Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.

Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

Immunohistological analysis of Tannerella forsythia-induced lesions in a murine model

Tannerella forsythia has been implicated as a defined periodontal pathogen. In the present study a mouse model was used to determine the phenotype of leukocytes in the lesions induced by subcutaneous injections of either live (group A) or nonviable (group B) T. forsythia. Control mice (group C) received the vehicle only. Lesions were excised at days 1, 2, 4, and 7. An avidin-biotin immunoperoxidase method was used to stain infiltrating CD4(+) and CD8(+) T cells, CD14(+) macrophages, CD19(+) B cells, and neutrophils. Hematoxylin and eosin sections demonstrated lesions with central necrotic cores surrounded by neutrophils, macrophages and lymphocytes in both group A and group B mice. Lesions from control mice exhibited no or only occasional solitary leukocytes. In both groups A and B, neutrophils were the dominant leukocyte in the lesion 1 day after injection, the numbers decreasing over the 7-day experimental period. There was a relatively low mean percent of CD4(+) and CD8(+) T cells in the lesions and, whereas the percent of CD8(+) T cells remained constant, there was a significant increase in the percent of CD4(+) T cells at day 7. This increase was more evident in group A mice. The mean percent of CD14(+) macrophages and CD19(+) B cells remained low over the experimental period, although there was a significantly higher mean percent of CD19(+) B cells at day 1. In conclusion, the results showed that immunization of mice with live T. forsythia induced a stronger immune response than nonviable organisms. The inflammatory response presented as a nonspecific immune response with evidence of an adaptive (T-cell) response by day 7. Unlike Porphyromonas gingivalis, there was no inhibition of neutrophil migration.

Long-term in vivo biostability of poly(dimethylsiloxane) / poly(hexamethylene oxide) mixed macrodiol-based polyurethane elastomers

The long-term biostability of a novel thermoplastic polyurethane elastomer (Elast-Eon(TM) 2 80A) synthesized using poly(hexamethylene oxide) (PHMO) and poly(dimethylsiloxane) (PDMS) macrodiols has been studied using an in vivo ovine model. The material's biostability was compared with that of three commercially available control materials, Pellethane(R) 2363-80A, Pellethane(R) 2363-55D and Bionate(R) 55D, after subcutaneous implantation of strained compression moulded flat sheet dumbbells in sheep for periods ranging from 3 to 24 months. Scanning electron microscopy, attenuated total reflectance-Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy were used to assess changes in the surface chemical structure and morphology of the materials. Gel permeation chromatography, differential scanning calorimetry and tensile testing were used to examine changes in bulk characteristics of the materials. The results showed that the biostability of the soft flexible PDMS-based test polyurethane was significantly better than the control material of similar softness, Pellethane(R) 80A, and as good as or better than both of the harder commercially available negative control polyurethanes. Pellethane(R) 55D and Bionate(R) 55D. Changes observed in the surface of the Pellethane(R) materials were consistent with oxidation of the aliphatic polyether soft segment and hydrolysis of the urethane bonds joining hard to soft segment with degradation in Pellethane(R) 80A significantly more severe than that observed in Pellethane(R) 55D. Very minor changes were seen on the surfaces of the Elast-Eon(TM) 2 80A and Bionate(R) 55D materials. There was a general trend of molecular weight decreasing with time across all polymers and the molecular weights of all materials decreased at a similar relative rate. The polydispersity ratio, M-w/M-n, increased with time for all materials. Tensile tests indicated that UTS increased in Elast-Eon(TM) 2 80A and Bionate(R) 55D following implantation under strained conditions. However, ultimate strain decreased and elastic modulus increased in the explanted specimens of all three materials when compared with their unimplanted unstrained counterparts. The results indicate that a soft, flexible PDMS-based polyurethane synthesized using 20% PHMO and 80% PDMS macrodiols has excellent long-term biostability compared with commercially available polyurethanes. (C) 2004 Elsevier Ltd. All rights reserved.

