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.

Entropy generation for microscale forced convection: effects of different thermal boundary conditions, velocity slip, temperature jump, viscous dissipation, and duct geometry

This work presents closed form solutions for fully developed temperature distribution and entropy generation due to forced convection in microelectromechanical systems (MEMS) in the Slip-flow regime, for which the Knudsen number lies within the range 0.001

Methods for Categorical Longitudinal Survey Data: Understanding Employment Status of Australian Women

Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.

Effect of ethylene vinyl acetate (EVA) closed cell foam on transmitted forces in mouthguard material

Objectives: To compare transmitted forces through ethylene vinyl acetate (EVA) mouthguard material and the same EVA material with gas inclusions in the form of a closed cell foam. Method: EVA mouthguard materials with and without foam gas inclusions and 4 mm thick were impacted with a constant force from an impact pendulum. Various porosity levels in the foam materials were produced by 1%, 5%, and 10% by weight foaming agent. The forces transmitted through the EVA after energy absorption by the test materials were measured with a force sensor and compared. Results: Only minor non-significant differences in transmitted forces through the EVA with and without foam were shown. Conclusions: The inclusion of gas in the form of a closed cell foam in 4 mm thick EVA mouthguard materials did not improve the impact performance of the EVA mouthguard material.

Development of the student placement evaluation form: A tool for assessing student fieldwork performance

Evaluation of students undertaking fieldwork education placements is a critical process in the health professions. As training programs and practice evolve, systems for assessing students need to be reviewed and updated constantly. In 1995, staff of the occupational therapy training program at the University of Queensland, Australia decided to develop a new tool for assessing student fieldwork performance. Using an action research methodology, a team developed the Student Placement Evaluation Form, a flexible and comprehensive criterion-referenced evaluation tool. The present paper examines action research as an appropriate methodology for considering real-life organisational problems in a systematic and participatory manner. The action research cycles undertaken, including preliminary information gathering, tool development, trial stages and current use of the tool, are detailed in the report. Current and future development of the tool is also described.

Algebraic Bethe ansatz method for the exact calculation of energy spectra and form factors: applications to models of Bose-Einstein condensates and metallic nanograins

In this review we demonstrate how the algebraic Bethe ansatz is used for the calculation of the-energy spectra and form factors (operator matrix elements in the basis of Hamiltonian eigenstates) in exactly solvable quantum systems. As examples we apply the theory to several models of current interest in the study of Bose-Einstein condensates, which have been successfully created using ultracold dilute atomic gases. The first model we introduce describes Josephson tunnelling between two coupled Bose-Einstein condensates. It can be used not only for the study of tunnelling between condensates of atomic gases, but for solid state Josephson junctions and coupled Cooper pair boxes. The theory is also applicable to models of atomic-molecular Bose-Einstein condensates, with two examples given and analysed. Additionally, these same two models are relevant to studies in quantum optics; Finally, we discuss the model of Bardeen, Cooper and Schrieffer in this framework, which is appropriate for systems of ultracold fermionic atomic gases, as well as being applicable for the description of superconducting correlations in metallic grains with nanoscale dimensions.; In applying all the above models to. physical situations, the need for an exact analysis of small-scale systems is established due to large quantum fluctuations which render mean-field approaches inaccurate.

Insulin-regulatable phosphoproteins in 3T3-L1 adipocytes form detergent-insoluble complexes not associated with caveolin

Whole body glucose homeostasis is dependent on the action of insulin. In muscle and adipose tissues, insulin stimulates glucose uptake by inducing the translocation of vesicles containing the glucose transporter GLUT4 to the cell surface. While the mechanisms of insulin-regulated GLUT4 translocation are not fully understood, some signaling intermediates have been implicated in this process. Interestingly, som: of these intermediates, including IRS-1 and PI3K, have been localised to the same intracellular membrane fraction as the GLUT4 storage pool, designated here as the high-speed pellet (HSP) fraction. This raises the possibility that many of the downstream insulin signaling intermediates may be located within close proximity to intracellular GLUT4. The goal of this study was to test this hypothesis in 3T3-L1 adipocytes. A large proportion of adipocyte phosphoproteins co-fractionated in the HSP fraction. In an attempt to resolve insulin-regulatable phosphoproteins, we subjected P-32-labeled subcellular fractions to two-dimensional gel electrophoresis (2-DE). Insulin reproducibly stimulated the phosphorylation of 12 spots in the HSP fraction. Most of the HSP phosphoproteins were insoluble in the nonionic detergent Triton X-100, whereas integral membrane proteins such as GLUT4 and intracellular caveolin were soluble under the same conditions. These results suggest that insulin-regulatable phosphoproteins in adipocytes may be organized in microdomains within the cell and that this assembly may act as an efficient conductor of the signaling proteins to rapidly facilitate downstream biological responses. Further study is required to establish the molecular basis for these detergent-insoluble signaling complexes.

