19 research outputs found

    Measuring Success for a Future Vision: Defining Impact in Science Gateways/Virtual Research Environments

    Get PDF
    Scholars worldwide leverage science gateways/VREs for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this paper, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of e.g., their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations

    New MR sequences in daily practice: susceptibility weighted imaging. A pictorial essay

    Get PDF
    Background Susceptibility-weighted imaging (SWI) is a relatively new magnetic resonance (MR) technique that exploits the magnetic susceptibility differences of various tissues, such as blood, iron and calcification, as a new source of contrast enhancement. This pictorial review is aimed at illustrating and discussing its main clinical applications. Methods SWI is based on high-resolution, threedimensional (3D), fully velocity-compensated gradientecho sequences using both magnitude and phase images. A phase mask obtained from the MR phase images is multiplied with magnitude images in order to increase the visualisation of the smaller veins and other sources of susceptibility effects, which are displayed at best after postprocessing of the 3D dataset with the minimal intensity projection (minIP) algorithm. Results SWI is very useful in detecting cerebral microbleeds in ageing and occult low-flow vascular malformations, in characterising brain tumours and degenerative diseases of the brain, and in recognizing calcifications in various pathological conditions. The phase images are especially useful in differentiating between paramagnetic susceptibility effects of blood and diamagnetic effects of calcium. SWI can also be used to evaluate changes in iron content in different neurodegenerative disorders. Conclusion SWI is useful in differentiating and characterising diverse brain disorders

    Prevalence of anaemia in older persons: systematic review

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Ageing populations will impact on healthcare provision, especially since extra years are not necessarily spent in good health. It is important to identify and understand the significance of common medical problems in older people. Anaemia may be one such problem. We report on the prevalence of anaemia in cohorts of elderly people in the general population. The presence of anaemia is associated with a worse prognosis for both morbidity and mortality.</p> <p>Methods</p> <p>Electronic searching and reference lists of published reports were used to identify studies that reported on prevalence of anaemia in cohorts of at least 100 individuals predominantly aged 65 years and over living in developed countries, together with criteria used to define anaemia. Studies of anaemia prevalence in specific disease groups or published before 1980 were excluded. Prevalence data for the entire cohort, for men and women separately and for different age bands were extracted.</p> <p>Results</p> <p>Forty-five studies contributed data. Thirty-four studies (n = 85,409) used WHO criteria to define anaemia. The weighted mean prevalence was 17% (3–50%) overall, and 12% (3–25%) in studies based in the community (27, n = 69,975), 47% (31–50%) in nursing homes (3, n = 1481), and 40% (40–72%) in hospital admissions (4, n = 13,953). Anaemia prevalence increased with age, was slightly higher in men than women, and was higher in black people than white. Most individuals classified as anaemic using WHO criteria were only mildly anaemic.</p> <p>Conclusion</p> <p>Anaemia, as defined by WHO criteria, is common in older people living in the community and particularly common in nursing home residents and hospital admissions. Predicted demographic changes underline the need to understand more about anaemia in older people.</p

    Leveraging XSEDE HPC resources to address computational challenges with high-resolution topography data

    No full text
    Leveraging service-oriented architectures and taking advantage of the high-performance compute resources provided by XSEDE, we have developed standards-based web services to address the challenges associated with processing large volumes of high resolution topography data. These web services make results from community software packages and other cyberinfrastructure-based applications available to the wider earth sciences community via the OpenTopography Facility and the CyberGIS Gateway

    Lessons Learned with Laser Scanning Point Cloud Management in Hadoop HBase

    Get PDF
    While big data technologies are growing rapidly and benefit a wide range of science and engineering domains, many barriers remain for the remote sensing community to fully exploit the benefits provided by these emerging powerful technologies. To overcome these barriers, this paper presents the in-depth experience gained when adopting a distributed computing framework – Hadoop HBase – for storage, indexing, and integration of large scale, high resolution laser scanning point cloud data. Four data models were conceptualized, implemented, and rigorously investigated to explore the advantageous features of distributed, key-value database systems. In addition, the comparison of the four models facilitated the reassessment of several well-known point cloud management techniques founded in traditional computing environments in the new context of the distributed, key-value database. The four models were derived from two row-key designs and two columns structures, thereby demonstrating various considerations during the development of a data solution for high-resolution, city-scale aerial laser scan for a portion of Dublin, Ireland. This paper presents lessons learned from the data model design and its implementation for spatial data management in a distributed computing framework. The study is a step towards full exploitation of powerful emerging computing assets for dense spatio-temporal data.The Hadoop cluster used for the work presented in this paper was provided by allocation TG-CIE170036 - Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-154856

    Anemia in the critically ill patient

    No full text
    Anemia occurs frequently in critically ill patients. In many cases, the underlying cause(s) are easy to detect, but sometimes the diagnosis is challenging for intensivist not particularly expert in hematology. The main causes of anemia in ICU patients are described, particularly focusing on diseases not commonly encountered in this setting and thus difficult to identify. \ua9 Springer-Verlag Italia 2015

    Cheminformatics Meets Molecular Mechanics: A Combined Application of Knowledge-Based Pose Scoring and Physical Force Field-Based Hit Scoring Functions Improves the Accuracy of Structure-Based Virtual Screening

    No full text
    Poor performance of scoring functions is a well-known bottleneck in structure-based virtual screening, which is most frequently manifested in the scoring functions’ inability to discriminate between true ligands versus known non-binders (therefore designated as binding decoys). This deficiency leads to a large number of false positive hits resulting from virtual screening. We have hypothesized that filtering out or penalizing docking poses recognized as non-native (i.e., pose decoys) should improve the performance of virtual screening in terms of improved identification of true binders. Using several concepts from the field of cheminformatics, we have developed a novel approach to identifying pose decoys from an ensemble of poses generated by computational docking procedures. We demonstrate that the use of target-specific pose (-scoring) filter in combination with a physical force field-based scoring function (MedusaScore) leads to significant improvement of hit rates in virtual screening studies for 12 of the 13 benchmark sets from the clustered version of the Database of Useful Decoys (DUD). This new hybrid scoring function outperforms several conventional structure-based scoring functions, including XSCORE∷HMSCORE, ChemScore, PLP, and Chemgauss3, in six out of 13 data sets at early stage of VS (up 1% decoys of the screening database). We compare our hybrid method with several novel VS methods that were recently reported to have good performances on the same DUD data sets. We find that the retrieved ligands using our method are chemically more diverse in comparison with two ligand-based methods (FieldScreen and FLAP∷LBX). We also compare our method with FLAP∷RBLB, a high-performance VS method that also utilizes both the receptor and the cognate ligand structures. Interestingly, we find that the top ligands retrieved using our method are highly complementary to those retrieved using FLAP∷RBLB, hinting effective directions for best VS applications. We suggest that this integrative virtual screening approach combining cheminformatics and molecular mechanics methodologies may be applied to a broad variety of protein targets to improve the outcome of structure-based drug discovery studies
    corecore