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Item type:Publication, Access status: with files , Artificial neural networks for quantitative online NMR spectroscopy(Springer, 2020-05-09); ; ; ; Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data. [Figure not available: see fulltext.].Publicationtype: Journal ArticleScopus© Citations 28 278 279 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Quantification of the dynamics of population heterogeneities in CHO cultures with stably integrated fluorescent markers(Springer, 2020-03-04); ; ; ; Cell population heterogeneities and their changes in mammalian cell culture processes are still not well characterized. In this study, the formation and dynamics of cell population heterogeneities were investigated with flow cytometry and stably integrated fluorescent markers based on the lentiviral gene ontology (LeGO) vector system. To achieve this, antibody-producing CHO cells were transduced with different LeGO vectors to stably express single or multiple fluorescent proteins. This enables the tracking of the transduced populations and is discussed in two case studies from the field of bioprocess engineering: In case study I, cells were co-transduced to express red, green, and blue fluorescent proteins and the development of sub-populations and expression heterogeneities were investigated in high passage cultivations (total 130 days). The formation of a fast-growing and more productive population was observed with a simultaneous increase in cell density and product titer. In case study II, different preculture growth phases and their influence on the population dynamics were investigated in mixed batch cultures with flow cytometry (offline and automated). Four cell line derivatives, each expressing a different fluorescent protein, were generated and cultivated for different time intervals, corresponding to different growth phases. Mixed cultures were inoculated from them, and changes in the composition of the cell populations were observed during the first 48 h of cultivation with reduced process productivity. In summary, we showed how the dynamics of population heterogeneities can be characterized. This represents a novel approach to investigate the dynamics of cell population heterogeneities under near-physiological conditions with changing productivity in mammalian cell culture processes.Publicationtype: Journal ArticleScopus© Citations 4 280 183 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Can cloud point-based enrichment, preservation, and detection methods help to bridge gaps in aquatic nanometrology?(Springer, 2016-08-24); ; ; ; Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.Publicationtype: Journal ArticleScopus© Citations 34 320 488 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Determination of pharmaceuticals in sewage sludge and biochar from hydrothermal carbonization using different quantification approaches and matrix effect studies(Springer, 2014-08-07); ; ; ; Producing valuable biochar from waste materials using thermal processes like hydrothermal carbonization (HTC) has gained attention in recent years. However, the fate of micropollutants present in these waste sources have been neglected, although they might entail the risk of environmental pollution. Thus, an HPLC-MS/MS method was developed for 12 pharmaceuticals to determine the micropollutant load of biochar, which was made from sewage sludge via HTC within 4 h at 210 °C. Pressurized liquid extraction was applied to extract the compounds. Because of the high load of co-extracted matter, matrix effects in HPLC-MS/MS were investigated using matrix effect profiles. Interfering compounds suppressed 50 % of the phenazone signal in sewage sludge and 70 % in biochar, for example. The quantification approaches external calibration, internal standard analysis, and standard addition were compared considering recovery rates, standard deviations, and measurement uncertainties. The external analysis resulted in decreased or enhanced recovery rates. Spiking before LC-MS/MS compensated instrumental matrix effects. Still, recovery rates remained below 70 % for most compounds because this approach neglects sample losses during the extraction. Internal standards compensated for the matrix effects sufficiently for up to five compounds. The standard addition over the whole procedure proved to compensate for the matrix effects for 11 compounds and achieved recovery rates between 85 and 125 %. Additionally, results showed good reproducibility and validity. Only sulfamethoxazole recovery rate remained below 70 % in sewage sludge. Real sample analysis showed that three pharmaceuticals were detected in the biochar, while the corresponding sewage sludge source contained 8 of the investigated compounds.Publicationtype: Journal ArticleScopus© Citations 37 40