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Sample records for hierarchical metabolomics demonstrates

  1. NMR metabolomics demonstrates phenotypic plasticity of sea buckthorn (Hippophaë rhamnoides) berries with respect to growth conditions in Finland and Canada.

    Science.gov (United States)

    Kortesniemi, Maaria; Sinkkonen, Jari; Yang, Baoru; Kallio, Heikki

    2017-03-15

    The berries of sea buckthorn (Hippophaë rhamnoides ssp. rhamnoides) cultivars 'Terhi' and 'Tytti' were studied with respect to their growth location, 60° and 68°N latitude in Finland and 46°N in Canada, using (1)H NMR metabolomics. The berries of 'Terhi' were characterised by stronger signals of quinic acid, while 'Tytti' had higher levels of O-ethyl β-d-glucopyranoside. The metabolic profile of the northernmost berries was distinctly different from those grown in southern Finland or Canada. Berries from northern Finland had relatively higher levels of quinic acid, glucose, l-quebrachitol and ascorbic acid. Ethyl glucoside was shown to accumulate by several fold at the late stage of maturation in the south as it correlated with degree days (r=0.63) and global radiation (r=0.59), but not in the north. The variance in the composition of the sea buckthorn berries demonstrates plasticity in the acclimatisation to growth environments.

  2. A multi-platform metabolomics approach demonstrates changes in energy metabolism and the transsulfuration pathway in Chironomus tepperi following exposure to zinc

    Energy Technology Data Exchange (ETDEWEB)

    Long, Sara M., E-mail: hoskins@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia); Tull, Dedreia L., E-mail: dedreia@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Jeppe, Katherine J., E-mail: k.jeppe@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia); Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, The University of Melbourne, 3010 (Australia); De Souza, David P., E-mail: desouzad@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Dayalan, Saravanan, E-mail: sdayalan@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Pettigrove, Vincent J., E-mail: vpet@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, The University of Melbourne, 3010 (Australia); McConville, Malcolm J., E-mail: malcolmm@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Hoffmann, Ary A., E-mail: ary@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia); School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia)

    2015-05-15

    Highlights: • An integrated metabolomics approach was applied to examine zinc exposure in midges. • Changes in carbohydrate and energy metabolism were observed using GC–MS. • Transsulfuration pathway is affected by zinc exposure. • Heavy metals other than zinc affect the transsulfuration pathways differently. - Abstract: Measuring biological responses in resident biota is a commonly used approach to monitoring polluted habitats. The challenge is to choose sensitive and, ideally, stressor-specific endpoints that reflect the responses of the ecosystem. Metabolomics is a potentially useful approach for identifying sensitive and consistent responses since it provides a holistic view to understanding the effects of exposure to chemicals upon the physiological functioning of organisms. In this study, we exposed the aquatic non-biting midge, Chironomus tepperi, to two concentrations of zinc chloride and measured global changes in polar metabolite levels using an untargeted gas chromatography–mass spectrometry (GC–MS) analysis and a targeted liquid chromatography–mass spectrometry (LC–MS) analysis of amine-containing metabolites. These data were correlated with changes in the expression of a number of target genes. Zinc exposure resulted in a reduction in levels of intermediates in carbohydrate metabolism (i.e., glucose 6-phosphate, fructose 6-phosphate and disaccharides) and an increase in a number of TCA cycle intermediates. Zinc exposure also resulted in decreases in concentrations of the amine containing metabolites, lanthionine, methionine and cystathionine, and an increase in metallothionein gene expression. Methionine and cystathionine are intermediates in the transsulfuration pathway which is involved in the conversion of methionine to cysteine. These responses provide an understanding of the pathways affected by zinc toxicity, and how these effects are different to other heavy metals such as cadmium and copper. The use of complementary

  3. Metabolomics investigation of whey intake

    DEFF Research Database (Denmark)

    Stanstrup, Jan

    interest since it has been shown that it is possible to achieve greater weight loss on a high protein diet as oppose to a high carbohydrate diet. Furthermore, it has been demonstrated that specifically milk-derived whey proteins have certain biological properties that might be beneficial in the treatment...... and prevention of the metabolic syndrome related to obesity and diabetes. In this thesis the effects of whey intake on the human metabolome was investigated using a metabolomics approach. We demonstrated that intake of whey causes a decreased rate of gastric emptying compared to other protein sources...... prediction. A pipeline combining these tools in a single workflow is described, and the potential impact in the field of metabolomics highlighted....

  4. Nutritional Metabolomics

    DEFF Research Database (Denmark)

    Gürdeniz, Gözde

    of the crucial steps is data preprocessing, which is particularly cumbersome for complex liquid chromatography mass spectrometry (LC-MS) data. Accordingly, in PAPER I, different LC-MS data preprocessing tools, MarkerLynx, MZmine, XCMS and a customised method (spectral binning and chromatographic collapsing) were......Lynx, MZmine and XCMS) and 16 to 40 % were specific to each tool. Two reasons for these differences were pointed out: (1) changing the parameter settings of each software tool has a great impact on the number of detected features; (2) each software tool employs different methods in their peak detection...... and alignment algorithms, such that each has pros and cons. Thus, the use of more than one software tool and/or the use of several parameter settings during data preprocessing are likely to decrease the risk of failing to detect features (potential marker candidates) in untargeted metabolomics. On the other...

  5. Nutritional Metabolomics

    DEFF Research Database (Denmark)

    Gürdeniz, Gözde

    and alignment algorithms, such that each has pros and cons. Thus, the use of more than one software tool and/or the use of several parameter settings during data preprocessing are likely to decrease the risk of failing to detect features (potential marker candidates) in untargeted metabolomics. On the other...... handling, this thesis also deals with biological interpretation of postprandial metabolism and trans fatty acid (TFA) intake. Two nutritional issues were objects of investigation: 1) metabolic states as a function of time since the last meal and 2) markers related to intakes of cis- and trans-fat. Plasma...... to TFA intake (16 weeks) and its depletion (12 weeks) were examined in order to identify metabolic patterns affected by this potentially toxic fat using a parallel intervention study. In addition, the impact of cis- vs. trans-fat intake on a glucose challenge was investigated (PAPER II). The postprandial...

  6. Metabolomics in food science.

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    Cevallos-Cevallos, Juan Manuel; Reyes-De-Corcuera, José Ignacio

    2012-01-01

    Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science.

  7. Probabilistic Principal Component Analysis for Metabolomic Data.

    LENUS (Irish Health Repository)

    Nyamundanda, Gift

    2010-11-23

    Abstract Background Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. Results Here, probabilistic principal component analysis (PPCA) which addresses some of the limitations of PCA, is reviewed and extended. A novel extension of PPCA, called probabilistic principal component and covariates analysis (PPCCA), is introduced which provides a flexible approach to jointly model metabolomic data and additional covariate information. The use of a mixture of PPCA models for discovering the number of inherent groups in metabolomic data is demonstrated. The jackknife technique is employed to construct confidence intervals for estimated model parameters throughout. The optimal number of principal components is determined through the use of the Bayesian Information Criterion model selection tool, which is modified to address the high dimensionality of the data. Conclusions The methods presented are illustrated through an application to metabolomic data sets. Jointly modeling metabolomic data and covariates was successfully achieved and has the potential to provide deeper insight to the underlying data structure. Examination of confidence intervals for the model parameters, such as loadings, allows for principled and clear interpretation of the underlying data structure. A software package called MetabolAnalyze, freely available through the R statistical software, has been developed to facilitate implementation of the presented methods in the metabolomics field.

  8. Metabolomic profiling from formalin-fixed, paraffin-embedded tumor tissue using targeted LC/MS/MS: application in sarcoma.

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    Andrew D Kelly

    Full Text Available The relatively new field of onco-metabolomics attempts to identify relationships between various cancer phenotypes and global metabolite content. Previous metabolomics studies utilized either nuclear magnetic resonance spectroscopy or gas chromatography/mass spectrometry, and analyzed metabolites present in urine and serum. However, direct metabolomic assessment of tumor tissues is important for determining altered metabolism in cancers. In this respect, the ability to obtain reliable data from archival specimens is desirable and has not been reported to date. In this feasibility study, we demonstrate the analysis of polar metabolites extracted directly from ten formalin-fixed, paraffin-embedded (FFPE specimens, including five soft tissue sarcomas and five paired normal samples. Using targeted liquid chromatography-tandem mass spectrometry (LC/MS/MS via selected reaction monitoring (SRM, we detect an average of 106 metabolites across the samples with excellent reproducibility and correlation between different sections of the same specimen. Unsupervised hierarchical clustering and principal components analysis reliably recovers a priori known tumor and normal tissue phenotypes, and supervised analysis identifies candidate metabolic markers supported by the literature. In addition, we find that diverse biochemical processes are well-represented in the list of detected metabolites. Our study supports the notion that reliable and broadly informative metabolomic data may be acquired from FFPE soft tissue sarcoma specimens, a finding that is likely to be extended to other malignancies.

  9. Metabolomics and Epidemiology Working Group

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    The Metabolomics and Epidemiology (MetEpi) Working Group promotes metabolomics analyses in population-based studies, as well as advancement in the field of metabolomics for broader biomedical and public health research.

  10. Cancer Metabolomics and the Human Metabolome Database

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    David S. Wishart

    2016-03-01

    Full Text Available The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB. The HMDB is currently the world’s largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer.

  11. Metabolomics investigation of whey intake

    DEFF Research Database (Denmark)

    Stanstrup, Jan

    syndrome are complex disorders and are not caused by a high-calorie diet and low exercise level alone. The specific nature of the nutrients, independent of their caloric value, also play a role. The question is which. In the quest to answer this question the qualitative intake of protein is of special...... and prevention of the metabolic syndrome related to obesity and diabetes. In this thesis the effects of whey intake on the human metabolome was investigated using a metabolomics approach. We demonstrated that intake of whey causes a decreased rate of gastric emptying compared to other protein sources...... interest since it has been shown that it is possible to achieve greater weight loss on a high protein diet as oppose to a high carbohydrate diet. Furthermore, it has been demonstrated that specifically milk-derived whey proteins have certain biological properties that might be beneficial in the treatment...

  12. The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets

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    Carroll Adam J

    2010-07-01

    Full Text Available Abstract Background Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Description Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.. Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP their own data to the server for online processing via a novel raw data processing pipeline. Conclusions MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to

  13. Metabolomics in hypertension.

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    Nikolic, Sonja B; Sharman, James E; Adams, Murray J; Edwards, Lindsay M

    2014-06-01

    Hypertension is the most prevalent chronic medical condition and a major risk factor for cardiovascular morbidity and mortality. In the majority of hypertensive cases, the underlying cause of hypertension cannot be easily identified because of the heterogeneous, polygenic and multi-factorial nature of hypertension. Metabolomics is a relatively new field of research that has been used to evaluate metabolic perturbations associated with disease, identify disease biomarkers and to both assess and predict drug safety and efficacy. Metabolomics has been increasingly used to characterize risk factors for cardiovascular disease, including hypertension, and it appears to have significant potential for uncovering mechanisms of this complex disease. This review details the analytical techniques, pre-analytical steps and study designs used in metabolomics studies, as well as the emerging role for metabolomics in gaining mechanistic insights into the development of hypertension. Suggestions as to the future direction for metabolomics research in the field of hypertension are also proposed.

  14. Serum metabolomic profiling in acute alcoholic hepatitis identifies multiple dysregulated pathways.

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    Vikrant Rachakonda

    Full Text Available BACKGROUND AND OBJECTIVES: While animal studies have implicated derangements of global energy homeostasis in the pathogenesis of acute alcoholic hepatitis (AAH, the relevance of these findings to the development of human AAH remains unclear. Using global, unbiased serum metabolomics analysis, we sought to characterize alterations in metabolic pathways associated with severe AAH and identify potential biomarkers for disease prognosis. METHODS: This prospective, case-control study design included 25 patients with severe AAH and 25 ambulatory patients with alcoholic cirrhosis. Serum samples were collected within 24 hours of the index clinical encounter. Global, unbiased metabolomics profiling was performed. Patients were followed for 180 days after enrollment to determine survival. RESULTS: Levels of 234 biochemicals were altered in subjects with severe AAH. Random-forest analysis, principal component analysis, and integrated hierarchical clustering methods demonstrated that metabolomics profiles separated the two cohorts with 100% accuracy. Severe AAH was associated with enhanced triglyceride lipolysis, impaired mitochondrial fatty acid beta oxidation, and upregulated omega oxidation. Low levels of multiple lysolipids and related metabolites suggested decreased plasma membrane remodeling in severe AAH. While most measured bile acids were increased in severe AAH, low deoxycholate and glycodeoxycholate levels indicated intestinal dysbiosis. Several changes in substrate utilization for energy homeostasis were identified in severe AAH, including increased glucose consumption by the pentose phosphate pathway, altered tricarboxylic acid (TCA cycle activity, and enhanced peptide catabolism. Finally, altered levels of small molecules related to glutathione metabolism and antioxidant vitamin depletion were observed in patients with severe AAH. Univariable logistic regression revealed 15 metabolites associated with 180-day survival in severe AAH. CONCLUSION

  15. Metabolomics in chemical ecology.

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    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

    Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

  16. The human serum metabolome.

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    Nikolaos Psychogios

    Full Text Available Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.

  17. Current metabolomics: technological advances.

    Science.gov (United States)

    Putri, Sastia P; Yamamoto, Shinya; Tsugawa, Hiroshi; Fukusaki, Eiichiro

    2013-07-01

    Metabolomics, the global quantitative assessment of metabolites in a biological system, has played a pivotal role in various fields of science in the post-genomic era. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression, but also form part of the regulatory system in an integrated manner. Therefore, metabolomics is often considered a powerful tool to provide an instantaneous snapshot of the physiology of a cell. The power of metabolomics lies on the acquisition of analytical data in which metabolites in a cellular system are quantified, and the extraction of the most meaningful elements of the data by using various data analysis tool. In this review, we discuss the latest development of analytical techniques and data analyses methods in metabolomics study.

  18. Metabolomics in dyslipidemia.

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    Chen, Hua; Miao, Hua; Feng, Ya-Long; Zhao, Ying-Yong; Lin, Rui-Chao

    2014-01-01

    Hyperlipidemia is an important public health problem with increased incidence and prevalence worldwide. Current clinical biomarkers, triglyceride, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol lack the necessary specificity and sensitivity and only increase significantly after serious dyslipidemia. Therefore, sensitive biomarkers are needed for hyperlipidemia. Hyperlipidemia-specific biomarkers would improve clinical diagnosis and therapeutic treatment at early disease stages. The aim of metabolomics is to identify untargeted and global small-molecule metabolite profiles from cells, biofluids, and tissues. This method offers the potential for a holistic approach to improve disease diagnoses and our understanding of underlying pathologic mechanisms. This review summarizes analytical techniques, data collection and analysis for metabolomics, and metabolomics in hyperlipidemia animal models and clinical studies. Mechanisms of hypolipemia and antilipemic drug therapy are also discussed. Metabolomics provides a new opportunity to gain insight into metabolic profiling and pathophysiologic mechanisms of hyperlipidemia.

  19. The food metabolome

    DEFF Research Database (Denmark)

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine

    2014-01-01

    The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according...... to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food...... by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still...

  20. Metabolomics and protozoan parasites.

    Science.gov (United States)

    Paget, Timothy; Haroune, Nicolas; Bagchi, Sushmita; Jarroll, Edward

    2013-06-01

    In this review, we examine the state-of-the-art technologies (gas and liquid chromatography, mass spectroscopy and nuclear magnetic resonance, etc.) in the well-established area of metabolomics especially as they relate to protozoan parasites.

  1. Metabolomics er fremtiden

    DEFF Research Database (Denmark)

    Pedersern, Birger

    2010-01-01

    Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet......Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet...

  2. Quality assurance of metabolomics.

    Science.gov (United States)

    Bouhifd, Mounir; Beger, Richard; Flynn, Thomas; Guo, Lining; Harris, Georgina; Hogberg, Helena; Kaddurah-Daouk, Rima; Kamp, Hennicke; Kleensang, Andre; Maertens, Alexandra; Odwin-DaCosta, Shelly; Pamies, David; Robertson, Donald; Smirnova, Lena; Sun, Jinchun; Zhao, Liang; Hartung, Thomas

    2015-01-01

    Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.

  3. Metabolomic change precedes apple superficial scald symptoms.

    Science.gov (United States)

    Rudell, David R; Mattheis, James P; Hertog, Maarten L A T M

    2009-09-23

    Untargeted metabolic profiling was employed to characterize metabolomic changes associated with 'Granny Smith' apple superficial scald development following 1-MCP or DPA treatment. Partial least-squares discriminant analyses were used to link metabolites with scald, postharvest treatments, and storage duration. Models revealed metabolomic differentiation between untreated controls and fruit treated with DPA or 1-MCP within 1 week following storage initiation. Metabolic divergence between controls and DPA-treated fruit after 4 weeks of storage preceded scald symptom development by 2 months. alpha-Farnesene oxidation products with known associations to scald, including conjugated trienols, 6-methyl-5-hepten-2-one, and 6-methyl-5-hepten-2-ol, were associated with presymptomatic as well as scalded control fruit. Likewise, a large group of putative triterpenoids with mass spectral features similar to those of ursolic acid and beta-sitosterol were associated with control fruit and scald. Results demonstrate that extensive metabolomic changes associated with scald precede actual symptom development.

  4. Unintended effects in genetically modified crops: revealed by metabolomics?

    Science.gov (United States)

    Rischer, Heiko; Oksman-Caldentey, Kirsi-Marja

    2006-03-01

    In Europe the commercialization of food derived from genetically modified plants has been slow because of the complex regulatory process and the concerns of consumers. Risk assessment is focused on potential adverse effects on humans and the environment, which could result from unintended effects of genetic modifications: unintended effects are connected to changes in metabolite levels in the plants. One of the major challenges is how to analyze the overall metabolite composition of GM plants in comparison to conventional cultivars, and one possible solution is offered by metabolomics. The ultimate aim of metabolomics is the identification and quantification of all small molecules in an organism; however, a single method enabling complete metabolome analysis does not exist. Given a comprehensive extraction method, a hierarchical strategy--starting with global fingerprinting and followed by complementary profiling attempts--is the most logical and economic approach to detect unintended effects in GM crops.

  5. New electromigration-driven enrichment techniques for peptidomics and metabolomics

    NARCIS (Netherlands)

    Lindenburg, Petrus Wilhelmus

    2012-01-01

    In thesis the power of electrophoretic on-line concentration procedures for peptidomics and metabolomics is demonstrated. Tow examples are given: isotachophoresis with spacer molecules and electroextraction. Electromigration is capable of enhancing selective analyte migration. Selective analyte migr

  6. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard;

    2012-01-01

    a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure......Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  7. Hierarchical photocatalysts.

    Science.gov (United States)

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

    As a green and sustainable technology, semiconductor-based heterogeneous photocatalysis has received much attention in the last few decades because it has potential to solve both energy and environmental problems. To achieve efficient photocatalysts, various hierarchical semiconductors have been designed and fabricated at the micro/nanometer scale in recent years. This review presents a critical appraisal of fabrication methods, growth mechanisms and applications of advanced hierarchical photocatalysts. Especially, the different synthesis strategies such as two-step templating, in situ template-sacrificial dissolution, self-templating method, in situ template-free assembly, chemically induced self-transformation and post-synthesis treatment are highlighted. Finally, some important applications including photocatalytic degradation of pollutants, photocatalytic H2 production and photocatalytic CO2 reduction are reviewed. A thorough assessment of the progress made in photocatalysis may open new opportunities in designing highly effective hierarchical photocatalysts for advanced applications ranging from thermal catalysis, separation and purification processes to solar cells.

  8. Multi-Organ Contribution to the Metabolic Plasma Profile Using Hierarchical Modelling.

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    Frida Torell

    Full Text Available Hierarchical modelling was applied in order to identify the organs that contribute to the levels of metabolites in plasma. Plasma and organ samples from gut, kidney, liver, muscle and pancreas were obtained from mice. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC TOF-MS at the Swedish Metabolomics centre, Umeå University, Sweden. The multivariate analysis was performed by means of principal component analysis (PCA and orthogonal projections to latent structures (OPLS. The main goal of this study was to investigate how each organ contributes to the metabolic plasma profile. This was performed using hierarchical modelling. Each organ was found to have a unique metabolic profile. The hierarchical modelling showed that the gut, kidney and liver demonstrated the greatest contribution to the metabolic pattern of plasma. For example, we found that metabolites were absorbed in the gut and transported to the plasma. The kidneys excrete branched chain amino acids (BCAAs and fatty acids are transported in the plasma to the muscles and liver. Lactic acid was also found to be transported from the pancreas to plasma. The results indicated that hierarchical modelling can be utilized to identify the organ contribution of unknown metabolites to the metabolic profile of plasma.

  9. Metabolomics Reveals Metabolic Alterations by Intrauterine Growth Restriction in the Fetal Rabbit Brain

    Science.gov (United States)

    van Vliet, Erwin; Eixarch, Elisenda; Illa, Miriam; Arbat-Plana, Ariadna; González-Tendero, Anna; Hogberg, Helena T.; Zhao, Liang; Hartung, Thomas; Gratacos, Eduard

    2013-01-01

    Background Intrauterine Growth Restriction (IUGR) due to placental insufficiency occurs in 5–10% of pregnancies and is a major risk factor for abnormal neurodevelopment. The perinatal diagnosis of IUGR related abnormal neurodevelopment represents a major challenge in fetal medicine. The development of clinical biomarkers is considered a promising approach, but requires the identification of biochemical/molecular alterations by IUGR in the fetal brain. This targeted metabolomics study in a rabbit IUGR model aimed to obtain mechanistic insight into the effects of IUGR on the fetal brain and identify metabolite candidates for biomarker development. Methodology/Principal Findings At gestation day 25, IUGR was induced in two New Zealand rabbits by 40–50% uteroplacental vessel ligation in one horn and the contralateral horn was used as control. At day 30, fetuses were delivered by Cesarian section, weighed and brains collected for metabolomics analysis. Results showed that IUGR fetuses had a significantly lower birth and brain weight compared to controls. Metabolomics analysis using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) and database matching identified 78 metabolites. Comparison of metabolite intensities using a t-test demonstrated that 18 metabolites were significantly different between control and IUGR brain tissue, including neurotransmitters/peptides, amino acids, fatty acids, energy metabolism intermediates and oxidative stress metabolites. Principle component and hierarchical cluster analysis showed cluster formations that clearly separated control from IUGR brain tissue samples, revealing the potential to develop predictive biomarkers. Moreover birth weight and metabolite intensity correlations indicated that the extent of alterations was dependent on the severity of IUGR. Conclusions IUGR leads to metabolic alterations in the fetal rabbit brain, involving neuronal viability, energy metabolism, amino acid levels, fatty

  10. Metabolomics reveals metabolic alterations by intrauterine growth restriction in the fetal rabbit brain.

    Directory of Open Access Journals (Sweden)

    Erwin van Vliet

    Full Text Available BACKGROUND: Intrauterine Growth Restriction (IUGR due to placental insufficiency occurs in 5-10% of pregnancies and is a major risk factor for abnormal neurodevelopment. The perinatal diagnosis of IUGR related abnormal neurodevelopment represents a major challenge in fetal medicine. The development of clinical biomarkers is considered a promising approach, but requires the identification of biochemical/molecular alterations by IUGR in the fetal brain. This targeted metabolomics study in a rabbit IUGR model aimed to obtain mechanistic insight into the effects of IUGR on the fetal brain and identify metabolite candidates for biomarker development. METHODOLOGY/PRINCIPAL FINDINGS: At gestation day 25, IUGR was induced in two New Zealand rabbits by 40-50% uteroplacental vessel ligation in one horn and the contralateral horn was used as control. At day 30, fetuses were delivered by Cesarian section, weighed and brains collected for metabolomics analysis. Results showed that IUGR fetuses had a significantly lower birth and brain weight compared to controls. Metabolomics analysis using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS and database matching identified 78 metabolites. Comparison of metabolite intensities using a t-test demonstrated that 18 metabolites were significantly different between control and IUGR brain tissue, including neurotransmitters/peptides, amino acids, fatty acids, energy metabolism intermediates and oxidative stress metabolites. Principle component and hierarchical cluster analysis showed cluster formations that clearly separated control from IUGR brain tissue samples, revealing the potential to develop predictive biomarkers. Moreover birth weight and metabolite intensity correlations indicated that the extent of alterations was dependent on the severity of IUGR. CONCLUSIONS: IUGR leads to metabolic alterations in the fetal rabbit brain, involving neuronal viability, energy metabolism, amino

  11. Microbial metabolomics in open microscale platforms

    Science.gov (United States)

    Barkal, Layla J.; Theberge, Ashleigh B.; Guo, Chun-Jun; Spraker, Joe; Rappert, Lucas; Berthier, Jean; Brakke, Kenneth A.; Wang, Clay C. C.; Beebe, David J.; Keller, Nancy P.; Berthier, Erwin

    2016-01-01

    The microbial secondary metabolome encompasses great synthetic diversity, empowering microbes to tune their chemical responses to changing microenvironments. Traditional metabolomics methods are ill-equipped to probe a wide variety of environments or environmental dynamics. Here we introduce a class of microscale culture platforms to analyse chemical diversity of fungal and bacterial secondary metabolomes. By leveraging stable biphasic interfaces to integrate microculture with small molecule isolation via liquid–liquid extraction, we enable metabolomics-scale analysis using mass spectrometry. This platform facilitates exploration of culture microenvironments (including rare media typically inaccessible using established methods), unusual organic solvents for metabolite isolation and microbial mutants. Utilizing Aspergillus, a fungal genus known for its rich secondary metabolism, we characterize the effects of culture geometry and growth matrix on secondary metabolism, highlighting the potential use of microscale systems to unlock unknown or cryptic secondary metabolites for natural products discovery. Finally, we demonstrate the potential for this class of microfluidic systems to study interkingdom communication between fungi and bacteria. PMID:26842393

  12. The Role of Metabolomics in Brain Metabolism Research.

    Science.gov (United States)

    Ivanisevic, Julijana; Siuzdak, Gary

    2015-09-01

    This special edition of the Journal of Neuroimmune Pharmacology focuses on the leading edge of metabolomics in brain metabolism research. The topics covered include a metabolomic field overview and the challenges in neuroscience metabolomics. The workflow and utility of different analytical platforms to profile complex biological matrices that include biofluids, brain tissue and cells, are shown in several case studies. These studies demonstrate how global and targeted metabolite profiling can be applied to distinguish disease stages and to understand the effects of drug action on the central nervous system (CNS). Finally, we discuss the importance of metabolomics to advance the understanding of brain function that includes ligand-receptor interactions and new insights into the mechanisms of CNS disorders.

