215 research outputs found

    Radar‐Sounding Characterization of the Subglacial Groundwater Table Beneath Hiawatha Glacier, Greenland

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    Radar-sounding surveys associated with the discovery of a large impact crater beneath Hiawatha Glacier, Greenland, revealed bright, flat subglacial reflections hypothesized to originate from a subglacial groundwater table. We test this hypothesis using radiometric and hydrologic analysis of those radar data. The dielectric loss between the reflection from the top of the basal layer and subglacial reflection and their reflectivity difference represent dual constraints upon the complex permittivity of the basal material. Either ice-cemented debris or fractured, well-drained bedrock explain the basal layer's radiometric properties. The subglacial reflector's geometry is parallel to isopotential hydraulic head contours, located 7.5–15.3 m below the interface, and 11 ± 7 dB brighter than the ice–basal layer reflection. We conclude that this subglacial reflection is a groundwater table and that its detection was enabled by the wide bandwidth of the radar system and unusual geologic setting, suggesting a path for future direct radar detection of subglacial groundwater elsewhere

    Estimates of array and pool-construction variance for planning efficient DNA-pooling genome wide association studies

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    <p>Abstract</p> <p>Background</p> <p>Until recently, genome-wide association studies (GWAS) have been restricted to research groups with the budget necessary to genotype hundreds, if not thousands, of samples. Replacing individual genotyping with genotyping of DNA pools in Phase I of a GWAS has proven successful, and dramatically altered the financial feasibility of this approach. When conducting a pool-based GWAS, how well SNP allele frequency is estimated from a DNA pool will influence a study's power to detect associations. Here we address how to control the variance in allele frequency estimation when DNAs are pooled, and how to plan and conduct the most efficient well-powered pool-based GWAS.</p> <p>Methods</p> <p>By examining the variation in allele frequency estimation on SNP arrays between and within DNA pools we determine how array variance [var(e<sub>array</sub>)] and pool-construction variance [var(e<sub>construction</sub>)] contribute to the total variance of allele frequency estimation. This information is useful in deciding whether replicate arrays or replicate pools are most useful in reducing variance. Our analysis is based on 27 DNA pools ranging in size from 74 to 446 individual samples, genotyped on a collective total of 128 Illumina beadarrays: 24 1M-Single, 32 1M-Duo, and 72 660-Quad.</p> <p>Results</p> <p>For all three Illumina SNP array types our estimates of var(e<sub>array</sub>) were similar, between 3-4 × 10<sup>-4 </sup>for normalized data. Var(e<sub>construction</sub>) accounted for between 20-40% of pooling variance across 27 pools in normalized data.</p> <p>Conclusions</p> <p>We conclude that relative to var(e<sub>array</sub>), var(e<sub>construction</sub>) is of less importance in reducing the variance in allele frequency estimation from DNA pools; however, our data suggests that on average it may be more important than previously thought. We have prepared a simple online tool, PoolingPlanner (available at <url>http://www.kchew.ca/PoolingPlanner/</url>), which calculates the effective sample size (ESS) of a DNA pool given a range of replicate array values. ESS can be used in a power calculator to perform pool-adjusted calculations. This allows one to quickly calculate the loss of power associated with a pooling experiment to make an informed decision on whether a pool-based GWAS is worth pursuing.</p

    Presymptomatic risk assessment for chronic non-communicable diseases

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    The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the journal's pdf versio

    Dynamic early identification of hip replacement implants with high revision rates. Study based on the NJR data from UK during 2004-2012

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    BACKGROUND: Hip replacement and hip resurfacing are common surgical procedures with an estimated risk of revision of 4% over 10 year period. Approximately 58% of hip replacements will last 25 years. Some implants have higher revision rates and early identification of poorly performing hip replacement implant brands and cup/head brand combinations is vital. AIMS: Development of a dynamic monitoring method for the revision rates of hip implants. METHODS: Data on the outcomes following the hip replacement surgery between 2004 and 2012 was obtained from the National Joint Register (NJR) in the UK. A novel dynamic algorithm based on the CUmulative SUM (CUSUM) methodology with adjustment for casemix and random frailty for an operating unit was developed and implemented to monitor the revision rates over time. The Benjamini-Hochberg FDR method was used to adjust for multiple testing of numerous hip replacement implant brands and cup/ head combinations at each time point. RESULTS: Three poorly performing cup brands and two cup/ head brand combinations have been detected. Wright Medical UK Ltd Conserve Plus Resurfacing Cup (cup o), DePuy ASR Resurfacing Cup (cup e), and Endo Plus (UK) Limited EP-Fit Plus Polyethylene cup (cup g) showed stable multiple alarms over the period of a year or longer. An addition of a random frailty term did not change the list of underperforming components. The model with added random effect was more conservative, showing less and more delayed alarms. CONCLUSIONS: Our new algorithm is an efficient method for early detection of poorly performing components in hip replacement surgery. It can also be used for similar tasks of dynamic quality monitoring in healthcare

    Socio-demographic factors and edentulism: the Nigerian experience

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    BACKGROUND: The rate of total edentulism is said to be increasing in developing countries and this had been attributed mainly to the high prevalence of periodontal diseases and caries. Several reports have shown that non-disease factors such as attitude, behavior, dental attendance, characteristics of health care systems and socio-demographic factors play important roles in the aetiopathogenesis of edentulism. The aim of this study was to assess the relationship between socio-demographic factors and edentulism. METHODS: A total of 152 patients made up of 80 (52.6%) males and 72 (47.4%) females who presented in two prosthetic clinics located in an urban and a rural area were included in the study. The relationship between gender, age, socio-economic status and edentulism in this study population was established. RESULTS: No significant relationship between gender and denture demand was noted in the study. The demand for complete dentures increased with age while the demand for removable partial dentures also increased with age until the 3(rd )decade and then started to decline. A significant relationship was found between denture demand and the level of education with a higher demand in lower educational groups (p < 0.001). In addition, the lower socio-economic group had a higher demand more for prostheses than the higher group. CONCLUSIONS: The findings in this study revealed a significant relationship between socio-demographic variables and edentulism with age, educational level and socio-economic status playing vital roles in edentulism and denture demand

    Asteroseismology and Interferometry

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    Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36

    Selecting Forecasting Methods

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    I examined six ways of selecting forecasting methods: Convenience, “what’s easy,” is inexpensive, but risky. Market popularity, “what others do,” sounds appealing but is unlikely to be of value because popularity and success may not be related and because it overlooks some methods. Structured judgment, “what experts advise,” which is to rate methods against prespecified criteria, is promising. Statistical criteria, “what should work,” are widely used and valuable, but risky if applied narrowly. Relative track records, “what has worked in this situation,” are expensive because they depend on conducting evaluation studies. Guidelines from prior research, “what works in this type of situation,” relies on published research and offers a low-cost, effective approach to selection. Using a systematic review of prior research, I developed a flow chart to guide forecasters in selecting among ten forecasting methods. Some key findings: Given enough data, quantitative methods are more accurate than judgmental methods. When large changes are expected, causal methods are more accurate than naive methods. Simple methods are preferable to complex methods; they are easier to understand, less expensive, and seldom less accurate. To select a judgmental method, determine whether there are large changes, frequent forecasts, conflicts among decision makers, and policy considerations. To select a quantitative method, consider the level of knowledge about relationships, the amount of change involved, the type of data, the need for policy analysis, and the extent of domain knowledge. When selection is difficult, combine forecasts from different methods
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