The structure of quantum Lie algebras for the classical series, B-l, C-l and D-l

The structure constants of quantum Lie algebras depend on a quantum deformation parameter q and they reduce to the classical structure constants of a Lie algebra at q = 1. We explain the relationship between the structure constants of quantum Lie algebras and quantum Clebsch-Gordan coefficients for adjoint x adjoint --> adjoint We present a practical method for the determination of these quantum Clebsch-Gordan coefficients and are thus able to give explicit expressions for the structure constants of the quantum Lie algebras associated to the classical Lie algebras B-l, C-l and D-l. In the quantum case the structure constants of the Cartan subalgebra are non-zero and we observe that they are determined in terms of the simple quantum roots. We introduce an invariant Killing form on the quantum Lie algebras and find that it takes values which are simple q-deformations of the classical ones.

Extended GCD and Hermite normal form algorithms via lattice basis reduction

Extended gcd calculation has a long history and plays an important role in computational number theory and linear algebra. Recent results have shown that finding optimal multipliers in extended gcd calculations is difficult. We present an algorithm which uses lattice basis reduction to produce small integer multipliers x(1), ..., x(m) for the equation s = gcd (s(1), ..., s(m)) = x(1)s(1) + ... + x(m)s(m), where s1, ... , s(m) are given integers. The method generalises to produce small unimodular transformation matrices for computing the Hermite normal form of an integer matrix.

Dysregulated hematopoiesis and a progressive neurological disorder induced by expression of an activated form of the human common beta chain in transgenic mice

Previously we described activating mutations of h beta(c), the common signaling subunit of the receptors for the hematopoietic and inflammatory cytokines, GM-CSF, IL-3, and IL-5. The activated mutant, h beta(c)FI Delta, is able to confer growth factor-independent proliferation on the murine myeloid cell line FDC-P1, and on primary committed myeloid progenitors. We have used this activating mutation to study the effects of chronic cytokine receptor stimulation. Transgenic mice were produced carrying the h beta(c)FI Delta cDNA linked to the constitutive promoter derived from the phosphoglycerate kinase gene, PGK-1. Transgene expression was demonstrated in several tissues and functional activity of the mutant receptor was confirmed in hematopoietic tissues by the presence of granulocyte macrophage and macrophage colony-forming cells (CFU-GM and CFU-M) in the absence of added cytokines. All transgenic mice display a myeloproliferative disorder characterized by splenomegaly, erythrocytosis, and granulocytic and megakaryocytic hyperplasia. This disorder resembles the human disease polycythemia vera, suggesting that activating mutations in h beta(c) may play a role in the pathogenesis of this myeloproliferative disorder. In addition, these transgenic mice develop a sporadic, progressive neurological disease and display bilateral, symmetrical foci of necrosis in the white matter of brain stem associated with an accumulation of macrophages. Thus, chronic h beta(c) activation has the potential to contribute to pathological events in the central nervous system.

Truncation errors in finite difference models for solute transport equation with first-order reaction

The truncation errors associated with finite difference solutions of the advection-dispersion equation with first-order reaction are formulated from a Taylor analysis. The error expressions are based on a general form of the corresponding difference equation and a temporally and spatially weighted parametric approach is used for differentiating among the various finite difference schemes. The numerical truncation errors are defined using Peclet and Courant numbers and a new Sink/Source dimensionless number. It is shown that all of the finite difference schemes suffer from truncation errors. Tn particular it is shown that the Crank-Nicolson approximation scheme does not have second order accuracy for this case. The effects of these truncation errors on the solution of an advection-dispersion equation with a first order reaction term are demonstrated by comparison with an analytical solution. The results show that these errors are not negligible and that correcting the finite difference scheme for them results in a more accurate solution. (C) 1999 Elsevier Science B.V. All rights reserved.

Life-cycle preferences over consumption and health: when is cost-effectiveness analysis equivalent to cost-benefit analysis?

This paper studies life-cycle preferences over consumption and health status. We show that cost-effectiveness analysis is consistent with cost-benefit analysis if the Lifetime utility function is additive over time, multiplicative in the utility of consumption and the utility of health status, and if the utility of consumption is constant over time. We derive the conditions under which the lifetime utility function takes this form, both under expected utility theory and under rank-dependent utility theory, which is currently the most important nonexpected utility theory. If cost-effectiveness analysis is consistent with cost-benefit analysis, it is possible to derive tractable expressions for the willingness to pay for quality-adjusted life-years (QALYs). The willingness to pay for QALYs depends on wealth, remaining life expectancy, health status, and the possibilities for intertemporal substitution of consumption. (C) 1999 Elsevier Science B.V. All rights reserved.