44 research outputs found

    Low literacy and written drug information: information-seeking, leaflet evaluation and preferences, and roles for images

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    Background Low-literate patients are at risk to misinterpret written drug information. For the (co-) design of targeted patient information, it is key to involve this group in determining their communication barriers and information needs. Objective To gain insight into how people with low literacy use and evaluate written drug information, and to identify ways in which they feel the patient leaflet can be improved, and in particular how images could be used. Setting Food banks and an education institution for Dutch language training in the Netherlands. Method Semi-structured focus groups and individual interviews were held with low-literate participants (n = 45). The thematic framework approach was used for analysis to identify themes in the data. Main outcome measure Low-literate people’s experience with patient information leaflets, ideas for improvements, and perceptions on possible uses for visuals. Results Patient information leaflets were considered discouraging to use, and information difficult to find and understand. Many rely on alternative information sources. The leaflet should be shorter, and improved in terms of organisation, legibility and readability. Participants thought images could increase the leaflet’s appeal, help ask questions, provide an overview, help understand textual information, aid recall, reassure, and even lead to increased confidence, empowerment and feeling of safety. Conclusion Already at the stages of paying attention to the leaflet and maintaining interest in the message, low-literate patients experience barriers in the communication process through written drug information. Short, structured, visual/textual explanations can lower the motivational threshold to use the leaflet, improve understanding, and empower the low-literate target group

    Efficient initial pool generation for weighted graph problems using parallel overlap assembly

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    Abstract. Most DNA computing algorithms for mathematical problems start with combinatorial generation of an initial pool. Several methods for initialpool generation have been proposed, including hybridization/ligation and mix/split methods. Here, we implement and compare parallel overlap assembly with the hybridization/ligation method. We applied these methods to the molecular algorithm to solve an instance of the graph problem with weighted edges. Our experimental results show that parallel overlap assembly is a better choice in terms of generation speed and material consumption than the hybridization/ligation method. Simulation of parallel overlap assembly was performed to investigate the potential and the limitation of the method.

    A viral microRNA functions as an orthologue of cellular miR-155

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    All metazoan eukaryotes express microRNAs (miRNAs), roughly 22-nucleotide regulatory RNAs that can repress the expression of messenger RNAs bearing complementary sequences. Several DNA viruses also express miRNAs in infected cells, suggesting a role in viral replication and pathogenesis. Although specific viral miRNAs have been shown to autoregulate viral mRNAs or downregulate cellular mRNAs, the function of most viral miRNAs remains unknown. Here we report that the miR-K12-11 miRNA encoded by Kaposi's-sarcoma-associated herpes virus (KSHV) shows significant homology to cellular miR-155, including the entire miRNA 'seed' region. Using a range of assays, we show that expression of physiological levels of miR-K12-11 or miR-155 results in the downregulation of an extensive set of common mRNA targets, including genes with known roles in cell growth regulation. Our findings indicate that viral miR-K12-11 functions as an orthologue of cellular miR-155 and probably evolved to exploit a pre-existing gene regulatory pathway in B cells. Moreover, the known aetiological role of miR-155 in B-cell transformation suggests that miR-K12-11 may contribute to the induction of KSHV-positive B-cell tumours in infected patients

    Deterministic Polynomial-Time Algorithms for Designing Short DNA Words

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    LNCS v. 6108 is Proceedings of the 7th Annual Conference, TAMC 2010Designing short DNA words is a problem of constructing n DNA strings (words) with the minimum length such that the Hamming distance between each pair is at least k and the words satisfy a set of extra constraints. This problem has applications in DNA computing, DNA self-assembly, and DNA arrays. Previous works include those that extended results from coding theory to obtain bounds on code size for biologically motivated constraints and those that applied heuristic local searches, genetic algorithms, and randomized algorithms. In particular, Kao, Sanghi and Schweller developed polynomial-time randomized algorithms to construct n DNA words of length 9· max {logn,k} satisfying a sets of constraints with high probability. In this paper, we give deterministic polynomial-time algorithms to construct DNA words based on expander codes, Ramanujan graphs, and derandomization techniques. Our algorithms can construct n DNA words of length max {3logn, 4k} or 2.1 logn + 6.28 k satisfying the same sets of constraints as the words constructed by the algorithms of Kao et al. We have also extended these algorithms to construct words that satisfy a larger set of constraints for which the algorithms of Kao et al. do not work. © 2010 Springer-Verlag.link_to_subscribed_fulltextThe 7th Annual Conference on Theory and Applications of Models of Computation (TAMC 2010), Prague, Czech Republic, 7-11 June 2010. In Lecture Notes in Computer Science, 2010, v. 6108, p. 308-31
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