50 research outputs found

    Conflict resolution and a framework for collaborative interactive evolution

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    Abstract Interactive evolutionary computation (IEC) has proven useful in a variety of applications by combining the subjective evaluation of a user with the massive parallel search power of the genetic algorithm (GA). Here, we articulate a framework for an extension of IEC into collaborative interactive evolution, in which multiple users guide the evolutionary process. In doing so, we introduce the ability for users to combine their efforts for the purpose of evolving effective solutions to problems. This necessarily gives rise to the possibility of conflict between users. We draw on the salient features of the GA to resolve these conflicts and lay the foundation for this new paradigm to be used as a tool for conflict resolution in complex group-wise human-computer interaction tasks

    Thiopurine Methyltransferase Predicts the Extent of Cytotoxicty and DNA Damage in Astroglial Cells after Thioguanine Exposure

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    Thiopurine methyltransferase (Tpmt) is the primary enzyme responsible for deactivating thiopurine drugs. Thiopurine drugs (i.e., thioguanine [TG], mercaptopurine, azathioprine) are commonly used for the treatment of cancer, organ transplant, and autoimmune disorders. Chronic thiopurine therapy has been linked to the development of brain cancer (most commonly astrocytomas), and Tpmt status has been associated with this risk. Therefore, we investigated whether the level of Tpmt protein activity could predict TG-associated cytotoxicity and DNA damage in astrocytic cells. We found that TG induced cytotoxicity in a dose-dependent manner in Tpmt+/+, Tpmt+/− and Tpmt−/− primary mouse astrocytes and that a low Tpmt phenotype predicted significantly higher sensitivity to TG than did a high Tpmt phenotype. We also found that TG exposure induced significantly more DNA damage in the form of single strand breaks (SSBs) and double strand breaks (DSBs) in primary astrocytes with low Tpmt versus high Tpmt. More interestingly, we found that Tpmt+/− astrocytes had the highest degree of cytotoxicity and genotoxicity (i.e., IC50, SSBs and DSBs) after TG exposure. We then used human glioma cell lines as model astroglial cells to represent high (T98) and low (A172) Tpmt expressers and found that A172 had the highest degree of cytoxicity and SSBs after TG exposure. When we over-expressed Tpmt in the A172 cell line, we found that TG IC50 was significantly higher and SSB's were significantly lower as compared to mock transfected cells. This study shows that low Tpmt can lead to greater sensitivity to thiopurine therapy in astroglial cells. When Tpmt deactivation at the germ-line is considered, this study also suggests that heterozygosity may be subject to the greatest genotoxic effects of thiopurine therapy

    Penetration of the Stigma and Style Elicits a Novel Transcriptome in Pollen Tubes, Pointing to Genes Critical for Growth in a Pistil

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    Pollen tubes extend through pistil tissues and are guided to ovules where they release sperm for fertilization. Although pollen tubes can germinate and elongate in a synthetic medium, their trajectory is random and their growth rates are slower compared to growth in pistil tissues. Furthermore, interaction with the pistil renders pollen tubes competent to respond to guidance cues secreted by specialized cells within the ovule. The molecular basis for this potentiation of the pollen tube by the pistil remains uncharacterized. Using microarray analysis in Arabidopsis, we show that pollen tubes that have grown through stigma and style tissues of a pistil have a distinct gene expression profile and express a substantially larger fraction of the Arabidopsis genome than pollen grains or pollen tubes grown in vitro. Genes involved in signal transduction, transcription, and pollen tube growth are overrepresented in the subset of the Arabidopsis genome that is enriched in pistil-interacted pollen tubes, suggesting the possibility of a regulatory network that orchestrates gene expression as pollen tubes migrate through the pistil. Reverse genetic analysis of genes induced during pollen tube growth identified seven that had not previously been implicated in pollen tube growth. Two genes are required for pollen tube navigation through the pistil, and five genes are required for optimal pollen tube elongation in vitro. Our studies form the foundation for functional genomic analysis of the interactions between the pollen tube and the pistil, which is an excellent system for elucidation of novel modes of cell–cell interaction

    Invasive cells in animals and plants: searching for LECA machineries in later eukaryotic life

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    At the poles across kingdoms: phosphoinositides and polar tip growth

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    Collaborative Interactive Evolution

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    This paper examines the efficacy of genetic algorithms (GAs) in combining input from multiple users to control a single interactive system, such as an educational exhibit at a museum. Specifically, the idea of collaborative interactive evolution (that is, interactive evolution with input from multiple users) is introduced for this purpose. Two fitness functions are proposed to guide the collaborative interactive evolution, as well as two non-GA methods for combining user input. The usefulness and success of each of these methods is examined, and the GA is shown to be a viable means for combining user input for the control of a single interactive system

    Conflict Resolution and a Framework for Collaborative Interactive Evolution

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    Interactive evolutionary computation (IEC) has proven useful in a variety of applications by combining the subjective evaluation of a user with the massive parallel search power of the genetic algorithm (GA). Here, we articulate a framework for an extension of IEC into collaborative interactive evolution, in which multiple users guide the evolutionary process. In doing so, we introduce the ability for users to combine their efforts for the purpose of evolving effective solutions to problems. This necessarily gives rise to the possibility of conflict between users. We draw on the salient features of the GA to resolve these conflicts and lay the foundation for this new paradigm to be used as a tool for conflict resolution in complex group-wise human-computer interaction tasks
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