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von Mammen, S.

Publications and source records attributed to von Mammen, S..

2 recordsLinked to original sources

Thrombo-inflammation analyzed in a validated seven-layer platelet decision model: cellular decisions are tough problems fast and heuristically solved

Decisions in biology happen fast and are driven by evolution to optimize survival chances. In platelets, this is achieved by organizing signaling cascades into rapid decision-funnels with modulatory crosstalk. We show that network decision processes underlying cellular decisions are tough to solve (equivalent to classical satisfiability problems, SAT). Hence, heuristics, modular decision-making, and decision funnels are required for efficient decisions. We establish this using a seven-layer platelet decision network that agrees well with all available genetic and functional experimental data. Platelet decision cascades are robust to perturbations: For example, receptors such as TRPM7 modulate platelet activity. However, knockouts of the receptors still leave platelets reactive overall. Dynamic control resolves relaying functions from kinases to cytoskeleton alterations. This allows fast execution of platelet shape change or aggregation. Stress conditions can shift platelet decision funnels towards constant activation of aggregation or immune signaling, causing thrombosis or thrombo-inflammation. Based on the network dynamics, we conclude that platelets pragmatically resolve the complex (non-polynomial (NP)) cellular decision problems by using a similar relaxation to those proposed in mathematics - many different configurations end up in similar states. Metamathematical considerations (no mathematical proof) suggest that NP problems are more complex then P problems. One sentence abstractWe show that cellular decision problems like the platelet signaling cascade may need unexpectedly long to solve but in general, they are efficiently solved using heuristics ("decision funnels"), implying fast decisions but the risk of chronic stress and inflammation.

bioinformatics↗

Interactive, visual simulation of a spatio-temporal model of gas exchange in the human alveolus

In interdisciplinary fields such as systems biology, close collaboration between experimentalists and theorists is crucial for the success of a project. Theoretical modeling in physiology usually describes complex systems with many interdependencies. On one hand, these models have to be grounded on experimental data. On the other hand, experimenters must be able to penetrate the model in its dependencies in order to correctly interpret the results in the physiological context. When theorists and experimenters collaborate, communicating results and ideas is sometimes challenging. We promote interactive, visual simulations as an engaging way to communicate theoretical models in physiology and to thereby advance our understanding of the process of interest. We defined a new spatio-temporal model for gas exchange in the human alveolus and implemented it in an interactive simulation software named Alvin. In Alvin, the course of the simulation can be traced in a three-dimensional rendering of an alveolus and dynamic plots. The user can interact by configuring essential model parameters. Alvin allows to run and compare multiple simulation instances simultaneously. The mathematical model was developed with the aim of visualization and the simulation software was engineered based on a requirements analysis. Our work resulted in an integrative gas exchange model and an interactive application that exceed the current standards. We exemplified the use of Alvin for research by identifying unknown dependencies in published experimental data. Employing a detailed questionnaire, we showed the benefits of Alvin for education. We postulate that interactive, visual simulation of theoretical models, as we have implemented with Alvin on respiratory processes in the alveolus, can be of great help for communication between specialists and thereby advancing research.

bioinformatics↗