344 research outputs found

    Muon spin rotation measurements of the superfluid density in fresh and aged superconducting PuCoGa5_5

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    We have measured the temperature dependence and magnitude of the superfluid density ρs(T)\rho_{\rm s}(T) via the magnetic field penetration depth λ(T)\lambda(T) in PuCoGa5_5 (nominal critical temperature Tc0=18.5T_{c0} = 18.5 K) using the muon spin rotation technique in order to investigate the symmetry of the order parameter, and to study the effects of aging on the superconducting properties of a radioactive material. The same single crystals were measured after 25 days (Tc=18.25T_c = 18.25 K) and 400 days (Tc=15.0T_c = 15.0 K) of aging at room temperature. The temperature dependence of the superfluid density is well described in both materials by a model using d-wave gap symmetry. The magnitude of the muon spin relaxation rate σ\sigma in the aged sample, σ1/λ2ρs/m\sigma\propto 1/\lambda^2\propto\rho_s/m^*, where mm^* is the effective mass, is reduced by about 70% compared to fresh sample. This indicates that the scattering from self-irradiation induced defects is not in the limit of the conventional Abrikosov-Gor'kov pair-breaking theory, but rather in the limit of short coherence length (about 2 nm in PuCoGa5_5) superconductivity.Comment: 11 page

    An in vivo strategy for knockdown of circular RNAs

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    Exonic circular RNAs (circRNAs) are highly abundant RNAs generated mostly from exons of protein-coding genes. Assaying the functions of circRNAs is not straightforward as common approaches for circRNA depletion tend to also alter the levels of mRNAs generated from the hosting gene. Here we describe a methodology for specific knockdown of circRNAs in vivo with tissue and cell resolution. We also describe an experimental and computational platform for determining the potential off-target effects as well as for verifying the obtained phenotypes. Briefly, we utilize shRNAs targeted to the circRNA-specific back-splice junction to specifically downregulate the circRNA. We utilized this methodology to downregulate five circRNAs that are highly expressed in Drosophila. There were no effects on the levels of their linear counterparts or any RNA with complementarity to the expressed shRNA. Interestingly, downregulation of circCtrip resulted in developmental lethality that was recapitulated with a second shRNA. Moreover, downregulation of individual circRNAs caused specific changes in the fly head transcriptome, suggesting roles for these circRNAs in the fly nervous system. Together, our results provide a methodological approach that enables the comprehensive study of circRNAs at the organismal and cellular levels and generated for the first time flies in which specific circRNAs are downregulated

    Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

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    Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

    A note on Youden's J and its cost ratio

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    <p>Abstract</p> <p>Background</p> <p>The Youden index, the sum of sensitivity and specificity minus one, is an index used for setting optimal thresholds on medical tests.</p> <p>Discussion</p> <p>When using this index, one implicitly uses decision theory with a ratio of misclassification costs which is equal to one minus the prevalence proportion of the disease. It is doubtful whether this cost ratio truly represents the decision maker's preferences. Moreover, in populations with a different prevalence, a selected threshold is optimal with reference to a different cost ratio.</p> <p>Summary</p> <p>The Youden index is not a truly optimal decision rule for setting thresholds because its cost ratio varies with prevalence. Researchers should look into their cost ratio and employ it in a decision theoretic framework to obtain genuinely optimal thresholds.</p
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