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Florian Horn

Researcher at University of Erlangen-Nuremberg

Publications -  28
Citations -  466

Florian Horn is an academic researcher from University of Erlangen-Nuremberg. The author has contributed to research in topics: Image quality & Interferometry. The author has an hindex of 12, co-authored 28 publications receiving 388 citations.

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Identification of cellular deoxyhypusine synthase as a novel target for antiretroviral therapy

TL;DR: It is demonstrated that inhibition of DHS by CNI-1493 or RNA interference efficiently suppressed the retroviral replication cycle in cell culture and primary cells and no measurable drug-induced adverse effects on cell cycle transition, apoptosis, and general cytotoxicity were observed.
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The Adenovirus Type 5 E1B-55K Oncoprotein Actively Shuttles in Virus-Infected Cells, Whereas Transport of E4orf6 Is Mediated by a CRM1-Independent Mechanism

TL;DR: It is demonstrated that adenovirus infection does not inhibit the function of the E1B-55K nuclear export signal and that E1Bs shuttles in infected cells, and this results strengthen the potential role of E 1B- 55K as the “driving force” forAdenoviral late mRNA export.
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Improved reconstruction of phase-stepping data for Talbot–Lau x-ray imaging

TL;DR: Three improvements to the phase-stepping reconstruction are proposed to use prior knowledge to compute more accurate grating positions to reduce moiré artifacts, to utilize noise variance information to reduce dark-field and phase noise in high-visibility acquisitions, and to perform correction of an estimation bias in the interferometer visibility.
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Optimisation of image reconstruction for phase-contrast x-ray Talbot–Lau imaging with regard to mechanical robustness

TL;DR: An algorithm to determine the differential phase-contrast image with the help of just one calibration image, which is valid for a long time-period and it is possible to save measurement-time, as it is not necessary to take a reference image for each measurement.
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A beam hardening and dispersion correction for x-ray dark-field radiography

TL;DR: The authors show that the influence of and dispersion can be quantified by simulation and, thus, measured image data can be corrected and an increase in contrast is shown compared to the original image, which might simplify a further image-based diagnosis.