@article{HunkerGossmannRamanetal.2021, author = {Hunker, Jan L. and Gossmann, Matthias and Raman, Aravind Hariharan and Linder, Peter}, title = {Artificial neural networks in cardiac safety assessment: Classification of chemotherapeutic compound effects on hiPSC-derived cardiomyocyte contractility}, series = {Journal of Pharmacological and Toxicological Methods}, volume = {111}, journal = {Journal of Pharmacological and Toxicological Methods}, number = {Article number 107044}, publisher = {Elsevier}, address = {New York}, issn = {1056-8719}, doi = {10.1016/j.vascn.2021.107044}, year = {2021}, language = {en} } @article{GriegerSchwabedalWendeletal.2021, author = {Grieger, Niklas and Schwabedal, Justus T. C. and Wendel, Stefanie and Ritze, Yvonne and Bialonski, Stephan}, title = {Automated scoring of pre-REM sleep in mice with deep learning}, series = {Scientific Reports}, volume = {11}, journal = {Scientific Reports}, number = {Art. 12245}, publisher = {Springer Nature}, address = {London}, issn = {2045-2322}, doi = {10.1038/s41598-021-91286-0}, year = {2021}, abstract = {Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accuracies for the classical sleep stages of Wake, REM, and Non-REM. Meanwhile, it has been recognized that the statistics of transitional stages such as pre-REM, found between Non-REM and REM, may hold additional insight into the physiology of sleep and are now under vivid investigation. We propose a classification system based on a simple neural network architecture that scores the classical stages as well as pre-REM sleep in mice. When restricted to the classical stages, the optimized network showed state-of-the-art classification performance with an out-of-sample F1 score of 0.95 in male C57BL/6J mice. When unrestricted, the network showed lower F1 scores on pre-REM (0.5) compared to the classical stages. The result is comparable to previous attempts to score transitional stages in other species such as transition sleep in rats or N1 sleep in humans. Nevertheless, we observed that the sequence of predictions including pre-REM typically transitioned from Non-REM to REM reflecting sleep dynamics observed by human scorers. Our findings provide further evidence for the difficulty of scoring transitional sleep stages, likely because such stages of sleep are under-represented in typical data sets or show large inter-scorer variability. We further provide our source code and an online platform to run predictions with our trained network.}, language = {en} } @article{OliveiraMolinnusBegingetal.2021, author = {Oliveira, Danilo A. and Molinnus, Denise and Beging, Stefan and Siqueira Jr, Jos{\´e} R. and Sch{\"o}ning, Michael Josef}, title = {Biosensor Based on Self-Assembled Films of Graphene Oxide and Polyaniline Using a Field-Effect Device Platform}, series = {physica status solidi (a) applications and materials science}, volume = {218}, journal = {physica status solidi (a) applications and materials science}, number = {13}, publisher = {Wiley-VCH}, address = {Weinheim}, issn = {1862-6319}, doi = {10.1002/pssa.202000747}, pages = {1 -- 9}, year = {2021}, abstract = {A new functionalization method to modify capacitive electrolyte-insulator-semiconductor (EIS) structures with nanofilms is presented. Layers of polyallylamine hydrochloride (PAH) and graphene oxide (GO) with the compound polyaniline:poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (PANI:PAAMPSA) are deposited onto a p-Si/SiO2 chip using the layer-by-layer technique (LbL). Two different enzymes (urease and penicillinase) are separately immobilized on top of a five-bilayer stack of the PAH:GO/PANI:PAAMPSA-modified EIS chip, forming a biosensor for detection of urea and penicillin, respectively. Electrochemical characterization is performed by constant capacitance (ConCap) measurements, and the film morphology is characterized by atomic force microscopy (AFM) and scanning electron microscopy (SEM). An increase in the average sensitivity of the modified biosensors (EIS-nanofilm-enzyme) of around 15\% is found in relation to sensors, only carrying the enzyme but without the nanofilm (EIS-enzyme). In this sense, the nanofilm acts as a stable bioreceptor onto the EIS chip improving the output signal in terms of sensitivity and stability.