@article{AlexyukBogoyavlenskiyAlexyuketal.2021,
  author    = {Alexyuk, Madina and Bogoyavlenskiy, Andrey and Alexyuk, Pavel and Moldakhanov, Yergali and Berezin, Vladimir and Digel, Ilya},
  title     = {Epipelagic microbiome of the Small Aral Sea: Metagenomic structure and ecological diversity},
  series = {MicrobiologyOpen},
  volume    = {10},
  journal   = {MicrobiologyOpen},
  number    = {1},
  publisher = {Wiley},
  address   = {Weinheim},
  issn      = {2045-8827},
  doi       = {10.1002/mbo3.1142},
  pages     = {1 -- 10},
  year      = {2021},
  abstract  = {Microbial diversity studies regarding the aquatic communities that experienced or are experiencing environmental problems are essential for the comprehension of the remediation dynamics. In this pilot study, we present data on the phylogenetic and ecological structure of microorganisms from epipelagic water samples collected in the Small Aral Sea (SAS). The raw data were generated by massive parallel sequencing using the shotgun approach. As expected, most of the identified DNA sequences belonged to Terrabacteria and Actinobacteria (40\% and 37\% of the total reads, respectively). The occurrence of Deinococcus-Thermus, Armatimonadetes, Chloroflexi in the epipelagic SAS waters was less anticipated. Surprising was also the detection of sequences, which are characteristic for strict anaerobes—Ignavibacteria, hydrogen-oxidizing bacteria, and archaeal methanogenic species. We suppose that the observed very broad range of phylogenetic and ecological features displayed by the SAS reads demonstrates a more intensive mixing of water masses originating from diverse ecological niches of the Aral-Syr Darya River basin than presumed before.},
  language  = {en}
}
@misc{JungMuellerStaat2021,
  author    = {Jung, Alexander and M{\"u}ller, Wolfram and Staat, Manfred},
  title     = {Corrigendum to "Wind and fairness in ski jumping: A computer modelling analysis" [J. Biomech. 75 (2018) 147-153]},
  series = {Journal of Biomechanics},
  volume    = {128},
  journal   = {Journal of Biomechanics},
  number    = {Article number: 110690},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0021-9290},
  doi       = {10.1016/j.jbiomech.2021.110690},
  pages     = {1 Seite},
  year      = {2021},
  language  = {en}
}
@article{JablonskiPoghossianKeusgenetal.2021,
  author    = {Jablonski, Melanie and Poghossian, Arshak and Keusgen, Michael and Wege, Christina and Sch{\"o}ning, Michael Josef},
  title     = {Detection of plant virus particles with a capacitive field-effect sensor},
  series = {Analytical and Bioanalytical Chemistry},
  volume    = {413},
  journal   = {Analytical and Bioanalytical Chemistry},
  publisher = {Springer Nature},
  address   = {Cham},
  issn      = {1618-2650},
  doi       = {10.1007/s00216-021-03448-8},
  pages     = {5669 -- 5678},
  year      = {2021},
  abstract  = {Plant viruses are major contributors to crop losses and induce high economic costs worldwide. For reliable, on-site and early detection of plant viral diseases, portable biosensors are of great interest. In this study, a field-effect SiO2-gate electrolyte-insulator-semiconductor (EIS) sensor was utilized for the label-free electrostatic detection of tobacco mosaic virus (TMV) particles as a model plant pathogen. The capacitive EIS sensor has been characterized regarding its TMV sensitivity by means of constant-capacitance method. The EIS sensor was able to detect biotinylated TMV particles from a solution with a TMV concentration as low as 0.025 nM. A good correlation between the registered EIS sensor signal and the density of adsorbed TMV particles assessed from scanning electron microscopy images of the SiO2-gate chip surface was observed. Additionally, the isoelectric point of the biotinylated TMV particles was determined via zeta potential measurements and the influence of ionic strength of the measurement solution on the TMV-modified EIS sensor signal has been studied.},
