No abstract

Recent studies have shown that heat shock proteins and trehalose synthesis are important factors in the thermotolerance of the fission yeast Schizosaccharomyces pombe. We examined the effects of trehalose-6-phosphate (trehalose-6P) synthase overexpression on resistance to several stresses in cells of S. pombetransformed with a plasmid bearing the tps1 gene, which codes for trehalose-6P synthase, under the control of the strong thiamine-repressible promoter. Upon induction of trehalose-6P synthase, the elevated levels of intracellular trehalose correlated not only with increased tolerance to heat shock but also with resistance to freezing and thawing, dehydration, osmostress, and toxic levels of ethanol, indicating that trehalose may be the stress metabolite underlying the overlap in induced tolerance to these stresses. Among the isogenic strains transformed with this construct, one in which the gene coding for the trehalose-hydrolyzing enzyme, neutral trehalase, was disrupted accumulated trehalose to a greater extent and was more resistant to the above stresses. Increased trehalose concentration is thus a major determinant of the general stress protection response in S. pombe.

Nonlinear biobjective optimization, Efficient set, Outer approximation, Interval analysis, Branch-and-bound method, Discarding tests, Continuous location,

Continuous location, Competition, Centroid problem, Stackelberg problem, Evolutionary algorithms,

In this paper we empirically analyze several algorithms for solving a Huff-like competitive location and design model for profit maximization in the plane. In particular, an exact interval branch-and-bound method and a multistart heuristic already proposed in the literature are compared with UEGO (Universal Evolutionary Global Optimizer), a recent evolutionary algorithm. Both the multistart heuristic and UEGO use a Weiszfeld-like algorithm as local search procedure. The computational study shows that UEGO is superior to the multistart heuristic, and that by properly fine-tuning its parameters it usually (in the computational study, always) find the global optimal solution, and this in much less time than the interval branch-and-bound method. Furthermore, UEGO can solve much larger problems than the interval method.