  13. Determination of antiprotozoal drug mechanisms by metabolomics approaches.

    Science.gov (United States)

    Creek, Darren J; Barrett, Michael P

    2014-01-01

    The discovery, development and optimal utilization of pharmaceuticals can be greatly enhanced by knowledge of their modes of action. However, many drugs currently on the market act by unknown mechanisms. Untargeted metabolomics offers the potential to discover modes of action for drugs that perturb cellular metabolism. Development of high resolution LC-MS methods and improved data analysis software now allows rapid detection of drug-induced changes to cellular metabolism in an untargeted manner. Several studies have demonstrated the ability of untargeted metabolomics to provide unbiased target discovery for antimicrobial drugs, in particular for antiprotozoal agents. Furthermore, the utilization of targeted metabolomics techniques has enabled validation of existing hypotheses regarding antiprotozoal drug mechanisms. Metabolomics approaches are likely to assist with optimization of new drug candidates by identification of drug targets, and by allowing detailed characterization of modes of action and resistance of existing and novel antiprotozoal drugs.

  14. Metabolomics: a state-of-the-art technology for better understanding of male infertility.

    Science.gov (United States)

    Minai-Tehrani, A; Jafarzadeh, N; Gilany, K

    2016-08-01

    Male factor infertility affects approximately half of the infertile couples, in spite of many years of research on male infertility treatment and diagnosis; several outstanding questions remain to be addressed. In this regard, metabolomics as a novel field of omics has been suggested to be applied for male infertility problems. A variety of terms associated with metabolite quantity and quality have been established to demonstrate mixtures of metabolites. Despite metabolomics and metabolite analyses have been around more than decades, a limited number of studies concerning male infertility have been carried out. In this review, we summarised the latest finding in metabolomics techniques and metabolomics biomarkers correlated with male infertility. The rapid progress of a variety of metabolomics platforms, such as nonoptical and optical spectroscopy, could ease separation, recognition, classification and quantification of several metabolites and their metabolic pathways. Here, we recommend that the novel biomarkers determined in the course of metabolomics analysis may stand for potential application of treatment and future clinical practice.

  15. Metabolomics in asthma.

    Science.gov (United States)

    Luxon, Bruce A

    2014-01-01

    Asthma and airway inflammation are responses to infectious stimuli and the mechanisms of how they are mediated, whether by the innate or adaptive immune response systems, are complex and results in a broad spectrum of possible metabolic products. In principle, a syndrome such as asthma should have a characteristic temporal-spatial metabolic signature indicative of its current state and the constituents that caused it. Generally, the term metabolomics refers to the quantitative analysis of sets of small compounds from biological samples with molecular masses less than 1 kDa so unambiguous identification can be difficult and usually requires sophisticated instrumentation. The practical success of clinical metabolomics will largely hinge on a few key issues such as the ability to capture a readily available biofluid that can be analyzed to identify metabolite biomarkers with the required sensitivity and specificity in a cost-effective manner in a clinical setting. In this chapter, we review the current state of the metabolomics of asthma and airway inflammation with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and their future translation into the clinic as diagnostic aids for the choice of patient-specific therapies.

  16. Solving the differential biochemical Jacobian from metabolomics covariance data.

    Science.gov (United States)

    Nägele, Thomas; Mair, Andrea; Sun, Xiaoliang; Fragner, Lena; Teige, Markus; Weckwerth, Wolfram

    2014-01-01

    High-throughput molecular analysis has become an integral part in organismal systems biology. In contrast, due to a missing systematic linkage of the data with functional and predictive theoretical models of the underlying metabolic network the understanding of the resulting complex data sets is lacking far behind. Here, we present a biomathematical method addressing this problem by using metabolomics data for the inverse calculation of a biochemical Jacobian matrix, thereby linking computer-based genome-scale metabolic reconstruction and in vivo metabolic dynamics. The incongruity of metabolome coverage by typical metabolite profiling approaches and genome-scale metabolic reconstruction was solved by the design of superpathways to define a metabolic interaction matrix. A differential biochemical Jacobian was calculated using an approach which links this metabolic interaction matrix and the covariance of metabolomics data satisfying a Lyapunov equation. The predictions of the differential Jacobian from real metabolomic data were found to be correct by testing the corresponding enzymatic activities. Moreover it is demonstrated that the predictions of the biochemical Jacobian matrix allow for the design of parameter optimization strategies for ODE-based kinetic models of the system. The presented concept combines dynamic modelling strategies with large-scale steady state profiling approaches without the explicit knowledge of individual kinetic parameters. In summary, the presented strategy allows for the identification of regulatory key processes in the biochemical network directly from metabolomics data and is a fundamental achievement for the functional interpretation of metabolomics data.

  17. The human urine metabolome.

    Directory of Open Access Journals (Sweden)

    Souhaila Bouatra

    Full Text Available Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS, direct flow injection mass spectrometry (DFI/LC-MS/MS, inductively coupled plasma mass spectrometry (ICP-MS and high performance liquid chromatography (HPLC experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify a total of: 209 (209 by NMR, 179 (85 by GC-MS, 127 (127 by DFI/LC-MS/MS, 40 (40 by ICP-MS and 10 (10 by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database

  18. Livestock metabolomics and the livestock metabolome: A systematic review

    Science.gov (United States)

    Guo, An Chi; Sajed, Tanvir; Steele, Michael A.; Plastow, Graham S.; Wishart, David S.

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed. PMID:28531195

  19. Metabolomic imaging of prostate cancer with magnetic resonance spectroscopy and mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Spur, Eva-Margarete [Massachusetts General Hospital, Harvard Medical School, Department of Pathology, Boston, MA (United States); Massachusetts General Hospital, Harvard Medical School, Department of Radiology, Boston, MA (United States); Charite Universitaetsmedizin, Berlin (Germany); Decelle, Emily A.; Cheng, Leo L. [Massachusetts General Hospital, Harvard Medical School, Department of Pathology, Boston, MA (United States); Massachusetts General Hospital, Harvard Medical School, Department of Radiology, Boston, MA (United States)

    2013-07-15

    Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized noninvasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth in patients with asymptomatic PCa newly diagnosed by biopsy. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, PCa metabolomics is mainly studied by magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates has demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies has uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness noninvasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be applied not only to PCa, but also to different tissues and organs to evaluate other human malignancies and metabolic diseases. (orig.)

  20. Metabolomics protocols for filamentous fungi.

    Science.gov (United States)

    Gummer, Joel P A; Krill, Christian; Du Fall, Lauren; Waters, Ormonde D C; Trengove, Robert D; Oliver, Richard P; Solomon, Peter S

    2012-01-01

    Proteomics and transcriptomics are established functional genomics tools commonly used to study filamentous fungi. Metabolomics has recently emerged as another option to complement existing techniques and provide detailed information on metabolic regulation and secondary metabolism. Here, we describe broad generic protocols that can be used to undertake metabolomics studies in filamentous fungi.

  1. Analysis of longitudinal metabolomics data

    NARCIS (Netherlands)

    Jansen, J.J.; Hoefsloot, H.C.J.; Boelens, H.F.M.; Greef, J. van der; Smilde, A.K.

    2004-01-01

    Motivation: Metabolomics datasets are generally large and complex. Using principal component analysis (PCA), a simplified view of the variation in the data is obtained. The PCA model can be interpreted and the processes underlying the variation in the data can be analysed. In metabolomics, often a p

  2. Genome-enabled plant metabolomics.

    Science.gov (United States)

    Tohge, Takayuki; de Souza, Leonardo Perez; Fernie, Alisdair R

    2014-09-01

    The grand challenge currently facing metabolomics is that of comprehensitivity whilst next generation sequencing and advanced proteomics methods now allow almost complete and at least 50% coverage of their respective target molecules, metabolomics platforms at best offer coverage of just 10% of the small molecule complement of the cell. Here we discuss the use of genome sequence information as an enabling tool for peak identity and for translational metabolomics. Whilst we argue that genome information is not sufficient to compute the size of a species metabolome it is highly useful in predicting the occurrence of a wide range of common metabolites. Furthermore, we describe how via gene functional analysis in model species the identity of unknown metabolite peaks can be resolved. Taken together these examples suggest that genome sequence information is current (and likely will remain), a highly effective tool in peak elucidation in mass spectral metabolomics strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Hierarchical manifold learning.

    Science.gov (United States)

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Jo; Rueckert, Daniel

    2012-01-01

    We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,

  4. Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

    Science.gov (United States)

    Yu, Tao; Wang, Yongtao; Zhang, Huizhen; Johnson, Caroline H; Jiang, Yiming; Li, Xiangjun; Wu, Zeming; Liu, Tian; Krausz, Kristopher W; Yu, Aiming; Gonzalez, Frank J; Huang, Min; Bi, Huichang

    2016-06-01

    Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

  5. Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 3. Untargeted metabolomics.

    Science.gov (United States)

    Thomas, Funmilola Clara; Mudaliar, Manikhandan; Tassi, Riccardo; McNeilly, Tom N; Burchmore, Richard; Burgess, Karl; Herzyk, Pawel; Zadoks, Ruth N; Eckersall, P David

    2016-08-16

    Intramammary infection leading to bovine mastitis is the leading disease problem affecting dairy cows and has marked effects on the milk produced by infected udder quarters. An experimental model of Streptococcus uberis mastitis has previously been investigated for clinical, immunological and pathophysiological alteration in milk, and has been the subject of peptidomic and quantitative proteomic investigation. The same sample set has now been investigated with a metabolomics approach using liquid chromatography and mass spectrometry. The analysis revealed over 3000 chromatographic peaks, of which 690 were putatively annotated with a metabolite. Hierarchical clustering analysis and principal component analysis demonstrated that metabolite changes due to S. uberis infection were maximal at 81 hours post challenge with metabolites in the milk from the resolution phase at 312 hours post challenge being closest to the pre-challenge samples. Metabolic pathway analysis revealed that the majority of the metabolites mapped to carbohydrate and nucleotide metabolism show a decreasing trend in concentration up to 81 hours post-challenge whereas an increasing trend was found in lipid metabolites and di-, tri- and tetra-peptides up to the same time point. The increase in these peptides coincides with an increase in larger peptides found in the previous peptidomic analysis and is likely to be due to protease degradation of milk proteins. Components of bile acid metabolism, linked to the FXR pathway regulating inflammation, were also increased. Metabolomic analysis of the response in milk during mastitis provides an essential component to the full understanding of the mammary gland's response to infection.

  6. Metabolomics of Genetically Modified Crops

    Science.gov (United States)

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-01-01

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade. PMID:25334064

  7. Metabolomics of Genetically Modified Crops

    Directory of Open Access Journals (Sweden)

    Carolina Simó

    2014-10-01

    Full Text Available Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

  8. Metabolomics of genetically modified crops.

    Science.gov (United States)

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-10-20

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

  9. NMR-based metabolomics applications

    DEFF Research Database (Denmark)

    Iaccarino, Nunzia

    focused on the analysis of various samples covering a wide range of fields, namely, food and nutraceutical sciences, cell metabolomics and medicine using a metabolomics approach. Indeed, the first part of the thesis describes two exploratory studies performed on Algerian extra virgin olive oil and apple...... the appropriate use of these nutraceutical products. The last study explores the differences in the follicular fluid metabolome of hyper- and normoinsulinemic women affected with Polycystic Ovary Syndrome (PCOS). The study provides preliminary but interesting relationships between serum hormones and metabolites...

  10. Metabolomics in diabetes.

    Science.gov (United States)

    Zhang, Ai-hua; Qiu, Shi; Xu, Hong-ying; Sun, Hui; Wang, Xi-jun

    2014-02-15

    Characterization of metabolic changes is key to early detection, treatment, and understanding molecular mechanisms of diabetes. Diabetes represents one of the most important global health problems. Approximately 90% of diabetics have type 2 diabetes. Identification of effective screening markers is critical for early treatment and intervention that can delay and/or prevent complications associated with this chronic disease. Fortunately, metabolomics has introduced new insights into the pathology of diabetes as well as to predict disease onset and revealed new biomarkers to improve diagnostics in a range of diseases. Small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand T2D phenotypes. Characteristic patterns of metabolites can be revealed that broaden our understanding of T2D disorder. This technique-driven review aims to demystify the mechanisms of T2D, to provide updates on the applications of metabolomics in addressing T2D with a focus on metabolites based biomarker discovery. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Metabolomics in diabetic complications.

    Science.gov (United States)

    Filla, Laura A; Edwards, James L

    2016-04-01

    With a global prevalence of 9%, diabetes is the direct cause of millions of deaths each year and is quickly becoming a health crisis. Major long-term complications of diabetes arise from persistent oxidative stress and dysfunction in multiple metabolic pathways. The most serious complications involve vascular damage and include cardiovascular disease as well as microvascular disorders such as nephropathy, neuropathy, and retinopathy. Current clinical analyses like glycated hemoglobin and plasma glucose measurements hold some value as prognostic indicators of the severity of complications, but investigations into the underlying pathophysiology are still lacking. Advancements in biotechnology hold the key to uncovering new pathways and establishing therapeutic targets. Metabolomics, the study of small endogenous molecules, is a powerful toolset for studying pathophysiological processes and has been used to elucidate metabolic signatures of diabetes in various biological systems. Current challenges in the field involve correlating these biomarkers to specific complications to provide a better prediction of future risk and disease progression. This review will highlight the progress that has been made in the field of metabolomics including technological advancements, the identification of potential biomarkers, and metabolic pathways relevant to macro- and microvascular diabetic complications.

  12. The biology of plant metabolomics

    NARCIS (Netherlands)

    Hall, R.D.

    2011-01-01

    Following a general introduction, this book includes details of metabolomics of model species including Arabidopsis and tomato. Further chapters provide in-depth coverage of abiotic stress, data integration, systems biology, genetics, genomics, chemometrics and biostatisitcs. Applications of plant m

  13. Computational approaches for systems metabolomics.

    Science.gov (United States)

    Krumsiek, Jan; Bartel, Jörg; Theis, Fabian J

    2016-06-01

    Systems genetics is defined as the simultaneous assessment and analysis of multi-omics datasets. In the past few years, metabolomics has been established as a robust tool describing an important functional layer in this approach. The metabolome of a biological system represents an integrated state of genetic and environmental factors and has been referred to as a 'link between genotype and phenotype'. In this review, we summarize recent progresses in statistical analysis methods for metabolomics data in combination with other omics layers. We put a special focus on complex, multivariate statistical approaches as well as pathway-based and network-based analysis methods. Moreover, we outline current challenges and pitfalls of metabolomics-focused multi-omics analyses and discuss future steps for the field.

  14. Metabolomics Workbench (MetWB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Metabolomics Program's Data Repository and Coordinating Center (DRCC), housed at the San Diego Supercomputer Center (SDSC), University of California, San Diego,...

  15. Metabolomics of Genetically Modified Crops

    OpenAIRE

    2014-01-01

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resul...

  16. Prospects of implant with locking plate in fixation of subtrochanteric fracture: experimental demonstration of its potential benefits on synthetic femur model with supportive hierarchical nonlinear hyperelastic finite element analysis

    Directory of Open Access Journals (Sweden)

    Latifi Mohammed

    2012-04-01

    Full Text Available Abstract Background Effective fixation of fracture requires careful selection of a suitable implant to provide stability and durability. Implant with a feature of locking plate (LP has been used widely for treating distal fractures in femur because of its favourable clinical outcome, but its potential in fixing proximal fractures in the subtrochancteric region has yet to be explored. Therefore, this comparative study was undertaken to demonstrate the merits of the LP implant in treating the subtrochancteric fracture by comparing its performance limits against those obtained with the more traditional implants; angle blade plate (ABP and dynamic condylar screw plate (DCSP. Materials and Methods Nine standard composite femurs were acquired, divided into three groups and fixed with LP (n = 3, ABP (n = 3 and DCSP (n = 3. The fracture was modeled by a 20 mm gap created at the subtrochanteric region to experimentally study the biomechanical response of each implant under both static and dynamic axial loading paradigms. To confirm the experimental findings and to understand the critical interactions at the boundaries, the synthetic femur/implant systems were numerically analyzed by constructing hierarchical finite element models with nonlinear hyperelastic properties. The predictions from the analyses were then compared against the experimental measurements to demonstrate the validity of each numeric model, and to characterize the internal load distribution in the femur and load bearing properties of each implant. Results The average measurements indicated that the constructs with ABP, DCPS and LP respectively had overall stiffness values of 70.9, 110.2 and 131.4 N/mm, and exhibited reversible deformations of 12.4, 4.9 and 4.1 mm when the applied dynamic load was 400 N and plastic deformations of 11.3, 2.4 and 1.4 mm when the load was 1000 N. The corresponding peak cyclic loads to failure were 1100, 1167 and 1600 N. The errors

  17. A Metabolomic Perspective on Coeliac Disease

    NARCIS (Netherlands)

    Calabrò, A.; Gralka, E.; Luchinat, C.; Saccenti, E.; Tenori, L.

    2014-01-01

    Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already pr

  18. The next wave in metabolome analysis

    DEFF Research Database (Denmark)

    Nielsen, Jens; Oliver, S.

    2005-01-01

    to the genome makes it difficult to interpret metabolomic data. Nevertheless, functional genomics has produced examples of the use of metabolomics to elucidate the phenotypes of otherwise silent mutations. Despite several successes, we believe that future metabolomic studies must focus on the accurate...

  19. Metabolomic fingerprint of heart failure with preserved ejection fraction.

    Directory of Open Access Journals (Sweden)

    Beshay N Zordoky

    Full Text Available Heart failure (HF with preserved ejection fraction (HFpEF is increasingly recognized as an important clinical entity. Preclinical studies have shown differences in the pathophysiology between HFpEF and HF with reduced ejection fraction (HFrEF. Therefore, we hypothesized that a systematic metabolomic analysis would reveal a novel metabolomic fingerprint of HFpEF that will help understand its pathophysiology and assist in establishing new biomarkers for its diagnosis.Ambulatory patients with clinical diagnosis of HFpEF (n = 24, HFrEF (n = 20, and age-matched non-HF controls (n = 38 were selected for metabolomic analysis as part of the Alberta HEART (Heart Failure Etiology and Analysis Research Team project. 181 serum metabolites were quantified by LC-MS/MS and 1H-NMR spectroscopy. Compared to non-HF control, HFpEF patients demonstrated higher serum concentrations of acylcarnitines, carnitine, creatinine, betaine, and amino acids; and lower levels of phosphatidylcholines, lysophosphatidylcholines, and sphingomyelins. Medium and long-chain acylcarnitines and ketone bodies were higher in HFpEF than HFrEF patients. Using logistic regression, two panels of metabolites were identified that can separate HFpEF patients from both non-HF controls and HFrEF patients with area under the receiver operating characteristic (ROC curves of 0.942 and 0.981, respectively.The metabolomics approach employed in this study identified a unique metabolomic fingerprint of HFpEF that is distinct from that of HFrEF. This metabolomic fingerprint has been utilized to identify two novel panels of metabolites that can separate HFpEF patients from both non-HF controls and HFrEF patients.ClinicalTrials.gov NCT02052804.

  20. Metabolomic Fingerprint of Heart Failure with Preserved Ejection Fraction

    Science.gov (United States)

    Zordoky, Beshay N.; Sung, Miranda M.; Ezekowitz, Justin; Mandal, Rupasri; Han, Beomsoo; Bjorndahl, Trent C.; Bouatra, Souhaila; Anderson, Todd; Oudit, Gavin Y.; Wishart, David S.; Dyck, Jason R. B.

    2015-01-01

    Background Heart failure (HF) with preserved ejection fraction (HFpEF) is increasingly recognized as an important clinical entity. Preclinical studies have shown differences in the pathophysiology between HFpEF and HF with reduced ejection fraction (HFrEF). Therefore, we hypothesized that a systematic metabolomic analysis would reveal a novel metabolomic fingerprint of HFpEF that will help understand its pathophysiology and assist in establishing new biomarkers for its diagnosis. Methods and Results Ambulatory patients with clinical diagnosis of HFpEF (n = 24), HFrEF (n = 20), and age-matched non-HF controls (n = 38) were selected for metabolomic analysis as part of the Alberta HEART (Heart Failure Etiology and Analysis Research Team) project. 181 serum metabolites were quantified by LC-MS/MS and 1H-NMR spectroscopy. Compared to non-HF control, HFpEF patients demonstrated higher serum concentrations of acylcarnitines, carnitine, creatinine, betaine, and amino acids; and lower levels of phosphatidylcholines, lysophosphatidylcholines, and sphingomyelins. Medium and long-chain acylcarnitines and ketone bodies were higher in HFpEF than HFrEF patients. Using logistic regression, two panels of metabolites were identified that can separate HFpEF patients from both non-HF controls and HFrEF patients with area under the receiver operating characteristic (ROC) curves of 0.942 and 0.981, respectively. Conclusions The metabolomics approach employed in this study identified a unique metabolomic fingerprint of HFpEF that is distinct from that of HFrEF. This metabolomic fingerprint has been utilized to identify two novel panels of metabolites that can separate HFpEF patients from both non-HF controls and HFrEF patients. Clinical Trial Registration ClinicalTrials.gov NCT02052804 PMID:26010610

  1. Metabolomics: moving towards personalized medicine

    Directory of Open Access Journals (Sweden)

    Reniero Fabiano

    2009-10-01

    Full Text Available Abstract In many fields of medicine there is a growing interest in characterizing diseases at molecular level with a view to developing an individually tailored therapeutic approach. Metabolomics is a novel area that promises to contribute significantly to the characterization of various disease phenotypes and to the identification of personal metabolic features that can predict response to therapies. Based on analytical platforms such as mass spectrometry or NMR-based spectroscopy, the metabolomic approach enables a comprehensive overview of the metabolites, leading to the characterization of the metabolic fingerprint of a given sample. These metabolic fingerprints can then be used to distinguish between different disease phenotypes and to predict a drug's effectiveness and/or toxicity. Several studies published in the last few years applied the metabolomic approach in the field of pediatric medicine. Being a highly informative technique that can be used on samples collected non-invasively (e.g. urine or exhaled breath condensate, metabolomics has appeal for the study of pediatric diseases. Here we present and discuss the pediatric clinical studies that have taken the metabolomic approach.

  2. Food metabolomics: from farm to human.

    Science.gov (United States)

    Kim, Sooah; Kim, Jungyeon; Yun, Eun Ju; Kim, Kyoung Heon

    2016-02-01

    Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans.

  3. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...

  4. The Human Blood Metabolome-Transcriptome Interface

    Science.gov (United States)

    Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

    2015-01-01

    Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

  5. The Human Blood Metabolome-Transcriptome Interface.

    Directory of Open Access Journals (Sweden)

    Jörg Bartel

    2015-06-01

    Full Text Available Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the 'human blood metabolome-transcriptome interface' (BMTI. Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease.

  6. Metabolomics techniques in nanotoxicology studies.

    Science.gov (United States)

    Schnackenberg, Laura K; Sun, Jinchun; Beger, Richard D

    2012-01-01

    The rapid growth in the development of nanoparticles for uses in a variety of applications including targeted drug delivery, cancer therapy, imaging, and as biological sensors has led to questions about potential toxicity of such particles to humans. High-throughput methods are necessary to evaluate the potential toxicity of nanoparticles. The omics technologies are particularly well suited to evaluate toxicity in both in vitro and in vivo systems. Metabolomics, specifically, can rapidly screen for biomarkers related to predefined pathways or processes in biofluids and tissues. Specifically, oxidative stress has been implicated as a potential mechanism of toxicity in nanoparticles and is generally difficult to measure by conventional methods. Furthermore, metabolomics can provide mechanistic insight into nanotoxicity. This chapter focuses on the application of both LC/MS and NMR-based metabolomics approaches to study the potential toxicity of nanoparticles.

  7. Preprocessing of NMR metabolomics data.

    Science.gov (United States)

    Euceda, Leslie R; Giskeødegård, Guro F; Bathen, Tone F

    2015-05-01

    Metabolomics involves the large scale analysis of metabolites and thus, provides information regarding cellular processes in a biological sample. Independently of the analytical technique used, a vast amount of data is always acquired when carrying out metabolomics studies; this results in complex datasets with large amounts of variables. This type of data requires multivariate statistical analysis for its proper biological interpretation. Prior to multivariate analysis, preprocessing of the data must be carried out to remove unwanted variation such as instrumental or experimental artifacts. This review aims to outline the steps in the preprocessing of NMR metabolomics data and describe some of the methods to perform these. Since using different preprocessing methods may produce different results, it is important that an appropriate pipeline exists for the selection of the optimal combination of methods in the preprocessing workflow.

  8. A systems-level "misunderstanding": the plasma metabolome in Huntington's disease.

    Science.gov (United States)

    Rosas, Herminia D; Doros, Gheorghe; Bhasin, Swati; Thomas, Beena; Gevorkian, Sona; Malarick, Keith; Matson, Wayne; Hersch, Steven M

    2015-07-01

    Huntington's disease (HD) is a rare neurodegenerative disease caused by the expansion of an N-terminal repeat in the huntingtin protein. The protein is expressed in all cells in the body; hence, peripheral tissues, such as blood, may recapitulate processes in the brain. The plasma metabolome may provide a window into active processes that influence brain health and a unique opportunity to noninvasively identify processes that may contribute to neurodegeneration. Alterations in metabolic pathways in brain have been shown to profoundly impact HD. Therefore, identification and quantification of critical metabolomic perturbations could provide novel biomarkers for disease onset and disease progression. We analyzed the plasma metabolomic profiles from 52 premanifest (PHD), 102 early symptomatic HD, and 140 healthy controls (NC) using liquid chromatography coupled with a highly sensitive electrochemical detection platform. Alterations in tryptophan, tyrosine, purine, and antioxidant pathways were identified, including many related to energetic and oxidative stress and derived from the gut microbiome. Multivariate statistical modeling demonstrated mutually distinct metabolomic profiles, suggesting that the processes that determine onset were likely distinct from those that determine progression. Gut microbiome-derived metabolites particularly differentiated the PHD metabolome, while the symptomatic HD metabolome was increasingly influenced by metabolites that may reflect mutant huntingtin toxicity and neurodegeneration. Understanding the complex changes in the delicate balance of the metabolome and the gut microbiome in HD, and how they relate to disease onset, progression, and phenotypic variability in HD are critical questions for future research.

