TY - JOUR A1 - Andronic, Joseph A1 - Shirakashi, Ryo A1 - Pickel, Simone U. A1 - Westerling, Katherine M. A1 - Klein, Teresa A1 - Holm, Thorge A1 - Sauer, Markus A1 - Sukhorukov, Vladimir L. T1 - Hypotonic Activation of the Myo-Inositol Transporter SLC5A3 in HEK293 Cells Probed by Cell Volumetry, Confocal and Super-Resolution Microscopy JF - PLoS One N2 - Swelling-activated pathways for myo-inositol, one of the most abundant organic osmolytes in mammalian cells, have not yet been identified. The present study explores the SLC5A3 protein as a possible transporter of myo-inositol in hyponically swollen HEK293 cells. To address this issue, we examined the relationship between the hypotonicity-induced changes in plasma membrane permeability to myo-inositol Pino [m/s] and expression/localization of SLC5A3. Pino values were determined by cell volumetry over a wide tonicity range (100–275 mOsm) in myo-inositol-substituted solutions. While being negligible under mild hypotonicity (200–275 mOsm), Pino grew rapidly at osmolalities below 200 mOsm to reach a maximum of ∼3 nm/s at 100–125 mOsm, as indicated by fast cell swelling due to myo-inositol influx. The increase in Pino resulted most likely from the hypotonicity-mediated incorporation of cytosolic SLC5A3 into the plasma membrane, as revealed by confocal fluorescence microscopy of cells expressing EGFP-tagged SLC5A3 and super-resolution imaging of immunostained SLC5A3 by direct stochastic optical reconstruction microscopy (dSTORM). dSTORM in hypotonic cells revealed a surface density of membrane-associated SLC5A3 proteins of 200–2000 localizations/μm2. Assuming SLC5A3 to be the major path for myo-inositol, a turnover rate of 80–800 myo-inositol molecules per second for a single transporter protein was estimated from combined volumetric and dSTORM data. Hypotonic stress also caused a significant upregulation of SLC5A3 gene expression as detected by semiquantitative RT-PCR and Western blot analysis. In summary, our data provide first evidence for swelling-mediated activation of SLC5A3 thus suggesting a functional role of this transporter in hypotonic volume regulation of mammalian cells. KW - electrolytes KW - isotonic KW - membrane proteins KW - cell membranes KW - hypotonic KW - hypotonic solutions KW - tonicity KW - permeability Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-126408 VL - 10 IS - 3 ER - TY - JOUR A1 - Reinhard, Sebastian A1 - Helmerich, Dominic A. A1 - Boras, Dominik A1 - Sauer, Markus A1 - Kollmannsberger, Philip T1 - ReCSAI: recursive compressed sensing artificial intelligence for confocal lifetime localization microscopy JF - BMC Bioinformatics N2 - Background Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method. Results Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality. Conclusions Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility. KW - compressed sensing KW - AI KW - SMLM KW - FLIMbee KW - dSTORM Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-299768 VL - 23 IS - 1 ER - TY - THES A1 - Sauer, Markus T1 - Mixed-Reality for Enhanced Robot Teleoperation T1 - Mixed-Reality zur verbesserten Fernbedienung von Robotern N2 - In den letzten Jahren ist die Forschung in der Robotik soweit fortgeschritten, dass die Mensch-Maschine Schnittstelle zunehmend die kritischste Komponente für eine hohe Gesamtperformanz von Systemen zur Navigation und Koordination von Robotern wird. In dieser Dissertation wird untersucht wie Mixed-Reality Technologien für Nutzerschnittstellen genutzt werden können, um diese Gesamtperformanz zu erhöhen. Hierzu werden Konzepte und Technologien entwickelt, die durch Evaluierung mit Nutzertest ein optimiertes und anwenderbezogenes Design von Mixed-Reality Nutzerschnittstellen ermöglichen. Er werden somit sowohl die technische Anforderungen als auch die menschlichen Faktoren für ein konsistentes Systemdesign berücksichtigt. Nach einer detaillierten Problemanalyse und der Erstellung eines Systemmodels, das den Menschen als Schlüsselkomponente mit einbezieht, wird zunächst die Anwendung der neuartigen 3D-Time-of-Flight Kamera zur Navigation von Robotern, aber auch für den Einsatz in Mixed-Reality Schnittstellen analysiert und optimiert. Weiterhin wird gezeigt, wie sich der Netzwerkverkehr des Videostroms als wichtigstes Informationselement der meisten Nutzerschnittstellen für die Navigationsaufgabe auf der Netzwerk Applikationsebene in typischen Multi-Roboter Netzwerken mit dynamischen Topologien und Lastsituation optimieren lässt. Hierdurch ist es möglich in sonst in sonst typischen Ausfallszenarien den Videostrom zu erhalten und die Bildrate