42 research outputs found
Candidate gene study of FOXO1, FOXO4, and FOXO6 reveals no association with human longevity in Germans.
No full textHuman longevity and 11p15.5: a study in 1321 centenarians
No full textThe 11p15.5 chromosomal region (2.8Mb) is of particular interest as it encloses five genes (HRAS1, SIRT3, TH, INS and IGF2), the variability of which was found to be associated with life extension by association studies. Mostly important, the above genes are homologous of genes that modulate lifespan in model organisms. We scanned the area in four European sample groups for a total of 1321 centenarians and 1140 younger subjects, who shared with centenarians ethnicity and geographical origin, with a set of 239 SNPs. No significant results (P < 0.05) have been found on the earlier associated loci (ie, TH, IGF2, INS and HRAS1), and this study could not confirm the earlier findings on each of those genes. A meta-analysis was carried out on the SIRT3 SNP data; a total number of 2461 samples were included, but no positive association was found except for one SNP having a significant effect (rs939915). The same meta-analysis approach has been applied to the other 229 markers, and six SNPs have been found significant for the frequent genotype (rs4073591, DEAF1-rs4073590, KRTAP5-6-rs11040489, rs4930001, TSPAN32-rs800140 and rs16928120). This experience, although unable to confirm the earlier findings of the literature, highlights all the common difficulties of such studies in human longevity. Despite the rather negative findings presented here, the results derived from unprecedented studies involving such a large number of centenarians should be disseminated, thus contributing to set up adequate strategies to disentangle complex and likely heterogeneous phenotypes
No or only population-specific effect of PON1 on human longevity: A comprehensive meta-analysis
No full textParaoxonase 1 (PON1) has been suggested as a plausible candidate gene for human longevity due to its modulation of cardiovascular disease risk, by preventing oxidation of atherogenic low-density lipoprotein. The role of the PON1 192 Q/R polymorphism has been analyzed for association with survival at old age in several populations, albeit with controversial results. To reconcile the conflicting evidence, we performed a large association study with two samples of 2357 Germans and 1025 French, respectively. We combined our results with those from seven previous studies in the largest and most comprehensive meta-analysis on PON1 192 Q/R and longevity to-date, to include a total of 9580 individuals. No significant association of PON1 192 Q/R with longevity was observed, for either R allele or carriership. This finding relied on very large sample sizes, is supported by different analysis methods and is therefore considered very robust. Moreover, we have investigated a potential interaction of PON1 192 Q/R with APOE epsilon4 using data from four populations. Whereas a significant result was found in the German sample, this could not be confirmed in the other examined groups. Our large-scale meta-analysis provided no evidence that the PON1 192 Q/R polymorphism is associated with longevity, but this does not exclude the possibility of population-specific effects due to the influence of, and interaction between, different genetic and/or environmental factors (e.g. diet)
Summary Abstract: Measurement of deposited masses by means of a spiral centrifuge with quartz sensors
No full textSoft matter beats hard matter: rupturing of thin metal layers induced by a polymer substrate.
No full textThere is a growing interest on having an integrated electronic functionality over three dimensional large area surfaces for over decade (viz., paper like thin displays on furniture, interconnects, robot sensor skin, intelligent medical bandages or surgical tools etc).[1-4] Flexible polymer substrates sandwiched with electronic circuitry are increasingly in use for developing these applications. Understanding the perturbation of polymer substrate and the deforming behaviour of metallic thin films supposed to be the crucial challenges during the design of deformable electronics to avoid mechanical and electrical failure of the integrated and functionalized structures. Despite significant importance, studying the deformation of nanoscale metallic thin films below 50 nm remains a challenge. In the current investigation, we developed a method to apply optomechanical stress locally at nanoscopric scale to study the deformation of thin metal films of 5–50 nm. Further, the method also useful to probe the molecular level forces developed during the mass transport of the photosensitive polymer films under light irradiation. It is well known that the photosensitive polymer thin films containing azo-benzene groups, reacts strongly to light irradiation. During the irradiation with light interference pattern, photosensitive polymer film topography deforms and result in the formation of surface relief grating (SRG).[5,6] SRG formation is a suitable phenomenon due the mass transport of polymer occurring in regular and periodic fashion across the polymer surface to apply optomechanical stress locally. Metallic films with a thickness varying between 5 to 50 nm are deposited on photosensitive polymer films and under suitable irradiation conditions, we observed and studied an interesting regular and irregular metallic film deformation and rupturing behaviour at different interfering beam conditions (±45 and RL) and the metal film thicknesses.[7] We also studied the electrical conductivity behaviour of such deformed conductive metal films REFERENCES. [1]. V. J. Lumelsky, M. S. Shur, and S. Wagner, IEEE Sensors J. 1, pp. 41–51 (2001).[2]. J. Jones, S.P. Lacour and S. Wagner. MRS Proceedings, 863, B10.9 (2005).[3]. I. Sample, New Scientist 170, 23 (2001)[4]. J. Engel, J. Chen, C. Liu, B. R. Flachsbart, J. C. Selby, and M. A. Shannon, Mater. Res. Soc. Symp. Proc. 736 , pp. D.4.5.1-D4.5.6 (2003).[5]. N. S. Yadavalli, and S. Santer. J Appl. Phys. 113, 224340 (2013).[6]. N. S. Yadavalli, M. Saphiannikova, N. Lomadze, L. M. Goldenberg, and S. Santer. Appl. Phys. A 113, 263-272 (2013)[7]. N. S. Yadavalli, F. Linde, A. Kopyshev and S. Santer. ACS Appl. Mater. Interfaces 5, 7743-7747 (2013)
