427 research outputs found

    Blood analogue for thrombogenicity assessment

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    The chief problem at present with artificial heart valves is their thrombogenicity, which requires the recipients to undergo dangerous anticoagulant therapy, which is not always successful. The present accepted method of testing valve thrombogenicity is implantation in experimental animals. This technique is unsatisfactory because of its high cost, the lack of control, the length of the experiments and because differences between the blood of various species render the results of dubious value. A more fundamental approach to the problem based on fluid mechanics'fails because of the complexity of the situation and because of the opposed effects of a given fluid mechanical phenomenon. The in vitro use of blood is not possible due to the need for a single pass system to avoid recirculating clots, necessitating some thirty gallons of blood for a run of only one hour. An analogue method using a fluid which does not have the disadvantages of the alternatives described above, therefore, seems worth exploring. Rennetized milk is a possible fluid for such a purpose and experiments were performed to ascertain whether it behaves in a manner analogous to blood in respect of its essential clotting properties. The first indications from the Lee-White inverted test tube test were very promising with milk behaving in a manner apparently identical to blood. Further experiments using the Stagnation Point Flow Chamber showed that there was a striking similarity in the microscopic appearance of the deposits forming at and around the stagnation point when a jet of milk/blood impinges normally onto a glass slide. A subsequent experiment, in which the fluids are pumped through a mesh, revealed that the sequence of clot growth as measured by the pressure variation upstream of the mesh is the same for both fluids. Finally, full scale tests of the clotting propensity of various heart valves were performed using an artificial heart system, which showed that the location and appearance of the clots forming on the valves with rennetized milk were similar to those found in humans and that the results were reproducible. It is, therefore, apparent that rennetized milk shows great potential as an analogue for the flow related clotting of blood and can be used for testing artificial heart valves provided care is taken in the choice of materials for construction

    Cosmogenic ^(10)Be and ^(36)Cl geochronology of offset alluvial fans along the northern Death Valley fault zone: Implications for transient strain in the eastern California shear zone

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    The northern Death Valley fault zone (NDVFZ) has long been recognized as a major right-lateral strike-slip fault in the eastern California shear zone (ECSZ). However, its geologic slip rate has been difficult to determine. Using high-resolution digital topographic imagery and terrestrial cosmogenic nuclide dating, we present the first geochronologically determined slip rate for the NDVFZ. Our study focuses on the Red Wall Canyon alluvial fan, which exposes clean dextral offsets of seven channels. Analysis of airborne laser swath mapping data indicates ∼297 ± 9 m of right-lateral displacement on the fault system since the late Pleistocene. In situ terrestrial cosmogenic ^(10)Be and ^(36)Cl geochronology was used to date the Red Wall Canyon fan and a second, correlative fan also cut by the fault. Beryllium 10 dates from large cobbles and boulders provide a maximum age of 70 +22/−20 ka for the offset landforms. The minimum age of the alluvial fan deposits based on ^(36)Cl depth profiles is 63 ± 8 ka. Combining the offset measurement with the cosmogenic ^(10)Be date yields a geologic fault slip rate of 4.2 +1.9/−1.1 mm yr^(−1), whereas the ^(36)Cl data indicate 4.7 +0.9/−0.6 mm yr^(−1) of slip. Summing these slip rates with known rates on the Owens Valley, Hunter Mountain, and Stateline faults at similar latitudes suggests a total geologic slip rate across the northern ECSZ of ∼8.5 to 10 mm yr^(−1). This rate is commensurate with the overall geodetic rate and implies that the apparent discrepancy between geologic and geodetic data observed in the Mojave section of the ECSZ does not extend north of the Garlock fault. Although the overall geodetic rates are similar, the best estimates based on geology predict higher strain rates in the eastern part of the ECSZ than to the west, whereas the observed geodetic strain is relatively constant

    Fine-mapping reveals novel alternative splicing of the dopamine transporter

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    Center for Human Genetic Research, Massachusetts General Hospital and Department of Neurology, Harvard Medical School, Harvard University, Boston, Massachusetts.Graduate Program in Biology and Biomedical Science, Yale University, New Haven, Connecticut.The dopamine transporter gene (, ) has been implicated in the pathogenesis of numerous psychiatric and neurodevelopmental disorders, including schizophrenia (SZ). We previously detected association between SZ and intronic variants that replicated in two independent Caucasian samples, but had no obvious function. In follow-up analyses, we sequenced the coding and intronic regions of to identify complete linkage disequilibrium patterns of common variations. We genotyped 78 polymorphisms, narrowing the potentially causal region to two correlated clusters of associated SNPs localized predominantly to introns 3 and 4. Our computational analysis of these intronic regions predicted a novel cassette exon within intron 3, designated E3b, which is conserved among primates. We confirmed alternative splicing of E3b in post-mortem human substantia nigra (SN). As E3b introduces multiple in-frame stop codons, the open reading frame is truncated and the spliced product may undergo nonsense mediated decay. Thus, factors that increase E3b splicing could reduce the amount of unspliced product available for translation. Observations consistent with this prediction were made using cellular assays and in post-mortem human SN. In mini-gene constructs, the extent of splicing is also influenced by at least two common haplotypes, so the alternative splicing was evaluated in relation to SZ risk. Meta-analyses across genome-wide association studies did not support the initial associations and further post-mortem studies did not suggest case-control differences in splicing. These studies do not provide a compelling link to schizophrenia. However, the impact of the alternative splicing on other neuropsychiatric disorders should be investigated. © 2010 Wiley-Liss, Inc

    Creation of an Open-Access, Mutation-Defined Fibroblast Resource for Neurological Disease Research

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    Our understanding of the molecular mechanisms of many neurological disorders has been greatly enhanced by the discovery of mutations in genes linked to familial forms of these diseases. These have facilitated the generation of cell and animal models that can be used to understand the underlying molecular pathology. Recently, there has been a surge of interest in the use of patient-derived cells, due to the development of induced pluripotent stem cells and their subsequent differentiation into neurons and glia. Access to patient cell lines carrying the relevant mutations is a limiting factor for many centres wishing to pursue this research. We have therefore generated an open-access collection of fibroblast lines from patients carrying mutations linked to neurological disease. These cell lines have been deposited in the National Institute for Neurological Disorders and Stroke (NINDS) Repository at the Coriell Institute for Medical Research and can be requested by any research group for use in in vitro disease modelling. There are currently 71 mutation-defined cell lines available for request from a wide range of neurological disorders and this collection will be continually expanded. This represents a significant resource that will advance the use of patient cells as disease models by the scientific community

    Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

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    The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

    A framework for human microbiome research

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    A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

    Structure, function and diversity of the healthy human microbiome

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    Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

    Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.

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    Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Variant annotation was supported by software resources provided via the Caché Campus program of the InterSystems GmbH to Alexander Teumer

    Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

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    Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression
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