6 research outputs found

    Audio on the GPU: Real-Time Time Domain Audio Convolution on Graphics Cards

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    The architecture of CPUs has shifted in recent years from increased speed to more cores on the chips. With this change, more developers are focusing on parallelism; however, many developers have not taken advantage of a common hardware component that specializes in parallel applications: the Graphics Processing Unit (GPU). By writing code to execute on GPUs, developers have been able to gain increased performance over the traditional CPU in many problem domains, including signal processing. Time domain convolution is an important component of signal processing. Currently, the fastest process to perform convolution is frequency domain multiplication. In addition to being more complex, inconsistencies such as missing data are difficult to solve in the frequency domain. It has been shown that executing frequency domain multiplication on GPUs improves performance, but there is no research for time domain convolution on GPUs. This thesis provides two algorithms that implement time domain convolution on GPUs: one algorithm is for computing convolution all at once and another is designed for real time computation and playing the results. The results from this thesis indicate that using the GPU significantly reduces processing time for time domain convolution

    Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

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    Bi-allelic Loss-of-Function CACNA1B Mutations in Progressive Epilepsy-Dyskinesia.

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    The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment.MAK is funded by an NIHR Research Professorship and receives funding from the Wellcome Trust, Great Ormond Street Children's Hospital Charity, and Rosetrees Trust. E.M. received funding from the Rosetrees Trust (CD-A53) and Great Ormond Street Hospital Children's Charity. K.G. received funding from Temple Street Foundation. A.M. is funded by Great Ormond Street Hospital, the National Institute for Health Research (NIHR), and Biomedical Research Centre. F.L.R. and D.G. are funded by Cambridge Biomedical Research Centre. K.C. and A.S.J. are funded by NIHR Bioresource for Rare Diseases. The DDD Study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (grant number WT098051). We acknowledge support from the UK Department of Health via the NIHR comprehensive Biomedical Research Centre award to Guy's and St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. This research was also supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. J.H.C. is in receipt of an NIHR Senior Investigator Award. The research team acknowledges the support of the NIHR through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health, or Wellcome Trust. E.R.M. acknowledges support from NIHR Cambridge Biomedical Research Centre, an NIHR Senior Investigator Award, and the University of Cambridge has received salary support in respect of E.R.M. from the NHS in the East of England through the Clinical Academic Reserve. I.E.S. is supported by the National Health and Medical Research Council of Australia (Program Grant and Practitioner Fellowship)

    Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

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    International audienceGenetic roots of multiple sclerosis The genetics underlying who develops multiple sclerosis (MS) have been difficult to work out. Examining more than 47,000 cases and 68,000 controls with multiple genome-wide association studies, the International Multiple Sclerosis Genetics Consortium identified more than 200 risk loci in MS (see the Perspective by Briggs). Focusing on the best candidate genes, including a model of the major histocompatibility complex region, the authors identified statistically independent effects at the genome level. Gene expression studies detected that every major immune cell type is enriched for MS susceptibility genes and that MS risk variants are enriched in brain-resident immune cells, especially microglia. Up to 48% of the genetic contribution of MS can be explained through this analysis. Science , this issue p. eaav7188 ; see also p. 138

    Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

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    INTRODUCTION: Multiple sclerosis (MS) is an inflammatory and degenerative disease of the central nervous system (CNS) that often presents in young adults. Over the past decade, certain elements of the genetic architecture of susceptibility have gradually emerged, but most of the genetic risk for MS remained unknown. RATIONALE: Earlier versions of the MS genetic map had highlighted the role of the adaptive arm of the immune system, implicating multiple different T cell subsets. We expanded our knowledge of MS susceptibility by performing a genetic association study in MS that leveraged genotype data from 47,429 MS cases and 68,374 control subjects. We enhanced this analysis with an in-depth and comprehensive evaluation of the functional impact of the susceptibility variants that we uncovered. RESULTS: We identified 233 statistically independent associations with MS susceptibility that are genome-wide significant. The major histocompatibility complex (MHC) contains 32 of these associations, and one, the first MS locus on a sex chromosome, is found in chromosome X. The remaining 200 associations are found in the autosomal non-MHC genome. Our genome-wide partitioning approach and large-scale replication effort allowed the evaluation of other variants that did not meet our strict threshold of significance, such as 416 variants that had evidence of statistical replication but did not reach the level of genome-wide statistical significance. Many of these loci are likely to be true susceptibility loci. The genome-wide and suggestive effects jointly explain ~48% of the estimated heritability for MS. Using atlases of gene expression patterns and epigenomic features, we documented that enrichment for MS susceptibility loci was apparent in many different immune cell types and tissues, whereas there was an absence of enrichment in tissue-level brain profiles. We extended the annotation analyses by analyzing new data generated from human induced pluripotent stem cell–derived neurons as well as from purified primary human astrocytes and microglia, observing that enrichment for MS genes is seen in human microglia, the resident immune cells of the brain, but not in astrocytes or neurons. Further, we have characterized the functional consequences of many MS susceptibility variants by identifying those that influence the expression of nearby genes in immune cells or brain. Last, we applied an ensemble of methods to prioritize 551 putative MS susceptibility genes that may be the target of the MS variants that meet a threshold of genome-wide significance. This extensive list of MS susceptibility genes expands our knowledge more than twofold and highlights processes relating to the development, maturation, and terminal differentiation of B, T, natural killer, and myeloid cells that may contribute to the onset of MS. These analyses focus our attention on a number of different cells in which the function of MS variants should be further investigated. Using reference protein-protein interaction maps, these MS genes can also be assembled into 13 communities of genes encoding proteins that interact with one another; this higher-order architecture begins to assemble groups of susceptibility variants whose functional consequences may converge on certain protein complexes that can be prioritized for further evaluation as targets for MS prevention strategies. CONCLUSION: We report a detailed genetic and genomic map of MS susceptibility, one that explains almost half of this disease’s heritability. We highlight the importance of several cells of the peripheral and brain resident immune systems—implicating both the adaptive and innate arms—in the translation of MS genetic risk into an auto-immune inflammatory process that targets the CNS and triggers a neurodegenerative cascade. In particular, the myeloid component highlights a possible role for microglia that requires further investigation, and the B cell component connects to the narrative of effective B cell–directed therapies in MS. These insights set the stage for a new generation of functional studies to uncover the sequence of molecular events that lead to disease onset. This perspective on the trajectory of disease onset will lay the foundation for developing primary prevention strategies that mitigate the risk of developing MS

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