The Experts below are selected from a list of 112476 Experts worldwide ranked by ideXlab platform
Lucio H. Castilla - One of the best experts on this subject based on the ideXlab platform.
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Preleukemia and Leukemia-Initiating Cell Activity in inv(16) Acute Myeloid Leukemia.
Frontiers in oncology, 2018Co-Authors: John Anto Pulikkan, Lucio H. CastillaAbstract:Acute myeloid leukemia (AML) is a collection of hematologic malignancies with specific driver mutations that direct the pathology of the disease. The understanding of the origin and function of these mutations at early stages of transformation is critical to understand the etiology of the disease and for the design of effective therapies. The chromosome inversion inv(16) is thought to arise as a founding mutation in a hematopoietic stem cell (HSC) to produce preleukemic HSCs (preL-HSCs) with myeloid bias and differentiation block, and predisposed to AML. Studies in mice and human AML cells have established that inv(16) AML follows a clonal evolution model, in which preL-HSCs expressing the fusion protein CBFβ-SMMHC persist asymptomatic in the bone marrow. The emerging leukemia-initiating cells (LICs) are composed by the inv(16) and a Heterogeneous Set of mutations. In this review, we will discuss the current understanding of inv(16) preleukemia development, and the function of CBFβ-SMMHC related to preleukemia progression and LIC activity. We also discuss important open mechanistic questions in the etiology of inv(16) AML.
John Anto Pulikkan - One of the best experts on this subject based on the ideXlab platform.
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Preleukemia and Leukemia-Initiating Cell Activity in inv(16) Acute Myeloid Leukemia.
Frontiers in oncology, 2018Co-Authors: John Anto Pulikkan, Lucio H. CastillaAbstract:Acute myeloid leukemia (AML) is a collection of hematologic malignancies with specific driver mutations that direct the pathology of the disease. The understanding of the origin and function of these mutations at early stages of transformation is critical to understand the etiology of the disease and for the design of effective therapies. The chromosome inversion inv(16) is thought to arise as a founding mutation in a hematopoietic stem cell (HSC) to produce preleukemic HSCs (preL-HSCs) with myeloid bias and differentiation block, and predisposed to AML. Studies in mice and human AML cells have established that inv(16) AML follows a clonal evolution model, in which preL-HSCs expressing the fusion protein CBFβ-SMMHC persist asymptomatic in the bone marrow. The emerging leukemia-initiating cells (LICs) are composed by the inv(16) and a Heterogeneous Set of mutations. In this review, we will discuss the current understanding of inv(16) preleukemia development, and the function of CBFβ-SMMHC related to preleukemia progression and LIC activity. We also discuss important open mechanistic questions in the etiology of inv(16) AML.
Focht Erich - One of the best experts on this subject based on the ideXlab platform.
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Optimizing sparse matrix-vector multiplication in NEC SX-Aurora vector engine
2020Co-Authors: Gómez Crespo Constantino, Casas Guix Marc, Mantovani Filippo, Focht ErichAbstract:Sparse Matrix-Vector multiplication (SpMV) is an essential piece of code used in many High Performance Computing (HPC) applications. As previous literature shows, achieving efficient vectorization and performance in modern multi-core systems is nothing straightforward. It is important then to revisit the current stateof-the-art matrix formats and optimizations to be able to deliver deliver high performance in long vector architectures. In this tech-report, we describe how to develop an efficient implementation that achieves high throughput in the NEC Vector Engine: a 256 element-long vector architecture. Combining several pre-processing and kernel optimizations we obtain an average 12% improvement over a base SELLC-s implementation on a Heterogeneous Set of 24 matrices
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Optimizing sparse matrix-vector multiplication in NEC SX-Aurora vector engine
2020Co-Authors: Gómez Crespo Constantino, Casas Guix Marc, Mantovani Filippo, Focht ErichAbstract:Sparse Matrix-Vector multiplication (SpMV) is an essential piece of code used in many High Performance Computing (HPC) applications. As previous literature shows, achieving efficient vectorization and performance in modern multi-core systems is nothing straightforward. It is important then to revisit the current stateof-the-art matrix formats and optimizations to be able to deliver deliver high performance in long vector architectures. In this tech-report, we describe how to develop an efficient implementation that achieves high throughput in the NEC Vector Engine: a 256 element-long vector architecture. Combining several pre-processing and kernel optimizations we obtain an average 12% improvement over a base SELLC-s implementation on a Heterogeneous Set of 24 matrices.Preprin
Cheryl L Tran - One of the best experts on this subject based on the ideXlab platform.
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thrombotic microangiopathy care pathway a consensus statement for the mayo clinic complement alternative pathway thrombotic microangiopathy cap tma disease oriented group
Mayo Clinic Proceedings, 2016Co-Authors: Jeffrey L Winters, Sanjeev Sethi, David L Murray, Maria Alice V Willrich, Nelson Leung, Roshini S Abraham, Hatem Amer, William J Hogan, Ariela L Marshall, Cheryl L TranAbstract:Thrombotic microangiopathies (TMAs) comprise a Heterogeneous Set of conditions linked by a common histopathologic finding of endothelial damage resulting in microvascular thromboses and potentially serious complications. The typical clinical presentation is microangiopathic hemolytic anemia accompanied by thrombocytopenia with varying degrees of organ ischemia. The differential diagnoses are generally broad, while the workup is frequently complex and can be confusing. This statement represents the joint recommendations from a multidisciplinary team of Mayo Clinic physicians specializing in the management of TMA. It comprises a series of evidence- and consensus-based clinical pathways developed to allow a uniform approach to the spectrum of care including when to suspect TMA, what differential diagnoses to consider, which diagnostic tests to order, and how to provide initial empiric therapy, as well as some guidance on subsequent management.
Gómez Crespo Constantino - One of the best experts on this subject based on the ideXlab platform.
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Optimizing sparse matrix-vector multiplication in NEC SX-Aurora vector engine
2020Co-Authors: Gómez Crespo Constantino, Casas Guix Marc, Mantovani Filippo, Focht ErichAbstract:Sparse Matrix-Vector multiplication (SpMV) is an essential piece of code used in many High Performance Computing (HPC) applications. As previous literature shows, achieving efficient vectorization and performance in modern multi-core systems is nothing straightforward. It is important then to revisit the current stateof-the-art matrix formats and optimizations to be able to deliver deliver high performance in long vector architectures. In this tech-report, we describe how to develop an efficient implementation that achieves high throughput in the NEC Vector Engine: a 256 element-long vector architecture. Combining several pre-processing and kernel optimizations we obtain an average 12% improvement over a base SELLC-s implementation on a Heterogeneous Set of 24 matrices
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Optimizing sparse matrix-vector multiplication in NEC SX-Aurora vector engine
2020Co-Authors: Gómez Crespo Constantino, Casas Guix Marc, Mantovani Filippo, Focht ErichAbstract:Sparse Matrix-Vector multiplication (SpMV) is an essential piece of code used in many High Performance Computing (HPC) applications. As previous literature shows, achieving efficient vectorization and performance in modern multi-core systems is nothing straightforward. It is important then to revisit the current stateof-the-art matrix formats and optimizations to be able to deliver deliver high performance in long vector architectures. In this tech-report, we describe how to develop an efficient implementation that achieves high throughput in the NEC Vector Engine: a 256 element-long vector architecture. Combining several pre-processing and kernel optimizations we obtain an average 12% improvement over a base SELLC-s implementation on a Heterogeneous Set of 24 matrices.Preprin