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DDC: 570 × Subject: Signal Transduction ×

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    Non-thermal plasma activates human keratinocytes by stimulation of antioxidant and phase II pathways
    (San Francisco, Calif. : Lightbinders, 2015) Schmidt, Anke; Dietrich, Stephan; Steuer, Anna; Weltmann, Klaus-Dieter; von Woedtke, Thomas; Masur, Kai; Wende, Kristian
    Non-thermal atmospheric pressure plasma provides a novel therapeutic opportunity to control redox-based processes, e.g. wound healing, cancer, and inflammatory diseases. By spatial and time-resolved delivery of reactive oxygen and nitrogen species, it allows stimulation or inhibition of cellular processes in biological systems. Our data show that both gene and protein expression is highly affected by non-thermal plasma. Nuclear factor erythroid-related factor 2 (NRF2) and phase II enzyme pathway components were found to act as key controllers orchestrating the cellular response in keratinocytes. Additionally, glutathione metabolism, which is a marker for NRF2-related signaling events, was affected. Among the most robustly increased genes and proteins, heme oxygenase 1, NADPH-quinone oxidoreductase 1, and growth factors were found. The roles of NRF2 targets, investigated by siRNA silencing, revealed that NRF2 acts as an important switch for sensing oxidative stress events. Moreover, the influence of non-thermal plasma on the NRF2 pathway prepares cells against exogenic noxae and increases their resilience against oxidative species. Via paracrine mechanisms, distant cells benefit from cell-cell communication. The finding that non-thermal plasma triggers hormesis-like processes in keratinocytes facilitates the understanding of plasma-tissue interaction and its clinical application.
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    The complexity of gene expression dynamics revealed by permutation entropy
    (London : BioMed Central Ltd., 2010) Sun, Xiaoliang; Zou, Yong; Nikiforova, Victoria; Kurths, Jürgen; Walther, Dirk
    Background: High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity.Results: Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes.Conclusions: We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data.