scispace - formally typeset
Search or ask a question
Institution

University of California, Irvine

EducationIrvine, California, United States
About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.
Topics: Population, Galaxy, Poison control, Cancer, Gene


Papers
More filters
Journal ArticleDOI
Gregory A. Roth1, Gregory A. Roth2, Degu Abate3, Kalkidan Hassen Abate4  +1025 moreInstitutions (333)
TL;DR: Non-communicable diseases comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5–74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional causes accounted for 18·6% (17·9–19·6), and injuries 8·0% (7·7–8·2).

5,211 citations

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
K. Hagiwara, Ken Ichi Hikasa1, Koji Nakamura, Masaharu Tanabashi1, M. Aguilar-Benitez, Claude Amsler2, R. M. Barnett3, Patricia R. Burchat4, C. D. Carone5, C. Caso, G. Conforto6, Olav Dahl3, Michael Doser7, Semen Eidelman8, Jonathan L. Feng9, L. K. Gibbons10, Maury Goodman11, Christoph Grab12, D. E. Groom3, Atul Gurtu13, Atul Gurtu7, K. G. Hayes14, J. J. Herna`ndez-Rey15, K. Honscheid16, Christopher Kolda17, Michelangelo L. Mangano7, David Manley18, Aneesh V. Manohar19, John March-Russell7, Alberto Masoni, Ramon Miquel3, Klaus Mönig, Hitoshi Murayama20, Hitoshi Murayama3, S. Sánchez Navas12, Keith A. Olive21, Luc Pape7, C. Patrignani, A. Piepke22, Matts Roos23, John Terning24, Nils A. Tornqvist23, T. G. Trippe3, Petr Vogel25, C. G. Wohl3, Ron L. Workman26, W-M. Yao3, B. Armstrong3, P. S. Gee3, K. S. Lugovsky, S. B. Lugovsky, V. S. Lugovsky, Marina Artuso27, D. Asner28, K. S. Babu29, E. L. Barberio7, Marco Battaglia7, H. Bichsel30, O. Biebel31, Philippe Bloch7, Robert N. Cahn3, Ariella Cattai7, R. S. Chivukula32, R. Cousins33, G. A. Cowan34, Thibault Damour35, K. Desler, R. J. Donahue3, D. A. Edwards, Victor Daniel Elvira, Jens Erler36, V. V. Ezhela, A Fassò7, W. Fetscher12, Brian D. Fields37, B. Foster38, Daniel Froidevaux7, Masataka Fukugita39, Thomas K. Gaisser40, L. Garren, H.-J. Gerber12, Frederick J. Gilman41, Howard E. Haber42, C. A. Hagmann28, J.L. Hewett4, Ian Hinchliffe3, Craig J. Hogan30, G. Höhler43, P. Igo-Kemenes44, John David Jackson3, Kurtis F Johnson45, D. Karlen, B. Kayser, S. R. Klein3, Konrad Kleinknecht46, I.G. Knowles47, P. Kreitz4, Yu V. Kuyanov, R. Landua7, Paul Langacker36, L. S. Littenberg48, Alan D. Martin49, Tatsuya Nakada7, Tatsuya Nakada50, Meenakshi Narain32, Paolo Nason, John A. Peacock47, Helen R. Quinn4, Stuart Raby16, Georg G. Raffelt31, E. A. Razuvaev, B. Renk46, L. Rolandi7, Michael T Ronan3, L.J. Rosenberg51, Christopher T. Sachrajda52, A. I. Sanda53, Subir Sarkar54, Michael Schmitt55, O. Schneider50, Douglas Scott56, W. G. Seligman57, Michael H. Shaevitz57, Torbjörn Sjöstrand58, George F. Smoot3, Stefan M Spanier4, H. Spieler3, N. J. C. Spooner59, Mark Srednicki60, A. Stahl, Todor Stanev40, M. Suzuki3, N. P. Tkachenko, German Valencia61, K. van Bibber28, Manuella Vincter62, D. R. Ward63, Bryan R. Webber63, M R Whalley49, Lincoln Wolfenstein41, J. Womersley, C. L. Woody48, O. V. Zenin 
Tohoku University1, University of Zurich2, Lawrence Berkeley National Laboratory3, Stanford University4, College of William & Mary5, University of Urbino6, CERN7, Budker Institute of Nuclear Physics8, University of California, Irvine9, Cornell University10, Argonne National Laboratory11, ETH Zurich12, Tata Institute of Fundamental Research13, Hillsdale College14, Spanish National Research Council15, Ohio State University16, University of Notre Dame17, Kent State University18, University of California, San Diego19, University of California, Berkeley20, University of Minnesota21, University of Alabama22, University of Helsinki23, Los Alamos National Laboratory24, California Institute of Technology25, George Washington University26, Syracuse University27, Lawrence Livermore National Laboratory28, Oklahoma State University–Stillwater29, University of Washington30, Max Planck Society31, Boston University32, University of California, Los Angeles33, Royal Holloway, University of London34, Université Paris-Saclay35, University of Pennsylvania36, University of Illinois at Urbana–Champaign37, University of Bristol38, University of Tokyo39, University of Delaware40, Carnegie Mellon University41, University of California, Santa Cruz42, Karlsruhe Institute of Technology43, Heidelberg University44, Florida State University45, University of Mainz46, University of Edinburgh47, Brookhaven National Laboratory48, Durham University49, University of Lausanne50, Massachusetts Institute of Technology51, University of Southampton52, Nagoya University53, University of Oxford54, Northwestern University55, University of British Columbia56, Columbia University57, Lund University58, University of Sheffield59, University of California, Santa Barbara60, Iowa State University61, University of Alberta62, University of Cambridge63
TL;DR: This biennial Review summarizes much of Particle Physics using data from previous editions, plus 2205 new measurements from 667 papers, and features expanded coverage of CP violation in B mesons and of neutrino oscillations.
Abstract: This biennial Review summarizes much of Particle Physics. Using data from previous editions, plus 2205 new measurements from 667 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We also summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors, probability, and statistics. This edition features expanded coverage of CP violation in B mesons and of neutrino oscillations. For the first time we cover searches for evidence of extra dimensions (both in the particle listings and in a new review). Another new review is on Grand Unified Theories. A booklet is available containing the Summary Tables and abbreviated versions of some of the other sections of this full Review. All tables, listings, and reviews (and errata) are also available on the Particle Data Group website: http://pdg.lbl.gov.

