The Proteomic Code: a molecular recognition code for proteins

<p>Abstract</p> <p>Background</p> <p>The Proteomic Code is a set of rules by which information in genetic material is transferred into the physico-chemical properties of amino acids. It determines how individual amino acids interact with each other during folding and in specific protein-protein interactions. The Proteomic Code is part of the redundant Genetic Code.</p> <p>Review</p> <p>The 25-year-old history of this concept is reviewed from the first independent suggestions by Biro and Mekler, through the works of Blalock, Root-Bernstein, Siemion, Miller and others, followed by the discovery of a Common Periodic Table of Codons and Nucleic Acids in 2003 and culminating in the recent conceptualization of partial complementary coding of interacting amino acids as well as the theory of the nucleic acid-assisted protein folding.</p> <p>Methods and conclusions</p> <p>A novel cloning method for the design and production of specific, high-affinity-reacting proteins (SHARP) is presented. This method is based on the concept of proteomic codes and is suitable for large-scale, industrial production of specifically interacting peptides.</p

Visualizing Rank Deficient Models: A Row Equation Geometry of Rank Deficient Matrices and Constrained-Regression

Situations often arise in which the matrix of independent variables is not of full column rank. That is, there are one or more linear dependencies among the independent variables. This paper covers in detail the situation in which the rank is one less than full column rank and extends this coverage to include cases of even greater rank deficiency. The emphasis is on the row geometry of the solutions based on the normal equations. The author shows geometrically how constrained-regression/generalized-inverses work in this situation to provide a solution in the face of rank deficiency

A Simplified Method to Distinguish Farmed (Salmo salar) from Wild Salmon: Fatty Acid Ratios Versus Astaxanthin Chiral Isomers

Mislabeling of farmed and wild salmon sold in markets has been reported. Since the fatty acid content of fish may influence human health and thus consumer behavior, a simplified method to identify wild and farmed salmon is necessary. Several studies have demonstrated differences in lipid profiles between farmed and wild salmon but no data exists validating these differences with government-approved methods to accurately identify the origin of these fish. Current methods are both expensive and complicated, using highly specialized equipment not commonly available. Therefore, we developed a testing protocol using gas chromatography (GC), to determine the origin of salmon using fatty acid profiles. We also compared the GC method with the currently approved FDA (United States Food and Drug Administration) technique that uses analysis of carotenoid optical isomers and found 100% agreement. Statistical validation (n = 30) was obtained showing elevated 18:2n-6 (z = 4.56; P = 0.0001) and decreased 20:1n-9 (z = 1.79; P = 0.07) in farmed samples. The method is suitable for wide adaptation because fatty acid methyl ester analysis is a well-established procedure in labs that conduct analysis of lipid composition and food constituents. GC analysis for determining the origin of North American salmon compared favorably with the astaxanthin isomer technique used by the FDA and showed that the fatty acid 18:2n-6 was the key indicator associated with the origin of these salmon

Assessing the context of health care utilization in Ecuador: A spatial and multilevel analysis

<p>Abstract</p> <p>Background</p> <p>There are few studies that have analyzed the context of health care utilization, particularly in Latin America. This study examines the context of utilization of health services in Ecuador; focusing on the relationship between provision of services and use of both preventive and curative services.</p> <p>Methods</p> <p>This study is cross-sectional and analyzes data from the 2004 National Demographic and Maternal & Child Health dataset. Provider variables come from the Ecuadorian System of Social Indicators (SIISE). Global Moran's I statistic is used to assess spatial autocorrelation of the provider variables. Multilevel modeling is used for the simultaneous analysis of provision of services at the province-level with use of services at the individual level.</p> <p>Results</p> <p>Spatial analysis indicates no significant differences in the density of health care providers among Ecuadorian provinces. After adjusting for various predisposing, enabling, need factors and interaction terms, density of public practice health personnel was positively associated with use of preventive care, particularly among rural households. On the other hand, density of private practice physicians was positively associated with use of curative care, particularly among urban households.</p> <p>Conclusions</p> <p>There are significant public/private, urban/rural gaps in provision of services in Ecuador; which in turn affect people's use of services. It is necessary to strengthen the public health care delivery system (which includes addressing distribution of health workers) and national health information systems. These efforts could improve access to health care, and inform the civil society and policymakers on the advances of health care reform.</p

Predation risk and foraging behavior of the hoary marmot in Alaska

I observed hoary marmots for three field seasons to determine how the distribution of food and the risk of predation influenced marmots' foraging behavior. I quantified the amount of time Marmota caligata foraged in different patches of alpine meadows and assessed the distribution and abundance of vegetation eaten by marmots in these meadows. Because marmots dig burrows and run to them when attacked by predators, marmot-toburrow distance provided an index of predation risk that could be specified for different meadow patches.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46873/1/265_2004_Article_BF00292992.pd