Self-reproducing entities in an artifical chemistry: implications of autopoietic and other organisations

The SCL model system, an artificial chemistry used for the illustration of the concept autopoiesis, is extended to show self-reproducing entities. The theory of autopoiesis was developed by the biologists Humberto Maturana and Francisco Varela around 1971 to point out the organisation of living systems One of the aims of this theory is to explain the perceived autonomy of living beings. The degree to which the theory succeeds in doing so is investigated. Along the way some ambiguities m the theory are pointed out and suggestions for improvements are made. The conclusion, however, is th at autopoiesis alone is not sufficient for a high degree of autonomy, although it is a step in the right direction. Furthermore it is shown that the entities exhibited in the original SCL model system are not autopoietic, whereas in the extended system they are. Together with SCL some other real and artificial chemical model systems are investigated with respect to the two concepts autonomy and autopoiesis. Furthermore, the utility of autopoiesis as a guiding principle for Artificial Life research is considered. The conclusion is that because autopoiesis suffers from too many ambiguities, other concepts in conjunction with some aspects taken from autopoiesis should be preferred. In particular, the concept of organisation developed by Fontana and Buss (1994) and the theory of collectively auto catalytic networks advanced by Kauffman (1993) seem to be better starting points when working towards a definition of life or concerning questions of the origin of life. Nonetheless, autopoiesis remains useful because some of its variants stress the feature of self-individuation of living beings which the previously mentioned two theories only do to a lesser extent

Computing Combinatorial Intervention Strategies and Failure Modes in Signaling Networks

The identification of combinatorial intervention strategies and the elucidation of failure modes that may cause aberrant behavior of cellular signaling networks are highly relevant topics in cell biology, medicine, and pharmaceutical industry. We have recently introduced the concept of minimal intervention sets (MISs)—minimal combinations of knock-ins and knock-outs provoking a desired/observed response in certain target nodes—to tackle those problemswithin a Boolean/logical framework.We first generalize the notion ofMISs and then present several techniques for search space reduction facilitating the enumeration of MISs in networks of realistic size. One strategy exploits topological information about network-wide interdependencies between the nodes to discard unfavorable single interventions. A similar technique checks during the algorithm whether all target nodes of an intervention problem can be influenced in appropriate direction (up/down) by the interventions contained in MIS candidates. Another strategy takes lessons from electrical engineering: certain interventions are equivalent with respect to their effect on the target nodes and can therefore be grouped in fault equivalence classes (FECs). FECs resulting from so-called structural equivalence can be easily computed in a preprocessing step, with the advantage that only one representative per class needs to be considered when constructing the MISs in the main algorithm. With intervention problems from realistic networks as benchmarks, we show that these algorith-mic improvements may reduce the computation time up to 99%, increasing the applicabil-ity of MISs in practice. Key words: Boolean networks, diagnosis, drug target identification, failure equivalence classes

CNApy: a CellNetAnalyzer GUI in Python for Analyzing and Designing Metabolic Networks

SUMMARY: Constraint-based reconstruction and analysis (COBRA) is a widely used modeling framework for analyzing and designing metabolic networks. Here, we present CNApy, an open-source cross-platform desktop application written in Python, which offers a state-of-the-art graphical front-end for the intuitive analysis of metabolic networks with COBRA methods. While the basic look-and-feel of CNApy is similar to the user interface of the MATLAB toolbox CellNetAnalyzer, it provides various enhanced features by using components of the powerful Qt library. CNApy supports a number of standard and advanced COBRA techniques and further functionalities can be easily embedded in its GUI facilitating modular extension in the future. AVAILABILITY AND IMPLEMENTATION: CNApy can be installed via conda and its source code is freely available at https://github.com/cnapy-org/CNApy under the Apache 2 license

Controlling the gain contribution of background emitters in few-quantum-dot microlasers

