6,284 research outputs found
A metabolomics investigation on experimental interventions of acute alcohol consumption
No full textPhD (Biochemistry), North-West University, Potchefstroom CampusThis thesis, titled: "A metabolomics investigation on experimental interventions of acute alcohol consumption", deals with a current topic of global interest, namely, alcohol use and abuse. Alcohol abuse is associated with many serious, and even detrimental, health, social and economic consequences, and is one of the world’s leading risk factors for disability, morbidity and mortality. For these reasons it is a topic of growing concern in developing, as well as developed, countries. Alcohol is metabolized mainly in the liver by two nicotinamide adenine dinucleotide (NAD)-dependent enzymes — alcohol dehydrogenase and, subsequently, aldehyde dehydrogenase. In both of these reactions oxidized NAD (NAD+) is reduced to NADH, which increases the NAHD:NAD+ ratio in hepatocytes. This ratio controls the activity of several key metabolic enzymes and the direction of many reversible metabolic reactions, and its disruption is known to result in perturbations of various metabolic pathways. Various studies examining the effects of, and diseases related to, chronic alcohol abuse have been performed in the last few decades. However, to date, no comprehensive metabolomics study on the effects of acute alcohol consumption has been done. Thus, with the guidance of experts in the fields of metabolism, metabolomics and biostatistics, the first extensive, multidisciplinary metabolomics cross-over intervention study into the effects of acute alcohol consumption on the urinary metabolite profiles of healthy, young males was designed, and is presented in this thesis. The study consisted of analysing urine samples, collected from experimental participants over a defined period of time following four interventions, on two different analytical platforms — proton nuclear magnetic resonance (1H-NMR) spectroscopy as an untargeted approach, and gas chromatography—mass spectrometry (GC—MS) as a semi-targeted approach. The results from these investigations demonstrated the power of applying metabolomics to this area of research and provided the opportunity to obtain a holistic view of the urinary metabolic profile resulting from acute alcohol consumption. From both of these approaches a list of metabolites perturbed by acute alcohol consumption could be compiled with the use of statistical analyses. Various metabolic pathways were seen to be disrupted, most of them due to the known alcohol-induced increased NADH:NAD+ ratio. Additionally, two urinary metabolites — sorbitol, from the 1H-NMR analysis, and 2-hydroxyisobutyric acid, from the GC—MS investigation — not previously known to be associated with the consequences of acute alcohol consumption were identified in the metabolic profiles of the experimental participants following acute alcohol consumption. These novel findings could possibly be used as a basis for determining biomarkers of acute alcohol consumption, which could have various health, economic and legal benefits. This thesis, the eventual product of a skilfully designed and diligently carried out scientific study, is compiled and presented in article format as per the requirements of North-West University. The scientific contributions made during this study to the existing alcohol-related scientific knowledge resulted in three publications. Two (1 and 3) have already been published, and one (2) has been accepted for publication. 1. Irwin, C., Van Reenen, M., Mason, S., Mienie, L.J., Westerhuis, J.A. & Reinecke, C.J. 2016. Contribution towards a metabolite profile of the detoxification of benzoic acid through glycine conjugation: an intervention study. PLOS ONE, 11(12):e0167309. doi:10.1371/journal.pone. 0167309. 2. Irwin, C., Van Reenen, M., Mason, S., Mienie, L.J., Wevers, R.A., Westerhuis, J.A. & Reinecke, C.J. The 1H-NMR-based metabolite profile of acute alcohol consumption: a metabolomics intervention study. 3. Irwin, C., Mienie, L.J., Wevers, R.A., Mason, S., Westerhuis, J.A., Van Reenen, M. & Reinecke, C.J. 2018. GC—MS-based urinary organic acid profiling reveals multiple dysregulated metabolic pathways following experimental acute alcohol consumption. Scientific Reports, 8:5775. doi:10.1038/s41598-018-24128-1.Doctora
J.A. Daigneau
No full textPhotograph - J.A. Daigneau building, Athabasca, Alberta. It was built in 1912 by Joseph Daigneau and burnt down in 198
Author inscription in The Chinese slave-girl: a story of woman's life in China
No full textThis edition includes a gift inscription by author Rev. J.A. Davis, "To Rev. A. G. Russell with the warmest regards of the author J.A. Davis."Davis, John Agnell, 1839-1897
Targeted proteomic response to coffee consumption
No full textPurpose
Coffee is widely consumed and implicated in numerous health outcomes but the mechanisms by which coffee contributes to health is unclear. The purpose of this study was to test the effect of coffee drinking on candidate proteins involved in cardiovascular, immuno-oncological and neurological pathways.
Methods
We examined fasting serum samples collected from a previously reported single blinded, three-stage clinical trial. Forty-seven habitual coffee consumers refrained from drinking coffee for 1 month, consumed 4 cups of coffee/day in the second month and 8 cups/day in the third month. Samples collected after each coffee stage were analyzed using three multiplex proximity extension assays that, after quality control, measured a total of 247 proteins implicated in cardiovascular, immuno-oncological and neurological pathways and of which 59 were previously linked to coffee exposure. Repeated measures ANOVA was used to test the relationship between coffee treatment and each protein.
