Re-Infrastructuring for eHealth: Dealing with Turns in Infrastructure Development

In this paper, we examine infrastructuring in the context of developing national, public eHealth services in Norway. Specifically, we analyze the work of a project team engaged in the design and development of new web-based capabilities for communication between citizens and primary healthcare practitioners. We frame the case as a study of re-infrastructuring to signify a particular occasion of infrastructuring that entails facilitating a new logic within established social and technological networks. To make sense of the particularities of re-infrastructuring, we draw from research in infrastructure studies which considers embeddedness as a resource in infrastructure evolution. We analyze how actors worked to re-infrastructure through adapting primary care information systems, information flows and representations of patient data. Our findings show how the work of re-infrastructuring revolves around addressing two key design concerns: a) bringing novelty without being trapped in the existing arrangements or harming what is in place, b) bringing changes that are within a specific direction although they happen through distributed decision taking.     

Genetics and Epigenetics in Asthma

Asthma is one of the most common respiratory disease that affects both children and adults worldwide, with diverse phenotypes and underlying pathogenetic mechanisms poorly understood. As technology in genome sequencing progressed, scientific efforts were made to explain and predict asthma’s complexity and heterogeneity, and genome-wide association studies (GWAS) quickly became the preferred study method. Several gene markers and loci associated with asthma susceptibility, atopic and childhood-onset asthma were identified during the last few decades. Markers near the ORMDL3/GSDMB genes were associated with childhood-onset asthma, interleukin (IL)33 and IL1RL1 SNPs were associated with atopic asthma, and the Thymic Stromal Lymphopoietin (TSLP) gene was identified as protective against the risk to TH2-asthma. The latest efforts and advances in identifying and decoding asthma susceptibility are focused on epigenetics, heritable characteristics that affect gene expression without altering DNA sequence, with DNA methylation being the most described mechanism. Other less studied epigenetic mechanisms include histone modifications and alterations of miR expression. Recent findings suggest that the DNA methylation pattern is tissue and cell-specific. Several studies attempt to describe DNA methylation of different types of cells and tissues of asthmatic patients that regulate airway remodeling, phagocytosis, and other lung functions in asthma. In this review, we attempt to briefly present the latest advancements in the field of genetics and mainly epigenetics concerning asthma susceptibility.     

Metadata management,interoperability and Linked Data publishing support for Natural History Museums

Natural history museums (NHMs) form a rich source of knowledge about Earth’s biodiversity and natural history. However, an impressive abundance of high-quality scientific content available in NHMs around Europe remains largely unexploited due to a number of barriers, such as the lack of interconnection and interoperability between the management systems used by museums, the lack of centralized access through a European point of reference such as Europeana and the inadequacy of the current metadata and content organization. The Natural Europe project offers a coordinated solution at European level that aims to overcome those barriers. In this article, we present the architecture, deployment and evaluation of the Natural Europe infrastructure allowing the curators to publish, semantically describe and manage the museums’ cultural heritage objects, as well as disseminate them to Europeana.eu and BioCASE/GBIF. Additionally, we discuss the methodology followed for the transition of the infrastructure to the Semantic Web and the publishing of NHMs’ cultural heritage metadata as Linked Data, supporting the Europeana Data Model.     

The formulation of optimal mixtures with generalized disjunctive programming: A solvent design case study

Systematic approaches for the design of mixtures, based on a computer‐aided mixture/blend design (CAM^bD) framework, have the potential to deliver better products and processes. In most existing methodologies the number of mixture ingredients is fixed (usually a binary mixture) and the identity of at least one compound is chosen from a given set of candidate molecules. A novel CAM^bD methodology is presented for formulating the general mixture design problem where the number, identity and composition of mixture constituents are optimized simultaneously. To this end, generalized disjunctive programming is integrated into the CAM^bD framework to formulate the discrete choices. This generic methodology is applied to a case study to find an optimal solvent mixture that maximizes the solubility of ibuprofen. The best performance in this case study is obtained with a solvent mixture, showing the benefit of using mixtures instead of pure solvents to attain enhanced behavior. © 2016 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers AIChE J, 62: 1616–1633, 2016     

Could virtual reality applications pose real risks to children and adolescents? A systematic review of ethical issues and concerns

Virtual Reality - Virtual reality technologies (VRTs) are high-tech human–computer interfaces used to develop digital content and can be applied to multiple different areas, often offering...     

Enabling openness of valuable information resources: Curbing data subtractability and exclusion

In this paper we investigate how data openness can be made possible in communal settings. We adopt a utility perspective that foregrounds the use value of data, conceptualizing them as “goods.” On the basis of this conceptualization we explore 2 key goods' attributes: subtractability and exclusion. Our theoretical basis is built upon concepts from the theory of the commons, power theorizing, and notions related to data and information. Empirically, we investigate openness in the genetics domain through a longitudinal study of the evolving communal infrastructure for data related to 2 genes influencing women's susceptibility to breast and ovarian cancer (BRCA1 and BRCA2). We follow the continuously shifting “topology” of the BRCA information infrastructure and trace the multiple repositories that are put in place and the different arrangements for data collection, curation/quality assurance, access, and control that are tried out. In our analysis, we illustrate the actors' strategies for curbing the subtractability and exclusion attributes of data. We then propose a theoretically informed and empirically grounded framework that can guide understanding and action taking to enable data openness.