106 research outputs found

    The relationship between structural game characteristics and gambling behavior: a population-level study

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    The aim of this study was to examine the relationship between the structural characteristics and gambling behavior among video lottery terminal (VLT) gamblers. The study was ecological valid, because the data consisted of actual gambling behavior registered in the participants natural gambling environment without intrusion by researchers. Online behavioral tracking data from Multix, an eight game video lottery terminal, were supplied by Norsk-Tipping (the state owned gambling company in Norway). The sample comprised the entire population of Multix gamblers (N = 31,109) who had gambled in January 2010. The individual number of bets made across games was defined as the dependent variable, reward characteristics of a game (i.e., payback percentage, hit frequency, size of winnings and size of jackpot) and bet characteristics of a game (i.e., range of betting options and availability of advanced betting options) served as the independent variables. Control variables were age and gender. Two separate cross-classified multilevel random intercepts models were used to analyze the relationship between bets made, reward characteristics and bet characteristics, where the number of bets was nested within both individuals and within games. The results show that the number of bets is positively associated with payback percentage, hit frequency, being female and age, and negatively associated with size of wins and range of available betting options. In summary, the results show that the reward characteristics and betting options explained 27 % and 15 % of the variance in the number of bets made, respectively. It is concluded that structural game characteristics affect gambling behavior. Implications of responsible gambling are discussed

    Search for astronomical neutrinos from blazar TXS 0506+056 in super-kamiokande

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    We report a search for astronomical neutrinos in the energy region from several GeV to TeV in the direction of the blazar TXS 0506+056 using the Super-Kamiokande detector following the detection of a 100 TeV neutrinos from the same location by the IceCube collaboration. Using Super-Kamiokande neutrino data across several data samples observed from 1996 April to 2018 February we have searched for both a total excess above known backgrounds across the entire period as well as localized excesses on smaller timescales in that interval. No significant excess nor significant variation in the observed event rate are found in the blazar direction. Upper limits are placed on the electron- and muon-neutrino fluxes at the 90% confidence level as 6.0 × 10−7 and 4.5 × 10−7–9.3 × 10−10 [erg cm−2 s−1], respectively

    A functional peptidyl-tRNA hydrolase, ICT1, has been recruited into the human mitochondrial ribosome

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    Bioinformatic analysis classifies the human protein encoded by immature colon carcinoma transcript-1 (ICT1) as one of a family of four putative mitochondrial translation release factors. However, this has not been supported by any experimental evidence. As only a single member of this family, mtRF1a, is required to terminate the synthesis of all 13 mitochondrially encoded polypeptides, the true physiological function of ICT1 was unclear. Here, we report that ICT1 is an essential mitochondrial protein, but unlike the other family members that are matrix-soluble, ICT1 has become an integral component of the human mitoribosome. Release-factor assays show that although ICT1 has retained its ribosome-dependent PTH activity, this is codon-independent; consistent with its loss of both domains that promote codon recognition in class-I release factors. Mutation of the GGQ domain common to ribosome-dependent PTHs causes a loss of activity in vitro and, crucially, a loss of cell viability, in vivo. We suggest that ICT1 may be essential for hydrolysis of prematurely terminated peptidyl-tRNA moieties in stalled mitoribosomes

    Modified Chrispin-Norman chest radiography score for cystic fibrosis: observer agreement and correlation with lung function

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    Contains fulltext : 96114.pdf ( ) (Closed access)OBJECTIVE: To test observer agreement and two strategies for possible improvement (consensus meeting and reference images) for the modified Chrispin-Norman score for children with cystic fibrosis (CF). METHODS: Before and after a consensus meeting and after developing reference images three observers scored sets of 25 chest radiographs from children with CF. Observer agreement was tested for line, ring, mottled and large soft shadows, for overinflation and for the composite modified Chrispin-Norman score. Correlation with lung function was assessed. RESULTS: Before the consensus meeting agreement between observers 1 and 2 was moderate-good, but with observer 3 agreement was poor-fair. Scores correlated significantly with spirometry for observers 1 and 2 (-0.72<R<-0.42, P < 0.05), but not for observer 3. Agreement with observer 3 improved after the consensus meeting. Reference images improved agreement for overinflation and mottled and large shadows and correlation with lung function, but agreement for the modified Chrispin-Norman score did not improve further. CONCLUSION: Consensus meetings and reference images improve among-observer agreement for the modified Chrispin-Norman score, but good agreement was not achieved among all observers for the modified Chrispin-Norman score and for bronchial line and ring shadows

    Identification of Ligand Binding Sites of Proteins Using the Gaussian Network Model

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    The nonlocal nature of the protein-ligand binding problem is investigated via the Gaussian Network Model with which the residues lying along interaction pathways in a protein and the residues at the binding site are predicted. The predictions of the binding site residues are verified by using several benchmark systems where the topology of the unbound protein and the bound protein-ligand complex are known. Predictions are made on the unbound protein. Agreement of results with the bound complexes indicates that the information for binding resides in the unbound protein. Cliques that consist of three or more residues that are far apart along the primary structure but are in contact in the folded structure are shown to be important determinants of the binding problem. Comparison with known structures shows that the predictive capability of the method is significant

    The Short Non-Coding Transcriptome of the Protozoan Parasite Trypanosoma cruzi

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    The pathway for RNA interference is widespread in metazoans and participates in numerous cellular tasks, from gene silencing to chromatin remodeling and protection against retrotransposition. The unicellular eukaryote Trypanosoma cruzi is missing the canonical RNAi pathway and is unable to induce RNAi-related processes. To further understand alternative RNA pathways operating in this organism, we have performed deep sequencing and genome-wide analyses of a size-fractioned cDNA library (16–61 nt) from the epimastigote life stage. Deep sequencing generated 582,243 short sequences of which 91% could be aligned with the genome sequence. About 95–98% of the aligned data (depending on the haplotype) corresponded to small RNAs derived from tRNAs, rRNAs, snRNAs and snoRNAs. The largest class consisted of tRNA-derived small RNAs which primarily originated from the 3′ end of tRNAs, followed by small RNAs derived from rRNA. The remaining sequences revealed the presence of 92 novel transcribed loci, of which 79 did not show homology to known RNA classes

    Evaluation of gadolinium's action on water Cherenkov detector systems with EGADS

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    Used for both proton decay searches and neutrino physics, large water Cherenkov (WC) detectors have been very successful tools in particle physics. They are notable for their large masses and charged particle detection capabilities. While current WC detectors reconstruct charged particle tracks over a wide energy range, they cannot efficiently detect neutrons. Gadolinium (Gd) has the largest thermal neutron capture cross section of all stable nuclei and produces an 8 MeV gamma cascade that can be detected with high efficiency. Because of the many new physics opportunities that neutron tagging with a Gd salt dissolved in water would open up, a large-scale R&D program called EGADS was established to demonstrate this technique's feasibility. EGADS features all the components of a WC detector, chiefly a 200-ton stainless steel water tank furnished with 240 photo-detectors, DAQ, and a water system that removes all impurities in water while keeping Gd in solution. In this paper we discuss the milestones towards demonstrating the feasibility of this novel technique, and the features of EGADS in detail

    Computational Methods for Protein Identification from Mass Spectrometry Data

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    Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology

    The self-organizing fractal theory as a universal discovery method: the phenomenon of life

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    A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy
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