On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples

This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).

The other side of the coin: safety of complementary and alternative medicine

Most consumers consider complementary and alternative medicine (CAM) products inherently safe. The growing simultaneous use of CAM products and pharmaceutical drugs by Australian consumers increases the risk of CAM-drug interactions. The Therapeutic Goods Administration (TGA) has a two-tier, risk-based regulatory system for therapeutic goods - CAM products are regulated as low risk products and are assessed for quality and safety; and sponsors of products must hold the evidence for any claim of efficacy made about them. Adverse reactions to CAM products can be classified as intrinsic (innate to the product), or extrinsic (where the risk is not related to the product itself, but results from the failure of good manufacturing practice). Adverse reactions to CAM practices can be classified as risks of commission (which includes removal of medical therapy) and risks of omission (which includes failure to refer when appropriate). While few systematic studies of adverse events with CAM exist, and under-reporting is likely, most CAM products and practices do not appear to present a high risk; their safety needs to be put into the perspective of wider safety issues. A priority for research is to rigorously define the risks associated with both CAM products and practices so that their potential impact on public health can be assessed.

The use of simultaneous H-1 & P-31 magic angle spinning nuclear magnetic resonance measurements to characterize energy metabolism during the conversion of muscle to meat

In order to investigate the potential of magic angle spinning nuclear magnetic resonance (MAS NMR) in the elucidation of post-mortem metabolism in muscle biopsies, simultaneous H-1 and (31)p MAS NMR measurements were made continuously on postmortem (20 min to 24 h) muscle longissimus samples from rabbits. The animals had either been or not been given adrenaline (0.5 mg kg(-1) 4 h pre-slaughter) to deplete stores of muscle glycogen. The intracellular pH was calculated from H-1 spectra, and the post-mortem rate of formation of lactate was followed and quantified. Comparison of measurements made on muscle samples from rabbits treated with adrenaline with measurements made on muscle samples from untreated' rabbits revealed significant effects of adrenaline treatment on both pH (pH24 h = 6.42 vs. pH24 It = 5.60) and formation of lactate (16 mmol g(-1) vs. 65 mmol g(-1)). The P-31 NMR spectra were used to follow the rate of degradation of ATP and phosphocreatine. The present study clearly shows that MAS NMR has potential for the study of post-mortem energy metabolism.

Simultaneous detection and differentiation of human Polyomaviruses JC and BK by a rapid and sensitive PCR-ELAHA assay and a survey of the JCV subtypes within an Australian population

Human polyomaviruses JCV and BKV can cause several clinical manifestations in immunocompromised hosts, including progressive multifocal leukoencephalopathy (PML) and haemorrhagic cystitis. Molecular detection by polymerase chain reaction (PCR) is recognised as a sensitive and specific method for detecting human polyomaviruses in clinical samples. In this study, we developed a PCR assay using a single primer pair to amplify a segment of the VP1 gene of JCV and BKV. An enzyme linked amplicon hybridisation assay (ELAHA) using species-specific biotinylated oligonucleotide probes was used to differentiate between JCV and BKV. This assay (VP1-PCR-ELAHA) was evaluated and compared to a PCR assay targeting the human polyomavirus T antigen gene (pol-PCR). DNA sequencing was used to confirm the polyomavirus species identified by the VP1-PCR-ELAHA and to determine the subtype of each JCV isolate. A total of 297 urine specimens were tested and human polyomavirus was detected in 105 specimens (35.4%) by both PCR assays. The differentiation of JCV and BKV by the VP1-PCR-ELAHA showed good agreement with the results of DNA sequencing. Further, DNA sequencing of the JCV positive specimens showed the most prevalent JCV subtype in our cohort was 2a (27%) followed by 1b (20%), 1a (15%), 2c (14%), 4 (14%) and 2b (10%). The results of this study show that the VP1-PCR-ELAHA is a sensitive, specific and rapid method for detecting and differentiating human polyomaviruses JC and BK and is highly suitable for routine use in the clinical laboratory. (C) 2004 Wiley-Liss, Inc.

An advanced regularization methodology for use in watershed model calibration

A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.

Comparative phylogeographic summary statistics for testing simultaneous vicariance

Testing for simultaneous vicariance across comparative phylogeographic data sets is a notoriously difficult problem hindered by mutational variance, the coalescent variance, and variability across pairs of sister taxa in parameters that affect genetic divergence. We simulate vicariance to characterize the behaviour of several commonly used summary statistics across a range of divergence times, and to characterize this behaviour in comparative phylogeographic datasets having multiple taxon-pairs. We found Tajima's D to be relatively uncorrelated with other summary statistics across divergence times, and using simple hypothesis testing of simultaneous vicariance given variable population sizes, we counter-intuitively found that the variance across taxon pairs in Nei and Li's net nucleotide divergence (pi(net)), a common measure of population divergence, is often inferior to using the variance in Tajima's D across taxon pairs as a test statistic to distinguish ancient simultaneous vicariance from variable vicariance histories. The opposite and more intuitive pattern is found for testing more recent simultaneous vicariance, and overall we found that depending on the timing of vicariance, one of these two test statistics can achieve high statistical power for rejecting simultaneous vicariance, given a reasonable number of intron loci (> 5 loci, 400 bp) and a range of conditions. These results suggest that components of these two composite summary statistics should be used in future simulation-based methods which can simultaneously use a pool of summary statistics to test comparative the phylogeographic hypotheses we consider here.

Identifying causes for N2O accumulation in a lab-scale sequencing batch reactor performing simultaneous nitrification, denitrification and phosphorus removal

The recently described process of simultaneous nitrification, denitrification and phosphorus removal (SNDPR) has a great potential to save capital and operating costs for wastewater treatment plants. However, the presence of glycogen-accumulating organisms (GAOs) and the accumulation of nitrous oxide (N2O) can severely compromise the advantages of this process. In this study, these two issues were investigated using a lab-scale sequencing batch reactor performing SNDPR over a 5-month period. The reactor was highly enriched in polyphosphate-accumulating organisms (PAOs) and GAOs representing around 70% of the total microbial community. PAOs were the dominant population at all times and their abundance increased, while GAOs population decreased over the study period. Anoxic batch tests demonstrated that GAOs rather than denitrifying PAOs were responsible for denitrification. NO accumulated from denitrification and more than half of the nitrogen supplied in a reactor cycle was released into the atmosphere as NO. After mixing SNDPR sludge with other denitrifying sludge, N2O present in the bulk liquid was reduced immediately if external carbon was added. We therefore suggest that the N2O accumulation observed in the SNDPR reactor is an artefact of the low microbial diversity facilitated by the use of synthetic wastewater with only a single carbon source. (C) 2005 Elsevier B.V. All rights reserved.