective of experimental data analysis and inference of coupling from observed data. These methods are designed to address the estimation of medium to long range connectivity and their differences are particularly relevant in the context of volume conduction, that is known to produce spurious detections of connectivity. Finally, an asymmetric temporal metric is introduced in order to detect the direction of the coupling between different regions of the brain. The method developed in this thesis is based on a machine learning extensions of the well known concept of Granger causality. The thesis discussion is developed alongside examples of synthetic and experimental real data. The synthetic data are simulations of complex dynamical systems with the intention to mimic the behaviour of simple cortical neural assemblies. They are helpful to test the techniques developed in this thesis. The real datasets are provided to illustrate the problem of brain connectivity in the case of important neurological disorders such as Epilepsy and Parkinson’s disease. The methods of functional connectivity in this thesis are applied to intracranial EEG recordings in order to extract features, which characterize underlying spatiotemporal dynamics before during and after an epileptic seizure and predict seizure location and onset prior to conventional electrographic signs. The methodology is also applied to a MEG dataset containing healthy, Parkinson’s and dementia subjects with the scope of distinguishing patterns of pathological from physiological connectivity.

Complex temporal patterns in molecular dynamics:a direct measure of the phase-space exploration by the trajectory at macroscopic time scales

Computer simulated trajectories of bulk water molecules form complex spatiotemporal structures at the picosecond time scale. This intrinsic complexity, which underlies the formation of molecular structures at longer time scales, has been quantified using a measure of statistical complexity. The method estimates the information contained in the molecular trajectory by detecting and quantifying temporal patterns present in the simulated data (velocity time series). Two types of temporal patterns are found. The first, defined by the short-time correlations corresponding to the velocity autocorrelation decay times (â‰0.1â€ps), remains asymptotically stable for time intervals longer than several tens of nanoseconds. The second is caused by previously unknown longer-time correlations (found at longer than the nanoseconds time scales) leading to a value of statistical complexity that slowly increases with time. A direct measure based on the notion of statistical complexity that describes how the trajectory explores the phase space and independent from the particular molecular signal used as the observed time series is introduced. © 2008 The American Physical Society.

Non-rigid object tracking in complex scenes

A recently proposed colour based tracking algorithm has been established to track objects in real circumstances [Zivkovic, Z., Krose, B. 2004. An EM-like algorithm for color-histogram-based object tracking. In: Proc, IEEE Conf. on Computer Vision and Pattern Recognition, pp. 798-803]. To improve the performance of this technique in complex scenes, in this paper we propose a new algorithm for optimally adapting the ellipse outlining the objects of interest. This paper presents a Lagrangian based method to integrate a regularising component into the covariance matrix to be computed. Technically, we intend to reduce the residuals between the estimated probability distribution and the expected one. We argue that, by doing this, the shape of the ellipse can be properly adapted in the tracking stage. Experimental results show that the proposed method has favourable performance in shape adaption and object localisation.

Statnote 13: a more complex analysis of variance incorporating a 'repeated measures' factor

Experiments combining different groups or factors and which use ANOVA are a powerful method of investigation in applied microbiology. ANOVA enables not only the effect of individual factors to be estimated but also their interactions; information which cannot be obtained readily when factors are investigated separately. In addition, combining different treatments or factors in a single experiment is more efficient and often reduces the sample size required to estimate treatment effects adequately. Because of the treatment combinations used in a factorial experiment, the degrees of freedom (DF) of the error term in the ANOVA is a more important indicator of the ‘power’ of the experiment than the number of replicates. A good method is to ensure, where possible, that sufficient replication is present to achieve 15 DF for the error term of the ANOVA testing effects of particular interest. Finally, it is important to always consider the design of the experiment because this determines the appropriate ANOVA to use. Hence, it is necessary to be able to identify the different forms of ANOVA appropriate to different experimental designs and to recognise when a design is a split-plot or incorporates a repeated measure. If there is any doubt about which ANOVA to use in a specific circumstance, the researcher should seek advice from a statistician with experience of research in applied microbiology.

A simple, sensitive and selective quantum-dot-based western blot method for the simultaneous detection of multiple targets from cell lysates

Quantum dots (Qdots) are fluorescent nanoparticles that have great potential as detection agents in biological applications. Their optical properties, including photostability and narrow, symmetrical emission bands with large Stokes shifts, and the potential for multiplexing of many different colours, give them significant advantages over traditionally used fluorescent dyes. Here, we report the straightforward generation of stable, covalent quantum dot-protein A/G bioconjugates that will be able to bind to almost any IgG antibody, and therefore can be used in many applications. An additional advantage is that the requirement for a secondary antibody is removed, simplifying experimental design. To demonstrate their use, we show their application in multiplexed western blotting. The sensitivity of Qdot conjugates is found to be superior to fluorescent dyes, and comparable to, or potentially better than, enhanced chemiluminescence. We show a true biological validation using a four-colour multiplexed western blot against a complex cell lysate background, and have significantly improved previously reported non-specific binding of the Qdots to cellular proteins.

