07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
Browse
14 results
Search Results
Item Open Access ROSIE : RObust Sparse ensemble for outlIEr detection and gene selection in cancer omics data(2022) Jensch, Antje; Lopes, Marta B.; Vinga, Susana; Radde, NicoleThe extraction of novel information from omics data is a challenging task, in particular, since the number of features (e.g. genes) often far exceeds the number of samples. In such a setting, conventional parameter estimation leads to ill-posed optimization problems, and regularization may be required. In addition, outliers can largely impact classification accuracy. Here we introduce ROSIE, an ensemble classification approach, which combines three sparse and robust classification methods for outlier detection and feature selection and further performs a bootstrap-based validity check. Outliers of ROSIE are determined by the rank product test using outlier rankings of all three methods, and important features are selected as features commonly selected by all methods. We apply ROSIE to RNA-Seq data from The Cancer Genome Atlas (TCGA) to classify observations into Triple-Negative Breast Cancer (TNBC) and non-TNBC tissue samples. The pre-processed dataset consists of 16,600 genes and more than 1,000 samples. We demonstrate that ROSIE selects important features and outliers in a robust way. Identified outliers are concordant with the distribution of the commonly selected genes by the three methods, and results are in line with other independent studies. Furthermore, we discuss the association of some of the selected genes with the TNBC subtype in other investigations. In summary, ROSIE constitutes a robust and sparse procedure to identify outliers and important genes through binary classification. Our approach is ad hoc applicable to other datasets, fulfilling the overall goal of simultaneously identifying outliers and candidate disease biomarkers to the targeted in therapy research and personalized medicine frameworks.Item Open Access Entwicklung einer Methode zur Analyse der Tätigkeitsverteilung in Laborumgebungen der Lebenswissenschaften(Stuttgart : Fraunhofer Verlag, 2022) Castor, Jörg; Spath, Dieter (Univ.-Prof. Dr.-Ing. Dr.-Ing. E.h. Dr. h.c.)Laborarbeit der Lebenswissenschaften verändert sich. Wichtige Treiber sind dabei die Informatisierung und Automatisierung von Laborarbeit, die fachübergreifende Zusammenarbeit und Kommunikation sowie der steigende Anteil an wissensbasierter, theoretischer Arbeit. Die Auseinandersetzung mit Forschung und Praxis der Laborarbeit in den Lebenswissenschaften zeigte einen Mangel an wissenschaftlichen Erkenntnissen und Untersuchungen zu diesem Thema. Es existiert kein wissenschaftlicher Ansatz tätigkeitsbezogene Aspekte der lebenswissenschaftlichen Forschung und ihren Arbeitsorten systematisch zu untersuchen, um ein besseres Lagebild zur Arbeit in lebenswissenschaftlichen Laborumgebungen zu erhalten. Eine fundierte gestalterische Auseinandersetzung mit den prognostizierten und wahrnehmbaren Veränderungen von Laborarbeit kann so kaum erfolgen. Zielsetzung der vorliegenden Arbeit ist daher die Entwicklung einer wissenschaftlichen Methode zur Analyse der Tätigkeitsverteilung in Laborumgebungen der Lebenswissenschaften, um Anhaltspunkte für mögliche Fehlnutzungen, Verdrängungseffekte und andere Wirkungen im Spannungsfeld von Raum und Tätigkeiten zu bekommen. Die Methode ermöglicht zudem Aussagen zur Flächeneffizienz von Laborumgebungen. Der Begriff Laborumgebung beschreibt in der Arbeit den räumlichen Zusammenhang von Laboren mit Laborbänken, Laborabzügen, Schreib-/Auswerteplätzen, Sonderlaboren, Laborlagern sowie Büros und Kommunikationsflächen. Für die Anwendung der Methode werden jeweils nass-präparative Tätigkeiten, Schreib-, Lese- und Auswertetätigkeiten sowie Kommunikationstätigkeiten gebündelt. Kommunikationstätigkeiten werden eine besondere Relevanz in der modernen Forschungsarbeit zugeschrieben. Sie sind zudem die einzigen Tätigkeiten, die an allen Arbeitsorten in Laborumgebungen vorkommen. Als weitere Anwendung lässt die Methode daher eine Beurteilung der Qualität des raumbezogenen Informationsflusses und der tätigkeitsadäquaten Nutzung der Arbeitsorte in der Laborumgebung mittels eigener Qualitätsparameter für Kommunikation zu. In der praktischen Anwendung der Methode wird deutlich, dass die wissenschaftliche Herangehensweise gerade bei Einzeluntersuchungen einen gewissen Aufwand erfordert. Die Methode zeigte aber einen guten Praxisnutzen - insbesondere bei einer vergleichenden Untersuchung wie im Anwendungsbeispiel. So