TY - JOUR A1 - Ditzhaus, Marc A1 - Gaigall, Daniel T1 - A consistent goodness-of-fit test for huge dimensional and functional data JF - Journal of Nonparametric Statistics N2 - A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals. KW - Cramér-von-Mises statistic KW - separable Hilbert space KW - huge dimensional data KW - functional data Y1 - 2018 U6 - https://doi.org/10.1080/10485252.2018.1486402 SN - 1029-0311 VL - 30 IS - 4 SP - 834 EP - 859 PB - Taylor & Francis CY - Abingdon ER - TY - JOUR A1 - Jildeh, Zaid B. A1 - Oberländer, Jan A1 - Kirchner, Patrick A1 - Keusgen, Michael A1 - Wagner, Patrick H. A1 - Schöning, Michael Josef T1 - Experimental and Numerical Analyzes of a Sensor Based on Interdigitated Electrodes for Studying Microbiological Alterations JF - physica status solidi (a): applications and materials science N2 - In this work, a cell-based biosensor to evaluate the sterilization efficacy of hydrogen peroxide vapor sterilization processes is characterized. The transducer of the biosensor is based on interdigitated gold electrodes fabricated on an inert glass substrate. Impedance spectroscopy is applied to evaluate the sensor behavior and the alteration of test microorganisms due to the sterilization process. These alterations are related to changes in relative permittivity and electrical conductivity of the bacterial spores. Sensor measurements are conducted with and without bacterial spores (Bacillus atrophaeus), as well as after an industrial sterilization protocol. Equivalent two-dimensional numerical models based on finite element method of the periodic finger structures of the interdigitated gold electrodes are designed and validated using COMSOL® Multiphysics software by the application of known dielectric properties. The validated models are used to compute the electrical properties at different sensor states (blank, loaded with spores, and after sterilization). As a final result, we will derive and tabulate the frequency-dependent electrical parameters of the spore layer using a novel model that combines experimental data with numerical optimization techniques. Y1 - 2018 U6 - https://doi.org/10.1002/pssa.201700920 SN - 1862-6319 VL - 215 IS - 15 PB - Wiley-VCH CY - Weinheim ER - TY - CHAP A1 - Schöning, Michael Josef A1 - Wagner, Torsten A1 - Poghossian, Arshak A1 - Miyamoto, K.I. A1 - Werner, C.F. A1 - Krause, S. A1 - Yoshinobu, T. T1 - Light-addressable potentiometric sensors for (bio-)chemical sensing and imaging T2 - Encyclopedia of Interfacial Chemistry: Surface Science and Electrochemistry. Vol. 7 Y1 - 2018 SN - 9780128097397 SP - 295 EP - 308 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schwabedal, Justus T. C. A1 - Sippel, Daniel A1 - Brandt, Moritz D. A1 - Bialonski, Stephan T1 - Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning N2 - Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle. Y1 - 2018 U6 - https://doi.org/10.48550/arXiv.1809.08443 ER - TY - CHAP A1 - Bhattarai, Aroj A1 - Staat, Manfred ED - Artmann, Gerhard ED - Temiz Artmann, Aysegül ED - Zhubanova, Azhar A. ED - Digel, Ilya T1 - Mechanics of soft tissue reactions to textile mesh implants T2 - Biological, Physical and Technical Basics of Cell Engineering N2 - For pelvic floor disorders that cannot be treated with non-surgical procedures, minimally invasive surgery has become a more frequent and safer repair procedure. More than 20 million prosthetic meshes are implanted each year worldwide. The simple selection of a single synthetic mesh construction for any level and type of pelvic floor dysfunctions without adopting the design to specific requirements increase the risks for mesh related complications. Adverse events are closely related to chronic foreign body reaction, with enhanced formation of scar tissue around the surgical meshes, manifested as pain, mesh erosion in adjacent structures (with organ tissue cut), mesh shrinkage, mesh rejection and eventually recurrence. Such events, especially scar formation depend on effective porosity of the mesh, which decreases discontinuously at a critical stretch when pore areas decrease making the surgical reconstruction ineffective that further augments the re-operation costs. The extent of fibrotic reaction is increased with higher amount of foreign body material, larger surface, small pore size or with inadequate textile elasticity. Standardized studies of different meshes are essential to evaluate influencing factors for the failure and success of the reconstruction. Measurements of elasticity and tensile strength have to consider the mesh anisotropy as result of the textile structure. An appropriate mesh then should show some integration with limited scar reaction and preserved pores that are filled with local fat tissue. This chapter reviews various tissue reactions to different monofilament mesh implants that are used for incontinence and hernia repairs and study their mechanical behavior. This helps to predict the functional and biological outcomes after tissue reinforcement with meshes and permits further optimization of the meshes for the specific indications to improve the success of the surgical treatment. Y1 - 2018 SN - 978-981-10-7904-7 U6 - https://doi.org/10.1007/978-981-10-7904-7_11 SP - 251 EP - 275 PB - Springer CY - Singapore ER - TY - JOUR A1 - Molinnus, Denise A1 - Hardt, Gabriel A1 - Siegert, Petra A1 - Willenberg, Holger S. A1 - Poghossian, Arshak A1 - Keusgen, Michael A1 - Schöning, Michael Josef T1 - Detection of Adrenaline in Blood Plasma as Biomarker for Adrenal Venous Sampling JF - Electroanalysis N2 - An amperometric bi-enzyme biosensor based on substrate recycling principle for the amplification of the sensor signal has been developed for the detection of adrenaline in blood. Adrenaline can be used as biomarker verifying successful adrenal venous sampling procedure. The adrenaline biosensor has been realized via modification of a galvanic oxygen sensor with a bi-enzyme