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Institution

University of Bordeaux

EducationBordeaux, France
About: University of Bordeaux is a education organization based out in Bordeaux, France. It is known for research contribution in the topics: Population & Laser. The organization has 28811 authors who have published 55536 publications receiving 1619635 citations. The organization is also known as: UB.


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Journal ArticleDOI
03 Oct 1997-Science
TL;DR: This framework provides a realistic approach to identifying the neurobiological factors that produce vulnerability to addiction and to relapse in individuals with a history of addiction.
Abstract: Understanding the neurobiological mechanisms of addiction requires an integration of basic neuroscience with social psychology, experimental psychology, and psychiatry. Addiction is presented as a cycle of spiralling dysregulation of brain reward systems that progressively increases, resulting in compulsive drug use and a loss of control over drug-taking. Sensitization and counteradaptation are hypothesized to contribute to this hedonic homeostatic dysregulation, and the neurobiological mechanisms involved, such as the mesolimbic dopamine system, opioid peptidergic systems, and brain and hormonal stress systems, are beginning to be characterized. This framework provides a realistic approach to identifying the neurobiological factors that produce vulnerability to addiction and to relapse in individuals with a history of addiction.

2,391 citations

Journal ArticleDOI
TL;DR: A set of guidelines for the selection and interpretation of the methods that can be used by investigators who are attempting to examine macroautophagy and related processes, as well as by reviewers who need to provide realistic and reasonable critiques of papers that investigate these processes are presented.
Abstract: Research in autophagy continues to accelerate,(1) and as a result many new scientists are entering the field Accordingly, it is important to establish a standard set of criteria for monitoring macroautophagy in different organisms Recent reviews have described the range of assays that have been used for this purpose(2,3) There are many useful and convenient methods that can be used to monitor macroautophagy in yeast, but relatively few in other model systems, and there is much confusion regarding acceptable methods to measure macroautophagy in higher eukaryotes A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers of autophagosomes versus those that measure flux through the autophagy pathway; thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from fully functional autophagy that includes delivery to, and degradation within, lysosomes (in most higher eukaryotes) or the vacuole (in plants and fungi) Here, we present a set of guidelines for the selection and interpretation of the methods that can be used by investigators who are attempting to examine macroautophagy and related processes, as well as by reviewers who need to provide realistic and reasonable critiques of papers that investigate these processes This set of guidelines is not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to verify an autophagic response

