Effect of estrogen receptor-alpha (ESR1) gene polymorphism on high density lipoprotein levels in response to hormone replacement therapy

Studies have shown that estrogen replacement therapy and estrogen plus progestin replacement therapy alter serum levels of total, LDL and HDL cholesterol levels. However, HDL cholesterol levels in women vary considerably in response to hormone replacement therapy (HRT). A significant portion of the variability of these levels has been attributed to genetic factors. Therefore, we investigated the influence of estrogen receptor-alpha (ESR1) gene polymorphisms on HDL levels in response to postmenopausal HRT. We performed a prospective cohort study on 54 postmenopausal women who had not used HRT before the study and had no significant general medical illness. HRT consisted of conjugated equine estrogen and medroxyprogesterone acetate continuously for 1 year. The lipoprotein levels were measured from blood samples taken before the start of therapy and after 1 year of HRT. ESR1 polymorphism (MspI C>T, HaeIII C>T, PvuII C>T, and XbaI A>G) frequencies were assayed by restriction fragment length polymorphism. A general linear model was used to describe the relationships between HDL levels and genotypes after adjusting for age. A significant increase in HDL levels was observed after HRT (P = 0.029). Women with the ESR1 PvuII TT genotype showed a statistically significant increase in HDL levels after HRT (P = 0.032). No association was found between other ESR1 polymorphisms and HDL levels. According to our results, the ESR1 PvuII TT genotype was associated with increased levels of HDL after 1 year of HRT.

Reversible flow of cholesteryl ester between high-density lipoproteins and triacylglycerol-rich particles is modulated by the fatty acid composition and concentration of triacylglycerols

We determined the influence of fasting (FAST) and feeding (FED) on cholesteryl ester (CE) flow between high-density lipoproteins (HDL) and plasma apoB-lipoprotein and triacylglycerol (TG)-rich emulsions (EM) prepared with TG-fatty acids (FAs). TG-FAs of varying chain lengths and degrees of unsaturation were tested in the presence of a plasma fraction at d > 1.21 g/mL as the source of CE transfer protein. The transfer of CE from HDL to FED was greater than to FAST TG-rich acceptor lipoproteins, 18% and 14%, respectively. However, percent CE transfer from HDL to apoB-containing lipoproteins was similar for FED and FAST HDL. The CE transfer from HDL to EM depended on the EM TG-FA chain length. Furthermore, the chain length of the monounsaturated TG-containing EM showed a significant positive correlation of the CE transfer from HDL to EM (r = 0.81, P < 0.0001) and a negative correlation from EM to HDL (r = -041, P = 0.0088). Regarding the degree of EM TG-FAs unsaturation, among EMs containing C18, the CE transfer was lower from HDL to C18:2 compared to C18:1 and C18:3, 17.7%, 20.7%, and 20%, respectively. However, the CE transfer from EMs to HDL was higher to C18:2 than to C18:1 and C18:3, 83.7%, 51.2%, and 46.3%, respectively. Thus, the EM FA composition was found to be the rate-limiting factor regulating the transfer of CE from HDL. Consequently, the net transfer of CE between HDL and TG-rich particles depends on the specific arrangement of the TG acyl chains in the lipoprotein particle core.

Studies on the Rheology and the Mechanical Properties of Thermoplastic Elastomer from Latex Product Waste and High Density Polyethylene

Latex waste products contain rubber hydrocarbon of very high quality, which is only lightly cross linked. Selected wastes such as thread waste and glove waste were modified into processable materials by a novel economic process and thermoplastic elastomers were prepared by blending these modified waste materials with high density polyethylene in various proportions. The mechanical properties as well as the rheological behaviour of these blends were evaluated and compared with those of the natural rubber-high density polyethylene blends.

