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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 & Stars. The organization has 44686 authors who have published 95840 publications receiving 2907492 citations.


Papers
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Journal ArticleDOI
TL;DR: A case study of the New York Times coverage of nuclear technology from 1945 to the present shows that LDA is a useful tool for analysing trends and patterns in news content in large digital news archives relatively quickly.
Abstract: The huge collections of news content which have become available through digital technologies both enable and warrant scientific inquiry, challenging journalism scholars to analyse unprecedented amounts of texts. We propose Latent Dirichlet Allocation (LDA) topic modelling as a tool to face this challenge. LDA is a cutting edge technique for content analysis, designed to automatically organize large archives of documents based on latent topics, measured as patterns of word (co-)occurrence. We explain how this technique works, how different choices by the researcher affect the results and how the results can be meaningfully interpreted. To demonstrate its usefulness for journalism research, we conducted a case study of the New York Times coverage of nuclear technology from 1945 to the present, partially replicating a study by Gamson and Modigliani. This shows that LDA is a useful tool for analysing trends and patterns in news content in large digital news archives relatively quickly.

342 citations

Journal ArticleDOI
TL;DR: A well-resolved phylogeny of the main lineages of basidiomycetes is presented which suggests that the Sebacinaceae is the most basal group with known mycorrhizal members, and it is evident that there is a cosm of mycor Rhizal biodiversity yet to be discovered in this group.

341 citations

Journal ArticleDOI
TL;DR: A critical review of the recent contributions to iodine‐based, contrast‐enhanced CT research is provided to enable researchers just beginning to employ contrast enhancement to make sense of this complex new landscape of methodologies.
Abstract: Morphologists have historically had to rely on destructive procedures to visualize the three-dimensional (3-D) anatomy of animals. More recently, however, non-destructive techniques have come to the forefront. These include X-ray computed tomography (CT), which has been used most commonly to examine the mineralized, hard-tissue anatomy of living and fossil metazoans. One relatively new and potentially transformative aspect of current CT-based research is the use of chemical agents to render visible, and differentiate between, soft-tissue structures in X-ray images. Specifically, iodine has emerged as one of the most widely used of these contrast agents among animal morphologists due to its ease of handling, cost effectiveness, and differential affinities for major types of soft tissues. The rapid adoption of iodine-based contrast agents has resulted in a proliferation of distinct specimen preparations and scanning parameter choices, as well as an increasing variety of imaging hardware and software preferences. Here we provide a critical review of the recent contributions to iodine-based, contrast-enhanced CT research to enable researchers just beginning to employ contrast enhancement to make sense of this complex new landscape of methodologies. We provide a detailed summary of recent case studies, assess factors that govern success at each step of the specimen storage, preparation, and imaging processes, and make recommendations for standardizing both techniques and reporting practices. Finally, we discuss potential cutting-edge applications of diffusible iodine-based contrast-enhanced computed tomography (diceCT) and the issues that must still be overcome to facilitate the broader adoption of diceCT going forward.

341 citations

Journal ArticleDOI
TL;DR: This study evaluated immunological changes during SIT in pollinosis with a focus on type I allergy and found thatType I allergy patients are more likely to benefit from SIT treatment.
Abstract: Summary Background and Objective The mechanisms operative in specific immunotherapy (SIT) of Type I allergy are not completely understood. In the present study we evaluated immunological changes during SIT in pollinosis. Method Eight patients suffering from pollinosis (monosensitized to grass pollen) were treated with conventional SIT. All subjects had IgE specific for Phi p 1. a major allergen of timothy grass. In vitro changes in the immunological reactivity to grass pollen extract and to recombinant Phi p 1 were evaluated. Subjects were examined at three occasions: before, after 3 months and after I year of SIT. Results Serological analysis revealed a marked increase of grass pollen- and Phi p 1-specific IgG, titres of specific IgE did not change significantly. Lymphoproliferative responses to grass pollen extract and rPhl p 1 were reduced already after 3 months of treatment. Accordingly, the cloning efficiency for Ph1 p 1-specific T-cell clones (TCC) dropped markedly in all patients. The majority of allergen-specific TCC raised before SIT revealed a TH2-like pattern of cytokine production. TCC established after SIT revealed TH1 characteristics. This shift was due to a decrease in IL-4 rather than an increase in IFN-production by T cells. Investigations of the epitopes recognized by T cells before and after SIT did not reveal the outgrowth of new (ldquo;protecting”) specificities. We could not observe induction of allergen-speeific CD8+ lymphocytes (supressor cells). Conclusion Our data indicate that — on the level of TH lymphocytes — SIT induces tolerance to the allergen and a modulation of the cytokine pattern produced in response to allergen stimulation.

340 citations

Journal ArticleDOI
TL;DR: The amount of local anesthetic for 3‐in‐1 blocks can be reduced by using US guidance compared with the conventional NS‐guided technique.

340 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
20214,479
20204,533
20194,225