Results
Two neurology-related proteins including carboxypeptidase M (CPM) and neutral ceramidase (N-CDase or ASAH2), significantly increased after coffee intake (P 0.05); 9, 8 and 29 of these proteins related to cardiovascular, immuno-oncological and neurological pathways, respectively, and the levels of 41 increased with coffee intake.
Conclusions
CPM and N-CDase levels increased in response to coffee intake. These proteins have not previously been linked to coffee and are thus novel markers of coffee response worthy of further stud
Variable selection and validation in multivariate modelling
Full text linkMotivation Validation of variable selection and predictive performance is crucial in construction of robust multivariate models that generalize well, minimize overfitting and facilitate interpretation of results. Inappropriate variable selection leads instead to selection bias, thereby increasing the risk of model overfitting and false positive discoveries. Although several algorithms exist to identify a minimal set of most informative variables (i.e. the minimal-optimal problem), few can select all variables related to the research question (i.e. the all-relevant problem). Robust algorithms combining identification of both minimal-optimal and all-relevant variables with proper cross-validation are urgently needed. Results We developed the MUVR algorithm to improve predictive performance and minimize overfitting and false positives in multivariate analysis. In the MUVR algorithm, minimal variable selection is achieved by performing recursive variable elimination in a repeated double cross-validation (rdCV) procedure. The algorithm supports partial least squares and random forest modelling, and simultaneously identifies minimal-optimal and all-relevant variable sets for regression, classification and multilevel analyses. Using three authentic omics datasets, MUVR yielded parsimonious models with minimal overfitting and improved model performance compared with state-of-the-art rdCV. Moreover, MUVR showed advantages over other variable selection algorithms, i.e. Boruta and VSURF, including simultaneous variable selection and validation scheme and wider applicability
Variable importance in latent variable regression models
No full textThe quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable selection. Thus, these graphs provide visualization of the explanatory variables’ content of response related as well as systematic orthogonal variation at a quantitative level. Furthermore, these graphs are able to reveal and partition the explanatory variables into those that are crucial for both interpretation and predictive performance of the model, and those that are crucial for prediction performance but confounded by large contributions of orthogonal variation. Tools for assessment of explanatory variables may not only aid interpretation and understanding of the model but also be crucial for performing variable selection with the purpose of obtaining parsimonious models with high explanatory information content aswell as predictive performance. We show by example that by just using prediction performance as criterion for variable selection, it is possible to end up with a reducedmodel where the most selective variables are lost in the selection process
Group living homes for older people with dementia: Concept and effects
Full text linkEefsting, J.A. [Promotor]Pot, A.M. [Promotor]Depla, M.F.I.A. [Copromotor]Lange, J. de [Copromotor
Real-time synchronization of batch trajectories for on-line multivariate statistical process control using Dynamic Time Warping
Full text linkThis paper addresses the real-time monitoring of batch processes with multiple different local time trajectories of variables measured during the process run. For Unfold Principal Component Analysis (U-PCA)—or Unfold Partial Least Squares (U-PLS)-based on-line monitoring of batch processes, batch runs need to be synchronized, not only to have the same time length, but also such that key events happen at the same time. An adaptation from Kassidas et al.'s approach [1] will be introduced to achieve the on-line synchronization of batch trajectories using the Dynamic Time Warping (DTW) algorithm. In the proposed adaptation, a new boundaries definition is presented for accurate on-line synchronization of an ongoing batch, together with a way to adapt mapping boundaries to batch length. A relaxed greedy strategy is introduced to avoid assessing the optimal path each time a new sample is available. The key advantages of the proposed strategy are its computational speed and accuracy for the batch process context. Data from realistic simulations of a fermentation process of the Saccharomyces cerevisae cultivation are used to illustrate the performance of the proposed strategy.This research work was supported by the Spanish government under the project (DPI2008-06880-C03-03). We also gratefully acknowledge Jose Camacho PhD. for providing simulated data from a fermentation process of Saccharomyces cerevisae. The authors would also like to acknowledge the valuable suggestions made by Prof. Paul Taylor.González Martínez, JM.; Ferrer Riquelme, AJ.; Westerhuis, JA. (2011). Real-time synchronization of batch trajectories for on-line multivariate statistical process control using Dynamic Time Warping. Chemometrics and Intelligent Laboratory Systems. 105(2):195-206. https://doi.org/10.1016/j.chemolab.2011.01.003S195206105
Quantitative Raman reaction monitoring using the solvent as internal standard.
No full textDespite its potential, the use of Raman spectroscopy for real-time quantitative reaction monitoring is still rather limited. The problems of fluorescence, laser instability, low intensities, and the inner filter effect often outscore the advantages as narrow bands, the use of glass fibers, and low scattering of water and glass. In this paper, we present real-time quantitative monitoring of the catalyzed Heck reaction by using the solvent as internal standard. In this way, all multiplicative distortions, e.g., laser intensity variations or absorbance of the laser light, can be corrected for. We also show that a limited amount of fluorescence does not hamper the analysis. Finally, we present a new method to correct for the inner filter effect, i.e., the absorbance of Raman scattered light by the reaction medium. Simultaneous absorption measurements of the reaction mixture enable accurate correction of Raman signals for the inner filter effect. Thus, for reaction monitoring applications, a Raman spectrometer should be equipped with an absorbance measurement device
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