Effective Sample Size: Quick Estimation of the Effect of Related Samples in Genetic Case-Control Association Analyses

Correlated samples have been frequently avoided in case-control
genetic association
 studies in part because the methods for handling them are either not
easily implemented or not widely known. We
advocate one method for case-control association analysis of correlated
samples -- the effective sample size method -- as a simple and
accessible approach that does not require specialized computer programs.
The effective sample size method captures the variance inflation
of allele frequency estimation exactly, and can be used to modify the
chi-square test statistic, p-value, and 95% confidence interval of
odds-ratio simply by replacing the apparent number of allele counts with the
effective ones. For genotype frequency estimation, although a single
effective sample size is unable to completely characterize the variance inflation,
an averaged one can satisfactorily approximate the simulated result.
The effective sample size method is applied to the rheumatoid arthritis
siblings data collected from the North American Rheumatoid Arthritis Consortium (NARAC)
to establish a significant association with the interferon-induced
helicasel gene (IFIH1) previously being identified as a type 1 diabetes
susceptibility locus. Connections between the effective sample size
method and other methods, such as generalized estimation equation,
variance of eigenvalues for correlation matrices, and genomic controls,
are also discussed.
&#xa

Modulation of Opioid Receptor Binding by Cis and Trans Fatty Acids

In synaptosomal brain membranes, the addition of oleic acid (cis), elaidic acid (trans), and the cis and trans isomers of vaccenic acid, at a concentration of 0.87 Μmol of lipid/mg of protein, strongly reduced the B max and, to a lesser degree, the binding affinity of the Μ-selective opioid [ 3 H]Tyr-D-Ala-Gly-(Me)Phe-Gly-ol ([ 3 H]DAMGO). At comparable membrane content, the cis isomers of the fatty acids were more potent than their trans counterparts in inhibiting ligand binding and in decreasing membrane microviscosity, both at the membrane surface and in the core. However, trans- vaccenic acid affected opioid receptor binding in spite of just marginally altering membrane microviscosity. If the receptors were uncoupled from guanine nucleotide regulatory protein, an altered inhibition profile was obtained: the impairment of K D by the fatty acids was enhanced and that of B max reduced. Receptor interaction of the Δ-opioid [ 3 H](D-Pen 2 ,D-Pen 5 )enkephalin was modulated by lipids to a greater extent than that of [ 3 H]DAMGO: saturable binding was abolished by both oleic and elaidic acids. The binding of [ 3 H]naltrexone was less susceptible to inhibition by the fatty acids, particularly in the presence of sodium. In the absence of this cation, however, cis -vaccenic acid abolished the low-affinity binding component of [ 3 H]naltrexone. These findings support the membrane model of opioid receptor sequestration depicting different ionic environments for the Μ- and Δ-binding sites. The results of this work show distinct modulation of different types and molecular states of opioid receptor by fatty acids through mechanisms involving membrane fluidity and specific interactions with membrane constituents.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66085/1/j.1471-4159.1990.tb05787.x.pd

Geospatial dimensions of the renewable energy transition — The importance of prioritisation

The renewable energy transition is a priority for many researchers, policy makers, and political leaders because it is projected to stop the dependence of economic growth on increasing fossil fuel use and thus curtail climate change. This study examines how expert judgments affect development decisions to enable the renewable energy transition. Geospatial Multi-Criteria Decision Analyses (MCDA) are frequently used to select offshore wind energy (OWE) sites, however, they are often weak and/or often rely on limited judgement. The Analytical Hierarchy Process is used here with 25 diverse experts to assess the variability in priorities for OWE siting criteria. A geospatial MCDA is implemented using experts' individual priorities, aggregated weights and Monte Carlo simulations. Case study results reveal large variations in expert opinions and bias strongly affecting MCDAs weighted by single decision-makers. A group-decision approach is proposed to strengthen consent for OWE, underpinning the renewable energy transition

Dispelling the myths of online education: learning via the information superhighway

There continues to be a perception that online education is inferior to traditional education. In the U.S. online learning is more developed than in the U.K. This paper provides insights into a U.S. provision and takes a close look at what are perceived as weaknesses of on line learning and argues that these are not necessarily inherent weaknesses of this form of educational delivery. Then, results of two major studies, undertaken in the U.S. are provided comparing the effectiveness of online education to traditional education as perceived by current MBA students and past graduates. Results of these studies suggest that students of MBA modules and MBA graduates perceive the quality and effectiveness of online education to be similar to, if not higher than, the quality and effectiveness of traditional modules and programmes

Capital structure and its determinants in the United Kingdom – a decompositional analysis

Prior research on capital structure by Rajan and Zingales (1995) suggests that the level of gearing in UK companies is positively related to size and tangibility, and negatively correlated with profitability and the level of growth opportunities. However, as argued by Harris and Raviv (1991), 'The interpretation of results must be tempered by an awareness of the difficulties involved in measuring both leverage and the explanatory variables of interest'. In this study the focus is on the difficulties of measuring gearing, and the sensitivity of Rajan and Zingales' results to variations in gearing measures are tested. Based on an analysis of the capital structure of 822 UK companies, Rajan and Zingales' results are found to be highly definitional-dependent. The determinants of gearing appear to vary significantly, depending upon which component of debt is being analysed. In particular, significant differences are found in the determinants of long- and short-term forms of debt. Given that trade credit and equivalent, on average, accounts for more than 62% of total debt, the results are particularly sensitive to whether such debt is included in the gearing measure. It is argued, therefore, that analysis of capital structure is incomplete without a detailed examination of all forms of corporate debt

