High-density lipoprotein 17beta-estradiol fatty acyl esters and phytoestrogens : Impact on reverse cholesterol transport and women's cardiovascular health

Reverse cholesterol transport (RCT) is an important function of high-density lipoproteins (HDL) in the protection of atherosclerosis. RCT is the process by which HDL stimulates cholesterol removal from peripheral cells and transports it to the liver for excretion. Premenopausal women have a reduced risk for atherosclerosis compared to age-matched men and there exists a positive correlation for serum 17β-estradiol (E2) and HDL levels in premenopausal women supporting the role of E2 in atherosclerosis prevention. In premenopausal women, E2 associates with HDL as E2 fatty acyl esters. Discovery of the cellular targets, metabolism, and assessment of the macrophage cholesterol efflux potential of these HDL-associated E2 fatty acyl esters were the major objectives of this thesis (study I, III, and IV). Soy phytoestrogens, which are related to E2 in both structure and function, have been proposed to be protective against atherosclerosis but the evidence to support these claims is conflicting. Therefore, another objective of this thesis was to assess the ability of serum from postmenopausal women, treated with isoflavone supplements (compared to placebo), to promote macrophage cholesterol efflux (study II). The scope of this thesis was to cover the roles that HDL-associated E2 fatty acyl esters have in the cellular aspects of RCT and to determine if soy isoflavones can also influence RCT mechanisms. SR-BI was a pivotal cellular receptor, responsible for hepatic and macrophage uptake and macrophage cholesterol efflux potential of HDL-associated E2 fatty acyl esters. Functional SR-BI was also critical for proper LCAT esterification activity which could impact HDL-associated E2 fatty acyl ester assembly and its function. In hepatic cells, LDL receptors also contributed to HDL-associated E2 fatty acyl esters uptake and in macrophage cells, estrogen receptors (ERs) were necessary for both HDL-associated E2 ester-specific uptake and cholesterol efflux potential. HDL-containing E2 fatty acyl esters (E2-FAE) stimulated enhanced cholesterol efflux compared to male HDL (which are deficient in E2) demonstrating the importance of the E2 ester in this process. To support this, premenopausal female HDL, which naturally contains E2, showed greater macrophage cholesterol efflux compared to males. Additionally, hepatic and macrophage cells hydrolyzed the HDL-associated E2 fatty acyl ester into unesterified E2. This could have important biological ramifications because E2, not the esterified form, has potent cellular effects which may influence RCT mechanisms. Lastly, soy isoflavone supplementation in postmenopausal women did not modulate ABCA1-specific macrophage cholesterol efflux but did increase production of plasma pre-β HDL levels, a subclass of HDL. Therefore, the impact of isoflavones on RCT and cardiovascular health needs to be further investigated. Taken as a whole, HDL-associated E2 fatty acyl esters from premenopausal women and soy phytoestrogen treatment in postmenopausal women may be important factors that increase the efficiency of RCT through cellular lipoprotein-related processes and may have direct implications on the cardiovascular health of women.

Associations of gene polymorphisms and nutrition with calcium homeostasis and bone mineral density : Studies on skeletal nutrigenetics

Heredity explains a major part of the variation in calcium homeostasis and bone strength, and the susceptibility to osteoporosis is polygenetically regulated. Bone phenotype results from the interplay between lifestyle and genes, and several nutritional factors modulate bone health throughout life. Thus, nutrigenetics examining the genetic variation in nutrient intake and homeostatic control is an important research area in the etiology of osteoporosis. Despite continuing progress in the search for candidate genes for osteoporosis, the results thus far have been inconclusive. The main objective of this thesis was to investigate the associations of lactase, vitamin D receptor (VDR), calcium sensing receptor (CaSR) and parathyroid hormone (PTH) gene polymorphisms and lifestyle factors and their interactions with bone health in Finns at varying stages of the skeletal life span. Markers of calcium homeostasis and bone remodelling were measured from blood and urine samples. Bone strength was measured at peripheral and central bone sites. Lifestyle factors were assessed with questionnaires and interviews. Genetic lactase non-persistence (the C/C-13910 genotype) was associated with lower consumption of milk from childhood, predisposing females in particular to inadequate calcium intake. Consumption of low-lactose milk and milk products was shown to decrease the risk for inadequate calcium intake. In young adulthood, bone loss was more common in males than in females. Males with the lactase C/C-13910 genotype may be more susceptible to bone loss than males with the other lactase genotypes, although calcium intake predicts changes in bone mass more than the lactase genotype. The BsmI and FokI polymorphisms of the VDR gene were associated with bone mass in growing adolescents, but the associations weakened with age. In young adults, the A986S polymorphism of the calcium sensing receptor gene was associated with serum ionized calcium concentrations, and the BstBI polymorphism of the parathyroid gene was related to bone strength. The FokI polymorphism and sodium intake showed an interaction effect on urinary calcium excretion. A novel gene-gene interaction between the VDR FokI and PTH BstBI gene polymorphisms was found in the regulation of PTH secretion and urinary calcium excretion. Further research should be carried out with more number of Finns at varying stages of the skeletal life span and more detailed measurements of bone strength. Research should concern mechanisms by which genetic variants affect calcium homeostasis and bone strength, and the role of diet-gene and gene-gene interactions in the pathogenesis of osteoporosis.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Monte Carlo Simulations of Molecular Clusters in Nucleation

A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.

Lattice density-functional theory on graphene

A density-functional approach on the hexagonal graphene lattice is developed using an exact numerical solution to the Hubbard model as the reference system. Both nearest-neighbour and up to third nearest-neighbour hoppings are considered and exchange-correlation potentials within the local density approximation are parameterized for both variants. The method is used to calculate the ground-state energy and density of graphene flakes and infinite graphene sheet. The results are found to agree with exact diagonalization for small systems, also if local impurities are present. In addition, correct ground-state spin is found in the case of large triangular and bowtie flakes out of the scope of exact diagonalization methods.

Monte Carlo simulations of molecular clusters in nucleation

A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.