wurden durch die Vergleichsmöglichkeit im Anwendungsbeispiel sowohl Vorteile der effizienten Flächennutzung einer modernen »Multi-Space« Laborumgebung sichtbar, als auch die dadurch bedingten Schwierigkeiten hinsichtlich der Verdrängung raumtypischer Arbeitsweisen in dichteren räumlichen Funktionszusammenhängen.Item Open Access Cu-doped calcium phosphate supraparticles for bone tissue regeneration(2024) Höppel, Anika; Bahr, Olivia; Ebert, Regina; Wittmer, Annette; Seidenstuecker, Michael; Carolina Lanzino, M.; Gbureck, Uwe; Dembski, SofiaCalcium phosphate (CaP) minerals have shown great promise as bone replacement materials due to their similarity to the mineral phase of natural bone. In addition to biocompatibility and osseointegration, the prevention of infection is crucial, especially due to the high concern of antibiotic resistance. In this context, a controlled drug release as well as biodegradation are important features which depend on the porosity of CaP. An increase in porosity can be achieved by using nanoparticles (NPs), which can be processed to supraparticles, combining the properties of nano- and micromaterials. In this study, Cu-doped CaP supraparticles were prepared to improve the bone substitute properties while providing antibacterial effects. In this context, a modified sol-gel process was used for the synthesis of CaP NPs, where a Ca/P molar ratio of 1.10 resulted in the formation of crystalline β-tricalcium phosphate (β-TCP) after calcination at 1000 °C. In the next step, CaP NPs with Cu 2+ (0.5-15.0 wt%) were processed into supraparticles by a spray drying method. Cu release experiments of the different Cu-doped CaP supraparticles demonstrated a long-term sustained release over 14 days. The antibacterial properties of the supraparticles were determined against Gram-positive ( Bacillus subtilis and Staphylococcus aureus ) and Gram-negative ( Escherichia coli ) bacteria, where complete antibacterial inhibition was achieved using a Cu concentration of 5.0 wt%. In addition, cell viability assays of the different CaP supraparticles with human telomerase-immortalized mesenchymal stromal cells (hMSC-TERT) exhibited high biocompatibility with particle concentrations of 0.01 mg mL -1 over 72 hours.Item Open Access Editorial - optical microscopic and spectroscopic techniques targeting biological applications(2021) Micó, Vicente; Pedrini, Giancarlo; Lei, Ming; Zuo, Chao; Gao, PengItem Open Access Miniature low-cost γ-radiation sensor for localization of radioactively marked lymph nodes(2022) Behling, Merlin; Wezel, Felix; Pott, Peter P.Detection of metastasis spread at an early stage of disease in lymph nodes can be achieved by imaging techniques, such as PET and fluoride-marked tumor cells. Intraoperative detection of small metastasis can be problematic especially in minimally invasive surgical settings. A γ-radiation sensor can be inserted in the situs to facilitate intraoperative localization of the lymph nodes. In the minimally invasive setting, the sensor must fit through the trocar and for robot-aided interventions, a small, capsule-like device is favorable. Size reduction could be achieved by using only a few simple electronic parts packed in a single-use sensor-head also leading to a low-cost device. This paper first describes the selection of an appropriate low-cost diode, which is placed in a sensor head (Ø 12 mm) and characterized in a validation experiment. Finally, the sensor and its performance during a detection experiment with nine subjects is evaluated. The subjects had to locate a 137Cs source (138 kBq activity, 612 keV) below a wooden plate seven times. Time to accomplish this task and error rate were recorded and evaluated. The time needed by the subjects to complete each run was 95 ± 68.1 s for the first trial down to 40 ± 23.9 s for the last. All subjects managed to locate the 137Cs source precisely. Further reduction in size and a sterilizable housing are prerequisites for in vitro tests on explanted human lymph nodes and finally in vivo testing.Item Open Access Mathematical modeling and simulation of thyroid homeostasis : implications for the Allan-Herndon-Dudley syndrome(2022) Wolff, Tobias M.; Veil, Carina; Dietrich, Johannes W.; Müller, Matthias A.Introduction: A mathematical model of the pituitary-thyroid feedback loop is extended to deepen the understanding of the Allan-Herndon-Dudley syndrome (AHDS). The AHDS is characterized by unusual thyroid hormone concentrations and a mutation in the SLC16A2 gene encoding for the monocarboxylate transporter 8 (MCT8). This mutation