Large and small cribriform architecture have similar adverse clinical outcome on prostate cancer biopsies

Aims: Invasive cribriform and intraductal carcinoma (IDC) are associated with adverse outcome in prostate cancer patients, with the large cribriform pattern having the worst outcome in radical prostatectomies. Our objective was to determine the impact of the large and small cribriform patterns in prostate cancer biopsies. Methods and results: Pathological revision was carried out on biopsies of 1887 patients from the European Randomised Study of Screening for Prostate Cancer. The large cribriform pattern was defined as having at least twice the size of adjacent benign glands. The median follow-up time was 13.4 years. Hazard ratios for metastasis-free survival (MFS) and disease-specific survival (DSS) were calculated using Cox proportional hazards regression. Any cribriform pattern was found in 280 of 1887 men: 1.1% IDC in grade group (GG) 1, 18.2% in GG2, 57.1% in GG3, 55.4% in GG4 and 59.3% in GG5; the large cribriform pattern was present in 0, 0.5, 9.8, 18.1 and 17.3%, respectively. In multivariable analyses, small and large cribriform patterns were both (P &lt; 0.005) associated with worse MFS [small: hazard ratio (HR) = 3.04, 95% confidence interval (CI) = 1.93–4.78; large: HR = 3.17, 95% CI = 1.68–5.99] and DSS (small: HR = 4.07, 95% CI = 2.51–6.62; large: HR = 4.13, 95% CI = 2.14–7.98). Patients with the large cribriform pattern did not have worse MFS (P = 0.77) or DSS (P = 0.96) than those with the small cribriform pattern. Conclusions: Both small and large cribriform patterns are associated with worse MFS and DSS in prostate cancer biopsies. Patients with the large cribriform pattern on biopsy have a similar adverse outcome as those with the small cribriform pattern.</p

Generalized Interpolation Material Point Approach to High Melting Explosive with Cavities Under Shock

Criterion for contacting is critically important for the Generalized Interpolation Material Point(GIMP) method. We present an improved criterion by adding a switching function. With the method dynamical response of high melting explosive(HMX) with cavities under shock is investigated. The physical model used in the present work is an elastic-to-plastic and thermal-dynamical model with Mie-Gr\"uneissen equation of state. We mainly concern the influence of various parameters, including the impacting velocity $v$, cavity size $R$, etc, to the dynamical and thermodynamical behaviors of the material. For the colliding of two bodies with a cavity in each, a secondary impacting is observed. Correspondingly, the separation distance $D$ of the two bodies has a maximum value $D_{\max}$ in between the initial and second impacts. When the initial impacting velocity $v$ is not large enough, the cavity collapses in a nearly symmetric fashion, the maximum separation distance $D_{\max}$ increases with $v$. When the initial shock wave is strong enough to collapse the cavity asymmetrically along the shock direction, the variation of $D_{\max}$ with $v$ does not show monotonic behavior. Our numerical results show clear indication that the existence of cavities in explosive helps the creation of ``hot spots''.Comment: Figs.2,4,7,11 in JPG format; Accepted for publication in J. Phys. D: Applied Physic

Resolution of Biphasic Binding of the Opioid Antagonist Naltrexone in Brain Membranes

In synaptosomal membranes from rat brain cortex, in the presence of 150 m M NaC1, the opioid antagonist [ 3 H] naltrexone bound to two populations of receptor sites with affinities of 0.27 and 4.3 n M , respectively. Guanosine-5′-(3-thiotriphosphate) had little modulating effect and did not alter the biphasic nature of ligand binding. On the other hand, receptor-selective opioids differentially inhibited the two binding components of [ 3 H] naltrexone. As shown by nonlinear least-squares analysis, the Μ opioids Tyr-D-Ala-Gly-(Me)Phe-Gly-ol or sufentanil abolished high-affinity [ 3 H] naltrexone binding, whereas the Δ-selective ligands [D- Pen 2 , D-Pen 5 ] enkephalin, ICI 174, 864, and oxymorphindole inhibited and eventually eliminated the low-affinity component in a concentration-dependent manner. These results indicate that, in contrast to the guanine nucleotide-sensitive biphasic binding of opioid-alkaloid agonists, the heterogeneity of naltrexone binding in brain membranes reflects ligand interaction with different opioid-receptor types.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66340/1/j.1471-4159.1991.tb08288.x.pd

Data for Genetic Analysis Workshop 16 Problem 1, Association Analysis of Rheumatoid Arthritis Data

For Genetic Analysis Workshop 16 Problem 1, we provided data for genome-wide association analysis of rheumatoid arthritis. Single-nucleotide polymorphism (SNP) genotype data were provided for 868 cases and 1194 controls that had been assayed using an Illumina 550 k platform. In addition, phenotypic data were provided from genotyping DRB1 alleles, which were classified according to the rheumatoid arthritis shared epitope, levels of anti-cyclic citrullinated peptide, and levels of rheumatoid factor IgM. Several questions could be addressed using the data, including analysis of genetic associations using single SNPs or haplotypes, as well as gene-gene and genetic analysis of SNPs for qualitative and quantitative factors