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Institution

Pablo de Olavide University

EducationSeville, Andalucía, Spain
About: Pablo de Olavide University is a education organization based out in Seville, Andalucía, Spain. It is known for research contribution in the topics: Population & Context (language use). The organization has 3407 authors who have published 7949 publications receiving 156349 citations. The organization is also known as: Universidad Pablo de Olavide.


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Journal ArticleDOI
Daniel J. Klionsky1, Kotb Abdelmohsen2, Akihisa Abe3, Joynal Abedin4  +2519 moreInstitutions (695)
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are 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 monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

5,187 citations

Journal ArticleDOI
TL;DR: Gaia as discussed by the authors is a cornerstone mission in the science programme of the European Space Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach.
Abstract: Gaia is a cornerstone mission in the science programme of the EuropeanSpace Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page.

5,164 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

Journal ArticleDOI
Valerie Wood1, R. Gwilliam1, Marie-Adèle Rajandream1, M. Lyne1, Rachel Lyne1, A. Stewart2, J. Sgouros2, N. Peat2, Jacqueline Hayles2, Stephen Baker1, D. Basham1, Sharen Bowman1, Karen Brooks1, D. Brown1, Steve D.M. Brown1, Tracey Chillingworth1, Carol Churcher1, Mark O. Collins1, R. Connor1, Ann Cronin1, P. Davis1, Theresa Feltwell1, Andrew G. Fraser1, S. Gentles1, Arlette Goble1, N. Hamlin1, David Harris1, J. Hidalgo1, Geoffrey M. Hodgson1, S. Holroyd1, T. Hornsby1, S. Howarth1, Elizabeth J. Huckle1, Sarah E. Hunt1, Kay Jagels1, Kylie R. James1, L. Jones1, Matthew Jones1, S. Leather1, S. McDonald1, J. McLean1, P. Mooney1, Sharon Moule1, Karen Mungall1, Lee Murphy1, D. Niblett1, C. Odell1, Karen Oliver1, Susan O'Neil1, D. Pearson1, Michael A. Quail1, Ester Rabbinowitsch1, Kim Rutherford1, Simon Rutter1, David L. Saunders1, Kathy Seeger1, Sarah Sharp1, Jason Skelton1, Mark Simmonds1, R. Squares1, S. Squares1, K. Stevens1, K. Taylor1, Ruth Taylor1, Adrian Tivey1, S. Walsh1, T. Warren1, S. Whitehead1, John Woodward1, Guido Volckaert3, Rita Aert3, Johan Robben3, B. Grymonprez3, I. Weltjens3, E. Vanstreels3, Michael A. Rieger, M. Schafer, S. Muller-Auer, C. Gabel, M. Fuchs, C. Fritzc, E. Holzer, D. Moestl, H. Hilbert, K. Borzym4, I. Langer4, Alfred Beck4, Hans Lehrach4, Richard Reinhardt4, Thomas M. Pohl5, P. Eger5, Wolfgang Zimmermann, H. Wedler, R. Wambutt, Bénédicte Purnelle6, André Goffeau6, Edouard Cadieu7, Stéphane Dréano7, Stéphanie Gloux7, Valerie Lelaure7, Stéphanie Mottier7, Francis Galibert7, Stephen J. Aves8, Z. Xiang8, Cherryl Hunt8, Karen Moore8, S. M. Hurst8, M. Lucas9, M. Rochet9, Claude Gaillardin9, Victor A. Tallada10, Victor A. Tallada11, Andrés Garzón11, Andrés Garzón10, G. Thode10, Rafael R. Daga10, Rafael R. Daga11, L. Cruzado10, Juan Jimenez10, Juan Jimenez11, Miguel del Nogal Sánchez12, F. del Rey12, J. Benito12, Angel Domínguez12, José L. Revuelta12, Sergio Moreno12, John Armstrong13, Susan L. Forsburg14, L. Cerrutti1, Todd M. Lowe15, W. R. McCombie16, Ian T. Paulsen17, Judith A. Potashkin18, G. V. Shpakovski19, David W. Ussery20, Bart Barrell1, Paul Nurse2 
21 Feb 2002-Nature
TL;DR: The genome of fission yeast (Schizosaccharomyces pombe), which contains the smallest number of protein-coding genes yet recorded for a eukaryote, is sequenced and highly conserved genes important for eukARYotic cell organization including those required for the cytoskeleton, compartmentation, cell-cycle control, proteolysis, protein phosphorylation and RNA splicing are identified.
Abstract: We have sequenced and annotated the genome of fission yeast (Schizosaccharomyces pombe), which contains the smallest number of protein-coding genes yet recorded for a eukaryote: 4,824. The centromeres are between 35 and 110 kilobases (kb) and contain related repeats including a highly conserved 1.8-kb element. Regions upstream of genes are longer than in budding yeast (Saccharomyces cerevisiae), possibly reflecting more-extended control regions. Some 43% of the genes contain introns, of which there are 4,730. Fifty genes have significant similarity with human disease genes; half of these are cancer related. We identify highly conserved genes important for eukaryotic cell organization including those required for the cytoskeleton, compartmentation, cell-cycle control, proteolysis, protein phosphorylation and RNA splicing. These genes may have originated with the appearance of eukaryotic life. Few similarly conserved genes that are important for multicellular organization were identified, suggesting that the transition from prokaryotes to eukaryotes required more new genes than did the transition from unicellular to multicellular organization.

1,686 citations

Journal ArticleDOI
TL;DR: RASPA as discussed by the authors is a software package for simulating adsorption and diffusion of molecules in flexible nanoporous materials, which implements the latest state-of-the-art algorithms for molecular dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker's minimisation.
Abstract: A new software package, RASPA, for simulating adsorption and diffusion of molecules in flexible nanoporous materials is presented. The code implements the latest state-of-the-art algorithms for molecular dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker's minimisation. We show example applications of RASPA in computing coexistence properties, adsorption isotherms for single and multiple components, self- and collective diffusivities, reaction systems and visualisation. The software is released under the GNU General Public License.

1,139 citations


Authors

Showing all 3473 results

NameH-indexPapersCitations
Antoni Torres120123865049
Juan Bisquert10745046267
Berend Smit10145556755
Alejandro Lucia7568023967
Andrés Aguilera7022717858
Iván Mora-Seró6723523229
Oliver C. Mullins6640617060
Rafael Borja5727310528
Jos Oomens5642912924
Plácido Navas5628115678
Agustín R. González-Elipe5551913871
José M. Delgado-García512268305
G. Gregory Haff502529505
Manuel Delgado-Baquerizo501959586
Juan José González-Badillo491287337
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202330
2022104
2021710
2020689
2019599
2018617