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Institution

University of Tübingen

EducationTübingen, Germany
About: University of Tübingen is a education organization based out in Tübingen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 40555 authors who have published 84108 publications receiving 3015320 citations. The organization is also known as: Eberhard Karls University & Eberhard-Karls-Universität Tübingen.


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Journal ArticleDOI
Günter U. Höglinger1, Nadine M. Melhem2, Dennis W. Dickson3, Patrick M. A. Sleiman4, Li-San Wang4, Lambertus Klei2, Rosa Rademakers3, Rohan de Silva5, Irene Litvan6, David E. Riley7, John C. van Swieten8, Peter Heutink9, Zbigniew K. Wszolek3, Ryan J. Uitti3, Jana Vandrovcova5, Howard I. Hurtig4, Rachel G. Gross4, Walter Maetzler10, Stefano Goldwurm, Eduardo Tolosa11, Barbara Borroni12, Pau Pastor13, Laura B. Cantwell4, Mi Ryung Han4, Allissa Dillman14, Marcel P. van der Brug15, J. Raphael Gibbs14, J. Raphael Gibbs5, Mark R. Cookson14, Dena G. Hernandez5, Dena G. Hernandez14, Andrew B. Singleton14, Matthew J. Farrer16, Chang En Yu17, Lawrence I. Golbe18, Tamas Revesz5, John Hardy5, Andrew J. Lees5, Bernie Devlin2, Hakon Hakonarson4, Ulrich Müller19, Gerard D. Schellenberg4, Roger L. Albin20, Elena Alonso13, Angelo Antonini, Manuela Apfelbacher21, Steven E. Arnold4, Jesús Avila22, Thomas G. Beach, Sherry Beecher4, Daniela Berg23, Thomas D. Bird, Nenad Bogdanovic24, Agnita J.W. Boon8, Yvette Bordelon25, Alexis Brice26, Alexis Brice27, Herbert Budka28, Margherita Canesi, Wang Zheng Chiu8, Roberto Cilia, Carlo Colosimo29, Peter Paul De Deyn30, Justo Garcãa De Yebenes, Laura Donker Kaat8, Ranjan Duara31, Alexandra Durr26, Alexandra Durr27, Sebastiaan Engelborghs30, Giovanni Fabbrini29, Nicole A. Finch3, Robyn Flook32, Matthew P. Frosch33, Carles Gaig11, Douglas Galasko34, Thomas Gasser23, Marla Gearing35, Evan T. Geller4, Bernardino Ghetti36, Neill R. Graff-Radford3, Murray Grossman4, Deborah A. Hall37, Lili-Naz Hazrati38, Matthias Höllerhage1, Joseph Jankovic39, Jorge L. Juncos35, Anna Karydas40, Hans A. Kretzschmar41, Isabelle Leber27, Isabelle Leber26, Virginia M.-Y. Lee4, Andrew P. Lieberman20, Kelly E. Lyons42, Claudio Mariani, Eliezer Masliah34, Luke A. Massey5, Catriona McLean43, Nicoletta Meucci, Bruce L. Miller40, Brit Mollenhauer44, Jens Carsten Möller1, Huw R. Morris45, Christopher Morris46, Sean S. O'Sullivan5, Wolfgang H. Oertel1, Donatella Ottaviani29, Alessandro Padovani12, Rajesh Pahwa42, Gianni Pezzoli, Stuart Pickering-Brown47, Werner Poewe48, Alberto Rábano49, Alex Rajput50, Stephen G. Reich51, Gesine Respondek1, Sigrun Roeber41, Jonathan D. Rohrer5, Owen A. Ross3, Martin N. Rossor5, Giorgio Sacilotto, William W. Seeley40, Klaus Seppi48, Laura Silveira-Moriyama5, Salvatore Spina36, Karin Srulijes23, Peter St George-Hyslop52, Maria Stamelou1, David G. Standaert53, Silvana Tesei, Wallace W. Tourtellotte54, Claudia Trenkwalder44, Claire Troakes55, John Q. Trojanowski4, Juan C. Troncoso56, Vivianna M. Van Deerlin4, Jean Paul G. Vonsattel57, Gregor K. Wenning48, Charles L. White58, Pia Winter19, Chris Zarow59, Anna Zecchinelli 