Genetic Variation in the CYP2C Monooxygenase Enzyme Subfamily Shows No Association With Longevity in a German Population
No full textPhotoelasticity based dynamic tactile sensor
No full textThe paper presents design, construction and testing of a photoelasticity based dynamic sensor which is capable of detecting slip as well as providing normal force information. Starting with investigations into mechanism of slip, an approximate model of the sensor has been developed. This model explains the design improvements necessary to provide continuous signal during slip. The theoretical model also helps identify various sensor parameters to characterize the sensor. The developed sensor has been compared with other existing sensors and the experimental results from the sensor have been discussed for the type of signal the sensor provides. The sensor is also calibrated for normal force. The sensor is novel in the sense that it offers dynamic slip signal as well as the normal force information from a single contact location, it provides continuous signal during slip, and it has small size which can be easily incorporated into robotic fingers. The sensor has an edge over other existing sensors that its design is simple yet it provides strong signals which are largely unaffected by external disturbances. Copyright © 2005 by ASME
A feed forward neural network approach for matrix computations
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A new neural network approach for performing matrix computations is presented. The idea of this approach is to construct a feed-forward neural network (FNN) and then train it by matching a desired set of patterns. The solution of the problem is the converged weight of the FNN. Accordingly, unlike the conventional FNN research that concentrates on external properties (mappings) of the networks, this study concentrates on the internal properties (weights) of the network. The present network is linear and its weights are usually strongly constrained; hence, complicated overlapped network needs to be construct. It should be noticed, however, that the present approach depends highly on the training algorithm of the FNN. Unfortunately, the available training methods; such as, the original Back-propagation (BP) algorithm, encounter many deficiencies when applied to matrix algebra problems; e. g., slow convergence due to improper choice of learning rates (LR). Thus, this study will focus on the development of new efficient and accurate FNN training methods. One improvement suggested to alleviate the problem of LR choice is the use of a line search with steepest descent method; namely, bracketing with golden section method. This provides an optimal LR as training progresses. Another improvement proposed in this study is the use of conjugate gradient (CG) methods to speed up the training process of the neural network. The computational feasibility of these methods is assessed on two matrix problems; namely, the LU-decomposition of both band and square ill-conditioned unsymmetric matrices and the inversion of square ill-conditioned unsymmetric matrices. In this study, two performance indexes have been considered; namely, learning speed and convergence accuracy. Extensive computer simulations have been carried out using the following training methods: steepest descent with line search (SDLS) method, conventional back propagation (BP) algorithm, and conjugate gradient (CG) methods; specifically, Fletcher Reeves conjugate gradient (CGFR) method and Polak Ribiere conjugate gradient (CGPR) method. The performance comparisons between these minimization methods have demonstrated that the CG training methods give better convergence accuracy and are by far the superior with respect to learning time; they offer speed-ups of anything between 3 and 4 over SDLS depending on the severity of the error goal chosen and the size of the problem. Furthermore, when using Powell's restart criteria with the CG methods, the problem of wrong convergence directions usually encountered in pure CG learning methods is alleviated. In general, CG methods with restarts have shown the best performance among all other methods in training the FNN for LU-decomposition and matrix inversion. Consequently, it is concluded that CG methods are good candidates for training FNN of matrix computations, in particular, Polak-Ribidre conjugate gradient method with Powell's restart criteria
EFFECTS OF DOBUTAMINE ON HEMODYNAMICS AND LEFT VENTRICULAR PERFORMANCE IN THE EARLY POST CARDIOPULMONARY BYPASS PERIOD
No full textLow copy numbers of complement C4 and homozygous deficiency of C4A may predispose to severe disease and earlier disease onset in patients with systemic lupus erythematosus
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