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Institution

University of Maryland, College Park

EducationCollege Park, Maryland, United States
About: University of Maryland, College Park is a education organization based out in College Park, Maryland, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 60446 authors who have published 155900 publications receiving 7273683 citations. The organization is also known as: The University of Maryland & College Park.


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Journal ArticleDOI
TL;DR: The optimal simulation protocol for each program has been implemented in CHARMM-GUI and is expected to be applicable to the remainder of the additive C36 FF including the proteins, nucleic acids, carbohydrates, and small molecules.
Abstract: Proper treatment of nonbonded interactions is essential for the accuracy of molecular dynamics (MD) simulations, especially in studies of lipid bilayers. The use of the CHARMM36 force field (C36 FF) in different MD simulation programs can result in disagreements with published simulations performed with CHARMM due to differences in the protocols used to treat the long-range and 1-4 nonbonded interactions. In this study, we systematically test the use of the C36 lipid FF in NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM. A wide range of Lennard-Jones (LJ) cutoff schemes and integrator algorithms were tested to find the optimal simulation protocol to best match bilayer properties of six lipids with varying acyl chain saturation and head groups. MD simulations of a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer were used to obtain the optimal protocol for each program. MD simulations with all programs were found to reasonably match the DPPC bilayer properties (surface area per lipid, chain order para...

2,182 citations

Journal ArticleDOI
Barbara A. Methé1, Karen E. Nelson1, Mihai Pop2, Heather Huot Creasy3  +250 moreInstitutions (42)
14 Jun 2012-Nature
TL;DR: The Human Microbiome Project (HMP) Consortium has established a population-scale framework which catalyzed significant development of metagenomic protocols resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomics data available to the scientific community as mentioned in this paper.
Abstract: A variety of microbial communities and their genes (microbiome) exist throughout the human body, playing fundamental roles in human health and disease. The NIH funded Human Microbiome Project (HMP) Consortium has established a population-scale framework which catalyzed significant development of metagenomic protocols resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 to 18 body sites up to three times, which to date, have generated 5,177 microbial taxonomic profiles from 16S rRNA genes and over 3.5 Tb of metagenomic sequence. In parallel, approximately 800 human-associated reference genomes have been sequenced. Collectively, these data represent the largest resource to date describing the abundance and variety of the human microbiome, while providing a platform for current and future studies.

