A Linked Open Data-Based Terminology to Describe Libre/Free and Open-source Software: Incremental Development Study.

BACKGROUND: There is a variety of libre/free and open-source software (LIFOSS) products for medicine and health care. To support health care and IT professionals select an appropriate software product for given tasks, several comparison studies and web platforms, such as Medfloss.org, are available. However, due to the lack of a uniform terminology for health informatics, ambiguous or imprecise terms are used to describe the functionalities of LIFOSS. This makes comparisons of LIFOSS difficult and may lead to inappropriate software selection decisions. Using Linked Open Data (LOD) promises to address these challenges. OBJECTIVE: We describe LIFOSS systematically with the help of the underlying Health Information Technology Ontology (HITO). We publish HITO and HITO-based software product descriptions using LOD to obtain the following benefits: (1) linking and reusing existing terminologies and (2) using Semantic Web tools for viewing and querying the LIFOSS data on the World Wide Web. METHODS: HITO was incrementally developed and implemented. First, classes for the description of software products in health IT evaluation studies were identified. Second, requirements for describing LIFOSS were elicited by interviewing domain experts. Third, to describe domain-specific functionalities of software products, existing catalogues of features and enterprise functions were analyzed and integrated into the HITO knowledge base. As a proof of concept, HITO was used to describe 25 LIFOSS products. RESULTS: HITO provides a defined set of classes and their relationships to describe LIFOSS in medicine and health care. With the help of linked or integrated catalogues for languages, programming languages, licenses, features, and enterprise functions, the functionalities of LIFOSS can be precisely described and compared. We publish HITO and the LIFOSS descriptions as LOD; they can be queried and viewed using different Semantic Web tools, such as Resource Description Framework (RDF) browsers, SPARQL Protocol and RDF Query Language (SPARQL) queries, and faceted searches. The advantages of providing HITO as LOD are demonstrated by practical examples. CONCLUSIONS: HITO is a building block to achieving unambiguous communication among health IT professionals and researchers. Providing LIFOSS product information as LOD enables barrier-free and easy access to data that are often hidden in user manuals of software products or are not available at all. Efforts to establish a unique terminology of medical and health informatics should be further supported and continued.

Use of some cost-effective technologies for a routine clinical pathology laboratory.

Classically, the need for highly sophisticated instruments with important economic costs has been a major limiting factor for clinical pathology laboratories, especially in developing countries. With the aim of making clinical pathology more accessible, a wide variety of free or economical technologies have been developed worldwide in the last few years. 3D printing and Arduino approaches can provide up to 94% economical savings in hardware and instrumentation in comparison to commercial alternatives. The vast selection of point-of-care-tests (POCT) currently available also limits the need for specific instruments or personnel, as they can be used almost anywhere and by anyone. Lastly, there are dozens of free and libre digital tools available in health informatics. This review provides an overview of the state-of-the-art on cost-effective alternatives with applications in routine clinical pathology laboratories. In this context, a variety of technologies including 3D printing and Arduino, lateral flow assays, plasmonic biosensors, and microfluidics, as well as laboratory information systems, are discussed. This review aims to serve as an introduction to different technologies that can make clinical pathology more accessible and, therefore, contribute to achieve universal health coverage.

Towards Precise Descriptions of Medical Free/Libre and Open Source Software.

The web portal Medfloss.org lists over 360 medical free/libre and open source software (MEDFLOSS) projects. These projects are described with the help of a self-developed nomenclature. Due to inconsistencies, the nomenclature shall be replaced by HITO, the Health IT Ontology. HITO is developed iteratively based on different use cases. This paper aims to describe methods and results of the second HITO use case in which HITO is extended to improve the description, retrieval and comparisons of MEDFLOSS projects on Medfloss.org. We use a mixed-methods approach to add concepts and relationships to describe MEDFLOSS precisely. The resulting HITO version stresses functional descriptions based on features and supported enterprise functions, rather than just describing technical characteristics. However, describing a larger number of MEDFLOSS projects requires the commitment of the community.

Free/Libre open source software in health care: a review.