}, language = {en} } @article{HeelDiktaBraekers2021, author = {Heel, Mareike van and Dikta, Gerhard and Braekers, Roel}, title = {Bootstrap based goodness‑of‑fit tests for binary multivariate regression models}, series = {Journal of the Korean Statistical Society}, volume = {51}, journal = {Journal of the Korean Statistical Society}, publisher = {Springer Nature}, address = {Singapur}, issn = {2005-2863 (Online)}, doi = {10.1007/s42952-021-00142-4}, pages = {28 Seiten}, year = {2021}, abstract = {We consider a binary multivariate regression model where the conditional expectation of a binary variable given a higher-dimensional input variable belongs to a parametric family. Based on this, we introduce a model-based bootstrap (MBB) for higher-dimensional input variables. This test can be used to check whether a sequence of independent and identically distributed observations belongs to such a parametric family. The approach is based on the empirical residual process introduced by Stute (Ann Statist 25:613-641, 1997). In contrast to Stute and Zhu's approach (2002) Stute \& Zhu (Scandinavian J Statist 29:535-545, 2002), a transformation is not required. Thus, any problems associated with non-parametric regression estimation are avoided. As a result, the MBB method is much easier for users to implement. To illustrate the power of the MBB based tests, a small simulation study is performed. Compared to the approach of Stute \& Zhu (Scandinavian J Statist 29:535-545, 2002), the simulations indicate a slightly improved power of the MBB based method. Finally, both methods are applied to a real data set.}, language = {en} } @book{DiktaScheer2021, author = {Dikta, Gerhard and Scheer, Marsel}, title = {Bootstrap Methods: With Applications in R}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-73480-0}, doi = {10.1007/978-3-030-73480-0}, pages = {XVI, 256 Seiten}, year = {2021}, abstract = {This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time. The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.}, language = {en} } @article{JablonskiPoghossianSeverinetal.2021, author = {Jablonski, Melanie and Poghossian, Arshak and Severin, Robin and Keusgen, Michael and Wege, Christian and Sch{\"o}ning, Michael Josef}, title = {Capacitive Field-Effect Biosensor Studying Adsorption of Tobacco Mosaic Virus Particles}, series = {Micromachines}, volume = {12}, journal = {Micromachines}, number = {1}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/mi12010057}, pages = {Artikel 57}, year = {2021}, abstract = {Plant virus-like particles, and in particular, tobacco mosaic virus (TMV) particles, are increasingly being used in nano- and biotechnology as well as for biochemical sensing purposes as nanoscaffolds for the high-density immobilization of receptor molecules. The sensitive parameters of TMV-assisted biosensors depend, among others, on the density of adsorbed TMV particles on the sensor surface, which is affected by both the adsorption conditions and surface properties of the sensor. In this work, Ta₂O₅-gate field-effect capacitive sensors have been applied for the label-free electrical detection of TMV adsorption. The impact of the TMV concentration on both the sensor signal and the density of TMV particles adsorbed onto the Ta₂O₅-gate surface has been studied systematically by means of field-effect and scanning electron microscopy methods. In addition, the surface density of TMV particles loaded under different incubation times has been investigated. Finally, the field-effect sensor also demonstrates the label-free detection of penicillinase immobilization as model bioreceptor on TMV particles.}, language = {en} } @article{JablonskiMuenstermannNorketal.2021, author = {Jablonski, Melanie and M{\"u}nstermann, Felix and Nork, Jasmina and Molinnus, Denise and Muschallik, Lukas and Bongaerts, Johannes and Wagner, Torsten and Keusgen, Michael and Siegert, Petra and Sch{\"o}ning, Michael Josef}, title = {Capacitive field-effect biosensor applied for the detection of acetoin in alcoholic beverages and fermentation broths}, series = {physica status solidi (a) applications and materials science}, volume = {218}, journal = {physica status solidi (a) applications and materials science}, number = {13}, publisher = {Wiley-VCH}, address = {Weinheim}, issn = {1862-6319}, doi = {10.1002/pssa.202000765}, pages = {7 Seiten}, year = {2021}, abstract = {An acetoin biosensor based on a capacitive electrolyte-insulator-semiconductor (EIS) structure modified with the enzyme acetoin reductase, also known as butane-2,3-diol dehydrogenase (Bacillus clausii DSM 8716ᵀ), is applied for acetoin detection in beer, red wine, and fermentation broth samples for the first time. The EIS sensor consists of an Al/p-Si/SiO₂/Ta₂O₅ layer structure with immobilized acetoin reductase on top of the Ta₂O₅ transducer layer by means of crosslinking via glutaraldehyde. The unmodified and enzyme-modified sensors are electrochemically characterized by means of leakage current, capacitance-voltage, and constant capacitance methods, respectively.