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Institution

University of Tokyo

EducationTokyo, Japan
About: University of Tokyo is a education organization based out in Tokyo, Japan. It is known for research contribution in the topics: Population & Gene. The organization has 134564 authors who have published 337567 publications receiving 10178620 citations. The organization is also known as: Todai & Universitas Tociensis.


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Journal ArticleDOI
TL;DR: SDSS-III as mentioned in this paper is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars.
Abstract: Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS DR8 (which occurred in Jan 2011). This paper presents an overview of the four SDSS-III surveys. BOSS will measure redshifts of 1.5 million massive galaxies and Lya forest spectra of 150,000 quasars, using the BAO feature of large scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z 100 per resolution element), H-band (1.51-1.70 micron) spectra of 10^5 evolved, late-type stars, measuring separate abundances for ~15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. MARVELS will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10-40 m/s, ~24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. (Abridged)

2,265 citations

Journal ArticleDOI
08 Aug 2013-Nature
TL;DR: Using a rational approach to isolate CD4+FOXP3+ regulatory T (Treg)-cell-inducing bacterial strains from the human indigenous microbiota may allow for tailored therapeutic manipulation of human immune disorders.
Abstract: Manipulation of the gut microbiota holds great promise for the treatment of inflammatory and allergic diseases. Although numerous probiotic microorganisms have been identified, there remains a compelling need to discover organisms that elicit more robust therapeutic responses, are compatible with the host, and can affect a specific arm of the host immune system in a well-controlled, physiological manner. Here we use a rational approach to isolate CD4(+)FOXP3(+) regulatory T (Treg)-cell-inducing bacterial strains from the human indigenous microbiota. Starting with a healthy human faecal sample, a sequence of selection steps was applied to obtain mice colonized with human microbiota enriched in Treg-cell-inducing species. From these mice, we isolated and selected 17 strains of bacteria on the basis of their high potency in enhancing Treg cell abundance and inducing important anti-inflammatory molecules--including interleukin-10 (IL-) and inducible T-cell co-stimulator (ICOS)--in Treg cells upon inoculation into germ-free mice. Genome sequencing revealed that the 17 strains fall within clusters IV, XIVa and XVIII of Clostridia, which lack prominent toxins and virulence factors. The 17 strains act as a community to provide bacterial antigens and a TGF-β-rich environment to help expansion and differentiation of Treg cells. Oral administration of the combination of 17 strains to adult mice attenuated disease in models of colitis and allergic diarrhoea. Use of the isolated strains may allow for tailored therapeutic manipulation of human immune disorders.

2,242 citations

Journal ArticleDOI
TL;DR: RANKL selectively induces NFATc1 expression via TRAF6 and c-Fos signaling pathways, and may represent a master switch for regulating terminal differentiation of osteoclasts, functioning downstream of RANKL.

