A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

Toy model for a relational formulation of quantum theory

In the absence of an external frame of reference-i.e., in background independent theories such as general relativity-physical degrees of freedom must describe relations between systems. Using a simple model, we investigate how such a relational quantum theory naturally arises by promoting reference systems to the status of dynamical entities. Our goal is twofold. First, we demonstrate using elementary quantum theory how any quantum mechanical experiment admits a purely relational description at a fundamental. Second, we describe how the original non-relational theory approximately emerges from the fully relational theory when reference systems become semi-classical. Our technique is motivated by a Bayesian approach to quantum mechanics, and relies on the noiseless subsystem method of quantum information science used to protect quantum states against undesired noise. The relational theory naturally predicts a fundamental decoherence mechanism, so an arrow of time emerges from a time-symmetric theory. Moreover, our model circumvents the problem of the collapse of the wave packet as the probability interpretation is only ever applied to diagonal density operators. Finally, the physical states of the relational theory can be described in terms of spin networks introduced by Penrose as a combinatorial description of geometry, and widely studied in the loop formulation of quantum gravity. Thus, our simple bottom-up approach (starting from the semiclassical limit to derive the fully relational quantum theory) may offer interesting insights on the low energy limit of quantum gravity.

COMPREENSÃO DA VULNERABILIDADE CRIMINAL FEMININA A PARTIR DA ANÁLISE DO CARÁTER

O presente estudo teve por objetivos a) identificar aspectos da história de vida pessoal, das etapas de desenvolvimento evolutivo e das relações familiares e afetivas de mulheres que cumprem pena em regime fechado, com o intuito de colher elementos significativos e contributivos para a compreensão da vulnerabilidade criminal feminina; b) realizar uma análise sistematizada do caráter, segundo abordagem de Wilhelm Reich, a partir do conteúdo do discurso clínico dessas mulheres. Para tal foram estudados três casos de mulheres reclusas em regime fechado no Centro de Ressocialização Feminino, na cidade de São José do Rio Preto, que respondem pelos artigos 33 e 35 da Lei 11343/06, que refere-se ao tráfico de drogas ilícitas e a associação para o crime, e artigo 157 do Código Penal Brasileiro, que refere-se a roubo. O conteúdo das entrevistas realizadas indicou graves dificuldades no crescimento e desenvolvimento por ambiente desfavorável e por relações psico-afetivas empobrecidas ou insatisfatórias. Encontrou-se em comum nos casos estudados, segundo uma análise reichiana, indicativos de fixação na oralidade, ou seja, traços orais insatisfatórios relacionados à primeira infância, indicando pouca referência identificatória que lhes oferecesse base para defenderem-se da realidade. Entendeu-se que tais falhas desenvolvimentais podem indicar vulnerabilidade para ações criminais como forma de defesa contra angústia, fazendo com que atuem de forma mais imediata ou impulsiva na busca de satisfação.

Functional split and crosslinking of the membrane domain of the β subunit of proton-translocating transhydrogenase from Escherichia coli

Proton pumping nicotinamide nucleotide transhydrogenase from Escherichia coli contains an α subunit with the NAD(H)-binding domain I and a β subunit with the NADP(H)-binding domain III. The membrane domain (domain II) harbors the proton channel and is made up of the hydrophobic parts of the α and β subunits. The interface in domain II between the α and the β subunits has previously been investigated by cross-linking loops connecting the four transmembrane helices in the α subunit and loops connecting the nine transmembrane helices in the β subunit. However, to investigate the organization of the nine transmembrane helices in the β subunit, a split was introduced by creating a stop codon in the loop connecting transmembrane helices 9 and 10 by a single mutagenesis step, utilizing an existing downstream start codon. The resulting enzyme was composed of the wild-type α subunit and the two new peptides β1 and β2. As compared to other split membrane proteins, the new transhydrogenase was remarkably active and catalyzed activities for the reduction of 3-acetylpyridine-NAD + by NADPH, the cyclic reduction of 3-acetylpyridine-NAD + by NADH (mediated by bound NADP(H)), and proton pumping, amounting to about 50-107% of the corresponding wild-type activities. These high activities suggest that the α subunit was normally folded, followed by a concerted folding of β1 + β2. Cross-linking of a βS105C-βS237C double cysteine mutant in the functional split cysteine-free background, followed by SDS-PAGE analysis, showed that helices 9, 13, and 14 were in close proximity. This is the first time that cross-linking between helices in the same β subunit has been demonstrated.

