Memorial University of Newfoundland

About: Memorial University of Newfoundland is a education organization based out in St. John's, Newfoundland and Labrador, Canada. It is known for research contribution in the topics: Population & Gadus. The organization has 13818 authors who have published 27785 publications receiving 743594 citations. The organization is also known as: Memorial University & Memorial University of Newfoundland and Labrador.

Epidemiology of cardiovascular disease in chronic renal disease.

Abstract: The risk of cardiovascular disease in patients with chronic renal disease appears to be far greater than in the general population. For example, among patients treated by hemodialysis or peritoneal dialysis, the prevalence of coronary artery disease is approximately 40% and the prevalence of left ventricular hypertrophy is approximately 75%. Cardiovascular mortality has been estimated to be approximately 9% per year. Even after stratification by age, gender, race, and the presence or absence of diabetes, cardiovascular mortality in dialysis patients is 10 to 20 times higher than in the general population. Patients with chronic renal disease should be considered in the highest risk group for subsequent cardiovascular events. Cardiac failure is more common in chronic renal disease patients than in the general population, and is an independent predictor of death in chronic renal disease. Among hemodialysis and peritoneal dialysis patients, the prevalence of cardiac failure is approximately 40%. Both coronary artery disease and left ventricular hypertrophy are risk factors for the development of cardiac failure. In practice, it is difficult to determine whether cardiac failure reflects left ventricular dysfunction or extracellular fluid volume overload. Patients who develop clinical manifestations of cardiac failure should be evaluated for cardiovascular disease.

Efficient algorithms for agglomerative hierarchical clustering methods

Abstract: Whenevern objects are characterized by a matrix of pairwise dissimilarities, they may be clustered by any of a number of sequential, agglomerative, hierarchical, nonoverlapping (SAHN) clustering methods. These SAHN clustering methods are defined by a paradigmatic algorithm that usually requires 0(n 3) time, in the worst case, to cluster the objects. An improved algorithm (Anderberg 1973), while still requiring 0(n 3) worst-case time, can reasonably be expected to exhibit 0(n 2) expected behavior. By contrast, we describe a SAHN clustering algorithm that requires 0(n 2 logn) time in the worst case. When SAHN clustering methods exhibit reasonable space distortion properties, further improvements are possible. We adapt a SAHN clustering algorithm, based on the efficient construction of nearest neighbor chains, to obtain a reasonably general SAHN clustering algorithm that requires in the worst case 0(n 2) time and space. Whenevern objects are characterized byk-tuples of real numbers, they may be clustered by any of a family of centroid SAHN clustering methods. These methods are based on a geometric model in which clusters are represented by points ink-dimensional real space and points being agglomerated are replaced by a single (centroid) point. For this model, we have solved a class of special packing problems involving point-symmetric convex objects and have exploited it to design an efficient centroid clustering algorithm. Specifically, we describe a centroid SAHN clustering algorithm that requires 0(n 2) time, in the worst case, for fixedk and for a family of dissimilarity measures including the Manhattan, Euclidean, Chebychev and all other Minkowski metrics.

The Sulfur-Containing Amino Acids: An Overview

Abstract: Methionine, cysteine, homocysteine, and taurine are the 4 common sulfur-containing amino acids, but only the first 2 are incorporated into proteins. Sulfur belongs to the same group in the periodic table as oxygen but is much less electronegative. This difference accounts for some of the distinctive properties of the sulfur-containing amino acids. Methionine is the initiating amino acid in the synthesis of virtually all eukaryotic proteins; N-formylmethionine serves the same function in prokaryotes. Within proteins, many of the methionine residues are buried in the hydrophobic core, but some, which are exposed, are susceptible to oxidative damage. Cysteine, by virtue of its ability to form disulfide bonds, plays a crucial role in protein structure and in protein-folding pathways. Methionine metabolism begins with its activation to S-adenosylmethionine. This is a cofactor of extraordinary versatility, playing roles in methyl group transfer, 5'-deoxyadenosyl group transfer, polyamine synthesis, ethylene synthesis in plants, and many others. In animals, the great bulk of S-adenosylmethionine is used in methylation reactions. S-Adenosylhomocysteine, which is a product of these methyltransferases, gives rise to homocysteine. Homocysteine may be remethylated to methionine or converted to cysteine by the transsulfuration pathway. Methionine may also be metabolized by a transamination pathway. This pathway, which is significant only at high methionine concentrations, produces a number of toxic endproducts. Cysteine may be converted to such important products as glutathione and taurine. Taurine is present in many tissues at higher concentrations than any of the other amino acids. It is an essential nutrient for cats.

Where are Cultural and Social in Ecosystem Services? A Framework for Constructive Engagement

Abstract: A focus on ecosystem services (ES) is seen as a means for improving decisionmaking. In the research to date, the valuation of the material contributions of ecosystems to human well-being has been emphasized, with less attention to important cultural ES and nonmaterial values. This gap persists because there is no commonly accepted framework for eliciting less tangible values, characterizing their changes, and including them alongside other services in decisionmaking. Here, we develop such a framework for ES research and practice, addressing three challenges: (1) Nonmaterial values are ill suited to characterization using monetary methods; (2) it is difficult to unequivocally link particular changes in socioecological systems to particular changes in cultural benefits; and (3) cultural benefits are associated with many services, not just cultural ES. There is no magic bullet, but our framework may facilitate fuller and more socially acceptable integrations of ES information into planning and management.