2,235 citations

Journal ArticleDOI
Lorenzo Galluzzi1, Lorenzo Galluzzi2, Lorenzo Galluzzi3, Stuart A. Aaronson4, John M. Abrams5, Emad S. Alnemri6, David W. Andrews7, Eric H. Baehrecke8, Nicolas G. Bazan9, Mikhail V. Blagosklonny10, Klas Blomgren11, Klas Blomgren12, Christoph Borner13, Dale E. Bredesen14, Dale E. Bredesen15, Catherine Brenner16, Maria Castedo3, Maria Castedo1, Maria Castedo2, John A. Cidlowski17, Aaron Ciechanover18, Gerald M. Cohen19, V De Laurenzi20, R De Maria21, Mohanish Deshmukh22, Brian David Dynlacht23, Wafik S. El-Deiry24, Richard A. Flavell25, Richard A. Flavell26, Simone Fulda27, Carmen Garrido1, Carmen Garrido28, Pierre Golstein16, Pierre Golstein1, Pierre Golstein29, Marie-Lise Gougeon30, Douglas R. Green, Hinrich Gronemeyer16, Hinrich Gronemeyer1, Hinrich Gronemeyer31, György Hajnóczky6, J. M. Hardwick32, Michael O. Hengartner33, Hidenori Ichijo34, Marja Jäättelä, Oliver Kepp3, Oliver Kepp2, Oliver Kepp1, Adi Kimchi35, Daniel J. Klionsky36, Richard A. Knight37, Sally Kornbluth38, Sharad Kumar, Beth Levine26, Beth Levine5, Stuart A. Lipton, Enrico Lugli17, Frank Madeo39, Walter Malorni21, Jean-Christophe Marine40, Seamus J. Martin41, Jan Paul Medema42, Patrick Mehlen43, Patrick Mehlen16, Gerry Melino44, Gerry Melino19, Ute M. Moll45, Ute M. Moll46, Eugenia Morselli2, Eugenia Morselli3, Eugenia Morselli1, Shigekazu Nagata47, Donald W. Nicholson48, Pierluigi Nicotera19, Gabriel Núñez36, Moshe Oren35, Josef M. Penninger49, Shazib Pervaiz50, Marcus E. Peter51, Mauro Piacentini44, Jochen H. M. Prehn52, Hamsa Puthalakath53, Gabriel A. Rabinovich54, Rosario Rizzuto55, Cecília M. P. Rodrigues56, David C. Rubinsztein57, Thomas Rudel58, Luca Scorrano59, Hans-Uwe Simon60, Hermann Steller61, Hermann Steller26, J. Tschopp62, Yoshihide Tsujimoto63, Peter Vandenabeele64, Ilio Vitale2, Ilio Vitale1, Ilio Vitale3, Karen H. Vousden65, Richard J. Youle17, Junying Yuan66, Boris Zhivotovsky67, Guido Kroemer1, Guido Kroemer3, Guido Kroemer2 
French Institute of Health and Medical Research1, Institut Gustave Roussy2, University of Paris-Sud3, Icahn School of Medicine at Mount Sinai4, University of Texas Southwestern Medical Center5, Thomas Jefferson University6, McMaster University7, University of Massachusetts Medical School8, LSU Health Sciences Center New Orleans9, Roswell Park Cancer Institute10, Boston Children's Hospital11, University of Gothenburg12, University of Freiburg13, University of California, San Francisco14, Buck Institute for Research on Aging15, Centre national de la recherche scientifique16, National Institutes of Health17, Technion – Israel Institute of Technology18, University of Leicester19, University of Chieti-Pescara20, Istituto Superiore di Sanità21, University of North Carolina at Chapel Hill22, New York University23, University of Pennsylvania24, Yale University25, Howard Hughes Medical Institute26, University of Ulm27, University of Burgundy28, Aix-Marseille University29, Pasteur Institute30, University of Strasbourg31, Johns Hopkins University32, University of Zurich33, University of Tokyo34, Weizmann Institute of Science35, University of Michigan36, University College London37, Duke University38, University of Graz39, Ghent University40, Trinity College, Dublin41, University of Amsterdam42, University of Lyon43, University of Rome Tor Vergata44, Stony Brook University45, University of Göttingen46, Kyoto University47, Merck & Co.48, Austrian Academy of Sciences49, National University of Singapore50, University of Chicago51, Royal College of Surgeons in Ireland52, La Trobe University53, University of Buenos Aires54, University of Padua55, University of Lisbon56, University of Cambridge57, University of Würzburg58, University of Geneva59, University of Bern60, Rockefeller University61, University of Lausanne62, Osaka University63, University of California, San Diego64, University of Glasgow65, Harvard University66, Karolinska Institutet67
TL;DR: A nonexhaustive comparison of methods to detect cell death with apoptotic or nonapoptotic morphologies, their advantages and pitfalls is provided and the importance of performing multiple, methodologically unrelated assays to quantify dying and dead cells is emphasized.
Abstract: Cell death is essential for a plethora of physiological processes, and its deregulation characterizes numerous human diseases Thus, the in-depth investigation of cell death and its mechanisms constitutes a formidable challenge for fundamental and applied biomedical research, and has tremendous implications for the development of novel therapeutic strategies It is, therefore, of utmost importance to standardize the experimental procedures that identify dying and dead cells in cell cultures and/or in tissues, from model organisms and/or humans, in healthy and/or pathological scenarios Thus far, dozens of methods have been proposed to quantify cell death-related parameters However, no guidelines exist regarding their use and interpretation, and nobody has thoroughly annotated the experimental settings for which each of these techniques is most appropriate Here, we provide a nonexhaustive comparison of methods to detect cell death with apoptotic or nonapoptotic morphologies, their advantages and pitfalls These guidelines are intended for investigators who study cell death, as well as for reviewers who need to constructively critique scientific reports that deal with cellular demise Given the difficulties in determining the exact number of cells that have passed the point-of-no-return of the signaling cascades leading to cell death, we emphasize the importance of performing multiple, methodologically unrelated assays to quantify dying and dead cells

2,218 citations


Authors

Showing all 135252 results

NameH-indexPapersCitations
Ronald C. Kessler2741332328983
Donald P. Schneider2421622263641
George M. Whitesides2401739269833
Jing Wang1844046202769
Tadamitsu Kishimoto1811067130860
Yusuke Nakamura1792076160313
Dennis J. Selkoe177607145825
David L. Kaplan1771944146082
D. M. Strom1763167194314
Masayuki Yamamoto1711576123028
Krzysztof Matyjaszewski1691431128585
Yang Yang1642704144071
Qiang Zhang1611137100950
Kenji Kangawa1531117110059
Takashi Taniguchi1522141110658
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023354
20221,250
202112,942
202013,511
201912,656