| Περίληψη: | High-density lipoproteins are small (diameter of 8 to 10 nanometers) complex particles consisting of a variety of lipid components and apolipoproteins with the transportation of excess cholesterol from peripheral cells to the liver for degradation being their main function. Apolipoproteins and lipids are important for the structural formation of the lipoprotein particles and they possess a key role in lipoprotein metabolism and interaction. With the use of statistical methods, lipids such as phospholipids, fatty acids, triglycerides and cholesterol and apolipoproteins such as APOA1, APOE3, and APOC3 were analyzed in an effort to understand the underlying association between them and three major biological functions of HDL: 1) Reverse Cholesterol Transfer, 2) Antioxidant Function, 3) Anti-inflammatory Function. These three HDL functional properties are directly associated with the risk of atherosclerosis development and progression and include the HDL particle capacity to efflux cellular cholesterol and the antioxidative and anti-inflammatory properties. Specifically, multivariate data analysis and machine learning techniques such as regression, random forests, and general inferential statistics were used in order to test hypotheses based on previous research and discover variables that affect in a great extend the above three major functional HDL properties. Part of data and other information have originated from the combination of two research publications, [(Zvintzou, et al. 2017), (Filou, et al. 2016)] both regarding the analysis of HDL and some of its subpopulations in specific genetic background mice (C57BL/6 and Apoe-/- x Apoa1-/-, respectively) infected with adenoviruses expressing three different human apolipoproteins, APOC3 and APOA1, APOE3, respectively.
|
|---|
