Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Metabolism of plasma cholesterol and lipoprotein parameters are related to a higher degree of insulin sensitivity in high HDL-C healthy normal weight subjects

Abstract Background We have searched if plasma high density lipoprotein-cholesterol (HDL-C) concentration interferes simultaneously with whole-body cholesterol metabolism and insulin sensitivity in normal weight healthy adult subjects. Methods We have measured the activities of several plasma components that are critically influenced by insulin and that control lipoprotein metabolism in subjects with low and high HDL-C concentrations. These parameters included cholesteryl ester transfer protein (CETP), phospholipid transfer protein (PLTP), lecithin cholesterol acyl transferase (LCAT), post-heparin lipoprotein lipase (LPL), hepatic lipase (HL), pre-beta-1HDL, and plasma sterol markers of cholesterol synthesis and intestinal absorption. Results In the high-HDL-C group, we found lower plasma concentrations of triglycerides, alanine aminotransferase, insulin, HOMA-IR index, activities of LCAT and HL compared with the low HDL-C group; additionally, we found higher activity of LPL and pre-beta-1HDL concentration in the high-HDL-C group. There were no differences in the plasma CETP and PLTP activities. Conclusions These findings indicate that in healthy hyperalphalipoproteinemia subjects, several parameters that control the metabolism of plasma cholesterol and lipoproteins are related to a higher degree of insulin sensitivity.

Red and infrared light distribution in blood.

Low level laser therapy (LLLT) is used in several applications, including the reduction of inflammatory processes. It might be used to prevent the systemic inflammatory response syndrome (SIRS), which some patients develop after cardiopulmonary bypass (CPB) surgery. The objectives of this study were to investigate light distribution inside blood, in order to implement the LLLT during CPB, and, through this study, to determine the best wavelength and the best way to perform the treatment. The blood, diluted to the same conditions of CPB procedure was contained inside a cuvette and an optical fiber was used to collect the scattered light. Two wavelengths were used: 632.8 nm and 820 nm. Light distribution in blood inside CPB tubes was also evaluated. Compared to the 820 nm light, the 632.8 nm light is scattered further away from the laser beam, turning it possible that a bigger volume of blood be treated. The blood should be illuminated through the smallest diameter CPB tube, using at least four distinct points around it, in only one cross section, because the blood is kept passing through the tube all the time and the whole volume will be illuminated.