Titel Deelnemers "Korte inhoud" "Optimization of an artificial neural network structure for modelling carbon capture in spray columns" "Ulderico Di Caprio, Emine Kayahan, Min Wu, Tom Van Gerven, Steffen Waldherr, Mumin Enis Leblebici" "Anthropogenic CO2 emissions reinforce global warming. The most mature technology to capture post-combustion CO2 is the absorption with aqueous monoethanolamine (MEA) in spray or packed columns. However, this process is not considered economically viable. One reason for this hindrance is the low overall mass transfer coefficients (KGa) resulting in large process volumes that are high in capital and operating costs. Spray columns offer some advantages over the packed columns such as the lack of expensive column internals, low pressure drop and higher KGa. Although several spray columns have been investigated experimentally, there are only a few efforts to model this process. Because of the high intercorrelation between the process variables, modelling is a complex task. Machine learning techniques have shown great accuracy in modeling this kind of systems using large amounts of data. Artificial neural network (ANN) is one of the most promising and highly modular techniques in this field. The aim of this work is to find the ANN structure with higher accuracy and generalization capabilities to model the KGa for CO2 absorption in spray columns using aqueous MEA. The ANN is trained using the back-propagation algorithm. The structure with higher accuracy and generalization properties is searched by a Bayesian optimizer. The trained model has a coefficient of determination (R2) of 0.98, and a mean squared error (MSE) of 7.89e-4 on the validation set. It returns prediction errors below 20%. The optimizer found that the autoencoder structure had the higher prediction accuracy and generalization capabilities. This shape has great feature importance extrapolation capabilities, allowing the ANN to have a high prediction accuracy. The proposed procedure can be applied also for other processes where transfer coefficients need to be estimated and optimized." "Using resource constraints derived from genomic and proteomic data in metabolic network models" "Kobe De Becker, Niccolo Totis, Kristel Bernaerts, Steffen Waldherr" "The tyrosine phosphatase SHP2 increases robustness and information transfer within IL-6-induced JAK/STAT signalling" "Steffen Waldherr" "BACKGROUND: Cell-to-cell heterogeneity is an inherent feature of multicellular organisms and is central in all physiological and pathophysiological processes including cellular signal transduction. The cytokine IL-6 is an essential mediator of pro- and anti-inflammatory processes. Dysregulated IL-6-induced intracellular JAK/STAT signalling is associated with severe inflammatory and proliferative diseases. Under physiological conditions JAK/STAT signalling is rigorously controlled and timely orchestrated by regulatory mechanisms such as expression of the feedback-inhibitor SOCS3 and activation of the protein-tyrosine phosphatase SHP2 (PTPN11). Interestingly, the function of negative regulators seems not to be restricted to controlling the strength and timely orchestration of IL-6-induced STAT3 activation. Exemplarily, SOCS3 increases robustness of late IL-6-induced STAT3 activation against heterogenous STAT3 expression and reduces the amount of information transferred through JAK/STAT signalling. METHODS: Here we use multiplexed single-cell analyses and information theoretic approaches to clarify whether also SHP2 contributes to robustness of STAT3 activation and whether SHP2 affects the amount of information transferred through IL-6-induced JAK/STAT signalling. RESULTS: SHP2 increases robustness of both basal, cytokine-independent STAT3 activation and early IL-6-induced STAT3 activation against differential STAT3 expression. However, SHP2 does not affect robustness of late IL-6-induced STAT3 activation. In contrast to SOCS3, SHP2 increases the amount of information transferred through IL-6-induced JAK/STAT signalling, probably by reducing cytokine-independent STAT3 activation and thereby increasing sensitivity of the cells. These effects are independent of SHP2-dependent MAPK activation. CONCLUSION: In summary, the results of this study extend our knowledge of the functions of SHP2 in IL-6-induced JAK/STAT signalling. SHP2 is not only a repressor of basal and cytokine-induced STAT3 activity, but also ensures robustness and transmission of information. Plain English summary Cells within a multicellular organism communicate with each other to exchange information about the environment. Communication between cells is facilitated by soluble molecules that transmit information from one cell to the other. Cytokines such as interleukin-6 are important soluble mediators that are secreted when an organism is faced with infections or inflammation. Secreted cytokines bind to receptors within the membrane of their target cells. This binding induces activation of an intracellular cascade of reactions called signal transduction, which leads to cellular responses. An important example of intracellular signal transduction is JAK/STAT signalling. In healthy organisms signalling is controlled and timed by regulatory mechanisms, whose activation results in a controlled shutdown of signalling pathways. Interestingly, not all cells within an organism are identical. They differ in the amount of proteins involved in signal transduction, such as STAT3. These differences shape cellular communication and responses to intracellular signalling. Here, we show that an important negative regulatory protein called SHP2 (or PTPN11) is not only responsible for shutting down signalling, but also for steering signalling in heterogeneous cell populations. SHP2 increases robustness of STAT3 activation against variable STAT3 amounts in individual cells. Additionally, it increases the amount of information transferred through JAK/STAT signalling by increasing the dynamic range of pathway activation in heterogeneous cell populations. This is an amazing new function of negative regulatory proteins that contributes to communication in heterogeneous multicellular organisms in health and disease. Video Abstract." "Comparing cell population balance model simulation through Gaussian processes and discretisation" "Armin Küper, Niccolo Totis, Steffen Waldherr" "A Population-Based Approach to Study the Effects of Growth and Division Rates on the Dynamics of Cell Size Statistics" "Niccolo Totis, Steffen Waldherr" "Observer and controller design for a methane bioconversion process" "Kobe De Becker, Steffen Waldherr" "Gaussian Processes for Improved Dynamic Modeling in the Predictive Control of an Arduino Temperature Control Lab" "Steffen Waldherr" "Adaptive predictive control of bioprocesses with constraint-based modeling and estimation" "Banafsheh Jabarivelisdeh, Steffen Waldherr" "Numerical Gaussian process Kalman filtering" "Armin Küper, Steffen Waldherr" "Luenberger observer design for a dynamic system with embedded linear program, applied to bioprocesses" "Kobe De Becker, Kristel Bernaerts, Steffen Waldherr"