2,172 citations

Journal ArticleDOI
Christopher J L Murray1, Jerry Puthenpurakal Abraham2, Mohammed K. Ali3, Miriam Alvarado1, Charles Atkinson1, Larry M. Baddour4, David Bartels5, Emelia J. Benjamin6, Kavi Bhalla5, Gretchen L. Birbeck7, Ian Bolliger1, Roy Burstein1, Emily Carnahan1, Honglei Chen8, David Chou1, Sumeet S. Chugh9, Aaron Cohen10, K. Ellicott Colson1, Leslie T. Cooper11, William G. Couser12, Michael H. Criqui13, Kaustubh Dabhadkar3, Nabila Dahodwala14, Goodarz Danaei5, Robert P. Dellavalle15, Don C. Des Jarlais16, Daniel Dicker1, Eric L. Ding5, E. Ray Dorsey17, Herbert C. Duber1, Beth E. Ebel12, Rebecca E. Engell1, Majid Ezzati18, David T. Felson6, Mariel M. Finucane5, Seth Flaxman19, Abraham D. Flaxman1, Thomas D. Fleming1, Mohammad H. Forouzanfar1, Greg Freedman1, Michael Freeman1, Sherine E. Gabriel4, Emmanuela Gakidou1, Richard F. Gillum20, Diego Gonzalez-Medina1, Richard A. Gosselin21, Bridget F. Grant8, Hialy R. Gutierrez22, Holly Hagan23, Rasmus Havmoeller24, Rasmus Havmoeller9, Howard J. Hoffman8, Kathryn H. Jacobsen25, Spencer L. James1, Rashmi Jasrasaria1, Sudha Jayaraman5, Nicole E. Johns1, Nicholas J Kassebaum12, Shahab Khatibzadeh5, Lisa M. Knowlton5, Qing Lan, Janet L Leasher26, Stephen S Lim1, John K Lin5, Steven E. Lipshultz27, Stephanie J. London8, Rafael Lozano, Yuan Lu5, Michael F. Macintyre1, Leslie Mallinger1, Mary M. McDermott28, Michele Meltzer29, George A. Mensah8, Catherine Michaud30, Ted R. Miller31, Charles Mock12, Terrie E. Moffitt32, Ali A. Mokdad1, Ali H. Mokdad1, Andrew E. Moran22, Dariush Mozaffarian5, Dariush Mozaffarian33, Tasha B. Murphy1, Mohsen Naghavi1, K.M. Venkat Narayan3, Robert G. Nelson8, Casey Olives12, Saad B. Omer3, Katrina F Ortblad1, Bart Ostro34, Pamela M. Pelizzari35, David Phillips1, C. Arden Pope36, Murugesan Raju37, Dharani Ranganathan1, Homie Razavi, Beate Ritz38, Frederick P. Rivara12, Thomas Roberts1, Ralph L. Sacco27, Joshua A. Salomon5, Uchechukwu K.A. Sampson39, Ella Sanman1, Amir Sapkota40, David C. Schwebel41, Saeid Shahraz42, Kenji Shibuya43, Rupak Shivakoti17, Donald H. Silberberg14, Gitanjali M Singh5, David Singh44, Jasvinder A. Singh41, David A. Sleet, Kyle Steenland3, Mohammad Tavakkoli5, Jennifer A. Taylor45, George D. Thurston23, Jeffrey A. Towbin46, Monica S. Vavilala12, Theo Vos1, Gregory R. Wagner47, Martin A. Weinstock48, Marc G. Weisskopf5, James D. Wilkinson27, Sarah Wulf1, Azadeh Zabetian3, Alan D. Lopez49 
14 Aug 2013-JAMA
TL;DR: To measure the burden of diseases, injuries, and leading risk factors in the United States from 1990 to 2010 and to compare these measurements with those of the 34 countries in the Organisation for Economic Co-operation and Development (OECD), systematic analysis of descriptive epidemiology was used.
Abstract: Importance Understanding the major health problems in the United States and how they are changing over time is critical for informing national health policy. Objectives To measure the burden of diseases, injuries, and leading risk factors in the United States from 1990 to 2010 and to compare these measurements with those of the 34 countries in the Organisation for Economic Co-operation and Development (OECD) countries. Design We used the systematic analysis of descriptive epidemiology of 291 diseases and injuries, 1160 sequelae of these diseases and injuries, and 67 risk factors or clusters of risk factors from 1990 to 2010 for 187 countries developed for the Global Burden of Disease 2010 Study to describe the health status of the United States and to compare US health outcomes with those of 34 OECD countries. Years of life lost due to premature mortality (YLLs) were computed by multiplying the number of deaths at each age by a reference life expectancy at that age. Years lived with disability (YLDs) were calculated by multiplying prevalence (based on systematic reviews) by the disability weight (based on population-based surveys) for each sequela; disability in this study refers to any short- or long-term loss of health. Disability-adjusted life-years (DALYs) were estimated as the sum of YLDs and YLLs. Deaths and DALYs related to risk factors were based on systematic reviews and meta-analyses of exposure data and relative risks for risk-outcome pairs. Healthy life expectancy (HALE) was used to summarize overall population health, accounting for both length of life and levels of ill health experienced at different ages. Results US life expectancy for both sexes combined increased from 75.2 years in 1990 to 78.2 years in 2010; during the same period, HALE increased from 65.8 years to 68.1 years. The diseases and injuries with the largest number of YLLs in 2010 were ischemic heart disease, lung cancer, stroke, chronic obstructive pulmonary disease, and road injury. Age-standardized YLL rates increased for Alzheimer disease, drug use disorders, chronic kidney disease, kidney cancer, and falls. The diseases with the largest number of YLDs in 2010 were low back pain, major depressive disorder, other musculoskeletal disorders, neck pain, and anxiety disorders. As the US population has aged, YLDs have comprised a larger share of DALYs than have YLLs. The leading risk factors related to DALYs were dietary risks, tobacco smoking, high body mass index, high blood pressure, high fasting plasma glucose, physical inactivity, and alcohol use. Among 34 OECD countries between 1990 and 2010, the US rank for the age-standardized death rate changed from 18th to 27th, for the age-standardized YLL rate from 23rd to 28th, for the age-standardized YLD rate from 5th to 6th, for life expectancy at birth from 20th to 27th, and for HALE from 14th to 26th. Conclusions and Relevance From 1990 to 2010, the United States made substantial progress in improving health. Life expectancy at birth and HALE increased, all-cause death rates at all ages decreased, and age-specific rates of years lived with disability remained stable. However, morbidity and chronic disability now account for nearly half of the US health burden, and improvements in population health in the United States have not kept pace with advances in population health in other wealthy nations.