  language  = {en}
}
@article{PoghossianSchoening2021,
  author    = {Poghossian, Arshak and Sch{\"o}ning, Michael Josef},
  title     = {Recent progress in silicon-based biologically sensitive field-effect devices},
  series = {Current Opinion in Electrochemistry},
  journal   = {Current Opinion in Electrochemistry},
  number    = {Article number: 100811},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2451-9103},
  doi       = {10.1016/j.coelec.2021.100811},
  year      = {2021},
  abstract  = {Biologically sensitive field-effect devices (BioFEDs) advantageously combine the electronic field-effect functionality with the (bio)chemical receptor's recognition ability for (bio)chemical sensing. In this review, basic and widely applied device concepts of silicon-based BioFEDs (ion-sensitive field-effect transistor, silicon nanowire transistor, electrolyte-insulator-semiconductor capacitor, light-addressable potentiometric sensor) are presented and recent progress (from 2019 to early 2021) is discussed. One of the main advantages of BioFEDs is the label-free sensing principle enabling to detect a large variety of biomolecules and bioparticles by their intrinsic charge. The review encompasses applications of BioFEDs for the label-free electrical detection of clinically relevant protein biomarkers, deoxyribonucleic acid molecules and viruses, enzyme-substrate reactions as well as recording of the cell acidification rate (as an indicator of cellular metabolism) and the extracellular potential.},
  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}
}
@book{Laack2021,
  author    = {Laack, Walter van},
  title     = {Gr{\"o}ßer als das ganze Universum},
  publisher = {van Laack GmbH},
  address   = {Aachen},
  isbn      = {978-3-936624-38-0},
  pages     = {120 Seiten},
  year      = {2021},
  language  = {de}
}
@article{BallVoegeleGrajewskietal.2021,
  author    = {Ball, Christopher Stephen and V{\"o}gele, Stefan and Grajewski, Matthias and Kuckshinrichs, Wilhelm},
  title     = {E-mobility from a multi-actor point of view: Uncertainties and their impacts},
  series = {Technological Forecasting and Social Change},
  volume    = {170},
  journal   = {Technological Forecasting and Social Change},
  number    = {Art. 120925},
  publisher = {Elsevier},
  address   = {Amsterdam},
  isbn      = {0040-1625},
  doi       = {10.1016/j.techfore.2021.120925},
  year      = {2021},
  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}
}
@phdthesis{Jung2021,
  author    = {Jung, Alexander},
  title     = {Electromechanical modelling and simulation of hiPSC-derived cardiac cell cultures},
  publisher = {Universit{\"a}t Duisburg-Essen},
  isbn      = {978-3-9821811-1-0},
  url       = {http://nbn-resolving.de/https://nbn-resolving.org/urn:nbn:de:hbz:464-20210624-134942-7},
  pages     = {III, 135 Seiten},
  year      = {2021},
  language  = {en}
}
@techreport{StoelzleFeixThomasEngelstaedteretal.2021,
  author    = {St{\"o}lzle-Feix, Sonja and Thomas, Ulrich and Engelst{\"a}dter, Max and Goßmann, Matthias and Linder, Peter and Staat, Manfred and Raman, Aravind Hariharan and Jung, Alexander and Fertig, Niels},
  title     = {Plattformtechnologie f{\"u}r kardiale Sicherheitspharmakologie basierend auf teilsynthetischem Herzmuskelgewebe (FLEXcyte) : gemeinsamer FuE-Abschlussbericht aller Partner des Verbundprojektes : Projektlaufzeit: 01.10.2018 bis 30.09.2020},
  publisher = {Nanion Technologies GmbH},
  address   = {M{\"u}nchen},
  doi       = {10.2314/KXP:1813208581},
  pages     = {IV, 85 Seiten, 2 ungez{\"a}hlte Seiten},
  year      = {2021},
  language  = {de}
}