2,310 citations

Journal ArticleDOI
John Allison1, K. Amako2, John Apostolakis3, Pedro Arce4, Makoto Asai5, Tsukasa Aso6, Enrico Bagli, Alexander Bagulya7, Sw. Banerjee8, G. Barrand9, B. R. Beck10, Alexey Bogdanov11, D. Brandt, Jeremy M. C. Brown12, Helmut Burkhardt3, Ph Canal8, D. Cano-Ott4, Stephane Chauvie, Kyung-Suk Cho13, G.A.P. Cirrone14, Gene Cooperman15, M. A. Cortés-Giraldo16, G. Cosmo3, Giacomo Cuttone14, G.O. Depaola17, Laurent Desorgher, X. Dong15, Andrea Dotti5, Victor Daniel Elvira8, Gunter Folger3, Ziad Francis18, A. Galoyan19, L. Garnier9, M. Gayer3, K. Genser8, Vladimir Grichine3, Vladimir Grichine7, Susanna Guatelli20, Susanna Guatelli21, Paul Gueye22, P. Gumplinger23, Alexander Howard24, Ivana Hřivnáčová9, S. Hwang13, Sebastien Incerti25, Sebastien Incerti26, A. Ivanchenko3, Vladimir Ivanchenko3, F.W. Jones23, S. Y. Jun8, Pekka Kaitaniemi27, Nicolas A. Karakatsanis28, Nicolas A. Karakatsanis29, M. Karamitrosi30, M.H. Kelsey5, Akinori Kimura31, Tatsumi Koi5, Hisaya Kurashige32, A. Lechner3, S. B. Lee33, Francesco Longo34, M. Maire, Davide Mancusi, A. Mantero, E. Mendoza4, B. Morgan35, K. Murakami2, T. Nikitina3, Luciano Pandola14, P. Paprocki3, J Perl5, Ivan Petrović36, Maria Grazia Pia, W. Pokorski3, J. M. Quesada16, M. Raine, Maria A.M. Reis37, Alberto Ribon3, A. Ristic Fira36, Francesco Romano14, Giorgio Ivan Russo14, Giovanni Santin38, Takashi Sasaki2, D. Sawkey39, J. I. Shin33, Igor Strakovsky40, A. Taborda37, Satoshi Tanaka41, B. Tome, Toshiyuki Toshito, H.N. Tran42, Pete Truscott, L. Urbán, V. V. Uzhinsky19, Jerome Verbeke10, M. Verderi43, B. Wendt44, H. Wenzel8, D. H. Wright5, Douglas Wright10, T. Yamashita, J. Yarba8, H. Yoshida45 
TL;DR: Geant4 as discussed by the authors is a software toolkit for the simulation of the passage of particles through matter, which is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics and radiation protection.
Abstract: Geant4 is a software toolkit for the simulation of the passage of particles through matter. It is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics and radiation protection. Over the past several years, major changes have been made to the toolkit in order to accommodate the needs of these user communities, and to efficiently exploit the growth of computing power made available by advances in technology. The adaptation of Geant4 to multithreading, advances in physics, detector modeling and visualization, extensions to the toolkit, including biasing and reverse Monte Carlo, and tools for physics and release validation are discussed here.

2,260 citations

Journal ArticleDOI
01 Jan 2017-Gut
TL;DR: This fifth edition of the Maastricht Consensus Report describes how experts from 24 countries examined new data related to H. pylori infection in the various clinical scenarios and provided recommendations on the basis of the best available evidence and relevance.
Abstract: Important progress has been made in the management of Helicobacter pylori infection and in this fifth edition of the Maastricht Consensus Report, key aspects related to the clinical role of H. pylori were re-evaluated in 2015. In the Maastricht V/Florence Consensus Conference, 43 experts from 24 countries examined new data related to H. pylori in five subdivided workshops: (1) Indications/Associations, (2) Diagnosis, (3) Treatment, (4) Prevention/Public Health, (5) H. pylori and the Gastric Microbiota. The results of the individual workshops were presented to a final consensus voting that included all participants. Recommendations are provided on the basis of the best available evidence and relevance to the management of H. pylori infection in the various clinical scenarios.

2,219 citations

Journal ArticleDOI
TL;DR: The first Gaia data release, Gaia DR1 as discussed by the authors, consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues.
Abstract: Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims: A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods: The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results: Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues - a realisation of the Tycho-Gaia Astrometric Solution (TGAS) - and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of 3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr-1 for the proper motions. A systematic component of 0.3 mas should be added to the parallax uncertainties. For the subset of 94 000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr-1. For the secondary astrometric data set, the typical uncertainty of the positions is 10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to0.03 mag over the magnitude range 5 to 20.7. Conclusions: Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.

2,174 citations


Authors

Showing all 28995 results

NameH-indexPapersCitations
Nicholas G. Martin1921770161952
George F. Koob171935112521
Daniel J. Jacob16265676530
Arthur W. Toga1591184109343
James M. Tour14385991364
Floyd E. Bloom13961672641
Herbert Y. Meltzer137114881371
Jean-Marie Tarascon136853137673
Stanley Nattel13277865700
Michel Haïssaguerre11775762284
Liquan Chen11168944229
Marion Leboyer11077350767
Jean-François Dartigues10663146682
Alexa S. Beiser10636647457
Robert Dantzer10549746554
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202378
2022393
20213,110
20203,362
20193,245
20183,143