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    Immune cell‐based microrobots for remote magnetic actuation, antitumor activity, and medical imaging
    (2024) Dogan, Nihal Olcay; Suadiye, Eylül; Wrede, Paul; Lazovic, Jelena; Dayan, Cem Balda; Soon, Ren Hao; Aghakhani, Amirreza; Richter, Gunther; Sitti, Metin
    Translating medical microrobots into clinics requires tracking, localization, and performing assigned medical tasks at target locations, which can only happen when appropriate design, actuation mechanisms, and medical imaging systems are integrated into a single microrobot. Despite this, these parameters are not fully considered when designing macrophage‐based microrobots. This study presents living macrophage‐based microrobots that combine macrophages with magnetic Janus particles coated with FePt nanofilm for magnetic steering and medical imaging and bacterial lipopolysaccharides for stimulating macrophages in a tumor‐killing state. The macrophage‐based microrobots combine wireless magnetic actuation, tracking with medical imaging techniques, and antitumor abilities. These microrobots are imaged under magnetic resonance imaging and optoacoustic imaging in soft‐tissue‐mimicking phantoms and ex vivo conditions. Magnetic actuation and real‐time imaging of microrobots are demonstrated under static and physiologically relevant flow conditions using optoacoustic imaging. Further, macrophage‐based microrobots are magnetically steered toward urinary bladder tumor spheroids and imaged with a handheld optoacoustic device, where the microrobots significantly reduce the viability of tumor spheroids. The proposed approach demonstrates the proof‐of‐concept feasibility of integrating macrophage‐based microrobots into clinic imaging modalities for cancer targeting and intervention, and can also be implemented for various other medical applications.
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    Modified TMV particles as beneficial scaffolds to present sensor enzymes
    (2015) Koch, Claudia; Wabbel, Katrin; Eber, Fabian J.; Krolla-Sidenstein, Peter; Azucena, Carlos; Gliemann, Hartmut; Eiben, Sabine; Geiger, Fania; Wege, Christina
    Tobacco mosaic virus (TMV) is a robust nanotubular nucleoprotein scaffold increasingly employed for the high density presentation of functional molecules such as peptides, fluorescent dyes, and antibodies. We report on its use as advantageous carrier for sensor enzymes. A TMV mutant with a cysteine residue exposed on every coat protein (CP) subunit (TMVCys) enabled the coupling of bifunctional maleimide-polyethylene glycol (PEG)-biotin linkers (TMVCys/Bio). Its surface was equipped with two streptavidin [SA]-conjugated enzymes: glucose oxidase ([SA]-GOx) and horseradish peroxidase ([SA]-HRP). At least 50% of the CPs were decorated with a linker molecule, and all thereof with active enzymes. Upon use as adapter scaffolds in conventional “high-binding” microtiter plates, TMV sticks allowed the immobilization of up to 45-fold higher catalytic activities than control samples with the same input of enzymes. Moreover, they increased storage stability and reusability in relation to enzymes applied directly to microtiter plate wells. The functionalized TMV adsorbed to solid supports showed a homogeneous distribution of the conjugated enzymes and structural integrity of the nanorods upon transmission electron and atomic force microscopy. The high surface-increase and steric accessibility of the viral scaffolds in combination with the biochemical environment provided by the plant viral coat may explain the beneficial effects. TMV can, thus, serve as a favorable multivalent nanoscale platform for the ordered presentation of bioactive proteins.
