287 research outputs found

    Transport and Spectroscopic Studies of the Effects of Fullerene Structure on the Efficiency and Lifetime of Polythiophene-based Solar Cells

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    Time-dependent measurements of both power conversion efficiency and ultraviolet-visible absorption spectroscopy have been observed for solar cell blends containing the polymer poly(3-hexylthiophene-2,5-diyl) (P3HT) with two different functionalized C60 electron acceptor molecules: commercially available [6,6]-phenyl C61 butyric acid methyl ester (PCBM) or [6,6]-phenyl C61 butyric acid octadecyl ester (PCBOD) produced in this laboratory. Efficiency was found to decay with an exponential time dependence, while spectroscopic features show saturating exponential behavior. Time constants extracted from both types of measurements showed reasonable agreement for samples produced from the same blend. In comparison to the PCBM samples, the stability of the PCBOD blends was significantly enhanced, while both absorption and power conversion efficiency were decreased.Comment: manuscript submitted to Solar Energy Materials and Solar Cell

    Multiscale Kinetic Monte-Carlo for Simulating Epitaxial Growth

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    We present a fast Monte-Carlo algorithm for simulating epitaxial surface growth, based on the continuous-time Monte-Carlo algorithm of Bortz, Kalos and Lebowitz. When simulating realistic growth regimes, much computational time is consumed by the relatively fast dynamics of the adatoms. Continuum and continuum-discrete hybrid methods have been developed to approach this issue; however in many situations, the density of adatoms is too low to efficiently and accurately simulate as a continuum. To solve the problem of fast adatom dynamics, we allow adatoms to take larger steps, effectively reducing the number of transitions required. We achieve nearly a factor of ten speed up, for growth at moderate temperatures and large D/F.Comment: 7 pages, 6 figures; revised text, accepted by PR

    Influence of functionalized fullerene structure on polymer photovoltaic degradation

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    The time dependence of device performance has been measured for photocells using blends containing the conjugated polymer, poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) with two different functionalized C60 electron acceptor molecules: commercially available [6,6]-phenyl C61 butyric acid methyl ester (PCBM) or [6,6]-phenyl C61 butyric acid octadecyl ester (PCBOD) produced in this laboratory. Performance was characterized by the short-circuit current output of the devices, with the time dependence of PCBM samples typically degrading exponentially. Variations in the characteristic lifetime of the devices were observed to depend on the molar fraction of the electron acceptor molecules (calculated with respect to the MEH-PPV monomer fraction). In comparison to the PCBM samples, the stability of the PCBOD blends was significantly enhanced, with a one or two order of magnitude improvement. Corresponding spectroscopic data with similar time evolution as the transport measurements suggest an independent means for determining and understanding degradation mechanisms

    In Vivo Quantification of Placental Insufficiency by BOLD MRI: A Human Study

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    Fetal health is critically dependent on placental function, especially placental transport of oxygen from mother to fetus. When fetal growth is compromised, placental insufficiency must be distinguished from modest genetic growth potential. If placental insufficiency is present, the physician must trade off the risk of prolonged fetal exposure to placental insufficiency against the risks of preterm delivery. Current ultrasound methods to evaluate the placenta are indirect and insensitive. We propose to use Blood-Oxygenation-Level-Dependent (BOLD) MRI with maternal hyperoxia to quantitatively assess mismatch in placental function in seven monozygotic twin pairs naturally matched for genetic growth potential. In-utero BOLD MRI time series were acquired at 29 to 34 weeks gestational age. Maps of oxygen Time-To-Plateau (TTP) were obtained in the placentas by voxel-wise fitting of the time series. Fetal brain and liver volumes were measured based on structural MR images. After delivery, birth weights were obtained and placental pathological evaluations were performed. Mean placental TTP negatively correlated with fetal liver and brain volumes at the time of MRI as well as with birth weights. Mean placental TTP positively correlated with placental pathology. This study demonstrates the potential of BOLD MRI with maternal hyperoxia to quantify regional placental function in vivo.National Institutes of Health (U.S.) (Grant U01 HD087211)National Institutes of Health (U.S.) (Grant R01 EB017337

    A new ghost cell/level set method for moving boundary problems:application to tumor growth

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    In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics—an effect observed in real tumor growth

    Missense Mutation in Exon 2 of SLC36A1 Responsible for Champagne Dilution in Horses