  9. Hierarchical Multiagent Reinforcement Learning

    Science.gov (United States)

    2004-01-25

    In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In

  10. COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access.

    Science.gov (United States)

    Salek, Reza M; Neumann, Steffen; Schober, Daniel; Hummel, Jan; Billiau, Kenny; Kopka, Joachim; Correa, Elon; Reijmers, Theo; Rosato, Antonio; Tenori, Leonardo; Turano, Paola; Marin, Silvia; Deborde, Catherine; Jacob, Daniel; Rolin, Dominique; Dartigues, Benjamin; Conesa, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; O'Hagan, Steve; Hao, Jie; van Vliet, Michael; Sysi-Aho, Marko; Ludwig, Christian; Bouwman, Jildau; Cascante, Marta; Ebbels, Timothy; Griffin, Julian L; Moing, Annick; Nikolski, Macha; Oresic, Matej; Sansone, Susanna-Assunta; Viant, Mark R; Goodacre, Royston; Günther, Ulrich L; Hankemeier, Thomas; Luchinat, Claudio; Walther, Dirk; Steinbeck, Christoph

    Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative 'coordination of standards in metabolomics' (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities' participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.

  11. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...

  12. Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate.

    Directory of Open Access Journals (Sweden)

    Biswapriya B Misra

    Full Text Available Anthropogenic CO2 presently at 400 ppm is expected to reach 550 ppm in 2050, an increment expected to affect plant growth and productivity. Paired stomatal guard cells (GCs are the gate-way for water, CO2, and pathogen, while mesophyll cells (MCs represent the bulk cell-type of green leaves mainly for photosynthesis. We used the two different cell types, i.e., GCs and MCs from canola (Brassica napus to profile metabolomic changes upon increased CO2 through supplementation with bicarbonate (HCO3-. Two metabolomics platforms enabled quantification of 268 metabolites in a time-course study to reveal short-term responses. The HCO3- responsive metabolomes of the cell types differed in their responsiveness. The MCs demonstrated increased amino acids, phenylpropanoids, redox metabolites, auxins and cytokinins, all of which were decreased in GCs in response to HCO3-. In addition, the GCs showed differential increases of primary C-metabolites, N-metabolites (e.g., purines and amino acids, and defense-responsive pathways (e.g., alkaloids, phenolics, and flavonoids as compared to the MCs, indicating differential C/N homeostasis in the cell-types. The metabolomics results provide insights into plant responses and crop productivity under future climatic changes where elevated CO2 conditions are to take center-stage.

  13. Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate.

    Science.gov (United States)

    Misra, Biswapriya B; de Armas, Evaldo; Tong, Zhaohui; Chen, Sixue

    2015-01-01

    Anthropogenic CO2 presently at 400 ppm is expected to reach 550 ppm in 2050, an increment expected to affect plant growth and productivity. Paired stomatal guard cells (GCs) are the gate-way for water, CO2, and pathogen, while mesophyll cells (MCs) represent the bulk cell-type of green leaves mainly for photosynthesis. We used the two different cell types, i.e., GCs and MCs from canola (Brassica napus) to profile metabolomic changes upon increased CO2 through supplementation with bicarbonate (HCO3-). Two metabolomics platforms enabled quantification of 268 metabolites in a time-course study to reveal short-term responses. The HCO3- responsive metabolomes of the cell types differed in their responsiveness. The MCs demonstrated increased amino acids, phenylpropanoids, redox metabolites, auxins and cytokinins, all of which were decreased in GCs in response to HCO3-. In addition, the GCs showed differential increases of primary C-metabolites, N-metabolites (e.g., purines and amino acids), and defense-responsive pathways (e.g., alkaloids, phenolics, and flavonoids) as compared to the MCs, indicating differential C/N homeostasis in the cell-types. The metabolomics results provide insights into plant responses and crop productivity under future climatic changes where elevated CO2 conditions are to take center-stage.

  14. NMR-Based Milk Metabolomics

    Directory of Open Access Journals (Sweden)

    Hanne C. Bertram

    2013-04-01

    Full Text Available Milk is a key component in infant nutrition worldwide and, in the Western parts of the world, also in adult nutrition. Milk of bovine origin is both consumed fresh and processed into a variety of dairy products including cheese, fermented milk products, and infant formula. The nutritional quality and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR-based metabolomics trends in milk research, including applications linking the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining a better understanding of how milk composition is linked to nutritional or quality traits.

  15. Metabolomic Approaches in Cancer Epidemiology

    Directory of Open Access Journals (Sweden)

    Mukesh Verma

    2015-08-01

    Full Text Available Metabolomics is the study of low molecular weight molecules or metabolites produced within cells and biological systems. It involves technologies such as mass spectrometry (MS and nuclear magnetic resonance spectroscopy (NMR that can measure hundreds of thousands of unique chemical entities (UCEs. The metabolome provides one of the most accurate reflections of cellular activity at the functional level and can be leveraged to discern mechanistic information during normal and disease states. The advantages of metabolomics over other “omics” include its high sensitivity and ability to enable the analysis of relatively few metabolites compared with the number of genes and messenger RNAs (mRNAs. In clinical samples, metabolites are more stable than proteins or RNA. In fact, metabolomic profiling in basic, epidemiologic, clinical, and translational studies has revealed potential new biomarkers of disease and therapeutic outcome and has led to a novel mechanistic understanding of pathogenesis. These potential biomarkers include novel metabolites associated with cancer initiation, regression, and recurrence. Unlike genomics or even proteomics, however, the degree of metabolite complexity and heterogeneity within biological systems presents unique challenges that require specialized skills and resources to overcome. This article discusses epidemiologic studies of altered metabolite profiles in several cancers as well as challenges in the field and potential approaches to overcoming them.

  16. Metabolomic systems biology of trypanosomes

    NARCIS (Netherlands)

    Barrett, Michael P.; Bakker, Barbara M.; Breitling, Rainer

    Metabolomics analysis, which aims at the systematic identification and quantification of all metabolites in biological systems, is emerging as a powerful new tool to identify biomarkers of disease, report on cellular responses to environmental perturbation, and to identify the targets of drugs. Here

  17. Hierarchical Affinity Propagation

    CERN Document Server

    Givoni, Inmar; Frey, Brendan J

    2012-01-01

    Affinity propagation is an exemplar-based clustering algorithm that finds a set of data-points that best exemplify the data, and associates each datapoint with one exemplar. We extend affinity propagation in a principled way to solve the hierarchical clustering problem, which arises in a variety of domains including biology, sensor networks and decision making in operational research. We derive an inference algorithm that operates by propagating information up and down the hierarchy, and is efficient despite the high-order potentials required for the graphical model formulation. We demonstrate that our method outperforms greedy techniques that cluster one layer at a time. We show that on an artificial dataset designed to mimic the HIV-strain mutation dynamics, our method outperforms related methods. For real HIV sequences, where the ground truth is not available, we show our method achieves better results, in terms of the underlying objective function, and show the results correspond meaningfully to geographi...

  18. Recent advances of metabolomics in plant biotechnology.

    Science.gov (United States)

    Okazaki, Yozo; Saito, Kazuki

    2012-01-01

    Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants.

  19. LC-MS-based metabolomics: an update.

    Science.gov (United States)

    Fang, Zhong-Ze; Gonzalez, Frank J

    2014-08-01

    Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics can have a major impact in multiple research fields, especially when combined with other technologies, such as stable isotope tracers and genetically modified mice. This review highlights recent applications of metabolomic technology in the study of xenobiotic metabolism and toxicity, and the understanding of disease pathogenesis and therapeutics. Metabolomics has been employed to study metabolism of noscapine, an aryl hydrocarbon receptor antagonist, and to determine the mechanisms of liver toxicities of rifampicin and isoniazid, trichloroethylene, and gemfibrozil. Metabolomics-based insights into the pathogenesis of inflammatory bowel disease, alcohol-induced liver diseases, non-alcoholic steatohepatitis, and farnesoid X receptor signaling pathway-based therapeutic target discovery will also be discussed. Limitations in metabolomics technology such as sample preparation and lack of LC-MS databases and metabolite standards, need to be resolved in order to improve and broaden the application of metabolomic studies.

  20. Metabolomics of Apc Min/+ mice genetically susceptible to intestinal cancer

    Science.gov (United States)

    2014-01-01

    Background To determine how diets high in saturated fat could increase polyp formation in the mouse model of intestinal neoplasia, Apc Min/+ , we conducted large-scale metabolome analysis and association study of colon and small intestine polyp formation from plasma and liver samples of Apc Min/+ vs. wild-type littermates, kept on low vs. high-fat diet. Label-free mass spectrometry was used to quantify untargeted plasma and acyl-CoA liver compounds, respectively. Differences in contrasts of interest were analyzed statistically by unsupervised and supervised modeling approaches, namely Principal Component Analysis and Linear Model of analysis of variance. Correlation between plasma metabolite concentrations and polyp numbers was analyzed with a zero-inflated Generalized Linear Model. Results Plasma metabolome in parallel to promotion of tumor development comprises a clearly distinct profile in Apc Min/+ mice vs. wild type littermates, which is further altered by high-fat diet. Further, functional metabolomics pathway and network analyses in Apc Min/+ mice on high-fat diet revealed associations between polyp formation and plasma metabolic compounds including those involved in amino-acids metabolism as well as nicotinamide and hippuric acid metabolic pathways. Finally, we also show changes in liver acyl-CoA profiles, which may result from a combination of Apc Min/+ -mediated tumor progression and high fat diet. The biological significance of these findings is discussed in the context of intestinal cancer progression. Conclusions These studies show that high-throughput metabolomics combined with appropriate statistical modeling and large scale functional approaches can be used to monitor and infer changes and interactions in the metabolome and genome of the host under controlled experimental conditions. Further these studies demonstrate the impact of diet on metabolic pathways and its relation to intestinal cancer progression. Based on our results, metabolic signatures

  1. Functional metabolomics reveals novel active products in the DHA metabolome

    Directory of Open Access Journals (Sweden)

    Masakazu eShinohara

    2012-04-01

    Full Text Available Endogenous mechanisms for successful resolution of an acute inflammatory response and the local return to homeostasis are of interest because excessive inflammation underlies many human diseases. In this review, we provide an update and overview of functional metabolomics that identified a new bioactive metabolome of docosahexaenoic acid (DHA. Systematic studies revealed that DHA was converted to DHEA-derived novel bioactive products as well as aspirin-triggered (AT forms of protectins. The new oxygenated DHEA derived products blocked PMN chemotaxis, reduced P-selectin expression and platelet-leukocyte adhesion, and showed organ protection in ischemia/reperfusion injury. These products activated cannabinoid receptor (CB2 receptor and not CB1 receptors. The AT-PD1 reduced neutrophil (PMN recruitment in murine peritonitis. With human cells, AT-PD1 decreased transendothelial PMN migration as well as enhanced efferocytosis of apoptotic human PMN by macrophages. The recent findings reviewed here indicate that DHEA oxidative metabolism and aspirin-triggered conversion of DHA produce potent novel molecules with anti-inflammatory and organ-protective properties, opening the DHA metabolome functional roles.

  2. Urinary metabolomic fingerprinting after consumption of a probiotic strain in women with mastitis.

    Science.gov (United States)

    Vázquez-Fresno, Rosa; Llorach, Rafael; Marinic, Jelena; Tulipani, Sara; Garcia-Aloy, Mar; Espinosa-Martos, Irene; Jiménez, Esther; Rodríguez, Juan Miguel; Andres-Lacueva, Cristina

    2014-09-01

    Infectious mastitis is a common condition among lactating women, with staphylococci and streptococci being the main aetiological agents. In this context, some lactobacilli strains isolated from breast milk appear to be particularly effective for treating mastitis and, therefore, constitute an attractive alternative to antibiotherapy. A (1)H NMR-based metabolomic approach was applied to detect metabolomic differences after consuming a probiotic strain (Lactobacillus salivarius PS2) in women with mastitis. 24h urine of women with lactational mastitis was collected at baseline and after 21 days of probiotic (PB) administration. Multivariate analysis (OSC-PLS-DA and hierarchical clustering) showed metabolome differences after PB treatment. The discriminant metabolites detected at baseline were lactose, and ibuprofen and acetaminophen (two pharmacological drugs commonly used for mastitis pain), while, after PB intake, creatine and the gut microbial co-metabolites hippurate and TMAO were detected. In addition, a voluntary desertion of the pharmacological drugs ibuprofen and acetaminophen was observed after probiotic administration. The application of NMR-based metabolomics enabled the identification of the overall effects of probiotic consumption among women suffering from mastitis and highlighted the potential of this approach in evaluating the outcomes of probiotics consumption. To our knowledge, this is the first time that this approach has been applied in women with mastitis during lactation. Copyright © 2014. Published by Elsevier Ltd.

  3. NMR-based milk metabolomics

    DEFF Research Database (Denmark)

    Sundekilde, Ulrik; Larsen, Lotte Bach; Bertram, Hanne Christine S.

    2013-01-01

    Milk is a key component in infant nutrition worldwide and, in the Western parts of the world, also in adult nutrition. Milk of bovine origin is both consumed fresh and processed into a variety of dairy products including cheese, fermented milk products, and infant formula. The nutritional quality...... and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking...... the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive...

  4. Visualization of Multivariate Metabolomic Data

    Institute of Scientific and Technical Information of China (English)

    ZHOU Jun; CAO Bei; ZHENG Tian; LIU Lin-sheng; GUO Sheng; DUAN Jin-ao; AA Ji-ye; WANG Guang-ji; ZHANG Feng-yi; GU Rong-rong; WANG Xin-wen; ZHAO Chun-yan; LI Meng-jie; SHI Jian

    2011-01-01

    Objective Although principal components analysis profiles greatly facilitate the visualization and interpretation of the multivariate data,the quantitative concepts in both scores plot and loading plot are rather obscure.This article introduced three profiles that assisted the better understanding of metabolomic data.Methods The discriminatory profile,heat map,and statistic profile were developed to visualize the multivariate data obtained from high-throughput GC-TOF-MS analysis.Results The discriminatory profile and heat map obviously showed the discriminatory metabolites between the two groups,while the statistic profile showed the potential markers of statistic significance.Conclusion The three types of profiles greatly facilitate our understanding of the metabolomic data and the identification of the potential markers.

  5. Plasma metabolomic profiles enhance precision medicine for volunteers of normal health.

    Science.gov (United States)

    Guo, Lining; Milburn, Michael V; Ryals, John A; Lonergan, Shaun C; Mitchell, Matthew W; Wulff, Jacob E; Alexander, Danny C; Evans, Anne M; Bridgewater, Brandi; Miller, Luke; Gonzalez-Garay, Manuel L; Caskey, C Thomas

    2015-09-01

    Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care.

  6. Hierarchical self-organization of tectonic plates

    OpenAIRE

    2010-01-01

    The Earth's surface is subdivided into eight large tectonic plates and many smaller ones. We reconstruct the plate tessellation history and demonstrate that both large and small plates display two distinct hierarchical patterns, described by different power-law size-relationships. While small plates display little organisational change through time, the structure of the large plates oscillate between minimum and maximum hierarchical tessellations. The organization of large plates rapidly chan...

  7. Hierarchical Nanoceramics for Industrial Process Sensors

    Energy Technology Data Exchange (ETDEWEB)

    Ruud, James, A.; Brosnan, Kristen, H.; Striker, Todd; Ramaswamy, Vidya; Aceto, Steven, C.; Gao, Yan; Willson, Patrick, D.; Manoharan, Mohan; Armstrong, Eric, N., Wachsman, Eric, D.; Kao, Chi-Chang

    2011-07-15

    This project developed a robust, tunable, hierarchical nanoceramics materials platform for industrial process sensors in harsh-environments. Control of material structure at multiple length scales from nano to macro increased the sensing response of the materials to combustion gases. These materials operated at relatively high temperatures, enabling detection close to the source of combustion. It is anticipated that these materials can form the basis for a new class of sensors enabling widespread use of efficient combustion processes with closed loop feedback control in the energy-intensive industries. The first phase of the project focused on materials selection and process development, leading to hierarchical nanoceramics that were evaluated for sensing performance. The second phase focused on optimizing the materials processes and microstructures, followed by validation of performance of a prototype sensor in a laboratory combustion environment. The objectives of this project were achieved by: (1) synthesizing and optimizing hierarchical nanostructures; (2) synthesizing and optimizing sensing nanomaterials; (3) integrating sensing functionality into hierarchical nanostructures; (4) demonstrating material performance in a sensing element; and (5) validating material performance in a simulated service environment. The project developed hierarchical nanoceramic electrodes for mixed potential zirconia gas sensors with increased surface area and demonstrated tailored electrocatalytic activity operable at high temperatures enabling detection of products of combustion such as NOx close to the source of combustion. Methods were developed for synthesis of hierarchical nanostructures with high, stable surface area, integrated catalytic functionality within the structures for gas sensing, and demonstrated materials performance in harsh lab and combustion gas environments.

  8. Symbiosis of chemometrics and metabolomics: Past, present, and future

    NARCIS (Netherlands)

    Greef, J. van der; Smilde, A.K.

    2005-01-01

    Metabolomics is a growing area in the field of systems biology. Metabolomics has already a long history and also the connection of metabolomics with chemometrics goes back some time. This review discusses the symbiosis of metabolomics and chemometrics with emphasis on the medical domain, puts the co

  9. Recent advances in plant metabolomics and greener pastures.

    Science.gov (United States)

    Sumner, Lloyd W

    2010-01-27

    Metabolomics is an extension of the omics concept and experimental approaches. However, is metabolomics just another trendy omics fashion perturbation or is metabolomics actually delivering novel content and value? This article highlights some recent advances that definitely support the role of plant metabolomics in the movement toward greener pastures.

  10. A Metabolomic Perspective on Coeliac Disease

    Science.gov (United States)

    Calabrò, Antonio

    2014-01-01

    Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD) revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism. PMID:24665364

  11. Getting the right answers: understanding metabolomics challenges.

    Science.gov (United States)

    Beisken, Stephan; Eiden, Michael; Salek, Reza M

    2015-01-01

    Small molecules within biological systems provide powerful insights into the biological roles, processes and states of organisms. Metabolomics is the study of the concentrations, structures and interactions of these thousands of small molecules, collectively known as the metabolome. Metabolomics is at the interface between chemistry, biology, statistics and computer science, requiring multidisciplinary skillsets. This presents unique challenges for researchers to fully utilize the information produced and to capture its potential diagnostic power. A good understanding of study design, sample preparation, analysis methods and data analysis is essential to get the right answers for the right questions. We outline the current state of the art, benefits and challenges of metabolomics to create an understanding of metabolomics studies from the experimental design to data analysis.

  12. Metabolomics and bioactive substances in plants

    DEFF Research Database (Denmark)

    Khakimov, Bekzod

    Metabolomic analysis of plants broadens understanding of how plants may benefit humans, animals and the environment, provide sustainable food and energy, and improve current agricultural, pharmacological and medicinal practices in order to bring about healthier and longer life. The quality...... and amount of the extractible biological information is largely determined by data acquisition, data processing and analysis methodologies of the plant metabolomics studies. This PhD study focused mainly on the development and implementation of new metabolomics methodologies for improved data acquisition...... and data processing. The study mainly concerned the three most commonly applied analytical techniques in plant metabolomics, GC-MS, LC-MS and NMR. In addition, advanced chemometrics methods e.g. PARAFAC2 and ASCA have been extensively used for development of complex metabolomics data processing...

  13. A Metabolomic Perspective on Coeliac Disease

    Directory of Open Access Journals (Sweden)

    Antonio Calabrò

    2014-01-01

    Full Text Available Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism.

  14. Metabolomic Analysis of the Skeletal Muscle of Mice Overexpressing PGC-1α.

    Directory of Open Access Journals (Sweden)

    Yukino Hatazawa

    Full Text Available Peroxisome proliferator-activated receptor (PPAR γ coactivator 1α (PGC-1α is a coactivator of various nuclear receptors and other transcription factors whose expression increases in the skeletal muscle during exercise. We have previously made transgenic mice overexpressing PGC-1α in the skeletal muscle (PGC-1α-Tg mice. PGC-1α upregulates the expression of genes associated with red fibers, mitochondrial function, fatty acid oxidation, and branched chain amino acid (BCAA degradation. However, global analyses of the actual metabolic products have not been investigated. In this study, we conducted metabolomic analysis of the skeletal muscle in PGC-1α-Tg mice by capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry. Principal component analysis and hierarchical cluster analysis showed clearly distinguishable changes in the metabolites between PGC-1α-Tg and wild-type control mice. Changes were observed in metabolite levels of various metabolic pathways such as the TCA cycle, pentose phosphate pathway, nucleotide synthesis, purine nucleotide cycle, and amino acid metabolism, including BCAA and β-alanine. Namely, metabolic products of the TCA cycle increased in PGC-1α-Tg mice, with increased levels of citrate (2.3-fold, succinate (2.2-fold, fumarate (2.8-fold, and malate (2.3-fold observed. Metabolic products associated with the pentose phosphate pathway and nucleotide biosynthesis also increased in PGC-1α-Tg mice. Meanwhile, BCAA levels decreased (Val, 0.7-fold; Leu, 0.8-fold; and Ile, 0.7-fold, and Glu (3.1-fold and Asp (2.2-fold levels increased. Levels of β-alanine and related metabolites were markedly decreased in PGC-1α-Tg mice. Coordinated regulation of the TCA cycle and amino acid metabolism, including BCAA, suggests that PGC-1α plays important roles in energy metabolism. Moreover, our metabolomics data showing the activation of the purine nucleotide pathway, malate-aspartate shuttle, as well as

  15. A metabolomic approach to animal vitreous humor topographical composition: a pilot study.

    Directory of Open Access Journals (Sweden)

    Emanuela Locci

    Full Text Available The purpose of this study was to evaluate the feasibility of a (1H-NMR-based metabolomic approach to explore the metabolomic signature of different topographical areas of vitreous humor (VH in an animal model. Five ocular globes were enucleated from five goats and immediately frozen at -80 °C. Once frozen, three of them were sectioned, and four samples corresponding to four different VH areas were collected: the cortical, core, and basal, which was further divided into a superior and an inferior fraction. An additional two samples were collected that were representative of the whole vitreous body. (1H-NMR spectra were acquired for twenty-three goat vitreous samples with the aim of characterizing the metabolomic signature of this biofluid and identifying whether any site-specific patterns were present. Multivariate statistical analysis (MVA of the spectral data were carried out, including Principal Component Analysis (PCA, Hierarchical Cluster Analysis (HCA, and Partial Least Squares Discriminant Analysis (PLS-DA. A unique metabolomic signature belonging to each area was observed. The cortical area was characterized by lactate, glutamine, choline, and its derivatives, N-acetyl groups, creatine, and glycerol; the core area was characterized by glucose, acetate, and scyllo-inositol; and the basal area was characterized by branched-chain amino acids (BCAA, betaine, alanine, ascorbate, lysine, and myo-inositol. We propose a speculative approach on the topographic role of these molecules that are mainly responsible for metabolic differences among the as-identified areas. (1H-NMR-based metabolomic analysis has shown to be an important tool for investigating the VH. In particular, this approach was able to assess in the samples here analyzed the presence of different functional areas on the basis of a different metabolite distribution.

  16. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  17. Hierarchical auxetic mechanical metamaterials.

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I; Azzopardi, Keith M; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N

    2015-02-11

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  18. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  19. Hierarchical Auxetic Mechanical Metamaterials

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

    2015-02-01

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  20. Applied Bayesian Hierarchical Methods

    CERN Document Server

    Congdon, Peter D

    2010-01-01

    Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.

  1. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  2. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  3. Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

    Science.gov (United States)

    Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

    2017-07-12

    Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Metabolomics reveals insect metabolic responses associated with fungal infection.

    Science.gov (United States)

    Xu, Yong-Jiang; Luo, Feifei; Gao, Qiang; Shang, Yanfang; Wang, Chengshu

    2015-06-01

    The interactions between insects and pathogenic fungi are complex. We employed metabolomic techniques to profile insect metabolic dynamics upon infection by the pathogenic fungus Beauveria bassiana. Silkworm larvae were infected with fungal spores and microscopic observations demonstrated that the exhaustion of insect hemocytes was coupled with fungal propagation in the insect body cavity. Metabolomic analyses revealed that fungal infection could significantly alter insect energy and nutrient metabolisms as well as the immune defense responses, including the upregulation of carbohydrates, amino acids, fatty acids, and lipids, but the downregulation of eicosanoids and amines. The insect antifeedant effect of the fungal infection was evident with the reduced level of maclurin (a component of mulberry leaves) in infected insects but elevated accumulations in control insects. Insecticidal and cytotoxic mycotoxins like oosporein and beauveriolides were also detected in insects at the later stages of infection. Taken together, the metabolomics data suggest that insect immune responses are energy-cost reactions and the strategies of nutrient deprivation, inhibition of host immune responses, and toxin production would be jointly employed by the fungus to kill insects. The data obtained in this study will facilitate future functional studies of genes and pathways associated with insect-fungus interactions.

  5. Neonatal Metabolomic Profiles Related to Prenatal Arsenic Exposure.

    Science.gov (United States)

    Laine, Jessica E; Bailey, Kathryn A; Olshan, Andrew F; Smeester, Lisa; Drobná, Zuzana; Stýblo, Miroslav; Douillet, Christelle; García-Vargas, Gonzalo; Rubio-Andrade, Marisela; Pathmasiri, Wimal; McRitchie, Susan; Sumner, Susan J; Fry, Rebecca C

    2017-01-03

    Prenatal inorganic arsenic (iAs) exposure is associated with health effects evident at birth and later in life. An understanding of the relationship between prenatal iAs exposure and alterations in the neonatal metabolome could reveal critical molecular modifications, potentially underpinning disease etiologies. In this study, nuclear magnetic resonance (NMR) spectroscopy-based metabolomic analysis was used to identify metabolites in neonate cord serum associated with prenatal iAs exposure in participants from the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort, in Gómez Palacio, Mexico. Through multivariable linear regression, ten cord serum metabolites were identified as significantly associated with total urinary iAs and/or iAs metabolites, measured as %iAs, %monomethylated arsenicals (MMAs), and %dimethylated arsenicals (DMAs). A total of 17 metabolites were identified as significantly associated with total iAs and/or iAs metabolites in cord serum. These metabolites are indicative of changes in important biochemical pathways such as vitamin metabolism, the citric acid (TCA) cycle, and amino acid metabolism. These data highlight that maternal biotransformation of iAs and neonatal levels of iAs and its metabolites are associated with differences in neonate cord metabolomic profiles. The results demonstrate the potential utility of metabolites as biomarkers/indicators of in utero environmental exposure.

  6. Metabolomics in neonatology: fact or fiction?

    Science.gov (United States)

    Fanos, V; Van den Anker, J; Noto, A; Mussap, M; Atzori, L

    2013-02-01

    The newest 'omics' science is metabolomics, the latest offspring of genomics, considered the most innovative of the 'omics' sciences. Metabolomics, also called the 'new clinical biochemistry', is an approach based on the systematic study of the complete set of metabolites in a biological sample. The metabolome is considered the most predictive phenotype and is capable of considering epigenetic differences. It is so close to the phenotype that it can be considered the phenotype itself. In the last three years about 5000 papers have been listed in PubMed on this topic, but few data are available in the newborn. The aim of this review, after a description of background and technical procedures, is to analyse the clinical applications of metabolomics in neonatology, covering the following points: gestational age, postnatal age, type of delivery, zygosity, perinatal asphyxia, intrauterine growth restriction, prenatal inflammation and brain injury, respiratory, cardiovascular renal, metabolic diseases; sepsis, necrotizing enterocolitis and antibiotic treatment; nutritional studies on maternal milk and formula, pharma-metabolomics, long-term diseases. Pros and cons of metabolomics are also discussed. All this comes about with the non-invasive collection of a few drops of urine (exceptionally important for the neonate, especially those of low birth weight). Only time and large-scale studies to validate initial results will place metabolomics within neonatology. In any case, it is important for perinatologists to learn and understand this new technology to offer their patients the utmost in diagnostic and therapeutic opportunities.

  7. Metabolomics for Biomarker Discovery in Gastroenterological Cancer

    Science.gov (United States)

    Nishiumi, Shin; Suzuki, Makoto; Kobayashi, Takashi; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

    2014-01-01

    The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis. PMID:25003943

  8. Impact of storage conditions on the urinary metabolomics fingerprint.

    Science.gov (United States)

    Laparre, Jérôme; Kaabia, Zied; Mooney, Mark; Buckley, Tom; Sherry, Mark; Le Bizec, Bruno; Dervilly-Pinel, Gaud

    2017-01-25

    Urine stability during storage is essential in metabolomics to avoid misleading conclusions or erroneous interpretations. Facing the lack of comprehensive studies on urine metabolome stability, the present work performed a follow-up of potential modifications in urinary chemical profile using LC-HRMS on the basis of two parameters: the storage temperature (+4 °C, -20 °C, -80 °C and freeze-dried stored at -80 °C) and the storage duration (5-144 days). Both HILIC and RP chromatographies have been implemented in order to globally monitor the urinary metabolome. Using an original data processing associated to univariate and multivariate data analysis, our study confirms that chemical profiles of urine samples stored at +4 °C are very rapidly modified, as observed for instance for compounds such as:N-acetyl Glycine, Adenosine, 4-Amino benzoic acid, N-Amino diglycine, creatine, glucuronic acid, 3-hydroxy-benzoic acid, pyridoxal, l-pyroglutamic acid, shikimic acid, succinic acid, thymidine, trigonelline and valeryl-carnitine, while it also demonstrates that urine samples stored at -20 °C exhibit a global stability over a long period with no major modifications compared to -80 °C condition. This study is the first to investigate long term stability of urine samples and report potential modifications in the urinary metabolome, using both targeted approach monitoring individually a large number (n > 200) of urinary metabolites and an untargeted strategy enabling assessing for global impact of storage conditions.

  9. anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data

    Directory of Open Access Journals (Sweden)

    Zamboni Nicola

    2008-04-01

    Full Text Available Abstract Background Compared to other omics techniques, quantitative metabolomics is still at its infancy. Complex sample preparation and analytical procedures render exact quantification extremely difficult. Furthermore, not only the actual measurement but also the subsequent interpretation of quantitative metabolome data to obtain mechanistic insights is still lacking behind the current expectations. Recently, the method of network-embedded thermodynamic (NET analysis was introduced to address some of these open issues. Building upon principles of thermodynamics, this method allows for a quality check of measured metabolite concentrations and enables to spot metabolic reactions where active regulation potentially controls metabolic flux. So far, however, widespread application of NET analysis in metabolomics labs was hindered by the absence of suitable software. Results We have developed in Matlab a generalized software called 'anNET' that affords a user-friendly implementation of the NET analysis algorithm. anNET supports the analysis of any metabolic network for which a stoichiometric model can be compiled. The model size can span from a single reaction to a complete genome-wide network reconstruction including compartments. anNET can (i test quantitative data sets for thermodynamic consistency, (ii predict metabolite concentrations beyond the actually measured data, (iii identify putative sites of active regulation in the metabolic reaction network, and (iv help in localizing errors in data sets that were found to be thermodynamically infeasible. We demonstrate the application of anNET with three published Escherichia coli metabolome data sets. Conclusion Our user-friendly and generalized implementation of the NET analysis method in the software anNET allows users to rapidly integrate quantitative metabolome data obtained from virtually any organism. We envision that use of anNET in labs working on quantitative metabolomics will provide the

  10. MetaboLyzer: a novel statistical workflow for analyzing Postprocessed LC-MS metabolomics data.

    Science.gov (United States)

    Mak, Tytus D; Laiakis, Evagelia C; Goudarzi, Maryam; Fornace, Albert J

    2014-01-07

    Metabolomics, the global study of small molecules in a particular system, has in the past few years risen to become a primary -omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer's workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography-mass spectrometry (LC-MS)-based metabolomic data sets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to γ radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a total of

  11. Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A.

    Science.gov (United States)

    Nagato, Edward G; Simpson, André J; Simpson, Myrna J

    2016-01-01

    (1)H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of (1)H NMR spectra were used to screen metabolome changes after 48h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009-0.135 μg/L), while for malathion the second lowest (0.08μg/L) and two highest exposure concentrations (0.32μg/L and 0.47μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045μg/L and 0.09μg/L) and malathion (0.08μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by changes in the metabolome. For BPA exposures, the PCA scores plot showed a significant change in metabolome at 0.1mg/L, 1.4mg/L and 2.1mg/L of exposure. Individual metabolite changes from 0.7 to 2.1mg/L of BPA exposure showed increases in amino acids such as alanine, valine, isoleucine, leucine, arginine, phenylalanine and

  12. Onboard hierarchical network

    Science.gov (United States)

    Tunesi, Luca; Armbruster, Philippe

    2004-02-01

    The objective of this paper is to demonstrate a suitable hierarchical networking solution to improve capabilities and performances of space systems, with significant recurrent costs saving and more efficient design & manufacturing flows. Classically, a satellite can be split in two functional sub-systems: the platform and the payload complement. The platform is in charge of providing power, attitude & orbit control and up/down-link services, whereas the payload represents the scientific and/or operational instruments/transponders and embodies the objectives of the mission. One major possibility to improve the performance of payloads, by limiting the data return to pertinent information, is to process data on board thanks to a proper implementation of the payload data system. In this way, it is possible to share non-recurring development costs by exploiting a system that can be adopted by the majority of space missions. It is believed that the Modular and Scalable Payload Data System, under development by ESA, provides a suitable solution to fulfil a large range of future mission requirements. The backbone of the system is the standardised high data rate SpaceWire network http://www.ecss.nl/. As complement, a lower speed command and control bus connecting peripherals is required. For instance, at instrument level, there is a need for a "local" low complexity bus, which gives the possibility to command and control sensors and actuators. Moreover, most of the connections at sub-system level are related to discrete signals management or simple telemetry acquisitions, which can easily and efficiently be handled by a local bus. An on-board hierarchical network can therefore be defined by interconnecting high-speed links and local buses. Additionally, it is worth stressing another important aspect of the design process: Agencies and ESA in particular are frequently confronted with a big consortium of geographically spread companies located in different countries, each one

  13. Metabolomics Application in Maternal-Fetal Medicine

    Directory of Open Access Journals (Sweden)

    Vassilios Fanos

    2013-01-01

    Full Text Available Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, preterm delivery, premature rupture of membranes, gestational diabetes mellitus, preeclampsia, neonatal asphyxia, and hypoxic-ischemic encephalopathy. The aim of this review is to summarize and comment on original data available in relevant published works in order to emphasize the clinical potential of metabolomics in obstetrics in the immediate future.

  14. Using metabolomics to evaluate food intake

    DEFF Research Database (Denmark)

    Manach, Claudine; Brennan, Lorraine; Dragsted, Lars Ove

    2015-01-01

    Improving dietary assessment is essential for modern nutritional epidemiology. This chapter discusses the potential of metabolomics for the identification of new biomarkers of intake and presents the first candidate biomarkers discovered using this approach. It then describes the challenges that ...

  15. Metabolomics in Population-Based Research

    Science.gov (United States)

    Metabolomics is the study of small molecules of both endogenous and exogenous origin, such as metabolic substrates and their products, lipids, small peptides, vitamins and other protein cofactors generated by metabolism, which are downstream from genes.

  16. Metabolomics application in maternal-fetal medicine.

    Science.gov (United States)

    Fanos, Vassilios; Atzori, Luigi; Makarenko, Karina; Melis, Gian Benedetto; Ferrazzi, Enrico

    2013-01-01

    Metabolomics in maternal-fetal medicine is still an "embryonic" science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, preterm delivery, premature rupture of membranes, gestational diabetes mellitus, preeclampsia, neonatal asphyxia, and hypoxic-ischemic encephalopathy. The aim of this review is to summarize and comment on original data available in relevant published works in order to emphasize the clinical potential of metabolomics in obstetrics in the immediate future.

  17. Development of quantitative metabolomics for Pichia pastoris

    NARCIS (Netherlands)

    Carnicer,, M.; Canelas, A.B.; Ten Pierick, A.; Zeng, Z.; Van Dam, J.; Albiol, J.; Ferrer, P.; Heijnen, J.J.; Van Gulik, W.

    2011-01-01

    Accurate, reliable and reproducible measurement of intracellular metabolite levels has become important for metabolic studies of microbial cell factories. A first critical step for metabolomic studies is the establishment of an adequate quenching and washing protocol, which ensures effective arrest

  18. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, M.

    1993-07-01

    In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

  19. The metabolome of induced pluripotent stem cells reveals metabolic changes occurring in somatic cell reprogramming

    Institute of Scientific and Technical Information of China (English)

    Athanasia D Panopoulos; Margaret Lutz; W Travis Berggren; Kun Zhang; Ronald M Evans; Gary Siuzdak; Juan Carlos Izpisua Belmonte; Oscar Yanes; SergioRuiz; Yasuyuki S Kida; Dinh Diep; Ralf Tautenhahn; Aida Herrerias; Erika M Batchelder; Nongluk Plongthongkum

    2012-01-01

    Metabolism is vital to every aspect of cell function,yet the metabolome of induced pluripotent stem cells (iPSCs)remains largely unexplored.Here we report,using an untargeted metabolomics approach,that human iPSCs share a pluripotent metabolomic signature with embryonic stem cells (ESCs) that is distinct from their parental cells,and that is characterized by changes in metabolites involved in cellular respiration.Examination of cellular bioenergetics corroborated with our metabolomic analysis,and demonstrated that somatic cells convert from an oxidative state to a glycolytic state in pluripotency.Interestingly,the bioenergetics of various somatic cells correlated with their reprogramming efficiencies.We further identified metabolites that differ between iPSCs and ESCs,which revealed novel metabolic pathways that play a critical role in regulating somatic cell reprogramming.Our findings are the first to globally analyze the metabolome of iPSCs,and provide mechanistic insight into a new layer of regulation involved in inducing pluripotency,and in evaluating iPSC and ESC equivalence.

  20. Potential role of metabolomics in diagnosis and surveillance of gastric cancer.

    Science.gov (United States)

    Chan, Angela W; Gill, Richdeep S; Schiller, Daniel; Sawyer, Michael B

    2014-09-28

    Gastric cancer is one of the deadliest cancers worldwide, and is especially prevalent in Asian countries. With such high morbidity and mortality, early diagnosis is essential to achieving curative intent treatment and long term survival. Metabolomics is a new field of study that analyzes metabolites from biofluids and tissue samples. While metabolomics is still in its infancy, there are numerous potential applications in oncology, specifically early diagnosis. Only a few studies in the literature have examined metabolomics' role in gastric cancer. Various fatty acid, carbohydrate, nucleic acid, and amino acid metabolites have been identified that distinguish gastric cancer from normal tissue and benign gastric disease. However, findings from these few studies are at times conflicting. Most studies demonstrate some relationship of cancer cells to the Warburg Effect, in that glycolysis predominates with conversion of pyruvate to lactate. This is one of the most consistent findings across the literature. There is less consistency in metabolomic signature with respect to nucleic acids, lipids and amino acids. In spite of this, metabolomics holds some promise for cancer surveillance but further studies are necessary to achieve consistency and validation before it can be widely employed as a clinical tool.

  1. Sweat: a sample with limited present applications and promising future in metabolomics.

    Science.gov (United States)

    Mena-Bravo, A; Luque de Castro, M D

    2014-03-01

    Sweat is a biofluid with present scant use as clinical sample. This review tries to demonstrate the advantages of sweat over other biofluids such as blood or urine for routine clinical analyses and the potential when related to metabolomics. With this aim, critical discussion of sweat samplers and equipment for analysis of target compounds in this sample is made. Well established routine analyses in sweat as is that to diagnose cystic fibrosis, and the advantages and disadvantages of sweat versus urine or blood for doping control have also been discussed. Methods for analytes such as essential metals and xenometals, ethanol and electrolytes in sweat in fact constitute target metabolomics approaches or belong to any metabolomics subdiscipline such as metallomics, ionomics or xenometabolomics. The higher development of biomarkers based on genomics or proteomics as omics older than metabolomics is discussed and also the potential role of metabolomics in systems biology taking into account its emergent implementation. Normalization of the volume of sampled sweat constitutes a present unsolved shortcoming that deserves investigation. Foreseeable trends in this area are outlined. Copyright © 2013 Elsevier B.V. All rights reserved.

  2. Nontargeted modification-specific metabolomics study based on liquid chromatography-high-resolution mass spectrometry.

    Science.gov (United States)

    Dai, Weidong; Yin, Peiyuan; Zeng, Zhongda; Kong, Hongwei; Tong, Hongwei; Xu, Zhiliang; Lu, Xin; Lehmann, Rainer; Xu, Guowang

    2014-09-16

    Modifications of genes and proteins have been extensively studied in systems biology using comprehensive analytical strategies. Although metabolites are frequently modified, these modifications have not been studied using -omics approaches. Here a general strategy for the nontargeted profiling of modified metabolites, which we call "nontargeted modification-specific metabolomics", is reported. A key aspect of this strategy was the combination of in-source collision-induced dissociation liquid chromatography-mass spectrometry (LC-MS) and global nontargeted LC-MS-based metabolomics. Characteristic neutral loss fragments that are specific for acetylation, sulfation, glucuronidation, glucosidation, or ribose conjugation were reproducibly detected using human urine as a model specimen for method development. The practical application of this method was demonstrated by profiling urine samples from liver cirrhosis patients. Approximately 900 features were identified as modified endogenous metabolites and xenobiotics. Moreover, this strategy supports the identification of compounds not included in traditional metabolomics databases (HMDB, Metlin, and KEGG), which are currently referred to as "unknowns" in metabolomics projects. Nontargeted modification-specific metabolomics opens a new perspective in systems biology.

  3. MEASURING VARIABILITY SOURCES IN NMR METABOLOMIC STUDIES

    OpenAIRE

    Rozet, Eric; de Tullio, Pascal; Hubert, Philippe; Govaerts., B.

    2013-01-01

    Due to the huge amount of information available in NMR spectra obtained from the analysis of metabolomic experiments, multivariate analysis such as Principal Component Analysis (PCA) are required to understand the influence of treatments over the metabolites [1]. However, many experiments in metabolomics studies have more complexes variability structures than simply comparing several treatments: they may include time effects, biological effects such as diet or hormonal status, and other bloc...

  4. Blood Transcriptomics and Metabolomics for Personalized Medicine

    Science.gov (United States)

    2015-10-31

    progress in human immunology , where transcriptomics of isolated cell populations provided necessary information [15–17]. Nonetheless, a review on “blood...databases are biased towards cancer , under- representing the immunology in white blood cells. Second, many path- ways are based on tissues other than blood...metabolomics in oncology: a review . Clin Cancer Res 2009;15. [52] Armitage EG. Metabolomics in cancer biomarker discovery: current trends and fu- ture

  5. Metabolomic profiling in cattle experimentally infected with Mycobacterium avium subsp. paratuberculosis.

    Directory of Open Access Journals (Sweden)

    Jeroen De Buck

    Full Text Available The sensitivity of current diagnostics for Johne's disease, a slow, progressing enteritis in ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP, is too low to reliably detect all infected animals in the subclinical stage. The objective was to identify individual metabolites or metabolite profiles that could be used as biomarkers of early MAP infection in ruminants. In a monthly follow-up for 17 months, calves infected at 2 weeks of age were compared with aged-matched controls. Sera from all animals were analyzed by 1H nuclear magnetic resonance spectrometry. Spectra were acquired, processed, and quantified for analysis. The concentration of many metabolites changed over time in all calves, but some metabolites only changed over time in either infected or non-infected groups and the change in others was impacted by the infection. Hierarchical multivariate statistical analysis achieved best separation between groups between 300 and 400 days after infection. Therefore, a cross-sectional comparison between 1-year-old calves experimentally infected at various ages with either a high- or a low-dose and age-matched non-infected controls was performed. Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS DA yielded distinct separation of non-infected from infected cattle, regardless of dose and time (3, 6, 9 or 12 months after infection. Receiver Operating Curves demonstrated that constructed models were high quality. Increased isobutyrate in the infected cattle was the most important agreement between the longitudinal and cross-sectional analysis. In general, high- and low-dose cattle responded similarly to infection. Differences in acetone, citrate, glycerol and iso-butyrate concentrations indicated energy shortages and increased fat metabolism in infected cattle, whereas changes in urea and several amino acids (AA, including the branched chain AA, indicated increased protein turnover. In conclusion, metabolomics

  6. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  7. ECMDB: the E. coli Metabolome Database.

    Science.gov (United States)

    Guo, An Chi; Jewison, Timothy; Wilson, Michael; Liu, Yifeng; Knox, Craig; Djoumbou, Yannick; Lo, Patrick; Mandal, Rupasri; Krishnamurthy, Ram; Wishart, David S

    2013-01-01

    The Escherichia coli Metabolome Database (ECMDB, http://www.ecmdb.ca) is a comprehensively annotated metabolomic database containing detailed information about the metabolome of E. coli (K-12). Modelled closely on the Human and Yeast Metabolome Databases, the ECMDB contains >2600 metabolites with links to ∼1500 different genes and proteins, including enzymes and transporters. The information in the ECMDB has been collected from dozens of textbooks, journal articles and electronic databases. Each metabolite entry in the ECMDB contains an average of 75 separate data fields, including comprehensive compound descriptions, names and synonyms, chemical taxonomy, compound structural and physicochemical data, bacterial growth conditions and substrates, reactions, pathway information, enzyme data, gene/protein sequence data and numerous hyperlinks to images, references and other public databases. The ECMDB also includes an extensive collection of intracellular metabolite concentration data compiled from our own work as well as other published metabolomic studies. This information is further supplemented with thousands of fully assigned reference nuclear magnetic resonance and mass spectrometry spectra obtained from pure E. coli metabolites that we (and others) have collected. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of E. coli's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers but also to molecular biologists, systems biologists and individuals in the biotechnology industry.

  8. Clinical impact of human breast milk metabolomics.

    Science.gov (United States)

    Cesare Marincola, Flaminia; Dessì, Angelica; Corbu, Sara; Reali, Alessandra; Fanos, Vassilios

    2015-12-01

    Metabolomics is a research field concerned with the analysis of metabolome, the complete set of metabolites in a given cell, tissue, or biological sample. Being able to provide a molecular snapshot of biological systems, metabolomics has emerged as a functional methodology in a wide range of research areas such as toxicology, pharmacology, food technology, nutrition, microbial biotechnology, systems biology, and plant biotechnology. In this review, we emphasize the applications of metabolomics in investigating the human breast milk (HBM) metabolome. HBM is the recommended source of nutrition for infants since it contains the optimal balance of nutrients for developing babies, and it provides a range of benefits for growth, immunity, and development. The molecular mechanisms beyond the inter- and intra-variability of HBM that make its composition unique are yet to be well-characterized. Although still in its infancy, the study of HBM metabolome has already proven itself to be of great value in providing insights into this biochemical variability in relation to mother phenotype, diet, disease, and lifestyle. The results of these investigations lay the foundation for further developments useful to identify normal and aberrant biochemical changes as well as to develop strategies to promote healthy infant feeding practices.

  9. Distinguishing between the metabolome and xenobiotic exposome in environmental field samples analysed by direct-infusion mass spectrometry based metabolomics and lipidomics.

    Science.gov (United States)

    Southam, Andrew D; Lange, Anke; Al-Salhi, Raghad; Hill, Elizabeth M; Tyler, Charles R; Viant, Mark R

    2014-01-01

    Environmental metabolomics is increasingly used to investigate organismal responses to complex chemical mixtures, including waste water effluent (WWE). In parallel, increasingly sensitive analytical methods are being used in metabolomics studies, particularly mass spectrometry. This introduces a considerable, yet overlooked, challenge that high analytical sensitivity will not only improve the detection of endogenous metabolites in biological specimens but also exogenous chemicals. If these often unknown xenobiotic features are not removed from the "biological" dataset, they will bias the interpretation and could lead to incorrect conclusions about the biotic response. Here we illustrate and validate a novel workflow classifying the origin of peaks detected in biological samples as: endogenous, xenobiotics, or metabolised xenobiotics. The workflow is demonstrated using direct infusion mass spectrometry-based metabolomic analysis of testes from roach exposed to different concentrations of a complex WWE. We show that xenobiotics and their metabolic products can be detected in roach testes (including triclosan, chloroxylenol and chlorophene), and that these compounds have a disproportionately high level of statistical significance within the total (bio)chemical changes induced by the WWE. Overall we have demonstrated that this workflow extracts more information from an environmental metabolomics study of complex mixture exposures than was possible previously.

  10. Diurnal effects of anoxia on the metabolome of the seagrass Zostera marina

    DEFF Research Database (Denmark)

    Hasler-Sheetal, Harald; Fragner, Lena; Holmer, Marianne

    2015-01-01

    We investigated the response, adaptation and tolerance mechanisms of the temperate seagrass Zostera marina to water column anoxia. We exposed Z. marina to a diurnal light/dark cycle under anoxia and assessed the metabolic response by measuring the metabolome with gas chromatography coupled to mass...... shunt as such mitigation mechanisms that alleviate pyruvate levels and lead to carbon and nitrogen storage during anoxia. This work demonstrates the applicability of metabolomics to assess low oxygen stress responses of Z. marina and allows us to propose an anoxia recovery model....

  11. Can metabolomics in addition to genomics add to prognostic and predictive information in breast cancer?

    Science.gov (United States)

    Howell, Anthony

    2010-11-16

    Genomic data from breast cancers provide additional prognostic and predictive information that is beginning to be used for patient management. The question arises whether additional information derived from other 'omic' approaches such as metabolomics can provide additional information. In an article published this month in BMC Cancer, Borgan et al. add metabolomic information to genomic measures in breast tumours and demonstrate, for the first time, that it may be possible to further define subgroups of patients which could be of value clinically. See research article: http://www.biomedcentral.com/1471-2407/10/628.

  12. Assessment of fruit juice authenticity using UPLC-QToF MS: a metabolomics approach.

    Science.gov (United States)

    Jandrić, Z; Roberts, D; Rathor, M N; Abrahim, A; Islam, M; Cannavan, A

    2014-04-01

    In recent years, with the growing complexity of global food supply chains and trade, food fraud, including adulteration of high value foods with cheaper substitutes, has become an increasingly important issue. A metabolomics approach can be applied to discover biomarkers that can be used to trace food adulteration. A study was undertaken to discover novel, potential biomarkers for the rapid detection of the adulteration of fruit juices with cheaper alternatives. Pineapple, orange, grapefruit, apple, clementine, and pomelo were investigated. Untargeted metabolite fingerprinting was performed by UPLC-QToF MS with multivariate data analysis. Twenty-one differential metabolites were selected, contributing to the separation between pineapple, orange and grapefruit juices, and their admixtures down to 1% adulteration level. A targeted metabolomics method was then optimised and adulteration could be detected at 1%. The results demonstrate that metabolomics has potential as a screening tool for the rapid detection of food adulteration. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Metabolomics continues to flourish: highlights from the 2014 Metabolomics Society Conference

    NARCIS (Netherlands)

    Roessner, U.; Hall, R.D.

    2014-01-01

    The Metabolomics Society has now been organising its annual meetings for 10 years! The 10th annual conference returned, in June, to Tsuruoka, Japan where the very first meeting was also held in 2005—just shortly after our society had been formally established and our journal Metabolomics had brought

  14. Metabolomics and dereplication strategies in natural products.

    Science.gov (United States)

    Tawfike, Ahmed Fares; Viegelmann, Christina; Edrada-Ebel, Ruangelie

    2013-01-01

    Metabolomic methods can be utilized to screen diverse biological sources of potentially novel and sustainable sources of antibiotics and pharmacologically-active drugs. Dereplication studies by high resolution Fourier transform mass spectrometry coupled to liquid chromatography (LC-HRFTMS) and nuclear magnetic resonance (NMR) spectroscopy can establish the chemical profile of endophytic and/or endozoic microbial extracts and their plant or animal sources. Identifying the compounds of interest at an early stage will aid in the isolation of the bioactive components. Therefore metabolite profiling is important for functional genomics and in the search for new pharmacologically active compounds. Using the tools of metabolomics through the employment of LC-HRFTMS as well as high resolution NMR will be a very efficient approach. Metabolomic profiling has found its application in screening extracts of macroorganisms as well as in the isolation and cultivation of suspected microbial producers of bioactive natural products.Metabolomics is being applied to identify and biotechnologically optimize the production of pharmacologically active secondary metabolites. The links between metabolome evolution during optimization and processing factors can be identified through metabolomics. Information obtained from a metabolomics dataset can efficiently establish cultivation and production processes at a small scale which will be finally scaled up to a fermenter system, while maintaining or enhancing synthesis of the desired compounds. MZmine (BMC Bioinformatics 11:395-399, 2010; http://mzmine.sourceforge.net/download.shtml ) and SIEVE ( http://www.vastscientific.com/resources/index.html ; Rapid Commun Mass Spectrom 22:1912-1918, 2008) softwares are utilized to perform differential analysis of sample populations to find significant expressed features of complex biomarkers between parameter variables. Metabolomes are identified with the aid of existing high resolution MS and NMR

  15. NMR-based Metabolomics Applications in Biological and Environmental Science

    Science.gov (United States)

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

  16. Plant Metabolomics : the missiong link in functional genomics strategies

    NARCIS (Netherlands)

    Hall, R.D.; Beale, M.; Fiehn, O.; Hardy, N.; Summer, L.; Bino, R.