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

A New Gridding Technique for High Density Microarray Images Using Intensity Projection Profile of Best Sub Image

As the technologies for the fabrication of high quality microarray advances rapidly, quantification of microarray data becomes a major task. Gridding is the first step in the analysis of microarray images for locating the subarrays and individual spots within each subarray. For accurate gridding of high-density microarray images, in the presence of contamination and background noise, precise calculation of parameters is essential. This paper presents an accurate fully automatic gridding method for locating suarrays and individual spots using the intensity projection profile of the most suitable subimage. The method is capable of processing the image without any user intervention and does not demand any input parameters as many other commercial and academic packages. According to results obtained, the accuracy of our algorithm is between 95-100% for microarray images with coefficient of variation less than two. Experimental results show that the method is capable of gridding microarray images with irregular spots, varying surface intensity distribution and with more than 50% contamination

Rice husk ash – A valuable reinforcement for high density polyethylene

This paper presents the results of a study on the use of rice husk ash (RHA) for property modification of high density polyethylene (HDPE). Rice husk is a waste product of the rice processing industry. It is used widely as a fuel which results in large quantities of RHA. Here, the characterization of RHA has been done with the help of X-ray diffraction (XRD), Inductively Coupled Plasma Atomic Emission Spectroscopy (ICPAES), light scattering based particle size analysis, Fourier transform infrared spectroscopy (FTIR) and Scanning Electron Microscope (SEM). Most reports suggest that RHA when blended directly with polymers without polar groups does not improve the properties of the polymer substantially. In this study RHA is blended with HDPE in the presence of a compatibilizer. The compatibilized HDPE-RHA blend has a tensile strength about 18% higher than that of virgin HDPE. The elongation-at-break is also higher for the compatibilized blend. TGA studies reveal that uncompatibilized as well as compatibilized HDPERHA composites have excellent thermal stability. The results prove that RHA is a valuable reinforcing material for HDPE and the environmental pollution arising from RHA can be eliminated in a profitable way by this technique.

Modification of Polypropylene/High Density Polyethylene Blend Using Nanokaolinite Clay and E-Glass Fibre: Preparation, Characterization and Micromechanical Modelling

Upgrading two widely used standard plastics, polypropylene (PP) and high density polyethylene (HDPE), and generating a variety of useful engineering materials based on these blends have been the main objective of this study. Upgradation was effected by using nanomodifiers and/or fibrous modifiers. PP and HDPE were selected for modification due to their attractive inherent properties and wide spectrum of use. Blending is the engineered method of producing new materials with tailor made properties. It has the advantages of both the materials. PP has high tensile and flexural strength and the HDPE acts as an impact modifier in the resultant blend. Hence an optimized blend of PP and HDPE was selected as the matrix material for upgradation. Nanokaolinite clay and E-glass fibre were chosen for modifying PP/HDPE blend. As the first stage of the work, the mechanical, thermal, morphological, rheological, dynamic mechanical and crystallization characteristics of the polymer nanocomposites prepared with PP/HDPE blend and different surface modified nanokaolinite clay were analyzed. As the second stage of the work, the effect of simultaneous inclusion of nanokaolinite clay (both N100A and N100) and short glass fibres are investigated. The presence of nanofiller has increased the properties of hybrid composites to a greater extent than micro composites. As the last stage, micromechanical modeling of both nano and hybrid A composite is carried out to analyze the behavior of the composite under load bearing conditions. These theoretical analyses indicate that the polymer-nanoclay interfacial characteristics partially converge to a state of perfect interfacial bonding (Takayanagi model) with an iso-stress (Reuss IROM) response. In the case of hybrid composites the experimental data follows the trend of Halpin-Tsai model. This implies that matrix and filler experience varying amount of strain and interfacial adhesion between filler and matrix and also between the two fillers which play a vital role in determining the modulus of the hybrid composites.A significant observation from this study is that the requirement of higher fibre loading for efficient reinforcement of polymers can be substantially reduced by the presence of nanofiller together with much lower fibre content in the composite. Hybrid composites with both nanokaolinite clay and micron sized E-glass fibre as reinforcements in PP/HDPE matrix will generate a novel class of high performance, cost effective engineering material.

High Density Single Crystalline GaN Nanodot Arrays Fabricated Using Template-Assisted Selective Growth

High density, uniform GaN nanodot arrays with controllable size have been synthesized by using template-assisted selective growth. The GaN nanodots with average diameter 40nm, 80nm and 120nm were selectively grown by metalorganic chemical vapor deposition (MOCVD) on a nano-patterned SiO2/GaN template. The nanoporous SiO2 on GaN surface was created by inductively coupled plasma etching (ICP) using anodic aluminum oxide (AAO) template as a mask. This selective regrowth results in highly crystalline GaN nanodots confirmed by high resolution transmission electron microscopy. The narrow size distribution and uniform spatial position of the nanoscale dots offer potential advantages over self-assembled dots grown by the Stranski–Krastanow mode.

