Publications by authors named "V Stierle"

Azobenzene analogues of the tubulin polymerisation inhibitor combretastatin A4 (PSTs) were previously developed to optically control microtubule dynamics in living systems, with subsecond response time and single-cell spatial precision, by reversible photoswitching of their bioactivity with near-UV/visible light. First-generation PSTs were sufficiently potent and photoswitchable for use in live cells and embryos. However, the link between their seconds-scale and hours-scale bioactivity remained untested.

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There is increasing evidence that exposure to weak electromagnetic fields (EMFs) generated by modern telecommunications or household appliances has physiological consequences, including reports of electromagnetic field hypersensitivity (EHS) leading to adverse health effects. Although symptoms can be serious, no underlying mechanism for EHS is known and there is no general cure or effective therapy. Here, we present the case study of a self-reported EHS patient whose symptoms include severe headaches, generalized fatigue, cardiac arrhythmia, attention and memory deficit, and generalized systemic pain within minutes of exposure to telecommunications (Wifi, cellular phones), high tension lines and electronic devices.

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In addition to its role in translation termination, eRF3A has been implicated in the nonsense-mediated mRNA decay (NMD) pathway through its interaction with UPF1. NMD is a RNA quality control mechanism, which detects and degrades aberrant mRNAs as well as some normal transcripts including those that harbour upstream open reading frames in their 5' leader sequence. In this study, we used RNA-sequencing and ribosome profiling to perform a genome wide analysis of the effect of either eRF3A or UPF1 depletion in human cells.

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To support the emerging battle against antimicrobial resistance (AMR), detection methods that allow fast and accurate antimicrobial susceptibility testing (AST) are urgently needed. The early identification and application of an appropriate antibiotic treatment leads to lower mortality rates and substantial cost savings and prevents the development of resistant pathogens. In this work, we present a diffraction-based method, which is capable of quantitative bacterial growth, mobility, and susceptibility measurements.

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In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it an inexpensive tool for label-free, continuous live cell imaging, yet there is only little work on analysing such time-lapse image sequences. We propose (1) a cell detector for LFM images based on fully convolutional networks and residual learning, and (2) a probabilistic model based on moral lineage tracing that explicitly handles multiple detections and temporal successor hypotheses by clustering and tracking simultaneously.

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