Data assimilation for precipitation nowcasting using Bayesian inference

This work introduces a new variational Bayes data assimilation method for the stochastic estimation of precipitation dynamics using radar observations for short term probabilistic forecasting (nowcasting). A previously developed spatial rainfall model based on the decomposition of the observed precipitation field using a basis function expansion captures the precipitation intensity from radar images as a set of ‘rain cells’. The prior distributions for the basis function parameters are carefully chosen to have a conjugate structure for the precipitation field model to allow a novel variational Bayes method to be applied to estimate the posterior distributions in closed form, based on solving an optimisation problem, in a spirit similar to 3D VAR analysis, but seeking approximations to the posterior distribution rather than simply the most probable state. A hierarchical Kalman filter is used to estimate the advection field based on the assimilated precipitation fields at two times. The model is applied to tracking precipitation dynamics in a realistic setting, using UK Met Office radar data from both a summer convective event and a winter frontal event. The performance of the model is assessed both traditionally and using probabilistic measures of fit based on ROC curves. The model is shown to provide very good assimilation characteristics, and promising forecast skill. Improvements to the forecasting scheme are discussed

The role of the extracellular loops of the CGRP receptor, a family B GPCR

The CGRP (calcitonin gene-related peptide) receptor is a family B GPCR (G-protein-coupled receptor). It consists of a GPCR, CLR (calcitonin receptor-like receptor) and an accessory protein, RAMP1 (receptor activity-modifying protein 1). RAMP1 is needed for CGRP binding and also cell-surface expression of CLR. There have been few systematic studies of the ECLs (extracellular loops) of family B GPCRs. However, they are likely to be especially important for the interaction of the N-termini of the peptide agonists that are the natural agonists for these receptors. We have carried out alanine scans on all three ECLs of CLR, as well as their associated juxtamembrane regions. Residues within all three loops influence CGRP binding and receptor activation. Mutation of Ala203 and Ala206 on ECL1 to leucine increased the affinity of CGRP. Residues at the top of TM (transmembrane) helices 2 and 3 influenced CGRP binding and receptor activation. L351A and E357A in TM6/ECL3 reduced receptor expression and may be needed for CLR association with RAMP1. ECL2 seems especially important for CLR function; of the 16 residues so far examined in this loop, eight residues reduce the potency of CGRP at stimulating cAMP production when mutated to alanine.

Similarity between class A and class B G-protein-coupled receptors exemplified through calcitonin gene-related peptide receptor modelling and mutagenesis studies

Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A-class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg(2.39), His(2.43) and Glu(3.46), which makes a polar lock with T(6.37). These alignments and models provide useful tools for understanding class B GPCR function.

Comparison of configurations for high-recovery inland desalination systems

Desalination of brackish groundwater (BW) is an effective approach to augment water supply, especially for inland regions that are far from seawater resources. Brackish water reverse osmosis (BWRO) desalination is still subject to intensive energy consumption compared to the theoretical minimum energy demand. Here, we review some of the BWRO plants with various system arrangements. We look at how to minimize energy demands, as these contribute considerably to the cost of desalinated water. Different configurations of BWRO system have been compared from the view point of normalized specific energy consumption (SEC). Analysis is made at theoretical limits. The SEC reduction of BWRO can be achieved by (i) increasing number of stages, (ii) using an energy recovery device (ERD), or (iii) operating the BWRO in batch mode or closed circuit mode. Application of more stages not only reduces SEC but also improves water recovery. However, this improvement is less pronounced when the number of stages exceeds four. Alternatively and more favourably, the BWRO system can be operated in Closed Circuit Desalination (CCD) mode and gives a comparative SEC to that of the 3-stage system with a recovery ratio of 80%. A further reduction of about 30% in SEC can be achieved through batch-RO operation. Moreover, the costly ERDs and booster pumps are avoided with both CCD and batch-RO, thus furthering the effectiveness of lowering the costs of these innovative approaches. © 2012 by the authors.

