scispace - formally typeset
Search or ask a question
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.


Papers
More filters
Journal ArticleDOI
Patricio Godoy, Nicola J. Hewitt, Ute Albrecht1, Melvin E. Andersen, Nariman Ansari2, Sudin Bhattacharya, Johannes G. Bode1, Jennifer Bolleyn3, Christoph Borner4, J Böttger5, Albert Braeuning, Robert A. Budinsky6, Britta Burkhardt7, Neil R. Cameron8, Giovanni Camussi9, Chong Su Cho10, Yun Jaie Choi10, J. Craig Rowlands6, Uta Dahmen11, Georg Damm12, Olaf Dirsch11, María Teresa Donato13, Jian Dong, Steven Dooley14, Dirk Drasdo15, Dirk Drasdo5, Dirk Drasdo16, Rowena Eakins17, Karine Sá Ferreira4, Valentina Fonsato9, Joanna Fraczek3, Rolf Gebhardt5, Andrew Gibson17, Matthias Glanemann12, Christopher E. Goldring17, María José Gómez-Lechón, Geny M. M. Groothuis18, Lena Gustavsson19, Christelle Guyot, David Hallifax20, Seddik Hammad21, Adam S. Hayward8, Dieter Häussinger1, Claus Hellerbrand22, Philip Hewitt23, Stefan Hoehme5, Hermann-Georg Holzhütter12, J. Brian Houston20, Jens Hrach, Kiyomi Ito24, Hartmut Jaeschke25, Verena Keitel1, Jens M. Kelm, B. Kevin Park17, Claus Kordes1, Gerd A. Kullak-Ublick, Edward L. LeCluyse, Peng Lu, Jennifer Luebke-Wheeler, Anna Lutz4, Daniel J. Maltman, Madlen Matz-Soja5, Patrick D. McMullen, Irmgard Merfort4, Simon Messner, Christoph Meyer14, Jessica Mwinyi, Dean J. Naisbitt17, Andreas K. Nussler7, Peter Olinga18, Francesco Pampaloni2, Jingbo Pi, Linda J. Pluta, Stefan Przyborski8, Anup Ramachandran25, Vera Rogiers3, Cliff Rowe17, Celine Schelcher26, Kathrin Schmich4, Michael Schwarz, Bijay Singh10, Ernst H. K. Stelzer2, Bruno Stieger, Regina Stöber, Yuichi Sugiyama, Ciro Tetta27, Wolfgang E. Thasler26, Tamara Vanhaecke3, Mathieu Vinken3, Thomas S. Weiss28, Agata Widera, Courtney G. Woods, Jinghai James Xu29, Kathy Yarborough, Jan G. Hengstler 
TL;DR: This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro and how closely hepatoma, stem cell and iPS cell–derived hepatocyte-like-cells resemble real hepatocytes.
Abstract: This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.

1,085 citations

Journal ArticleDOI
24 Dec 2015-Nature
TL;DR: A genome-wide scan for selection using ancient DNA is reported, capitalizing on the largest ancient DNA data set yet assembled: 230 West Eurasians who lived between 6500 and 300 bc, including 163 with newly reported data.
Abstract: Ancient DNA makes it possible to observe natural selection directly by analysing samples from populations before, during and after adaptation events. Here we report a genome-wide scan for selection using ancient DNA, capitalizing on the largest ancient DNA data set yet assembled: 230 West Eurasians who lived between 6500 and 300 bc, including 163 with newly reported data. The new samples include, to our knowledge, the first genome-wide ancient DNA from Anatolian Neolithic farmers, whose genetic material we obtained by extracting from petrous bones, and who we show were members of the population that was the source of Europe's first farmers. We also report a transect of the steppe region in Samara between 5600 and 300 bc, which allows us to identify admixture into the steppe from at least two external sources. We detect selection at loci associated with diet, pigmentation and immunity, and two independent episodes of selection on height.

1,083 citations

Journal ArticleDOI
TL;DR: A comprehensive genetic analysis of 304 primary DLBCLs identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data to provide a roadmap for an actionableDLBCL classification.
Abstract: Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification.

1,081 citations

Proceedings Article
07 Dec 2015
TL;DR: A new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition is introduced, showing that across layers the texture representations increasingly capture the statistical properties of natural images while making object information more and more explicit.
Abstract: Here we introduce a new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition. Samples from the model are of high perceptual quality demonstrating the generative power of neural networks trained in a purely discriminative fashion. Within the model, textures are represented by the correlations between feature maps in several layers of the network. We show that across layers the texture representations increasingly capture the statistical properties of natural images while making object information more and more explicit. The model provides a new tool to generate stimuli for neuroscience and might offer insights into the deep representations learned by convolutional neural networks.

1,081 citations

Journal ArticleDOI
TL;DR: The present review summarizes and compares the results of different laboratories investigating the neuroanatomical and neurochemical basis of conditioned fear, focusing primarily on the behavioral models of freezing and fear-potentiated startle in rats and describes the pathways mediating and modulating fear.

1,079 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
Network Information
Related Institutions (5)
Heidelberg University
119.1K papers, 4.6M citations

98% related

Ludwig Maximilian University of Munich
161.5K papers, 5.7M citations

98% related

University of Zurich
124K papers, 5.3M citations

95% related

Technische Universität München
123.4K papers, 4M citations

95% related

Radboud University Nijmegen
83K papers, 3.2M citations

94% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023206
2022854
20214,700
20204,480
20194,045
20183,634