University of Marburg1, University of Pittsburgh2, Mayo Clinic3, University of Pennsylvania4, University College London5, University of Louisville6, Case Western Reserve University7, Erasmus University Rotterdam8, VU University Amsterdam9, University of Tübingen10, University of Barcelona11, University of Brescia12, University of Navarra13, National Institutes of Health14, Scripps Research Institute15, University of British Columbia16, University of Washington17, Rutgers University18, University of Giessen19, University of Michigan20, University of Würzburg21, Autonomous University of Madrid22, German Center for Neurodegenerative Diseases23, Karolinska Institutet24, University of California, Los Angeles25, French Institute of Health and Medical Research26, Centre national de la recherche scientifique27, Medical University of Vienna28, Sapienza University of Rome29, University of Antwerp30, Mount Sinai Hospital31, Flinders University32, Harvard University33, University of California, San Diego34, Emory University35, Indiana University36, Rush University Medical Center37, University of Toronto38, Baylor College of Medicine39, University of California, San Francisco40, Ludwig Maximilian University of Munich41, University of Kansas42, Mental Health Research Institute43, University of Göttingen44, Cardiff University45, Newcastle University46, University of Manchester47, Innsbruck Medical University48, Carlos III Health Institute49, University of Saskatchewan50, University of Maryland, Baltimore51, University of Cambridge52, University of Alabama at Birmingham53, Veterans Health Administration54, King's College London55, Johns Hopkins University56, Columbia University57, University of Texas Southwestern Medical Center58, University of Southern California59
TL;DR: Two independent variants in MAPT affecting risk for PSP are confirmed, one of which influences MAPT brain expression and the genes implicated encode proteins for vesicle-membrane fusion at the Golgi-endosomal interface and for a myelin structural component.
Abstract: Progressive supranuclear palsy (PSP) is a movement disorder with prominent tau neuropathology. Brain diseases with abnormal tau deposits are called tauopathies, the most common of which is Alzheimer's disease. Environmental causes of tauopathies include repetitive head trauma associated with some sports. To identify common genetic variation contributing to risk for tauopathies, we carried out a genome-wide association study of 1,114 individuals with PSP (cases) and 3,247 controls (stage 1) followed by a second stage in which we genotyped 1,051 cases and 3,560 controls for the stage 1 SNPs that yielded P ≤ 10−3. We found significant previously unidentified signals (P < 5 × 10−8) associated with PSP risk at STX6, EIF2AK3 and MOBP. We confirmed two independent variants in MAPT affecting risk for PSP, one of which influences MAPT brain expression. The genes implicated encode proteins for vesicle-membrane fusion at the Golgi-endosomal interface, for the endoplasmic reticulum unfolded protein response and for a myelin structural component.