Funding: European Research Council under the European Union's Seventh Framework ERC Grant Agreement No. 615613; German Research Foundation via Grant-No.: Re2974/10-1, Gi1121/1-1.We provide experimental and theoretical insight into single-emitter lasing effects in a quantum dot (QD)-microlaser under controlled variation of background gain provided by off-resonant discrete gain centers. For that purpose, we apply an advanced two-color excitation concept where the background gain contribution of off-resonant QDs can be continuously tuned by precisely balancing the relative excitation power of two lasers emitting at different wavelengths. In this way, by selectively exciting a singleresonant QD and off-resonant QDs, we identify distinct single-QD signatures in the lasing characteristics and distinguish between gain contributions of a single resonant emitter and a countable number of offresonant background emitters to the optical output of the microlaser. Our work addresses the importantquestion whether single-QD lasing is feasible in experimentally accessible systems and shows that, for the investigated microlaser, the single-QD gain needs to be supported by the background gain contribution ofoff-resonant QDs to reach the transition to lasing. Interestingly, while a single QD cannot drive the investigated micropillar into lasing, its relative contribution to the emission can be as high as 70% and it dominates the statistics of emitted photons in the intermediate excitation regime below threshold.Publisher PDFPeer reviewe

Exploring the photon-number distribution of bimodal microlasers with a transition edge sensor

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework ERC Grant Agreement No. 615613, within the EURAMET joint research project MIQC2 from the European Union's Horizon 2020 Research and Innovation Programme and the EMPIR Participating States and from the German Research Foundation within the project RE2974/10-1. The authors thank the State of Bavaria for financial support.A photon-number resolving transition edge sensor (TES) is used to measure the photon-number distribution of two microcavity lasers. The investigated devices are bimodal microlasers with similar emission intensity and photon statistics with respect to the photon auto-correlation. Both high-β microlasers show partly thermal and partly coherent emission around the lasing threshold. For higher pump powers, the strong mode of microlaser { A } emits Poissonian distributed photons while the emission of the weak mode is thermal. In contrast, laser { B } shows a bistability resulting in overlayed thermal and Poissonian distributions. While a standard Hanbury Brown and Twiss experiment cannot distinguish between simple thermal emission of laser { A } and the temporal mode switching of the bistable laser { B }, TESs allow us to measure the photon-number distribution which provides important insight into the underlying emission processes. Indeed, our experimental data and its theoretical description by a master equation approach show that TESs are capable of revealing subtle effects like mode switching of bimodal microlasers. As such our studies clearly demonstrate the benefit and importance of investigating nanophotonic devices via photon-number resolving transition edge sensors.PostprintPeer reviewe

Bladder cancer cells acquire competent mechanisms to escape Fas-mediated apoptosis and immune surveillance in the course of malignant transformation

Mechanisms of resistance against Fas-mediated cell killing have been reported in different malignancies. However, the biological response of immune escape mechanisms might depend on malignant transformation of cancer cells. In this study we investigated different mechanisms of immune escape in 2 well-differentiated low-grade (RT4 and RT112) and 2 poorly differentiated high-grade (T24 and TCCSUP) bladder cancer cell lines. Fas, the receptor of Fas-ligand, is expressed and shedded by human transitional bladder carcinoma cell lines RT4, RT112, T24 and TCCSUP. Cytotoxicity and apoptosis assays demonstrate that in spite of the Fas expression, poorly differentiated T24 and TCCSUP cells are insensitive towards either recombinant Fas-ligand or agonistic apoptosis-inducing monoclonal antibody against Fas. In poorly differentiated T24 and TCCSUP cell lines we were able to detect marked Fas-ligand protein by flow cytometry and Western blot analysis. In grade 1 RT4 and RT112 cells only minor expression of Fas-ligand possibly because of proteinase action. Fas-ligand mRNA translation or post-translational processing seems to be regulated differentially in the cancer cell lines depending on malignant transformation. In co-culture experiments we show that poorly differentiated cells can induce apoptosis and cell death in Jurkat cells and activated peripheral blood mononuclear cells. This in vitro study suggests that bladder cancer cells can take advantage of different mechanisms of immune evasion and become more competent in avoiding immune surveillance during transformation to higher-grade malignant disease. © 2001 Cancer Research Campaign www.bjcancer.co