    2002-01-01

    After the establishment of technologies for high-throughput DNA sequencing (genomics), gene expression analysis (transcriptomics), and protein analysis (proteomics), the remaining functional genomics challenge is that of metabolomics. Metabolomics is the term coined for essentially comprehensive, no

  17. Metabolomics

    DEFF Research Database (Denmark)

    Pedersen, Hans

    ) spectroscopy (Paper II), fluorescence spectroscopy (Paper III) and gas chromatography coupled to mass spectrometry (GC-MS). The principles of the three data acquisition techniques have been briefly described and the methods have been compared. The techniques complement each other, which makes room for data...... fusion where data from different platforms can be combined. Complex data are obtained when samples are analysed using NMR, fluorescence and GC-MS. Chemometrics methods which can be used to extract the relevant information from the obtained data are presented. Focus has been on principal component...... many redundant variables. These have been suggested to be eliminated using an approach termed reduction of redundant variables (RRV), which is time consuming but efficient, since the curse of dimensionality is reduced and the risk of over-fit is decreased. The use of appropriate multivariate models...

  18. Metabolomics

    DEFF Research Database (Denmark)

    Pedersen, Hans

    ) spectroscopy (Paper II), fluorescence spectroscopy (Paper III) and gas chromatography coupled to mass spectrometry (GC-MS). The principles of the three data acquisition techniques have been briefly described and the methods have been compared. The techniques complement each other, which makes room for data...... analysis (PCA), parallel factor analysis (PARAFAC), PARAFAC2 and partial least squares discriminant analysis (PLS-DA) all being described in depth. It can be a challenge to determine the appropriate number of components in PARAFAC2, since no specific tools have been developed for this purpose. Paper I...

  19. Equivalence Checking of Hierarchical Combinational Circuits

    DEFF Research Database (Denmark)

    Williams, Poul Frederick; Hulgaard, Henrik; Andersen, Henrik Reif

    1999-01-01

    This paper presents a method for verifying that two hierarchical combinational circuits implement the same Boolean functions. The key new feature of the method is its ability to exploit the modularity of circuits to reuse results obtained from one part of the circuits in other parts. We demonstrate...... our method on large adder and multiplier circuits....

  20. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

    Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-07

    Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

  1. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  2. Metabolomics data normalization with EigenMS.

    Directory of Open Access Journals (Sweden)

    Yuliya V Karpievitch

    Full Text Available Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated. Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (p<0.05 as compared to only 1840 metabolite signals in the raw data. Our results support the use of singular value decomposition-based normalization for metabolomics data.

  3. Self-assembled biomimetic superhydrophobic hierarchical arrays.

    Science.gov (United States)

    Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

    2013-09-01

    Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. Hierarchical self-organization of tectonic plates

    CERN Document Server

    Morra, Gabriele; Müller, R Dietmar

    2010-01-01

    The Earth's surface is subdivided into eight large tectonic plates and many smaller ones. We reconstruct the plate tessellation history and demonstrate that both large and small plates display two distinct hierarchical patterns, described by different power-law size-relationships. While small plates display little organisational change through time, the structure of the large plates oscillate between minimum and maximum hierarchical tessellations. The organization of large plates rapidly changes from a weak hierarchy at 120-100 million years ago (Ma) towards a strong hierarchy, which peaked at 65-50, Ma subsequently relaxing back towards a minimum hierarchical structure. We suggest that this fluctuation reflects an alternation between top and bottom driven plate tectonics, revealing a previously undiscovered tectonic cyclicity at a timescale of 100 million years.

  5. Fusion of mass spectrometry-based metabolomics data

    NARCIS (Netherlands)

    Smilde, A.K.; Werf, M.J. van der; Bijlsma, S.; Werff-van der Vat, B.J.C. van der; Jellema, R.H.

    2005-01-01

    A general method is presented for combining mass spectrometry-based metabolomics data. Such data are becoming more and more abundant, and proper tools for fusing these types of data sets are needed. Fusion of metabolomics data leads to a comprehensive view on the metabolome of an organism or biologi

  6. A Nontargeted UHPLC-HRMS Metabolomics Pipeline for Metabolite Identification: Application to Cardiac Remote Ischemic Preconditioning.

    Science.gov (United States)

    Kouassi Nzoughet, Judith; Bocca, Cinzia; Simard, Gilles; Prunier-Mirebeau, Delphine; Chao de la Barca, Juan Manuel; Bonneau, Dominique; Procaccio, Vincent; Prunier, Fabrice; Lenaers, Guy; Reynier, Pascal

    2017-02-07

    In recent years, the number of investigations based on nontargeted metabolomics has increased, although often without a thorough assessment of analytical strategies applied to acquire data. Following published guidelines for metabolomics experiments, we report a validated nontargeted metabolomics strategy with pipeline for unequivocal identification of metabolites using the MSMLS molecule library. We achieved an in-house database containing accurate m/z values, retention times, isotopic patterns, full MS, and MS/MS spectra. A UHPLC-HRMS Q-Exactive method was developed, and experimental variations were determined within and between 3 experimental days. The extraction efficiency as well as the accuracy, precision, repeatability, and linearity of the method were assessed, the method demonstrating good performances. The methodology was further blindly applied to plasma from remote ischemic pre-conditioning (RIPC) rats. Samples, previously analyzed by targeted metabolomics using completely different protocol, analytical strategy, and platform, were submitted to our analytical pipeline. A combination of multivariate and univariate statistical analyses was employed. Selection of putative biomarkers from OPLS-DA model and S-plot was combined to jack-knife confidence intervals, metabolites' VIP values, and univariate statistics. Only variables with strong model contribution and highly statistical reliability were selected as discriminated metabolites. Three biomarkers identified by the previous targeted metabolomics study were found in the current work, in addition to three novel metabolites, emphasizing the efficiency of the current methodology and its ability to identify new biomarkers of clinical interest, in a single sequence. The biomarkers were identified to level 1 according to the metabolomics standard initiative and confirmed by both RPLC and HILIC-HRMS.

  7. Clinical application of metabolomics in neonatology.

    Science.gov (United States)

    Fanos, Vassilios; Antonucci, Roberto; Barberini, Luigi; Noto, Antonio; Atzori, Luigi

    2012-04-01

    The youngest and more rapidly increasing "omic" discipline, called metabolomics, is the process of describing the phenotype of a cell, tissue or organism through the full complement of metabolites present. Metabolomics measure global sets of low molecular weight metabolites (including amino acids, organic acids, sugars, fatty acids, lipids, steroids, small peptides, vitamins, etc.), thus providing a "snapshot" of the metabolic status of a cell, tissue or organism in relation to genetic variations or external stimuli. The use of metabolomics appears to be a promising tool in neonatology. The management of sick newborns might improve if more information on perinatal/neonatal maturational processes and their metabolic background were available. Urine ("a window on the organism") is a biofluid particularly suitable for metabolomic analysis in neonatology because it may be collected by using simple, noninvasive techniques and because it may provide valuable diagnostic information. In this review, the authors report the few literature data on neonatal metabolomics, including their personal experience, in the following fields: intrauterine growth restriction, perinatal transition, asphyxia, brain injury and hypothermia, maternal milk evaluation, postnatal maturation, bronchiolitis, sepsis, patent ductus arteriosus, respiratory distress syndrome, nephrouropathies, metabolic diseases, antibiotic treatment, perinatal programming and long-term outcome in extremely low birth-weight infants.

  8. Application of Metabolomics in Thyroid Cancer Research

    Directory of Open Access Journals (Sweden)

    Anna Wojakowska

    2015-01-01

    Full Text Available Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput “omics” techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

  9. Basics of mass spectrometry based metabolomics.

    Science.gov (United States)

    Courant, Frédérique; Antignac, Jean-Philippe; Dervilly-Pinel, Gaud; Le Bizec, Bruno

    2014-11-01

    The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

  10. Systematic Applications of Metabolomics in Metabolic Engineering

    Directory of Open Access Journals (Sweden)

    Robert A. Dromms

    2012-12-01

    Full Text Available The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

  11. Systematic Applications of Metabolomics in Metabolic Engineering

    Science.gov (United States)

    Dromms, Robert A.; Styczynski, Mark P.

    2012-01-01

    The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering. PMID:24957776

  12. A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification

    Directory of Open Access Journals (Sweden)

    Marín Ignacio

    2007-11-01

    Full Text Available Abstract Background Classification procedures are widely used in phylogenetic inference, the analysis of expression profiles, the study of biological networks, etc. Many algorithms have been proposed to establish the similarity between two different classifications of the same elements. However, methods to determine significant coincidences between hierarchical and non-hierarchical partitions are still poorly developed, in spite of the fact that the search for such coincidences is implicit in many analyses of massive data. Results We describe a novel strategy to compare a hierarchical and a dichotomic non-hierarchical classification of elements, in order to find clusters in a hierarchical tree in which elements of a given "flat" partition are overrepresented. The key improvement of our strategy respect to previous methods is using permutation analyses of ranked clusters to determine whether regions of the dendrograms present a significant enrichment. We show that this method is more sensitive than previously developed strategies and how it can be applied to several real cases, including microarray and interactome data. Particularly, we use it to compare a hierarchical representation of the yeast mitochondrial interactome and a catalogue of known mitochondrial protein complexes, demonstrating a high level of congruence between those two classifications. We also discuss extensions of this method to other cases which are conceptually related. Conclusion Our method is highly sensitive and outperforms previously described strategies. A PERL script that implements it is available at http://www.uv.es/~genomica/treetracker.

  13. Collaborative Hierarchical Sparse Modeling

    CERN Document Server

    Sprechmann, Pablo; Sapiro, Guillermo; Eldar, Yonina C

    2010-01-01

    Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the sparsity-inducing property of the Lasso model, at the individual feature level, with the block-sparsity property of the group Lasso model, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the hierarchical Lasso, which shows important practical modeling advantages. We then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level but not necessarily at the lower one. Signals then share the same active groups, or classes, but not necessarily the same active set. This is very well suited for applications such as source separation. An efficient optimization procedure, which guarantees convergence to the global opt...

  14. Sulfites and the wine metabolome.

    Science.gov (United States)

    Roullier-Gall, Chloé; Hemmler, Daniel; Gonsior, Michael; Li, Yan; Nikolantonaki, Maria; Aron, Alissa; Coelho, Christian; Gougeon, Régis D; Schmitt-Kopplin, Philippe

    2017-12-15

    In a context of societal concern about food preservation, the reduction of sulfite input plays a major role in the wine industry. To improve the understanding of the chemistry involved in the SO2 protection, a series of bottle aged Chardonnay wines made from the same must, but with different concentrations of SO2 added at pressing were analyzed by ultrahigh resolution mass spectrometry (FT-ICR-MS) and excitation emission matrix fluorescence (EEMF). Metabolic fingerprints from FT-ICR-MS data could discriminate wines according to the added concentration to the must but they also revealed chemistry-related differences according to the type of stopper, providing a wine metabolomics picture of the impact of distinct stopping strategies. Spearman rank correlation was applied to link the statistically modeled EEMF components (parallel factor analysis (PARAFAC)) and the exact mass information from FT-ICR-MS, and thus revealing the extent of sulfur-containing compounds which could show some correlation with fluorescence fingerprints. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Network Marker Selection for Untargeted LC-MS Metabolomics Data.

    Science.gov (United States)

    Cai, Qingpo; Alvarez, Jessica A; Kang, Jian; Yu, Tianwei

    2017-02-17

    Untargeted metabolomics using high-resolution liquid chromatography-mass spectrometry (LC-MS) is becoming one of the major areas of high-throughput biology. Functional analysis, that is, analyzing the data based on metabolic pathways or the genome-scale metabolic network, is critical in feature selection and interpretation of metabolomics data. One of the main challenges in the functional analyses is the lack of the feature identity in the LC-MS data itself. By matching mass-to-charge ratio (m/z) values of the features to theoretical values derived from known metabolites, some features can be matched to one or more known metabolites. When multiple matchings occur, in most cases only one of the matchings can be true. At the same time, some known metabolites are missing in the measurements. Current network/pathway analysis methods ignore the uncertainty in metabolite identification and the missing observations, which could lead to errors in the selection of significant subnetworks/pathways. In this paper, we propose a flexible network feature selection framework that combines metabolomics data with the genome-scale metabolic network. The method adopts a sequential feature screening procedure and machine learning-based criteria to select important subnetworks and identify the optimal feature matching simultaneously. Simulation studies show that the proposed method has a much higher sensitivity than the commonly used maximal matching approach. For demonstration, we apply the method on a cohort of healthy subjects to detect subnetworks associated with the body mass index (BMI). The method identifies several subnetworks that are supported by the current literature, as well as detects some subnetworks with plausible new functional implications. The R code is available at http://web1.sph.emory.edu/users/tyu8/MSS.

  16. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

    Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

  17. HDS: Hierarchical Data System

    Science.gov (United States)

    Pearce, Dave; Walter, Anton; Lupton, W. F.; Warren-Smith, Rodney F.; Lawden, Mike; McIlwrath, Brian; Peden, J. C. M.; Jenness, Tim; Draper, Peter W.

    2015-02-01

    The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023). HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

  18. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  19. [Metabolomics analysis of taxadiene producing yeasts].

    Science.gov (United States)

    Yan, Huifang; Ding, Mingzhu; Yuan, Yingjin

    2014-02-01

    In order to study the inherent difference among terpenes producing yeasts from the point of metabolomics, we selected taxadiene producing yeasts as the model system. The changes of cellular metabolites during fermentation log phase of artificial functional yeasts were determined using metabolomics methods. The results represented that compared to W303-1A as a blank control, the metabolites in glycolysis, tricarboxylic acid cycle (TCA) cycle and several amino acids were influenced. And due to the changes of metabolites, the growth of cells was inhibited to a certain extent. Among the metabolites identified, citric acid content in taxadiene producing yeasts changed the most, the decreasing amplitude reached 90% or more. Therefore, citric acid can be a marker metabolite for the future study of artificial functional yeasts. The metabolomics analysis of taxadiene producing yeasts can provide more information in further studies on optimization of terpenes production in heterologous chassis.

  20. Metabolomics to Explore Impact of Dairy Intake

    Directory of Open Access Journals (Sweden)

    Hong Zheng

    2015-06-01

    Full Text Available Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health.

  1. Microbiome, Metabolome and Inflammatory Bowel Disease

    Science.gov (United States)

    Ahmed, Ishfaq; Roy, Badal C.; Khan, Salman A.; Septer, Seth; Umar, Shahid

    2016-01-01

    Inflammatory Bowel Disease (IBD) is a multifactorial disorder that conceptually occurs as a result of altered immune responses to commensal and/or pathogenic gut microbes in individuals most susceptible to the disease. During Crohn’s Disease (CD) or Ulcerative Colitis (UC), two components of the human IBD, distinct stages define the disease onset, severity, progression and remission. Epigenetic, environmental (microbiome, metabolome) and nutritional factors are important in IBD pathogenesis. While the dysbiotic microbiota has been proposed to play a role in disease pathogenesis, the data on IBD and diet are still less convincing. Nonetheless, studies are ongoing to examine the effect of pre/probiotics and/or FODMAP reduced diets on both the gut microbiome and its metabolome in an effort to define the healthy diet in patients with IBD. Knowledge of a unique metabolomic fingerprint in IBD could be useful for diagnosis, treatment and detection of disease pathogenesis. PMID:27681914

  2. Microbiome, Metabolome and Inflammatory Bowel Disease

    Directory of Open Access Journals (Sweden)

    Ishfaq Ahmed

    2016-06-01

    Full Text Available Inflammatory Bowel Disease (IBD is a multifactorial disorder that conceptually occurs as a result of altered immune responses to commensal and/or pathogenic gut microbes in individuals most susceptible to the disease. During Crohn’s Disease (CD or Ulcerative Colitis (UC, two components of the human IBD, distinct stages define the disease onset, severity, progression and remission. Epigenetic, environmental (microbiome, metabolome and nutritional factors are important in IBD pathogenesis. While the dysbiotic microbiota has been proposed to play a role in disease pathogenesis, the data on IBD and diet are still less convincing. Nonetheless, studies are ongoing to examine the effect of pre/probiotics and/or FODMAP reduced diets on both the gut microbiome and its metabolome in an effort to define the healthy diet in patients with IBD. Knowledge of a unique metabolomic fingerprint in IBD could be useful for diagnosis, treatment and detection of disease pathogenesis.

  3. Blood transcriptomics and metabolomics for personalized medicine

    Directory of Open Access Journals (Sweden)

    Shuzhao Li

    2016-01-01

    Full Text Available Molecular analysis of blood samples is pivotal to clinical diagnosis and has been intensively investigated since the rise of systems biology. Recent developments have opened new opportunities to utilize transcriptomics and metabolomics for personalized and precision medicine. Efforts from human immunology have infused into this area exquisite characterizations of subpopulations of blood cells. It is now possible to infer from blood transcriptomics, with fine accuracy, the contribution of immune activation and of cell subpopulations. In parallel, high-resolution mass spectrometry has brought revolutionary analytical capability, detecting >10,000 metabolites, together with environmental exposure, dietary intake, microbial activity, and pharmaceutical drugs. Thus, the re-examination of blood chemicals by metabolomics is in order. Transcriptomics and metabolomics can be integrated to provide a more comprehensive understanding of the human biological states. We will review these new data and methods and discuss how they can contribute to personalized medicine.

  4. High Aerobic Capacity Mitigates Changes in the Plasma Metabolomic Profile Associated with Aging.

    Science.gov (United States)

    Falegan, Oluyemi S; Vogel, Hans J; Hittel, Dustin S; Koch, Lauren G; Britton, Steven L; Hepple, Russ T; Shearer, Jane

    2017-02-03

    Advancing age is associated with declines in maximal oxygen consumption. Declines in aerobic capacity not only contribute to the aging process but also are an independent risk factor for morbidity, cardiovascular disease, and all-cause mortality. Although statistically convincing, the relationships between aerobic capacity, aging, and disease risk remain largely unresolved. To this end, we employed sensitive, system-based metabolomics approach to determine whether enhanced aerobic capacity could mitigate some of the changes seen in the plasma metabolomic profile associated with aging. Metabolomic profiles of plasma samples obtained from young (13 month) and old (26 month) rats bred for low (LCR) or high (HCR) running capacity using proton nuclear magnetic resonance spectroscopy ((1)H NMR) were examined. Results demonstrated strong profile separation in old and low aerobic capacity rats, whereas young and high aerobic capacity rat models were less predictive. Significantly differential metabolites between the groups include taurine, acetone, valine, and trimethylamine-N-oxide among other metabolites, specifically citrate, succinate, isovalerate, and proline, were differentially increased in older HCR animals compared with their younger counterparts. When interactions between age and aerobic capacity were examined, results demonstrated that enhanced aerobic capacity could mitigate some but not all age-associated alterations in the metabolomic profile.

  5. Metabolomics data normalization with EigenMS.

    Science.gov (United States)

    Karpievitch, Yuliya V; Nikolic, Sonja B; Wilson, Richard; Sharman, James E; Edwards, Lindsay M

    2014-01-01

    Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated). Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (pmetabolomics data.

  6. Genomic and metabolomic profile associated to microalbuminuria.

    Directory of Open Access Journals (Sweden)

    Vannina G Marrachelli

    Full Text Available To identify factors related with the risk to develop microalbuminuria using combined genomic and metabolomic values from a general population study. One thousand five hundred and two subjects, Caucasian, more than 18 years, representative of the general population, were included. Blood pressure measurement and albumin/creatinine ratio were measured in a urine sample. Using SNPlex, 1251 SNPs potentially associated to urinary albumin excretion (UAE were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54 ± 19, 50.6% men, ACR>30 mg/g in 81 subjects with high genotyping call rate were analysed. A characteristic metabolomic profile, which included products from mitochondrial and extra mitochondrial metabolism as well as branched amino acids and their derivative signals, were observed in microalbuminuric as compare to normoalbuminuric subjects. The comparison of the metabolomic profile between subjects with different UAE status for each of the genotypes associated to microalbuminuria revealed two SNPs, the rs10492025_TT of RPH3A gene and the rs4359_CC of ACE gene, with minimal or no statistically significant differences. Subjects with and without microalbuminuria, who shared the same genotype and metabolomic profile, differed in age. Microalbuminurics with the CC genotype of the rs4359 polymorphism and with the TT genotype of the rs10492025 polymorphism were seven years older and seventeen years younger, respectively as compared to the whole microalbuminuric subjects. With the same metabolomic environment, characteristic of subjects with microalbuminuria, the TT genotype of the rs10492025 polymorphism seems to increase and the CC genotype of the rs4359 polymorphism seems to reduce risk to develop microalbuminuria.

  7. Metabolomic applications in nutritional research: a perspective.

    Science.gov (United States)

    O'Gorman, Aoife; Brennan, Lorraine

    2015-10-01

    Metabolomics focuses on the global study of metabolites in cells, tissues and biofluids. Analytical technologies such as nuclear magnetic resonance (NMR) spectroscopy and hyphenated mass spectrometry (MS) combined with advanced multivariate statistical methods allow us to study perturbations in metabolism. The close link between metabolism and nutrition has seen the application of metabolomics in nutritional research increase in recent times. Such applications can be divided into three main categories, namely (1) the area of dietary biomarker identification, (2) diet-related diseases and (3) nutritional interventions. The present perspective gives an overview of these applications and an outlook to the future.

  8. Multicollinearity in hierarchical linear models.

    Science.gov (United States)

    Yu, Han; Jiang, Shanhe; Land, Kenneth C

    2015-09-01

    This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model.

  9. Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

    Energy Technology Data Exchange (ETDEWEB)

    Nagato, Edward G.; Simpson, André J.; Simpson, Myrna J., E-mail: myrna.simpson@utoronto.ca

    2016-01-15

    Highlights: • Metabolomics detected shifts with sub-lethal exposure to contaminants. • Diazinon and malathion induced comparable, non-linear responses. • Bisphenol-A resulted in energy impairment. • Overall, insight into sub-lethal toxicity was garnered using NMR-based metabolomics. - Abstract: {sup 1}H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of {sup 1}H NMR spectra were used to screen metabolome changes after 48 h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009–0.135 μg/L), while for malathion the second lowest (0.08 μg/L) and two highest exposure concentrations (0.32 μg/L and 0.47 μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045 μg/L and 0.09 μg/L) and malathion (0.08 μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by

  10. COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access

    NARCIS (Netherlands)

    Salek, R.M.; Neumann, S.; Schober, D.; Hummel, J.; Billiau, K.; Kopka, J.; Correa, E.; Reijmers, T.; Rosato, A.; Tenori, L.; Turano, P.; Marin, S.; Deborde, C.; Jacob, D.; Rolin, D.; Dartigues, B.; Conesa, P.; Haug, K.; Rocca-Serra, P.; O’Hagan, S.; Hao, J.; Vliet, M. van; Sysi-Aho, M.; Ludwig, C.; Bouwman, J.; Cascante, M.; Ebbels, T.; Griffin, J.L.; Moing, A.; Nikolski, M.; Oresic, M.; Sansone, S.A.; Viant, M.R.; Goodacre, R.; Günther, U.L.; Hankemeier, T.; Luchinat, C.; Walther, D.; Steinbeck, C.

    2015-01-01

    Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and

  11. Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

    Energy Technology Data Exchange (ETDEWEB)

    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Gouveia-Figueira, Sandra [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå (Sweden); Pinto, Rui [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Bioinformatics Infrastructure for Life Sciences (Sweden); Trygg, Johan [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Zivkovic, Angela M. [Department of Nutrition, University of California, Davis, One Shields Ave, CA 95616 (United States); Nording, Malin L., E-mail: malin.nording@umu.se [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden)

    2016-02-18

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a

  12. Context updates are hierarchical

    Directory of Open Access Journals (Sweden)

    Anton Karl Ingason

    2016-10-01

    Full Text Available This squib studies the order in which elements are added to the shared context of interlocutors in a conversation. It focuses on context updates within one hierarchical structure and argues that structurally higher elements are entered into the context before lower elements, even if the structurally higher elements are pronounced after the lower elements. The crucial data are drawn from a comparison of relative clauses in two head-initial languages, English and Icelandic, and two head-final languages, Korean and Japanese. The findings have consequences for any theory of a dynamic semantics.

  13. Obesity and psychotic disorders: uncovering common mechanisms through metabolomics

    Directory of Open Access Journals (Sweden)

    Matej Orešič

    2012-09-01

    Full Text Available Primary obesity and psychotic disorders are similar with respect to the associated changes in energy balance and co-morbidities, including metabolic syndrome. Such similarities do not necessarily demonstrate causal links, but instead suggest that specific causes of and metabolic disturbances associated with obesity play a pathogenic role in the development of co-morbid disorders, potentially even before obesity develops. Metabolomics – the systematic study of metabolites, which are small molecules generated by the process of metabolism – has been important in elucidating the pathways underlying obesity-associated co-morbidities. This review covers how recent metabolomic studies have advanced biomarker discovery and the elucidation of mechanisms underlying obesity and its co-morbidities, with a specific focus on metabolic syndrome and psychotic disorders. The importance of identifying metabolic markers of disease-associated intermediate phenotypes – traits modulated but not encoded by the DNA sequence – is emphasized. Such markers would be applicable as diagnostic tools in a personalized healthcare setting and might also open up novel therapeutic avenues.

  14. Metabolomic insight into soy sauce through (1)H NMR spectroscopy.

    Science.gov (United States)

    Ko, Bong-Kuk; Ahn, Hyuk-Jin; van den Berg, Frans; Lee, Cherl-Ho; Hong, Young-Shick

    2009-08-12

    Soy sauce, a well-known seasoning in Asia and throughout the world, consists of many metabolites that are produced during fermentation or aging and that have various health benefits. However, their comprehensive assessment has been limited due to targeted or instrumentally specific analysis. This paper presents for the first time a metabolic characterization of soy sauce, especially that aged up to 12 years, to obtain a global understanding of the metabolic variations through (1)H NMR spectroscopy coupled with multivariate pattern recognition techniques. Elevated amino acids and organic acids and the consumption of carbohydrate were associated with continuous involvement of microflora in aging for 12 years. In particular, continuous increases in the levels of betaine were found during aging for up to 12 years, demonstrating that microbial- or enzyme-related metabolites were also coupled with osmotolerant or halophilic bacteria present during aging. This work provides global insights into soy sauce through a (1)H NMR-based metabolomic approach that enhances the current understanding of the holistic metabolome and allows assessment of soy sauce quality.

  15. CE–MS for metabolomics: Developments and applications in the period 2014–2016

    Science.gov (United States)

    Somsen, Govert W.; de Jong, Gerhardus J.

