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- Alehagen, Urban, et al.
(författare)
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Significant Changes in Metabolic Profiles after Intervention with Selenium and Coenzyme Q10 in an Elderly Population
- 2019
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Ingår i: BIOMOLECULES. - : MDPI. - 2218-273X. ; 9:10
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Tidskriftsartikel (refereegranskat)abstract
- Selenium and coenzyme Q10 (SeQ10) are important for normal cellular function. Low selenium intake leads to increased cardiovascular mortality. Intervention with these substances with healthy elderly persons over a period of four years in a double-blind, randomised placebo-controlled prospective study showed reduced cardiovascular mortality, increased cardiac function, and a lower level of NT-proBNP. Therefore, we wanted to evaluate changes in biochemical pathways as a result of the intervention with SeQ10 using metabolic profiling. From a population of 443 healthy elderly individuals that were given 200 µg selenium and 200 mg coenzyme Q10, or placebo daily for four years, we selected nine males on active intervention and nine males on placebo for metabolic profiling in the main study. To confirm the results, two validation studies (study 1 n = 60 males, study 2 n = 37 males) were conducted. Principal component analyses were used on clinical and demographic data to select representative sets of samples for analysis and to divide the samples into batches for analysis. Gas chromatography time-of-flight mass spectrometry-based metabolomics was applied. The metabolite data were evaluated using univariate and multivariate approaches, mainly T-tests and orthogonal projections to latent structures (OPLS) analyses. Out of 95 identified metabolites, 19 were significantly decreased due to the intervention after 18 months of intervention. Significant changes could be seen in the pentose phosphate, the mevalonate, the beta-oxidation and the xanthine oxidase pathways. The intervention also resulted in changes in the urea cycle, and increases in the levels of the precursors to neurotransmitters of the brain. This adds information to previous published results reporting decreased oxidative stress and inflammation. This is the first-time metabolic profiling has been applied to elucidate the mechanisms behind an intervention with SeQ10. The study is small and should be regarded as hypothesis-generating; however, the results are interesting and, therefore, further research in the area is needed.
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| 2. |
- Dhillon, Sundeep S., et al.
(författare)
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Metabolic profiling of zebrafish embryo development from blastula period to early larval stages
- 2019
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Ingår i: PLOS ONE. - San Francisco : Public Library of Science. - 1932-6203. ; 14:5
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Tidskriftsartikel (refereegranskat)abstract
- The zebrafish embryo is a popular model for drug screening, disease modelling and molecular genetics. In this study, samples were obtained from zebrafish at different developmental stages. The stages that were chosen were 3/4, 4/5, 24, 48, 72 and 96 hours post fertilization (hpf). Each sample included fifty embryos. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). Principle component analysis (PCA) was applied to get an overview of the data and orthogonal projection to latent structure discriminant analysis (OPLS-DA) was utilised to discriminate between the developmental stages. In this way, changes in metabolite profiles during vertebrate development could be identified. Using a GC-TOF-MS metabolomics approach it was found that nucleotides and metabolic fuel (glucose) were elevated at early stages of embryogenesis, whereas at later stages amino acids and intermediates in the Krebs cycle were abundant. This agrees with zebrafish developmental biology, as organs such as the liver and pancreas develop at later stages. Thus, metabolomics of zebrafish embryos offers a unique opportunity to investigate large scale changes in metabolic processes during important developmental stages in vertebrate development. In terms of stability of the metabolic profile and viability of the embryos, it was concluded at 72 hpf was a suitable time point for the use of zebrafish as a model system in numerous scientific applications.
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| 5. |
- Lundstedt-Enkel, Katrin, et al.
(författare)
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Different multivariate approaches to material discovery, process development, PAT and environmental process monitoring
- 2006
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 84:1-2, s. 201-207
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Tidskriftsartikel (refereegranskat)abstract
- The aim with the present paper is to illustrate the use of multivariate strategies (i.e. integration of different multivariate methods) with five examples, four from the pharmaceutical industry and one from environmental research. In the first part, two examples wherein hierarchical models are applied to quality control (QC) and process control are discussed. In the second part a more complex problem and a strategy for material discovery/development are presented wherein a combination of multivariate calibration, multivariate analysis and multivariate design is needed. In the third part, a process analytical/optimization problem is illustrated with a two-step process, demanding that different multivariate tools are combined in a sequential way so that a useful model can be established and the process can be understood. In the final part the usefulness of principal component analysis followed by soft independent modelling of class analogy is illustrated with an example from environmental process monitoring. The five examples from quite different areas show that the chemometric tools are even more powerful if used integrated. However, different strategies and combinations of the tools have to be applied, depending on the problem and the aim.