zu stabilisieren. Diese fortgeschrittenen Technologien werden dann auch dem entwickelten Konzept der generischen 3D Mixed Reality Schnittselle eingesetzt. Dieses Konzept ermöglicht eine integrierte 3D Darstellung der verfügbaren Information, so dass räumliche Beziehungen von Informationen aufrechterhalten werden und somit die Anzahl der mentalen Transformationen beim menschlichen Bediener reduziert wird. Gleichzeitig werden durch diesen Ansatz auch immersive Stereo Anzeigetechnologien unterstützt, welche zusätzlich das räumliche Verständnis der entfernten Situation fördern. Die in der Dissertation vorgestellten und evaluierten Ansätze nutzen auch die Tatsache, dass sich eine lokale Autonomie von Robotern heute sehr robust realisieren lässt. Dies wird zum Beispiel zur Realisierung eines Assistenzsystems mit variabler Autonomie eingesetzt. Hierbei erhält der Fernbediener über eine Kraftrückkopplung kombiniert mit einer integrierten Augmented Reality Schnittstelle, einen Eindruck über die Situation am entfernten Arbeitsbereich, aber auch über die aktuelle Navigationsintention des Roboters. Die durchgeführten Nutzertests belegen die signifikante Steigerung der Navigationsperformanz durch den entwickelten Ansatz. Die robuste lokale Autonomie ermöglicht auch den in der Dissertation eingeführten Ansatz der prädiktiven Mixed-Reality Schnittstelle. Die durch diesen Ansatz entkoppelte Regelschleife über den Menschen ermöglicht es die Sichtbarkeit von unvermeidbaren Systemverzögerungen signifikant zu reduzieren. Zusätzlich können durch diesen Ansatz beide für die Navigation hilfreichen Blickwinkel in einer 3D-Nutzerschnittstelle kombiniert werden – der exozentrische Blickwinkel und der egozentrische Blickwinkel als Augmented Reality Sicht. N2 - With the progress in robotics research the human machine interfaces reach more and more the status of being the major limiting factor for the overall system performance of a system for remote navigation and coordination of robots. In this monograph it is elaborated how mixed reality technologies can be applied for the user interfaces in order to increase the overall system performance. Concepts, technologies, and frameworks are developed and evaluated in user studies which enable for novel user-centered approaches to the design of mixed-reality user interfaces for remote robot operation. Both the technological requirements and the human factors are considered to achieve a consistent system design. Novel technologies like 3D time-of-flight cameras are investigated for the application in the navigation tasks and for the application in the developed concept of a generic mixed reality user interface. In addition it is shown how the network traffic of a video stream can be shaped on application layer in order to reach a stable frame rate in dynamic networks. The elaborated generic mixed reality framework enables an integrated 3D graphical user interface. The realized spatial integration and visualization of available information reduces the demand for mental transformations for the human operator and supports the use of immersive stereo devices. The developed concepts make also use of the fact that local robust autonomy components can be realized and thus can be incorporated as assistance systems for the human operators. A sliding autonomy concept is introduced combining force and visual augmented reality feedback. The force feedback component allows rendering the robot's current navigation intention to the human operator, such that a real sliding autonomy with seamless transitions is achieved. The user-studies prove the significant increase in navigation performance by application of this concept. The generic mixed reality user interface together with robust local autonomy enables a further extension of the teleoperation system to a short-term predictive mixed reality user interface. With the presented concept of operation, it is possible to significantly reduce the visibility of system delays for the human operator. In addition, both advantageous characteristics of a 3D graphical user interface for robot teleoperation- an exocentric view and an augmented reality view – can be combined. T3 - Forschungsberichte in der Robotik = Research Notes in Robotics - 5 KW - Mobiler Roboter KW - Autonomer Roboter KW - Mensch-Maschine-Schnittstelle KW - Mixed Reality KW - Mensch-Roboter-Interaktion KW - Teleoperation KW - Benutzerschnittstelle KW - Robotik KW - Mensch-Maschine-System KW - Human-Robot-Interaction KW - Teleoperation KW - User Interface Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-55083 SN - 978-3-923959-67-9 ER -