Optimizing radiation therapy treatments by exploring tumour ecosystem dynamics in-silico

In this contribution, we propose a system-level compartmental population dynamics model of tumour cells that interact with the patient (innate) immune system under the impact of radiation therapy (RT). The resulting in silico - model enables us to analyse the system-level impact of radiation on the tumour ecosystem. The Tumour Control Probability (TCP) was calculated for varying conditions concerning therapy fractionation schemes, radio-sensitivity of tumour sub-clones, tumour population doubling time, repair speed and immunological elimination parameters. The simulations exhibit a therapeutic benefit when applying the initial 3 fractions in an interval of 2 days instead of daily delivered fractions. This effect disappears for fast-growing tumours and in the case of incomplete repair. The results suggest some optimisation potential for combined hyperthermia-radiotherapy. Regarding the sensitivity of the proposed model, cellular repair of radiation-induced damages is a key factor for tumour control. In contrast to this, the radio-sensitivity of immune cells does not influence the TCP as long as the radio-sensitivity is higher than those for tumour cells. The influence of the tumour sub-clone structure is small (if no competition is included). This work demonstrates the usefulness of in silico – modelling for identifying optimisation potentials

Sequence selection in an autocatalytic binary polymer model

An autocatalytic pattern matching polymer system is studied as an abstract model for chemical ecosystem evolution. Highly ordered populations with particular sequence patterns appear spontaneously out of a vast number of possible states. The interplay between the selected microscopic sequence patterns and the macroscopic cooperative structures is examined. Stability, fluctuations, and evolutionary selection mechanisms are investigated for the involved self-organizing processes

Minimal model of self-replicating nanocells: a physically embodied information-free scenario

The building of minimal self-reproducing systems with a physical embodiment (generically called protocells) is a great challenge, with implications for both theory and applied sciences. Although the classical view of a living protocell assumes that it includes information-carrying molecules as an essential ingredient, a dividing cell-like structure can be built from a metabolism-container coupled system, only. An example of such a system, modeled with dissipative particle dynamics, is presented here. This article demonstrates how a simple coupling between a precursor molecule and surfactant molecules forming micelles can experience a growth-division cycle in a predictable manner, and analyzes the influence of crucial parameters on this replication cycle. Implications of these results for origins of cellular life and living technology are outlined.Comment: 9 pages, 10 figure

On the Growth Rate of Non-Enzymatic Molecular Replicators

It is well known that non-enzymatic template directed molecular replicators X + nO ---> 2X exhibit parabolic growth d[X]/dt = k [X]^{1/2}. Here, we analyze the dependence of the effective replication rate constant k on hybridization energies, temperature, strand length, and sequence composition. First we derive analytical criteria for the replication rate k based on simple thermodynamic arguments. Second we present a Brownian dynamics model for oligonucleotides that allows us to simulate their diffusion and hybridization behavior. The simulation is used to generate and analyze the effect of strand length, temperature, and to some extent sequence composition, on the hybridization rates and the resulting optimal overall rate constant k. Combining the two approaches allows us to semi-analytically depict a fitness landscape for template directed replicators. The results indicate a clear replication advantage for longer strands at low temperatures.Comment: Submitted to: Entrop

Towards low-carbon conferencing : acceptance of virtual conferencing solutions and other sustainability measures in the ALIFE community

The latest report from the Intergovernmental Panel on Climate Change (IPCC) estimated that humanity has a time window of about 12 years in order to prevent anthropogenic climate change of catastrophic magnitude. Green house gas emission from air travel, which is currently rising, is possibly one of the factors that can be most readily reduced. Within this context, we advocate for the re-design of academic conferences in order to decrease their environmental footprint. Today, virtual technologies hold the promise to substitute many forms of physical interactions and increasingly make their way into conferences to reduce the number of travelling delegates. Here, we present the results of a survey in which we gathered the opinion on this topic of academics worldwide. Results suggest there is ample room for challenging the (dangerous) business-as-usual inertia of scientific lifestyle

The MATCHIT automaton : exploiting compartmentalization for the synthesis of branched polymers

We propose an automaton, a theoretical framework that demonstrates how to improve the yield of the synthesis of branched chemical polymer reactions. This is achieved by separating substeps of the path of synthesis into compartments. We use chemical containers (chemtainers) to carry the substances through a sequence of fixed successive compartments. We describe the automaton in mathematical terms and show how it can be configured automatically in order to synthesize a given branched polymer target. The algorithm we present finds an optimal path of synthesis in linear time. We discuss how the automaton models compartmentalized structures found in cells, such as the endoplasmic reticulum and the Golgi apparatus, and we show how this compartmentalization can be exploited for the synthesis of branched polymers such as oligosaccharides. Lastly, we show examples of artificial branched polymers and discuss how the automaton can be configured to synthesize them with maximal yield