membrane combining a genetically modified laccase and a pyrroloquinoline quinone-dependent glucose dehydrogenase. The measurement conditions such as pH value and temperature were optimized to enhance the sensor performance. A high sensitivity and a low detection limit of about 0.5–1 nM adrenaline have been achieved in phosphate buffer at pH 7.4, relevant for measurements in blood samples. The sensitivity of the biosensor to other catecholamines such as noradrenaline, dopamine and dobutamine has been studied. Finally, the sensor has been successfully applied for the detection of adrenaline in human blood plasma. Y1 - 2018 U6 - https://doi.org/10.1002/elan.201800026 SN - 1521-4109 VL - 30 IS - 5 SP - 937 EP - 942 PB - Wiley-VCH CY - Weinheim ER - TY - JOUR A1 - Poghossian, Arshak A1 - Jablonski, Melanie A1 - Koch, Claudia A1 - Bronder, Thomas A1 - Rolka, David A1 - Wege, Christina A1 - Schöning, Michael Josef T1 - Field-effect biosensor using virus particles as scaffolds for enzyme immobilization JF - Biosensors and Bioelectronics N2 - A field-effect biosensor employing tobacco mosaic virus (TMV) particles as scaffolds for enzyme immobilization is presented. Nanotubular TMV scaffolds allow a dense immobilization of precisely positioned enzymes with retained activity. To demonstrate feasibility of this new strategy, a penicillin sensor has been developed by coupling a penicillinase with virus particles as a model system. The developed field-effect penicillin biosensor consists of an Al-p-Si-SiO₂-Ta₂O₅-TMV structure and has been electrochemically characterized in buffer solutions containing different concentrations of penicillin G. In addition, the morphology of the biosensor surface with virus particles was characterized by scanning electron microscopy and atomic force microscopy methods. The sensors possessed a high penicillin sensitivity of ~ 92 mV/dec in a nearly-linear range from 0.1 mM to 10 mM, and a low detection limit of about 50 µM. The long-term stability of the penicillin biosensor was periodically tested over a time period of about one year without any significant loss of sensitivity. The biosensor has also been successfully applied for penicillin detection in bovine milk samples. Y1 - 2018 U6 - https://doi.org/10.1016/j.bios.2018.03.036 SN - 0956-5663 VL - 110 SP - 168 EP - 174 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Rabehi, Amine A1 - Garlan, Benjamin A1 - Achtsnicht, Stefan A1 - Krause, Hans-Joachim A1 - Offenhäusser, Andreas A1 - Ngo, Kieu A1 - Neveu, Sophie A1 - Graff-Dubois, Stephanie A1 - Kokabi, Hamid T1 - Magnetic detection structure for Lab-on-Chip applications based on the frequency mixing technique JF - Sensors N2 - A magnetic frequency mixing technique with a set of miniaturized planar coils was investigated for use with a completely integrated Lab-on-Chip (LoC) pathogen sensing system. The system allows the detection and quantification of superparamagnetic beads. Additionally, in terms of magnetic nanoparticle characterization ability, the system can be used for immunoassays using the beads as markers. Analytical calculations and simulations for both excitation and pick-up coils are presented; the goal was to investigate the miniaturization of simple and cost-effective planar spiral coils. Following these calculations, a Printed Circuit Board (PCB) prototype was designed, manufactured, and tested for limit of detection, linear response, and validation of theoretical concepts. Using the magnetic frequency mixing technique, a limit of detection of 15 µg/mL of 20 nm core-sized nanoparticles was achieved without any shielding. KW - Lab-on-Chip KW - magnetic sensing KW - frequency mixing KW - superparamagnetic nanoparticles KW - magnetic beads Y1 - 2018 U6 - https://doi.org/10.3390/s18061747 SN - 1424-8220 VL - 18 IS - 6 PB - MDPI CY - Basel ER - TY - JOUR A1 - Bhattarai, Aroj A1 - Staat, Manfred T1 - Computational comparison of different textile implants to correct apical prolapse in females JF - Current Directions in Biomedical Engineering N2 - Prosthetic textile implants of different shapes, sizes and polymers are used to correct the apical prolapse after hysterectomy (removal of the uterus). The selection of the implant before or during minimally invasive surgery depends on the patient’s anatomical defect, intended function after reconstruction and most importantly the surgeon’s preference. Weakness or damage of the supporting tissues during childbirth, menopause or previous pelvic surgeries may put females in higher risk of prolapse. Numerical simulations of reconstructed pelvic floor with weakened tissues and organ supported by textile product models: DynaMesh®-PRS soft, DynaMesh®-PRP soft and DynaMesh®-CESA from FEG Textiletechnik mbH, Germany are compared. Y1 - 2018 U6 - https://doi.org/10.1515/cdbme-2018-0159 VL - 4 IS - 1 SP - 661 EP - 664 PB - De Gruyter CY - Berlin ER - TY - JOUR A1 - Horbach, Andreas A1 - Staat, Manfred T1 - Optical strain measurement for the modeling of surgical meshes and their porosity JF - Current Directions in Biomedical Engineering N2 - The porosity of surgical meshes makes them flexible for large elastic deformation and establishes the healing conditions of good tissue in growth. The biomechanic modeling of orthotropic and compressible materials requires new materials models and simulstaneoaus fit of deformation in the load direction as well as trannsversely to to load. This nonlinear modeling can be achieved by an optical deformation measurement. At the same time the full field deformation measurement allows the dermination of the change of porosity with deformation. Also the socalled effective porosity, which has been defined to asses the tisssue interatcion with the mesh implants, can be determined from the global deformation of the surgical meshes. Y1 - 2018 U6 - https://doi.org/10.1515/cdbme-2018-0045 SN - 2364-5504 VL - Band 4 IS - 1 SP - 181 EP - 184 PB - De Gruyter CY - Berlin ER -