OBJECTIVES: To assess the current state of the art and the contribution of Free/Libre Open Source Software in health care (FLOSS-HC). METHODS: The review is based on a narrative review of the scientific literature as well as sources in the context of FLOSS-HC available through the Internet. All relevant available sources have been integrated into the MedFLOSS database and are freely available to the community. RESULTS: The literature review reveals that publications about FLOSS-HC are scarce. The largest part of information about FLOSS-HC is available on dedicated websites and not in the academic literature. There are currently FLOSS alternatives available for nearly every specialty in health care. Maturity and quality varies considerably and there is little information available on the percentage of systems that are actually used in health care delivery. CONCLUSIONS: The global impact of FLOSS-HC is still very limited and no figures on the penetration and usage of FLOSS-HC are available. However, there has been a considerable growth in the last 5 to 10 years. While there where only few systems available a decade ago, in the meantime many systems got available (e.g., more than 300 in the MedFLOSS database). While FLOSS concepts play an important role in most IT related sectors (e.g., telecommunications, embedded devices) the healthcare industry is lagging behind this trend.

Open source and healthcare in Europe - time to put leading edge ideas into practice.

Free/Libre and Open Source Software (FLOSS) is a process of software development, a method of licensing and a philosophy. Although FLOSS plays a significant role in several market areas, the impact in the health care arena is still limited. FLOSS is promoted as one of the most effective means for overcoming fragmentation in the health care sector and providing a basis for more efficient, timely and cost effective health care provision. The 2008 European Federation for Medical Informatics (EFMI) Special Topic Conference (STC) explored a range of current and future issues related to FLOSS in healthcare (FLOSS-HC). In particular, there was a focus on health records, ubiquitous computing, knowledge sharing, and current and future applications. Discussions resulted in a list of main barriers and challenges for use of FLOSS-HC. Based on the outputs of this event, the 2004 Open Steps events and subsequent workshops at OSEHC2009 and Med-e-Tel 2009, a four-step strategy has been proposed for FLOSS-HC: 1) a FLOSS-HC inventory; 2) a FLOSS-HC collaboration platform, use case database and knowledge base; 3) a worldwide FLOSS-HC network; and 4) FLOSS-HC dissemination activities. The workshop will further refine this strategy and elaborate avenues for FLOSS-HC from scientific, business and end-user perspectives. To gain acceptance by different stakeholders in the health care industry, different activities have to be conducted in collaboration. The workshop will focus on the scientific challenges in developing methodologies and criteria to support FLOSS-HC in becoming a viable alternative to commercial and proprietary software development and deployment.

AGnES: supporting general practitioners with qualified medical practice personnel: model project evaluation regarding quality and acceptance.

BACKGROUND: The German AGnES (community-based, e-health-assisted systemic support for primary care) project allows general practitioners (GPs) to delegate certain elements of medical care, including house calls, to qualified AGnES employees and thereby provide primary care to a larger number of patients. AGnES projects of various types have been carried out in a number of German federal states from 2005 onward. In this article, an evaluation of the AGnES projects to date is presented. METHODS: Patient data (age, sex, diagnoses, level of care, mobility, etc.) and each of the specific activities carried out in the AGnES framework were documented with standardized computer-based instruments. The GPs, AGnES employees, and patients also underwent standardized interviews. The acceptance of the AGnES project, competence of the AGnES employees, and quality of medical care within the projects were evaluated. The participating GPs themselves assessed the quality of medical care. RESULTS: By July 8, 2008, 8386 house calls on a total of 1486 patients had been made within the framework of the AGnES projects. The evaluation revealed a high degree of acceptance of the project among the participating GPs, AGnES employees, and patients. The GPs considered the quality of medical care within the AGnES project to be good for the vast majority of patients. CONCLUSION: Structural redundancy is avoided by directly placing the AGnES employees in the general practitioners' practices. Based on the results of the AGnES projects, the law in Germany has now been amended to enable implementation of the AGnES project in the regular health care system from January 2009 onward. The next steps to be taken are the establishment of adequate reimbursement within the catalog of the statutory health insurance scheme and a detailed definition of the required qualifications.

Deep brain stimulation in a rat model modulates TH, CaMKIIa and Homer1 gene expression.