2,159 citations

Journal ArticleDOI
TL;DR: In this paper, the impact of acquisitions on the subsequent innovation performance of acquiring firms in the chemicals industry is examined, and the authors distinguish between technological acquisitions, acquisitions in which technology is a component of the acquired firm's assets, and non-technological acquisitions: acquisitions that do not involve a technological component.
Abstract: This paper examines the impact of acquisitions on the subsequent innovation performance of acquiring firms in the chemicals industry We distinguish between technological acquisitions, acquisitions in which technology is a component of the acquired firm's assets, and nontechnological acquisitions: acquisitions that do not involve a technological component We develop a framework relating acquisitions to firm innovation performance and develop a set of measures for quantifying the technological inputs a firm obtains through acquisitions We find that within technological acquisitions absolute size of the acquired knowledge base enhances innovation performance, while relative size of the acquired knowledge base reduces innovation output The relatedness of acquired and acquiring knowledge bases has a nonlinear impact on innovation output Nontechnological acquisitions do not have a significant effect on subsequent innovation output Copyright © 2001 John Wiley & Sons, Ltd

2,147 citations

Journal ArticleDOI
TL;DR: In this article, a theoretical model linking empowering leadership with creativity via several intervening variables was built and tested, and they found that, as anticipated, empowering leadership positively affected psychological empowerment, which in turn influenced both intrinsic motivation and creative process engagement.
Abstract: Synthesizing theories of leadership, empowerment, and creativity, this research built and tested a theoretical model linking empowering leadership with creativity via several intervening variables. Using survey data from professional employees and their supervisors in a large information technology company in China, we found that, as anticipated, empowering leadership positively affected psychological empowerment, which in turn influenced both intrinsic motivation and creative process engagement. These latter two variables then had a positive influence on creativity. Empowerment role identity moderated the link between empowering leadership and psychological empowerment, whereas leader encouragement of creativity moderated the connection between psychological empowerment and creative process engagement.

2,123 citations


Authors

Showing all 60868 results

NameH-indexPapersCitations
Timothy M. Heckman170754141237
Donald G. Truhlar1651518157965
Tobin J. Marks1591621111604
Yongsun Kim1562588145619
Richard J. Davidson15660291414
Terrence J. Sejnowski155845117382
Roberto Romero1511516108321
Jongmin Lee1502257134772
Kevin J. Gaston15075085635
Bernard Moss14783076991
Steven L. Salzberg147407231756
Gregory R Snow1471704115677
Fabian Walter14699983016
Timothy P. Hughes14583191357
Marco Zanetti1451439104610
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023162
2022754
20216,744
20207,208
20197,072
20186,716