35 resultados para copy number variant


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Nitric oxide (NO), produced by endothelial nitric oxide synthase (eNOS), plays important roles in normal vascular homeostasis, and reduced endothelial NO bioactivity is an important feature of vascular disease states. The Glu298Asp (G894T) polymorphic variant of eNOS has been associated with vascular disease, but functional data are lacking. Accordingly, we examined the relationships between NO-mediated endothelial function, the presence of the eNOS Glu298Asp variant, and clinical risk factors for atherosclerosis. Endothelium-dependent vasorelaxations to different agonists were determined in human saphenous veins obtained from patients with coronary artery disease and identified risk factors (n = 104). Patients were genotyped for the eNOS G894T polymorphism. Nitric oxide-mediated endothelial vasorelaxations were highly variable between patients. Reduced vasorelaxations were associated with increased number of clinical risk factors for atherosclerosis (r = - 0.54, P

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We describe a simple theoretical model to investigate the anomalous effects of opacity on spectral line ratios, as previously studied in elements such as Fe XV and Fe XVII. The model developed is general: it is not specific to a particular atomic system, thus giving applicability to a number of coronal and chromospheric plasmas; furthermore, it may be applied to a variety of astrophysically relevant geometries. The analysis is underpinned by geometrical arguments, and we outline a technique for it to be used as a tool for the explicit diagnosis of plasma geometry in distant astrophysical objects.

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Alzheimer's disease (AD) is a progressive neurodegenerative disorder that has been associated, sometimes controversially, with polymorphisms in a number of genes. Recently the butyrylcholinesterase K variant (BCHE K) allele has been shown to act in synergy with the apolipoprotein E epsilon4 (APOE epsilon4) allele to promote risk for AD. Most subsequent replicative studies have been unable to confirm these findings. We have conducted a case-control association study using a clinically well defined group of late onset AD patients (n=175) and age and sex matched control subjects (n=187) from the relatively genetically homogeneous Northern Ireland population to test this association. The BCHE genotypes of patients were found to be significantly different from controls (chi(2)=23.68, df=2, p

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WHIRLBOB, also known as STRIBOBr2, is an AEAD (Authenticated Encryption with Associated Data) algorithm derived from STRIBOBr1 and the Whirlpool hash algorithm. WHIRLBOB/STRIBOBr2 is a second round candidate in the CAESAR competition. As with STRIBOBr1, the reduced-size Sponge design has a strong provable security link with a standardized hash algorithm. The new design utilizes only the LPS or ρ component of Whirlpool in flexibly domain-separated BLNK Sponge mode. The number of rounds is increased from 10 to 12 as a countermeasure against Rebound Distinguishing attacks. The 8 ×8 - bit S-Box used by Whirlpool and WHIRLBOB is constructed from 4 ×4 - bit “MiniBoxes”. We report on fast constant-time Intel SSSE3 and ARM NEON SIMD WHIRLBOB implementations that keep full miniboxes in registers and access them via SIMD shuffles. This is an efficient countermeasure against AES-style cache timing side-channel attacks. Another main advantage of WHIRLBOB over STRIBOBr1 (and most other AEADs) is its greatly reduced implementation footprint on lightweight platforms. On many lower-end microcontrollers the total software footprint of π+BLNK = WHIRLBOB AEAD is less than half a kilobyte. We also report an FPGA implementation that requires 4,946 logic units for a single round of WHIRLBOB, which compares favorably to 7,972 required for Keccak / Keyak on the same target platform. The relatively small S-Box gate count also enables efficient 64-bit bitsliced straight-line implementations. We finally present some discussion and analysis on the relationships between WHIRLBOB, Whirlpool, the Russian GOST Streebog hash, and the recent draft Russian Encryption Standard Kuznyechik.

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Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.