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Institution

Boston University

EducationBoston, Massachusetts, United States
About: Boston University is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 48688 authors who have published 119622 publications receiving 6276020 citations. The organization is also known as: BU & Boston U.


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Journal ArticleDOI
17 Feb 2011-Nature
TL;DR: It is shown that enforced Tert or PGC-1α expression or germline deletion of p53 substantially restores PGC network expression, mitochondrial respiration, cardiac function and gluconeogenesis in the setting of telomere dysfunction.
Abstract: Telomere dysfunction activates p53-mediated cellular growth arrest, senescence and apoptosis to drive progressive atrophy and functional decline in high-turnover tissues. The broader adverse impact of telomere dysfunction across many tissues including more quiescent systems prompted transcriptomic network analyses to identify common mechanisms operative in haematopoietic stem cells, heart and liver. These unbiased studies revealed profound repression of peroxisome proliferator-activated receptor gamma, coactivator 1 alpha and beta (PGC-1α and PGC-1β, also known as Ppargc1a and Ppargc1b, respectively) and the downstream network in mice null for either telomerase reverse transcriptase (Tert) or telomerase RNA component (Terc) genes. Consistent with PGCs as master regulators of mitochondrial physiology and metabolism, telomere dysfunction is associated with impaired mitochondrial biogenesis and function, decreased gluconeogenesis, cardiomyopathy, and increased reactive oxygen species. In the setting of telomere dysfunction, enforced Tert or PGC-1α expression or germline deletion of p53 (also known as Trp53) substantially restores PGC network expression, mitochondrial respiration, cardiac function and gluconeogenesis. We demonstrate that telomere dysfunction activates p53 which in turn binds and represses PGC-1α and PGC-1β promoters, thereby forging a direct link between telomere and mitochondrial biology. We propose that this telomere-p53-PGC axis contributes to organ and metabolic failure and to diminishing organismal fitness in the setting of telomere dysfunction.

1,096 citations

Journal ArticleDOI
TL;DR: It is reported here that inherited variants in the SORL1 neuronal sorting receptor are associated with late-onset Alzheimer disease, and it is shown that SOR l1 directs trafficking of APP into recycling pathways and that when SORl1 is underexpressed, APP is sorted into Aβ-generating compartments.
Abstract: The recycling of the amyloid precursor protein (APP) from the cell surface via the endocytic pathways plays a key role in the generation of amyloid beta peptide (Abeta) in Alzheimer disease. We report here that inherited variants in the SORL1 neuronal sorting receptor are associated with late-onset Alzheimer disease. These variants, which occur in at least two different clusters of intronic sequences within the SORL1 gene (also known as LR11 or SORLA) may regulate tissue-specific expression of SORL1. We also show that SORL1 directs trafficking of APP into recycling pathways and that when SORL1 is underexpressed, APP is sorted into Abeta-generating compartments. These data suggest that inherited or acquired changes in SORL1 expression or function are mechanistically involved in causing Alzheimer disease.