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| 6. |
- Lundstedt-Enkel, Katrin, et al.
(författare)
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QSBMR - Quantitative Structure Biomagnification Relationships : Physicochemical and Structural Descriptors Important for the Biomagnification of Organochlorines and Brominated Flame Retardants
- 2006
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Ingår i: Journal of Chemometrics. - : Wiley. - 0886-9383 .- 1099-128X. ; 20:8-10, s. 392-401
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this project is to establish models to predict the biomagnification of contaminants present in Baltic Sea biota. In this paper a quantitative model that we term QSBMR-Quantitative Structure Biomagnification Relationships is presented. This model describes the relationship between the biomagnification factors (BMFs) for several organochlorines (OCs) and brominated flame retardants (BFRs), for example, polychlorinated biphenyls (PCBs), polybrominated diphenylethers (PBDEs) and hexabromocyclododecane (HBCD), and their descriptors, for example, physico-chemical properties and structural descriptors. The concentrations of contaminants in herring (Clupea harengus) muscle and guillemot (Uria aalge) egg from the Baltic Sea were used. The BMFs were calculated with the randomly sampled ratios (RSR) method that denotes the BMFs with a measure of the variation. In order to describe the physico-chemical properties and chemical structures, approximately 100 descriptors for the contaminants were generated: (a), by using the software (TSAR); (b) finding log Kow values from the literature, and (c) creating binary fingerprint variables that described the position of the chlorine and bromine for the respective PCB and PBDE molecules. Partial least squares (PLS) regression was used to model the relationship between the contaminants' BMF and the descriptors and the resulting QSBMR revealed that more than 20 descriptors in combination were important for the biomagnification of OCs and BFRs between herring and guillemot. The model including all contaminants (R2X=0.73, R2Y=0.87 and Q2=0.63, three components) explained approximately as much of the variation as the model with the PCBs alone (R2X=0.83, R2Y=0.87 and Q2=0.58, two components). The model with the BFRs alone (R2X=0.68, R2Y=0.88 and Q2 = 0.41, two components) had a slightly lower Q2 than the model including all contaminants. For validation, a training set of seven contaminants was selected by multivariate design (MVD) and a model was established. This model was then used to predict the BMFs of the test set (seven contaminants not included in the model). The resulting R2 for the regression Observed BMF versus Predicted BMF was high (0.65). The good models showed that descriptors important for the biomagnification of OCs and BFRs had been used. These types of models will be useful for in silico predictions of the biomagnification of new, not yet investigated, compounds as an aid in risk assessments.
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| 10. |
- Torell, Frida, et al.
(författare)
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Metabolic Profiling of Multiorgan Samples : Evaluation of MODY5/RCAD Mutant Mice
- 2018
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 17:7, s. 2293-2306
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Tidskriftsartikel (refereegranskat)abstract
- In the present study, we performed a metabolomics analysis to evaluate a MODY5/RCAD mouse mutant line as a potential model for HNF1B-associated diseases. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) of gut, kidney, liver, muscle, pancreas, and plasma samples uncovered the tissue specific metabolite distribution. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) was used to identify the differences between MODY5/RCAD and wild-type mice in each of the tissues. The differences included, for example, increased levels of amino acids in the kidneys and reduced levels of fatty acids in the muscles of the MODY5/RCAD mice. Interestingly, campesterol was found in higher concentrations in the MODY5/RCAD mice, with a four-fold and three-fold increase in kidneys and pancreas, respectively. As expected, the MODY5/RCAD mice displayed signs of impaired renal function in addition to disturbed liver lipid metabolism, with increased lipid and fatty acid accumulation in the liver. From a metabolomics perspective, the MODY5/RCAD model was proven to display a metabolic pattern similar to what would be suspected in HNF1B-associated diseases. These findings were in line with the presumed outcome of the mutation based on the different anatomy and function of the tissues as well as the effect of the mutation on development.
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