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Institution

University of Copenhagen

EducationCopenhagen, Denmark
About: University of Copenhagen is a education organization based out in Copenhagen, Denmark. It is known for research contribution in the topics: Population & Medicine. The organization has 57645 authors who have published 149740 publications receiving 5903093 citations. The organization is also known as: Copenhagen University & Københavns Universitet.


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Journal ArticleDOI
Benjamin F. Voight1, Benjamin F. Voight2, Benjamin F. Voight3, Gina M. Peloso4, Gina M. Peloso5, Marju Orho-Melander6, Ruth Frikke-Schmidt7, Maja Barbalić8, Majken K. Jensen3, George Hindy6, Hilma Holm9, Eric L. Ding3, Toby Johnson10, Heribert Schunkert11, Nilesh J. Samani12, Nilesh J. Samani13, Robert Clarke14, Jemma C. Hopewell14, John F. Thompson12, Mingyao Li2, Gudmar Thorleifsson9, Christopher Newton-Cheh, Kiran Musunuru3, Kiran Musunuru1, James P. Pirruccello1, James P. Pirruccello3, Danish Saleheen15, Li Chen16, Alexandre F.R. Stewart16, Arne Schillert11, Unnur Thorsteinsdottir17, Unnur Thorsteinsdottir9, Gudmundur Thorgeirsson17, Sonia S. Anand18, James C. Engert19, Thomas M. Morgan20, John A. Spertus21, Monika Stoll22, Klaus Berger22, Nicola Martinelli23, Domenico Girelli23, Pascal P. McKeown24, Christopher Patterson24, Stephen E. Epstein25, Joseph M. Devaney25, Mary Susan Burnett25, Vincent Mooser26, Samuli Ripatti27, Ida Surakka27, Markku S. Nieminen27, Juha Sinisalo27, Marja-Liisa Lokki27, Markus Perola4, Aki S. Havulinna4, Ulf de Faire28, Bruna Gigante28, Erik Ingelsson28, Tanja Zeller29, Philipp S. Wild29, Paul I.W. de Bakker, Olaf H. Klungel30, Anke-Hilse Maitland-van der Zee30, Bas J M Peters30, Anthonius de Boer30, Diederick E. Grobbee30, Pieter Willem Kamphuisen31, Vera H.M. Deneer, Clara C. Elbers30, N. Charlotte Onland-Moret30, Marten H. Hofker31, Cisca Wijmenga31, W. M. Monique Verschuren, Jolanda M. A. Boer, Yvonne T. van der Schouw30, Asif Rasheed, Philippe M. Frossard, Serkalem Demissie5, Serkalem Demissie4, Cristen J. Willer32, Ron Do3, Jose M. Ordovas33, Jose M. Ordovas34, Gonçalo R. Abecasis32, Michael Boehnke32, Karen L. Mohlke35, Mark J. Daly3, Mark J. Daly1, Candace Guiducci1, Noël P. Burtt1, Aarti Surti1, Elena Gonzalez1, Shaun Purcell1, Shaun Purcell3, Stacey Gabriel1, Jaume Marrugat, John F. Peden14, Jeanette Erdmann11, Patrick Diemert11, Christina Willenborg11, Inke R. König11, Marcus Fischer36, Christian Hengstenberg36, Andreas Ziegler11, Ian Buysschaert37, Diether Lambrechts37, Frans Van de Werf37, Keith A.A. Fox38, Nour Eddine El Mokhtari39, Diana Rubin, Jürgen Schrezenmeir, Stefan Schreiber39, Arne Schäfer39, John Danesh15, Stefan Blankenberg29, Robert Roberts16, Ruth McPherson16, Hugh Watkins14, Alistair S. Hall40, Kim Overvad41, Eric B. Rimm3, Eric Boerwinkle8, Anne Tybjærg-Hansen7, L. Adrienne Cupples5, L. Adrienne Cupples4, Muredach P. Reilly2, Olle Melander6, Pier Mannuccio Mannucci42, Diego Ardissino, David S. Siscovick43, Roberto Elosua, Kari Stefansson9, Kari Stefansson17, Christopher J. O'Donnell3, Christopher J. O'Donnell4, Veikko Salomaa4, Daniel J. Rader2, Leena Peltonen27, Leena Peltonen44, Stephen M. Schwartz43, David Altshuler, Sekar Kathiresan 
11 Aug 2012
TL;DR: In this paper, a Mendelian randomisation analysis was performed to compare the effect of HDL cholesterol, LDL cholesterol, and genetic score on risk of myocardial infarction.
Abstract: Methods We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20 913 myocardial infarction cases, 95 407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12 482 cases of myocardial infarction and 41 331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol. – ¹³) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with noncarriers. This diff erence in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84–0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88–1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58–0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68–1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45–1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69–2·69, p=2×10

