2,086 research outputs found

    Cats, comics and Knausgård : promoting student reading at a UK academic library with a leisure reading collection

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    This case study describes the creation of a leisure reading collection in the Clifford Whitworth library at the University of Salford. It briefly surveys existing literature on leisure reading collections and looks at the growing interest among UK academic libraries in recreational reading. It considers the reasons for promoting reading as a leisure activity to students and describes the processes of selecting, purchasing and marketing the collection at Salford. It also considers possible future developments for the collection and the evaluation of the library’s attempts to encourage a culture of reading amongst Salford students. The positive response to the collection suggests the development of leisure reading is a worthwhile activity for academic libraries to focus on and the study contains useful information for others who are interested in creating a similar collection

    Communicating product user reviews and ratings in interfaces for e-commerce: a multimodal approach

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    This paper describes a comparative empirical evaluation study that uses multimodal presentations to communicate review messages in an e-commerce platform. Previous studies demonstrate the effective use of multimodality in different problem domains (e.g. e-learning). In this paper, multimodality and expressive avatars are used to communicate information related to product reviews messages. The data of the reviews was opportunistically collected from Facebook and Twitter. Two independent groups of users were used to evaluate two different presentations of reviews and ratings using as a basis an experimental e- commerce platform. The control group used a text-based with emojis presentation and the experimental group used a multimodal approach based on expressive avatars. Three parameters of usability were measured. These were efficiency, effectiveness, user satisfaction, and user preference. The result showed that the two approaches performed similarly. These findings provide a basis for further experiments in which text, emojis and expressive avatars can be combine to communicate a larger volume of reviews and ratings

    Aptamer-based multiplexed proteomic technology for biomarker discovery

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    Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

    Cancer somatic mutations cluster in a subset of regulatory sites predicted from the ENCODE data

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    Background: Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. The ENCODE project has mapped potential regulatory sites across the complete genome in many cell types, and these regions have been shown to harbour many of the somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. The ENCODE data suggests a very large number of regulatory sites, and methods are needed to identify those that are most relevant and to connect them to the genes that they control. Methods: Predictive models of gene expression were developed by integrating the ENCODE data for regulation, including transcription factor binding and DNase1 hypersensitivity, with RNA-seq data for gene expression. A penalized regression method was used to identify the most predictive potential regulatory sites for each transcript. Known cancer somatic mutations from the COSMIC database were mapped to potential regulatory sites, and we examined differences in the mapping frequencies associated with sites chosen in regulatory models and other (rejected) sites. The effects of potential confounders, for example replication timing, were considered. Results: Cancer somatic mutations preferentially occupy those regulatory regions chosen in our models as most predictive of gene expression. Conclusion: Our methods have identified a significantly reduced set of regulatory sites that are enriched in cancer somatic mutations and are more predictive of gene expression. This has significance for the mechanistic interpretation of cancer mutations, and the understanding of genetic regulation

    Differences in genotype and virulence among four multidrug-resistant <i>Streptococcus pneumoniae</i> isolates belonging to the PMEN1 clone

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    We report on the comparative genomics and characterization of the virulence phenotypes of four &lt;i&gt;S. pneumoniae&lt;/i&gt; strains that belong to the multidrug resistant clone PMEN1 (Spain&lt;sup&gt;23F&lt;/sup&gt; ST81). Strains SV35-T23 and SV36-T3 were recovered in 1996 from the nasopharynx of patients at an AIDS hospice in New York. Strain SV36-T3 expressed capsule type 3 which is unusual for this clone and represents the product of an in vivo capsular switch event. A third PMEN1 isolate - PN4595-T23 - was recovered in 1996 from the nasopharynx of a child attending day care in Portugal, and a fourth strain - ATCC700669 - was originally isolated from a patient with pneumococcal disease in Spain in 1984. We compared the genomes among four PMEN1 strains and 47 previously sequenced pneumococcal isolates for gene possession differences and allelic variations within core genes. In contrast to the 47 strains - representing a variety of clonal types - the four PMEN1 strains grouped closely together, demonstrating high genomic conservation within this lineage relative to the rest of the species. In the four PMEN1 strains allelic and gene possession differences were clustered into 18 genomic regions including the capsule, the blp bacteriocins, erythromycin resistance, the MM1-2008 prophage and multiple cell wall anchored proteins. In spite of their genomic similarity, the high resolution chinchilla model was able to detect variations in virulence properties of the PMEN1 strains highlighting how small genic or allelic variation can lead to significant changes in pathogenicity and making this set of strains ideal for the identification of novel virulence determinant

    Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

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    With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

    Synchronized cycles of bacterial lysis for in vivo delivery

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    The pervasive view of bacteria as strictly pathogenic has given way to an ppreciation of the widespread prevalence of beneficial microbes within the human body. Given this milieu, it is perhaps inevitable that some bacteria would evolve to preferentially grow in environments that harbor disease and thus provide a natural platform for the development of engineered therapies. Such therapies could benefit from bacteria that are programmed to limit bacterial growth while continually producing and releasing cytotoxic agents in situ. Here, we engineer a clinically relevant bacterium to lyse synchronously at a threshold population density and to release genetically encoded cargo. Following quorum lysis, a small number of surviving bacteria reseed the growing population, thus leading to pulsatile delivery cycles. We use microfluidic devices to characterize the engineered lysis strain and we demonstrate its potential as a drug deliver platform via co-culture with human cancer cells in vitro. As a proof of principle, we track the bacterial population dynamics in ectopic syngeneic colorectal tumors in mice. The lysis strain exhibits pulsatile population dynamics in vivo, with mean bacterial luminescence that remained two orders of magnitude lower than an unmodified strain. Finally, guided by previous findings that certain bacteria can enhance the efficacy of standard therapies, we orally administer the lysis strain, alone or in combination with a clinical chemotherapeutic, to a syngeneic transplantation model of hepatic colorectal metastases. We find that the combination of both circuit-engineered bacteria and chemotherapy leads to a notable reduction of tumor activity along with a marked survival benefit over either therapy alone. Our approach establishes a methodology for leveraging the tools of synthetic biology to exploit the natural propensity for certain bacteria to colonize disease sites.National Institute of General Medical Sciences (U.S.) (GM069811)San Diego Center for Systems Biology (P50 GM085764)National Cancer Institute (U.S.). Swanson Biotechnology Center (Koch Institute Support Grant (P30-CA14051))National Institute of Environmental Health Sciences (Core Center Grant (P30- ES002109))National Institutes of Health (U.S.) (NIH Pathway to Independence Award NIH (K99 CA197649-01))Misrock Postdoctoral fellowshipNational Defense Science and Engineering Graduate (NDSEG) Fellowshi
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