Pseudoxanthoma elasticum (PXE) is a genetic disorder associated to mutations in the ABCC6 gene; however, the pathogenetic mechanisms leading to elastic fibre calcifications and to clinical manifestations are still unknown. Dermal fibroblasts, directly involved in the production of the extracellular milieu, have been isolated from healthy subjects and from patients affected by PXE, cultured in vitro and characterized for their ability to produce reactive oxygen species, for structural and functional properties of their cell membranes, for changes in their protein profile. Data demonstrate that oxidative stress has profound and endurable consequences on PXE fibroblast phenotype being responsible for: reduced levels of global DNA methylation, increased amount of carbonylated proteins and of lipid peroxidation products, altered structural properties of cell membranes, modified protein expression. Data shed new light on the pathogenetic pathways in PXE, by identifying a network of proteins affecting elastic fibre calcification through inefficient vitamin K recycling, and highlight the role of differentially expressed proteins as targets for validating the efficacy of future therapeutic strategies aiming to delay and/or revert the pathologic phenotype of PXE fibroblasts. Moreover, data open new perspectives for investigating PXE-like phenotypes in the absence of ABCC6 mutations. 相似文献
Stepwise multiple linear regression (SMLR) and principal components regression (PCR) have been used to predict the percentages of cows', goats' and ewes' milk in Iberico cheese, using the results obtained by electrophoretic analysis (PAGE and IEF) of whey proteins, using standard cheeses. Similar predictions of the percentages of milks from the three species were obtained when either SMLR or PCR were applied to the electrophoretic data, i.e. the optical intensity of the electrophoretic bands (PAGE or IEF) of the whey proteins. The root mean square error of prediction in cross-validation (RMSEPCV) was lower than 4% in all cases. 相似文献
Magnetic Resonance Materials in Physics, Biology and Medicine - Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small... 相似文献
Cloud computing is becoming a very popular form of distributed computing, in which digital resources are shared via the Internet. The user is provided with an overview of many available resources. Cloud providers want to get the most out of their resources, and users are inclined to pay less for better performance. Task scheduling is one of the most important aspects of cloud computing. In order to achieve high performance from cloud computing systems, tasks need to be scheduled for processing by appropriate computing resources. The large search space of this issue makes it an NP-hard problem, and more random search methods are required to solve this problem. Multiple solutions have been proposed with several algorithms to solve this problem until now. This paper presents a hybrid algorithm called GSAGA to solve the Task Scheduling Problem (TSP) in cloud computing. Although it has a high ability to search the problem space, the Genetic Algorithm (GA) performs poorly in terms of stability and local search. It is therefore possible to create a stable algorithm by combining the general search capacities of the GA with the Gravitational Search Algorithm (GSA). Our experimental results indicate that the proposed algorithm can solve the problem with higher efficiency compared with the state-of-the-art.
Software Quality Journal - The number of electronic control units (ECU) installed in vehicles is increasingly high. Manufacturers must improve the software quality and reduce cost by proposing... 相似文献
Machine Learning - Machine Learning studies often involve a series of computational experiments in which the predictive performance of multiple models are compared across one or more datasets. The... 相似文献
This paper is a contribution to the prediction of edge fracture behavior using uncoupled ductile fracture models. A fully integrated simulation framework for the edge fracture prediction is proposed with the shear-induced pre-damage considered. User-defined material subroutines are coded with uncoupled ductile fracture models (Lou-Huh, Oh, Brozzo) incorporated, which are calibrated using the fracture strains of various loading paths. A series of 3D numerical simulations are performed and compared with the results of hole-expansion tests. The effects of pre-damage field and fracture models are analyzed and discussed.
In the steel industry, the iron making system deals with large quantities of materials and energy and so it can play a critical role in reducing emissions and production costs. More specifically, excess by-product gases should be used for electricity generation; otherwise, they lead to pollution. A life cycle analysis is performed to compare the environmental impact of an iron making system with a combined cycle power plant (CCPP), to a system producing the same amount of electricity in a coal power plant. The results for a Chinese steel plant show a 33% reduction in the energy conservation and emission reduction potential for the CCPP system, which is thus more environmentally friendly. A mathematical programming formulation is then proposed for optimal scheduling. It incorporates key technological constraints and is sensitive to hourly changing electricity prices. The outcome is a 19% increase in revenue from electricity sales compared to a schedule that does not dynamically adjust to the price profile. The results also show that emissions from by-product gases can be avoided completely. The paper ends with a sensitivity analysis to evaluate the impact of changes in product demand, gas storage and CCPP capacity, and emission cost. 相似文献