Criteria for implementing interventions to reduce health inequalities in primary care settings in European regions.

BACKGROUND: The current social and political context is generating socio-economic inequalities between and within countries, causing and widening health inequalities. The development and implementation of interventions in primary health care (PHC) settings seem unavoidable. Attempts have been made to draw up adequate criteria to guide and evaluate interventions but none for the specific case of PHC. This methodological article aims to contribute to this field by developing and testing a set of criteria for guiding and evaluating real-life interventions to reduce health inequalities in PHC settings in European regions. METHODS: A literature review, nominal group technique, survey and evaluation template were used to design and test a set of criteria. The questionnaire was answered by professionals in charge of 46 interventions carried out in 12 European countries, and collected detailed information about each intervention. Third-party experts scored the interventions using the set of evaluation criteria proposed. RESULTS: Nine criteria to guide and evaluate interventions were proposed: relevance, appropriateness, applicability, innovation, quality assurance, adequacy of resources, effectiveness in the process, effectiveness in results and mainstreaming. A working definition was drawn up for each one. These criteria were then used to evaluate the interventions identified. CONCLUSIONS: The set of criteria drawn up to guide the design, implementation and evaluation of interventions to reduce health inequalities in PHC will be a useful instrument to be applied to interventions under development for culturally, politically and socio-economically diverse PHC contexts throughout Europe.

Tear fluid proteomics multimarkers for diabetic retinopathy screening.

BACKGROUND: The aim of the project was to develop a novel method for diabetic retinopathy screening based on the examination of tear fluid biomarker changes. In order to evaluate the usability of protein biomarkers for pre-screening purposes several different approaches were used, including machine learning algorithms. METHODS: All persons involved in the study had diabetes. Diabetic retinopathy (DR) was diagnosed by capturing 7-field fundus images, evaluated by two independent ophthalmologists. 165 eyes were examined (from 119 patients), 55 were diagnosed healthy and 110 images showed signs of DR. Tear samples were taken from all eyes and state-of-the-art nano-HPLC coupled ESI-MS/MS mass spectrometry protein identification was performed on all samples. Applicability of protein biomarkers was evaluated by six different optimally parameterized machine learning algorithms: Support Vector Machine, Recursive Partitioning, Random Forest, Naive Bayes, Logistic Regression, K-Nearest Neighbor. RESULTS: Out of the six investigated machine learning algorithms the result of Recursive Partitioning proved to be the most accurate. The performance of the system realizing the above algorithm reached 74% sensitivity and 48% specificity. CONCLUSIONS: Protein biomarkers selected and classified with machine learning algorithms alone are at present not recommended for screening purposes because of low specificity and sensitivity values. This tool can be potentially used to improve the results of image processing methods as a complementary tool in automatic or semiautomatic systems.

Model requirements for Biobank Software Systems.

UNLABELLED: Biobanks are essential tools in diagnostics and therapeutics research and development related to personalized medicine. Several international recommendations, standards and guidelines exist that discuss the legal, ethical, technological, and management requirements of biobanks. Today's biobanks are much more than just collections of biospecimens. They also store a huge amount of data related to biological samples which can be either clinical data or data coming from biochemical experiments. A well-designed biobank software system also provides the possibility of finding associations between stored elements. Modern research biobanks are able to manage multicenter sample collections while fulfilling all requirements of data protection and security. While developing several biobanks and analyzing the data stored in them, our research group recognized the need for a well-organized, easy-to-check requirements guideline that can be used to develop biobank software systems. International best practices along with relevant ICT standards were integrated into a comprehensive guideline: The Model Requirements for the Management of Biological Repositories (BioReq), which covers the full range of activities related to biobank development. The guideline is freely available on the Internet for the research community. AVAILABILITY: The database is available for free at http://bioreq.astridbio.com/bioreq_v2.0.pdf.

Geno viewer, a SAM/BAM viewer tool.

UNLABELLED: The ever evolving Next Generation Sequencing technology is calling for new and innovative ways of data processing and visualization. Following a detailed survey of the current needs of researchers and service providers, the authors have developed GenoViewer: a highly user-friendly, easy-to-operate SAM/BAM viewer and aligner tool. GenoViewer enables fast and efficient NGS assembly browsing, analysis and read mapping. It is highly customized, making it suitable for a wide range of NGS related tasks. Due to its relatively simple architecture, it is easy to add specialised visualization functionalities, facilitating further customised data analysis. The software's source code is freely available; it is open for project and task-specific modifications. AVAILABILITY: The database is available for free at http://www.genoviewer.com/