Failure of a medulloblastoma-derived mutant of SUFU to suppress WNT signaling

Germline mutations of APC in patients with Turcot syndrome (colon cancer and medulloblastoma), was well as somatic mutations of APC, beta-catenin, and Axin in sporadic medulloblastomas (MBs) have shown the importance of WNT signaling in the pathogenesis of MB. A subset of children with MB have germline mutations of SUFU, a known inhibitor of Hedgehog signal transduction. A recent report suggested that murine Sufu can bind beta-catenin, export it from the nucleus, and thereby repress beta-catenin/T-cell factor (Tcf)-mediated transcription. We show that an MB-derived mutant of SUFU has lost the ability to decrease nuclear levels of beta-catenin, and cannot inhibit beta-catenin/Tcf-mediated transcription as compared to wild type SUFU. Our results suggest that loss of function of SUFU results in overactivity of both the Sonic Hedgehog, and the WNT signaling pathways, leading to excessive proliferation and failure to differentiate resulting in MB.

Predictive genetic test decisions for Huntington's disease: context, appraisal and new moral imperatives

Predictive testing is one of the new genetic technologies which, in conjunction with developing fields such as pharmacogenomics, promises many benefits for preventive and population health. Understanding how individuals appraise and make genetic test decisions is increasingly relevant as the technology expands. Lay understandings of genetic risk and test decision-making, located within holistic life frameworks including family or kin relationships, may vary considerably from clinical representations of these phenomena. The predictive test for Huntington's disease (HD), whilst specific to a single-gene, serious, mature-onset but currently untreatable disorder, is regarded as a model in this context. This paper reports upon a qualitative Australian study which investigated predictive test decision-making by individuals at risk for HD, the contexts of their decisions and the appraisals which underpinned them. In-depth interviews were conducted in Australia with 16 individuals at 50% risk for HD, with variation across testing decisions, gender, age and selected characteristics. Findings suggested predictive testing was regarded as a significant life decision with important implications for self and others, while the right not to know genetic status was staunchly and unanimously defended. Multiple contexts of reference were identified within which test decisions were located, including intra- and inter-personal frameworks, family history and experience of HID, and temporality. Participants used two main criteria in appraising test options: perceived value of, or need for the test information, for self and/or significant others, and degree to which such information could be tolerated and managed, short and long-term, by self and/or others. Selected moral and ethical considerations involved in decision-making are examined, as well as the clinical and socio-political contexts in which predictive testing is located. The paper argues that psychosocial vulnerabilities generated by the availability of testing technologies and exacerbated by policy imperatives towards individual responsibility and self-governance should be addressed at broader societal levels. (C) 2003 Elsevier Science Ltd. All rights reserved.

Influence of Observer Presence on Pacific Damsel Bug Behavior: Who is Watching Whom?

When direct observations are used to study animal behavior the presence of the observer may alter the animal and hence influence the data being collected, yet few studies have quantified this effect. We conducted direct observation studies in the glasshouse to assess the relative influence of observer presence on the behavior of Pacific damsel bugs, Nabis kinbergii, a potentially important predator of crop pests. Comparisons of predator activity, predator distribution, prey (Helicoverpa armigera) mortality and prey distribution between frequently observed and minimally observed treatments, during diurnal and nocturnal observation sessions showed that the frequency of observer presence had no apparent impact on Pacific damsel bug behavior. This is the first documented test of the impact of observer presence in an insect system. To place our results in context, we reviewed 15 papers on the influence of observer presence in a range of animals. We established that just over half of these papers found evidence for an effect. Nevertheless, direct observations should be useful in further studies of Pacific damsel bug behavior, and researchers using direct observations to study the behavior of other animals should be cognizant of observer effects during design and interpretation of their study.

Predictive genetic test decisions for Huntington's disease: Elucidating the test/no-test dichotomy

Predictive genetic testing for serious, mature-onset genetic illness represents a unique context in health decision making. This article presents findings from an exploratory qualitative Australian-based study into the decision making of individuals at risk for Huntington's disease (HD) with regard to predictive genetic testing. Sixteen in-depth interviews were conducted with a range of at-risk individuals. Data analysis revealed four discrete decision-making positions rather than a 'to test' or not to test' dichotomy. A conceptual dimension of (non-)openness and (non-)engagement characterized the various decisions. Processes of decision making and a concept of 'test readiness' were identified. Findings from this research, while not generalizable, are discussed in relation to theoretical frameworks and stage models of health decision making, as well as possible clinical implications.

