Qualitative serum organic acid profiles of HIV-infected individuals not on antiretroviral treatment

The first application of gas chromatography mass spectrometry (GC–MS) metabolomics to the analysis of organic acid profiles in sera of asymptomatic human immunodeficiency virus (HIV)-infected individuals (n = 18) compared to uninfected controls (n = 21), is reported here. Several organic acids are well-established diagnostic biomarkers of mitochondrial dysfunction, making the analysis of the organic acid metabolome well suited to monitoring the progressive disruption of mitochondrial structure and function during HIV infection. Using a multifaceted analytical-bioinformatics procedure, at least 10 of these metabolites could be linked to (1) disrupted mitochondrial metabolism, (2) changes in lipid metabolism and (3) oxidative stress, all of which are aberrations caused by HIV infection. Because of the role of the mitochondria in apoptosis, higher levels of this type of cell death in infected (compared to uninfected) individuals was used to support GC–MS data. This study demonstrates that mass spectrometry metabolomics detects biomarkers of mitochondrial dysfunction which could potentially be developed into indicators of HIV infection, perhaps also to monitor disease progression and the response to antiretroviral treatment.The National Research Foundationhttp://www.springerlink.com/content/1573-3882/nf201

The SL2S Galaxy-scale Gravitational Lens Sample. I. The alignment of mass and light in massive early-type galaxies at z=0.2-0.9

We study the relative alignment of mass and light in a sample of 16 massive early-type galaxies at z=0.2-0.9 that act as strong gravitational lenses. The sample was identified from deep multi-band images obtained as part of the Canada France Hawaii Telescope Legacy Survey as part of the Strong Lensing Legacy Survey (SL2S). Higher resolution follow-up imaging is available for a subset of 10 systems. We construct gravitational lens models and infer total enclosed mass, elongation, and position angle of the mass distribution. By comparison with the observed distribution of light we infer that there is a substantial amount of external shear with mean value $= 0.12 \pm 0.05$, arising most likely from the environment of the SL2S lenses. In a companion paper, we combine these measurements with follow-up Keck spectroscopy to study the evolution of the stellar and dark matter content of early-type galaxies as a function of cosmic time

Metabolomics of urinary organic acids in respiratory chain deficiencies in children

Metabolomic analysis of the urinary organic acids from 39 selected children with defined respiratory chain deficiencies (RCDs) was performed using untargeted gas chromatography–mass spectrometry, revealing the presence of 255 endogenous and 46 exogenous substances. Variable reduction identified 92 variables from the endogenous substances, which could be analysed by univariate and multivariate statistical methods. Using these methods, no characteristic organic acid biomarker profile could be defined of practical value for diagnostic purposes for complex I (CI), complex III (CIII) and multiple complex (CM) deficiencies. The statistical procedures used did, however, disclose 24 metabolites that were practical highly (d > 0.75) and statistically (p < 0.05) significant for the combined and clinically closely related group of RCDs. Several of these metabolites occur in single enzyme inherited metabolic diseases, but most were not previously reported to be linked to the metabolic perturbations that are due to RCDs. Ultimately, we constructed a global metabolic profile of carbohydrate, amino acid and fatty acid catabolism, illuminating the diverse and complex biochemical consequences of these disorders. This metabolomics investigation disclosed a metabolite profile that has the potential to define an extended and characteristic biosignature for RCDs and the development of a non-invasive screening procedure for these disorders.This study formed part of BioPAD Project BPP007.The South African Department of Science and Technology and North-West University.http://link.springer.com/journal/11306hb2017Paediatrics and Child Healt

The stellar masses and specific star-formation rates of submillimetre galaxies

Establishing the stellar masses (M*), and hence specific star-formation rates (sSFRs) of submillimetre galaxies (SMGs) is crucial for determining their role in the cosmic galaxy/star formation. However, there is as yet no consensus over the typical M* of SMGs. Specifically, even for the same set of SMGs, the reported average M* have ranged over an order of magnitude, from ~5x10^10 Mo to ~5x10^11 Mo. Here we study how different methods of analysis can lead to such widely varying results. We find that, contrary to recent claims in the literature, potential contamination of IRAC 3-8 um photometry from hot dust associated with an active nucleus is not the origin of the published discrepancies in derived M*. Instead, we expose in detail how inferred M* depends on assumptions made in the photometric fitting, and quantify the individual and cumulative effects of different choices of initial mass function, different brands of evolutionary synthesis models, and different forms of assumed star-formation history. We review current observational evidence for and against these alternatives as well as clues from the hydrodynamical simulations, and conclude that, for the most justifiable choices of these model inputs, the average M* of SMGs is ~2x10^11 Mo. We also confirm that this number is perfectly reasonable in the light of the latest measurements of their dynamical masses, and the evolving M* function of the overall galaxy population. M* of this order imply that the average sSFR of SMGs is comparable to that of other star-forming galaxies at z>2, at 2-3 Gyr^-1. This supports the view that, while rare outliers may be found at any M*, most SMGs simply form the top end of the main-sequence of star-forming galaxies at these redshifts. Conversely, this argues strongly against the viewpoint that SMGs are extreme pathological objects, of little relevance in the cosmic history of star-formation.Comment: Accepted to A&A. 13 pages, 5 figures, 3 tables. Main changes: 1) investigation that the main-sequence does not change the location as much as SMGs when changing SFHs; 2) a new table added with all stellar mass estimates for individual SMGs (machine-readable version in the source file). V3: missing references adde

A new method for transforming data to normality with application to density estimation

