Institution
Radboud University Nijmegen
Education•Nijmegen, 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 published on a yearly basis
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University of Washington1, California Institute of Technology2, Stockholm University3, University of Maryland, College Park4, Humboldt University of Berlin5, Goddard Space Flight Center6, National Central University7, Weizmann Institute of Science8, Macau University of Science and Technology9, Tel Aviv University10, University of California, Santa Barbara11, University of Michigan12, Northwestern University13, Adler Planetarium14, University of California, Berkeley15, Lawrence Berkeley National Laboratory16, Soka University of America17, Centre national de la recherche scientifique18, Radboud University Nijmegen19, University of Wisconsin–Milwaukee20, Los Alamos National Laboratory21
TL;DR: The Zwicky Transient Facility (ZTF) as mentioned in this paper is a new optical time-domain survey that uses the Palomar 48 inch Schmidt telescope, which provides a 47 deg^2 field of view and 8 s readout time, yielding more than an order of magnitude improvement in survey speed relative to its predecessor survey.
Abstract: The Zwicky Transient Facility (ZTF) is a new optical time-domain survey that uses the Palomar 48 inch Schmidt telescope. A custom-built wide-field camera provides a 47 deg^2 field of view and 8 s readout time, yielding more than an order of magnitude improvement in survey speed relative to its predecessor survey, the Palomar Transient Factory. We describe the design and implementation of the camera and observing system. The ZTF data system at the Infrared Processing and Analysis Center provides near-real-time reduction to identify moving and varying objects. We outline the analysis pipelines, data products, and associated archive. Finally, we present on-sky performance analysis and first scientific results from commissioning and the early survey. ZTF's public alert stream will serve as a useful precursor for that of the Large Synoptic Survey Telescope.
1,009 citations
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TL;DR: Genome sequencing can be applied as a single genetic test to reliably identify and characterize the comprehensive spectrum of genetic variation, providing a genetic diagnosis in the majority of patients with severe ID.
Abstract: Severe intellectual disability (ID) occurs in 0.5% of newborns and is thought to be largely genetic in origin. The extensive genetic heterogeneity of this disorder requires a genome-wide detection of all types of genetic variation. Microarray studies and, more recently, exome sequencing have demonstrated the importance of de novo copy number variations (CNVs) and single-nucleotide variations (SNVs) in ID, but the majority of cases remain undiagnosed. Here we applied whole-genome sequencing to 50 patients with severe ID and their unaffected parents. All patients included had not received a molecular diagnosis after extensive genetic prescreening, including microarray-based CNV studies and exome sequencing. Notwithstanding this prescreening, 84 de novo SNVs affecting the coding region were identified, which showed a statistically significant enrichment of loss-of-function mutations as well as an enrichment for genes previously implicated in ID-related disorders. In addition, we identified eight de novo CNVs, including single-exon and intra-exonic deletions, as well as interchromosomal duplications. These CNVs affected known ID genes more frequently than expected. On the basis of diagnostic interpretation of all de novo variants, a conclusive genetic diagnosis was reached in 20 patients. Together with one compound heterozygous CNV causing disease in a recessive mode, this results in a diagnostic yield of 42% in this extensively studied cohort, and 62% as a cumulative estimate in an unselected cohort. These results suggest that de novo SNVs and CNVs affecting the coding region are a major cause of severe ID. Genome sequencing can be applied as a single genetic test to reliably identify and characterize the comprehensive spectrum of genetic variation, providing a genetic diagnosis in the majority of patients with severe ID.
1,002 citations
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01 Jan 2010TL;DR: In this paper, the identification and quantification of moderating effects in complex causal structures by means of Partial Least Squares Path Modeling is discussed. But the authors do not consider the effect of group comparisons.
Abstract: Along with the development of scientific disciplines, namely social sciences, hypothesized relationships become increasingly more complex. Besides the examination of direct effects, researchers are more and more interested in moderating effects. Moderating effects are evoked by variables whose variation influences the strength or the direction of a relationship between an exogenous and an endogenous variable. Investigators using partial least squares path modeling need appropriate means to test their models for such moderating effects. We illustrate the identification and quantification of moderating effects in complex causal structures by means of Partial Least Squares Path Modeling. We also show that group comparisons, i.e. comparisons of model estimates for different groups of observations, represent a special case of moderating effects by having the grouping variable as a categorical moderator variable. We provide profound answers to typical questions related to testing moderating effects within PLS path models:
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How can a moderating effect be drawn in a PLS path model, taking into account that the available software only permits direct effects?