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    Automated imaging-based abdominal organ segmentation and quality control in 20,000 participants of the UK Biobank and German National Cohort Studies
    (2022) Kart, Turkay; Fischer, Marc; Winzeck, Stefan; Glocker, Ben; Bai, Wenjia; Bülow, Robin; Emmel, Carina; Friedrich, Lena; Kauczor, Hans-Ulrich; Keil, Thomas; Kröncke, Thomas; Mayer, Philipp; Niendorf, Thoralf; Peters, Annette; Pischon, Tobias; Schaarschmidt, Benedikt M.; Schmidt, Börge; Schulze, Matthias B.; Umutle, Lale; Völzke, Henry; Küstner, Thomas; Bamberg, Fabian; Schölkopf, Bernhard; Rückert, Daniel; Gatidis, Sergios
    Large epidemiological studies such as the UK Biobank (UKBB) or German National Cohort (NAKO) provide unprecedented health-related data of the general population aiming to better understand determinants of health and disease. As part of these studies, Magnetic Resonance Imaging (MRI) is performed in a subset of participants allowing for phenotypical and functional characterization of different organ systems. Due to the large amount of imaging data, automated image analysis is required, which can be performed using deep learning methods, e. g. for automated organ segmentation. In this paper we describe a computational pipeline for automated segmentation of abdominal organs on MRI data from 20,000 participants of UKBB and NAKO and provide results of the quality control process. We found that approx. 90% of data sets showed no relevant segmentation errors while relevant errors occurred in a varying proportion of data sets depending on the organ of interest. Image-derived features based on automated organ segmentations showed relevant deviations of varying degree in the presence of segmentation errors. These results show that large-scale, deep learning-based abdominal organ segmentation on MRI data is feasible with overall high accuracy, but visual quality control remains an important step ensuring the validity of down-stream analyses in large epidemiological imaging studies.
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    Muscle preflex response to perturbations in locomotion : in vitro experiments and simulations with realistic boundary conditions
    (2023) Araz, Matthew; Weidner, Sven; Izzi, Fabio; Badri-Spröwitz, Alexander; Siebert, Tobias; Häufle, Daniel F. B.
    Neuromuscular control loops feature substantial communication delays, but mammals run robustly even in the most adverse conditions. In vivo experiments and computer simulation results suggest that muscles’ preflex - an immediate mechanical response to a perturbation - could be the critical contributor. Muscle preflexes act within a few milliseconds, an order of magnitude faster than neural reflexes. Their short-lasting action makes mechanical preflexes hard to quantify in vivo. Muscle models, on the other hand, require further improvement of their prediction accuracy during the non-standard conditions of perturbed locomotion. Our study aims to quantify the mechanical work done by muscles during the preflex phase (preflex work) and test their mechanical force modulation. We performed in vitro experiments with biological muscle fibers under physiological boundary conditions, which we determined in computer simulations of perturbed hopping. Our findings show that muscles initially resist impacts with a stereotypical stiffness response - identified as short-range stiffness - regardless of the exact perturbation condition. We then observe a velocity adaptation to the force related to the amount of perturbation similar to a damping response. The main contributor to the preflex work modulation is not the change in force due to a change in fiber stretch velocity (fiber damping characteristics) but the change in magnitude of the stretch due to the leg dynamics in the perturbed conditions. Our results confirm previous findings that muscle stiffness is activity-dependent and show that also damping characteristics are activity-dependent. These results indicate that neural control could tune the preflex properties of muscles in expectation of ground conditions leading to previously inexplicable neuromuscular adaptation speeds.
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    Muscle prestimulation tunes velocity preflex in simulated perturbed hopping
    (2023) Izzi, Fabio; Mo, An; Schmitt, Syn; Badri-Spröwitz, Alexander; Häufle, Daniel F. B.
    Muscle fibres possess unique visco-elastic properties, which generate a stabilising zero-delay response to unexpected perturbations. This instantaneous response - termed “preflex” - mitigates neuro-transmission delays, which are hazardous during fast locomotion due to the short stance duration. While the elastic contribution to preflexes has been studied extensively, the function of fibre viscosity due to the force-velocity relation remains unknown. In this study, we present a novel approach to isolate and quantify the preflex force produced by the force-velocity relation in musculo-skeletal computer simulations. We used our approach to analyse the muscle response to ground-level perturbations in simulated vertical hopping. Our analysis focused on the preflex-phase - the first 30 ms after impact - where neuronal delays render a controlled response impossible. We found that muscle force at impact and dissipated energy increase with perturbation height, helping reject the perturbations. However, the muscle fibres reject only 15% of step-down perturbation energy with constant stimulation. An open-loop rising stimulation, observed in locomotion experiments, amplified the regulatory effects of the muscle fibre’s force–velocity relation, resulting in 68% perturbation energy rejection. We conclude that open-loop neuronal tuning of muscle activity around impact allows for adequate feed-forward tuning of muscle fibre viscous capacity, facilitating energy adjustment to unexpected ground-level perturbations.