Human Soluble platelet-selectin ELISA kit

A self-organizing migrating genetic algorithm(C-SOMGA) is developed for animal diet formulation. This paper presents animal diet formulation using stochastic and genetic algorithm. Bi-objective models for cost minimization and shelf life maximization are developed. These objectives are achieved by combination of stochastic programming and C-SOMGA. Stochastic programming is used to introduce nutrient variability for animal diet Self-organizing migrating genetic algorithm provides exact and quick solution and presents an innovative approach towards successful application of soli computing technique in the area of animal diet formulation.

The association between the concentration/activity of selenium/selenoproteins in plasma and type 2 diabetes mellitus is still a matter of debate. This cross-sectional pilot study evaluates whether patients with diabetes present a different plasma selenoproteins status than a healthy control group and examines whether the introduction of clinical parameters allows the detection of correlations and further grouping criteria. For this purpose, the levels of plasma glutathione peroxidase (GPx), selenoprotein P (SelP), and seleno-albumin (SeAlb) present in 40 patients affected by type 2 diabetes mellitus were determined simultaneously and accurately by a newly developed analytical method. The results show that patients with diabetes demonstrate significantly lower levels of GPx and SeAlb with respect to healthy subjects (11 +/- 3 ng/mL and 9 +/- 2 ng/mL vs 18 +/- 8 ng/mL and 11 +/- 2 ng/mL, respectively). Significant negative correlations were revealed among GPx, SeAlb, and clinical parameters including fasting plasma glucose, hemoglobin A1c, and the albumin-to-creatinine ratio. Our findings suggest an association between the individual selenoproteins concentration and the presence of diabetes, including associated clinical parameters. It currently cannot be ascertained whether the altered selenoproteins status is a consequence or a causative factor for diabetes. This study demonstrates the potential of a method for individual selenoproteins determination for investigating the biochemical relationship between selenium and diabetes. (Translational Research 2010;156:242-250)