07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
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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 Modeling of biocatalytic reactions: a workflow for model calibration, selection, and validation using Bayesian statistics(2019) Eisenkolb, Ina; Jensch, Antje; Eisenkolb, Kerstin; Kramer, Andrei; Buchholz, Patrick C. F.; Pleiss, Jürgen; Spiess, Antje; Radde, NicoleWe present a workflow for kinetic modeling of biocatalytic reactions which combines methods from Bayesian learning and uncertainty quantification for model calibration, model selection, evaluation, and model reduction in a consistent statistical frame-work. Our workflow is particularly tailored to sparse data settings in which a considerable variability of the parameters remains after the models have been adapted to available data, a ubiquitous problem in many real-world applications. Our workflow is exemplified on an enzyme-catalyzed two-substrate reaction mechanism describing the symmetric carboligation of 3,5-dimethoxy-benzaldehyde to (R)-3,3',5,5'-tetramethoxybenzoin catalyzed by benzaldehyde lyase from Pseudomonas fluorescens. Results indicate a substrate-dependent inactivation of enzyme, which is in accordance with other recent studies.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 Rapid sampling of Escherichia coli after changing oxygen conditions reveals transcriptional dynamics(2017) Wulffen, Joachim von; Ulmer, Andreas; Jäger, Günter; Sawodny, Oliver; Feuer, RonnyEscherichia coli is able to shift between anaerobic and aerobic metabolism by adapting its gene expression, e.g., of metabolic genes, to the new environment. The dynamics of gene expression that result from environmental shifts are limited, amongst others, by the time needed for regulation and transcription elongation. In this study, we examined gene expression dynamics after an anaerobic-to-aerobic shift on a short time scale (0.5, 1, 2, 5, and 10 min) by RNA sequencing with emphasis on delay times and transcriptional elongation rates (TER). Transient expression patterns and timing of differential expression, characterized by delay and elongation, were identified as key features of the dataset. Gene ontology enrichment analysis revealed early upregulation of respiratory and iron-related gene sets. We inferred specific TERs of 89 operons with a mean TER of 42.0 nt/s and mean delay time of 22.4 s. TERs correlate with sequence features, such as codon bias, whereas delay times correlate with the involvement of regulators. The presented data illustrate that at very short times after a shift in oxygenation, extensional changes of the transcriptome, such as temporary responses, can be observed. Besides regulation, TERs contribute to the dynamics of gene expression.Item Open Access Implementation and validation of the extended Hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models(2017) Kleinbach, Christian; Martynenko, Oleksandr; Promies, Janik; Häufle, Daniel F. B.; Fehr, Jörg; Schmitt, SynIn the state of the art finite element AHBMs for car crash analysis in the LS-DYNA software material named *MAT_MUSCLE (*MAT_156) is used for active muscles modeling. It has three elements in parallel configuration, which has several major drawbacks: restraint approximation of the physical reality, complicated parameterization and absence of the integrated activation dynamics. This study presents implementation of the extended four element Hill-type muscle model with serial damping and eccentric force-velocity relation including Ca2+ dependent activation dynamics and internal method for physiological muscle routing.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 Model-based characterization of inflammatory gene expression patterns of activated macrophages(2016) Rex, Julia; Albrecht, Ute; Ehlting, Christian; Thomas, Maria; Zanger, Ulrich M.; Sawodny, Oliver; Häussinger, Dieter; Ederer, Michael; Feuer, Ronny; Bode, Johannes G.Macrophages are cells with remarkable plasticity. They integrate signals from their microenvironment leading to context-dependent polarization into classically (M1) or alternatively (M2) activated macrophages, representing two extremes of a broad spectrum of divergent phenotypes. Thereby, macrophages deliver protective and pro-regenerative signals towards injured tissue but, depending on the eliciting damage, may also be responsible for the generation and aggravation of tissue injury. Although incompletely understood, there is emerging evidence that macrophage polarization is critical for these antagonistic roles. To identify activation-specific expression patterns of chemokines and cytokines that may confer these distinct effects a systems biology approach was applied. A comprehensive literature-based Boolean model was developed to describe the M1 (LPS-activated) and M2 (IL-4/13-activated) polarization types. The model was validated using high-throughput transcript expression data from murine bone marrow derived macrophages. By dynamic modeling of gene expression, the chronology of pathway activation and autocrine signaling was estimated. Our results provide a deepened understanding of the physiological balance leading to M1/M2 activation, indicating the relevance of co-regulatory signals at the level of Akt1 or Akt2 that may be important for directing macrophage polarization.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.