1,183 research outputs found

    Modelling height in adolescence: a comparison of methods for estimating the age at peak height velocity

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    Background: Controlling for maturational status and timing is crucial in lifecourse epidemiology. One popular non-invasive measure of maturity is the age at peak height velocity (PHV). There are several ways to estimate age at PHV, but it is unclear which of these to use in practice. Aim: To find the optimal approach for estimating age at PHV. Subjects and methods: Methods included the Preece & Baines non-linear growth model, multi-level models with fractional polynomials, SuperImposition by Translation And Rotation (SITAR) and functional data analysis. These were compared through a simulation study and using data from a large cohort of adolescent boys from the Christ’s Hospital School. Results: The SITAR model gave close to unbiased estimates of age at PHV, but convergence issues arose when measurement error was large. Preece & Baines achieved close to unbiased estimates, but shares similarity with the data generation model for our simulation study and was also computationally inefficient, taking 24 hours to fit the data from Christ’s Hospital School. Functional data analysis consistently converged, but had higher mean bias than SITAR. Almost all methods demonstrated strong correlations (r > 0.9) between true and estimated age at PHV. Conclusions: Both SITAR or the PBGM are useful models for adolescent growth and provide unbiased estimates of age at peak height velocity. Care should be taken as substantial bias and variance can occur with large measurement error

    Aptamer-based multiplexed proteomic technology for biomarker discovery

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    Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

    Measurement of the hadronic photon structure function F_{2}^{γ} at LEP2

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    The hadronic structure function of the photon F_{2}^{γ} (x, Q²) is measured as a function of Bjorken x and of the photon virtuality Q² using deep-inelastic scattering data taken by the OPAL detector at LEP at e⁺e⁻ centre-of-mass energies from 183 to 209 GeV. Previous OPAL measurements of the x dependence of F_{2}^{γ} are extended to an average Q² of 〈Q²〉=780 GeV² using data in the kinematic range 0.15<x<0.98. The Q² evolution of F_{2}^{γ} is studied for 12.1<〈Q²〉<780 GeV² using three ranges of x. As predicted by QCD, the data show positive scaling violations in F_{2}^{γ} with F_{2}^{γ} (Q²)/α = (0.08±0.02⁺⁰·⁰⁵_₀.₀₃) + (0.13±0.01⁺⁰·⁰¹_₀.₀₁) lnQ², where Q² is in GeV², for the central x region 0.10–0.60. Several parameterisations of F_{2}^{γ} are in qualitative agreement with the measurements whereas the quark-parton model prediction fails to describe the data

    Measurement of the charm structure function F_{2,c)^{γ} of the photon at LEP

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    The production of charm quarks is studied in deep-inelastic electron–photon scattering using data recorded by the OPAL detector at LEP at nominal e⁺e⁻ centre-of-mass energies from 183 to 209 GeV. The charm quarks have been identified by full reconstruction of charged D* mesons using their decays into D⁰π with the D⁰ observed in two decay modes with charged particle final states, Kπ and Kπππ. The cross-section σ^{D*} for production of charged D* in the reaction e⁺e⁻→e⁺e⁻D*Χ is measured in a restricted kinematical region using two bins in Bjorken x, 0.00140.1 the perturbative QCD calculation at next-to-leading order agrees perfectly with the measured cross-section. For x<0.1 the measured cross-section is 43.8±14.3±6.3±2.8 pb with a next-to-leading order prediction of 17.0⁺²·⁹_₂.₃ pb

    Measurement of triple gauge boson couplings from W⁺W⁻ production at LEP energies up to 189 GeV

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    A measurement of triple gauge boson couplings is presented, based on W-pair data recorded by the OPAL detector at LEP during 1998 at a centre-of-mass energy of 189 GeV with an integrated luminosity of 183 pb⁻¹. After combining with our previous measurements at centre-of-mass energies of 161–183 GeV we obtain κ = 0.97_{-0.16}^{+0.20}, g_{1}^{z} = 0.991_{-0.057}^{+0.060} and λ = -0.110_{-0.055}^{+0.058}, where the errors include both statistical and systematic uncertainties and each coupling is determined by setting the other two couplings to their Standard Model values. These results are consistent with the Standard Model expectations