Numerical simulation of abrupt contraction flows using the Double Convected Pom-Pom model

The Double Convected Pom-Pom model was recently introduced to circumvent some numerical and theological defects found in other formulations of the Pom-Pom concept. It is used here for the simulation of a benchmark problem: the flow in an abrupt planar contraction. The predictions are compared with birefringence measurements and show reasonable quantitative agreement with experimental data. A parametric study is also carried out with the aim of analysing the effect of the branching parameter on vortex dynamics and extrudate swell. The results show that the Double Convected Pom-Pom model (DCPP) model is able to discriminate between branched and linear macromolecular structures in accordance with experimental observations. In that respect, the role of the extensional properties in determining complex flow behaviour is stressed. Also, the ratio of the first normal stress difference to the shear stress appears to play a major role in die swell observation. For the time being, the role of the second normal stress difference appears to be less obvious to evaluate in this complex flow. (C) 2004 Elsevier B.V. All rights reserved.

Gelatinization of starch in mixed sugar systems

Sugars affect the gelatinization of starch, with the effect varying significantly between sugars. Since many food products contain a mixture of sugar sources, it is important to understand how their mixtures affect starch gelatinization. In a Rapid Visco Analyser study of maize starch gelatinization, changing proportions in binary mixtures of refined sugars saw a largely proportionate change in starch gelatinization properties. However, binary mixture of pure sugars and honey, or a model honey system (the main sugars in honey) and honey responded differently. Generally, replacing 25% or 50% of the refined sugar or model honey system with honey gave a large change in starch gelatinization properties, while further increases in honey level had little further effect. Differences between honey and buffered model honey system (either gluconic acid, or a mixture of citric acid and di-sodium phosphate) showed the sensitivity of starch gelatinization to the composition of the nonsaccharide component. (c) 2004 Swiss Society of Food Science and Technology. Published by Elsevier Ltd. All rights reserved.

Normalized Gaussian Networks with Mixed Feature Data

With mixed feature data, problems are induced in modeling the gating network of normalized Gaussian (NG) networks as the assumption of multivariate Gaussian becomes invalid. In this paper, we propose an independence model to handle mixed feature data within the framework of NG networks. The method is illustrated using a real example of breast cancer data.

Large scale experiments on gravel and mixed beaches: Experimental procedure, data documentation and initial results

This paper provides information on the experimental set-up, data collection methods and results to date for the project Large scale modelling of coarse grained beaches, undertaken at the Large Wave Channel (GWK) of FZK in Hannover by an international group of researchers in Spring 2002. The main objective of the experiments was to provide full scale measurements of cross-shore processes on gravel and mixed beaches for the verification and further development of cross-shore numerical models of gravel and mixed sediment beaches. Identical random and regular wave tests were undertaken for a gravel beach and a mixed sand/gravel beach set up in the flume. Measurements included profile development, water surface elevation along the flume, internal pressures in the swash zone, piezometric head levels within the beach, run-up, flow velocities in the surf-zone and sediment size distributions. The purpose of the paper is to present to the scientific community the experimental procedure, a summary of the data collected, some initial results, as well as a brief outline of the on-going research being carried out with the data by different research groups. The experimental data is available to all the scientific community following submission of a statement of objectives, specification of data requirements and an agreement to abide with the GWK and EU protocols. (C) 2005 Elsevier B.V. All rights reserved.

Stoichiometric and kinetic characterisation of Nitrobacter in mixed culture by decoupling the growth and energy generation processes

