Electronic flaw simulator for eddy current probe calibration

Electronic flaw simulator cycled into the eddy current system eliminates errors in probe calibration. A discrimination level reference established in the probe permits recognition of those flaws in materials with an equivalent volume equal to or greater than the reference

Genetic signal maximization using environmental regression

Joint analyses of correlated phenotypes in genetic epidemiology studies are common. However, these analyses primarily focus on genetic correlation between traits and do not take into account environmental correlation. We describe a method that optimizes the genetic signal by accounting for stochastic environmental noise through joint analysis of a discrete trait and a correlated quantitative marker. We conducted bivariate analyses where heritability and the environmental correlation between the discrete and quantitative traits were calculated using Genetic Analysis Workshop 17 (GAW17) family data. The resulting inverse value of the environmental correlation between these traits was then used to determine a new β coefficient for each quantitative trait and was constrained in a univariate model. We conducted genetic association tests on 7,087 nonsynonymous SNPs in three GAW17 family replicates for Affected status with the β coefficient fixed for three quantitative phenotypes and compared these to an association model where the β coefficient was allowed to vary. Bivariate environmental correlations were 0.64 (± 0.09) for Q1, 0.798 (± 0.076) for Q2, and −0.169 (± 0.18) for Q4. Heritability of Affected status improved in each univariate model where a constrained β coefficient was used to account for stochastic environmental effects. No genome-wide significant associations were identified for either method but we demonstrated that constraining β for covariates slightly improved the genetic signal for Affected status. This environmental regression approach allows for increased heritability when the β coefficient for a highly correlated quantitative covariate is constrained and increases the genetic signal for the discrete trait

Influence of molecular weight on the phase behavior and structure formation of branched side-chain hairy-rod polyfluorene in bulk phase.

We report on an experimental study of the self-organization and phase behavior of hairy-rod π -conjugated branched side-chain polyfluorene, poly[9,9-bis(2-ethylhexyl)-fluorene-2,7-diyl]—i.e., poly[2,7–(9,9–bis(2–ethylhexyl)fluorene] (PF2∕6) —as a function of molecular weight (Mn) . The results have been compared to those of phenomenological theory. Samples for which Mn=3–147 kg∕mol were used. First, the stiffness of PF2∕6 , the assumption of the theory, has been probed by small-angle neutron scattering in solution. Thermogravimetry has been used to show that PF2∕6 is thermally stable over the conditions studied. Second, the existence of nematic and hexagonal phases has been phenomenologically identified for lower and higher Mn (LMW, Mn<Mn* and HMW, Mn>Mn* ) regimes, respectively, based on free-energy argument of nematic and hexagonal hairy rods and found to correspond to the experimental x-ray diffraction (XRD) results for PF2∕6 . By using the lattice parameters of PF2∕6 as an experimental input, the nematic-hexagonal transition has been predicted in the vicinity of glassification temperature (Tg) of PF2∕6 . Then, by taking the orientation parts of the free energies into account the nematic-hexagonal transition has been calculated as a function of temperature and Mn and a phase diagram has been formed. Below Tg of 80 °C only (frozen) nematic phase is observed for Mn<Mn*=104 g∕mol and crystalline hexagonal phase for Mn>Mn* . The nematic-hexagonal transition upon heating is observed for the HMW regime depending weakly on Mn , being at 140–165 °C for Mn>Mn* . Third, the phase behavior and structure formation as a function of Mn have been probed using powder and fiber XRD and differential scanning calorimetry and reasonable semiquantitative agreement with theory has been found for Mn≥3 kg∕mol . Fourth, structural characteristics are widely discussed. The nematic phase of LMW materials has been observed to be denser than high-temperature nematic phase of HMW compounds. The hexagonal phase has been found to be paracrystalline in the (ab0) plane but a genuine crystal meridionally. We also find that all these materials including the shortest 10-mer possess the formerly observed rigid five-helix hairy-rod molecular structure

Confidence set of putative quantitative trait loci in whole genome scans with application to the Genetic Analysis Workshop 17 simulated data

As genetic maps become more highly dense, the ability to sufficiently localize putative disease loci becomes an achievable goal. This has prompted an increased interest in methods for constructing confidence intervals for the location of variants that contribute to a trait. Such intervals are important because, by reducing the number of candidate loci, they can help in the design of cost-effective and time-efficient follow-up studies. We introduce a new approach that can be used in whole-genome scans to obtain a confidence set of loci that contribute at least a predetermined percentage h to the overall genetic variation of a quantitative phenotype. The method is developed in the framework of generalized linear mixed models and can accommodate families of arbitrary size and structure. We apply our method to the Genetic Analysis Workshop 17 simulated data where we scan chromosomes 6, 15, 20, 21, and 22 to uncover loci regulating the simulated phenotype Q2. For the analyses we had prior knowledge of the simulation model used to generate the phenotype

Do rare variant genotypes predict common variant genotypes?