1,878 citations

Journal ArticleDOI
TL;DR: In this article, the main results obtained by the BRAHMS Collaboration on the properties of hot and dense hadronic and partonic matter produced in ultrarelativistic heavy ion collisions at RHIC are reviewed.

1,860 citations

Journal ArticleDOI
TL;DR: Top-class soccer players performed more high-intensity running during a game and were better at the Yo-Yo test than moderate professional players; fatigue occurred towards the end of matches as well as temporarily during the game, independently of competitive standard and of team position; defenders covered a shorter distance in high- intensity running than players in other playing positions.
Abstract: The aim of this study was to assess physical fitness, match performance and development of fatigue during competitive matches at two high standards of professional soccer. Computerized time-motion analyses were performed 2-7 times during the competitive season on 18 top-class and 24 moderate professional soccer players. In addition, the players performed the Yo-Yo intermittent recovery test. The top-class players performed 28 and 58% more (P < 0.05) high-intensity running and sprinting, respectively, than the moderate players (2.43 +/- 0.14 vs 1.90 +/- 0.12 km and 0.65 +/- 0.06 vs 0.41 +/- 0.03 km, respectively). The top-class players were better (11%; P < 0.05) on the Yo-Yo intermittent recovery test than the moderate players (2.26 +/- 0.08 vs 2.04 +/- 0.06 km, respectively). The amount of high-intensity running, independent of competitive standard and playing position, was lower (35-45%; P < 0.05) in the last than in the first 15 min of the game. After the 5-min period during which the amount of high-intensity running peaked, performance was reduced (P < 0.05) by 12% in the following 5 min compared with the game average. Substitute players (n = 13) covered 25% more (P < 0.05) ground during the final 15 min of high-intensity running than the other players. The coefficient of variation in high-intensity running was 9.2% between successive matches, whereas it was 24.8% between different stages of the season. Total distance covered and the distance covered in high-intensity running were higher (P < 0.05) for midfield players, full-backs and attackers than for defenders. Attackers and full-backs covered a greater (P < 0.05) distance in sprinting than midfield players and defenders. The midfield players and full-backs covered a greater (P < 0.05) distance than attackers and defenders in the Yo-Yo intermittent recovery test (2.23 +/- 0.10 and 2.21 +/- 0.04 vs 1.99 +/- 0.11 and 1.91 +/- 0.12 km, respectively). The results show that: (1) top-class soccer players performed more high-intensity running during a game and were better at the Yo-Yo test than moderate professional players; (2) fatigue occurred towards the end of matches as well as temporarily during the game, independently of competitive standard and of team position; (3) defenders covered a shorter distance in high-intensity running than players in other playing positions; (4) defenders and attackers had a poorer Yo-Yo intermittent recovery test performance than midfielders and full-backs; and (5) large seasonal changes were observed in physical performance during matches.

1,859 citations

Journal ArticleDOI
TL;DR: An international group of experts in pharmacokinetic modeling recommends a consensus nomenclature to describe in vivo molecular imaging of reversibly binding radioligands.
Abstract: An international group of experts in pharmacokinetic modeling recommends a consensus nomenclature to describe in vivo molecular imaging of reversibly binding radioligands.

