Discovering conversational topics and emotions associated with Demonetization tweets in India

Social media platforms contain great wealth of information which provides us opportunities explore hidden patterns or unknown correlations, and understand people's satisfaction with what they are discussing. As one showcase, in this paper, we summarize the data set of Twitter messages related to recent demonetization of all Rs. 500 and Rs. 1000 notes in India and explore insights from Twitter's data. Our proposed system automatically extracts the popular latent topics in conversations regarding demonetization discussed in Twitter via the Latent Dirichlet Allocation (LDA) based topic model and also identifies the correlated topics across different categories. Additionally, it also discovers people's opinions expressed through their tweets related to the event under consideration via the emotion analyzer. The system also employs an intuitive and informative visualization to show the uncovered insight. Furthermore, we use an evaluation measure, Normalized Mutual Information (NMI), to select the best LDA models. The obtained LDA results show that the tool can be effectively used to extract discussion topics and summarize them for further manual analysis.Comment: 6 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:1608.02519 by other authors; text overlap with arXiv:1705.08094 by other author

A day that unites all nurses

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The Phyre2 web portal for protein modeling, prediction and analysis

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission

Identification and characterization of PhbF: A DNA binding protein with regulatory role in the PHB metabolism of Herbaspirillum seropedicae SmR1

<p>Abstract</p> <p>Background</p> <p><it>Herbaspirillum seropedicae </it>SmR1 is a nitrogen fixing endophyte associated with important agricultural crops. It produces polyhydroxybutyrate (PHB) which is stored intracellularly as granules. However, PHB metabolism and regulatory control is not yet well studied in this organism.</p> <p>Results</p> <p>In this work we describe the characterization of the PhbF protein from <it>H. seropedicae </it>SmR1 which was purified and characterized after expression in <it>E. coli</it>. The purified PhbF protein was able to bind to eleven putative promoters of genes involved in PHB metabolism in <it>H. seropedicae </it>SmR1. <it>In silico </it>analyses indicated a probable DNA-binding sequence which was shown to be protected in DNA footprinting assays using purified PhbF. Analyses using <it>lacZ </it>fusions showed that PhbF can act as a repressor protein controlling the expression of PHB metabolism-related genes.</p> <p>Conclusions</p> <p>Our results indicate that <it>H. seropedicae </it>SmR1 PhbF regulates expression of <it>phb</it>-related genes by acting as a transcriptional repressor. The knowledge of the PHB metabolism of this plant-associated bacterium may contribute to the understanding of the plant-colonizing process and the organism's resistance and survival <it>in planta</it>.</p

Patient and caregiver perspectives on managing pain in advanced cancer: A qualitative longitudinal study

Background: Despite advances in treatment of pain in advanced cancer, it remains a major source of suffering with adverse effects on patients’ life quality. There is increasing understanding of its multi-dimensional nature and the variable responsiveness of medication to complex pain. Less clear is how patients and their caregivers respond to and manage pain complexity. Aim: To explore patients’ and carers’ experiences of advanced cancer pain and the processes that they engage in to manage pain. Design: Qualitative study employing face-to-face interviews at two time points and audio diaries. Data were analysed using grounded theory strategies. Setting/participants: Purposive sample of 21 advanced cancer patients and 16 carers from oncology outpatients in a tertiary cancer centre and a hospice. Results: Three distinct patterns of pain were discerned in patients’ accounts, distinguishable in terms of complexity, severity, transiency and degree of perceived control over pain. Pain was dynamic reflecting changes in the disease process, access to and effectiveness of pain relief. For patients and carers, neither pain relief nor expertise in pain management is secured once and for all. The main drivers of help-seeking and action by patients to manage pain were the sensory experiences of pain and meaning attached to it, not beliefs about analgesia. Conclusion: The complex and dynamic nature of pain and how it was understood shaped help-seeking and pain management. Variable effectiveness of pain relief for different pain types were challenging for patients and professionals in achieving relief

Evolutionary Sequence Analysis and Visualization with Wasabi

Wasabi is an open-source, web-based graphical environment for evolutionary sequence analysis and visualization, designed to work with multiple sequence alignments within their phylogenetic context. Its interactive user interface provides convenient access to external data sources and computational tools and is easily extendable with custom tools and pipelines using a plugin system. Wasabi stores intermediate editing and analysis steps as workflow histories and provides direct-access web links to datasets, allowing for reproducible, collaborative research, and easy dissemination of the results. In addition to shared analyses and installation-free usage, the web-based design allows Wasabi to be run as a cross-platform, stand-alone application and makes its integration to other web services straightforward. This chapter gives a detailed description and guidelines for the use of Wasabi's analysis environment. Example use cases will give step-by-step instructions for practical application of the public Wasabi, from quick data visualization to branched analysis pipelines and publishing of results. We end with a brief discussion of advanced usage of Wasabi, including command-line communication, interface extension, offline usage, and integration to local and public web services.Peer reviewe

Any difference? Use of a CAM provider among cancer patients, coronary heart disease (CHD) patients and individuals with no cancer/CHD

<p>Abstract</p> <p>Background</p> <p>Although use of complementary and alternative medicine (CAM) among cancer patients has been described previously, prevalence of use has not commonly been compared to other disease groups in a true population sample where CAM use or cancer is not the main focus. The aims of the present study are to (1) examine how CAM use in cancer patients differs from people with a previous CHD diagnosis and people with no cancer or CHD diagnosis in an unselected general population and (2), investigate the use of a CAM provider among individuals with a previous cancer diagnosis.</p> <p>Methods</p> <p>A total of 8040 men and women aged 29 to 87 in the city of Tromsø, Norway filled in a questionnaire developed specifically for the Tromsø V study with questions on life style and health issues. Visits to a CAM provider within the last 12 months and information on cancer, heart attack and angina pectoris (heart cramp) were among the questions. 1449 respondents were excluded from the analyses.</p> <p>Results</p> <p>Among the 6591 analysed respondents 331 had a prior cancer diagnosis, of whom 7.9% reported to have seen a CAM provider within the last 12 months. This did not differ significantly from neither the CHD group (6.4%, p = 0.402) nor the no cancer/CHD group (9.5%, p = 0.325).</p> <p>Conclusion</p> <p>According to this study, the proportion of cancer patients seeing a CAM provider was not statistically significantly different from patients with CHD or individuals without cancer or CHD.</p

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge.</p> <p>Results</p> <p>Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few.</p> <p>Conclusion</p> <p>GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at <url>http://pcarvalho.com/patternlab</url>.</p

What traits are carried on mobile genetic elements, and why?

Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes