scispace - formally typeset
Search or ask a question
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.
Topics: Population, Gene, Catalysis, Magnetic field, Galaxy


Papers
More filters
Journal ArticleDOI
TL;DR: The mass-dependent fractionation laws that describe the partitioning of isotopes are different for kinetic and equilibrium reactions as discussed by the authors, characterized by the exponent relating the fractionation factors for two isotope ratios such that α2/1 = α3/1β.

817 citations

Journal ArticleDOI
12 Jan 1995-Nature
TL;DR: It is shown that targeted disruption of the mouse εl subunit gene resulted in significant reduction of the NMDA receptor channel current and long-term potentiation at the hippocampal CA1 synapses, which supports the notion that the NMda receptor channel-dependent synaptic plasticity is the cellular basis of certain forms of learning.
Abstract: THE NMDA (TV-methyl-D-aspartate) receptor channel is important for synaptic plasticity, which is thought to underlie learning, memory and development1, 2. The NMDA receptor channel is formed by at least two members of the glutamate receptor (GluR) channel subunit families, the GluRe (NR2) and GiuRζ (NR1) sub-unit families3–8. The four e subunits are distinct in distribution, properties and regulation5–14. On the basis of the Mg2+ sensitivity and expression patterns, we have proposed that the ei (NR2A) and e2 (NR2B) subunits play a role in synaptic plasticity6, 14. Here we show that targeted disruption of the mouse el subunit gene resulted in significant reduction of the NMDA receptor channel current and long-term potentiation at the hippocampal CA1 synapses. The mutant mice also showed a moderate deficiency in spatial learning. These results support the notion that the NMDA receptor channel-dependent synaptic plasticity is the cellular basis of certain forms of learning.

817 citations

Journal ArticleDOI
03 Oct 2003-Science
TL;DR: It is shown that the magnetic monopole can appear in the crystal momentum space of solids in the accessible low-energy region in the context of the anomalous Hall effect.
Abstract: Efforts to find the magnetic monopole in real space have been made in cosmic rays and in particle accelerators, but there has not yet been any firm evidence for its existence because of its very heavy mass, ∼10 16 giga–electron volts We show that the magnetic monopole can appear in the crystal momentum space of solids in the accessible low-energy region (∼01 to 1 electron volts) in the context of the anomalous Hall effect We report experimental results together with first-principles calculations on the ferromagnetic crystal SrRuO 3 that provide evidence for the magnetic monopole in the crystal momentum space

816 citations

Proceedings ArticleDOI
23 Jul 2014
TL;DR: This paper presents a method to analyze the powers of a given trilinear form and obtain upper bounds on the asymptotic complexity of matrix multiplication and obtains the upper bound ω < 2.3728639 on the exponent of square matrix multiplication, which slightly improves the best known upper bound.
Abstract: This paper presents a method to analyze the powers of a given trilinear form (a special kind of algebraic construction also called a tensor) and obtain upper bounds on the asymptotic complexity of matrix multiplication. Compared with existing approaches, this method is based on convex optimization, and thus has polynomial-time complexity. As an application, we use this method to study powers of the construction given by Coppersmith and Winograd [Journal of Symbolic Computation, 1990] and obtain the upper bound ω

815 citations

Journal ArticleDOI
TL;DR: Evidence is provided that miR132 regulates neuronal morphogenesis by decreasing levels of the GTPase-activating protein, p250GAP, which reveals that a CREB-regulated miRNA regulates neuronal Morphogenesis by responding to extrinsic trophic cues.
Abstract: MicroRNAs (miRNAs) regulate cellular fate by controlling the stability or translation of mRNA transcripts. Although the spatial and temporal patterning of miRNA expression is tightly controlled, little is known about signals that induce their expression nor mechanisms of their transcriptional regulation. Furthermore, few miRNA targets have been validated experimentally. The miRNA, miR132, was identified through a genome-wide screen as a target of the transcription factor, cAMP-response element binding protein (CREB). miR132 is enriched in neurons and, like many neuronal CREB targets, is highly induced by neurotrophins. Expression of miR132 in cortical neurons induced neurite outgrowth. Conversely, inhibition of miR132 function attenuated neuronal outgrowth. We provide evidence that miR132 regulates neuronal morphogenesis by decreasing levels of the GTPase-activating protein, p250GAP. These data reveal that a CREB-regulated miRNA regulates neuronal morphogenesis by responding to extrinsic trophic cues.

815 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
Network Information
Related Institutions (5)
Kyoto University
217.2K papers, 6.5M citations

99% related

Nagoya University
128.2K papers, 3.2M citations

98% related

University of Tsukuba
79.4K papers, 1.9M citations

98% related

Hokkaido University
115.4K papers, 2.6M citations

97% related

Osaka University
185.6K papers, 5.1M citations

97% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023354
20221,250
202112,943
202013,512
201912,656