Thesis (Ph.D. (Statistics))--North-West University, Potchefstroom Campus, 2005.One of the main objectives of this dissertation is to derive efficient non-parametric estimators for an unknown density f . It is well known that the ordinary kernel density estimator has, despite of several good properties, some drawbacks. For example, it suffers from boundary bias and it also exhibits spurious bumps in the tails. Various solutions to overcome these defects are presented in this study, which include the application of a transformation kernel density estimator. The latter estimator (if implemented correctly) is pursued as a simultaneous solution for both boundary bias and spurious bumps in the tails. The estimator also has, among others, the ability to detect and estimate density modes more effectively. To apply the transformation kernel density estimator an effective transformation of the data is required. To achieve this objective, an extensive discussion of parametric transformations introduced and studied in the literature is presented firstly, emphasizing the practical feasibility of these transformations. Secondly, known methods of estimating the parameters associated with these transformations are discussed (e.g. profile maximum likelihood), and two new estimation techniques, referred to as the minimum residual and minimum distance methods, are introduced. Furthermore, new procedures are developed to select a parametric transformation that is suitable for application to a given set of data. Finally, utilizing the above techniques, the desired optimal transformation to any target distribution (e.g. the normal distribution) is introduced, which has the property that it can also be iterated. A polynomial approximation of the optimal transformation function is presented. It is shown that the performance of this transformation exceeds that of any transformation available in the literature. In the context of transformation kernel density estimation, we present a comprehensive literature study of current methods available and then introduce the new semi-parametric transformation estimation procedure based on the optimal transformation of data to normality. However, application of the optimal transformation in this context requires special attention. In order to create a density estimator that addresses both boundary bias and spurious bumps in the tails simultaneously in an automatic way, a generalized bandwidth adaptation procedure is developed, which is applied in conjunction with a newly developed constant shift procedure. Furthermore, the optimal transformation function is based on a kernel distribution function estimator. A new data-based smoothing parameter (bandwidth selector) is invented, and it is shown that this selector has better performance than a well established bandwidth selector proposed in the literature. To evaluate the performance of the newly proposed semi-parametric transformation estimation procedure, a simulation study is presented based on densities that consist of a wide range of forms. Some of the main results derived in the Monte Carlo simulation study include that: * the proposed optimal transformation function can take on all the possible shapes of a parametric transformation as well as any combination of these shapes, which result in high p-values when testing normality of the transformed data. * the new minimum residual and minimum distance techniques contribute to better transformations to normality, when a parametric transformation is applicable. * the newly proposed semi-parametric transformation kernel density estimator perform well for unimodal, low and high kurtosis densities. Moreover, it estimates densities with much curvature (e.g. modes and valleys) more effectively than existing procedures in the literature. * the new transformation density estimator does not exhibit spurious bumps in the tail regions. * boundary bias is addressed automatically. In conclusion, practical examples based on real-life data are presented.Doctora

Single nucleotide and copy number polymorphisms of the SULT1A1 gene in a South African Tswana population group

Previous studies on gene mapping have firmly established variation in segments of the DNA structure amongst different population groups. SULT1A1 is one of four SULT1A genes that maps to the short arm of chromosome 16, and this area has been shown to contain many repetitive sequences and to be highly duplicated. Using the polymerase chain reaction (PCR)-based restriction fragment length polymorphism method, we set out to determine the SULT1A1 genotype and allele frequency distributions in the largest sample studied to date: a homogeneous South African Tswana population of 1867 individuals from the Prospective Urban and Rural Epidemiological (PURE) study, and found the SULT1A1*1 and SULT1A1*2 alleles present at a frequency of 0.68 and 0.32, respectively. This finding corresponded with those obtained for the Black, Caucasian, and mixed-race South African groups reported in previous studies. Next, using a quantitative multiplex PCR method to estimate the SULT1A1 gene number of copies in 459 subjects of our population, we discovered between one and five copies: 0.65% of the subjects had a single copy (allele deletion) and 60.14% of the subjects had three or more copies. Our findings correspond with an earlier study on a small African-American group, but differ from those based on two Caucasian groups. Whereas the genotype distribution was comparable to the Caucasian groups, there was a significant difference in the number of copies, which indicated a genetic link between Tswana and African-American populations despite differences in cultural lifestyle associated with their geographical location

Organic acid profile of isovaleric acidemia: a comprehensive metabolomics approach

Isovaleric acidemia (IVA, MIM 248600) can be a severe and potentially life-threatening disease in affected neonates, but with a positive prognosis on treatment for some phenotypes. This study presents the first application of metabolomics to evaluate the metabolite profiles derived from urine samples of untreated and treated IVA patients as well as of obligate heterozygotes. All IVA patients carried the same homozygous c.367 G > A nucleotide change in exon 4 of the IVD gene but manifested phenotypic diversity. Concurrent class analysis (CONCA) was used to compare all the metabolites from the original complete data set obtained from the three case and two control groups used in this investigation. This application of CONCA has not been reported previously, and is used here to compare four different modes of scaling of all metabolites. The variables important in discrimination from the CONCA thus enabled the recognition of different metabolic patterns encapsulated within the data sets that would not have been revealed by using only one mode of scaling. Application of multivariate and univariate analyses disclosed 11 important metabolites that distinguished untreated IVA from controls. These included well-established diagnostic biomarkers of IVA, endogenous detoxification markers, and 3-hydroxycaproic acid, an indicator of ketosis, but not reported previously for this disease. Nine metabolites were identified that reflected the effect of treatment of IVA. They included detoxification products and indicators related to the high carbohydrate and low protein diet which formed the hallmark of the treatment. This investigation also provides the first comparative metabolite profile for heterozygotes of this inherited metabolic disorder. The detection of informative metabolites in even very low concentrations in all three experimental groups highlights the potential advantage of the holistic mode of analysis of inherited metabolic diseases in a metabolomics investigatio