504 citations

Journal ArticleDOI
TL;DR: This Review focuses on recent advances in the understanding of the transcriptional functions of NFAT proteins in the immune system and provides new insights into their potential roles in cancer development.
Abstract: Nuclear factor of activated T cells (NFAT) was first identified more than two decades ago as a major stimulation-responsive DNA-binding factor and transcriptional regulator in T cells. It is now clear that NFAT proteins have important functions in other cells of the immune system and regulate numerous developmental programmes in vertebrates. Dysregulation of these programmes can lead to malignant growth and cancer. This Review focuses on recent advances in our understanding of the transcriptional functions of NFAT proteins in the immune system and provides new insights into their potential roles in cancer development.

504 citations

Journal ArticleDOI
TL;DR: Among the tyrosine kinase inhibitors that are commercially available as yet, the agents that target EGFR, erlotinib and gefitinib, display the broadest spectrum of adverse effects on skin and hair, including folliculitis, paronychia, facial hair growth, facial erythema, and varying forms of frontal alopecia.
Abstract: Tyrosine kinase inhibitors (TKI) are effective in the targeted treatment of various malignancies. Imatinib was the first to be introduced into clinical oncology, and it was followed by drugs such as gefitinib, erlotinib, sorafenib, sunitinib, and dasatinib. Although they share the same mechanism of action, namely competitive ATP inhibition at the catalytic binding site of tyrosine kinase, they differ from each other in the spectrum of targeted kinases, their pharmacokinetics as well as substance-specific adverse effects. With variations from drug to drug, tyrosine kinase inhibitors cause skin toxicity, including folliculitis, in more than 50% of patients. Among the tyrosine kinase inhibitors that are commercially available as yet, the agents that target EGFR, erlotinib and gefitinib, display the broadest spectrum of adverse effects on skin and hair, including folliculitis, paronychia, facial hair growth, facial erythema, and varying forms of frontal alopecia. In contrast, folliculitis is not common during administration of sorafenib and sunitinib, which target VEGFR, PDGFR, FLT3, and others, whereas both agents have been associated with subungual splinter hemorrhages. Periorbital edema is a common adverse effect of imatinib. Besides the haematological side effects of most of TKIs like anemia, thrombopenia and neutropenia, the most common extra-heamatologic adverse effects are edema, nausea, hypothyroidism, vomiting and diarrhea. Regarding possible long term effects, recently cardiac toxicity with congestive heart failure is under debate in patients receiving imatinib and sunitinib therapy; however, this observation was probably relate to patients selection, although, TKIs overall appear to be a very well tolerated drug class.

503 citations

Journal ArticleDOI
TL;DR: The time-dependent variational principle provides a unifying framework for time-evolution methods and optimization methods in the context of matrix product states and a new integration scheme for studying time evolution, which can cope with arbitrary Hamiltonians, including those with long-range interactions.
Abstract: We show that the time-dependent variational principle provides a unifying framework for time-evolution methods and optimization methods in the context of matrix product states. In particular, we introduce a new integration scheme for studying time evolution, which can cope with arbitrary Hamiltonians, including those with long-range interactions. Rather than a Suzuki-Trotter splitting of the Hamiltonian, which is the idea behind the adaptive time-dependent density matrix renormalization group method or time-evolving block decimation, our method is based on splitting the projector onto the matrix product state tangent space as it appears in the Dirac-Frenkel time-dependent variational principle. We discuss how the resulting algorithm resembles the density matrix renormalization group (DMRG) algorithm for finding ground states so closely that it can be implemented by changing just a few lines of code and it inherits the same stability and efficiency. In particular, our method is compatible with any Hamiltonian for which ground-state DMRG can be implemented efficiently. In fact, DMRG is obtained as a special case of our scheme for imaginary time evolution with infinite time step.

503 citations

Journal ArticleDOI
TL;DR: Recursive Feature Elimination and Zero-Norm Optimization which are based on the training of support vector machines (SVM) can provide more accurate solutions than standard filter methods for feature selection for EEG channels.
Abstract: Designing a brain computer interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying electroencephalogram (EEG) signals we propose the usage of the state of the art feature selection algorithms Recursive Feature Elimination and Zero-Norm Optimization which are based on the training of support vector machines (SVM) . These algorithms can provide more accurate solutions than standard filter methods for feature selection . We adapt the methods for the purpose of selecting EEG channels. For a motor imagery paradigm we show that the number of used channels can be reduced significantly without increasing the classification error. The resulting best channels agree well with the expected underlying cortical activity patterns during the mental tasks. Furthermore we show how time dependent task specific information can be visualized.

503 citations


Authors

Showing all 41039 results

NameH-indexPapersCitations
John Q. Trojanowski2261467213948
Lily Yeh Jan16246773655
Monique M.B. Breteler15954693762
Wolfgang Wagner1562342123391
Thomas Meitinger155716108491
Hermann Brenner1511765145655
Amartya Sen149689141907
Bernhard Schölkopf1481092149492
Niels Birbaumer14283577853
Detlef Weigel14251684670
Peter Lang140113698592
Marco Colonna13951271166
António Amorim136147796519
Alexis Brice13587083466
Elias Campo13576185160
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023206
2022854
20214,700
20204,480
20194,045
20183,634