Evaluation of the use of high-density SNP genotyping to implement UPOV Model 2 for DUS testing in barley

Developments in high-throughput genotyping provide an opportunity to explore the application of marker technology in distinctness, uniformity and stability (DUS) testing of new varieties. We have used a large set of molecular markers to assess the feasibility of a UPOV Model 2 approach: “Calibration of threshold levels for molecular characteristics against the minimum distance in traditional characteristics”. We have examined 431 winter and spring barley varieties, with data from UK DUS trials comprising 28 characteristics, together with genotype data from 3072 SNP markers. Inter varietal distances were calculated and we found higher correlations between molecular and morphological distances than have been previously reported. When varieties were grouped by kinship, phenotypic and genotypic distances of these groups correlated well. We estimated the minimum marker numbers required and showed there was a ceiling after which the correlations do not improve. To investigate the possibility of breaking through this ceiling, we attempted genomic prediction of phenotypes from genotypes and higher correlations were achieved. We tested distinctness decisions made using either morphological or genotypic distances and found poor correspondence between each method.

Optimising the analysis of transcript data using high density oligonucleotide arrays and genomic DNA-based probe selection

Background: Affymetrix GeneChip arrays are widely used for transcriptomic studies in a diverse range of species. Each gene is represented on a GeneChip array by a probe- set, consisting of up to 16 probe-pairs. Signal intensities across probe- pairs within a probe-set vary in part due to different physical hybridisation characteristics of individual probes with their target labelled transcripts. We have previously developed a technique to study the transcriptomes of heterologous species based on hybridising genomic DNA (gDNA) to a GeneChip array designed for a different species, and subsequently using only those probes with good homology. Results: Here we have investigated the effects of hybridising homologous species gDNA to study the transcriptomes of species for which the arrays have been designed. Genomic DNA from Arabidopsis thaliana and rice (Oryza sativa) were hybridised to the Affymetrix Arabidopsis ATH1 and Rice Genome GeneChip arrays respectively. Probe selection based on gDNA hybridisation intensity increased the number of genes identified as significantly differentially expressed in two published studies of Arabidopsis development, and optimised the analysis of technical replicates obtained from pooled samples of RNA from rice. Conclusion: This mixed physical and bioinformatics approach can be used to optimise estimates of gene expression when using GeneChip arrays.

Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species

High-density oligonucleotide (oligo) arrays are a powerful tool for transcript profiling. Arrays based on GeneChip® technology are amongst the most widely used, although GeneChip® arrays are currently available for only a small number of plant and animal species. Thus, we have developed a method to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species and tested the method by analysing the transcriptome of Brassica oleracea L., a species for which no GeneChip® array is available, using a GeneChip® array designed for Arabidopsis thaliana (L.) Heynh. Genomic DNA from B. oleracea was labelled and hybridised to the ATH1-121501 GeneChip® array. Arabidopsis thaliana probe-pairs that hybridised to the B. oleracea genomic DNA on the basis of the perfect-match (PM) probe signal were then selected for subsequent B. oleracea transcriptome analysis using a .cel file parser script to generate probe mask files. The transcriptional response of B. oleracea to a mineral nutrient (phosphorus; P) stress was quantified using probe mask files generated for a wide range of gDNA hybridisation intensity thresholds. An example probe mask file generated with a gDNA hybridisation intensity threshold of 400 removed > 68 % of the available PM probes from the analysis but retained >96 % of available A. thaliana probe-sets. Ninety-nine of these genes were then identified as significantly regulated under P stress in B. oleracea, including the homologues of P stress responsive genes in A. thaliana. Increasing the gDNA hybridisation intensity thresholds up to 500 for probe-selection increased the sensitivity of the GeneChip® array to detect regulation of gene expression in B. oleracea under P stress by up to 13-fold. Our open-source software to create probe mask files is freely available http://affymetrix.arabidopsis.info/xspecies/ webcite and may be used to facilitate transcriptomic analyses of a wide range of plant and animal species in the absence of custom arrays.

