Institution
University of Paris
Education•Paris, France•
About: University of Paris is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Transplantation. The organization has 102426 authors who have published 174180 publications receiving 5041753 citations. The organization is also known as: Sorbonne.
Papers published on a yearly basis
Papers
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University of Alberta1, Cedars-Sinai Medical Center2, Harvard University3, Johns Hopkins University4, Cleveland Clinic5, University of Arizona6, Hannover Medical School7, Mayo Clinic8, University of Pittsburgh9, University of Maryland, Baltimore10, University of Paris11, Washington University in St. Louis12, University of Alabama13, Westmead Hospital14, University of North Carolina at Chapel Hill15, University of Vienna16, Autonomous University of Barcelona17, NewYork–Presbyterian Hospital18, Cornell University19
TL;DR: The willingness of the Banff process to adapt continuously in response to new research and improve potential weaknesses, led to the implementation of six working groups on the following areas: isolated v‐lesion, fibrosis scoring, glomerular lesions, molecular pathology, polyomavirus nephropathy and quality assurance.
738 citations
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TL;DR: A perspective of different classes of geophysical, climate-induced, and meteorological disasters based on the extent of interaction between the UAV and terrestrially deployed wireless sensors is presented, with suitable network architectures designed for each of these cases.
Abstract: This article presents a vision for future unmanned aerial vehicles (UAV)-assisted disaster management, considering the holistic functions of disaster prediction, assessment, and response. Here, UAVs not only survey the affected area but also assist in establishing vital wireless communication links between the survivors and nearest available cellular infrastructure. A perspective of different classes of geophysical, climate-induced, and meteorological disasters based on the extent of interaction between the UAV and terrestrially deployed wireless sensors is presented in this work, with suitable network architectures designed for each of these cases. The authors outline unique research challenges and possible solutions for maintaining connected aerial meshes for handoff between UAVs and for systems-specific, security- and energy-related issues. This article is part of a special issue on drones.
738 citations
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TL;DR: Specific IgA serum concentrations decreased notably 1 month after the onset of symptoms, but neutralizing IgA remained detectable in saliva for a longer time (days 49 to 73 post-symptoms).
Abstract: Humoral immune responses are typically characterized by primary IgM antibody responses followed by secondary antibody responses associated with immune memory and comprised of of IgG, IgA and IgE. Here we measured acute humoral responses to SARS-CoV-2, including the frequency of antibody-secreting cells and the presence of SARS-CoV-2-specific neutralizing antibodies in the serum, saliva and broncho-alveolar fluid of 159 patients with COVID-19. Early SARS-CoV-2-specific humoral responses were dominated by IgA antibodies. Peripheral expansion of IgA plasmablasts with mucosal-homing potential was detected shortly after the onset of symptoms and peaked during the third week of the disease. The virus-specific antibody responses included IgG, IgM and IgA, but IgA contributed to virus neutralization to a greater extent compared with IgG. Specific IgA serum concentrations decreased notably one month after the onset of symptoms, but neutralizing IgA remained detectable in saliva for a longer time (days 49 to 73 post symptoms). These results represent a critical observation given the emerging information as to the types of antibodies associated with optimal protection against re-infection, and whether vaccine regimens should consider targeting a potent but potentially short-lived IgA response.
738 citations
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Wellcome Trust Sanger Institute1, Ludwig Maximilian University of Munich2, Max Planck Society3, Cambridge University Hospitals NHS Foundation Trust4, University of Würzburg5, University of Pavia6, International Agency for Research on Cancer7, Istituto Giannina Gaslini8, University of Nebraska Omaha9, University College London10, University of Oxford11, University of Paris12, University of Nebraska–Lincoln13
TL;DR: A gene, SH2D1A, is identified that is mutated in XLP patients and encodes a novel protein composed of a single SH2 domain that is expressed in many tissues involved in the immune system.
Abstract: X-linked lymphoproliferative syndrome (XLP or Duncan disease) is characterized by extreme sensitivity to Epstein-Barr virus (EBV), resulting in a complex phenotype manifested by severe or fatal infectious mononucleosis, acquired hypogammaglobulinemia and malignant lymphoma. We have identified a gene, SH2D1A, that is mutated in XLP patients and encodes a novel protein composed of a single SH2 domain. SH2D1A is expressed in many tissues involved in the immune system. The identification of SH2D1A will allow the determination of its mechanism of action as a possible regulator of the EBV-induced immune response.
737 citations
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TL;DR: A new boundary detection approach for shape modeling that detects the global minimum of an active contour model’s energy between two end points and explores the relation between the maximum curvature along the resulting contour and the potential generated from the image.
Abstract: A new boundary detection approach for shape modeling is presented. It detects the global minimum of an active contour model‘s energy between two end points. Initialization is made easier and the curve is not trapped at a local minimum by spurious edges. We modify the “snake” energy by including the internal regularization term in the external potential term. Our method is based on finding a path of minimal length in a Riemannian metric. We then make use of a new efficient numerical method to find this shortest path.
It is shown that the proposed energy, though based only on a potential integrated along the curve, imposes a regularization effect like snakes. We explore the relation between the maximum curvature along the resulting contour and the potential generated from the image.
The method is capable to close contours, given only one point on the objects‘ boundary by using a topology-based saddle search routine.
We show examples of our method applied to real aerial and medical images.
736 citations
Authors
Showing all 102613 results
Name | H-index | Papers | Citations |
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Guido Kroemer | 236 | 1404 | 246571 |
David H. Weinberg | 183 | 700 | 171424 |
Paul M. Thompson | 183 | 2271 | 146736 |
Chris Sander | 178 | 713 | 233287 |
Sophie Henrot-Versille | 171 | 957 | 157040 |
Richard H. Friend | 169 | 1182 | 140032 |
George P. Chrousos | 169 | 1612 | 120752 |
Mika Kivimäki | 166 | 1515 | 141468 |
Martin Karplus | 163 | 831 | 138492 |
William J. Sandborn | 162 | 1317 | 108564 |
Darien Wood | 160 | 2174 | 136596 |
Monique M.B. Breteler | 159 | 546 | 93762 |
Paul Emery | 158 | 1314 | 121293 |
Wolfgang Wagner | 156 | 2342 | 123391 |
Joao Seixas | 153 | 1538 | 115070 |