Critical current of a superconductor measured via injection of spin polarized carriers

In this paper we report a direct evidence of the suppression of critical current due to pair-breaking in a superconducting micro-bridge when the measurement is carried out by injecting spin polarised carriers instead of normal electrons. A thin layer of La0.7Ca0.3MnO3 was used as the source of spin polarised carriers. The micro-bridge was formed on the DyBa2Cu3O7-d thin film by photo-lithographic techniques. The design of our spin-injection device allowed us to inject spin-polarised carriers from the La0.7Ca0.3MnO3 layer directly to the DyBa2Cu3O7- d micro-bridge (without any insulating buffer layer) making it possible to measure the critical current when polarised electrons alone are injected into the superconductor. Our results confirm the role of polarised carriers in breaking the Cooper pairs in the superconductor.Comment: 8 pages, 4 figure

Peak effect and its evolution with defect structure in YBa2Cu3O7-d thin films at microwave frequencies

The vortex dynamics in YBa2Cu3O7-d thin films have been studied at microwave frequencies. A pronounced peak in the surface resistance, Rs, is observed in these films at frequencies of 4.88 and 9.55 GHz for magnetic fields varying from 0.2 to 0.8 T. The peak is associated with an order-disorder transformation of the flux line lattice as the temperature or field is increased. The occurrence of the peak in Rs is crucially dependent on the depinning frequency, wp and on the nature and concentration of growth defects present in these films. Introduction of artificial defects by swift heavy ion irradiation with 200 MeV Ag ion at a fluence of 4x1010 ions/cm2 enhances wp and suppresses the peak at 4.88 GHz but the peak at 9.55 GHz remains unaffected. A second peak at lower temperature has also been observed at 9.55 GHz. This is related to twin boundaries from angular dependence studies of Rs. Based on the temperature variation of Rs, vortex phase diagrams have been constructed at 9.55 GHz.Comment: 8 pages, 4 figures Submitted to Physical Review

Decoding of Superimposed Traces Produced by Direct Sequencing of Heterozygous Indels

Direct Sanger sequencing of a diploid template containing a heterozygous insertion or deletion results in a difficult-to-interpret mixed trace formed by two allelic traces superimposed onto each other. Existing computational methods for deconvolution of such traces require knowledge of a reference sequence or the availability of both direct and reverse mixed sequences of the same template. We describe a simple yet accurate method, which uses dynamic programming optimization to predict superimposed allelic sequences solely from a string of letters representing peaks within an individual mixed trace. We used the method to decode 104 human traces (mean length 294 bp) containing heterozygous indels 5 to 30 bp with a mean of 99.1% bases per allelic sequence reconstructed correctly and unambiguously. Simulations with artificial sequences have demonstrated that the method yields accurate reconstructions when (1) the allelic sequences forming the mixed trace are sufficiently similar, (2) the analyzed fragment is significantly longer than the indel, and (3) multiple indels, if present, are well-spaced. Because these conditions occur in most encountered DNA sequences, the method is widely applicable. It is available as a free Web application Indelligent at http://ctap.inhs.uiuc.edu/dmitriev/indel.asp

Peak effect in a superconducting DyBa2Cu3O7-y film at microwave frequencies

We report the observation of a peak in the microwave (9.55 GHz) surface resistance in an epitaxial DyBa2Cu3O7-y superconducting film in magnetic fields (parallel to the c axis) ranging between 0.2 to 0.9 Tesla. Such a peak is absent in the measurements done in zero-field. The temperature and field dependence of the peak suggests that this peak could be associated with the peak effect phenomenon reflecting the order-disorder transformation in the flux-line lattice. A strong dependence of this peak effect at frequencies close to the depinning frequency of the flux line lattice is observed.Comment: 1 text, 4 figures (all postscript) to be published in Phys. Rev.

Host resistance stability to downy mildew in pearl millet and pathogenic variability in Sclerospora graminicola

Downy mildew, caused by Sclerospora graminicola, is a major pathogen of pearl millet (Pennisetum glaucum) in Asia and Africa. So development of resistant cultivars has been a major goal of national and international breeding programs. Stability of resistance in pearl millet lines developed at ICRISAT was studied through a collaborative International Pearl Millet Downy Mildew Virulence Nursery (IPMDMVN). The reactions to downy mildew of 11 pearl millet lines at 17 locations in India, Burkina Faso, Mali, Niger, and Nigeria from 1995 to 1999 were recorded. Disease incidence varied significantly among lines, locations, and years. The tested pearl millet lines exhibited significant differential resistance. Resistance in lines IP 18292, IP 18293, 700651 and P 310-17 was most stable regardless of the location or season. Analysis of the variation in resistance also suggested that the resistance in IP 18292 and IP 18293 was variable and depended on the locations and years, while the resistance in 700651 and P 310-17 was highly stable across locations and over years. The latter two lines could prove to be the most valuable sources of downy mildew resistance. The results also revealed significant differences in S. graminicola populations at different locations, with the highest disease at Bagauda (Nigeria) and Durgapura (India) and lowest from Coimbatore and Aurangabad (India). Based on the reaction of the 11 pearl millet lines, the 17 S. graminicola populations were grouped into six putative pathotypes (undefined populations closer to races)

Genomewide Association Study for Determinants of HIV-1 Acquisition and Viral Set Point in HIV-1 Serodiscordant Couples with Quantified Virus Exposure

Host genetic factors may be important determinants of HIV-1 sexual acquisition. We performed a genome-wide association study (GWAS) for host genetic variants modifying HIV-1 acquisition and viral control in the context of a cohort of African HIV-1 serodiscordant heterosexual couples. To minimize misclassification of HIV-1 risk, we quantified HIV-1 exposure, using data including plasma HIV-1 concentrations, gender, and condom use.We matched couples without HIV-1 seroconversion to those with seroconversion by quantified HIV-1 exposure risk. Logistic regression of single nucleotide polymorphisms (SNPs) for 798 samples from 496 HIV-1 infected and 302 HIV-1 exposed, uninfected individuals was performed to identify factors associated with HIV-1 acquisition. In addition, a linear regression analysis was performed using SNP data from a subset (n = 403) of HIV-1 infected individuals to identify factors predicting plasma HIV-1 concentrations.After correcting for multiple comparisons, no SNPs were significantly associated with HIV-1 infection status or plasma HIV-1 concentrations.This GWAS controlling for HIV-1 exposure did not identify common host genotypes influencing HIV-1 acquisition. Alternative strategies, such as large-scale sequencing to identify low frequency variation, should be considered for identifying novel host genetic predictors of HIV-1 acquisition

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator