Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

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.

Fate of hairpin transcript components during RNA silencing and its suppression in transgenic virus-resistant tobacco

Transgenic tobacco plants, carrying a Potato virus Y (PVY)-NIa hairpin sequence separated by a unique unrelated spacer sequence were specifically silenced and highly resistant to PVY infection. In such plants neither PVY-NIa nor spacer transgene transcripts were detectable by specific quantitative real time reverse transcriptase PCR (RT-qPCR) assays of similar relative efficiencies developed for direct comparative analysis. However, small interfering RNAs (siRNAs) specific for the PVY sequence of the transgene and none specific for the LNYV spacer sequence were detected. Following infection with Cucumber mosaic virus (CMV), which suppresses dsRNA-induced RNA silencing, transcript levels of PVY-NIa as well as spacer sequence increased manifold with the same time course. The cellular abundance of the single-stranded (ss) spacer sequence was consistently higher than that of PVY dsRNA in all cases. The results show that during RNA silencing and its suppression of a hairpin transcript in transgenic tobacco, the ssRNA spacer sequence is affected differently than the dsRNA. In PVY-silenced plants. the spacer is efficiently degraded by a mechanism not involving the accumulation of siRNAs, while following suppression of RNA silencing by CMV, the spacer appears protected from degradation. Crown Copyright (c) 2006 Published by Elsevier B.V. All rights reserved.

Comparison of active venom components between Eastern brown snakes collected from South Australia and Queensland

The abundance and activity of the prothrombin activator (pseutarin C) within the venom of the Eastern brown snake (Pseudonaja textilis textilis) is the primary determinant of its coagulation potency. Textilinin-1, also in this venom, is a plasmin inhibitor which is thought to exert its toxic effects through the slowing of fibrinolysis. The aim of this report is to determine if there are differences in the potency of the venom from Eastern brown snakes collected from South Australia (SA) compared to those from Queensland (QLD). A concentration of 0.4 mu g/ml venom protein from six QLD specimens clotted citrated plasma in an average time of 21.4 +/- 3.3 s compared to 68.7 +/- 2.4 s for the same amount of SA venom (averaged for six individuals). The more potent procoagulant activity of the QLD venom was measured between 0.4 and 94 mu g/ml venom protein in plasma. The anti-plasmin activity of textilinin was also greater in the venom of the snakes collected from QLD, causing full inhibition of plasmin at approximately 1.88 mu g/ml of venom protein compared to approximately 7.5 mu g/ml for the SA venoms. It is concluded that geographic differentiation of the Eastern brown snakes results in significant differences venom potency.

The influence of pressure during solidification of high pressure die cast aluminium telecommunications components

The effects of process variables on the quality of high-pressure die cast components was determined with the aid of in-cavity pressure sensors. In particular, the effects of set intensification pressure, delay time, and casting velocity have been investigated. The in-cavity pressure sensor has been used to determine how conditions within the die-cavity are related to the process parameters regulated by the die casting machine, and in turn the effect of variations in these parameters on the integrity of the final part. Porosity was found to decrease with increasing intensification pressure and increase with increasing casting velocity. The delay time before the application of the intensification pressure was not observed to have a significant effect on porosity levels. (c) 2006 Elsevier B.V. All rights reserved.

A low-cost, easy-to-use, real-time power system simulator

We present the design rationale and basic workings of a low-cost, easy-to-use power system simulator developed to support investigations into human interface design for a hydropower plant. The power system simulator is based on three important components: models of power system components, a data repository, and human interface elements. Dynamic Data Exchange (DDE) allows simulator components to communicate with each other within the simulator. To construct the modules of the simulator we have combined the advantages of commercial software such as Matlab/Simulink, ActiveX Control, Visual Basic and Excel and integrated them in the simulator. An important advantage of our approach is that further components of the simulator now can be developed independently. An initial assessment of the simulator indicates it is fit for intended purpose.

Heart rate variability characterization using a time-frequency based instantaneous frequency estimation technique

In this paper, a new method for characterizing the newborn heart rate variability (HRV) is proposed. The central of the method is the newly proposed technique for instantaneous frequency (IF) estimation specifically designed for nonstationary multicomponen signals such as HRV. The new method attempts to characterize the newborn HRV using features extracted from the time–frequency (TF) domain of the signal. These features comprise the IF, the instantaneous bandwidth (IB) and instantaneous energy (IE) of the different TF components of the HRV. Applied to the HRV of both normal and seizure suffering newborns, this method clearly reveals the locations of the spectral peaks and their time-varying nature. The total energy of HRV components, ET and ratio of energy concentrated in the low-frequency (LF) to that in high frequency (HF) components have been shown to be significant features in identifying the HRV of newborn with seizures.

Towards a refinement calculus for concurrent real-time programs

We define a language and a predicative semantics to model concurrent real-time programs. We consider different communication paradigms between the concurrent components of a program: communication via shared variables and asynchronous message passing (for different models of channels). The semantics is the basis for a refinement calculus to derive machine-independent concurrent real-time programs from specifications. We give some examples of refinement laws that deal with concurrency.