The deleterious effects of a disrupted copper metabolism are illustrated by hereditary diseases caused by mutations in the genes coding for the copper transporters ATP7A and ATP7B. Menkes disease, involving ATP7A, is a fatal neurodegenerative disorder of copper deficiency. Mutations in ATP7B lead to Wilson disease, which is characterized by a predominantly hepatic copper accumulation. The low incidence and the phenotypic variability of human copper toxicosis hamper identification of causal genes or modifier genes involved in the disease pathogenesis. The Labrador retriever was recently characterized as a new canine model for copper toxicosis. Purebred dogs have reduced genetic variability, which facilitates identification of genes involved in complex heritable traits that might influence phenotype in both humans and dogs. We performed a genome-wide association study in 235 Labrador retrievers and identified two chromosome regions containing ATP7A and ATP7B that were associated with variation in hepatic copper levels. DNA sequence analysis identified missense mutations in each gene. The amino acid substitution ATP7B:p.Arg1453Gln was associated with copper accumulation, whereas the amino acid substitution ATP7A:p.Thr327Ile partly protected against copper accumulation. Confocal microscopy indicated that aberrant copper metabolism upon expression of the ATP7B variant occurred because of mis-localization of the protein in the endoplasmic reticulum. Dermal fibroblasts derived from ATP7A:p.Thr327Ile dogs showed copper accumulation and delayed excretion. We identified the Labrador retriever as the first natural, non-rodent model for ATP7B-associated copper toxicosis. Attenuation of copper accumulation by the ATP7A mutation sheds an interesting light on the interplay of copper transporters in body copper homeostasis and warrants a thorough investigation of ATP7A as a modifier gene in copper-metabolism disorders. The identification of two new functional variants in ATP7A and ATP7B contributes to the biological understanding of protein function, with relevance for future development of therapy.
While many works have been devoted to service matchmaking and modeling nonfunctional properties, the problem of matching service requests to offers in an optimal way has not yet been extensively studied. In this paper we formalize three kinds of optimal service selection problems, based on different criteria. Then we study their complexity and implement solutions. We prove that one-time costs make the optimal selection problem computationally hard; in the absence of these costs the problem can be solved in polynomial time. We designed and implemented both exact and heuristic (suboptimal) algorithms for the hard case, and carried out a preliminary experimental evaluation with interesting results.
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimization. It is a multi-start or iterative process, in which each GRASP iteration consists of two phases, a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Since 1989, numerous papers on the basic aspects of GRASP, as well as enhancements to the basic metaheuristic, have appeared in the literature. GRASP has been applied to a wide range of combinatorial optimization problems, ranging from scheduling and routing to drawing and turbine balancing. This is the second of two papers with an annotated bibliography of the GRASP literature from 1989 to 2008. In the companion paper, algorithmic aspects of GRASP are surveyed. In this paper, we cover the literature where GRASP is applied to scheduling,
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimization. It is a multi-start or iterative process, in which each GRASP iteration consists of two phases, a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Since 1989, numerous papers on the basic aspects of GRASP, as well as enhancements to the basic metaheuristic have appeared in the literature. GRASP has been applied to a wide range of combinatorial optimization problems, ranging from scheduling and routing to drawing and turbine balancing. This is the first of two papers with an annotated bibliography of the GRASP literature from 1989 to 2008. This paper covers algorithmic aspects of GRASP
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