Evaluation of computational methods for the reconstruction of HLA haplotypes

Human leukocyte antigen (HLA) haplotypes are frequently evaluated for population history inferences and association studies. However, the available typing techniques for the main HLA loci usually do not allow the determination of the allele phase and the constitution of a haplotype, which may be obtained by a very time-consuming and expensive family-based segregation study. Without the family-based study, computational inference by probabilistic models is necessary to obtain haplotypes. Several authors have used the expectation-maximization (EM) algorithm to determine HLA haplotypes, but high levels of erroneous inferences are expected because of the genetic distance among the main HLA loci and the presence of several recombination hotspots. In order to evaluate the efficiency of computational inference methods, 763 unrelated individuals stratified into three different datasets had their haplotypes manually defined in a family-based study of HLA-A, -B, -DRB1 and -DQB1 segregation, and these haplotypes were compared with the data obtained by the following three methods: the Expectation-Maximization (EM) and Excoffier-Laval-Balding (ELB) algorithms using the arlequin 3.11 software, and the PHASE method. When comparing the methods, we observed that all algorithms showed a poor performance for haplotype reconstruction with distant loci, estimating incorrect haplotypes for 38%-57% of the samples considering all algorithms and datasets. We suggest that computational haplotype inferences involving low-resolution HLA-A, HLA-B, HLA-DRB1 and HLA-DQB1 haplotypes should be considered with caution.

Behavioral Types for Embedded Software - A Survey

At present, there is a variety of formalisms for modeling and analyzing the communication behavior of components. Due to a tremendous increase in size and complexity of embedded systems accompanied by shorter time to market cycles and cost reduction, so called behavioral type systems become more and more important. This chapter presents an overview and a taxonomy of behavioral types. The intentions of this taxonomy are to provide a guidance for software engineers and to form the basis for future research.

Specification and Evaluation of Safety Properties in a Component-Based Software Engineering Process

Over the past years, component-based software engineering has become an established paradigm in the area of complex software intensive systems. However, many techniques for analyzing these systems for critical properties currently do not make use of the component orientation. In particular, safety analysis of component-based systems is an open field of research. In this chapter we investigate the problems arising and define a set of requirements that apply when adapting the analysis of safety properties to a component-based software engineering process. Based on these requirements some important component-oriented safety evaluation approaches are examined and compared.

Effect of image analysis software on neurofunctional activation during processing of emotional human faces

Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.

Reference distribution of the bioelectrical impedance vector in healthy term newborns

Bioelectrical impedance vector analysis (BIVA) is a new method that is used for the routine monitoring of the variation in body fluids and nutritional status with assumptions regarding body composition values. The aim of the present study was to determine bivariate tolerance intervals of the whole-body impedance vector and to describe phase angle (PA) values for healthy term newborns aged 7-28 d. This descriptive cross-sectional study was conducted on healthy term neonates born at a low-risk public maternity. General and anthropometric neonatal data and bioelectrical impedance data (800 mu A-50 kHz) were obtained. Bivariate vector analysis was conducted with the resistance-reactance (RXc) graph method. The BIVA software was used to construct the graphs. The study was conducted on 109 neonates (52.3% females) who were born at term, adequate for gestational age, exclusively breast-fed and aged 13 (SD 3.6) d. We constructed one standard, reference, RXc-score graph and RXc-tolerance ellipses (50, 75 and 95 %) that can be used with any analyser. Mean PA was 3.14 (SD 0.43)degrees (3.12 (SD 0.39)degrees for males and 3.17 (SD 0.48)degrees for females). Considering the overlapping of ellipses of males and females with the general distribution, a graph for newborns aged 7-28 d with the same reference tolerance ellipse was defined for boys and girls. The results differ from those reported in the literature probably, in part, due to the ethnic differences in body composition. BIVA and PA permit an assessment without the need to know body weight and the prediction error of conventional impedance formulas.

MDA-based re-engineering with Object-Z

This paper describes a practical application of MDA and reverse engineering based on a domain-specific modelling language. A well defined metamodel of a domain-specific language is useful for verification and validation of associated tools. We apply this approach to SIFA, a security analysis tool. SIFA has evolved as requirements have changed, and it has no metamodel. Hence, testing SIFA’s correctness is difficult. We introduce a formal metamodelling approach to develop a well-defined metamodel of the domain. Initially, we develop a domain model in EMF by reverse engineering the SIFA implementation. Then we transform EMF to Object-Z using model transformation. Finally, we complete the Object-Z model by specifying system behavior. The outcome is a well-defined metamodel that precisely describes the domain and the security properties that it analyses. It also provides a reliable basis for testing the current SIFA implementation and forward engineering its successor.

Effect of PTK/ZK on the Angiogenic Switch in Head and Neck Tumors

Transformation of small avascular masses of tumor cells into rapidly progressive cancers is triggered by the angiogenic switch, a process that involves vascular endothelial growth factor (VEGF) signaling. We have shown that VEGF enhances the survival and angiogenic potential of endothelial cells by activating the Bcl-2-CXCL8 signaling axis. The purpose of this study was to evaluate the effect of a small-molecule inhibitor of VEGF receptors (PTK/ZK) on the initial stages of head and neck tumor angiogenesis. In vitro, PTK/ZK blocked head and neck tumor cell (OSCC3 or UM-SCC-17B)-induced Bcl-2 and CXCL8 expression in endothelial cells. Oral administration of PTK/ZK decreased xenograft head and neck tumor microvessel density, and inhibited Bcl-2 and CXCL8 expression in tumor-associated endothelial cells. Analysis of these data demonstrates that PTK/ZK blocks downstream targets of VEGF signaling in endothelial cells, and suggests that PTK/ZK may inhibit the angiogenic switch in head and neck tumors. Abbreviations: HDMEC, human dermal microvascular endothelial cells; VEGF, vascular endothelial growth factor; CXCL8, CXC ligand-8; PTK/ZK, PTK787/ZK222584.

Peripheral T-Cell tolerance defined through transgenic mouse studies

Selection in the thymus restricted by MHC and self-peptide shapes the diverse reactivities of the T-cell population which subsequently seeds into the peripheral tissues, in anticipation of the universe of pathogen antigens to which the organism may be exposed. A necessary corollary is the potential for T-cell self-reactivity (autoimmunity) in the periphery. Transgenic mouse models in which transgene expression in the thymus is prevented or excluded, have been particularly useful for determining the immunological outcome when T-cells encounter transgene-encoded 'self' antigen in peripheral tissues. Data suggest that non-mutually exclusive mechanisms of T-cells 'ignoring' self-antigen, T-cell deletion, T-cell anergy and T-cell immunoregulation have evolved to prevent self-reactivity while maintaining T-cell diversity. The peripheral T-cell repertoire, far from being static following maturation through the thymus, is in a dynamic stated determined by these peripheral selective and immunoregulatory influences. This article reviews the evidence with particular reference to CD8+ive T-cells.

Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.