    2016-01-01

    CE–MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE–MS approaches for metabolomics studies. In this paper, which is a follow‐up of a previous review paper covering the years 2012–2014 (Electrophoresis 2015, 36, 212–224), recent CE–MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE–MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE–MS is also demonstrated. Representative examples illustrate the applicability of CE–MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE–MS‐based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. PMID:27718257

  16. CE-MS for metabolomics: Developments and applications in the period 2014-2016.

    Science.gov (United States)

    Ramautar, Rawi; Somsen, Govert W; de Jong, Gerhardus J

    2017-01-01

    CE-MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolomics studies. In this paper, which is a follow-up of a previous review paper covering the years 2012-2014 (Electrophoresis 2015, 36, 212-224), recent CE-MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE-MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE-MS is also demonstrated. Representative examples illustrate the applicability of CE-MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2016 The Authors ELECTROPHORESIS Published by Wiley-VCH Verlag GmbH & Co. KGaA.

  17. Mass spectrometric signatures of the blood plasma metabolome for disease diagnostics.

    Science.gov (United States)

    Lokhov, Petr G; Balashova, Elena E; Voskresenskaya, Anna A; Trifonova, Oxana P; Maslov, Dmitry L; Archakov, Alexander I

    2016-01-01

    In metabolomics, a large number of small molecules can be detected in a single run. However, metabolomic data do not include the absolute concentrations of each metabolite. Generally, mass spectrometry analyses provide metabolite concentrations that are derived from mass peak intensities, and the peak intensities are strictly dependent on the type of mass spectrometer used, as well as the technical characteristics, options and protocols applied. To convert mass peak intensities to actual concentrations, calibration curves have to be generated for each metabolite, and this represents a significant challenge depending on the number of metabolites that are detected and involved in metabolome-based diagnostics. To overcome this limitation, and to facilitate the development of diagnostic tests based on metabolomics, mass peak intensities may be expressed in quintiles. The present study demonstrates the advantage of this approach. The examples of diagnostic signatures, which were designed in accordance to this approach, are provided for lung and prostate cancer (leading causes of mortality due to cancer in developed countries) and impaired glucose tolerance (which precedes type 2 diabetes, the most common endocrinology disease worldwide).

  18. Metabolomic applications to decipher gut microbial metabolic influence in health and disease

    Directory of Open Access Journals (Sweden)

    Francois-Pierre eMartin

    2012-04-01

    Full Text Available Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial mammalian cross-talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease aetiology, diagnostic stratification and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR spectroscopy and mass spectrometry (MS provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation.

  19. Analytical metabolomics: nutritional opportunities for personalized health.

    Science.gov (United States)

    McNiven, Elizabeth M S; German, J Bruce; Slupsky, Carolyn M

    2011-11-01

    Nutrition is the cornerstone of health; survival depends on acquiring essential nutrients, and dietary components can both prevent and promote disease. Metabolomics, the study of all small molecule metabolic products in a system, has been shown to provide a detailed snapshot of the body's processes at any particular point in time, opening up the possibility of monitoring health and disease, prevention and treatment. Metabolomics has the potential to fundamentally change clinical chemistry and, by extension, the fields of nutrition, toxicology and medicine. Technological advances, combined with new knowledge of the human genome and gut microbiome, have made and will continue to make possible earlier, more accurate, less invasive diagnoses, all while enhancing our understanding of the root causes of disease and leading to a generation of dietary recommendations that enable optimal health. This article reviews the recent contributions of metabolomics to the fields of nutrition, toxicology and medicine. It is expected that these fields will eventually blend together through development of new technologies in metabolomics and genomics into a new area of clinical chemistry: personalized medicine.

  20. Metabolomics in the fight against malaria

    Directory of Open Access Journals (Sweden)

    Jorge L Salinas

    2014-08-01

    Full Text Available Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC, a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.

  1. Analysis of metabolomics data from twin families

    NARCIS (Netherlands)

    Draisma, Hermanus Henricus Maria

    2011-01-01

    Metabolomics is the comprehensive analysis of small molecules involved in metabolism, on the basis of samples that have been obtained from organisms in a given physiological state. Data obtained from measurements of trait levels in twin families can be used to elucidate the importance of genetic and

  2. Metabolomics for Plant Improvement: Status and Prospects

    Directory of Open Access Journals (Sweden)

    Rakesh Kumar

    2017-08-01

    Full Text Available Post-genomics era has witnessed the development of cutting-edge technologies that have offered cost-efficient and high-throughput ways for molecular characterization of the function of a cell or organism. Large-scale metabolite profiling assays have allowed researchers to access the global data sets of metabolites and the corresponding metabolic pathways in an unprecedented way. Recent efforts in metabolomics have been directed to improve the quality along with a major focus on yield related traits. Importantly, an integration of metabolomics with other approaches such as quantitative genetics, transcriptomics and genetic modification has established its immense relevance to plant improvement. An effective combination of these modern approaches guides researchers to pinpoint the functional gene(s and the characterization of massive metabolites, in order to prioritize the candidate genes for downstream analyses and ultimately, offering trait specific markers to improve commercially important traits. This in turn will improve the ability of a plant breeder by allowing him to make more informed decisions. Given this, the present review captures the significant leads gained in the past decade in the field of plant metabolomics accompanied by a brief discussion on the current contribution and the future scope of metabolomics to accelerate plant improvement.

  3. NMR-based Metabolomics for Cancer Research

    Science.gov (United States)

    Metabolomics is considered as a complementary tool to other omics platforms to provide a snapshot of the cellular biochemistry and physiology taking place at any instant. Metabolmics approaches have been widely used to provide comprehensive and quantitative analyses of the metabo...

  4. Analyzing metabolomics-based challenge tests

    NARCIS (Netherlands)

    Vis, D.J.; Westerhuis, J.A.; Jacobs, D.M.; Duynhoven, van J.P.M.; Wopereis, S.; Ommen, van B.; Hendriks, M.M.W.B.; Smilde, A.K.

    2015-01-01

    Challenge tests are used to assess the resilience of human beings to perturbations by analyzing responses to detect functional abnormalities. Well known examples are allergy tests and glucose tolerance tests. Increasingly, metabolomics analysis of blood or serum samples is used to analyze the biolog

  5. Data fusion in metabolomic cancer diagnostics

    DEFF Research Database (Denmark)

    Bro, Rasmus; Nielsen, Hans Jørgen; Savorani, Francesco

    2013-01-01

    We have recently shown that fluorescence spectroscopy of plasma samples has promising abilities regarding early detection of colorectal cancer. In the present paper, these results were further developed by combining fluorescence with the biomarkers, CEA and TIMP-1 and traditional metabolomic...

  6. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis.

    Science.gov (United States)

    Alonso, Cristina; Fernández-Ramos, David; Varela-Rey, Marta; Martínez-Arranz, Ibon; Navasa, Nicolás; Van Liempd, Sebastiaan M; Lavín Trueba, José L; Mayo, Rebeca; Ilisso, Concetta P; de Juan, Virginia G; Iruarrizaga-Lejarreta, Marta; delaCruz-Villar, Laura; Mincholé, Itziar; Robinson, Aaron; Crespo, Javier; Martín-Duce, Antonio; Romero-Gómez, Manuel; Sann, Holger; Platon, Julian; Van Eyk, Jennifer; Aspichueta, Patricia; Noureddin, Mazen; Falcón-Pérez, Juan M; Anguita, Juan; Aransay, Ana M; Martínez-Chantar, María Luz; Lu, Shelly C; Mato, José M

    2017-05-01

    Nonalcoholic fatty liver disease (NAFLD) is a consequence of defects in diverse metabolic pathways that involve hepatic accumulation of triglycerides. Features of these aberrations might determine whether NAFLD progresses to nonalcoholic steatohepatitis (NASH). We investigated whether the diverse defects observed in patients with NAFLD are caused by different NAFLD subtypes with specific serum metabolomic profiles, and whether these can distinguish patients with NASH from patients with simple steatosis. We collected liver and serum from methionine adenosyltransferase 1a knockout (MAT1A-KO) mice, which have chronically low levels of hepatic S-adenosylmethionine (SAMe) and spontaneously develop steatohepatitis, as well as C57Bl/6 mice (controls); the metabolomes of all samples were determined. We also analyzed serum metabolomes of 535 patients with biopsy-proven NAFLD (353 with simple steatosis and 182 with NASH) and compared them with serum metabolomes of mice. MAT1A-KO mice were also given SAMe (30 mg/kg/day for 8 weeks); liver samples were collected and analyzed histologically for steatohepatitis. Livers of MAT1A-KO mice were characterized by high levels of triglycerides, diglycerides, fatty acids, ceramides, and oxidized fatty acids, as well as low levels of SAMe and downstream metabolites. There was a correlation between liver and serum metabolomes. We identified a serum metabolomic signature associated with MAT1A-KO mice that also was present in 49% of the patients; based on this signature, we identified 2 NAFLD subtypes. We identified specific panels of markers that could distinguish patients with NASH from patients with simple steatosis for each subtype of NAFLD. Administration of SAMe reduced features of steatohepatitis in MAT1A-KO mice. In an analysis of serum metabolomes of patients with NAFLD and MAT1A-KO mice with steatohepatitis, we identified 2 major subtypes of NAFLD and markers that differentiate steatosis from NASH in each subtype. These might be

  7. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    NARCIS (Netherlands)

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites

  8. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    NARCIS (Netherlands)

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites rele

  9. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    NARCIS (Netherlands)

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites rele

  10. A Reexamination of Methods of Hierarchic Composition in the AHP

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhi-yong

    2002-01-01

    This paper demonstrates that we should use two different hierarchic composition methods for the two different types of levels in the AHP. The first method is using the weighted geometric mean to synthesize the judgments of alternative-type-level elements, which is the only hierarchic composition method for the alternative-type level in an AHP hierarchy, and the rank is preserved automatically. The second one is using the weighted arithmetic mean to synthesize the priorities of the criteria-type-level elements, which is the only hierarchic composition method for all the criteria-type levels, and rank reversals are allowed.

  11. Metabolomics of Clostridial Biofuel Production

    Energy Technology Data Exchange (ETDEWEB)

    Rabinowitz, Joshua D [Princeton Univ., NJ (United States); Aristilde, Ludmilla [Cornell Univ., Ithaca, NY (United States); Amador-Noguez, Daniel [Univ. of Wisconsin, Madison, WI (United States)

    2015-09-08

    Members of the genus Clostridium collectively have the ideal set of the metabolic capabilities for fermentative biofuel production: cellulose degradation, hydrogen production, and solvent excretion. No single organism, however, can effectively convert cellulose into biofuels. Here we developed, using metabolomics and isotope tracers, basic science knowledge of Clostridial metabolism of utility for future efforts to engineer such an organism. In glucose fermentation carried out by the biofuel producer Clostridium acetobutylicum, we observed a remarkably ordered series of metabolite concentration changes as the fermentation progressed from acidogenesis to solventogenesis. In general, high-energy compounds decreased while low-energy species increased during solventogenesis. These changes in metabolite concentrations were accompanied by large changes in intracellular metabolic fluxes, with pyruvate directed towards acetyl-CoA and solvents instead of oxaloacetate and amino acids. Thus, the solventogenic transition involves global remodeling of metabolism to redirect resources from biomass production into solvent production. In contrast to C. acetobutylicum, which is an avid fermenter, C. cellulolyticum metabolizes glucose only slowly. We find that glycolytic intermediate concentrations are radically different from fast fermenting organisms. Associated thermodynamic and isotope tracer analysis revealed that the full glycolytic pathway in C. cellulolyticum is reversible. This arises from changes in cofactor utilization for phosphofructokinase and an alternative pathway from phosphoenolpyruvate to pyruvate. The net effect is to increase the high-energy phosphate bond yield of glycolysis by 150% (from 2 to 5) at the expense of lower net flux. Thus, C. cellulolyticum prioritizes glycolytic energy efficiency over speed. Degradation of cellulose results in other sugars in addition to glucose. Simultaneous feeding of stable isotope-labeled glucose and unlabeled pentose sugars

  12. An Unsupervised Model for Exploring Hierarchical Semantics from Social Annotations

    Science.gov (United States)

    Zhou, Mianwei; Bao, Shenghua; Wu, Xian; Yu, Yong

    This paper deals with the problem of exploring hierarchical semantics from social annotations. Recently, social annotation services have become more and more popular in Semantic Web. It allows users to arbitrarily annotate web resources, thus, largely lowers the barrier to cooperation. Furthermore, through providing abundant meta-data resources, social annotation might become a key to the development of Semantic Web. However, on the other hand, social annotation has its own apparent limitations, for instance, 1) ambiguity and synonym phenomena and 2) lack of hierarchical information. In this paper, we propose an unsupervised model to automatically derive hierarchical semantics from social annotations. Using a social bookmark service Del.icio.us as example, we demonstrate that the derived hierarchical semantics has the ability to compensate those shortcomings. We further apply our model on another data set from Flickr to testify our model's applicability on different environments. The experimental results demonstrate our model's efficiency.

  13. Comprehensive metabolomics identified lipid peroxidation as a prominent feature in human plasma of patients with coronary heart diseases

    Directory of Open Access Journals (Sweden)

    Jianhong Lu

    2017-08-01

    Full Text Available Coronary heart disease (CHD is a complex human disease associated with inflammation and oxidative stress. The underlying mechanisms and diagnostic biomarkers for the different types of CHD remain poorly defined. Metabolomics has been increasingly recognized as an enabling technique with the potential to identify key metabolomic features in an attempt to understand the pathophysiology and differentiate different stages of CHD. We performed comprehensive metabolomic analysis in human plasma from 28 human subjects with stable angina (SA, myocardial infarction (MI, and healthy control (HC. Subsequent analysis demonstrated a uniquely altered metabolic profile in these CHD: a total of 18, 37 and 36 differential metabolites were identified to distinguish SA from HC, MI from SA, and MI from HC groups respectively. Among these metabolites, glycerophospholipid (GPL metabolism emerged as the most significantly disturbed pathway. Next, we used a targeted metabolomic approach to systematically analyze GPL, oxidized phospholipid (oxPL, and downstream metabolites derived from polyunsaturated fatty acids (PUFAs, such as arachidonic acid and linoleic acid. Surprisingly, lipids associated with lipid peroxidation (LPO pathways including oxidized PL and isoprostanes, isomers of prostaglandins, were significantly elevated in plasma of MI patients comparing to HC and SA, consistent with the notion that oxidative stress-induced LPO is a prominent feature in CHD. Our studies using the state-of-the-art metabolomics help to understand the underlying biological mechanisms involved in the pathogenesis of CHD; LPO metabolites may serve as potential biomarkers to differentiation MI from SA and HC.

  14. Present and foreseeable future of metabolomics in forensic analysis.

    Science.gov (United States)

    Castillo-Peinado, L S; Luque de Castro, M D

    2016-06-21

    The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed.

  15. Metabolomics and its application to studying metal toxicity.

    Science.gov (United States)

    Booth, Sean C; Workentine, Matthew L; Weljie, Aalim M; Turner, Raymond J

    2011-11-01

    Here we explain the omics approach of metabolomics and how it can be applied to study a physiological response to toxic metal exposure. This review aims to educate the metallomics field to the tool of metabolomics. Metabolomics is becoming an increasingly used tool to compare natural and challenged states of various organisms, from disease states in humans to toxin exposure to environmental systems. This approach is key to understanding and identifying the cellular or biochemical targets of metals and the underlying physiological response. Metabolomics steps are described and overviews of its application to metal toxicity to organisms are given. As this approach is very new there are yet only a small number of total studies and therefore only a brief overview of some metal metabolomics studies is described. A frank critical evaluation of the approach is given to provide newcomers to the method a clear idea of the challenges and the rewards of applying metabolomics to their research.

  16. Development of a metabolomic radiation signature in urine from patients undergoing total body irradiation.

    Science.gov (United States)

    Laiakis, Evagelia C; Mak, Tytus D; Anizan, Sebastien; Amundson, Sally A; Barker, Christopher A; Wolden, Suzanne L; Brenner, David J; Fornace, Albert J

    2014-04-01

    The emergence of the threat of radiological terrorism and other radiological incidents has led to the need for development of fast, accurate and noninvasive methods for detection of radiation exposure. The purpose of this study was to extend radiation metabolomic biomarker discovery to humans, as previous studies have focused on mice. Urine was collected from patients undergoing total body irradiation at Memorial Sloan-Kettering Cancer Center prior to hematopoietic stem cell transplantation at 4-6 h postirradiation (a single dose of 1.25 Gy) and 24 h (three fractions of 1.25 Gy each). Global metabolomic profiling was obtained through analysis with ultra performance liquid chromatography coupled to time-of-flight mass spectrometry (TOFMS). Prior to further analyses, each sample was normalized to its respective creatinine level. Statistical analysis was conducted by the nonparametric Kolmogorov-Smirnov test and the Fisher's exact test and markers were validated against pure standards. Seven markers showed distinct differences between pre- and post-exposure samples. Of those, trimethyl-l-lysine and the carnitine conjugates acetylcarnitine, decanoylcarnitine and octanoylcarnitine play an important role in the transportation of fatty acids across mitochondria for subsequent fatty acid β-oxidation. The remaining metabolites, hypoxanthine, xanthine and uric acid are the final products of the purine catabolism pathway, and high levels of excretion have been associated with increased oxidative stress and radiation induced DNA damage. Further analysis revealed sex differences in the patterns of excretion of the markers, demonstrating that generation of a sex-specific metabolomic signature will be informative and can provide a quick and reliable assessment of individuals in a radiological scenario. This is the first radiation metabolomics study in human urine laying the foundation for the use of metabolomics in biodosimetry and providing confidence in biomarker

  17. Hierarchical partial order ranking.

    Science.gov (United States)

    Carlsen, Lars

    2008-09-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritization of polluted sites is given.

  18. Trees and Hierarchical Structures

    CERN Document Server

    Haeseler, Arndt

    1990-01-01

    The "raison d'etre" of hierarchical dustering theory stems from one basic phe­ nomenon: This is the notorious non-transitivity of similarity relations. In spite of the fact that very often two objects may be quite similar to a third without being that similar to each other, one still wants to dassify objects according to their similarity. This should be achieved by grouping them into a hierarchy of non-overlapping dusters such that any two objects in ~ne duster appear to be more related to each other than they are to objects outside this duster. In everyday life, as well as in essentially every field of scientific investigation, there is an urge to reduce complexity by recognizing and establishing reasonable das­ sification schemes. Unfortunately, this is counterbalanced by the experience of seemingly unavoidable deadlocks caused by the existence of sequences of objects, each comparatively similar to the next, but the last rather different from the first.

  19. Optimisation by hierarchical search

    Science.gov (United States)

    Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

    2015-03-01

    Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

  20. Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress

    Science.gov (United States)

    2015-10-01

    metabolomic profiling of women with and without post- traumatic stress disorder (PTSD) to derive a signature of chronic stress and then apply that metabolomic...noted that phobic anxiety and social isolation were suggestively associated with increased risk of ovarian cancer (hazard ratios of 1.14 and 1.24...TERMS ovarian cancer, psychosocial stress, depression, anxiety , social support, metabolomics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

  1. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

    2012-01-01

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

  2. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L; Bod, Rens; Christiansen, Morten H

    2012-11-22

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science.

  3. Associative Hierarchical Random Fields.

    Science.gov (United States)

    Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

    2014-06-01

    This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.

  4. NMR-based metabolomics for the environmental assessment of Kaohsiung Harbor sediments exemplified by a marine amphipod (Hyalella azteca).

    Science.gov (United States)

    Chiu, K H; Dong, C D; Chen, C F; Tsai, M L; Ju, Y R; Chen, T M; Chen, C W

    2017-03-03

    Inflow of wastewater from upstream causes a large flux of pollutants to enter Kaohsiung Harbor in Taiwan daily. To reveal the ecological risk posed by Kaohsiung Harbor sediments, an ecological metabolomic approach was employed to investigate environmental factors pertinent to the physiological regulation of the marine amphipod Hyalella azteca. The amphipods were exposed to sediments collected from different stream inlets of the Love River (LR), Canon River (CR), Jen-Gen River (JR), and Salt River (SR). Harbor entrance 1 (E1) was selected as a reference site. After 10-day exposure, metabolomic analysis of the Hyalella azteca revealed differences between two groups: {E1, LR, CR} and {JR, SR}. The metabolic pathways identified in the two groups of amphipods were significantly different. The results demonstrated that NMR-based metabolomics can be effectively used to characterize metabolic response related to sediment from polluted areas.

  5. An LC-MS-based metabolomics approach for exploring urinary metabolome modifications after cocoa consumption.

    Science.gov (United States)

    Llorach, Rafael; Urpi-Sarda, Mireia; Jauregui, Olga; Monagas, Maria; Andres-Lacueva, Cristina

    2009-11-01

    Cocoa-phytochemicals have been related to the health-benefits of cocoa consumption. Metabolomics has been proposed as a powerful tool to characterize both the intake and the effects on the metabolism of dietary components. Human urine metabolome modifications after single cocoa intake were explored in a randomized, crossed, and controlled trial. After overnight fasting, 10 subjects consumed randomly either a single dose of cocoa powder with milk or water, or milk without cocoa. Urine samples were collected before the ingestion and at 0-6, 6-12, and 12-24-h after test-meals consumption. Samples were analyzed by HPLC-q-ToF, followed by multivariate data analysis. Results revealed an important effect on urinary metabolome during the 24 h after cocoa powder intake. These changes were not influenced by matrix as no global differences were found between cocoa powder consumption with milk or with water. Overall, 27 metabolites related to cocoa-phytochemicals, including alkaloid derivatives, polyphenol metabolites (both host and microbial metabolites) and processing-derived products such as diketopiperazines, were identified as the main contributors to the urinary modifications after cocoa powder intake. These results confirm that metabolomics will contribute to better characterization of the urinary metabolome in order to further explore the metabolism of phytochemicals and its relation with human health.

  6. Tested Demonstrations.

    Science.gov (United States)

    Sands, Robert; And Others

    1982-01-01

    Procedures for two demonstrations are provided. The solubility of ammonia gas in water is demonstrated by introducing water into a closed can filled with the gas, collapsing the can. The second demonstration relates scale of standard reduction potentials to observed behavior of metals in reactions with hydrogen to produce hydrogen gas. (Author/JN)

  7. Application of metabolomics technology in the research of Chinese medicine.

    Science.gov (United States)

    Liu, Ping; Wang, Ping

    2014-04-01

    In recent years, a novel analytical technology, metabolomics is widely used in the modern research of Chinese medicine (CM). Metabolomics adopts a "top-down" strategy to reflect the function of organisms from terminal symptoms of metabolic network and understand metabolic changes of a complete system caused by interventions. As a holistic approach, metabolomics technology, including nuclear magnetic resonance, gas chromatography-mass spectrometry, and liquid chromatography-mass spectrometry, favorable to express the meaning of basic theories of CM, CM syndrome and Chinese herb. Therefore, we believe that metabolomics technology will greatly benefit to development for the research of CM in the light of modern sciences.

  8. MVAPACK: a complete data handling package for NMR metabolomics.

    Science.gov (United States)

    Worley, Bradley; Powers, Robert

    2014-05-16

    Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set.

  9. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    CERN Document Server

    Jelonek, M

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.

  10. Eicosapentaenoic acid prevents high fat diet-induced metabolic disorders: Genomic and metabolomic analyses of underlying mechanism

    Science.gov (United States)

    Previously our lab demonstrated eicosapenaenoic acid (EPA)'s ability to prevent high-fat (HF) diet-induced obesity by decreasing insulin resistance, glucose intolerance and inflammation. In the current study, we used genomic and metabolomic approaches to further investigate the molecular basis for t...

  11. Combining Amine Metabolomics and Quantitative Proteomics of Cancer Cells Using Derivatization with Isobaric Tags

    OpenAIRE

    Murphy,J. Patrick; Everley, Robert A.; Coloff, Jonathan L.; Steven P. Gygi

    2014-01-01

    Quantitative metabolomics and proteomics technologies are powerful approaches to explore cellular metabolic regulation. Unfortunately, combining the two technologies typically requires different LC-MS setups for sensitive measurement of metabolites and peptides. One approach to enhance the analysis of certain classes of metabolites is by derivatization with various types of tags to increase ionization and chromatographic efficiency. We demonstrate here that derivatization of amine metabolites...

  12. Hierarchical Boltzmann simulations and model error estimation

    Science.gov (United States)

    Torrilhon, Manuel; Sarna, Neeraj

    2017-08-01

    A hierarchical simulation approach for Boltzmann's equation should provide a single numerical framework in which a coarse representation can be used to compute gas flows as accurately and efficiently as in computational fluid dynamics, but a subsequent refinement allows to successively improve the result to the complete Boltzmann result. We use Hermite discretization, or moment equations, for the steady linearized Boltzmann equation for a proof-of-concept of such a framework. All representations of the hierarchy are rotationally invariant and the numerical method is formulated on fully unstructured triangular and quadrilateral meshes using a implicit discontinuous Galerkin formulation. We demonstrate the performance of the numerical method on model problems which in particular highlights the relevance of stability of boundary conditions on curved domains. The hierarchical nature of the method allows also to provide model error estimates by comparing subsequent representations. We present various model errors for a flow through a curved channel with obstacles.

  13. Object tracking with hierarchical multiview learning

    Science.gov (United States)

    Yang, Jun; Zhang, Shunli; Zhang, Li

    2016-09-01

    Building a robust appearance model is useful to improve tracking performance. We propose a hierarchical multiview learning framework to construct the appearance model, which has two layers for tracking. On the top layer, two different views of features, grayscale value and histogram of oriented gradients, are adopted for representation under the cotraining framework. On the bottom layer, for each view of each feature, three different random subspaces are generated to represent the appearance from multiple views. For each random view submodel, the least squares support vector machine is employed to improve the discriminability for concrete and efficient realization. These two layers are combined to construct the final appearance model for tracking. The proposed hierarchical model assembles two types of multiview learning strategies, in which the appearance can be described more accurately and robustly. Experimental results in the benchmark dataset demonstrate that the proposed method can achieve better performance than many existing state-of-the-art algorithms.

  14. Assembling hierarchical cluster solids with atomic precision.

    Science.gov (United States)

    Turkiewicz, Ari; Paley, Daniel W; Besara, Tiglet; Elbaz, Giselle; Pinkard, Andrew; Siegrist, Theo; Roy, Xavier

    2014-11-12

    Hierarchical solids created from the binary assembly of cobalt chalcogenide and iron oxide molecular clusters are reported. Six different molecular clusters based on the octahedral Co6E8 (E = Se or Te) and the expanded cubane Fe8O4 units are used as superatomic building blocks to construct these crystals. The formation of the solid is driven by the transfer of charge between complementary electron-donating and electron-accepting clusters in solution that crystallize as binary ionic compounds. The hierarchical structures are investigated by single-crystal X-ray diffraction, providing atomic and superatomic resolution. We report two different superstructures: a superatomic relative of the CsCl lattice type and an unusual packing arrangement based on the double-hexagonal close-packed lattice. Within these superstructures, we demonstrate various compositions and orientations of the clusters.

