instruction:
In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
question:
Motivation: Deep sequencing of clinical samples is now an established tool for the detection of infectious pathogens, with direct medical applications. The large amount of data generated produces an opportunity to detect species even at very low levels, provided that computational tools can effectively profile the relevant metagenomic communities. Data interpretation is complicated by the fact that short sequencing reads can match multiple organisms and by the lack of completeness of existing databases, in particular for viral pathogens. Here we present metaMix, a Bayesian mixture model framework for resolving complex metagenomic mixtures. We show that the use of parallel Monte Carlo Markov chains for the exploration of the species space enables the identification of the set of species most likely to contribute to the mixture. Results: We demonstrate the greater accuracy of metaMix compared with relevant methods, particularly for profiling complex communities consisting of several related species. We designed metaMix specifically for the analysis of deep transcriptome sequencing datasets, with a focus on viral pathogen detection; however, the principles are generally applicable to all types of metagenomic mixtures. Availability and implementation: metaMix is implemented as a user friendly R package, freely available on CRAN: http://cran.r-project.org/web/packages/metaMix Contact: sofia.morfopoulou.10@ucl.ac.uk Supplementary information: Supplementary data are available at Bionformatics online.
answer:
Bayesian mixture analysis for metagenomic community profiling


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The worldwide prevalence of herpes simplex virus (HSV) and the shortage of efficient vaccines and novel therapeutic strategies against HSV are widely global concerns. The abundance on the virion and the major stimulus for the virus-neutralizing antibodies makes gD a predominant candidate for cure of HSV infection. In this study, we generated a monoclonal antibody (mAb), termed m27f, targeting to glycoprotein D (gD) of HSV-2, which also has cross-reactivity against HSV-1 gD. It has a high level of neutralizing activity against both HSV-1 and HSV-2, and binds to a highly conserved region (residues 292-297) within the pro-fusion domain of gD. It can effectively block HSV cell-to-cell spread in vitro. The pre-or post-attachment neutralization assay and syncytium formation inhibition assay revealed that m27f neutralizes HSV at the post-binding stage. Moreover, therapeutic administration of m27f completely prevented infection-related mortality of mice challenged with a lethal dose of HSV-2. Our newly identified epitope for the neutralizing antibody would facilitate studies of gD-based HSV entry or vaccine design, and m27f itself demonstrated a high potential for adaptation as a protective or therapeutic drug against HSV.
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A novel glycoprotein D-specific monoclonal antibody neutralizes herpes simplex virus


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Little is known about how optimism/pessimism and health-related quality of life compare across cultures. Methods: Three samples of pregnant women in their final trimester were recruited from China, Ghana, and the United States (U.S.). Participants completed a survey that included the Life Orientation Test -Revised (LOT-R, an optimism/pessimism measure), the Short Form 12 (SF-12, a quality of life measure), and questions addressing health and demographic factors. A three-country set was created for analysis by matching women on age, gestational age at enrollment, and number of previous pregnancies. Anovas with post-hoc pairwise comparisons were used to compare results across the cohorts. Multivariate regression analysis was used to create a model to identify those variables most strongly associated with optimism/pessimism. LOT-R scores varied significantly across cultures in these samples, with Ghanaian pregnant women being the most optimistic and least pessimistic and Chinese pregnant women being the least optimistic overall and the least pessimistic in subscale analysis. Four key variables predicted approximately 20% of the variance in overall optimism scores: country of origin (p = .006), working for money (p = .05); level of education (p = .002), and ever being treated for emotional issues with medication (p < .001). Quality of life scores also varied by country in these samples, with the most pronounced difference occurring in the vitality measure. U.S. pregnant women reported far lower vitality scores than both Chinese and Ghanaian pregnant women in our sample. This research raises important questions regarding what it is about country of origin that so strongly influences optimism/pessimism among pregnant women. Further research is warranted exploring underlying conceptualization of optimism/pessimism and health related quality of life across countries.
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BMC Pregnancy and Childbirth Optimism/pessimism and health-related quality of life during pregnancy across three continents: a matched cohort study in China, Ghana, and the United States