Mapping Monte Carlo to Langevin dynamics: A Fokker-Planck approach

We propose a general method of using the Fokker-Planck equation (FPE) to link the Monte-Carlo (MC) and the Langevin micromagnetic schemes. We derive the drift and disusion FPE terms corresponding to the MC method and show that it is analytically equivalent to the stochastic Landau-Lifshitz-Gilbert (LLG) equation of Langevin-based micromagnetics. Subsequent results such as the time quantification factor for the Metropolis MC method can be rigorously derived from this mapping equivalence. The validity of the mapping is shown by the close numerical convergence between the MC method and the LLG equation for the case of a single magnetic particle as well as interacting arrays of particles. We also found that our Metropolis MC is accurate for a large range of damping factors $\alpha$, unlike previous time-quantified MC methods which break down at low $\alpha$, where precessional motion dominates.Comment: 4 pages, 4 figures. Accepted for publication in Phys. Rev. Let

Angular position of nodes in the superconducting gap of YBCO

The thermal conductivity of a YBCO single crystal has been studied as a function of the relative orientation of the crystal axes and a magnetic field rotating in the Cu-O planes. Measurements were carried out at several temperatures below T_c and at a fixed field of 30 kOe. A four-fold symmetry characteristic of a superconducting gap with nodes at odd multiples of 45 degrees in k-space was resolved. Experiments were performed to exclude a possible macroscopic origin for such a four-fold symmetry such as sample shape or anisotropic pinning. Our results impose an upper limit of 10% on the weight of the s-wave component of the essentially d-wave superconducting order parameter of YBCO.Comment: 10 pages, 4 figure

Risk factors for 3-year-mortality and a tool to screen patient in dialysis population

Introduction: Clinical parameters especially co‑morbidities among end stage renal disease (ESRD) patients are associated with mortality. This study aims to determine the risk factors that are associated with mortality within three years among prevalent patients with ESRD. Methods: This is a cohort study where prevalent ESRD patients’ details were recorded between May 2012 and October 2012. Their records were matched with national death record at the end of year 2015 to identify the deceased patients within three years. Four models were formulated with two models were based on logistic regression models but with different number of predictors and two models were developed based on risk scoring technique. The preferred models were validated by using sensitivity and specificity analysis. Results: A total of 1332 patients were included in the study. Majority succumbed due to cardiovascular disease (48.3%) and sepsis (41.3%). The identified risk factors were mode of dialysis (P < 0.001), diabetes mellitus (P < 0.001), chronic heart disease (P < 0.001) and leg amputation (P = 0.016). The accuracy of four models was almost similar with AUC between 0.680 and 0.711. The predictive models from logistic regression model and risk scoring model were selected as the preferred models based on both accuracy and simplicity. Besides the mode of dialysis, diabetes mellitus and its complications are the important predictors for early mortality among prevalent ESRD patients. Conclusions: The models either based on logistic regression or risk scoring model can be used to screen high risk prevalent ESRD patients

Low-Energy Quasiparticles in Cuprate Superconductors: A Quantitative Analysis

A residual linear term is observed in the thermal conductivity of optimally-doped Bi-2212 at very low temperatures whose magnitude is in excellent agreement with the value expected from Fermi-liquid theory and the d-wave energy spectrum measured by photoemission spectroscopy, with no adjustable parameters. This solid basis allows us to make a quantitative analysis of thermodynamic properties at low temperature and establish that thermally-excited quasiparticles are a significant, perhaps even the dominant mechanism in suppressing the superfluid density in cuprate superconductors Bi-2212 and YBCO.Comment: Revised version with additional page, figure, table and reference; to appear in Physical Review B (1 August 2000

Hit selection with false discovery rate control in genome-scale RNAi screens

RNA interference (RNAi) is a modality in which small double-stranded RNA molecules (siRNAs) designed to lead to the degradation of specific mRNAs are introduced into cells or organisms. siRNA libraries have been developed in which siRNAs targeting virtually every gene in the human genome are designed, synthesized and are presented for introduction into cells by transfection in a microtiter plate array. These siRNAs can then be transfected into cells using high-throughput screening (HTS) methodologies. The goal of RNAi HTS is to identify a set of siRNAs that inhibit or activate defined cellular phenotypes. The commonly used analysis methods including median ± kMAD have issues about error rates in multiple hypothesis testing and plate-wise versus experiment-wise analysis. We propose a methodology based on a Bayesian framework to address these issues. Our approach allows for sharing of information across plates in a plate-wise analysis, which obviates the need for choosing either a plate-wise or experimental-wise analysis. The proposed approach incorporates information from reliable controls to achieve a higher power and a balance between the contribution from the samples and control wells. Our approach provides false discovery rate (FDR) control to address multiple testing issues and it is robust to outliers