  15. Metabolomic analysis of three Mollicute species.

    Directory of Open Access Journals (Sweden)

    Anna A Vanyushkina

    Full Text Available We present a systematic study of three bacterial species that belong to the class Mollicutes, the smallest and simplest bacteria, Spiroplasma melliferum, Mycoplasma gallisepticum, and Acholeplasma laidlawii. To understand the difference in the basic principles of metabolism regulation and adaptation to environmental conditions in the three species, we analyzed the metabolome of these bacteria. Metabolic pathways were reconstructed using the proteogenomic annotation data provided by our lab. The results of metabolome, proteome and genome profiling suggest a fundamental difference in the adaptation of the three closely related Mollicute species to stress conditions. As the transaldolase is not annotated in Mollicutes, we propose variants of the pentose phosphate pathway catalyzed by annotated enzymes for three species. For metabolite detection we employed high performance liquid chromatography coupled with mass spectrometry. We used liquid chromatography method - hydrophilic interaction chromatography with silica column - as it effectively separates highly polar cellular metabolites prior to their detection by mass spectrometer.

  16. Metabolomics analysis of shucked mussels' freshness.

    Science.gov (United States)

    Aru, Violetta; Pisano, Maria Barbara; Savorani, Francesco; Engelsen, Søren Balling; Cosentino, Sofia; Cesare Marincola, Flaminia

    2016-08-15

    In this work a NMR metabolomics approach was applied to analyze changes in the metabolic profile of the bivalve mollusk Mytilus galloprovincialis upon storage at 0°C and 4°C for 10 and 6 days, respectively. The most significant microbial groups involved in spoilage of mussels were also investigated. The time-related metabolic signature of mussels was analysed by Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) which revealed a clear discrimination between the fresh samples and those stored at 0°C and 4°C. The results evidenced a noticeable increase in acetate, lactate, succinate, alanine, branched chain amino acids, trimethylamine and a progressive decline of osmolytes like betaine, homarine and taurine during storage. Exploration of the correlations of these metabolites with microbial counts suggested their use as potential biomarkers of spoilage. The results support the use of NMR metabolomics as a valuable tool to provide information on seafood freshness.

  17. Global open data management in metabolomics.

    Science.gov (United States)

    Haug, Kenneth; Salek, Reza M; Steinbeck, Christoph

    2017-02-01

    Chemical Biology employs chemical synthesis, analytical chemistry and other tools to study biological systems. Recent advances in both molecular biology such as next generation sequencing (NGS) have led to unprecedented insights towards the evolution of organisms' biochemical repertoires. Because of the specific data sharing culture in Genomics, genomes from all kingdoms of life become readily available for further analysis by other researchers. While the genome expresses the potential of an organism to adapt to external influences, the Metabolome presents a molecular phenotype that allows us to asses the external influences under which an organism exists and develops in a dynamic way. Steady advancements in instrumentation towards high-throughput and highresolution methods have led to a revival of analytical chemistry methods for the measurement and analysis of the metabolome of organisms. This steady growth of metabolomics as a field is leading to a similar accumulation of big data across laboratories worldwide as can be observed in all of the other omics areas. This calls for the development of methods and technologies for handling and dealing with such large datasets, for efficiently distributing them and for enabling re-analysis. Here we describe the recently emerging ecosystem of global open-access databases and data exchange efforts between them, as well as the foundations and obstacles that enable or prevent the data sharing and reanalysis of this data. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  18. Metabolomics as a diagnostic tool in gastroenterology

    Institute of Scientific and Technical Information of China (English)

    Vicky; De; Preter; Kristin; Verbeke

    2013-01-01

    Metabolomics has increasingly been applied in addition to other "omic" approaches in the study of the pathophysiology of different gastrointestinal diseases.Metabolites represent molecular readouts of the cell status reflecting a physiological phenotype.In addition,changes in metabolite concentrations induced by exogenous factors such as environmental and dietary factors which do not affect the genome,are taken into account.Metabolic reactions initiated by the host or gut microbiota can lead to "marker" metabolites present in different biological fluids that allow differentiation between health and disease.Several lines of evidence implicated the involvement of intestinal microbiota in the pathogenesis of inflammatory bowel disease(IBD).Also in irritable bowel syndrome(IBS),a role of an abnormal microbiota composition,so-called dysbiosis,is supported by experimental data.These compositional alterations could play a role in the aetiology of both diseases by altering the metabolic activities of the gut bacteria.Several studies have applied a metabolomic approach to identify these metabolite signatures.However,before translating a potential metabolite biomarker into clinical use,additional validation studies are required.This review summarizes contributions that metabolomics has made in IBD and IBS and presents potential future directions within the field.

  19. Fractal Analysis Based on Hierarchical Scaling in Complex Systems

    CERN Document Server

    Chen, Yanguang

    2016-01-01

    A fractal is in essence a hierarchy with cascade structure, which can be described with a set of exponential functions. From these exponential functions, a set of power laws indicative of scaling can be derived. Hierarchy structure and spatial network proved to be associated with one another. This paper is devoted to exploring the theory of fractal analysis of complex systems by means of hierarchical scaling. Two research methods are utilized to make this study, including logic analysis method and empirical analysis method. The main results are as follows. First, a fractal system such as Cantor set is described from the hierarchical angle of view; based on hierarchical structure, three approaches are proposed to estimate fractal dimension. Second, the hierarchical scaling can be generalized to describe multifractals, fractal complementary sets, and self-similar curve such as logarithmic spiral. Third, complex systems such as urban system are demonstrated to be a self-similar hierarchy. The human settlements i...

  20. What are hierarchical models and how do we analyze them?

    Science.gov (United States)

    Royle, Andy

    2016-01-01

    In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood and Bayesian perspectives. We go through the mechanics of maximizing the likelihood and characterizing the posterior distribution by Markov chain Monte Carlo (MCMC) methods. We give a general perspective on topics such as model selection and assessment of model fit, although we demonstrate these topics in practice in later chapters (especially Chapters 5, 6, 7, and 10 Chapter 5 Chapter 6 Chapter 7 Chapter 10)

  1. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    OpenAIRE

    Jelonek, Magdalena

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of m...

  2. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L., Ed.

    1983-01-01

    Free radical chlorination of methane is used in organic chemistry to introduce free radical/chain reactions. In spite of its common occurrence, demonstrations of the reaction are uncommon. Therefore, such a demonstration is provided, including background information, preparation of reactants/reaction vessel, introduction of reactants, irradiation,…

  3. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L., Ed.

    1983-01-01

    Discusses a supplement to the "water to rose" demonstration in which a pink color is produced. Also discusses blood buffer demonstrations, including hydrolysis of sodium bicarbonate, simulated blood buffer, metabolic acidosis, natural compensation of metabolic acidosis, metabolic alkalosis, acidosis treatment, and alkalosis treatment. Procedures…

  4. Complete Demonstration.

    Science.gov (United States)

    Yelon, Stephen; Maddocks, Peg

    1986-01-01

    Describes four-step approach to educational demonstration: tell learners they will have to perform; what they should notice; describe each step before doing it; and require memorization of steps. Examples illustrate use of this process to demonstrate a general mental strategy, and industrial design, supervisory, fine motor, and specific…

  5. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L., Ed.

    1987-01-01

    Describes two laboratory demonstrations in chemistry. One uses dry ice, freon, and freezer bags to demonstrate volume changes, vapor-liquid equilibrium, a simulation of a rain forest, and vaporization. The other uses the clock reaction technique to illustrate fast reactions and kinetic problems in releasing carbon dioxide during respiration. (TW)

  6. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L., Ed.

    1986-01-01

    Outlines a simple, inexpensive way of demonstrating electroplating using the reaction between nickel ions and copper metal. Explains how to conduct a demonstration of the electrolysis of water by using a colored Na2SO4 solution as the electrolyte so that students can observe the pH changes. (TW)

  7. Hierarchical fringe tracking

    CERN Document Server

    Petrov, Romain G; Boskri, Abdelkarim; Folcher, Jean-Pierre; Lagarde, Stephane; Bresson, Yves; Benkhaldoum, Zouhair; Lazrek, Mohamed; Rakshit, Suvendu

    2014-01-01

    The limiting magnitude is a key issue for optical interferometry. Pairwise fringe trackers based on the integrated optics concepts used for example in GRAVITY seem limited to about K=10.5 with the 8m Unit Telescopes of the VLTI, and there is a general "common sense" statement that the efficiency of fringe tracking, and hence the sensitivity of optical interferometry, must decrease as the number of apertures increases, at least in the near infrared where we are still limited by detector readout noise. Here we present a Hierarchical Fringe Tracking (HFT) concept with sensitivity at least equal to this of a two apertures fringe trackers. HFT is based of the combination of the apertures in pairs, then in pairs of pairs then in pairs of groups. The key HFT module is a device that behaves like a spatial filter for two telescopes (2TSF) and transmits all or most of the flux of a cophased pair in a single mode beam. We give an example of such an achromatic 2TSF, based on very broadband dispersed fringes analyzed by g...

  8. Hierarchical Reverberation Mapping

    CERN Document Server

    Brewer, Brendon J

    2013-01-01

    Reverberation mapping (RM) is an important technique in studies of active galactic nuclei (AGN). The key idea of RM is to measure the time lag $\\tau$ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of $\\tau$ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass $M_{\\rm BH}$. A major difficulty with RM campaigns is the large amount of data needed to measure $\\tau$. Recently, Fine et al (2012) introduced a new approach to RM where the BLR light curve is sparsely sampled, but this is counteracted by observing a large sample of AGN, rather than a single system. The results are combined to infer properties of the sample of AGN. In this letter we implement this method using a hierarchical Bayesian model and contrast this with the results from the previous stacked cross-correlation technique. We find that our inferences are more precise and allow fo...

  9. On the geostatistical characterization of hierarchical media

    Science.gov (United States)

    Neuman, Shlomo P.; Riva, Monica; Guadagnini, Alberto

    2008-02-01

    The subsurface consists of porous and fractured materials exhibiting a hierarchical geologic structure, which gives rise to systematic and random spatial and directional variations in hydraulic and transport properties on a multiplicity of scales. Traditional geostatistical moment analysis allows one to infer the spatial covariance structure of such hierarchical, multiscale geologic materials on the basis of numerous measurements on a given support scale across a domain or "window" of a given length scale. The resultant sample variogram often appears to fit a stationary variogram model with constant variance (sill) and integral (spatial correlation) scale. In fact, some authors, who recognize that hierarchical sedimentary architecture and associated log hydraulic conductivity fields tend to be nonstationary, nevertheless associate them with stationary "exponential-like" transition probabilities and variograms, respectively, the latter being a consequence of the former. We propose that (1) the apparent ability of stationary spatial statistics to characterize the covariance structure of nonstationary hierarchical media is an artifact stemming from the finite size of the windows within which geologic and hydrologic variables are ubiquitously sampled, and (2) the artifact is eliminated upon characterizing the covariance structure of such media with the aid of truncated power variograms, which represent stationary random fields obtained upon sampling a nonstationary fractal over finite windows. To support our opinion, we note that truncated power variograms arise formally when a hierarchical medium is sampled jointly across all geologic categories and scales within a window; cite direct evidence that geostatistical parameters (variance and integral scale) inferred on the basis of traditional variograms vary systematically with support and window scales; demonstrate the ability of truncated power models to capture these variations in terms of a few scaling parameters

  10. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

  11. Hierarchical clustering for graph visualization

    CERN Document Server

    Clémençon, Stéphan; Rossi, Fabrice; Tran, Viet Chi

    2012-01-01

    This paper describes a graph visualization methodology based on hierarchical maximal modularity clustering, with interactive and significant coarsening and refining possibilities. An application of this method to HIV epidemic analysis in Cuba is outlined.

  12. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

    The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

  13. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L.

    1990-01-01

    Included are three demonstrations that include the phase change of ice when under pressure, viscoelasticity and colloid systems, and flame tests for metal ions. The materials, procedures, probable results, and applications to real life situations are included. (KR)

  14. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L., Ed.

    1980-01-01

    Presented is a Corridor Demonstration which can be set up in readily accessible areas such as hallways or lobbies. Equipment is listed for a display of three cells (solar cells, fuel cells, and storage cells) which develop electrical energy. (CS)

  15. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L., Ed.

    1987-01-01

    Presents three demonstrations suitable for undergraduate chemistry classes. Focuses on experiments with calcium carbide, the induction by iron of the oxidation of iodide by dichromate, and the classical iodine clock reaction. (ML)

  16. Environmental metabolomics: a SWOT analysis (strengths, weaknesses, opportunities, and threats).

    Science.gov (United States)

    Miller, Marion G

    2007-02-01

    Metabolomic approaches have the potential to make an exceptional contribution to understanding how chemicals and other environmental stressors can affect both human and environmental health. However, the application of metabolomics to environmental exposures, although getting underway, has not yet been extensively explored. This review will use a SWOT analysis model to discuss some of the strengths, weaknesses, opportunities, and threats that are apparent to an investigator venturing into this relatively new field. SWOT has been used extensively in business settings to uncover new outlooks and identify problems that would impede progress. The field of environmental metabolomics provides great opportunities for discovery, and this is recognized by a high level of interest in potential applications. However, understanding the biological consequence of environmental exposures can be confounded by inter- and intra-individual differences. Metabolomic profiles can yield a plethora of data, the interpretation of which is complex and still being evaluated and researched. The development of the field will depend on the availability of technologies for data handling and that permit ready access metabolomic databases. Understanding the relevance of metabolomic endpoints to organism health vs adaptation vs variation is an important step in understanding what constitutes a substantive environmental threat. Metabolomic applications in reproductive research are discussed. Overall, the development of a comprehensive mechanistic-based interpretation of metabolomic changes offers the possibility of providing information that will significantly contribute to the protection of human health and the environment.

  17. Plant metabolomics and its potential application for human nutrition

    NARCIS (Netherlands)

    Hall, R.D.; Brouwer, I.D.; Fitzgerald, M.A.

    2008-01-01

    With the growing interest in the use of metabolomic technologies for a wide range of biological targets, food applications related to nutrition and quality are rapidly emerging. Metabolomics offers us the opportunity to gain deeper insights into, and have better control of, the fundamental biochemic

  18. Plant metabolomics and its potential application for human nutrition

    NARCIS (Netherlands)

    Hall, R.D.; Brouwer, I.D.; Fitzgerald, M.A.

    2008-01-01

    With the growing interest in the use of metabolomic technologies for a wide range of biological targets, food applications related to nutrition and quality are rapidly emerging. Metabolomics offers us the opportunity to gain deeper insights into, and have better control of, the fundamental

  19. Gas chromatography mass spectrometry : key technology in metabolomics

    NARCIS (Netherlands)

    Koek, Maud Marijtje

    2009-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues. Gas chromatography coupled to mass spectrometry (GC-MS) is very suitable for metabolomics analysis, as it combines high separation power with sensiti

  20. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    Science.gov (United States)

    Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

    2016-09-01

    Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

  1. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    Science.gov (United States)

    Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

    2016-12-01

    Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

  2. Metabolomics for Undergraduates: Identification and Pathway Assignment of Mitochondrial Metabolites

    Science.gov (United States)

    Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E. N.; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa

    2016-01-01

    Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening…

  3. Gas chromatography mass spectrometry : key technology in metabolomics

    NARCIS (Netherlands)

    Koek, Maud Marijtje

    2009-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues. Gas chromatography coupled to mass spectrometry (GC-MS) is very suitable for metabolomics analysis, as it combines high separation power with

  4. Metabolomic Profiling of Prostate Cancer Progression During Active Surveillance

    Science.gov (United States)

    2012-10-01

    cancer or a history of transurethral resection of the prostate (TURP) for benign prostatic hypertrophy are excluded. Somewhat surprisingly...AD_________________ Award Number: W81XWH-11-1-0451 TITLE: Metabolomic Profiling of Prostate Cancer...29 September 2012 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Metabolomic Profiling of Prostate Cancer Progression During Active Surveillance 5b

  5. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  6. Semantic Image Segmentation with Contextual Hierarchical Models.

    Science.gov (United States)

    Seyedhosseini, Mojtaba; Tasdizen, Tolga

    2016-05-01

    Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

  7. Metabolomics to Decipher the Chemical Defense of Cereals against Fusarium graminearum and Deoxynivalenol Accumulation

    Science.gov (United States)

    Gauthier, Léa; Atanasova-Penichon, Vessela; Chéreau, Sylvain; Richard-Forget, Florence

    2015-01-01

    Fusarium graminearum is the causal agent of Fusarium head blight (FHB) and Gibberella ear rot (GER), two devastating diseases of wheat, barley, and maize. Furthermore, F. graminearum species can produce type B trichothecene mycotoxins that accumulate in grains. Use of FHB and GER resistant cultivars is one of the most promising strategies to reduce damage induced by F. graminearum. Combined with genetic approaches, metabolomic ones can provide powerful opportunities for plant breeding through the identification of resistant biomarker metabolites which have the advantage of integrating the genetic background and the influence of the environment. In the past decade, several metabolomics attempts have been made to decipher the chemical defense that cereals employ to counteract F. graminearum. By covering the major classes of metabolites that have been highlighted and addressing their potential role, this review demonstrates the complex and integrated network of events that cereals can orchestrate to resist to F. graminearum. PMID:26492237

  8. A comprehensive and comparative GC-MS metabolomics study of non-volatiles in Tanzanian grown mango, pineapple, jackfruit, baobab and tamarind fruits.

    Science.gov (United States)

    Khakimov, Bekzod; Mongi, Richard J; Sørensen, Klavs M; Ndabikunze, Bernadette K; Chove, Bernard E; Engelsen, Søren Balling

    2016-12-15

    Tropical fruits contribute significantly to the total fruit intake worldwide. However, their metabolomes have not yet been investigated comprehensively, as most previous studies revealed only volatile and bulk compositions. This study compares non-volatile metabolites of five fruits grown in Tanzania. A new methodology is developed for broad-spectrum GC-MS metabolomics in fruits using a new derivatization and a two dimensional peak deconvolution techniques. A total of 92 peaks were detected from fruits of which 45 were identified. Jackfruits contained the highest amount of carbohydrates, while baobab contained the highest amount of fatty acids. The highest content of organic acids was detected in tamarind. Principal component analysis revealed insights into metabolic differences and similarities, while hierarchical cluster analysis correctly grouped the fruits according to their relationships in plants' phylogenetic tree. The developed methodology could potentially be applied in large-scale studies on fruit quality, authenticity/variety, optimization of post-harvest processing and storage.

  9. Metabolomics combined with chemometric tools (PCA, HCA, PLS-DA and SVM) for screening cassava (Manihot esculenta Crantz) roots during postharvest physiological deterioration.

    Science.gov (United States)

    Uarrota, Virgílio Gavicho; Moresco, Rodolfo; Coelho, Bianca; Nunes, Eduardo da Costa; Peruch, Luiz Augusto Martins; Neubert, Enilto de Oliveira; Rocha, Miguel; Maraschin, Marcelo

    2014-10-15

    Cassava roots are an important source of dietary and industrial carbohydrates and suffer markedly from postharvest physiological deterioration (PPD). This paper deals with metabolomics combined with chemometric tools for screening the chemical and enzymatic composition in several genotypes of cassava roots during PPD. Metabolome analyses showed increases in carotenoids, flavonoids, anthocyanins, phenolics, reactive scavenging species, and enzymes (superoxide dismutase family, hydrogen peroxide, and catalase) until 3-5days postharvest. PPD correlated negatively with phenolics and carotenoids and positively with anthocyanins and flavonoids. Chemometric tools such as principal component analysis, partial least squares discriminant analysis, and support vector machines discriminated well cassava samples and enabled a good prediction of samples. Hierarchical clustering analyses grouped samples according to their levels of PPD and chemical compositions.

  10. Hierarchical architecture of active knits

    Science.gov (United States)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-12-01

    Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm.

  11. Compliance with minimum information guidelines in public metabolomics repositories.

    Science.gov (United States)

    Spicer, Rachel A; Salek, Reza; Steinbeck, Christoph

    2017-09-26

    The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards.

  12. Error Analysis and Propagation in Metabolomics Data Analysis.

    Science.gov (United States)

    Moseley, Hunter N B

    2013-01-01

    Error analysis plays a fundamental role in describing the uncertainty in experimental results. It has several fundamental uses in metabolomics including experimental design, quality control of experiments, the selection of appropriate statistical methods, and the determination of uncertainty in results. Furthermore, the importance of error analysis has grown with the increasing number, complexity, and heterogeneity of measurements characteristic of 'omics research. The increase in data complexity is particularly problematic for metabolomics, which has more heterogeneity than other omics technologies due to the much wider range of molecular entities detected and measured. This review introduces the fundamental concepts of error analysis as they apply to a wide range of metabolomics experimental designs and it discusses current methodologies for determining the propagation of uncertainty in appropriate metabolomics data analysis. These methodologies include analytical derivation and approximation techniques, Monte Carlo error analysis, and error analysis in metabolic inverse problems. Current limitations of each methodology with respect to metabolomics data analysis are also discussed.

  13. Recent developments in liquid-phase separation techniques for metabolomics.

    Science.gov (United States)

    Ramautar, Rawi; de Jong, Gerhardus J

    2014-04-01

    Metabolomics is the comprehensive analysis of low molecular weight compounds in biological samples such as cells, body fluids and tissues. Comprehensive profiling of metabolites in complex sample matrices with the current analytical toolbox remains a huge challenge. Over the past few years, liquid chromatography-mass spectrometry (LC-MS) and capillary electrophoresis-mass spectrometry (CE-MS) have emerged as powerful complementary analytical techniques in the field of metabolomics. This Review provides an update of the most recent developments in LC-MS and CE-MS for metabolomics. Concerning LC-MS, attention is paid to developments in column technology and miniaturized systems, while strategies are discussed to improve the reproducibility and the concentration sensitivity of CE-MS for metabolomics studies. Novel interfacing techniques for coupling CE to MS are also considered. Representative examples illustrate the potential of the recent developments in LC-MS and CE-MS for metabolomics. Finally, some conclusions and perspectives are provided.

  14. Metabolome analysis - mass spectrometry and microbial primary metabolites

    DEFF Research Database (Denmark)

    Højer-Pedersen, Jesper Juul

    2008-01-01

    that are highly sensitive and specific, and to undertake this challenge mass spectrometry (MS) is among the best candidates. Along with analysis of the metabolome the research area of metabolomics has evolved. Metabolomics combines metabolite profiles, data mining and biochemistry and aims at understanding...... the interplay between metabolites. In this thesis, different topics have been addressed and discussed with the aim of advancing metabolomics to explore the concept in a physiological context. The metabolome comprises a wide variety of chemical compounds that act differently upon sample preparation...... glucose, galactose or ethanol, and metabolic footprinting by mass spectrometry was used to study the influence of carbon source on the extracellular metabolites. The results showed that footprints clustered according to the carbon source. Advances in technologies for analytical chemistry have mediated...

  15. Accurate, fully-automated NMR spectral profiling for metabolomics.

    Directory of Open Access Journals (Sweden)

    Siamak Ravanbakhsh

    Full Text Available Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid, BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF, defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error, in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of

  16. Advanced hierarchical distance sampling

    Science.gov (United States)

    Royle, Andy

    2016-01-01

    In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

  17. Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis.

    Directory of Open Access Journals (Sweden)

    Ketki D Verkhedkar

    Full Text Available BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a

  18. Tested Demonstrations.

    Science.gov (United States)

    Gilbert, George L., Ed.

    1987-01-01

    Describes two demonstrations to illustrate characteristics of substances. Outlines a method to detect the changes in pH levels during the electrolysis of water. Uses water pistols, one filled with methane gas and the other filled with water, to illustrate the differences in these two substances. (TW)

  19. ICT Demonstration

    DEFF Research Database (Denmark)

    Jensen, Tine Wirenfeldt; Bay, Gina

    In this demonstration we present and discuss two interrelated on-line learning resources aimed at supporting international students at Danish universities in building study skills (the Study Metro) and avoiding plagiarism (Stopplagiarism). We emphasize the necessity of designing online learning r...

  20. A hierarchical approach to forest landscape pattern characterization.

    Science.gov (United States)

    Wang, Jialing; Yang, Xiaojun

    2012-01-01

    Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

  1. Micromechanical design of hierarchical composites using global load sharing theory

    Science.gov (United States)

    Rajan, V. P.; Curtin, W. A.

    2016-05-01

    Hierarchical composites, embodied by natural materials ranging from bone to bamboo, may offer combinations of material properties inaccessible to conventional composites. Using global load sharing (GLS) theory, a well-established micromechanics model for composites, we develop accurate numerical and analytical predictions for the strength and toughness of hierarchical composites with arbitrary fiber geometries, fiber strengths, interface properties, and number of hierarchical levels, N. The model demonstrates that two key material properties at each hierarchical level-a characteristic strength and a characteristic fiber length-control the scalings of composite properties. One crucial finding is that short- and long-fiber composites behave radically differently. Long-fiber composites are significantly stronger than short-fiber composites, by a factor of 2N or more; they are also significantly tougher because their fiber breaks are bridged by smaller-scale fibers that dissipate additional energy. Indeed, an "infinite" fiber length appears to be optimal in hierarchical composites. However, at the highest level of the composite, long fibers localize on planes of pre-existing damage, and thus short fibers must be employed instead to achieve notch sensitivity and damage tolerance. We conclude by providing simple guidelines for microstructural design of hierarchical composites, including the selection of N, the fiber lengths, the ratio of length scales at successive hierarchical levels, the fiber volume fractions, and the desired properties of the smallest-scale reinforcement. Our model enables superior hierarchical composites to be designed in a rational way, without resorting either to numerical simulation or trial-and-error-based experimentation.

