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).

Ecoregion classification using a bayesian approach and centre-focused clusters

Ecological regions are increasingly used as a spatial unit for planning and environmental management. It is important to define these regions in a scientifically defensible way to justify any decisions made on the basis that they are representative of broad environmental assets. The paper describes a methodology and tool to identify cohesive bioregions. The methodology applies an elicitation process to obtain geographical descriptions for bioregions, each of these is transformed into a Normal density estimate on environmental variables within that region. This prior information is balanced with data classification of environmental datasets using a Bayesian statistical modelling approach to objectively map ecological regions. The method is called model-based clustering as it fits a Normal mixture model to the clusters associated with regions, and it addresses issues of uncertainty in environmental datasets due to overlapping clusters.

Incremental model transformation for the evolution of model-driven systems

Model transformations are an integral part of model-driven development. Incremental updates are a key execution scenario for transformations in model-based systems, and are especially important for the evolution of such systems. This paper presents a strategy for the incremental maintenance of declarative, rule-based transformation executions. The strategy involves recording dependencies of the transformation execution on information from source models and from the transformation definition. Changes to the source models or the transformation itself can then be directly mapped to their effects on transformation execution, allowing changes to target models to be computed efficiently. This particular approach has many benefits. It supports changes to both source models and transformation definitions, it can be applied to incomplete transformation executions, and a priori knowledge of volatility can be used to further increase the efficiency of change propagation.

Issues of robustness and high dimensionality in cluster analysis

Finite mixture models are being increasingly used to model the distributions of a wide variety of random phenomena. While normal mixture models are often used to cluster data sets of continuous multivariate data, a more robust clustering can be obtained by considering the t mixture model-based approach. Mixtures of factor analyzers enable model-based density estimation to be undertaken for high-dimensional data where the number of observations n is very large relative to their dimension p. As the approach using the multivariate normal family of distributions is sensitive to outliers, it is more robust to adopt the multivariate t family for the component error and factor distributions. The computational aspects associated with robustness and high dimensionality in these approaches to cluster analysis are discussed and illustrated.

Growth of Bose-Einstein condensates from thermal vapor

We report on a quantitative study of the growth process of 87Rb Bose-Einstein condensates. By continuous evaporative cooling we directly control the thermal cloud from which the condensate grows. We compare the experimental data with the results of a theoretical model based on quantum kinetic theory. We find quantitative agreement with theory for the situation of strong cooling, whereas in the weak cooling regime a distinctly different behavior is found in the experiment.

alpha-conotoxin EpI, a novel sulfated peptide from Conus episcopatus that selectively targets neuronal nicotinic acetylcholine receptors

We have isolated and characterized ol-conotoxin EpI, a novel sulfated peptide from the venom of the molluscivorous snail, Conus episcopatus, The peptide was classified as an cy-conotoxin based on sequence, disulfide connectivity, and pharmacological target. EpI has ho mology to sequences of previously described cu-conotoxins, particularly PnIA, PnIB, and ImI, However, EpI differs from previously reported conotoxins in that it has a sulfotyrosine residue, identified by amino acid analysis and mass spectrometry, Native EpI was shown to coelute with synthetic EpI, The peptide sequence is consistent with most, but not all, recognized criteria for predicting tyrosine sulfation sites in proteins and peptides, The activities of synthetic EpI and its unsulfated analogue [Tyr(15)]EpI were similar. Both peptides caused competitive inhibition of nicotine action on bovine adrenal chromaffin cells (neuronal nicotinic ACh receptors) but had no effect on the rat phrenic nerve-diaphragm (muscle nicotinic ACh receptors), Both EpI and [Tyr(15)]EpI partly inhibited acetylcholine-evoked currents in isolated parasympathetic neurons of rat intracardiac ganglia, These results indicate that EPI and [Tyr(15)]EpI selectively inhibit alpha 3 beta 2 and alpha 3 beta 4 nicotinic acetylcholine receptors.

In vivo measurement of the effect of intra-abdominal pressure on the human spine

In humans, intra-abdominal pressure (IAP) is elevated during many everyday activities. This experiment aimed to investigate the extent to which increased IAP-without concurrent activity of the abdominal or back extensor muscles-produces an extensor torque. With subjects positioned in side lying on a swivel table with its axis at L3, moments about this vertebral level were measured when IAP was transiently increased by electrical stimulation of the diaphragm via the phrenic nerve. There was no electromyographic activity in abdominal and back extensor muscles. When IAP was increased artificially to similar to 15% of the maximum IAP amplitude that could be generated voluntarily with the trunk positioned in flexion, a trunk extensor moment (similar to6 Nm) was recorded. The size of the effect was proportional to the increase in pressure. The extensor moment was consistent with that predicted from a model based on measurements of abdominal cross-sectional area and IAP moment arm. When IAP was momentarily increased while the trunk was flexed passively at a constant velocity, the external torque required to maintain the velocity was increased. These results provide the first in vivo data of the amplitude of extensor moment that is produced by increased IAP. Although the net effect of this extensor torque in functional tasks would be dependent on the muscles used to increase the IAP and their associated flexion torque, the data do provide evidence that IAP contributes, at least in part, to spinal stability. (C) 2001 Elsevier Science Ltd. All rights reserved.

