Publications by authors named "T Wieland"

Nucleoside diphosphate kinases (NDPKs) are encoded by genes and exist in various isoforms. Based on interactions with other proteins, they are involved in signal transduction, development and pathological processes such as tumorigenesis, metastasis and heart failure. In this study, we report a 1.

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Signal-responsive gene expression is essential for vascular development, yet the mechanisms integrating signaling inputs with transcriptional activities are largely unknown. Here we show that RNF20, the primary E3 ubiquitin ligase for histone H2B, plays a multifaceted role in sprouting angiogenesis. RNF20 mediates RNA polymerase (Pol II) promoter-proximal pausing at genes highly paused in endothelial cells, involved in VEGFA signaling, stress response, cell cycle control and mRNA splicing.

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Article Synopsis
  • Pathological cardiac remodeling can lead to heart failure, and the study focused on two long non-coding RNAs (lncRNAs) that are upregulated in failing hearts.
  • Overexpressing these lncRNAs in mice worsened heart dysfunction and increased hypertrophy and fibrosis in response to pressure overload.
  • Knocking out these lncRNAs reduced heart damage and improved blood vessel growth but also led to sudden death in some mice, highlighting their complex role in heart failure and potential as therapeutic targets.
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  • The rise of personalized medicine has highlighted the importance of comprehensive genomic profiling (CGP), but challenges in assay standardization and understanding bioinformatics hinder uniform implementation.
  • Two in-house CGP assays were compared in a research context, revealing both agreements and significant differences in detecting genetic variants and providing clinical recommendations.
  • These discrepancies were attributed to varied bioinformatics methods for variant analysis, emphasizing the need for careful consideration in implementing high-quality CGP to ensure consistent and reliable genomic insights.
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Background: Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on their specific content. Assessing the reidentification risk of genetic data is complex, yet there is a lack of guidelines or recommendations that support data processors in performing such an evaluation.

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