The growth, maintenance and lysis processes of Nitrobacter were characterised. A Nitrobacter culture was enriched in a sequencing batch reactor (SBR). Fluorescent in situ hybridisation showed that Nitrobacter constituted 73% of the bacterial population. Batch tests were carried out to measure the oxygen uptake rate and/or nitrite consumption rate when both nitrite and CO2 were in excess, and in the absence of either of these two substrates. The results obtained, along with the SBR performance data, allowed the determination of the maintenance coefficient and in situ cell lysis rate of Nitrobacter. Nitrobacter spends a significant amount of energy for maintenance, which varies considerably with the specific growth rate. At maximum growth, Nitrobacter consume nitrite at a rate of 0.042 mgN/mgCOD(biomass)center dot h for maintenance purposes, which increases more than threefold to 0.143 mgN/mgCOD(biomass)center dot h in the absence of growth. In the SBR, where Nitrobacter grew at 40% of its maximum growth rate, a maintenance coefficient of 0.113 mgN/mgCOD center dot h was found, resulting in 42% of the total amount of nitrite being consumed for maintenance. The above three maintenance coefficient values obtained at different growth rates appear to support the maintenance model proposed in Pirt (1982). The in situ lysis rate of Nitrobacter was determined to be 0.07/day under aerobic conditions at 22 C and pH 7.3. Further, the maximum specific growth rate of Nitrobacter was estimated to be 0.02/h (0.48/day). The affinity constant of Nitrobacter with respect to nitrite was determined to be 1.50 mgNO(2)(-)-N/L, independent of the presence or absence of CO2. (c) 2006 Wiley Periodicals, Inc.

Mixed order parameters, accidental nodes and broken time reversal symmetry in organic superconductors: a group theoretical analysis

We present a group theoretical analysis of several classes of organic superconductor. We predict that highly frustrated organic superconductors, such as K-(ET)(2)Cu-2(CN)(3) (where ET is BEDT-TTF, bis(ethylenedithio) tetrathiafulvalene) and beta'-[Pd(dmit)(2)](2)X, undergo two superconducting phase transitions, the first from the normal state to a d-wave superconductor and the second to a d + id state. We show that the monoclinic distortion of K-(ET)(2)Cu(NCS)(2) means that the symmetry of its superconducting order parameter is different from that of orthorhombic-K-(ET)(2)Cu[N(CN)(2)] Br. We propose that beta'' and theta phase organic superconductors have d(xy) + s order parameters.

Stoichiometric and kinetic characterisation of Nitrosomonas sp in mixed culture by decoupling the growth and energy generation processes

A novel method that relies on the decoupling of the energy production and biosynthesis processes was used to characterise the maintenance, cell lysis and growth processes of Nitrosomonas sp. A Nitrosolnonas culture was enriched in a sequencing batch reactor (SBR) with ammonium as the sole energy source. Fluorescent in situ hybridization (FISH) showed that Nitrosomonas bound to the NEU probe constituted 82% of the bacterial population, while no other known ammonium or nitrite oxidizing bacteria were detected. Batch tests were carried out under conditions that both ammonium and CO, were in excess, and in the absence of one of these two substrates. The oxygen uptake rate and nitrite production rate were measured during these batch tests. The results obtained from these batch tests, along with the SBR performance data, allowed the determination of the maintenance coefficient and the in situ cell lysis rate, as well as the maximum specific growth rate of the Nitrosomonas culture. It is shown that, during normal growth, the Nitrosomonas culture spends approximately 65% of the energy generated for maintenance. The maintenance coefficient was determined to be 0.14 - 0.16 mgN mgCOD(biomass)(-1) h(-1), and was shown to be independent of the specific growth rate. The in situ lysis rate and the maximum specific growth rate of the Nitrosomonas culture were determined to be 0.26 and 1.0 day(-1) (0.043 h(-1)), respectively, under aerobic conditions at 30 degrees C and pH7. (c) 2006 Elsevier B.V. All rights reserved.

A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants

The paper investigates a Bayesian hierarchical model for the analysis of categorical longitudinal data from a large social survey of immigrants to Australia. Data for each subject are observed on three separate occasions, or waves, of the survey. One of the features of the data set is that observations for some variables are missing for at least one wave. A model for the employment status of immigrants is developed by introducing, at the first stage of a hierarchical model, a multinomial model for the response and then subsequent terms are introduced to explain wave and subject effects. To estimate the model, we use the Gibbs sampler, which allows missing data for both the response and the explanatory variables to be imputed at each iteration of the algorithm, given some appropriate prior distributions. After accounting for significant covariate effects in the model, results show that the relative probability of remaining unemployed diminished with time following arrival in Australia.