Institution
University of Marburg
Education•Marburg, Germany•
About: University of Marburg is a education organization based out in Marburg, Germany. It is known for research contribution in the topics: Population & Virus. The organization has 23195 authors who have published 42907 publications receiving 1506069 citations. The organization is also known as: Philipps University of Marburg & Philipps-Universität.
Topics: Population, Virus, Gene, Exciton, Photoluminescence
Papers published on a yearly basis
Papers
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15 Mar 2007-Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
TL;DR: The work of the AASM Visual Scoring Task Force is described, including methodology, a literature review and the rationale behind the new rules, which define onset and termination of REM sleep periods and propose alternative measures for non-alpha generating subjects.
Abstract: The 1968 Rechtschaffen and Kales (R & K) sleep scoring man- ual was published 15 years after REM sleep was discovered. Advances in the ensuing 28 years warranted a re-look at visual scoring of sleep stages. This paper describes the work of the AASM Visual Scoring Task Force, including methodology, a literature review and the rationale behind the new rules. Reliability studies of R & K scoring were reviewed; reliabil- ity was low for stage one and moderate for slow wave sleep. Evidence indicated that K complexes and slow waves are expressed maximal fron- tally, spindles centrally and alpha rhythm over the occipital region. Three derivations of EEG, two of electro-oculography, and one of chin EMG were recommended. Scoring by 30-second epochs was retained. New terminology for sleep stages was proposed. Attenuation of alpha rhythm was determined to be the most valid electrophysiological marker of sleep onset. Alternative measures were proposed for non-alpha generating subjects. K complexes associated with arousals were determined to be insufficient alone to define the new stage N2. No evidence was found to justify dividing slow wave sleep into two stages. No reasons were found to alter the current slow wave amplitude criteria at any age. The phenomena of REM sleep were defined. The rules for defining onset and termination of REM sleep periods were simplified. Movement time was eliminated and major body movements defined. Studies are needed to test the reliability of the new rules. Future advances in technology may require modification of these rules with time.
955 citations
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TL;DR: Exendin-4 is an agonist and exendin-(9-39)-amide is a specific GLP-1 receptor antagonist, and both peptides stimulated the proinsulin gene expression at the level of transcription and reduced the effects of cAMP.
940 citations
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TL;DR: In this article, a systematic theory for the scaling of the Nusselt number Nu and of the Reynolds number Re in strong Rayleigh-Benard convection is suggested and shown to be compatible with recent experiments.
Abstract: A systematic theory for the scaling of the Nusselt number Nu and of the A systematic theory for the scaling of the Nusselt number Nu and of the Reynolds number Re in strong Rayleigh–Benard convection is suggested and shown to be compatible with recent experiments. It assumes a coherent large-scale convection roll (‘wind of turbulence’) and is based on the dynamical equations both in the bulk and in the boundary layers. Several regimes are identified in the Rayleigh number Ra versus Prandtl number Pr phase space, defined by whether the boundary layer or the bulk dominates the global kinetic and thermal dissipation, respectively, and by whether the thermal or the kinetic boundary layer is thicker. The crossover between the regimes is calculated. In the regime which has most frequently been studied in experiment (Ra [less, similar] 1011) the leading terms are Nu [similar] Ra1/4Pr1/8, Re [similar] Ra1/2Pr[minus sign]3/4 for Pr [less, similar] 1 and Nu [similar] Ra1/4Pr[minus sign]1/12, Re [similar] Ra1/2Pr[minus sign]5/6 for Pr [greater, similar] 1. In most measurements these laws are modified by additive corrections from the neighbouring regimes so that the impression of a slightly larger (effective) Nu vs. Ra scaling exponent can arise. The most important of the neighbouring regimes towards large Ra are a regime with scaling Nu [similar] Ra1/2Pr1/2, Re [similar] Ra1/2Pr[minus sign]1/2 for medium Pr (‘Kraichnan regime’), a regime with scaling Nu [similar] Ra1/5Pr1/5, Re [similar] Ra2/5Pr[minus sign]3/5 for small Pr, a regime with Nu [similar] Ra1/3, Re [similar] Ra4/9Pr[minus sign]2/3 for larger Pr, and a regime with scaling Nu [similar] Ra3/7Pr[minus sign]1/7, Re [similar] Ra4/7Pr[minus sign]6/7 for even larger Pr. In particular, a linear combination of the ¼ and the 1/3 power laws for Nu with Ra, Nu = 0.27Ra1/4 + 0.038Ra1/3 (the prefactors follow from experiment), mimics a 2/7 power-law exponent in a regime as large as ten decades. For very large Ra the laminar shear boundary layer is speculated to break down through the non-normal-nonlinear transition to turbulence and another regime emerges.
933 citations
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TL;DR: Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.
Abstract: Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.
930 citations
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University of Marburg1, University of Erlangen-Nuremberg2, Rovira i Virgili University3, University of Göttingen4, Max Planck Society5, University of California, Los Angeles6, International School for Advanced Studies7, University of Melbourne8, University of Trieste9, Ikerbasque10, University of Toronto11, Nanyang Technological University12, National Institutes of Health13, Stanford University14, Shanghai Jiao Tong University15, Tongji University16, University of Seville17, Karolinska Institutet18, Drexel University19, Sichuan University20, Rice University21, Northwestern University22, University of Basel23, Zhejiang University24, Heidelberg University25, University of Tokyo26, Harvard University27, University of Utah28, University of Michigan29, Swiss Federal Laboratories for Materials Science and Technology30, Seoul National University31, Saarland University32, Columbia University33, Chinese Academy of Sciences34, Kazan Federal University35, Emory University36, University of California, Irvine37, Autonomous University of Barcelona38, University of Massachusetts Amherst39, Pennsylvania State University40, Ghent University41, Imperial College London42, National Tsing Hua University43, South China University of Technology44, University of Ulm45, Hebrew University of Jerusalem46, Huazhong University of Science and Technology47, Peking University48
TL;DR: An overview of recent developments in nanomedicine is provided and the current challenges and upcoming opportunities for the field are highlighted and translation to the clinic is highlighted.
Abstract: The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic.
926 citations
Authors
Showing all 23488 results
Name | H-index | Papers | Citations |
---|---|---|---|
John C. Morris | 183 | 1441 | 168413 |
Russel J. Reiter | 169 | 1646 | 121010 |
Martin J. Blaser | 147 | 820 | 104104 |
Christopher T. Walsh | 139 | 819 | 74314 |
Markus Cristinziani | 131 | 1140 | 84538 |
James C. Paulson | 126 | 443 | 52152 |
Markus F. Neurath | 124 | 934 | 62376 |
Nicholas W. Wood | 123 | 614 | 66270 |
Florian Lang | 116 | 1421 | 66496 |
Howard I. Maibach | 116 | 1821 | 60765 |
Thomas G. Ksiazek | 113 | 398 | 46108 |
Frank Glorius | 113 | 663 | 49305 |
Eberhard Ritz | 111 | 1109 | 61530 |
Manfred T. Reetz | 110 | 959 | 42941 |
Wolfgang H. Oertel | 110 | 653 | 51147 |