The synthetic association hypothesis proposes that common genetic variants detectable in genome-wide association studies may reflect the net phenotypic effect of multiple rare polymorphisms distributed broadly within the focal gene rather than, as often assumed, the effect of common functional variants in high linkage disequilibrium with the focal marker. In a recent study, Dickson and colleagues demonstrated synthetic association in simulations and in two well-characterized, highly polymorphic human disease genes. The converse of this hypothesis is that rare variant genotypes must be correlated with common variant genotypes often enough to make the phenomenon of synthetic association possible. Here we used the exome genotype data provided for Genetic Analysis Workshop 17 to ask how often, how well, and under what conditions rare variant genotypes predict the genotypes of common variants within the same gene. We found nominal evidence of correlation between rare and common variants in 21-30% of cases examined for unrelated individuals; this rate increased to 38-44% for related individuals, underscoring the segregation that underlies synthetic association

TEMPO-oxidized cellulose nanofibril/polyvalent cations hydrogels: a multifaceted view of network interactions and inner structure

In the last years, hydrogels from renewable biopolymers and low-cost row materials are a hot topic for biomedical applications. In this context, cellulose nanofibrils are considered suitable building blocks for the synthesis of many biocompatible products, with a variety of chemical-physical properties. Herein we report a multi-technique and multi-scale study, from the molecular to the nanometric length scale, of the sol-gel transition observed in aqueous solutions of TEMPO-oxidized nano-sized cellulose fibrils (TOCNFs), when in the presence of polyvalent cations (Mg2+ and Ca2+). We combine the data from Small Angle Neutron Scattering (SANS), which provide information about the inner structure of the nanofibril, with those from UV Resonant Raman (UVRR) spectroscopy, which is a sensitive probe of the intra- and inter-molecular interactions in the gel and the liquid state. The transition between the gel and the liquid phases is investigated as a function of the concentration of both TOCNFs and cations, the nature of the latter, and the pH at which the phenomenon is observed. SANS analysis reveals that ion concentration induces an anisotropic swelling in the nanofibrils which, at the same time, become more and more flexible. The nanofibrils flexibility is also dependent on TOCNF concentration and pH value. UVRR allows us to elucidate the structural organization and hydrogen-bonding properties of water in aqueous TOCNF dispersions and gels, showing how water molecules partially lose their typical bulk-like tetrahedral organization when ions are added, and the gel phase is formed

GM1 Ganglioside role in the interaction of Alpha-synuclein with lipid membranes: Morphology and structure

Alpha-Synuclein (AS) is the protein playing the major role in Parkinson's disease (PD), a neurological disorder characterized by the degeneration of dopaminergic neurons and the accumulation of AS into amyloid plaques. The aggregation of AS into intermediate aggregates, called oligomers, and their pathological relation with biological membranes are considered key steps in the development and progression of the disease. Here we propose a multi-technique approach to study the effects of AS in its monomeric and oligomeric forms on artificial lipid membranes containing GM1 ganglioside. GM1 is a component of functional membrane micro-domains, called lipid rafts, and has been demonstrated to bind AS in neurons. With the aim to understand the relation between gangliosides and AS, here we exploit the complementarity of microscopy (Atomic Force Microscopy) and neutron scattering (Small Angle Neutron Scattering and Neutron Reflectometry) techniques to analyze the structural changes of two different membranes (Phosphatidylcholine and Phosphatidylcholine/GM1) upon binding with AS. We observe the monomer- and oligomer-interactions are both limited to the external membrane leaflet and that the presence of ganglioside leads to a stronger interaction of the membranes and AS in its monomeric and oligomeric forms with a stronger aggressiveness in the latter. These results support the hypothesis of the critical role of lipid rafts not only in the biofunctioning of the protein, but even in the development and the progression of the Parkinson's disease

Comparison of scoring methods for the detection of causal genes with or without rare variants

Rare causal variants are believed to significantly contribute to the genetic basis of common diseases or quantitative traits. Appropriate statistical methods are required to discover the highest possible number of disease-relevant variants in a genome-wide screening study. The publicly available Genetic Analysis Workshop 17 data set consists of 697 individuals and 24,487 genetic variants. It includes a simulated complex disease model with intermediate quantitative phenotypes. We compare four gene-wise scoring methods with respect to ranking of causal genes under variable allele frequency thresholds for collapsing of rare variants and considering whether or not rare variants were included. We also compare causal genes for which the ranks differ clearly between scoring methods regarding such characteristics as number and strength of causal variants. We corroborated our findings with additional simulations. We found that the maximum statistics method was superior in assigning high ranks to genes with a single strong causal variant. Hotelling’s T2 test was superior for genes with several independent causal variants. This was consistent for all phenotypes and was confirmed by single-gene analyses and additional simulations. The multivariate analysis performed similarly to Hotelling’s T2 test. The least absolute shrinkage and selection operator (LASSO) analysis was widely comparable with the maximum statistics method. We conclude that the maximum statistics method is a superior alternative to Hotelling’s T2 test if one expects only one independent causal variant per gene with a dominating effect. Such a variant could also be a supermarker derived by collapsing rare variants. Because the true nature of the genetic effect is unknown for real data, both methods need to be taken into consideration

Interrogating population structure and its impact on association tests

We found from our analysis of the Genetic Analysis Workshop 17 data that the population structure of the 697 unrelated individuals was an important confounding factor for association studies, even if it was not explicitly considered when simulating the phenotypes. We uncovered structures beyond the reported ethnicities and found ample evidence of phenotype–population structure associations. The first 10 principal components of the genotype data of the 697 individuals demonstrated much stronger associations with Q1, Q2, and the disease than did the individuals’ ethnicities. In addition, we observed that population structure was a confounding factor for the Q1-gene association when identifying the significant genes both with and without adjusting for the causal single-nucleotide polymorphisms, the ethnicities, and the principal components. Many false discoveries remained after adjusting for the causal single-nucleotide polymorphisms. Adjusting for the principal components appeared more effective than did adjusting for ethnicity in terms of preventing false discoveries. This analysis was performed with knowledge of the causal loci