leads to a loss of thyroid hormone transport activity. One hypothesis to explain the unusual hormone concentrations of AHDS patients is that due to the loss of thyroid hormone transport activity, thyroxine (T4) is partially retained in thyroid cells. This hypothesis is investigated by extending a mathematical model of the pituitary-thyroid feedback loop to include a model of the net effects of membrane transporters such that the thyroid hormone transport activity can be considered. A nonlinear modeling approach based on the Michaelis-Menten kinetics and its linear approximation are employed to consider the membrane transporters. The unknown parameters are estimated through a constrained parameter optimization. In dynamic simulations, damaged membrane transporters result in a retention of T4 in thyroid cells and ultimately in the unusual hormone concentrations of AHDS patients. The Michaelis-Menten modeling approach and its linear approximation lead to similar results. The results support the hypothesis that a partial retention of T4 in thyroid cells represents one mechanism responsible for the unusual hormone concentrations of AHDS patients. Moreover, our results suggest that the retention of T4 in thyroid cells could be the main reason for the unusual hormone concentrations of AHDS patients.Item Open Access Methodological concepts for data-integrated modeling of biological systems with applications in cancer biology(2023) Jensch, Antje; Radde, Nicole (Prof. Dr. rer. nat.)Item Open Access A statistical framework to optimize experimental design for inference problems in systems biology based on normalized data(2022) Thomaseth, Caterina; Radde, Nicole (Prof. Dr. rer. nat.)Inference problems in Systems Biology are primarily based on the theoretical assumption that a measured dataset comprises noisy realizations following some underlying stochastic distribution, having well-defined statistical properties. This uncertainty in the input quantities propagates through the inference process, influences the uncertainty of the estimated model parameters and subsequently affects the quality and reliability of model predictions. Understanding the mechanisms of noise propagation over an inference problem will therefore be instrumental in designing an optimal and robust experimental protocol to reduce the uncertainty of the estimated quantities of interest. This thesis investigates the underlying mechanisms of noise propagation from measured experimental data to estimated parameters by developing a statistical framework to characterize and analyse non-linear transformations of stochastic distributions. Among such non-linear transformations, data normalization, a required step for some common experimental techniques, requires specific attention, representing an additional modification of noise properties. Mathematically, the normalization step translates into ratios of two distributions. We consider standard assumptions on the distributions associated with biological raw data. In this thesis we explore three specific classes of inference problems relevant for Systems Biology applications. At first we consider the problem of statistical inference of different parametrized error models for normalized data. Subsequently, we investigate the effect of such error models when coupled with different normalization strategies on results of parameter estimation for dynamic models of biochemical reaction networks. We conclude this thesis by analysing the effects of noise propagation on Modular Response Analysis based network reconstruction. From our simulation results, we observe that non-linear noise transformations may lead to very uncertain and/or erroneous inference results. Additionally, based on the quantification of statistical measures for accuracy and precision of the inference results, we derive practical advice for an optimized and robust experimental design in order to reduce the uncertainty of the estimated quantities.Item Open Access Hepatectomy-induced alterations in hepatic perfusion and function : toward multi-scale computational modeling for a better prediction of post-hepatectomy liver function(2021) Christ, Bruno; Collatz, Maximilian; Dahmen, Uta; Herrmann, Karl-Heinz; Höpfl, Sebastian; König, Matthias; Lambers, Lena; Marz, Manja; Meyer, Daria; Radde, Nicole; Reichenbach, Jürgen R.; Ricken, Tim; Tautenhahn, Hans-MichaelLiver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.Item Open Access Editorial - computational modeling for liver surgery and interventions(2022) Christ, Bruno; Dahmen, Uta; Radde, Nicole; Ricken, Tim