APOA5 genotype influences the association between 25-hydroxyvitamin D and high density lipoprotein cholesterol

OBJECTIVE: Circulating levels of 25-hydroxyvitamin D (25OHD) are positively associated with high density lipoprotein (HDL) cholesterol. We sought to replicate a previously reported interaction between APOA5 genotype and vitamin D, and to examine whether HDL-associated genetic loci modify the association between serum 25OHD and HDL cholesterol. METHODS: We examined whether 42 single nucleotide polymorphisms (SNPs) modify the association between serum 25OHD and HDL cholesterol in the 1958 British Birth cohort (aged 45 years, n = 4978). RESULTS: We identified a borderline interaction between the SNP rs12272004 (near the APOA5) and serum 25OHD on HDL cholesterol (P(interaction) = 0.05). The interaction was particularly prominent among the samples collected during winter (P(interaction) = 0.001). None of the other loci showed an interaction with serum 25OHD concentrations on HDL cholesterol. CONCLUSIONS: Our study in 4978 British Whites provides further support that APOA5 genotype modifies the association between vitamin D metabolites and HDL cholesterol.

High density lipoproteins (HDLs) and atherosclerosis; the unanswered questions

The concentration of high density lipoprotein-cholesterol (HDL-C) has been found consistently to be a powerful negative predictor of premature coronary heart disease (CHD) in human prospective population studies. There is also circumstantial evidence from human intervention studies and direct evidence from animal intervention studies that HDLs protect against the development of atherosclerosis. HDLs have several documented functions, although the precise mechanism by which they prevent atherosclerosis remains uncertain. Nor is it known whether the cardioprotective properties of HDL are specific to one or more of the many HDL subpopulations that comprise the HDL fraction in human plasma. Several lifestyle and pharmacological interventions have the capacity to raise the level of HDL-C, although it is not known whether all are equally protective. Indeed, despite the large body of information identifying HDLs as potential therapeutic targets for the prevention of atherosclerosis, there remain many unanswered questions that must be addressed as a matter of urgency before embarking wholesale on HDL-C-raising therapies as strategies to prevent CHD. This review summarises what is known and highlights what we still need to know.

High density lipoprotein: guardian of the vascular system?

The role of low-density lipoprotein in the development of coronary heart disease (CHD) is well recognised. There is also growing evidence that high-density lipoprotein cholesterol (HDL-C) is a powerful inverse predictor for premature CHD and that maintaining a high HDL-C level may guard against atherosclerosis. Patients with low HDL-C levels often also have central obesity, insulin resistance and other features of the metabolic syndrome. This syndrome is both increasingly common and strongly implicated in the growing worldwide epidemic of type 2 diabetes. HDL-C may be increased by lifestyle changes, e.g. weight loss, physical activity and smoking cessation. Pharmacological agents such as fibrates, niacin and statins have also been shown significantly to elevate HDL-C. Although current guidelines are beginning to recognise the protective role of HDL-C level in preventing coronary events, HDL-C should be adopted soon as a target for intervention in its own right.

A high-density immunoblotting methodology for quantification of total protein levels and phosphorylation modifications

The components of many signaling pathways have been identified and there is now a need to conduct quantitative data-rich temporal experiments for systems biology and modeling approaches to better understand pathway dynamics and regulation. Here we present a modified Western blotting method that allows the rapid and reproducible quantification and analysis of hundreds of data points per day on proteins and their phosphorylation state at individual sites. The approach is of particular use where samples show a high degree of sample-to-sample variability such as primary cells from multiple donors. We present a case study on the analysis of >800 phosphorylation data points from three phosphorylation sites in three signaling proteins over multiple time points from platelets isolated from ten donors, demonstrating the technique's potential to determine kinetic and regulatory information from limited cell numbers and to investigate signaling variation within a population. We envisage the approach being of use in the analysis of many cellular processes such as signaling pathway dynamics to identify regulatory feedback loops and the investigation of potential drug/inhibitor responses, using primary cells and tissues, to generate information about how a cell's physiological state changes over time.