A numerical study of flexural buckling of foliated rock slopes

The occurrence of foliated rock masses is common in mining environment. Methods employing continuum approximation in describing the deformation of such rock masses possess a clear advantage over methods where each rock layer and each inter-layer interface (joint) is explicitly modelled. In devising such a continuum model it is imperative that moment (couple) stresses and internal rotations associated with the bending of the rock layers be properly incorporated in the model formulation. Such an approach will lead to a Cosserat-type theory. In the present model, the behaviour of the intact rock layer is assumed to be linearly elastic and the joints are assumed to be elastic-perfectly plastic. Condition of slip at the interfaces are determined by a Mohr-Coulomb criterion with tension cut off at zero normal stress. The theory is valid for large deformations. The model is incorporated into the finite element program AFENA and validated against an analytical solution of elementary buckling problems of a layered medium under gravity loading. A design chart suitable for assessing the stability of slopes in foliated rock masses against flexural buckling failure has been developed. The design chart is easy to use and provides a quick estimate of critical loading factors for slopes in foliated rock masses. It is shown that the model based on Euler's buckling theory as proposed by Cavers (Rock Mechanics and Rock Engineering 1981; 14:87-104) substantially overestimates the critical heights for a vertical slope and underestimates the same for sub-vertical slopes. Copyright (C) 2001 John Wiley & Sons, Ltd.

When the going gets rough: effect of maternal size manipulation on larval quality

Variation in larval size has been shown to be an important factor for the post-metamorphic performance of marine invertebrates but, despite its importance, few sources of this variation have been identified. For a range of taxa, offspring size is positively correlated with maternal size but the reasons for this correlation remain unclear. We halved the size of colonies in the bryozoan Bugula neritina 1 wk prior to reproduction (but during embryogenesis) to determine if larval size is a fixed or plastic trait. We manipulated colonies in such a way that the ratio of feeding zooids to reproductive zooids was constant between treatment and control colonies. We found that manipulating colony size strongly affects larval size; halved colonies produced larvae that were similar to13% smaller than those produced by intact colonies. We entered these data into a simple model based on previous work to estimate the likely post-metamorphic consequences of this reduction in larval size. The model predicted that larvae that came from manipulated colonies would suffer similar to300% higher post-metamorphic mortality and similar to50% lower fecundity as adults. Colonies that are faced with a stress appear to be trading off current offspring fitness to maximize their own long-term fitness and this may explain previous observations of compensatory growth in colonial organisms. This study demonstrates that larval size is a surprisingly dynamic trait and strong links exist between the maternal phenotype and the fitness of the offspring. The performance of settling larvae may be determined not only by their larval experience but also by the experience of their mothers.

Value congruence in leader-member exchange

In this study, hypotheses were tested that the quality of leader-member exchanges (LMX) depends on congruity of values between leader and member. Data on negotiating latitude and personal values were gathered from 160 members of 30 work groups in Australian organizations. Factor analysis revealed 5 value dimensions: Freedom, Achievement, Mateship, Obedience, and Coping. Analyses of variance supported the hypothesis that LMX quality is higher when leaders and members share achievement and obedience values. Subsequent exploratory analysis, however, indicated that a more complex model based on compatibility of leader authority and member affiliation values may provide a more complete representation.

Protecting Schrodinger cat states using feedback

A feedback model based on direct photodetection and micromaser-like atomic injection is proposed for the preservation of quantum coherence in a cavity. We show that in this way it is possible to slow down significantly the decoherence of Schrodinger cat states.

Emotions at multiple levels: An integration

Weiss and Isen have provided many supportive comments about the multi-level perspective, but also found limitations. Isen noted the importance of integrating affect, cognition, and motivation. Weiss commented similarly that the model lacked an integrating “thread.” He suggested that, to be truly multilevel, each level should constrain processes at other levels, and also provide guidance for the development of new concepts. Weiss also noted that the focus on biological processes was a strength of the model. I respond by suggesting that these very biological processes may constitute the “missing” thread. To illustrate this, I discuss some of the recent research on emotions in organizational settings, and argue that biology both constrains and guides theory at each level of the model. Based on this proposition, I revisit each of the five levels in the model, to demonstrate how this integration can be accomplished in this fashion. Finally, I address two additional points: aggregation bias, and the possibility of extending the model to include higher levels of industry and region.

