Open Access
Refine
Document Type
- Article (156) (remove)
Keywords
- virtual reality (4)
- Business Process Management Systems (2)
- Fuzzy Logic (2)
- software engineering (2)
- visualization (2)
- Assignment Automation (1)
- Augmented Reality (1)
- Business Process Modeling Notation (1)
- Git (1)
- Indusrie 4.0 (1)
Institute
Organische Chemie
(2021)
Identification and quantitative segmentation of individual blood vessels in mice visualized with preclinical imaging techniques is a tedious, manual or semiautomated task that can require weeks of reviewing hundreds of levels of individual data sets. Preclinical imaging, such as micro-magnetic resonance imaging (μMRI) can produce tomographic datasets of murine vasculature across length scales and organs, which is of outmost importance to study tumor progression, angiogenesis, or vascular risk factors for diseases such as Alzheimer’s. Training a neural network capable of accurate segmentation results requires a sufficiently large amount of labelled data, which takes a long time to compile. Recently, several reasonably automated approaches have emerged in the preclinical context but still require significant manual input and are less accurate than the deep learning approach presented in this paper—quantified by the Dice score. In this work, the implementation of a shallow, three-dimensional U-Net architecture for the segmentation of vessels in murine brains is presented, which is (1) open-source, (2) can be achieved with a small dataset (in this work only 8 μMRI imaging stacks of mouse brains were available), and (3) requires only a small subset of labelled training data. The presented model is evaluated together with two post-processing methodologies using a cross-validation, which results in an average Dice score of 61.34% in its best setup. The results show, that the methodology is able to detect blood vessels faster and more reliably compared to state-of-the-art vesselness filters with an average Dice score of 43.88% for the used dataset.
Development and trial of a blended learning concept for students in engineering study courses
(2018)
On the road again: Wie kann die Arbeitsgestaltung zur Arbeitsfreude bei mobiler Arbeit beitragen?
(2020)
Direct digital manufacturing – the role of cost accounting for online hubs to access industry 4.0
(2021)
Pharmaceutical agents or drugs often have a pronounced impact on protein-protein interactions in cells, and in particular, cell membranes. Changes of molecular conformations as well as of intermolecular interactions may affect dipole-dipole interaction between chromophoric groups, which can be proven by measuring the Förster resonance energy transfer (FRET). If these chromophores are located within or in close proximity to the plasma membrane, they are excited preferentially by an evanescent electromagnetic wave upon total internal reflection (TIR) of an incident laser beam. For the TIR-FRET screening of larger cell collectives, we performed three separate steps: (1) setting up of a membrane associated test system for probing the interaction between the epidermal growth factor receptor (EGFR) and the growth factor receptor-bound protein 2; (2) use of the Epac-SH188 sensor for quantitative evaluation under the microscope; and (3) application of a TIR fluorescence reader to probe the interaction of GFP with Nile Red. In the first two steps, we measured FRET from cyan (CFP) to yellow fluorescent protein (YFP) by spectral analysis and fluorescence lifetime imaging (FLIM) upon illumination of whole cells (epi-illumination) as well as selective illumination of their plasma membranes by TIR. In particular, TIR excitation permitted FRET measurements with high sensitivity and low background. The Epac sensor showed a more rapid response to pharmaceutical agents, e.g., Forskolin or the A2B adenosine receptor agonist NECA, in close proximity to the plasma membrane compared to the cytosol. Finally, FRET from a membrane associated GFP to Nile Red was used to test a multi-well TIR fluorescence reader with simultaneous detection of a larger number of samples.
Fluorescence Microscopy-Based Quantitation of GLUT4 Translocation: High Throughput or High Content?
(2020)
Integrated laser based pre‐tempering at laser welding of AISI 1045 steel by using 3D‐scanner optics
(2021)
Application of a robotic THz imaging system for sub-surface analysis of ancient human remains
(2019)
We used a robotic-based THz imaging system to investigate the sub-surface structure of an artificially mummified ancient Egyptian human left hand. The results obtained are compared to the results of a conventional CT and a micro-CT scan. Using such a robotic THz system promises new insights into the sub-surface structure of human remains. The depth resolution of the THz images exceeds the resolution of a conventional CT scan and is comparable with a micro-CT scan. The advantage of THz measurements over micro-CT scans is the fact that even comparatively large samples, like complete bodies, can be scanned. These would not fit into a conventional micro-CT scanner.
Designing a Randomized Trial with an Age Simulation Suit-Representing People with Health Impairments
(2020)
The Dimensional Accuracy of Thin-Walled Parts Manufactured by Laser-Powder Bed Fusion Process
(2020)
The over-expression and aggregation of α-synuclein (αSyn) are linked to the onset and pathology of Parkinson's disease. Native monomeric αSyn exists in an intrinsically disordered ensemble of interconverting conformations, which has made its therapeutic targeting by small molecules highly challenging. Nonetheless, here we successfully target the monomeric structural ensemble of αSyn and thereby identify novel drug-like small molecules that impact multiple pathogenic processes. Using a surface plasmon resonance high-throughput screen, in which monomeric αSyn is incubated with microchips arrayed with tethered compounds, we identified novel αSyn interacting drug-like compounds. Because these small molecules could impact a variety of αSyn forms present in the ensemble, we tested representative hits for impact on multiple αSyn malfunctions in vitro and in cells including aggregation and perturbation of vesicular dynamics. We thereby identified a compound that inhibits αSyn misfolding and is neuroprotective, multiple compounds that restore phagocytosis impaired by αSyn overexpression, and a compound blocking cellular transmission of αSyn. Our studies demonstrate that drug-like small molecules that interact with native αSyn can impact a variety of its pathological processes. Thus, targeting the intrinsically disordered ensemble of αSyn offers a unique approach to the development of small molecule research tools and therapeutics for Parkinson's disease.