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Institution

Radboud University Nijmegen

EducationNijmegen, Gelderland, Netherlands
About: Radboud University Nijmegen is a education organization based out in Nijmegen, Gelderland, Netherlands. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 35417 authors who have published 83035 publications receiving 3285064 citations. The organization is also known as: Catholic University of Nijmegen & Radboud University.


Papers
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Journal ArticleDOI
TL;DR: A second genetic variant in the 8q24 region that, in conjunction with another variant recently discovered, accounts for about 11%–13% of prostate cancer cases in individuals of European descent and 31% of cases in African Americans is reported.
Abstract: Prostate cancer is the most prevalent noncutaneous cancer in males in developed regions, with African American men having among the highest worldwide incidence and mortality rates. Here we report a second genetic variant in the 8q24 region that, in conjunction with another variant we recently discovered, accounts for about 11%-13% of prostate cancer cases in individuals of European descent and 31% of cases in African Americans. We made the current discovery through a genome-wide association scan of 1,453 affected Icelandic individuals and 3,064 controls using the Illumina HumanHap300 BeadChip followed by four replication studies. A key step in the discovery was the construction of a 14-SNP haplotype that efficiently tags a relatively uncommon (2%-4%) susceptibility variant in individuals of European descent that happens to be very common (approximately 42%) in African Americans. The newly identified variant shows a stronger association with affected individuals who have an earlier age at diagnosis.

884 citations

Journal ArticleDOI
16 Nov 2001-Cell
TL;DR: Using a cell-free RNA decay system, it is demonstrated that the mammalian exosome is required for rapid degradation of ARE-containing RNAs but not for poly(A) shortening.

884 citations

Journal ArticleDOI
Jens Kattge1, Gerhard Bönisch2, Sandra Díaz3, Sandra Lavorel  +751 moreInstitutions (314)
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

882 citations

Journal ArticleDOI
04 Feb 2014-PLOS ONE
TL;DR: There is strong evidence for PT interventions favoring intensive high repetitive task-oriented and task-specific training in all phases poststroke, and suggestions for prioritizing PT stroke research are given.
Abstract: Background Physical therapy (PT) is one of the key disciplines in interdisciplinary stroke rehabilitation. The aim of this systematic review was to provide an update of the evidence for stroke rehabilitation interventions in the domain of PT.

882 citations

Journal ArticleDOI
TL;DR: A minimum set of common outcome measures for studies of COVID-19, which includes a measure of viral burden, patient survival, and patient progression through the health-care system by use of the WHO Clinical Progression Scale are urged.
Abstract: Summary Clinical research is necessary for an effective response to an emerging infectious disease outbreak. However, research efforts are often hastily organised and done using various research tools, with the result that pooling data across studies is challenging. In response to the needs of the rapidly evolving COVID-19 outbreak, the Clinical Characterisation and Management Working Group of the WHO Research and Development Blueprint programme, the International Forum for Acute Care Trialists, and the International Severe Acute Respiratory and Emerging Infections Consortium have developed a minimum set of common outcome measures for studies of COVID-19. This set includes three elements: a measure of viral burden (quantitative PCR or cycle threshold), a measure of patient survival (mortality at hospital discharge or at 60 days), and a measure of patient progression through the health-care system by use of the WHO Clinical Progression Scale, which reflects patient trajectory and resource use over the course of clinical illness. We urge investigators to include these key data elements in ongoing and future studies to expedite the pooling of data during this immediate threat, and to hone a tool for future needs.

882 citations


Authors

Showing all 35749 results

NameH-indexPapersCitations
Charles A. Dinarello1901058139668
Richard H. Friend1691182140032
Yang Gao1682047146301
Ian J. Deary1661795114161
David T. Felson153861133514
Margaret A. Pericak-Vance149826118672
Fernando Rivadeneira14662886582
Shah Ebrahim14673396807
Mihai G. Netea142117086908
Mingshui Chen1411543125369
George Alverson1401653105074
Barry Blumenfeld1401909105694
Harvey B Newman139159488308
Tariq Aziz138164696586
Stylianos E. Antonarakis13874693605
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023123
2022492
20216,380
20206,080
20195,747
20185,114