A Clinical Decision Support using a Terminology Server to improve Patient Safety.

Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario.

A multidimensional segmentation evaluation for medical image data.

Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

Enterprise Architecture Management Design: Towards Understanding Organizational Contingencies, Design Principles and Effectiveness

Despite the increasing popularity of enterprise architecture management (EAM) in practice, many EAM initiatives either do not fully meet the expected targets or fail. Several frameworks have been suggested as guidelines to EA implementation, but companies seldom follow prescriptive frameworks. Instead, they follow very diverse implementation approaches that depend on their organizational contingencies and the way of adopting and evolving EAM over time. This research strives for a broader understanding of EAM by exploring context-dependent EAM adoption approaches as well as identifying the main EA principles that affect EA effectiveness. Based on two studies, this dissertation aims to address two main questions: (1) EAM design: Which approaches do companies follow when adopting EAM? (2) EA principles and their impact: What impact does EA principles have on EA effectiveness/quality? By utilizing both qualitative and quantitative research methods, this research contributes to exploring different EAM designs in different organizational contingencies as well as using EA principles as an effective means to achieve principle-based EAM design. My research can help companies identify a suitable EAM design that fits their organizational settings and shape their EA through a set of principles.

Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization.

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.

The molecular architecture of the TNF superfamily.

Ligands of the TNF (tumour necrosis factor) superfamily have pivotal roles in the organization and function of the immune system, and are implicated in the aetiology of several acquired and genetic diseases. TNF ligands share a common structural motif, the TNF homology domain (THD), which binds to cysteine-rich domains (CRDs) of TNF receptors. CRDs are composed of structural modules, whose variation in number and type confers heterogeneity upon the family. Protein folds reminiscent of the THD and CRD are also found in other protein families, raising the possibility that the mode of interaction between TNF and TNF receptors might be conserved in other contexts.

Individual systems-oriented psychotherapy: a therapy without family?

Individual systems-oriented psychotherapy: a therapy without family? - Pursuing and deepening the reflections of a task force of the CEF in Lausanne dedicated to individual systems-oriented psychotherapy, the author raises the question of the legitimacy of such a practice for systemic therapists : are systemic thought and clinical practice to be allowed to take an interest in the individual ? The ideological stakes having been better identified, the article can address the methodological and technical issues involved in this type of psychotherapy, and more succinctly, those of training in such a practice.

Genetic and phenotypic architecture of metabolic syndrome-associated components in dyslipidemic and normolipidemic subjects: the GEMS Study.

Atherogenic dyslipidemia, manifest by low HDL-cholesterol and high TG levels, is an important component of ATP-III defined metabolic syndrome. Here, we dissected the phenotypic and genetic architecture of these traits by assessing their relationships with other metabolically relevant measures, including plasma adipo-cytokines, highly sensitive C-reactive protein (hsCRP) and LDL particle size, in a large family data set (n=2800) and in an independent set of dyslipidemic cases (n=716) and normolipidemic controls (n=1073). We explored the relationships among these phenotypes using variable clustering and then estimated their genetic heritabilities and cross-trait correlations. In families, four clusters explained 61% of the total variance, with one adiposity-related cluster (including hsCRP), one BP-related cluster, and two lipid-related clusters (HDL-C, TG, adiponectin and LDL particle size; apoB and non-HDL-C). A similar structure was observed in dyslipidemic cases and normolipidemic controls. The genetic correlations in the families largely paralleled the phenotype clustering results, suggesting that common genes having pleiotropic effects contributed to the correlations observed. In summary, our analyses support a model of metabolic syndrome with two major components, body fat and lipids, each with two subcomponents, and quantifies their degree of overlap with each other and with metabolic-syndrome related measures (adipokines, LDL particle size and hsCRP).