}, language = {en} } @inproceedings{SchmidtsKraftWinkensetal.2021, author = {Schmidts, Oliver and Kraft, Bodo and Winkens, Marvin and Z{\"u}ndorf, Albert}, title = {Catalog integration of heterogeneous and volatile product data}, series = {DATA 2020: Data Management Technologies and Applications}, booktitle = {DATA 2020: Data Management Technologies and Applications}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-83013-7}, doi = {10.1007/978-3-030-83014-4_7}, pages = {134 -- 153}, year = {2021}, abstract = {The integration of frequently changing, volatile product data from different manufacturers into a single catalog is a significant challenge for small and medium-sized e-commerce companies. They rely on timely integrating product data to present them aggregated in an online shop without knowing format specifications, concept understanding of manufacturers, and data quality. Furthermore, format, concepts, and data quality may change at any time. Consequently, integrating product catalogs into a single standardized catalog is often a laborious manual task. Current strategies to streamline or automate catalog integration use techniques based on machine learning, word vectorization, or semantic similarity. However, most approaches struggle with low-quality or real-world data. We propose Attribute Label Ranking (ALR) as a recommendation engine to simplify the integration process of previously unknown, proprietary tabular format into a standardized catalog for practitioners. We evaluate ALR by focusing on the impact of different neural network architectures, language features, and semantic similarity. Additionally, we consider metrics for industrial application and present the impact of ALR in production and its limitations.}, language = {en} } @article{NeumaierWeissVeldemanetal.2021, author = {Neumaier, Felix and Weiss, Miriam and Veldeman, Michael and Kotliar, Konstantin and Wiesmann, Martin and Schulze-Steinen, Henna and H{\"o}llig, Anke and Clusmann, Hans and Schubert, Gerrit Alexander and Albanna, Walid}, title = {Changes in endogenous daytime melatonin levels after aneurysmal subarachnoid hemorrhage - preliminary findings from an observational cohort study}, series = {Clinical Neurology and Neurosurgery}, volume = {208}, journal = {Clinical Neurology and Neurosurgery}, number = {Article No.: 106870}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0303-8467}, doi = {10.1016/j.clineuro.2021.106870}, year = {2021}, abstract = {Aneurysmal subarachnoid hemorrhage (aSAH) is associated with early and delayed brain injury due to several underlying and interrelated processes, which include inflammation, oxidative stress, endothelial, and neuronal apoptosis. Treatment with melatonin, a cytoprotective neurohormone with anti-inflammatory, anti-oxidant and anti-apoptotic effects, has been shown to attenuate early brain injury (EBI) and to prevent delayed cerebral vasospasm in experimental aSAH models. Less is known about the role of endogenous melatonin for aSAH outcome and how its production is altered by the pathophysiological cascades initiated during EBI. In the present observational study, we analyzed changes in melatonin levels during the first three weeks after aSAH.}, language = {en} } @article{EngelmannShalabyShashaetal.2021, author = {Engelmann, Ulrich M. and Shalaby, Ahmed and Shasha, Carolyn and Krishnan, Kannan M. and Krause, Hans-Joachim}, title = {Comparative modeling of frequency mixing measurements of magnetic nanoparticles using micromagnetic simulations and Langevin theory}, series = {Nanomaterials}, volume = {11}, journal = {Nanomaterials}, number = {5}, publisher = {MDPI}, address = {Basel}, isbn = {2079-4991}, doi = {10.3390/nano11051257}, pages = {1 -- 16}, year = {2021}, abstract = {Dual frequency magnetic excitation of magnetic nanoparticles (MNP) enables enhanced biosensing applications. This was studied from an experimental and theoretical perspective: nonlinear sum-frequency components of MNP exposed to dual-frequency magnetic excitation were measured as a function of static magnetic offset field. The Langevin model in thermodynamic equilibrium was fitted to the experimental data to derive parameters of the lognormal core size distribution. These parameters were subsequently used as inputs for micromagnetic Monte-Carlo (MC)-simulations. From the hysteresis loops obtained from MC-simulations, sum-frequency components were numerically demodulated and compared with both experiment and Langevin model predictions. From the latter, we derived that approximately 90\% of the frequency mixing magnetic response signal is generated by the largest 10\% of MNP. We therefore suggest that small particles do not contribute to the frequency mixing signal, which is supported by MC-simulation results. Both theoretical approaches describe the experimental signal shapes well, but with notable differences between experiment and micromagnetic simulations. These deviations could result from Brownian relaxations which are, albeit experimentally inhibited, included in MC-simulation, or (yet unconsidered) cluster-effects of MNP, or inaccurately derived input for MC-simulations, because the largest particles dominate the experimental signal but concurrently do not fulfill the precondition of thermodynamic equilibrium required by Langevin theory.}, language = {en} }