The impact of general intellectual ability and white matter volume on the functional outcome of patients with bipolar disorder and their relatives

Background: There is substantial evidence that cognitive deficits and brain structural abnormalities are present in patients with Bipolar Disorder (BD) and in their first-degree relatives. Previous studies have demonstrated associations between cognition and functional outcome in BD patients but have not examined the role of brain morphological changes. Similarly, the functional impact of either cognition or brain morphology in relatives remains unknown. Therefore we focused on delineating the relationship between psychosocial functioning, cognition and brain structure, in relation to disease expression and genetic risk for BD. Methods: Clinical, cognitive and brain structural measures were obtained from 41 euthymic BD patients and 50 of their unaffected first-degree relatives. Psychosocial function was evaluated using the General Assessment of Functioning (GAF) scale. We examined the relationship between level of functioning and general intellectual ability (IQ), memory, attention, executive functioning, symptomatology, illness course and total gray matter, white matter and cerebrospinal fluid volumes. Limitations: Cross-sectional design. Results: Multiple regression analyses revealed that IQ, total white matter volume and a predominantly depressive illness course were independently associated with functional outcome in BD patients, but not in their relatives, and accounted for a substantial proportion (53%) of the variance in patients' GAF scores. There were no significant domain-specific associations between cognition and outcome after consideration of IQ. Conclusions: Our results emphasise the role of IQ and white matter integrity in relation to outcome in BD and carry significant implications for treatment interventions. © 2010 Elsevier B.V.

Polypropylene as a reductive agent for dehalogenation of brominated organic compounds

A new method for debromination of organics by a reductive medium like polypropylene is investigated. The reaction is carried out in inert atmosphere to avoid rapid oxidation of the polymer. Through this detoxification procedure, hydrogen bromide and small brominated alkanes are formed. Experiments in closed ampoules are carried out with tetrabromobisphenol A, dibromophenol, pentabromodiphenyl ether, dichlorophenol and an oil formed by pyrolysis of printed circuit boards in the Haloclean® process. The reaction is examined under isothermal conditions in a temperature range between 300 and 400°C and a residence time between 10 and 30 min. Optimal conditions were found at 350°C and at a residence time of 20 min. As chlorinated phenols are not destroyed under these conditions, the process may be a valuable procedure to gain hydrogen bromide out of mixtures of halogenated feed materials. Also, under atmospheric pressure, a reaction between polypropylene and brominated compounds takes place as could be proved by thermogravimetric analysis. Bromobenzene has an accelerating effect on the rate of weight loss of the polymer, but at higher concentrations, it can also be slowed down. © 2003 Elsevier Ltd. All rights reserved.

Generalized Convolution Transforms and Toeplitz Plus Hankel Integral Equations

Mathematics Subject Classification: 44A05, 44A35

Probabilistic DHP adaptive critic for nonlinear stochastic control systems

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Kárnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained.

Review of industrial temperature measurement technologies and research priorities for the thermal characterisation of the factories of the future

As the largest source of dimensional measurement uncertainty, addressing the challenges of thermal variation is vital to ensure product and equipment integrity in the factories of the future. While it is possible to closely control room temperature, this is often not practical or economical to realise in all cases where inspection is required. This article reviews recent progress and trends in seven key commercially available industrial temperature measurement sensor technologies primarily in the range of 0 °C–50 °C for invasive, semi-invasive and non-invasive measurement. These sensors will ultimately be used to measure and model thermal variation in the assembly, test and integration environment. The intended applications for these technologies are presented alongside some consideration of measurement uncertainty requirements with regard to the thermal expansion of common materials. Research priorities are identified and discussed for each of the technologies as well as temperature measurement at large. Future developments are briefly discussed to provide some insight into which direction the development and application of temperature measurement technologies are likely to head.

Theory of hybrid computational and physical measurement-based integration of thermal and dimensional measurement

In dimensional metrology, often the largest source of uncertainty of measurement is thermal variation. Dimensional measurements are currently scaled linearly, using ambient temperature measurements and coefficients of thermal expansion, to ideal metrology conditions at 20˚C. This scaling is particularly difficult to implement with confidence in large volumes as the temperature is unlikely to be uniform, resulting in thermal gradients. A number of well-established computational methods are used in the design phase of product development for the prediction of thermal and gravitational effects, which could be used to a greater extent in metrology. This paper outlines the theory of how physical measurements of dimension and temperature can be combined more comprehensively throughout the product lifecycle, from design through to the manufacturing phase. The Hybrid Metrology concept is also introduced: an approach to metrology, which promises to improve product and equipment integrity in future manufacturing environments. The Hybrid Metrology System combines various state of the art physical dimensional and temperature measurement techniques with established computational methods to better predict thermal and gravitational effects.

Bayesian Prediction of Weibull Distribution Based on Fixed and Random Sample Size

2000 Mathematics Subject Classification: 62E16, 65C05, 65C20.