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How does the type of measurement model of the independent and the moderator variables influence the detection of moderating effects?
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Before the model estimation, should the data be prepared in a particular manner? Should the indicators be centered (by having a mean of zero), standardized (by having a mean of zero and a standard deviation of one), or manipulated in any other way?
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How can the coefficients of moderating effects be estimated and interpreted?And, finally:
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How can the significance of moderating effects be determined?
Borrowing from the body of knowledge on modeling interaction effect within multiple regression, we develop a guideline on how to test moderating effects in PLS path models. In particular, we create a graphical representation of the necessary steps to take and decisions to make in the form of a flow chart. Starting with the analysis of the type of data available, via the measurement model specification, the flow chart leads the researcher through the decisions on how to prepare the data and how to model the moderating effect. The flow chart ends with the bootstrapping, as the preferred means to test significance, and the final interpretation of the model outcomes.
1,002 citations
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TL;DR: Pivotal for the clinical development of new sepsis therapies is the selection of patients on the basis of biomarkers and/or functional defects that provide specific insights into the expression or activity of the therapeutic target.
Abstract: Sepsis is defined as a life-threatening organ dysfunction that is caused by a dysregulated host response to infection. In sepsis, the immune response that is initiated by an invading pathogen fails to return to homeostasis, thus culminating in a pathological syndrome that is characterized by sustained excessive inflammation and immune suppression. Our understanding of the key mechanisms involved in the pathogenesis of sepsis has increased tremendously, yet this still needs to be translated into novel targeted therapeutic strategies. Pivotal for the clinical development of new sepsis therapies is the selection of patients on the basis of biomarkers and/or functional defects that provide specific insights into the expression or activity of the therapeutic target.
996 citations
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TL;DR: An extensive and comprehensive overview of Mg(2+) research over the last few decades is provided, focusing on the regulation of M g(2+) homeostasis in the intestine, kidney, and bone and disturbances which may result in hypomagnesemia.
Abstract: Magnesium (Mg(2+)) is an essential ion to the human body, playing an instrumental role in supporting and sustaining health and life. As the second most abundant intracellular cation after potassium, it is involved in over 600 enzymatic reactions including energy metabolism and protein synthesis. Although Mg(2+) availability has been proven to be disturbed during several clinical situations, serum Mg(2+) values are not generally determined in patients. This review aims to provide an overview of the function of Mg(2+) in human health and disease. In short, Mg(2+) plays an important physiological role particularly in the brain, heart, and skeletal muscles. Moreover, Mg(2+) supplementation has been shown to be beneficial in treatment of, among others, preeclampsia, migraine, depression, coronary artery disease, and asthma. Over the last decade, several hereditary forms of hypomagnesemia have been deciphered, including mutations in transient receptor potential melastatin type 6 (TRPM6), claudin 16, and cyclin M2 (CNNM2). Recently, mutations in Mg(2+) transporter 1 (MagT1) were linked to T-cell deficiency underlining the important role of Mg(2+) in cell viability. Moreover, hypomagnesemia can be the consequence of the use of certain types of drugs, such as diuretics, epidermal growth factor receptor inhibitors, calcineurin inhibitors, and proton pump inhibitors. This review provides an extensive and comprehensive overview of Mg(2+) research over the last few decades, focusing on the regulation of Mg(2+) homeostasis in the intestine, kidney, and bone and disturbances which may result in hypomagnesemia.
996 citations
Authors
Showing all 35749 results
Name | H-index | Papers | Citations |
---|---|---|---|
Charles A. Dinarello | 190 | 1058 | 139668 |
Richard H. Friend | 169 | 1182 | 140032 |
Yang Gao | 168 | 2047 | 146301 |
Ian J. Deary | 166 | 1795 | 114161 |
David T. Felson | 153 | 861 | 133514 |
Margaret A. Pericak-Vance | 149 | 826 | 118672 |
Fernando Rivadeneira | 146 | 628 | 86582 |
Shah Ebrahim | 146 | 733 | 96807 |
Mihai G. Netea | 142 | 1170 | 86908 |
Mingshui Chen | 141 | 1543 | 125369 |
George Alverson | 140 | 1653 | 105074 |
Barry Blumenfeld | 140 | 1909 | 105694 |
Harvey B Newman | 139 | 1594 | 88308 |
Tariq Aziz | 138 | 1646 | 96586 |
Stylianos E. Antonarakis | 138 | 746 | 93605 |