A Provably Convergent Control Closure Scheme for the Method of Moments of the Chemical Master Equation.

In this article, we introduce a novel moment closure scheme based on concepts from model predictive control (MPC) to accurately describe the time evolution of the statistical moments of the solution of the chemical master equation (CME). The method of moments, a set of ordinary differential equations frequently used to calculate the first moments, is generally not closed since lower-order moments depend on higher-order moments. To overcome this limitation, we interpret the moment equations as a nonlinear dynamical system, where the first moments serve as states, and the closing moments serve as the control input.

Model-Based and Data-Driven Control of Event- and Self-Triggered Discrete-Time Linear Systems.

The present paper considers the model-based and data-driven control of unknown discrete-time linear systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller.

Cell cycle progression and transmitotic apoptosis resistance promote escape from extrinsic apoptosis.

Extrinsic apoptosis relies on TNF-family receptor activation by immune cells or receptor-activating drugs. Here, we monitored cell cycle progression at a resolution of minutes to relate apoptosis kinetics and cell-to-cell heterogeneities in death decisions to cell cycle phases. Interestingly, we found that cells in S phase delay TRAIL receptor-induced death in favour of mitosis, thereby passing on an apoptosis-primed state to their offspring.

Robust and optimal predictive control of the COVID-19 outbreak.

We investigate adaptive strategies to robustly and optimally control the COVID-19 pandemic via social distancing measures based on the example of Germany. Our goal is to minimize the number of fatalities over the course of two years without inducing excessive social costs. We consider a tailored model of the German COVID-19 outbreak with different parameter sets to design and validate our approach.

Sample-based modeling reveals bidirectional interplay between cell cycle progression and extrinsic apoptosis.

Apoptotic cell death can be initiated through the extrinsic and intrinsic signaling pathways. While cell cycle progression promotes the responsiveness to intrinsic apoptosis induced by genotoxic stress or spindle poisons, this has not yet been studied conclusively for extrinsic apoptosis. Here, we combined fluorescence-based time-lapse monitoring of cell cycle progression and cell death execution by long-term time-lapse microscopy with sampling-based mathematical modeling to study cell cycle dependency of TRAIL-induced extrinsic apoptosis in NCI-H460/geminin cells.

Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities.

Modern cytometry methods allow collecting complex, multi-dimensional data sets from heterogeneous cell populations at single-cell resolution. While methods exist to describe the progression and order of cellular processes from snapshots of such populations, these descriptions are limited to arbitrary pseudotime scales. Here we describe MAPiT, an universal transformation method that recovers real-time dynamics of cellular processes from pseudotime scales by utilising knowledge of the distributions on the real scales.

Analysis of primitive genetic interactions for the design of a genetic signal differentiator.

We study the dynamic and static input-output behavior of several primitive genetic interactions and their effect on the performance of a genetic signal differentiator. In a simplified design, several requirements for the linearity and time-scales of processes like transcription, translation and competitive promoter binding were introduced. By experimentally probing simple genetic constructs in a cell-free experimental environment and fitting semi-mechanistic models to these data, we show that some of these requirements can be verified, while others are only met with reservations in certain operational regimes.

Moment Dynamics of Zirconia Particle Formation for Optimizing Particle Size Distribution.

We study the particle formation process of Zirconia ( ZrO 2 )-based material. With a model-based description of the particle formation process we aim for identifying the main growth mechanisms for different process parameters. After the introduction of a population balance based mathematical model, we derive the moment dynamics of the particle size distribution and compare the model to experimental data.

Sensitization of glioblastoma cells to TRAIL-induced apoptosis by IAP- and Bcl-2 antagonism.

Due to the lack of effective treatments for glioblastoma (GBM), we here studied the responsiveness of GBM cell lines to the combination of death ligand, TRAIL and the IAP antagonist, TL32711 (Birinapant). Responses were highly heterogeneous, with synergistic apoptosis as well as treatment resistance observed. Caspase-8 and Bid, together with caspase-3, form a nonlinear signalling hub that efficiently induced apoptosis in responder cell lines.

Bcl-2-mediated control of TRAIL-induced apoptotic response in the non-small lung cancer cell line NCI-H460 is effective at late caspase processing steps.

Dysregulation of the mitochondrial signaling pathway of apoptosis induction represents a major hurdle in tumor therapy. The objective of the presented work was to investigate the role of the intrinsic (mitochondrial) apoptotic pathway in the non-small lung cancer cell line NCI-H460 upon induction of apoptosis using the highly bioactive TRAIL derivative Db-scTRAIL. NCI-H460 cells were TRAIL sensitive but an only about 3 fold overexpression of Bcl-2 was sufficient to induce a highly TRAIL resistant phenotype, confirming that the mitochondrial pathway is crucial for TRAIL-induced apoptosis induction.

A resource dependent protein synthesis model for evaluating synthetic circuits.

Reliable in silico design of synthetic gene networks necessitates novel approaches to model the process of protein synthesis under the influence of limited resources. We present such a novel protein synthesis model which originates from the Ribosome Flow Model and among other things describes the movement of RNA-polymerase and ribosomes on mRNA and DNA templates, respectively. By analyzing the convergence properties of this model based upon geometric considerations, we present additional insights into the dynamic mechanisms of the process of protein synthesis.

The circuit-breaking algorithm for monotone systems.

In earlier work, we have introduced the circuit-breaking algorithm (CBA) for the analysis of intracellular regulation networks. This algorithm uses the network topology to construct a one-dimensional circuit-characteristic whose zeros correspond to the fixed points of the system. In this study, we apply the CBA to monotone systems whose flow preserves a partial order with respect to some orthant cone.