Design determines 70% of cost? A review of implications for design evaluation

This paper disputes the fact that product design determines 70% of costs and the implications that follow for design evaluation tools. Using the idea of decision chains, it is argued that such tools need to consider more of the downstream business activities and should take into account the current and future state of the business rather than some idealized view of it. To illustrate the argument, a series of experiments using an enterprise simulator are described that show the benefit from the application of a more holistic 'design for' technique. Design For the Existing Environment.

Evaluating design implementation strategies using enterprise simulation

Concurrent engineering and design for manufacture and assembly strategies have become pervasive in use in a wide array of industrial settings. These strategies have generally focused on product and process design issues based on capability concerns. The strategies have been historically justified using cost savings calculations focusing on easily quantifiable costs such as raw material savings or manufacturing or assembly operations no longer required. It is argued herein that neither the focus of the strategies nor the means of justification are adequate. Product and process design strategies should include both capability and capacity concerns and justification procedures should include the financial effects that the product and process changes would have on the entire company. The authors of this paper take this more holistic view of the problem and examine an innovative new design strategy using a comprehensive enterprise simulation tool. The results indicate that both the design strategy and the simulator show promise for further industrial use. © 2001 Elsevier Science B.V. All rights reserved.

Toward bacterial protein sub-cellular location prediction:single-class discrimminant models for all gram- and gram+ compartments

Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation - which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.

TATPred:a Bayesian method for the identification of twin arginine translocation pathway signal sequences

The twin arginine translocation (TAT) system ferries folded proteins across the bacterial membrane. Proteins are directed into this system by the TAT signal peptide present at the amino terminus of the precursor protein, which contains the twin arginine residues that give the system its name. There are currently only two computational methods for the prediction of TAT translocated proteins from sequence. Both methods have limitations that make the creation of a new algorithm for TAT-translocated protein prediction desirable. We have developed TATPred, a new sequence-model method, based on a Nave-Bayesian network, for the prediction of TAT signal peptides. In this approach, a comprehensive range of models was tested to identify the most reliable and robust predictor. The best model comprised 12 residues: three residues prior to the twin arginines and the seven residues that follow them. We found a prediction sensitivity of 0.979 and a specificity of 0.942.

A predictor of membrane class:discriminating α-helical and β-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.

Alpha helical trans-membrane proteins:enhanced prediction using a Bayesian approach

Membrane proteins, which constitute approximately 20% of most genomes, are poorly tractable targets for experimental structure determination, thus analysis by prediction and modelling makes an important contribution to their on-going study. Membrane proteins form two main classes: alpha helical and beta barrel trans-membrane proteins. By using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we addressed alpha-helical topology prediction. This method has accuracies of 77.4% for prokaryotic proteins and 61.4% for eukaryotic proteins. The method described here represents an important advance in the computational determination of membrane protein topology and offers a useful, and complementary, tool for the analysis of membrane proteins for a range of applications.

Beta barrel trans-membrane proteins:enhanced prediction using a Bayesian approach

Membrane proteins, which constitute approximately 20% of most genomes, form two main classes: alpha helical and beta barrel transmembrane proteins. Using methods based on Bayesian Networks, a powerful approach for statistical inference, we have sought to address beta-barrel topology prediction. The beta-barrel topology predictor reports individual strand accuracies of 88.6%. The method outlined here represents a potentially important advance in the computational determination of membrane protein topology.

Combining algorithms to predict bacterial protein sub-cellular location:parallel versus concurrent implementations

We describe a novel and potentially important tool for candidate subunit vaccine selection through in silico reverse-vaccinology. A set of Bayesian networks able to make individual predictions for specific subcellular locations is implemented in three pipelines with different architectures: a parallel implementation with a confidence level-based decision engine and two serial implementations with a hierarchical decision structure, one initially rooted by prediction between membrane types and another rooted by soluble versus membrane prediction. The parallel pipeline outperformed the serial pipeline, but took twice as long to execute. The soluble-rooted serial pipeline outperformed the membrane-rooted predictor. Assessment using genomic test sets was more equivocal, as many more predictions are made by the parallel pipeline, yet the serial pipeline identifies 22 more of the 74 proteins of known location.