Pickoff and spin-conversion quenchings of ortho-positronium in oxygen

The quenching processes of the thermalized ortho-positronium(o-Ps) on an oxygen molecule have been studied by the positron annihilation age-momentum correlation techinique(AMOC). The Doppler broadening spectrum of the 511 keV gamma-rays from the 2gamma annihilation of o-Ps in O_2 has been measured as a function of the o-Ps age. The rate of the quenching, consisting of the pickoff and the spin-conversion, is estimated from the positron lifetime spectrum. The ratio of the pickoff quenching rate to the spin-conversion rate is deduced from the Doppler broadening of the 511 keV gamma-rays from the annihilation of the o-Ps. The pickoff parameter ^1Z_eff, the effective number of the electrons per molecule which contribute to the pickoff quenching, for O_2 is determined to be 0.6 +- 0.4. The cross-section for the elastic spin-conversion quenching is determined to be (1.16 +- 0.01) * 10^{-19} cm^2.Comment: 4 pages with 5 eps figures, LaTeX2e(revtex4

High serum immunoglobulin g and m levels predict freedom from adverse cardiovascular events in hypertension: a nested case-control substudy of the Anglo-Scandinavian cardiac outcomes trial

Aims: We aimed to determine whether the levels of total serum IgM and IgG, together with specific antibodies against malondialdehyde-conjugated low-density lipoprotein (MDA-LDL), can improve cardiovascular risk discrimination. Methods and Results: The Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT) randomized 9098 patients in the UK and Ireland into the Blood Pressure-Lowering Arm. 485 patients that had cardiovascular (CV) events over 5.5 years were age and sex matched with 1367 controls. Higher baseline total serum IgG, and to a lesser extent IgM, were associated with decreased risk of CV events (IgG odds ratio (OR) per one standard deviation (SD) 0.80 [95% confidence interval, CI 0.72,0.89], p < 0.0001; IgM 0.83[0.75,0.93], p = 0.001), and particularly events due to coronary heart disease (CHD) (IgG OR 0.66 (0.57,0.76); p < 0.0001, IgM OR 0.81 (0.71,0.93); p = 0.002). The association persisted after adjustment for a basic model with variables in the Framingham Risk Score (FRS) as well as following inclusion of C-reactive protein (CRP) and N-terminal pro-B-type natriuretic peptide (NtProBNP). IgG and IgM antibodies against MDA-LDL were also associated with CV events but their significance was lost following adjustment for total serum IgG and IgM respectively. The area under the receiver operator curve for CV events was improved from the basic risk model when adding in total serum IgG, and there was improvement in continuous and categorical net reclassification (17.6% and 7.5% respectively) as well as in the integrated discrimination index. Conclusion: High total serum IgG levels are an independent predictor of freedom from adverse cardiovascular events, particularly those attributed to CHD, in patients with hypertension

ROMA (Rank-Ordered Multifractal Analysis) for intermittent fluctuations with global crossover behavior

Rank-Ordered Multifractal Analysis (ROMA), a recently developed technique that combines the ideas of parametric rank ordering and one parameter scaling of monofractals, has the capabilities of deciphering the multifractal characteristics of intermittent fluctuations. The method allows one to understand the multifractal properties through rank-ordered scaling or non-scaling parametric variables. The idea of the ROMA technique is applied to analyze the multifractal characteristics of the auroral zone electric field fluctuations observed by SIERRA. The observed fluctuations span across contiguous multiple regimes of scales with different multifractal characteristics. We extend the ROMA technique such that it can take into account the crossover behavior -- with the possibility of collapsing probability distributions functions (PDFs) -- over these contiguous regimes.Comment: 24 pages, 18 figure

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

Identification of proteins binding coding and non-coding human RNAs using protein microarrays

Background: The regulation and function of mammalian RNAs has been increasingly appreciated to operate via RNA-protein interactions. With the recent discovery of thousands of novel human RNA molecules by high-throughput RNA sequencing, efficient methods to uncover RNA-protein interactions are urgently required. Existing methods to study proteins associated with a given RNA are laborious and require substantial amounts of cell-derived starting material. To overcome these limitations, we have developed a rapid and large-scale approach to characterize binding of in vitro transcribed labeled RNA to ~9,400 human recombinant proteins spotted on protein microarrays. Results: We have optimized methodology to probe human protein microarrays with full-length RNA molecules and have identified 137 RNA-protein interactions specific for 10 coding and non-coding RNAs. Those proteins showed strong enrichment for common human RNA binding domains such as RRM, RBD, as well as K homology and CCCH type zinc finger motifs. Previously unknown RNA-protein interactions were discovered using this technique, and these interactions were biochemically verified between TP53 mRNA and Staufen1 protein as well as between HRAS mRNA and CNBP protein. Functional characterization of the interaction between Staufen 1 protein and TP53 mRNA revealed a novel role for Staufen 1 in preserving TP53 RNA stability. Conclusions: Our approach demonstrates a scalable methodology, allowing rapid and efficient identification of novel human RNA-protein interactions using RNA hybridization to human protein microarrays. Biochemical validation of newly identified interactions between TP53-Stau1 and HRAS-CNBP using reciprocal pull-down experiments, both in vitro and in vivo, demonstrates the utility of this approach to study uncharacterized RNA-protein interactions.Stem Cell and Regenerative Biolog