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Institution

University of Münster

EducationMünster, Germany
About: University of Münster is a education organization based out in Münster, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 35609 authors who have published 69059 publications receiving 2278534 citations. The organization is also known as: University of Munster & University of Muenster.


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Journal ArticleDOI
11 Sep 2003-Oncogene
TL;DR: The identification of MALAT-1 emphasizes the potential role of noncoding RNAs in human cancer and contributes to the identification of early-stage NSCLC patients that are at high risk to develop metastasis.
Abstract: Early-stage non-small cell lung cancer (NSCLC) can be cured by surgical resection, but a substantial fraction of patients ultimately dies due to distant metastasis. In this study, we used subtractive hybridization to identify gene expression differences in stage I NSCLC tumors that either did or did not metastasize in the course of disease. Individual clones (n=225) were sequenced and quantitative RT-PCR verified overexpression in metastasizing samples. Several of the identified genes (eIF4A1, thymosin beta4 and a novel transcript named MALAT-1) were demonstrated to be significantly associated with metastasis in NSCLC patients (n=70). The genes' association with metastasis was stage- and histology specific. The Kaplan-Meier analyses identified MALAT-1 and thymosin beta4 as prognostic parameters for patient survival in stage I NSCLC. The novel MALAT-1 transcript is a noncoding RNA of more than 8000 nt expressed from chromosome 11q13. It is highly expressed in lung, pancreas and other healthy organs as well as in NSCLC. MALAT-1 expressed sequences are conserved across several species indicating its potentially important function. Taken together, these data contribute to the identification of early-stage NSCLC patients that are at high risk to develop metastasis. The identification of MALAT-1 emphasizes the potential role of noncoding RNAs in human cancer.

1,955 citations

Journal ArticleDOI
TL;DR: In this paper, the use of a matrix for pulsed ultraviolet laser desorption mass spectrometry is shown to extend its applicability into the range of larger, thermally labile biomolecules.

1,909 citations

Journal ArticleDOI
Naomi R. Wray1, Stephan Ripke2, Stephan Ripke3, Stephan Ripke4  +259 moreInstitutions (79)
TL;DR: A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent and significant loci and finds important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia.
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

1,898 citations

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. Jensen1, George Hindy6, Hilma Holm9, Eric L. Ding1, Toby Johnson10, Heribert Schunkert11, Nilesh J. Samani12, Nilesh J. Samani13, Robert Clarke14, Jemma C. Hopewell14, John F. Thompson12, Mingyao Li3, Gudmar Thorleifsson9, Christopher Newton-Cheh, Kiran Musunuru1, Kiran Musunuru2, James P. Pirruccello2, James P. Pirruccello1, 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 Demissie4, Serkalem Demissie5, Cristen J. Willer32, Ron Do1, Jose M. Ordovas33, Jose M. Ordovas34, Gonçalo R. Abecasis32, Michael Boehnke32, Karen L. Mohlke35, Mark J. Daly1, Mark J. Daly2, Candace Guiducci2, Noël P. Burtt2, Aarti Surti2, Elena Gonzalez2, Shaun Purcell2, Shaun Purcell1, Stacey Gabriel2, 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. Rimm1, Eric Boerwinkle8, Anne Tybjærg-Hansen7, L. Adrienne Cupples4, L. Adrienne Cupples5, Muredach P. Reilly3, Olle Melander6, Pier Mannuccio Mannucci42, Diego Ardissino, David S. Siscovick43, Roberto Elosua, Kari Stefansson17, Kari Stefansson9, Christopher J. O'Donnell4, Christopher J. O'Donnell1, Veikko Salomaa4, Daniel J. Rader3, Leena Peltonen44, Leena Peltonen27, 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: This Perspective highlights the potential of metal-catalysed C-H bond activation reactions, which now extend beyond the field of traditional synthetic organic chemistry, and are more atom- and step-economical than previous methods.
Abstract: The beginning of the twenty-first century has witnessed significant advances in the field of C-H bond activation, and this transformation is now an established piece in the synthetic chemists' toolbox. This methodology has the potential to be used in many different areas of chemistry, for example it provides a perfect opportunity for the late-stage diversification of various kinds of organic scaffolds, ranging from relatively small molecules like drug candidates, to complex polydisperse organic compounds such as polymers. In this way, C-H activation approaches enable relatively straightforward access to a plethora of analogues or can help to streamline the lead-optimization phase. Furthermore, synthetic pathways for the construction of complex organic materials can now be designed that are more atom- and step-economical than previous methods and, in some cases, can be based on synthetic disconnections that are just not possible without C-H activation. This Perspective highlights the potential of metal-catalysed C-H bond activation reactions, which now extend beyond the field of traditional synthetic organic chemistry.

1,838 citations


Authors

Showing all 36075 results

NameH-indexPapersCitations
Hyun-Chul Kim1764076183227
Klaus Müllen1642125140748
Giacomo Bruno1581687124368
Anders M. Dale156823133891
Holger J. Schünemann141810113169
Joachim Heinrich136130976887
Markus Merschmeyer132118884975
Klaus Ley12949557964
Robert W. Mahley12836360774
Robert J. Kurman12739760277
Bart Barlogie12677957803
Thomas Schwarz12370154560
Carlos Caldas12254773840
Klaus Weber12152460346
Andrey L. Rogach11757646820
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023253
2022831
20213,683
20203,499
20193,236
20182,918