A new model to simulate and analyze proliferating cell populations in BrdU labeling experiments.

Background: This paper presents a novel model for proliferating cell populations in labeling experiments. It is especially tailored to the technique of Bromodeoxyuridine (BrdU), which is taken up by dividing cells and thus accumulates with increasing division number during uplabeling. The study of the evolving label intensities of BrdU labeled cell populations is aimed at quantifying proliferation properties such as division and death rates.

Pain modulators regulate the dynamics of PKA-RII phosphorylation in subgroups of sensory neurons.

Knowledge about the molecular structure of protein kinase A (PKA) isoforms is substantial. In contrast, the dynamics of PKA isoform activity in living primary cells has not been investigated in detail. Using a high content screening microscopy approach, we identified the RIIβ subunit of PKA-II to be predominantly expressed in a subgroup of sensory neurons.

Wound-healing growth factor, basic FGF, induces Erk1/2-dependent mechanical hyperalgesia.

Unlabelled: Growth factors such as nerve growth factor and glial cell line-derived neurotrophic factor are known to induce pain sensitization. However, a plethora of other growth factors is released during inflammation and tissue regeneration, and many of them are essential for wound healing. Which wound-healing factors also alter the sensitivity of nociceptive neurons is not well known.

A visual analytics approach for models of heterogeneous cell populations.

In recent years, cell population models have become increasingly common. In contrast to classic single cell models, population models allow for the study of cell-to-cell variability, a crucial phenomenon in most populations of primary cells, cancer cells, and stem cells. Unfortunately, tools for in-depth analysis of population models are still missing.

Threshold-free population analysis identifies larger DRG neurons to respond stronger to NGF stimulation.

Sensory neurons in dorsal root ganglia (DRG) are highly heterogeneous in terms of cell size, protein expression, and signaling activity. To analyze their heterogeneity, threshold-based methods are commonly used, which often yield highly variable results due to the subjectivity of the individual investigator. In this work, we introduce a threshold-free analysis approach for sparse and highly heterogeneous datasets obtained from cultures of sensory neurons.

Heterogeneity reduces sensitivity of cell death for TNF-stimuli.

Background: Apoptosis is a form of programmed cell death essential for the maintenance of homeostasis and the removal of potentially damaged cells in multicellular organisms. By binding its cognate membrane receptor, TNF receptor type 1 (TNF-R1), the proinflammatory cytokine Tumor Necrosis Factor (TNF) activates pro-apoptotic signaling via caspase activation, but at the same time also stimulates nuclear factor κB (NF-κB)-mediated survival pathways. Differential dose-response relationships of these two major TNF signaling pathways have been described experimentally and using mathematical modeling.

Identification of models of heterogeneous cell populations from population snapshot data.

Background: Most of the modeling performed in the area of systems biology aims at achieving a quantitative description of the intracellular pathways within a "typical cell". However, in many biologically important situations even clonal cell populations can show a heterogeneous response. These situations require study of cell-to-cell variability and the development of models for heterogeneous cell populations.

Bridging time scales in cellular decision making with a stochastic bistable switch.

Background: Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. Some of these transformations act over a very long time scale on the cell population level, up to the entire lifespan of the organism.

Results: In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occurring on a time scale of minutes to hours.

Amplitude distribution of stochastic oscillations in biochemical networks due to intrinsic noise.

Intrinsic noise is a common phenomenon in biochemical reaction networks and may affect the occurence and amplitude of sustained oscillations in the states of the network. To evaluate properties of such oscillations in the time domain, it is usually required to conduct long-term stochastic simulations, using for example the Gillespie algorithm. In this paper, we present a new method to compute the amplitude distribution of the oscillations without the need for long-term stochastic simulations.

Mechanism of PP2A-mediated IKK beta dephosphorylation: a systems biological approach.

Background: Biological effects of nuclear factor-kappaB (NF kappaB) can differ tremendously depending on the cellular context. For example, NF kappaB induced by interleukin-1 (IL-1) is converted from an inhibitor of death receptor induced apoptosis into a promoter of ultraviolet-B radiation (UVB)-induced apoptosis. This conversion requires prolonged NF kappaB activation and is facilitated by IL-1 + UVB-induced abrogation of the negative feedback loop for NF kappaB, involving a lack of inhibitor of kappaB (I kappaB alpha) protein reappearance.

Simulation of dynamics-coupling in piezoelectric tube scanners by reduced order finite element analysis.

Piezoelectric tube scanners are widely used in scanning probe microscopes to position the sample or the probe. Fast and accurate scanning requires the suppression of dominant low-frequency resonances as well as the compensation of dynamics-coupling effects. The present article gives a detailed description of the fully coupled tube scanner dynamics over a wide frequency range modeled by finite element (FE) analysis using the commercially available software package ANSYS.

Mathematical modeling and analysis of force induced bone growth.

Bone is a dynamic living tissue that undergoes continuous adaptation of its mass and structure in response to mechanical and biological environment demands. Studies of bone adaptation have focused on metabolic or mechanical stimulus, but mathematical models of bone adaptation considering both, are not available by now. In this paper, we propose a mathematical model of bone adaptation during a remodeling cycle due to mechanical stimulus with the introduction of osteocytes as mechanotransducers.

Steady state and (bi-) stability evaluation of simple protease signalling networks.

Signal transduction networks are complex, as are their mathematical models. Gaining a deeper understanding requires a system analysis. Important aspects are the number, location and stability of steady states.