High-frequency stimulation (HFS) of subthalamic nucleus (STN) is a therapy for late-stage Parkinson's disease. Its mechanisms of action are not yet fully understood. In the present study, gene expression analyses were performed in a rat model of Parkinson's disease, i.e. striatal 6-hydroxydopamine (6-OHDA) lesion. Using microarrays, gene expression was analysed in 1-mm-thick sagittal brain slices, including basal ganglia of five groups of male Wistar rats. These were unmanipulated rats (group A), unlesioned rats with implanted electrode but without stimulation (group B), unlesioned, stimulated rats (group C), 6-OHDA-lesioned rats with implanted electrode but without stimulation (group D), and finally 6-OHDA-lesioned and stimulated rats (group E). A statistically significant downregulation of tyrosine hydroxylase (TH) mRNA expression induced by 6-OHDA lesion and an HFS-induced TH upregulation in 6-OHDA-lesioned rats could be detected. It could be hypothesized that the HFS-induced upregulation of TH is the result of neuronal STN modulation and mediated via projections from STN to substantia nigra pars compacta. Furthermore, a downregulation of calcium/calmodulin-dependent protein kinase type IIA and Homer1 was observed. This downregulation could result in a reduced sensitivity towards glutamate in basal ganglia downstream of STN.

Inhibitory effects of interferon-gamma on activation of rat pancreatic stellate cells are mediated by STAT1 and involve down-regulation of CTGF expression.

Pancreatic stellate cells (PSCs) are the main source of extracellular matrix proteins in pancreatic fibrosis, a pathological feature of chronic pancreatitis and pancreatic cancer. Interferon-gamma (IFN-gamma) is an antifibrotic cytokine, but how precisely it exerts its effects on PSCs is largely unknown. Here, we have focussed on the role of STAT1 as well as target genes of IFN-gamma signalling. Our data indicate that IFN-gamma regulates the expression of two autocrine mediators of PSC activation, connective tissue growth factor and endothelin-1, in a transforming growth factor-beta1-antagonistic manner. STAT1 overexpression under the control of a tetracycline-dependent promoter revealed a close correlation between STAT1 expression and activation, the biological effects of IFN-gamma (growth inhibition, induction of apoptosis), and target gene expression. Our data further support the hypothesis that IFN-gamma interferes with stellate cell activation in the pancreas and suggest activated STAT1 as an inductor of a quiescent PSC phenotype.

3-Hydroxy-3-methylglutaryl coenzyme A reductase inhibitor Atorvastatin mediated effects depend on the activation status of target cells in PLP-EAE.

The effect of Atorvastatin on transcriptional activity in murine experimental autoimmune encephalomyelitis (EAE) induced by PLP peptide 139-151 was analyzed by DNA microarray technique in lymph nodes and spinal cord at onset (10 days), height (20 days) and first remission (30 days) of disease. Fourteen genes were selectively influenced by Atorvastatin in EAE mice. They are mainly related to immune cell functions and regulation of cell-to-cell interaction. Interestingly, seven genes were also differentially regulated in CFA-injected control mice. But qualitative and quantitative differences to EAE mice argue for a dependency of statin effects on the activation status of target cells. Differential regulation of the newly detected candidate genes of statin effects COX-1 and HSP-105 and the previously known statin-responsive genes ICAM-1 and CD86 was confirmed by Western blot and immunohistochemistry. Flow cytometric analysis of lymph node cells revealed that the effect of Atorvastatin treatment in non-immunized healthy animals resembled the effect of immunization with PLP peptide regarding changes of T helper cells, activated B cells and macrophages. In EAE mice, these effects were partially reversed by Atorvastatin treatment. Monitoring of expression of the newly identified candidate genes and patterns of lymphocyte subpopulations might predict the responsiveness of multiple sclerosis patients to statin treatment.

The Autoimmune Disease Database: a dynamically compiled literature-derived database.