1,858 citations

Journal ArticleDOI
TL;DR: The booklet describes the recommended International Standards examination, including both sensory and motor components, and describes the ASIA (American Spinal Injury Association) Impairment Scale (AIS) to classify the severity (i.e. completeness) of injury.
Abstract: This article represents the content of the booklet, International Standards for Neurological Classification of Spinal Cord Injury, revised 2011, published by the American Spinal Injury Association (ASIA). For further explanation of the clarifications and changes in this revision, see the accompanying article (Kirshblum S., et al. J Spinal Cord Med. 2011:doi 10.1179/107902611X13186000420242 The spinal cord is the major conduit through which motor and sensory information travels between the brain and body. The spinal cord contains longitudinally oriented spinal tracts (white matter) surrounding central areas (gray matter) where most spinal neuronal cell bodies are located. The gray matter is organized into segments comprising sensory and motor neurons. Axons from spinal sensory neurons enter and axons from motor neurons leave the spinal cord via segmental nerves or roots. In the cervical spine, there are 8 nerve roots. Cervical roots of C1-C7 are named according to the vertebra above which they exit (i.e. C1 exits above the C1 vertebra, just below the skull and C6 nerve roots pass between the C5 and C6 vertebrae) whereas C8 exists between the C7 and T1 vertebra; as there is no C8 vertebra. The C1 nerve root does not have a sensory component that is tested on the International Standards Examination. The thoracic spine has 12 distinct nerve roots and the lumbar spine consists of 5 distinct nerve roots that are each named accordingly as they exit below the level of the respective vertebrae. The sacrum consists of 5 embryonic sections that have fused into one bony structure with 5 distinct nerve roots that exit via the sacral foramina. The spinal cord itself ends at approximately the L1-2 vertebral level. The distal most part of the spinal cord is called the conus medullaris. The cauda equina is a cluster of paired (right and left) lumbosacral nerve roots that originate in the region of the conus medullaris and travel down through the thecal sac and exit via the intervertebral foramen below their respective vertebral levels. There may be 0, 1, or 2 coccygeal nerves but they do not have a role with the International Standards examination in accordance with the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI). Each root receives sensory information from skin areas called dermatomes. Similarly each root innervates a group of muscles called a myotome. While a dermatome usually represents a discrete and contiguous skin area, most roots innervate more than one muscle, and most muscles are innervated by more than one root. Spinal cord injury (SCI) affects conduction of sensory and motor signals across the site(s) of lesion(s), as well as the autonomic nervous system. By systematically examining the dermatomes and myotomes, as described within this booklet, one can determine the cord segments affected by the SCI. From the International Standards examination several measures of neurological damage are generated, e.g., Sensory and Motor Levels (on right and left sides), NLI, Sensory Scores (Pin Prick and Light Touch), Motor Scores (upper and lower limb), and ZPP. This booklet also describes the ASIA (American Spinal Injury Association) Impairment Scale (AIS) to classify the severity (i.e. completeness) of injury. This booklet begins with basic definitions of common terms used herein. The section that follows describes the recommended International Standards examination, including both sensory and motor components. Subsequent sections cover sensory and motor scores, the AIS classification, and clinical syndromes associated with SCI. For ease of reference, a worksheet (Appendix 1) of the recommended examination is included, with a summary of steps used to classify the injury (Appendix 2). A full-size version for photocopying and use in patient records has been included as an enclosure and may also be downloaded from the ASIA website (www.asia-spinalinjury.org). Additional details regarding the examination and e-Learning training materials can also be obtained from the website15.

1,858 citations


Authors

Showing all 58387 results

NameH-indexPapersCitations
Michael Karin236704226485
Matthias Mann221887230213
Peer Bork206697245427
Ronald Klein1941305149140
Kenneth S. Kendler1771327142251
Dorret I. Boomsma1761507136353
Ramachandran S. Vasan1721100138108
Unnur Thorsteinsdottir167444121009
Mika Kivimäki1661515141468
Jun Wang1661093141621
Anders Björklund16576984268
Gerald I. Shulman164579109520
Jaakko Kaprio1631532126320
Veikko Salomaa162843135046
Daniel J. Jacob16265676530
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023370
20221,266
202110,694
20209,956
20199,190
20188,620