1,093 citations

Journal ArticleDOI
Sekar Kathiresan1, Benjamin F. Voight1, Shaun Purcell2, Kiran Musunuru1, Diego Ardissino, Pier Mannuccio Mannucci3, Sonia S. Anand4, James C. Engert5, Nilesh J. Samani6, Heribert Schunkert7, Jeanette Erdmann7, Muredach P. Reilly8, Daniel J. Rader8, Thomas M. Morgan9, John A. Spertus10, Monika Stoll11, Domenico Girelli12, Pascal P. McKeown13, Christopher Patterson13, David S. Siscovick14, Christopher J. O'Donnell15, Roberto Elosua, Leena Peltonen16, Veikko Salomaa17, Stephen M. Schwartz14, Olle Melander18, David Altshuler1, Pier Angelica Merlini, Carlo Berzuini19, Luisa Bernardinelli19, Flora Peyvandi3, Marco Tubaro, Patrizia Celli, Maurizio Ferrario, Raffaela Fetiveau, Nicola Marziliano, Giorgio Casari20, Michele Galli, Flavio Ribichini12, Marco Rossi, Francesco Bernardi21, Pietro Zonzin, Alberto Piazza22, Jean Yee14, Yechiel Friedlander23, Jaume Marrugat, Gavin Lucas, Isaac Subirana, Joan Sala24, Rafael Ramos, James B. Meigs1, Gordon H. Williams1, David M. Nathan1, Calum A. MacRae1, Aki S. Havulinna17, Göran Berglund18, Joel N. Hirschhorn1, Rosanna Asselta, Stefano Duga, Marta Spreafico25, Mark J. Daly1, James Nemesh2, Joshua M. Korn1, Steven A. McCarroll1, Aarti Surti2, Candace Guiducci2, Lauren Gianniny2, Daniel B. Mirel2, Melissa Parkin2, Noël P. Burtt2, Stacey Gabriel2, John R. Thompson6, Peter S. Braund6, Benjamin J. Wright6, Anthony J. Balmforth26, Stephen G. Ball26, Alistair S. Hall26, Patrick Linsel-Nitschke7, Wolfgang Lieb7, Andreas Ziegler7, Inke R. König7, Christian Hengstenberg27, Marcus Fischer27, Klaus Stark27, Anika Grosshennig7, Michael Preuss7, H-Erich Wichmann28, Stefan Schreiber29, Willem H. Ouwehand19, Panos Deloukas30, Michael Scholz, François Cambien31, Mingyao Li8, Zhen Chen8, Robert L. Wilensky8, William H. Matthai8, Atif Qasim8, Hakon Hakonarson8, Joe Devaney32, Mary-Susan Burnett32, Augusto D. Pichard32, Kenneth M. Kent32, Lowell F. Satler32, Joseph M. Lindsay32, Ron Waksman32, Stephen E. Epstein32, Thomas Scheffold, Klaus Berger11, Andreas Huge11, Nicola Martinelli12, Oliviero Olivieri12, Roberto Corrocher12, Hilma Holm33, Gudmar Thorleifsson33, Unnur Thorsteinsdottir34, Kari Stefansson34, Ron Do5, Changchun Xie4, David S. Siscovick14 
TL;DR: SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with my Cardiovascular Infarction risk.
Abstract: We conducted a genome-wide association study testing single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for association with early-onset myocardial infarction in 2,967 cases and 3,075 controls We carried out replication in an independent sample with an effective sample size of up to 19,492 SNPs at nine loci reached genome-wide significance: three are newly identified (21q22 near MRPS6-SLC5A3-KCNE2, 6p24 in PHACTR1 and 2q33 in WDR12) and six replicated prior observations1, 2, 3, 4 (9p21, 1p13 near CELSR2-PSRC1-SORT1, 10q11 near CXCL12, 1q41 in MIA3, 19p13 near LDLR and 1p32 near PCSK9) We tested 554 common copy number polymorphisms (>1% allele frequency) and none met the pre-specified threshold for replication (P < 10-3) We identified 8,065 rare CNVs but did not detect a greater CNV burden in cases compared to controls, in genes compared to the genome as a whole, or at any individual locus SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with myocardial infarction risk

1,092 citations

Journal ArticleDOI
TL;DR: In this paper, a stochastic dynamic programming model is used to model the operating flexibility of a multinational corporation to shift production between two manufacturing plants located in different countries, the value of which is dependent upon the real exchange rate.
Abstract: The multinational corporation is a network of activities located in different countries. The value of this network derives from the opportunity to benefit from uncertainty through the coordination of subsidiaries which are geographically dispersed. We model this coordination as the operating flexibility to shift production between two manufacturing plants located in different countries. A stochastic dynamic programming model treats explicitly this flexibility as equivalent to owning an option, the value of which is dependent upon the real exchange rate. The model is extended to analyze hysteresis effects and within-country growth options. We show that the management of across-border coordination has led to changes in the heuristic rules used for performance evaluation and transfer pricing.

1,092 citations

Proceedings ArticleDOI
01 Oct 1993
TL;DR: In this paper, the authors demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal behavior, and that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks.
Abstract: We demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal behavior, and that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks. Intuitively, the critical characteristic of this self-similar traffic is that there is no natural length of a "burst": at every time scale ranging from a few milliseconds to minutes and hours, similar-looking traffic bursts are evident; we find that aggregating streams of such traffic typically intensifies the self-similarity ("burstiness") instead of smoothing it.Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a discussion of the underlying mathematical and statistical properties of self-similarity and their relationship with actual network behavior. We also consider some implications for congestion control in high-bandwidth networks and present traffic models based on self-similar stochastic processes that are simple, accurate, and realistic for aggregate traffic.

1,089 citations


Authors

Showing all 49233 results

NameH-indexPapersCitations
Walter C. Willett3342399413322
Robert Langer2812324326306
Meir J. Stampfer2771414283776
Ronald C. Kessler2741332328983
JoAnn E. Manson2701819258509
Albert Hofman2672530321405
George M. Whitesides2401739269833
Paul M. Ridker2331242245097
Eugene Braunwald2301711264576
Ralph B. D'Agostino2261287229636
David J. Hunter2131836207050
Daniel Levy212933194778
Christopher J L Murray209754310329
Tamara B. Harris2011143163979
André G. Uitterlinden1991229156747
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023223
2022810
20216,942
20206,837
20196,120
20185,593