BACKGROUND: Autoimmune diseases are disorders caused by an immune response directed against the body's own organs, tissues and cells. In practice more than 80 clinically distinct diseases, among them systemic lupus erythematosus and rheumatoid arthritis, are classified as autoimmune diseases. Although their etiology is unclear these diseases share certain similarities at the molecular level i.e. susceptibility regions on the chromosomes or the involvement of common genes. To gain an overview of these related diseases it is not feasible to do a literary review but it requires methods of automated analyses of the more than 500,000 Medline documents related to autoimmune disorders. RESULTS: In this paper we present the first version of the Autoimmune Disease Database which to our knowledge is the first comprehensive literature-based database covering all known or suspected autoimmune diseases. This dynamically compiled database allows researchers to link autoimmune diseases to the candidate genes or proteins through the use of named entity recognition which identifies genes/proteins in the corresponding Medline abstracts. The Autoimmune Disease Database covers 103 autoimmune disease concepts. This list was expanded to include synonyms and spelling variants yielding a list of over 1,200 disease names. The current version of the database provides links to 541,690 abstracts and over 5,000 unique genes/proteins. CONCLUSION: The Autoimmune Disease Database provides the researcher with a tool to navigate potential gene-disease relationships in Medline abstracts in the context of autoimmune diseases.

Peroxisome proliferator-activated receptor gamma overexpression inhibits pro-fibrogenic activities of immortalised rat pancreatic stellate cells.

Pancreatic stellate cells (PSCs) play a key role in the development of pancreatic fibrosis, a constant feature of chronic pancreatitis and pancreatic cancer. In response to pro-fibrogenic mediators, PSCs undergo an activation process that involves proliferation, enhanced production of extracellular matrix proteins and a phenotypic transition towards myofibroblasts. Ligands of the peroxisome proliferator-activated receptor gamma (PPARgamma), such as thiazolidinediones, are potent inhibitors of stellate cell activation and fibrogenesis in pancreas and liver. The effects of PPARgamma ligands, however, are at least in part mediated through PPARgamma-independent pathways. Here, we have chosen a different approach to study regulatory functions of PPARgamma in PSCs. Using immortalised rat PSCs, we have established a model of tetracycline (tet)-regulated PPARgamma overexpression. Induction of PPARgamma expression strongly inhibited proliferation and enhanced the rate of apoptotic cell death. Furthermore, PPARgamma-overexpressing cells synthesised less collagen than controls. To monitor effects of PPARgamma on PSC gene expression, we employed Affymetrix microarray technology. Using stringent selection criteria, we identified 21 up- and 19 down-regulated genes in PPARgamma-overexpressing cells. Most of the corresponding gene products are either involved in lipid metabolism, play a role in signal transduction, or are secreted molecules that regulate cell growth and differentiation. In conclusion, our data suggest an active role of PPARgamma in the induction of a quiescent PSC phenotype. PPARgamma-regulated genes in PSCs may serve as novel targets for the development of antifibrotic therapies.

Representation of individual gene expression in completely pooled mRNA samples.

Designing microarray experiments, scientists are often confronted with the question of pooling due to financial constraints, but discussion of the validity of pooling tends toward a sub-pooling recommendation. Since complete pooling protocols can be considered part of sub-pooling designs, gene expression data from three complete pooling experiments were analyzed. Data from complete pooled versus individual mRNA samples of rat brain tissue were compared to answer the question whether the pooled sample represents individual samples in small-sized experiments. Our analytic approach provided clear results concerning the Affymetrix MAS 5.0 signal and detection call parameters. Despite a strong similarity of arrays within experimental groups, the individual signals were evidently not appropriately represented in the pooled sample, with slightly more than half of all the genes considered. Our analysis reveals problems in cases of small complete pooling designs with less than six subjects pooled.

Automatic construction of gene relation networks using text mining and gene expression data.

Microarray gene expression analysis is a powerful high-throughput technique that enables researchers to monitor the expression of thousands of genes simultaneously. Using this methodology huge amounts of data are produced which have to be analysed. Clustering algorithms are used to group genes together based on a predefined distance measure. However, clustering algorithms do not necessarily group the genes in a biological meaningful way. Additional information is needed to improve the identification of disease relevant genes. The primary objective of our project is to support the analysis of microarray gene expression data by construction of gene relation networks (GRNs). Required information can not be found in a structured representation like a database. In contrast, a large number of relations are described in biomedical literature. The main outcome of this project is the implementation of a software system that provides clinicians and researchers with a tool that supports the analysis of microarray gene expression data by mapping known relationships from the biomedical literature to local gene expression experiments.