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    Champagne coat color in horses is controlled by a single, autosomal-dominant gene (CH). The phenotype produced by this gene is valued by many horse breeders, but can be difficult to distinguish from the effect produced by the Cream coat color dilution gene (CR). Three sires and their families segregating for CH were tested by genome scanning with microsatellite markers. The CH gene was mapped within a 6 cM region on horse chromosome 14 (LOD = 11.74 for θ = 0.00). Four candidate genes were identified within the region, namely SPARC [Secreted protein, acidic, cysteine-rich (osteonectin)], SLC36A1 (Solute Carrier 36 family A1), SLC36A2 (Solute Carrier 36 family A2), and SLC36A3 (Solute Carrier 36 family A3). SLC36A3 was not expressed in skin tissue and therefore not considered further. The other three genes were sequenced in homozygotes for CH and homozygotes for the absence of the dilution allele (ch). SLC36A1 had a nucleotide substitution in exon 2 for horses with the champagne phenotype, which resulted in a transition from a threonine amino acid to an arginine amino acid (T63R). The association of the single nucleotide polymorphism (SNP) with the champagne dilution phenotype was complete, as determined by the presence of the nucleotide variant among all 85 horses with the champagne dilution phenotype and its absence among all 97 horses without the champagne phenotype. This is the first description of a phenotype associated with the SLC36A1 gene

    New approaches for the assessment of vessel sizes in quantitative (cardio-)vascular X-ray analysis

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    This paper presents new approaches for the assessment of the arterial and reference diameters in (cardio-)vascular X-ray images, designed to overcome the problems experienced in conventional quantitative coronary and vascular angiography approaches. In single or “straight” vessel segments, the arterial and reference diameter directions were made independent of each other in order to be able to measure the minimal lumen diameter (MLD) more accurately, especially in curved vessel segments. For ostial segments, an extension of this approach was used, to allow measurement of ostial lesions in sidebranches more proximal than using conventional methods. Furthermore, two new bifurcation approaches were developed. The validation study shows that the straight segment approach results in significant smaller MLDs (on average 0.032 mm) and the ostial approach achieves on average an increase in %DS of 3.8% and an increase in lesion length of 0.59 mm due to loosening the directional constraint. The validation of our new bifurcation approaches in phantom data as well as clinical data shows only small differences between pre- and post-intervention measurements of the reference diameters outside the bifurcation core (errors smaller than 0.06 mm) and the bifurcation core area (errors smaller than 1.4% for phantom data). In summary, these new approaches have led to further improvements in the quantitative analyses of (cardio-)vascular X-ray angiographies

    Stochastic simulation and analysis of biomolecular reaction networks

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    <p>Abstract</p> <p>Background</p> <p>In recent years, several stochastic simulation algorithms have been developed to generate Monte Carlo trajectories that describe the time evolution of the behavior of biomolecular reaction networks. However, the effects of various stochastic simulation and data analysis conditions on the observed dynamics of complex biomolecular reaction networks have not recieved much attention. In order to investigate these issues, we employed a a software package developed in out group, called Biomolecular Network Simulator (BNS), to simulate and analyze the behavior of such systems. The behavior of a hypothetical two gene <it>in vitro </it>transcription-translation reaction network is investigated using the Gillespie exact stochastic algorithm to illustrate some of the factors that influence the analysis and interpretation of these data.</p> <p>Results</p> <p>Specific issues affecting the analysis and interpretation of simulation data are investigated, including: (1) the effect of time interval on data presentation and time-weighted averaging of molecule numbers, (2) effect of time averaging interval on reaction rate analysis, (3) effect of number of simulations on precision of model predictions, and (4) implications of stochastic simulations on optimization procedures.</p> <p>Conclusion</p> <p>The two main factors affecting the analysis of stochastic simulations are: (1) the selection of time intervals to compute or average state variables and (2) the number of simulations generated to evaluate the system behavior.</p

    An integrated epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic twins

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    DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing (MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.Funding support for this project was obtained from the European Research Council (project number 250157) and BGI. The study was also supported by TwinsUK, which is funded by the Wellcome Trust; European Community’s Seventh Framework Programme (FP7/2007-2013); and also receives support from the National Institute for Health Research (NIHR) BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas' NHS Foundation Trust and King’s College London. SNP Genotyping was performed by The Wellcome Trust Sanger Institute and National Eye Institute via NIH/CIDR. M.M. is the holder of Wellcome Trust Senior Investigator Award (Wellcome 098381). T.D.S. is the holder of an ERC Advanced Principal Investigator award (ERC 250157). A.P.M. is a Wellcome Trust Senior Research Fellow in Basic Biomedical Science (grant number WT098017). Skeletal muscle 450k methylation project is supported by European Community's Seventh Framework Programme (FP7/2007-2013) under DEXLIFE project (grant agreement no. HEALTH-F2-2011-279228)
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