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Institution

University of Minnesota

EducationMinneapolis, Minnesota, United States
About: University of Minnesota is a education organization based out in Minneapolis, Minnesota, United States. It is known for research contribution in the topics: Population & Transplantation. The organization has 117432 authors who have published 257986 publications receiving 11944239 citations. The organization is also known as: University of Minnesota, Twin Cities & University of Minnesota-Twin Cities.


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Journal ArticleDOI
TL;DR: The Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) at CERN as mentioned in this paper was designed to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1)
Abstract: The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

5,193 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 Gurtu7, Atul Gurtu13, 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 Murayama3, Hitoshi Murayama20, 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
12 Jul 1996-Cell
TL;DR: Cells undergoing apoptosis in vivo showed increased release of cy tochrome c to their cytosol, suggesting that mitochondria may function in apoptosis by releasing cytochrome c.

5,128 citations

Journal ArticleDOI
TL;DR: This article presents a practical convex hull algorithm that combines the two-dimensional Quickhull algorithm with the general-dimension Beneath-Beyond Algorithm, and provides empirical evidence that the algorithm runs faster when the input contains nonextreme points and that it used less memory.
Abstract: The convex hull of a set of points is the smallest convex set that contains the points. This article presents a practical convex hull algorithm that combines the two-dimensional Quickhull algorithm with the general-dimension Beneath-Beyond Algorithm. It is similar to the randomized, incremental algorithms for convex hull and delaunay triangulation. We provide empirical evidence that the algorithm runs faster when the input contains nonextreme points and that it used less memory. computational geometry algorithms have traditionally assumed that input sets are well behaved. When an algorithm is implemented with floating-point arithmetic, this assumption can lead to serous errors. We briefly describe a solution to this problem when computing the convex hull in two, three, or four dimensions. The output is a set of “thick” facets that contain all possible exact convex hulls of the input. A variation is effective in five or more dimensions.

5,050 citations


Authors

Showing all 118112 results

NameH-indexPapersCitations
Walter C. Willett3342399413322
David J. Hunter2131836207050
David Miller2032573204840
Mark I. McCarthy2001028187898
Dennis W. Dickson1911243148488
David H. Weinberg183700171424
Eric Boerwinkle1831321170971
John C. Morris1831441168413
Aaron R. Folsom1811118134044
H. S. Chen1792401178529
Jie Zhang1784857221720
Jasvinder A. Singh1762382223370
Feng Zhang1721278181865
Gang Chen1673372149819
Hongfang Liu1662356156290
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023200
20221,176
202111,903
202011,807
201910,984
201810,367