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Institution

University of California, Irvine

EducationIrvine, California, United States
About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.
Topics: Population, Galaxy, Poison control, Cancer, Gene


Papers
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Journal ArticleDOI
TL;DR: The role of heme in more active enzymatic chemical transformation began to be appreciated just after the discovery by Mason1 and Hayaishi2 that O2 O atoms can be enzymatically incorporated into organic substrates which represented the seminal discovery of oxygenases.
Abstract: Metalloporphyrins are widely used throughout the biosphere and of these heme (iron protoporphyrin IX, Fig. 1) is one of the most abundant and widely used. Heme shuttles electrons between proteins as in mitochondrial respiration or transports and stores O2 as with the globins. The role of heme in more active enzymatic chemical transformation began to be appreciated just after the discovery by Mason1 and Hayaishi2 that O2 O atoms can be enzymatically incorporated into organic substrates which represented the seminal discovery of oxygenases. While the enzymes used in these studies did not contain heme, it was not too long before heme-containing oxygenases also were discovered. In 1958 Klingenberg3 and Garfinkel4 found an unusual pigment in microsomes that when reduced in the presence of CO generated a spectrum with a peak at 450 nm instead of the expected 420 nm peak. Hence the name P450 was born. In 1964 Omura and Sato5,6 showed that this “pigment” is actually a protein and the function of this strange heme protein became clear in a seminal study by Estabrook et al.7 that demonstrated the involvement of the 450 nm pigment in steroid hydroxylation. Thus by the mid-1960s it was established that heme plays an active role in biology by somehow catalyzing the hydroxylation of organic substrates. While these discoveries certainly mark the beginning of modern approaches to studying heme enzyme oxygenases, the enzymatic role of heme dates much earlier to 1903 when horseradish peroxidase (HRP) was described.8 Indeed, owing to the ease of purification and stability of the various intermediates, HRP dominated heme enzyme studies until P450 was discovered. Figure 1 Structure of iron protoporphyrin IX. Heme enzymes can catalyze both reductive and oxidative chemistry but here we focus on those that catalyze oxidation reactions, and especially those for which crystal structures are available. There are two broad classes of heme enzyme oxidants: oxygenases that use O2 to oxidize, usually oxygenate, substrates and peroxidases that use H2O2 to oxidize, but not normally oxygenate, substrates. Of the two oxidants molecular oxygen is the most unusual because even though the oxidation of nearly all biological molecules by O2 is a thermodynamically favorable process, O2 is not a reactive molecule. The reason, of course, is that there is a large kinetic barrier to these reactions owing to O2 being a paramagnetic molecule so the reaction between a majority of biological molecules that have paired spins is a spin forbidden process. Overcoming this barrier is why Nature recruited transition metals and heme into enzyme active sites. As shown in Fig. 2, heme oxygenases bind O2 and store the O2 oxidizing equivalents in the iron, porphyrin, and/or amino acid side chains for further selective oxidation of substrates. Peroxidases use H2O2 as the oxidant and while not having the O2 spin barrier, H2O2 presents its own problems. The reaction between H2O2 and transition metals generates toxic hydroxyl radicals in the well known Fenton chemistry9 which would be highly destructive to enzyme active sites. As illustrated in Fig. 2, all heme oxidases are at some point in the catalytic cycle peroxidases. Molecular oxygen must first be reduced by two electrons to the peroxide level before the interesting chemistry starts: cleavage of the O-O bond. This bond can cleave either homolytically, which gives two hydroxyl radicals, or heterolytically to effectively give H2O and a naked O atom with only 6 valence electrons. Since the release of hydroxyl radicals in the active site must, in most cases, be avoided Nature has engineered heme enzyme active sites to ensure that the heterolytic pathway dominates. Figure 2 Oxygen and peroxide activation by heme enzymes. Oxygenases like P450 must have the iron reduced to ferrous (Fe(II) or Fe2+) before O2 can bind. The oxy complex is best described as ferric-superoxide, Fe(III)-OO−. A second electron transfer results ... The list of heme enzymes is substantial and thus it is necessary to be selective on which to discuss in detail. It may appear that a disproportionate amount of space is devoted to peroxidases and P450s. This is true and admittedly reflects the author’s own interests and area of expertise. Additionally, however, peroxidases are the most extensively studied heme enzymes and have provided fundamental insights into the chemistry and structure shared by many other enzymes. The other enzymes to be discussed were selected owing to both subtle variations on common themes and novel features that Nature selected for specific biological function.