5,143 citations

Journal ArticleDOI
TL;DR: This paper investigates two fundamental problems in computer vision: contour detection and image segmentation and presents state-of-the-art algorithms for both of these tasks.
Abstract: This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by user-specified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.

5,068 citations

Journal ArticleDOI
Theo Vos1, Christine Allen1, Megha Arora1, Ryan M Barber1  +696 moreInstitutions (260)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) as discussed by the authors was used to estimate the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015.

5,050 citations


Authors

Showing all 47751 results

NameH-indexPapersCitations
Daniel Levy212933194778
Rob Knight2011061253207
Lewis C. Cantley196748169037
Dennis W. Dickson1911243148488
Terrie E. Moffitt182594150609
Joseph Biederman1791012117440
John R. Yates1771036129029
John A. Rogers1771341127390
Avshalom Caspi170524113583
Yang Gao1682047146301
Carl W. Cotman165809105323
John H. Seinfeld165921114911
Gregg C. Fonarow1611676126516
Jerome I. Rotter1561071116296
David Cella1561258106402
Network Information
Related Institutions (5)
Stanford University
320.3K papers, 21.8M citations

97% related

Columbia University
224K papers, 12.8M citations

97% related

University of Washington
305.5K papers, 17.7M citations

97% related

University of California, Los Angeles
282.4K papers, 15.7M citations

97% related

University of Michigan
342.3K papers, 17.6M citations

97% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
2023252
20221,224
20216,518
20206,348
20195,610