    Linking the Epigenome to the Genome: Correlation of Different Features to DNA Methylation of CpG Islands

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    DNA methylation of CpG islands plays a crucial role in the regulation of gene expression. More than half of all human promoters contain CpG islands with a tissue-specific methylation pattern in differentiated cells. Still today, the whole process of how DNA methyltransferases determine which region should be methylated is not completely revealed. There are many hypotheses of which genomic features are correlated to the epigenome that have not yet been evaluated. Furthermore, many explorative approaches of measuring DNA methylation are limited to a subset of the genome and thus, cannot be employed, e.g., for genome-wide biomarker prediction methods. In this study, we evaluated the correlation of genetic, epigenetic and hypothesis-driven features to DNA methylation of CpG islands. To this end, various binary classifiers were trained and evaluated by cross-validation on a dataset comprising DNA methylation data for 190 CpG islands in HEPG2, HEK293, fibroblasts and leukocytes. We achieved an accuracy of up to 91% with an MCC of 0.8 using ten-fold cross-validation and ten repetitions. With these models, we extended the existing dataset to the whole genome and thus, predicted the methylation landscape for the given cell types. The method used for these predictions is also validated on another external whole-genome dataset. Our results reveal features correlated to DNA methylation and confirm or disprove various hypotheses of DNA methylation related features. This study confirms correlations between DNA methylation and histone modifications, DNA structure, DNA sequence, genomic attributes and CpG island properties. Furthermore, the method has been validated on a genome-wide dataset from the ENCODE consortium. The developed software, as well as the predicted datasets and a web-service to compare methylation states of CpG islands are available at http://www.cogsys.cs.uni-tuebingen.de/software/dna-methylation/

    Highly Parallel Translation of DNA Sequences into Small Molecules

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    A large body of in vitro evolution work establishes the utility of biopolymer libraries comprising 1010 to 1015 distinct molecules for the discovery of nanomolar-affinity ligands to proteins.[1], [2], [3], [4], [5] Small-molecule libraries of comparable complexity will likely provide nanomolar-affinity small-molecule ligands.[6], [7] Unlike biopolymers, small molecules can offer the advantages of cell permeability, low immunogenicity, metabolic stability, rapid diffusion and inexpensive mass production. It is thought that such desirable in vivo behavior is correlated with the physical properties of small molecules, specifically a limited number of hydrogen bond donors and acceptors, a defined range of hydrophobicity, and most importantly, molecular weights less than 500 Daltons.[8] Creating a collection of 1010 to 1015 small molecules that meet these criteria requires the use of hundreds to thousands of diversity elements per step in a combinatorial synthesis of three to five steps. With this goal in mind, we have reported a set of mesofluidic devices that enable DNA-programmed combinatorial chemistry in a highly parallel 384-well plate format. Here, we demonstrate that these devices can translate DNA genes encoding 384 diversity elements per coding position into corresponding small-molecule gene products. This robust and efficient procedure yields small molecule-DNA conjugates suitable for in vitro evolution experiments

    Discovery of VHE Gamma Radiation from IC443 with the MAGIC Telescope

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    We report the detection of a new source of very high energy (VHE, E_gamma >= 100GeV) gamma-ray emission located close to the Galactic Plane, MAGIC J0616+225, which is spatially coincident with SNR IC443. The observations were carried out with the MAGIC telescope in the periods December 2005 - January 2006 and December 2006 - January 2007. Here we present results from this source, leading to a VHE gamma-ray signal with a statistical significance of 5.7 sigma in the 2006/7 data and a measured differential gamma-ray flux consistent with a power law, described as dN_gamma/(dA dt dE) = (1.0 +/- 0.2)*10^(-11)(E/0.4 TeV)^(-3.1 +/- 0.3) cm^(-2)s^(-1)TeV^(-1). We briefly discuss the observational technique used and the procedure implemented for the data analysis. The results are put in the perspective of the multiwavelength emission and the molecular environment found in the region of IC443.Comment: Accepted by ApJ Letter
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