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Institution

University of Amsterdam

EducationAmsterdam, Noord-Holland, Netherlands
About: University of Amsterdam is a education organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 59309 authors who have published 140894 publications receiving 5984137 citations. The organization is also known as: UvA & Universiteit van Amsterdam.


Papers
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Journal ArticleDOI
27 Jul 2012-Science
TL;DR: More than 70% of all massive stars will exchange mass with a companion, leading to a binary merger in one-third of the cases, greatly exceed previous estimates and imply that binary interaction dominates the evolution of massive stars, with implications for populations ofmassive stars and their supernovae.
Abstract: The presence of a nearby companion alters the evolution of massive stars in binary systems, leading to phenomena such as stellar mergers, x-ray binaries, and gamma-ray bursts. Unambiguous constraints on the fraction of massive stars affected by binary interaction were lacking. We simultaneously measured all relevant binary characteristics in a sample of Galactic massive O stars and quantified the frequency and nature of binary interactions. More than 70% of all massive stars will exchange mass with a companion, leading to a binary merger in one-third of the cases. These numbers greatly exceed previous estimates and imply that binary interaction dominates the evolution of massive stars, with implications for populations of massive stars and their supernovae.

1,779 citations

Journal ArticleDOI
TL;DR: This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.
Abstract: Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.

1,776 citations

Journal ArticleDOI
07 Mar 2003-Cell
TL;DR: It is found that activation of HIF-1alpha is essential for myeloid cell infiltration and activation in vivo through a mechanism independent of VEGF, and its direct regulation of survival and function in the inflammatory microenvironment is demonstrated.

1,773 citations

Journal ArticleDOI
TL;DR: Widespread adoption and implementation of this tool will facilitate and improve critical appraisal of evidence from animal studies and enhance the efficiency of translatingAnimal research into clinical practice and increase awareness of the necessity of improving the methodological quality of animal studies.
Abstract: Systematic Reviews (SRs) of experimental animal studies are not yet common practice, but awareness of the merits of conducting such SRs is steadily increasing. As animal intervention studies differ from randomized clinical trials (RCT) in many aspects, the methodology for SRs of clinical trials needs to be adapted and optimized for animal intervention studies. The Cochrane Collaboration developed a Risk of Bias (RoB) tool to establish consistency and avoid discrepancies in assessing the methodological quality of RCTs. A similar initiative is warranted in the field of animal experimentation. We provide an RoB tool for animal intervention studies (SYRCLE’s RoB tool). This tool is based on the Cochrane RoB tool and has been adjusted for aspects of bias that play a specific role in animal intervention studies. To enhance transparency and applicability, we formulated signalling questions to facilitate judgment. The resulting RoB tool for animal studies contains 10 entries. These entries are related to selection bias, performance bias, detection bias, attrition bias, reporting bias and other biases. Half these items are in agreement with the items in the Cochrane RoB tool. Most of the variations between the two tools are due to differences in design between RCTs and animal studies. Shortcomings in, or unfamiliarity with, specific aspects of experimental design of animal studies compared to clinical studies also play a role. SYRCLE’s RoB tool is an adapted version of the Cochrane RoB tool. Widespread adoption and implementation of this tool will facilitate and improve critical appraisal of evidence from animal studies. This may subsequently enhance the efficiency of translating animal research into clinical practice and increase awareness of the necessity of improving the methodological quality of animal studies.

1,773 citations

Journal ArticleDOI
TL;DR: In this paper, an empirical analysis of the importance of comparison income for individual well-being or happiness is presented, where the authors use a self-reported measure of satisfaction with life as a measure of individual wellbeing.

1,760 citations


Authors

Showing all 59759 results

NameH-indexPapersCitations
Richard A. Flavell2311328205119
Scott M. Grundy187841231821
Stuart H. Orkin186715112182
Kenneth C. Anderson1781138126072
David A. Weitz1781038114182
Dorret I. Boomsma1761507136353
Brenda W.J.H. Penninx1701139119082
Michael Kramer1671713127224
Nicholas J. White1611352104539
Lex M. Bouter158767103034
Wolfgang Wagner1562342123391
Jerome I. Rotter1561071116296
David Cella1561258106402
David Eisenberg156697112460
Naveed Sattar1551326116368
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023198
2022698
20219,648
20208,534
20197,822
20186,407