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Institution

University of Vienna

EducationVienna, Austria
About: University of Vienna is a education organization based out in Vienna, Austria. It is known for research contribution in the topics: Population & Context (language use). The organization has 44686 authors who have published 95840 publications receiving 2907492 citations.


Papers
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Journal ArticleDOI
TL;DR: The microbial carbon pump is proposed as a conceptual framework to address the important, multifaceted biogeochemical problem of fixed carbon in the upper ocean.
Abstract: The biological pump is a process whereby CO(2) in the upper ocean is fixed by primary producers and transported to the deep ocean as sinking biogenic particles or as dissolved organic matter. The fate of most of this exported material is remineralization to CO(2), which accumulates in deep waters until it is eventually ventilated again at the sea surface. However, a proportion of the fixed carbon is not mineralized but is instead stored for millennia as recalcitrant dissolved organic matter. The processes and mechanisms involved in the generation of this large carbon reservoir are poorly understood. Here, we propose the microbial carbon pump as a conceptual framework to address this important, multifaceted biogeochemical problem.

1,194 citations

Journal ArticleDOI
TL;DR: In tumor bearing mice, application of non-PEGylated complexes through the tail vein resulted in reporter gene expression in tail and lung, but severe toxicity was observed in some mice, while PEGylation of the complexes mediated reporter gene transfer to the tumor without significant toxicity.
Abstract: We investigated the in vitro and in vivo properties of DNA/transferrin-polyethylenimine (800 kDa) complexes before and after covalent coupling of poly(ethylene glycol) (PEG). Upon incubation with plasma, the positively charged non-PEGylated DNA complexes form aggregates. Plasma proteins such as IgM, fibrinogen, fibronectin and complement C3 were found to bind to non-PEGylated DNA complexes. At DNA concentrations relevant for in vivo gene delivery a strong aggregation of erythrocytes was also observed. PEGylation of the complexes strongly reduces plasma protein binding and erythrocyte aggregation. Furthermore, PEGylated complex size was stabilized and had a reduced surface charge. Prolonged circulation in the blood of the PEGylated complexes was also observed when injected intravenously. In tumor bearing mice, application of non-PEGylated complexes through the tail vein resulted in reporter gene expression in tail and lung, but severe toxicity was observed in some mice. In contrast, PEGylated complexes mediated reporter gene transfer to the tumor without significant toxicity.

1,188 citations

Journal ArticleDOI
TL;DR: Ranibizumab monotherapy and combined with laser provided superior visual acuity gain over standard laser in patients with visual impairment due to DME and had a safety profile in DME similar to that in age-related macular degeneration.

1,187 citations

Journal ArticleDOI
TL;DR: The phylogenetic terrace aware (PTA) data structure is introduced for the efficient analysis under partition models and it is shown that an implementation of PTA in IQ-TREE leads to a substantial speedup of up to 4.5 and 8 times compared with the standard IQ- TREE and RAxML implementations, respectively.
Abstract: In phylogenomics the analysis of concatenated gene alignments, the so-called supermatrix, is commonly accompanied by the assumption of partition models. Under such models each gene, or more generally partition, is allowed to evolve under its own evolutionary model. Although partition models provide a more comprehensive analysis of supermatrices, missing data may hamper the tree search algorithms due to the existence of phylogenetic (partial) terraces. Here, we introduce the phylogenetic terrace aware (PTA) data structure for the efficient analysis under partition models. In the presence of missing data PTA exploits (partial) terraces and induced partition trees to save computation time. We show that an implementation of PTA in IQ-TREE leads to a substantial speedup of up to 4.5 and 8 times compared with the standard IQ-TREE and RAxML implementations, respectively. PTA is generally applicable to all types of partition models and common topological rearrangements thus can be employed by all phylogenomic inference software.

1,183 citations

Journal ArticleDOI
TL;DR: Two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences are presented, including the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum information about a Metagenome-Assembled Genomes (MIMAG), including estimates of genome completeness and contamination.
Abstract: We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.

1,171 citations


Authors

Showing all 45262 results

NameH-indexPapersCitations
Tomas Hökfelt158103395979
Wolfgang Wagner1562342123391
Hans Lassmann15572479933
Stanley J. Korsmeyer151316113691
Charles B. Nemeroff14997990426
Martin A. Nowak14859194394
Barton F. Haynes14491179014
Yi Yang143245692268
Peter Palese13252657882
Gérald Simonneau13058790006
Peter M. Elias12758149825
Erwin F. Wagner12537559688
Anton Zeilinger12563171013
Wolfgang Waltenberger12585475841
Michael Wagner12435154251
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023419
20221,085
20214,482
20204,534
20194,225