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Institution

University of Wisconsin-Madison

EducationMadison, Wisconsin, United States
About: University of Wisconsin-Madison is a education organization based out in Madison, Wisconsin, United States. It is known for research contribution in the topics: Population & Gene. The organization has 108707 authors who have published 237594 publications receiving 11883575 citations.


Papers
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Journal ArticleDOI
TL;DR: In vitro differentiation, enrichment, and transplantation of neural precursor cells from human ES cells are described, depicting humanES cells as a source of transplantable neural precursors for possible nervous system repair.
Abstract: The remarkable developmental potential and replicative capacity of human embryonic stem (ES) cells promise an almost unlimited supply of specific cell types for transplantation therapies. Here we describe the in vitro differentiation, enrichment, and transplantation of neural precursor cells from human ES cells. Upon aggregation to embryoid bodies, differentiating ES cells formed large numbers of neural tube-like structures in the presence of fibroblast growth factor 2 (FGF-2). Neural precursors within these formations were isolated by selective enzymatic digestion and further purified on the basis of differential adhesion. Following withdrawal of FGF-2, they differentiated into neurons, astrocytes, and oligodendrocytes. After transplantation into the neonatal mouse brain, human ES cell-derived neural precursors were incorporated into a variety of brain regions, where they differentiated into both neurons and astrocytes. No teratoma formation was observed in the transplant recipients. These results depict human ES cells as a source of transplantable neural precursors for possible nervous system repair.

1,982 citations

Journal ArticleDOI
TL;DR: In this paper, the possible responses of ecosystem processes to rising atmospheric CO2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics.
Abstract: The possible responses of ecosystem processes to rising atmospheric CO2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO2 (Wigley et al. 1991), and by climate changes resulting from effective CO2 concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2-SUL. Simulations with changing CO2 alone show a widely distributed terrestrial carbon sink of 1.4‐3.8 Pg C y ‐1 during the 1990s, rising to 3.7‐8.6 Pg C y ‐1 a century later. Simulations including climate change show a reduced sink both today (0.6‐ 3.0 Pg C y ‐1 ) and a century later (0.3‐6.6 Pg C y ‐1 ) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO2 effects at high CO2 concentrations. Four out of the six models show a further, climate-induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO2 concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO2 concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO2 and climate change. They reveal major uncertainties about the response of NEP to climate

1,982 citations

Journal ArticleDOI
TL;DR: This paper presents a new state-of-the-art implementation of the iChEM (Collaborative Innovation Center of Chemistry for Energy Materials) Key Laborotary of Catalysis, which automates the very labor-intensive and therefore expensive and therefore time-heavy and expensive process ofalysis.
Abstract: and Fuels Changzhi Li,† Xiaochen Zhao,† Aiqin Wang,† George W. Huber,†,‡ and Tao Zhang*,† †State Key Laborotary of Catalysis, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China ‡Department of Chemical and Biological Engineering, University of WisconsinMadison, Madison, Wisconsin 53706, United States

1,977 citations

Journal ArticleDOI
TL;DR: The history and philosophy of the Condor project is provided and how it has interacted with other projects and evolved along with the field of distributed computing is described.
Abstract: SUMMARY Since 1984, the Condor project has enabled ordinary users to do extraordinary computing. Today, the project continues to explore the social and technical problems of cooperative computing on scales ranging from the desktop to the world-wide computational Grid. In this paper, we provide the history and philosophy of the Condor project and describe how it has interacted with other projects and evolved along with the field of distributed computing. We outline the core components of the Condor system and describe how the technology of computing must correspond to social structures. Throughout, we reflect on the lessons of experience and chart the course travelled by research ideas as they grow into production systems. Copyright c � 2005 John Wiley & Sons, Ltd.

1,969 citations


Authors

Showing all 109671 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Ronald C. Kessler2741332328983
Gordon H. Guyatt2311620228631
Yi Chen2174342293080
David Miller2032573204840
Robert M. Califf1961561167961
Ronald Klein1941305149140
Joan Massagué189408149951
Jens K. Nørskov184706146151
Terrie E. Moffitt182594150609
H. S. Chen1792401178529
Ramachandran S. Vasan1721100138108
Masayuki Yamamoto1711576123028
Avshalom Caspi170524113583
Jiawei Han1681233143427
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023333
20221,391
202110,151
20209,483
20199,278
20188,546