University of Düsseldorf

About: University of Düsseldorf is a education organization based out in Düsseldorf, Germany. It is known for research contribution in the topics: Population & Diabetes mellitus. The organization has 25225 authors who have published 49155 publications receiving 1946434 citations.

UVA irradiation induces collagenase in human dermal fibroblasts in vitro and in vivo.

Abstract: We report the effect of UVA irradiation on collagen metabolism of fibroblasts, including both synthesis of the collagen degrading enzyme collagenase and de novo synthesis of type I collagen as the major structural component of the dermis. For this purpose confluent fibroblast monolayers were irradiated under standardized conditions (5, 15, 35, 60 J/cm2 using UVASUN 3000, Mutzhas, Munich, FRG, and UV source Sellas sunlight type 2.001, Sellas, Gevelsberg, FRG). Subsequently, total RNA was isolated and subjected to dot blot and northern blot analysis using oligolabelled cDNA clones for human type I collagen, collagenase and beta-actin. Collagen type I and beta-actin mRNA levels remained unaltered following irradiation, suggesting that the synthetic pathway of collagen metabolism at the pretranslational level is not affected by short-term UVA irradiation. However, collagenase mRNA was found to be dose-dependently induced in fibroblasts after irradiation, thus probably contributing to the actinic damage to the dermis. These in vitro data were confirmed in vivo using in situ hybridization on frozen sections of biopsy material obtained from UVA irradiated patients.

Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac).

Abstract: The need to integrate massively increasing amounts of data on the mammalian brain has driven several ambitious neuroscientific database projects that were started during the last decade. Databasing the brain's anatomical connectivity as delivered by tracing studies is of particular importance as these data characterize fundamental structural constraints of the complex and poorly understood functional interactions between the components of real neural systems. Previous connectivity databases have been crucial for analysing anatomical brain circuitry in various species and have opened exciting new ways to interpret functional data, both from electrophysiological and from functional imaging studies. The eventual impact and success of connectivity databases, however, will require the resolution of several methodological problems that currently limit their use. These problems comprise four main points: (i) objective representation of coordinate-free, parcellation-based data, (ii) assessment of the reliability and precision of individual data, especially in the presence of contradictory reports, (iii) data mining and integration of large sets of partially redundant and contradictory data, and (iv) automatic and reproducible transformation of data between incongruent brain maps. Here, we present the specific implementation of the 'collation of connectivity data on the macaque brain' (CoCoMac) database (http://www.cocomac.org). The design of this database addresses the methodological challenges listed above, and focuses on experimental and computational neuroscientists' needs to flexibly analyse and process the large amount of published experimental data from tracing studies. In this article, we explain step-by-step the conceptual rationale and methodology of CoCoMac and demonstrate its practical use by an analysis of connectivity in the prefrontal cortex.