Living cationic polymerization

The kinetics of the polymerization of styrene iniated by 1-chloro-1-phenyltehane/tin (IV) chloride in the presence of tetrabutylammonium chloride have been studied. Dilatometry studies at 25 °C were conducted and the orders of reaction were established. Molecular weight studies were conducted for these experiments using size exclusion chromatography. These studies indicated that transfer/termination reactions were present. The observed kinetics may be explained by a polymerization mechanism involving a single propagating species which is present in low concentrations. Reactions at 0 °C and -15 °C have shown that a "living" polymerization could be obtained at low temperatures. A method was derived to study the kinetics of a "living" polymerization by following the increase in degree of polymerization with time. Polymerizations of styrene were conducted using 1,4-bis(bromomethyl)benzene as a difunctional co-catalyst. These reactions produced polymers with broad or bimodal molecular weight distributions. These observations may be explained by the rate of initiation being slower than the rate of propagation or the presence of transfer/termination reactions. Reactions were conducted using a co-catalyst using a co-catalyst produced by the addition of 1,1-diphenylethane to 1,4-bis(bromomethyl)benzene. Size exclusion chromatography studies showed that the polymers produced had a narrower molecular weight distribution than those produced by polymerizations initiated by 1,4-bis(bromomethyl)benzene alone. However the polydispersity was still observed to increase with reaction time. This may also be explained by slow initiation compared to the rate of propagation. Polymerizations initiated by both bifunctional initiators were examined using the method of studying reaction kinetics by following the change in number average degree of polymerization. The results indicated that a straight line relationship could also be obtained with a non-living polymerization.

Studies in the anionic polymerization of methyl methacrylate

A study has been made of the anionic polymerization of methyl methacrylate using butyllithium and polystyryl lithium as initiators and using aluminium triisobutyl as a cocatalyst. The aspects of the polymerization that were examined were the effect of changing the order of addition of reagents, the temperature at which polymerization takes place and the polarity of the solvent. Trends were assessed in terms of molecular weight, molecular weight distribution and tacticity. In addition, a second monomer addition test was carried out to verify that the polymerization was truly a living one, and a kinetic study was attempted. Studies to investigate the effect of changing the order of addition of reagents showed that polymer with similar polydispersities and tacticities are produced whether the pre-mixing (mixing initiator and cocatalyst before addition of monomer) or the post-mixing (mixing monomer and cocatalyst before addition of initiator) method were used. However, polymerizations using the post-mixing mixing method demonstrated lower initiator efficiencies, possibly indicating a different initiating species. Investigations into the effect of changing the polymerization temperature show the molecular weight distribution to narrow as the temperature decreases, although a small amount of low molecular weight tailing was also observed at low temperature. A clear relationship between tacticity and temperature was observed with syndiotacticity increasing with decreasing temperature. Changes in solvent polarity were achieved by using mixtures of the standard solvent, toluene, with varying amounts of cyclohexane, tetrahydrofuran or dichloromethane. Experiments at low solvent polarity (using toluene/cyclohexane mixtures) showed problems with initiator solubility but produced polymer with lower polydispersity and higher syndiotacticity than in toluene alone. Experiments using toluene/THF mixtures yielded no polymer, thought to be owing to a side reaction between THF and aluminium triisobutyl. Increased solvent polarity, achieved using toluene/dichloromethane mixtures produced polymer with higher polydispersity and at lower yields than the conventional system, but also with higher syndiotacticity. Second monomer addition reactions demonstrated that the polymerization was 'living' since an increase in molecular weight was observed with no increase in polydispersity. Kinetic studies demonstrated the high speed of the polymerization but yielded no useful data.

