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Jun Suzuki

Bio: Jun Suzuki is an academic researcher from Tohoku University. The author has contributed to research in topics: Machine translation & Language model. The author has an hindex of 33, co-authored 227 publications receiving 4916 citations. Previous affiliations of Jun Suzuki include Nippon Telegraph and Telephone & Osaka Bioscience Institute.


Papers
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Journal ArticleDOI
09 Dec 2010-Nature
TL;DR: It is shown that TMEM16F (transmembrane protein 16F) is an essential component for the Ca2+-dependent exposure of PtdSer on the cell surface, which results from a defect in phospholipid scrambling activity and is found to carry a mutation at a splice-acceptor site of the gene encoding TMEM 16F, causing the premature termination of the protein.
Abstract: In all animal cells, phospholipids are asymmetrically distributed between the outer and inner leaflets of the plasma membrane. This asymmetrical phospholipid distribution is disrupted in various biological systems. For example, when blood platelets are activated, they expose phosphatidylserine (PtdSer) to trigger the clotting system. The PtdSer exposure is believed to be mediated by Ca(2+)-dependent phospholipid scramblases that transport phospholipids bidirectionally, but its molecular mechanism is still unknown. Here we show that TMEM16F (transmembrane protein 16F) is an essential component for the Ca(2+)-dependent exposure of PtdSer on the cell surface. When a mouse B-cell line, Ba/F3, was treated with a Ca(2+) ionophore under low-Ca(2+) conditions, it reversibly exposed PtdSer. Using this property, we established a Ba/F3 subline that strongly exposed PtdSer by repetitive fluorescence-activated cell sorting. A complementary DNA library was constructed from the subline, and a cDNA that caused Ba/F3 to expose PtdSer spontaneously was identified by expression cloning. The cDNA encoded a constitutively active mutant of TMEM16F, a protein with eight transmembrane segments. Wild-type TMEM16F was localized on the plasma membrane and conferred Ca(2+)-dependent scrambling of phospholipids. A patient with Scott syndrome, which results from a defect in phospholipid scrambling activity, was found to carry a mutation at a splice-acceptor site of the gene encoding TMEM16F, causing the premature termination of the protein.

781 citations

Journal ArticleDOI
26 Jul 2013-Science
TL;DR: The Xk-family protein Xkr8 mediates PtdSer exposure in response to apoptotic stimuli and has evolutionarily conserved roles in promoting the phagocytosis of dying cells by altering the phospholipid distribution in the plasma membrane.
Abstract: A classic feature of apoptotic cells is the cell-surface exposure of phosphatidylserine (PtdSer) as an “eat me” signal for engulfment. We show that the Xk-family protein Xkr8 mediates PtdSer exposure in response to apoptotic stimuli. Mouse Xkr8 −/− cells or human cancer cells in which Xkr8 expression was repressed by hypermethylation failed to expose PtdSer during apoptosis and were inefficiently engulfed by phagocytes. Xkr8 was activated directly by caspases and required a caspase-3 cleavage site for its function. CED-8, the only Caenorhabditis elegans Xk-family homolog, also promoted apoptotic PtdSer exposure and cell-corpse engulfment. Thus, Xk-family proteins have evolutionarily conserved roles in promoting the phagocytosis of dying cells by altering the phospholipid distribution in the plasma membrane.

432 citations

Journal ArticleDOI
TL;DR: Among 10 TMEM16 family members, 7 members could be divided into two subfamilies, Ca2+-dependent Cl− channels (16A and 16B) and Ca2-dependent lipid scramblases (16C, 16D, 16F, 16G, and 16J).

301 citations

Journal ArticleDOI
TL;DR: How PtdSer is exposed in apoptotic cells and in activated platelets is described and discussed, and Ptd Ser exposure in other biological processes is discussed.
Abstract: Phosphatidylserine (PtdSer) is a phospholipid that is abundant in eukaryotic plasma membranes. An ATP-dependent enzyme called flippase normally keeps PtdSer inside the cell, but PtdSer is exposed by the action of scramblase on the cell's surface in biological processes such as apoptosis and platelet activation. Once exposed to the cell surface, PtdSer acts as an 'eat me' signal on dead cells, and creates a scaffold for blood-clotting factors on activated platelets. The molecular identities of the flippase and scramblase that work at plasma membranes have long eluded researchers. Indeed, their identity as well as the mechanism of the PtdSer exposure to the cell surface has only recently been revealed. Here, we describe how PtdSer is exposed in apoptotic cells and in activated platelets, and discuss PtdSer exposure in other biological processes.

291 citations

Proceedings Article
01 Dec 2007
TL;DR: Experiments on Arabic-toEnglish translation indicated that a model trained with sparse binary features outperformed a conventional SMT system with a small number of features.
Abstract: We achieved a state of the art performance in statistical machine translation by using a large number of features with an online large-margin training algorithm. The millions of parameters were tuned only on a small development set consisting of less than 1K sentences. Experiments on Arabic-toEnglish translation indicated that a model trained with sparse binary features outperformed a conventional SMT system with a small number of features.

224 citations


Cited by
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
06 Jun 1986-JAMA
TL;DR: The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or her own research.
Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

7,563 citations

Journal Article
TL;DR: A unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity recognition, and semantic role labeling is proposed.
Abstract: We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This versatility is achieved by trying to avoid task-specific engineering and therefore disregarding a lot of prior knowledge. Instead of exploiting man-made input features carefully optimized for each task, our system learns internal representations on the basis of vast amounts of mostly unlabeled training data. This work is then used as a basis for building a freely available tagging system with good performance and minimal computational requirements.

6,734 citations

Journal ArticleDOI
TL;DR: A new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains, and implements a function tau(G,n) isin IRm that maps a graph G and one of its nodes n into an m-dimensional Euclidean space.
Abstract: Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains. This GNN model, which can directly process most of the practically useful types of graphs, e.g., acyclic, cyclic, directed, and undirected, implements a function tau(G,n) isin IRm that maps a graph G and one of its nodes n into an m-dimensional Euclidean space. A supervised learning algorithm is derived to estimate the parameters of the proposed GNN model. The computational cost of the proposed algorithm is also considered. Some experimental results are shown to validate the proposed learning algorithm, and to demonstrate its generalization capabilities.

5,701 citations

Journal ArticleDOI
Lorenzo Galluzzi1, Lorenzo Galluzzi2, Ilio Vitale3, Stuart A. Aaronson4  +183 moreInstitutions (111)
TL;DR: The Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives.
Abstract: Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field.

3,301 citations