Features of colorectal cancers with high-level microsatellite instability occurring in familial and sporadic settings

High-level microsatellite instability (AISI-H) is demonstrated in 10 to 15% of sporadic colorectal cancers and in most cancers presenting In the inherited condition hereditary nonpolyposis colorectal cancer (HNPCC). Distinction between these categories of MSI-H cancer is of clinical importance and the aim of this study was to assess clinical, pathological, and molecular features that might he discriminatory. One hundred and twelve MSI-H colorectal cancers from families fulfilling the Bethesda criteria were compared with 57 sporadic MSI-H colorectal cancers. HNPCC cancers presented at a lower age (P < 0.001) with no sporadic MSI-H cancer being diagnosed before the age of 57 years. MSI was less extensive in HNPCC cancers with 72% microsatellite markers showing band shifts compared with 87% in sporadic tumors (P < 0.001). Absent immunostaining for hMSH2 was only found in HNPCC tumors. Methylation of bMLH1 was observed in 87% of sporadic cancers but also in 55% of HNPCC tumors that showed loss of expression of hMLH1 (P = 0.02). HNPCC cancers were more frequently characterized by aberrant beta -catenin immunostaining as evidenced by nuclear positivity (P < 0.001). Aberrant p53 immunostaining was infrequent in both groups. There were no differences with respect to 5q loss of heterozygosity or codon 12 K-ras mutation, which were infrequent in both groups. Sporadic MSI-H cancers were more frequently heterogeneous (P < 0.001), poorly differentiated (P = 0.02), mucinous (P = 0.02), and proximally located (P = 0.04) than RNPCC tumors. In sporadic MSI-H cancers, contiguous adenomas were likely to be serrated whereas traditional adenomas were dominant in HNPCC. Lymphocytic infiltration was more pronounced in HNPCC but the results did not reach statistical significance. Overall, HNPCC cancers were more like common colorectal cancer in terms of morphology and expression of beta -catenin whereas sporadic MSI-H cancers displayed features consistent with a different morphogenesis. No individual feature was discriminatory for all RN-PCC cancers. However, a model based on four features was able to classify 94.5% of tumors as sporadic or HNPCC. The finding of multiple differences between sporadic and familial MSI-H colorectal cancer with respect to both genotype and phenotype is consistent with tumorigenesis through parallel evolutionary pathways and emphasizes the importance of studying the two groups separately.

Role of circumventricular organs in pro-inflammatory cytokine-induced activation of the hypothalamic-pituitary-adrenal axis

1. The past 15 years has seen the emergence of a new field of neuroscience research based primarily on how the immune system and the central nervous system can interact. A notable example of this interaction occurs when peripheral inflammation, infection or tissue injury activates the hypothalamic- pituitary-adrenal axis (HPA). 2. During such assaults, immune cells release the pro- inflammatory cytokines interleukin (IL)-1, IL-6 and tumour necrosis factor-alpha into the general circulation. 3. These cytokines are believed to act as mediators for HPA axis activation. However, physical limitations of cytokines impede their movement across the blood-brain barrier and, consequently, it has been unclear as to precisely how and where IL-1beta signals cross into the brain to trigger HPA axis activation. 4. Evidence from recent anatomical and functional studies suggests two neuronal networks may be involved in triggering HPA axis activity in response to circulating cytokines. These are catecholamine cells of the medulla oblongata and the circumventricular organs (CVO). 5. The present paper examines the role of CVO in generating HPA axis responses to pro-inflammatory cytokines and culminates with a proposed model based on cytokine signalling primarily involving the area postrema and catecholamine cells in the ventrolateral and dorsal medulla.

MapScript: A map algebra programming language incorporating neighborhood analysis

Map algebra is a data model and simple functional notation to study the distribution and patterns of spatial phenomena. It uses a uniform representation of space as discrete grids, which are organized into layers. This paper discusses extensions to map algebra to handle neighborhood operations with a new data type called a template. Templates provide general windowing operations on grids to enable spatial models for cellular automata, mathematical morphology, and local spatial statistics. A programming language for map algebra that incorporates templates and special processing constructs is described. The programming language is called MapScript. Example program scripts are presented to perform diverse and interesting neighborhood analysis for descriptive, model-based and processed-based analysis.