Cosmological Evolution of Dirac-Born-Infeld Field

We investigate the cosmological evolution of the system of a Dirac-Born-Infeld field plus a perfect fluid. We analyze the existence and stability of scaling solutions for the AdS throat and the quadratic potential. We find that the scaling solutions exist when the equation of state of the perfect fluid is negative and in the ultra-relativistic limit.Comment: 9 pages, 1 figure, LaTeX2e, references added, accepted for publication in JCA

Differential co-expression framework to quantify goodness of biclusters and compare biclustering algorithms

<p>Abstract</p> <p>Background</p> <p>Biclustering is an important analysis procedure to understand the biological mechanisms from microarray gene expression data. Several algorithms have been proposed to identify biclusters, but very little effort was made to compare the performance of different algorithms on real datasets and combine the resultant biclusters into one unified ranking.</p> <p>Results</p> <p>In this paper we propose differential co-expression framework and a differential co-expression scoring function to objectively quantify quality or goodness of a bicluster of genes based on the observation that genes in a bicluster are co-expressed in the conditions belonged to the bicluster and not co-expressed in the other conditions. Furthermore, we propose a scoring function to stratify biclusters into three types of co-expression. We used the proposed scoring functions to understand the performance and behavior of the four well established biclustering algorithms on six real datasets from different domains by combining their output into one unified ranking.</p> <p>Conclusions</p> <p>Differential co-expression framework is useful to provide quantitative and objective assessment of the goodness of biclusters of co-expressed genes and performance of biclustering algorithms in identifying co-expression biclusters. It also helps to combine the biclusters output by different algorithms into one unified ranking i.e. meta-biclustering.</p

MRP3: a molecular target for human glioblastoma multiforme immunotherapy.

<p>Abstract</p> <p>Background</p> <p>Glioblastoma multiforme (GBM) is refractory to conventional therapies. To overcome the problem of heterogeneity, more brain tumor markers are required for prognosis and targeted therapy. We have identified and validated a promising molecular therapeutic target that is expressed by GBM: human multidrug-resistance protein 3 (MRP3).</p> <p>Methods</p> <p>We investigated MRP3 by genetic and immunohistochemical (IHC) analysis of human gliomas to determine the incidence, distribution, and localization of MRP3 antigens in GBM and their potential correlation with survival. To determine MRP3 mRNA transcript and protein expression levels, we performed quantitative RT-PCR, raising MRP3-specific antibodies, and IHC analysis with biopsies of newly diagnosed GBM patients. We used univariate and multivariate analyses to assess the correlation of RNA expression and IHC of MRP3 with patient survival, with and without adjustment for age, extent of resection, and KPS.</p> <p>Results</p> <p>Real-time PCR results from 67 GBM biopsies indicated that 59/67 (88%) samples highly expressed <it>MRP3 </it>mRNA transcripts, in contrast with minimal expression in normal brain samples. Rabbit polyvalent and murine monoclonal antibodies generated against an extracellular span of MRP3 protein demonstrated reactivity with defined <it>MRP3</it>-expressing cell lines and GBM patient biopsies by Western blotting and FACS analyses, the latter establishing cell surface MRP3 protein expression. IHC evaluation of 46 GBM biopsy samples with anti-MRP3 IgG revealed MRP3 in a primarily membranous and cytoplasmic pattern in 42 (91%) of the 46 samples. Relative RNA expression was a strong predictor of survival for newly diagnosed GBM patients. Hazard of death for GBM patients with high levels of <it>MRP3 </it>RNA expression was 2.71 (95% CI: 1.54-4.80) times that of patients with low/moderate levels (p = 0.002).</p> <p>Conclusions</p> <p>Human GBMs overexpress MRP3 at both mRNA and protein levels, and elevated MRP3 mRNA levels in GBM biopsy samples correlated with a higher risk of death. These data suggest that the tumor-associated antigen MRP3 has potential use for prognosis and as a target for malignant glioma immunotherapy.</p