scispace - formally typeset
Search or ask a question
Institution

University of Graz

EducationGraz, Steiermark, Austria
About: University of Graz is a education organization based out in Graz, Steiermark, Austria. It is known for research contribution in the topics: Population & Context (language use). The organization has 17934 authors who have published 37489 publications receiving 1110980 citations. The organization is also known as: Carolo Franciscea Graecensis & Karl Franzens Universität.


Papers
More filters
Journal ArticleDOI
TL;DR: The industrial recycling network as mentioned in this paper integrates the re-use of "former waste" by an inter-company matching of production processes, which helps to reduce material and energy throughput in the economic system to sustainable levels.

227 citations

Journal ArticleDOI
TL;DR: It is shown that nucleocytosolic acetyl-coenzyme A (AcCoA) production is a metabolic repressor of autophagy during aging in yeast, and brain-specific knockdown of Drosophila AcCoA synthetase was sufficient to enhance autophagic protein clearance and prolong lifespan.

227 citations

Journal ArticleDOI
TL;DR: This review depicts the molecular and morphological steps of vasculogenesis and angiogenesis, which can give further insights into human placental development and maturation disorders.

226 citations

Journal ArticleDOI
TL;DR: In this article, a hypoplastic constitutive model for the three-dimensional nonlinear stress-strain and dilatant volume change behavior of granular materials is presented.

226 citations

Journal ArticleDOI
TL;DR: To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD is targeted.
Abstract: Objective To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD. Methods We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study. Results PSMD was associated with processing speed in all study samples with SVD (p-values between 2.8 × 10−3 and 1.8 × 10−10). PSMD explained most of the variance in processing speed (R2 ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers. Interpretation PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581–592.

226 citations


Authors

Showing all 18136 results

NameH-indexPapersCitations
David Haussler172488224960
Russel J. Reiter1691646121010
Frederik Barkhof1541449104982
Philip Scheltens1401175107312
Christopher D.M. Fletcher13867482484
Jennifer S. Haas12884071315
Jelena Krstic12683973457
Michael A. Kamm12463753606
Frances H. Arnold11951049651
Gert Pfurtscheller11750762873
Georg Kresse111430244729
Manfred T. Reetz11095942941
Alois Fürstner10845943085
David N. Herndon108122754888
David J. Williams107206062440
Network Information
Related Institutions (5)
Ludwig Maximilian University of Munich
161.5K papers, 5.7M citations

93% related

Heidelberg University
119.1K papers, 4.6M citations

93% related

University of Zurich
124K papers, 5.3M citations

90% related

Uppsala University
107.5K papers, 4.2M citations

90% related

University of Amsterdam
140.8K papers, 5.9M citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023174
2022422
20211,775
20201,759
20191,649
20181,541