401 research outputs found

    Experimental Resonance Enhanced Multiphoton Ionization (REMPI) studies of small molecules

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    Resonance enhanced multiphoton ionization (REMPI) utilizes tunable dye lasers to ionize an atom or molecule by first preparing an excited state by multiphoton absorption and then ionizing that state before it can decay. This process is highly selective with respect to both the initial and resonant intermediate states of the target, and it can be extremely sensitive. In addition, the products of the REMPI process can be detected as needed by analyzing the resulting electrons, ions, fluorescence, or by additional REMPI. This points to a number of exciting opportunities for both basic and applied science. On the applied side, REMPI has great potential as an ultrasensitive, highly selective detector for trace, reactive, or transient species. On the basic side, REMPI affords an unprecedented means of exploring excited state physics and chemistry at the quantum-state-specific level. An overview of current studies of excited molecular states is given to illustrate the principles and prospects of REMPI

    Rotationally resolved energy-dispersive photoelectron spectroscopy of H_2O: Photoionization of the C̃(0,0,0) state at 355 nm

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    Measured and calculated rotationally resolved photoelectron spectra for photoionization of low rotational levels of the C̃^1B_1 Rydberg state of water are reported. This is the first example of rotationally resolved photoionization spectra beyond the special cases of H_2, high-J levels, and threshold spectra. These spectra reveal very nonatomiclike behavior and, surprisingly, the influence of multiple Cooper minima in the photoelectron matrix elements

    Distribution of genetic diversity in wild European populations of prickly lettuce (Lactuca serriola): implications for plant genetic resources management

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    Genetic variation in Lactuca serriola, the closest wild relative of cultivated lettuce, was studied across Europe from the Czech Republic to the United Kingdom, using three molecular marker systems, simple sequence repeat (SSR, microsatellites), AFLP and nucleotide-binding site (NBS) profiling. The ‘functional’ marker system NBS profiling, targeting disease resistance genes of the NBS/LRR family, did not show marked differences in genetic diversity parameters to the other systems. The autogamy of the species resulted in low observed heterozygosity and high population differentiation. Intra-population variation ranged from complete homogeneity to nearly complete heterogeneity. The highest genetic diversity was found in central Europe. The SSR results were compared to SSR variation screened earlier in the lettuce collection of the Centre for Genetic Resources, the Netherlands (CGN). In the UK, practically only a single SSR genotype was found. This genotype together with a few other common SSR genotypes comprised a large part of the plants sampled on the continent. Among the ten most frequent SSR genotypes observed, eight were already present in the CGN collection. Overall, the CGN collection appears to already have a fair representation of genetic variation from NW Europe. The results are discussed in relation to sampling strategies for improving genebank collections of crop wild relatives

    Connections between Classical and Parametric Network Entropies

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    This paper explores relationships between classical and parametric measures of graph (or network) complexity. Classical measures are based on vertex decompositions induced by equivalence relations. Parametric measures, on the other hand, are constructed by using information functions to assign probabilities to the vertices. The inequalities established in this paper relating classical and parametric measures lay a foundation for systematic classification of entropy-based measures of graph complexity

    An individual based computational model of intestinal crypt fission and its application to predicting unrestrictive growth of the intestinal epithelium.

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    Intestinal crypt fission is a homeostatic phenomenon, observable in healthy adult mucosa, but which also plays a pathological role as the main mode of growth of some intestinal polyps. Building on our previous individual based model for the small intestinal crypt and on in vitro cultured intestinal organoids, we here model crypt fission as a budding process based on fluid mechanics at the individual cell level and extrapolated predictions for growth of the intestinal epithelium. Budding was always observed in regions of organoids with abundant Paneth cells. Our data support a model in which buds are biomechanically initiated by single stem cells surrounded by Paneth cells which exhibit greater resistance to viscoelastic deformation, a hypothesis supported by atomic force measurements of single cells. Time intervals between consecutive budding events, as simulated by the model and observed in vitro, were 2.84 and 2.62 days, respectively. Predicted cell dynamics was unaffected within the original crypt which retained its full capability of providing cells to the epithelium throughout fission. Mitotic pressure in simulated primary crypts forced upward migration of buds, which simultaneously grew into new protruding crypts at a rate equal to 1.03 days-1 in simulations and 0.99 days-1 in cultured organoids. Simulated crypts reached their final size in 4.6 days, and required 40 6.2 days to migrate to the top of the primary crypt. The growth of the secondary crypt is independent of its migration along the original crypt. Assuming unrestricted crypt fission and multiple budding events, a maximal growth rate of the intestinal epithelium of 0.10 days-1 43 is predicted and thus approximately 22 days are required for a 10-fold increase of polyp size. These predictions are in agreement with the time reported to develop macroscopic adenomas in mice after loss of Apc in intestinal stem cells

    An Examination of Not-For-Profit Stakeholder Networks for Relationship Management: A Small-Scale Analysis on Social Media

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    Using a small-scale descriptive network analysis approach, this study highlights the importance of stakeholder networks for identifying valuable stakeholders and the management of existing stakeholders in the context of mental health not-for-profit services. We extract network data from the social media brand pages of three health service organizations from the U.S., U.K., and Australia, to visually map networks of 579 social media brand pages (represented by nodes), connected by 5,600 edges. This network data is analyzed using a collection of popular graph analysis techniques to assess the differences in the way each of the service organizations manage stakeholder networks. We also compare node meta-information against basic topology measures to emphasize the importance of effectively managing relationships with stakeholders who have large external audiences. Implications and future research directions are also discussed

    Integrative Network Biology: Graph Prototyping for Co-Expression Cancer Networks

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    Network-based analysis has been proven useful in biologically-oriented areas, e.g., to explore the dynamics and complexity of biological networks. Investigating a set of networks allows deriving general knowledge about the underlying topological and functional properties. The integrative analysis of networks typically combines networks from different studies that investigate the same or similar research questions. In order to perform an integrative analysis it is often necessary to compare the properties of matching edges across the data set. This identification of common edges is often burdensome and computational intensive. Here, we present an approach that is different from inferring a new network based on common features. Instead, we select one network as a graph prototype, which then represents a set of comparable network objects, as it has the least average distance to all other networks in the same set. We demonstrate the usefulness of the graph prototyping approach on a set of prostate cancer networks and a set of corresponding benign networks. We further show that the distances within the cancer group and the benign group are statistically different depending on the utilized distance measure

    An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

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    Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON
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