Living cationic polymerization of isobutene

The polymerization of isobutene initiated by 1-chloro-1-phenylethane has been investigated, and molecular weight studies conducted using size exclusion chromatography. Polymerizations carried out in a 40/60 (v/v) mixture of dichloromethaneIcyclohexane, using titanium (IV) chloride as a catalyst in the presence of pyridine at -30 °C were found to be controlled and living. The number average molecular weights of the polymers increased linearly with monomer conversion, and the molecular weight distributions were between 1.15 and 1.20. Efficiencies of initiation were between 80 and 100%, and evidence was found to suggest that backbiting to the initiator had occurred, resulting in the formation of cyclic oligomers during the early stages of polymerization. The kinetics of polymerization can be explained in terms of active species in. equilibrium with dormant species. The effects of temperature. and dielectric constant on this equilibrium were studied and a model based upon the Fuoss equation was developed. Pyridine was found to behave as proton trap in the system, and when it was used in excess the rate of polymerization was retarded. By assuming that the catalyst and pyridine formed a one to one complex, it was possible to show that the reaction was second order with respect to the catalyst. The synthesis of low molecular weight polyisobutenes was studied. When the concentration of initiator was increased relative to that of the isobutene, such that the theoretical degree of polymerization was 20 or less, the rate of initiation was slow compared to propagation. The efficiency of initiation in these polymerizations was typically between 30 and 40 %. Optimal conditions of temperature. and.catalyst concentration were established, leading to a 60 % efficiency of initiation. A one-pot synthesis of phenol end-capped polyisobutene was attempted by adding phenol at the end of a living polymerization. Evidence to substantiate the existence of capped polymer chains in the resultant product was inconclusive. Block copolymerizations of oxetane and isobutene were conducted using 1-chloro-1phenylethane/TiCl4, but no copolymer or oxetane homopolymer could be isolated.

Living cationic polymerization of styrene monomers

This thesis describes an experimental investigation of synthesis of polystyrene under various polymerization conditions such as solvent polarity, temperature, initial concentrations of initiator, catalyst, monomer and added salts or co-catalyst, which was achieved using the living cationic polymerization technology in conjunction with gel permeation chromatography (GPC) and NMR spectroscopy. Polymerizations of styrene were conducted using 1-phenyl ethylchloride (1-PEC) as an initiator and tin tetrachloride (SnCI4) as a catalyst in the presence of tetra-n-Butylammonium chloride (nBu4NCI). Effects of solvent polarity varied by mixing dichloromethane (DCM) and less polar cyclohexane (C.hex), temperature, initial concentrations of SnC14, 1-PEC and nBu4NCI on the polymerizations were examined, and the conditions under which a living polymerization can be obtained were optimised as: [styrene]o ~ 0.75 - 2 M; [1-PEC]o ~ 0.005 - 0.05 M; [SnCI4Jo ~ 0.05 - 0.4 M; [nBu4NCIJo ~ 0.001 - 0.1 M; DCM/C.hex ~ 50/0 - 20/30 v/v; T ~ 0 to -45°C. Kinetic studies of styrene polymerization using the Omnifit sampling method showed that the number average molecular weight (Mn) of the polymers obtained increased in direct proportion to monomer conversion and agreed well with the theoretical Mn expected from the concentration ratios of monomer to initiator. The linearities of both the 1n([MJoI[M]) vs. time plot and the Mn vs. monomer conversion plot, and the narrow molecular weight distribution (MWD) measured using GPC demonstrated the livingness of the polymerizations, indicating the absence of irreversible termination and transfer within the lifetimes of the polymerizations. The proposed 'two species' propagation mechanism was found to apply for the styrene polymerization with 1-PEC/SnCI4 in the presence of nBu4NCl. The further kinetic experiments showed that living styrene polymerizations were achieved using the 1-PEC/SnCI4 initiating system in mixtures of DCM/C.hex 30/20 v/v at -15°C in the presence of various bromide salts, tetra-n-butylammonium bromide, tetra-n-pentylammonium bromide, tetra-n-heptylammonium bromide, and tetra-n-octylammonium bromide, respectively. The types of the bromide salts were found to have no significant effect on monomer conversion, Mn, polydispersity and initiation efficiency. Living polymerizations of styrene were also achieved using titanium tetrachloride (TiCI4) as a catalyst and 1-PEC as an initiator in the presence of a small amount of 2,6-di-tert-butylpyridine or pyridine instead of nBu4NCl. GPC analysis showed that the polymers obtained had narrow polydispersities (P.D. < 1.3), and the linearities of both the In([MJo/[MJ) vs. time plot and the Mn vs. monomer conversion plot demonstrated that the polymerizations are living, when the ratio of DCM and C.hex was less than 40 : 10 and the reaction temperature was not lower than -15°C. The reaction orders relative to TiCl4 and 1-PEC were estimated from the investigations into the rate of polymerization to be 2.56 and 1.0 respectively. lH and 13C NMR analysis of the resultant polystyrene would suggest the end-functionality of the product polymers is chlorine for all living polymerizations.