954 citations

02 Jul 2011
TL;DR: The framework sheds light on the different kinds of autoencoders, their learning complexity, their horizontal and vertical composability in deep architectures, their critical points, and their fundamental connections to clustering, Hebbian learning, and information theory.
Abstract: Autoencoders play a fundamental role in unsupervised learning and in deep architectures for transfer learning and other tasks. In spite of their fundamental role, only linear autoencoders over the real numbers have been solved analytically. Here we present a general mathematical framework for the study of both linear and non-linear autoencoders. The framework allows one to derive an analytical treatment for the most non-linear autoencoder, the Boolean autoencoder. Learning in the Boolean autoencoder is equivalent to a clustering problem that can be solved in polynomial time when the number of clusters is small and becomes NP complete when the number of clusters is large. The framework sheds light on the different kinds of autoencoders, their learning complexity, their horizontal and vertical composability in deep architectures, their critical points, and their fundamental connections to clustering, Hebbian learning, and information theory.

954 citations

Journal ArticleDOI
TL;DR: In this article, the authors estimate that East Antarctica is close to a balanced mass budget, but large losses of ice occur in the narrow outlet channels of West Antarctic glaciers and at the northern tip of the Antarctic peninsula.
Abstract: Observed estimates of ice losses in Antarctica combined with regional modelling of ice accumulation in the interior suggest that East Antarctica is close to a balanced mass budget, but large losses of ice occur in the narrow outlet channels of West Antarctic glaciers and at the northern tip of the Antarctic peninsula.

952 citations

Journal ArticleDOI
29 Jun 2018-Science
TL;DR: In this paper, the authors examine barriers and opportunities associated with these difficult-to-decarbonize services and processes, including possible technological solutions and research and development priorities, and examine the use of existing technologies to meet future demands for these services without net addition of CO2 to the atmosphere.
Abstract: Some energy services and industrial processes-such as long-distance freight transport, air travel, highly reliable electricity, and steel and cement manufacturing-are particularly difficult to provide without adding carbon dioxide (CO2) to the atmosphere. Rapidly growing demand for these services, combined with long lead times for technology development and long lifetimes of energy infrastructure, make decarbonization of these services both essential and urgent. We examine barriers and opportunities associated with these difficult-to-decarbonize services and processes, including possible technological solutions and research and development priorities. A range of existing technologies could meet future demands for these services and processes without net addition of CO2 to the atmosphere, but their use may depend on a combination of cost reductions via research and innovation, as well as coordinated deployment and integration of operations across currently discrete energy industries.

951 citations

Journal ArticleDOI
TL;DR: Specific detailed recommendations for each level have been established in this document, which are intended to improve the rate of early suspicion and diagnosis of, and therefore early intervention for, autism.
Abstract: The Child Neurology Society and American Academy of Neurology recently proposed to formulate Practice Parameters for the Diagnosis and Evaluation of Autism for their memberships. This endeavor was expanded to include representatives from nine professional organizations and four parent organizations, with liaisons from the National Institutes of Health. This document was written by this multidisciplinary Consensus Panel after systematic analysis of over 2,500 relevant scientific articles in the literature. The Panel concluded that appropriate diagnosis of autism requires a dual-level approach: (a) routine developmental surveillance, and (b) diagnosis and evaluation of autism. Specific detailed recommendations for each level have been established in this document, which are intended to improve the rate of early suspicion and diagnosis of, and therefore early intervention for, autism.

950 citations


Authors

Showing all 47751 results

NameH-indexPapersCitations
Daniel Levy212933194778
Rob Knight2011061253207
Lewis C. Cantley196748169037
Dennis W. Dickson1911243148488
Terrie E. Moffitt182594150609
Joseph Biederman1791012117440
John R. Yates1771036129029
John A. Rogers1771341127390
Avshalom Caspi170524113583
Yang Gao1682047146301
Carl W. Cotman165809105323
John H. Seinfeld165921114911
Gregg C. Fonarow1611676126516
Jerome I. Rotter1561071116296
David Cella1561258106402
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
2023252
20221,224
20216,518
20206,348
20195,610