  2. 演示即可视化--分层可视化方法实例化于PowerPoint2010中∗%Concept of Demonstration being Namely Visualization Shown by PowerPoint 2 0 1 0 with Hierarchical Visualization Methods

    Institute of Scientific and Technical Information of China (English)

    莫永华; 元钊

    2016-01-01

    With the arrival of the era of pictures,the popularity of multimedia teaching,the appli-cation of visualization method in teaching is becoming more and more important.Through visualiza-tion,we can not only help learners obtain information,but also can make information simpler,more specific and vivid.At present,however,the application of visualization method has problems of being unsystematic,vague in operation,and of poor operability.This paper takes full account of the“availa-bility”,combined with the new PowerPoint 2010 features (such as function orientation,SmartArt graphics,etc.),and instantiating the hierarchical visualization method (data-information-knowledge-intelligent visualization)into PowerPoint in order to make the visualization method simpler in Classifi-cation orderly,more conducive to melting the concept of“demonstration is namely visualization”into the first-line multimedia classroom teaching,which helps students cultivate visual literacy,shape Im-age thinking and innovative thinking.%随着读图时代的到来、多媒体教学的普及,可视化方法在教学中的应用显得越来越重要。通过可视化,不仅能够快速地帮助学习者获取信息,而且能够使信息更加简单化、具体化和形象化。但目前在可视化方法的应用中,存在不系统、笼统模糊及可操作性差等问题。该文充分考虑技术的“可用性”,结合 PowerPoint 2010的新特性(如功能导向、SmartArt图形等),把分层可视化方法(数据———信息———知识———智慧可视化)实例化到 Pow-erPoint中。这样使得可视化方法分类有序、简单易行,有利于“演示即可视化”理念融入广大多媒体课堂教学第一线,有助于培养学生的视觉素养、形象思维、创新思维等。

  3. Robust Pseudo-Hierarchical Support Vector Clustering

    DEFF Research Database (Denmark)

    Hansen, Michael Sass; Sjöstrand, Karl; Olafsdóttir, Hildur

    2007-01-01

    Support vector clustering (SVC) has proven an efficient algorithm for clustering of noisy and high-dimensional data sets, with applications within many fields of research. An inherent problem, however, has been setting the parameters of the SVC algorithm. Using the recent emergence of a method...... for calculating the entire regularization path of the support vector domain description, we propose a fast method for robust pseudo-hierarchical support vector clustering (HSVC). The method is demonstrated to work well on generated data, as well as for detecting ischemic segments from multidimensional myocardial...

  4. Hierarchical topic modeling with nested hierarchical Dirichlet process

    Institute of Scientific and Technical Information of China (English)

    Yi-qun DING; Shan-ping LI; Zhen ZHANG; Bin SHEN

    2009-01-01

    This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonparametric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as welt as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more free-grained topic relationships compared to the hierarchical latent Dirichlet allocation model.

  5. Metabolomics and bioactive substances in plants

    DEFF Research Database (Denmark)

    Khakimov, Bekzod

    (Analytical and Bioanalytical Chemistry, In Press, DOI: 10.1007/s00216-013-7341-z) outlines a novel GC-MS derivatization method using TMSCN for trimethylsilylation for improved analysis of complex biological mixtures . A review paper (Journal of Cereal Science, Accepted) written for the special issue...... of the Journal of Cereal Science dedicated to the journal’s 30th anniversary comprises current analytical challenges and perspectives of cereal metabolomics with emphasis on new development in the use of multivariate data nalysis methods for exploitation of the full information level in the analytical platforms...

  6. Metabolomics of cocaine: implications in toxicity.

    Science.gov (United States)

    Dinis-Oliveira, Ricardo Jorge

    2015-01-01

    Cocaine is the most commonly used illicit drug among those seeking care in Emergency Departments or drug detoxification centers. Cocaine, chemically known as benzoylmethylecgonine, is a naturally occurring substance found in the leaves of the Erythroxylum coca plant. The pharmacokinetics of cocaine is dependent on multiple factors, such as physical/chemical form, route of administration, genetics and concurrent consumption of alcohol. This review aims to discuss metabolomics of cocaine, namely by presenting all known metabolites of cocaine and their roles in the cocaine-mediated toxic effects.

  7. Metabolomic analysis of platelets during storage

    DEFF Research Database (Denmark)

    Paglia, Giuseppe; Sigurjónsson, Ólafur E; Rolfsson, Óttar;

    2015-01-01

    BACKGROUND: Platelet concentrates (PCs) can be prepared using three methods: platelet (PLT)-rich plasma, apheresis, and buffy coat. The aim of this study was to obtain a comprehensive data set that describes metabolism of buffy coat-derived PLTs during storage and to compare it with a previously...... measurements. This data set was obtained by combining a series of standard quality control assays to monitor the quality of stored PLTs and a deep coverage metabolomics study using liquid chromatography coupled with mass spectrometry. RESULTS: Stored PLTs showed a distinct metabolic transition occurring 4 days...

  8. Metabolomic analysis of urine samples by UHPLC-QTOF-MS: Impact of normalization strategies.

    Science.gov (United States)

    Gagnebin, Yoric; Tonoli, David; Lescuyer, Pierre; Ponte, Belen; de Seigneux, Sophie; Martin, Pierre-Yves; Schappler, Julie; Boccard, Julien; Rudaz, Serge

    2017-02-22

    Among the various biological matrices used in metabolomics, urine is a biofluid of major interest because of its non-invasive collection and its availability in large quantities. However, significant sources of variability in urine metabolomics based on UHPLC-MS are related to the analytical drift and variation of the sample concentration, thus requiring normalization. A sequential normalization strategy was developed to remove these detrimental effects, including: (i) pre-acquisition sample normalization by individual dilution factors to narrow the concentration range and to standardize the analytical conditions, (ii) post-acquisition data normalization by quality control-based robust LOESS signal correction (QC-RLSC) to correct for potential analytical drift, and (iii) post-acquisition data normalization by MS total useful signal (MSTUS) or probabilistic quotient normalization (PQN) to prevent the impact of concentration variability. This generic strategy was performed with urine samples from healthy individuals and was further implemented in the context of a clinical study to detect alterations in urine metabolomic profiles due to kidney failure. In the case of kidney failure, the relation between creatinine/osmolality and the sample concentration is modified, and relying only on these measurements for normalization could be highly detrimental. The sequential normalization strategy was demonstrated to significantly improve patient stratification by decreasing the unwanted variability and thus enhancing data quality.

  9. Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

    Science.gov (United States)

    Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

    2016-01-01

    Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

  10. Metabolomic signature associated with reproduction-regulated aging in Caenorhabditis elegans

    Science.gov (United States)

    Wan, Qin-Li; Shi, Xiaohuo; Liu, Jiangxin; Ding, Ai-Jun; Pu, Yuan-Zhu; Li, Zhigang; Wu, Gui-Sheng; Luo, Huai-Rong

    2017-01-01

    In Caenorhabditis elegans (C. elegans), ablation of germline stem cells (GSCs) leads to infertility, which extends lifespan. It has been reported that aging and reproduction are both inextricably associated with metabolism. However, few studies have investigated the roles of polar small molecules metabolism in regulating longevity by reproduction. In this work, we combined the nuclear magnetic resonance (NMR) and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to profile the water-soluble metabolome in C. elegans. Comparing the metabolic fingerprint between two physiological ages among different mutants, our results demonstrate that aging is characterized by metabolome remodeling and metabolic decline. In addition, by analyzing the metabolic profiles of long-lived germline-less glp-1 mutants, we discovered that glp-1 mutants regulate the levels of many age-variant metabolites to attenuate aging, including elevated concentrations of the pyrimidine and purine metabolism intermediates and decreased concentrations of the citric acid cycle intermediates. Interestingly, by analyzing the metabolome of daf-16;glp-1 double mutants, our results revealed that some metabolic exchange contributing to germline-mediated longevity was mediated by transcription factor FOXO/DAF-16, including pyrimidine metabolism and the TCA cycle. Based on a comprehensive metabolic analysis, we provide novel insight into the relationship between longevity and metabolism regulated by germline signals in C. elegans PMID:28177875

  11. Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

    Directory of Open Access Journals (Sweden)

    Veli Bakalov

    2016-12-01

    Full Text Available Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR, to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid, sham (pricked with an aseptic needle, and unmanipulated (positive control. We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate.

  12. Studying the Differences of Bacterial Metabolome and Microbiome in the Colon between Landrace and Meihua Piglets

    Directory of Open Access Journals (Sweden)

    Shijuan Yan

    2017-09-01

    Full Text Available This study was conducted to compare the microbiome and metabolome differences in the colon lumen from two pig breeds with different genetic backgrounds. Fourteen weaned piglets at 30 days of age, including seven Landrace piglets (a lean-type pig breed with a fast growth rate and seven Meihua piglets (a fatty-type Chinese local pig breed with a slow growth rate, were fed the same diets for 35 days. Untargeted metabolomics analyses showed that a total of 401 metabolites differed between Landrace and Meihua. Seventy of these 401 metabolites were conclusively identified. Landrace accumulated more short-chain fatty acids (SCFAs and secondary bile acids in the colon lumen. Moreover, expression of the SCFAs transporter (solute carrier family 5 member 8, SLC5A8 and receptor (G protein-coupled receptor 41, GPR41 in the colon mucosa was higher, while the bile acids receptor (farnesoid X receptor, FXR had lower expression in Landrace compared to Meihua. The relative abundances of 8 genera and 16 species of bacteria differed significantly between Landrace and Meihua, and were closely related to the colonic concentrations of bile acids or SCFAs based on Pearson's correlation analysis. Collectively, our results demonstrate for the first time that there were differences in the colonic microbiome and metabolome between Meihua and Landrace piglets, with the most profound disparity in production of SCFAs and secondary bile acids.

  13. Metabolomic profiles of myocardial ischemia under treatment with salvianolic acid B

    Science.gov (United States)

    2012-01-01

    Background Radix Salvia miltiorrhiza (Danshen) has been used as a principal herb in treating cardiovascular diseases in Chinese medicine. Salvianolic acid B (SA-B), a water-soluble active component of Danshen, was found to have anti-myocardial ischemia (anti-MI) effect. This study aims to investigate mechanisms of SA-B on MI. Methods Five conventional Western medicines (isosorbide dinitrate, verapamil, propranolol, captopril and trimethazine) with different mechanisms for treating cardiovascular diseases were selected as positive references to compare with SA-B in changing of the metabolomic profiles in MI rats under treatment. Potential mechanisms of SA-B were further investigated in H9C2 cell line. Results The metabolomic profiles between SA-B- and propranolol-treated MI rats were similar, since there was a big overlap between the two groups in the PLS-DA score plot. Finally, it was demonstrated that SA-B exhibited a protective effect on MI mainly by decreasing the concentration of cyclic adenosine monophosphate (cAMP) and Ca2+ and inhibiting protein kinase A (PKA). Conclusion SA-B and propanolol exhibited similar metabolomic profiles, indicating that the two drugs might have a similar mechanism. PMID:22409910

  14. Metabolomics analysis of collagen-induced arthritis in rats and interventional effects of oral tolerance.

    Science.gov (United States)

    Ding, Xinghong; Hu, Jinbo; Li, Jinfeng; Zhang, Yan; Shui, Bingjie; Ding, Zhishan; Yao, Li; Fan, Yongsheng

    2014-08-01

    A serum metabolomics method based on rapid resolution liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (RRLC-Q-TOF-MS) was performed for a holistic evaluation of the metabolic changes of collagen-induced arthritis (CIA) in rats and to assess the interventional effects of type II collagen (CII) in this model. Partial least-squares-discriminant analysis (PLS-DA) was employed to study the metabolic profiling of CIA rats and control rats. Ten metabolites, namely, 12(S)-HHTrE, 12(S)-HEPE, PGE2, TXB2, 12(S)-HETE, LysoPE(16:0), PE(O-18:0/0:0), Lyso-PE(18:2), Lyso-PE(20:4), and Lyso-PC(22:5) were identified as differential metabolites associated with the pathogenesis of CIA. These results suggested that dysregulation of the arachidonic acid (AA) and phospholipid metabolic networks is involved in the pathomechanism of CIA. Differential metabolomics and histopathological analyses demonstrated that CII inhibits the progress of arthritis. Furthermore, the therapeutic effects of CII on CIA may involve regulation of the disordered AA and phospholipid metabolic networks. This metabolomics study provides new insights into the pathogenesis of arthritis and, furthermore, indicates the potential mechanism underlying the significantly increased prevalence of metabolic syndrome, defined as a clustering of cardiovascular disease (CVD) risk factors, in arthritis patients. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. A smartphone metabolomics platform and its application to the assessment of cisplatin-induced kidney toxicity.

    Science.gov (United States)

    Kwon, Hyuknam; Park, Jooeun; An, Yongjin; Sim, Jaeho; Park, Sunghyouk

    2014-10-03

    The application of smartphones to medical devices has been gaining attention in addressing accessibility and cost issues in healthcare, and the detection of medically relevant compounds has been demonstrated using customized smartphone hardware and/or software. Metabolomics, a newly rising omics field, has also spawned many medical applications but requires highly sophisticated and expensive equipment. Here, we describe a portable smartphone platform, built with readily available and affordable materials, that can perform all of the critical aspects of metabolomics. Excluding the smartphone itself, the total materials for the platform were obtained at less than US $20. For spectral data acquisition, the system utilized visible light (400-700 nm) and a built-in camera. All of the data processing, statistical analysis, and final-visualization components necessary for decision making were implemented in the smartphone platform. The platform is generally applicable as long as the analytes absorb visible light. We provide a proof-of-concept example wherein the metabolomics platform was applied to the assessment of cisplatin-induced kidney toxicity in a rat model, correctly predicting 7 out of 8 test samples. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Establishment of Quantitative Severity Evaluation Model for Spinal Cord Injury by Metabolomic Fingerprinting

    Science.gov (United States)

    Yang, Hao; Cohen, Mitchell Jay; Chen, Wei; Sun, Ming-Wei; Lu, Charles Damien

    2014-01-01

    Spinal cord injury (SCI) is a devastating event with a limited hope for recovery and represents an enormous public health issue. It is crucial to understand the disturbances in the metabolic network after SCI to identify injury mechanisms and opportunities for treatment intervention. Through plasma 1H-nuclear magnetic resonance (NMR) screening, we identified 15 metabolites that made up an “Eigen-metabolome” capable of distinguishing rats with severe SCI from healthy control rats. Forty enzymes regulated these 15 metabolites in the metabolic network. We also found that 16 metabolites regulated by 130 enzymes in the metabolic network impacted neurobehavioral recovery. Using the Eigen-metabolome, we established a linear discrimination model to cluster rats with severe and mild SCI and control rats into separate groups and identify the interactive relationships between metabolic biomarkers in the global metabolic network. We identified 10 clusters in the global metabolic network and defined them as distinct metabolic disturbance domains of SCI. Metabolic paths such as retinal, glycerophospholipid, arachidonic acid metabolism; NAD–NADPH conversion process, tyrosine metabolism, and cadaverine and putrescine metabolism were included. In summary, we presented a novel interdisciplinary method that integrates metabolomics and global metabolic network analysis to visualize metabolic network disturbances after SCI. Our study demonstrated the systems biological study paradigm that integration of 1H-NMR, metabolomics, and global metabolic network analysis is useful to visualize complex metabolic disturbances after severe SCI. Furthermore, our findings may provide a new quantitative injury severity evaluation model for clinical use. PMID:24727691

  17. Metabolomic profiles of myocardial ischemia under treatment with salvianolic acid B

    Directory of Open Access Journals (Sweden)

    Lu Yonghai

    2012-03-01

    Full Text Available Abstract Background Radix Salvia miltiorrhiza (Danshen has been used as a principal herb in treating cardiovascular diseases in Chinese medicine. Salvianolic acid B (SA-B, a water-soluble active component of Danshen, was found to have anti-myocardial ischemia (anti-MI effect. This study aims to investigate mechanisms of SA-B on MI. Methods Five conventional Western medicines (isosorbide dinitrate, verapamil, propranolol, captopril and trimethazine with different mechanisms for treating cardiovascular diseases were selected as positive references to compare with SA-B in changing of the metabolomic profiles in MI rats under treatment. Potential mechanisms of SA-B were further investigated in H9C2 cell line. Results The metabolomic profiles between SA-B- and propranolol-treated MI rats were similar, since there was a big overlap between the two groups in the PLS-DA score plot. Finally, it was demonstrated that SA-B exhibited a protective effect on MI mainly by decreasing the concentration of cyclic adenosine monophosphate (cAMP and Ca2+ and inhibiting protein kinase A (PKA. Conclusion SA-B and propanolol exhibited similar metabolomic profiles, indicating that the two drugs might have a similar mechanism.

  18. The Gut Microbiome, Its Metabolome, and Their Relationship to Health and Disease.

    Science.gov (United States)

    Wu, Gary D

    2016-01-01

    Despite its importance in maintaining the health of the host, growing evidence suggests that gut microbiota may also be an important factor in the pathogenesis of various diseases. The composition of the microbiota can be influenced by many factors, including age, genetics, host environment, and diet. There are epidemiologic data associating diet with the development of inflammatory bowel disease as well as evidence that diet can influence both the form and the function of the microbiome. Based on this evidence, studies are now underway to examine the effect of defined formula diets, an effective therapeutic modality in Crohn's disease, on both the gut microbiome and its metabolome as a therapeutic probe. Diet has an impact upon both the composition and the function of the microbiota in part through small-molecule production that may influence the development of both immune-mediated and metabolic diseases. By comparing dietary intake, the gut microbiota, and the plasma metabolome in omnivores versus vegans, we provide evidence that the production of certain bacterial metabolites is constrained by the composition of the gut microbiota. In total, these results demonstrate the potential promise of dietary manipulation of the gut microbiota and its metabolome as a modality to both maintain health and treat disease.

  19. Extending the Dynamic Range in Metabolomics Experiments by Automatic Correction of Peaks Exceeding the Detection Limit.

    Science.gov (United States)

    Lisec, Jan; Hoffmann, Friederike; Schmitt, Clemens; Jaeger, Carsten

    2016-08-02

    Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN ( https://cran.r-project.org/ ) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.

  20. Simultaneous acquisition of three NMR spectra in a single experiment for rapid resonance assignments in metabolomics

    Indian Academy of Sciences (India)

    Shivanand M Pudakalakatti; Abhinav Dubey; Hanudatta S Atreya

    2015-06-01

    NMR-based approach to metabolomics typically involves the collection of two-dimensional (2D) heteronuclear correlation spectra for identification and assignment of metabolites. In case of spectral overlap, a 3D spectrum becomes necessary, which is hampered by slow data acquisition for achieving sufficient resolution. We describe here a method to simultaneously acquire three spectra (one 3D and two 2D) in a single data set, which is based on a combination of different fast data acquisition techniques such as G-matrix Fourier transform (GFT) NMR spectroscopy, parallel data acquisition and non-uniform sampling. The following spectra are acquired simultaneously: (1) 13C multiplicity edited GFT (3,2)D HSQC-TOCSY, (2) 2D [1H-1H] TOCSY and (3) 2D [13C-1H] HETCOR. The spectra are obtained at high resolution and provide high-dimensional spectral information for resolving ambiguities. While the GFT spectrum has been shown previously to provide good resolution, the editing of spin systems based on their CH multiplicities further resolves the ambiguities for resonance assignments. The experiment is demonstrated on a mixture of 21 metabolites commonly observed in metabolomics. The spectra were acquired at natural abundance of 13C. This is the first application of a combination of three fast NMR methods for small molecules and opens up new avenues for high-throughput approaches for NMR-based metabolomics.

  1. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

    Directory of Open Access Journals (Sweden)

    Jumpei Washio

    2016-06-01

    Full Text Available Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

  2. Challenges of metabolomics in human gut microbiota research.

    Science.gov (United States)

    Smirnov, Kirill S; Maier, Tanja V; Walker, Alesia; Heinzmann, Silke S; Forcisi, Sara; Martinez, Inés; Walter, Jens; Schmitt-Kopplin, Philippe

    2016-08-01

    The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine.

  3. The use of metabolomics in population-based research.

    Science.gov (United States)

    Su, L Joseph; Fiehn, Oliver; Maruvada, Padma; Moore, Steven C; O'Keefe, Stephen J; Wishart, David S; Zanetti, Krista A

    2014-11-01

    The NIH has made a significant commitment through the NIH Common Fund's Metabolomics Program to build infrastructure and capacity for metabolomics research, which should accelerate the field. Given this investment, it is the ideal time to start planning strategies to capitalize on the infrastructure being established. An obvious gap in the literature relates to the effective use of metabolomics in large-population studies. Although published reports from population-based studies are beginning to emerge, the number to date remains relatively small. Yet, there is great potential for using metabolomics in population-based studies to evaluate the effects of nutritional, pharmaceutical, and environmental exposures (the "exposome"); conduct risk assessments; predict disease development; and diagnose diseases. Currently, the majority of the metabolomics studies in human populations are in nutrition or nutrition-related fields. This symposium provided a timely venue to highlight the current state-of-science on the use of metabolomics in population-based research. This session provided a forum at which investigators with extensive experience in performing research within large initiatives, multi-investigator grants, and epidemiology consortia could stimulate discussion and ideas for population-based metabolomics research and, in turn, improve knowledge to help devise effective methods of health research. © 2014 American Society for Nutrition.

  4. Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study.

    Science.gov (United States)

    Surowiec, Izabella; Karimpour, Masoumeh; Gouveia-Figueira, Sandra; Wu, Junfang; Unosson, Jon; Bosson, Jenny A; Blomberg, Anders; Pourazar, Jamshid; Sandström, Thomas; Behndig, Annelie F; Trygg, Johan; Nording, Malin L

    2016-07-01

    Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure. Graphical Abstract Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas

  5. Metabolomic characteristics of arsenic-associated diabetes in a prospective cohort in Chihuahua, Mexico.

    Science.gov (United States)

    Martin, Elizabeth; González-Horta, Carmen; Rager, Julia; Bailey, Kathryn A; Sánchez-Ramírez, Blanca; Ballinas-Casarrubias, Lourdes; Ishida, María C; Gutiérrez-Torres, Daniela S; Hernández Cerón, Roberto; Viniegra Morales, Damián; Baeza Terrazas, Francisco A; Saunders, R Jesse; Drobná, Zuzana; Mendez, Michelle A; Buse, John B; Loomis, Dana; Jia, Wei; García-Vargas, Gonzalo G; Del Razo, Luz M; Stýblo, Miroslav; Fry, Rebecca

    2015-04-01

    Chronic exposure to inorganic arsenic (iAs) has been linked to an increased risk of diabetes, yet the specific disease phenotype and underlying mechanisms are poorly understood. In the present study we set out to identify iAs exposure-associated metabolites with altered abundance in nondiabetic and diabetic individuals in an effort to understand the relationship between exposure, metabolomic response, and disease status. A nested study design was used to profile metabolomic shifts in urine and plasma collected from 90 diabetic and 86 nondiabetic individuals matched for varying iAs concentrations in drinking water, body mass index, age, and sex. Diabetes diagnosis was based on measures of fasting plasma glucose and 2-h blood glucose. Multivariable models were used to identify metabolites with altered abundance associated with iAs exposure among diabetic and nondiabetic individuals. A total of 132 metabolites were identified to shift in urine or plasma in response to iAs exposure characterized by the sum of iAs metabolites in urine (U-tAs). Although many metabolites were altered in both diabetic and nondiabetic 35 subjects, diabetic individuals displayed a unique response to iAs exposure with 59 altered metabolites including those that play a role in tricarboxylic acid cycle and amino acid metabolism. Taken together, these data highlight the broad impact of iAs exposure on the human metabolome, and demonstrate some specificity of the metabolomic response between diabetic and nondiabetic individuals. These data may provide novel insights into the mechanisms and phenotype of diabetes associated with iAs exposure.

  6. Interpreting metabolomic profiles using unbiased pathway models.

    Directory of Open Access Journals (Sweden)

    Rahul C Deo

    2010-02-01

    Full Text Available Human disease is heterogeneous, with similar disease phenotypes resulting from distinct combinations of genetic and environmental factors. Small-molecule profiling can address disease heterogeneity by evaluating the underlying biologic state of individuals through non-invasive interrogation of plasma metabolite levels. We analyzed metabolite profiles from an oral glucose tolerance test (OGTT in 50 individuals, 25 with normal (NGT and 25 with impaired glucose tolerance (IGT. Our focus was to elucidate underlying biologic processes. Although we initially found little overlap between changed metabolites and preconceived definitions of metabolic pathways, the use of unbiased network approaches identified significant concerted changes. Specifically, we derived a metabolic network with edges drawn between reactant and product nodes in individual reactions and between all substrates of individual enzymes and transporters. We searched for "active modules"--regions of the metabolic network enriched for changes in metabolite levels. Active modules identified relationships among changed metabolites and highlighted the importance of specific solute carriers in metabolite profiles. Furthermore, hierarchical clustering and principal component analysis demonstrated that changed metabolites in OGTT naturally grouped according to the activities of the System A and L amino acid transporters, the osmolyte carrier SLC6A12, and the mitochondrial aspartate-glutamate transporter SLC25A13. Comparison between NGT and IGT groups supported blunted glucose- and/or insulin-stimulated activities in the IGT group. Using unbiased pathway models, we offer evidence supporting the important role of solute carriers in the physiologic response to glucose challenge and conclude that carrier activities are reflected in individual metabolite profiles of perturbation experiments. Given the involvement of transporters in human disease, metabolite profiling may contribute to improved

  7. Deliberate change without hierarchical influence?

    DEFF Research Database (Denmark)

    Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

    2017-01-01

    Purpose This paper aims to present that deliberate change is strongly associated with formal structures and top-down influence. Hierarchical configurations have been used to structure processes, overcome resistance and get things done. But is deliberate change also possible without formal...... reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

  8. Static Correctness of Hierarchical Procedures

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff

    1990-01-01

    A system of hierarchical, fully recursive types in a truly imperative language allows program fragments written for small types to be reused for all larger types. To exploit this property to enable type-safe hierarchical procedures, it is necessary to impose a static requirement on procedure calls....... We introduce an example language and prove the existence of a sound requirement which preserves static correctness while allowing hierarchical procedures. This requirement is further shown to be optimal, in the sense that it imposes as few restrictions as possible. This establishes the theoretical...... basis for a general type hierarchy with static type checking, which enables first-order polymorphism combined with multiple inheritance and specialization in a language with assignments. We extend the results to include opaque types. An opaque version of a type is different from the original but has...

  9. Metabolomics, a promising approach to translational research in cardiology

    Directory of Open Access Journals (Sweden)

    Martino Deidda

    2015-12-01

    In this article, we will provide a description of metabolomics in comparison with other, better known “omics” disciplines such as genomics and proteomics. In addition, we will review the current rationale for the implementation of metabolomics in cardiology, its basic methodology and the available data from human studies in this discipline. The topics covered will delineate the importance of being able to use the metabolomic information to understand the mechanisms of diseases from the perspective of systems biology, and as a non-invasive approach to the diagnosis, grading and treatment of cardiovascular diseases.

  10. A metabolomics study on human dietary intervention with apples

    DEFF Research Database (Denmark)

    Dragsted, L. O.; Kristensen, M.; Ravn-Haren, Gitte

    2009-01-01

    interpretation. Design considerations for metabolomic studies include the overall structure of the study as well as the control group, sample collection and handling, sample storage, sample analysis, quality control measures and plans for data analyses. Suggestions for designing feasible and ethical dietary......Metabolomics is a promising tool for searching out new biomarkers and the development of hypotheses in nutrition research. This chapter will describe the design of human dietary intervention studies where samples are collected for metabolomics analyses as well as the analytical issues and data...

  11. Metabolomics in the identification of biomarkers of dietary intake.

    Science.gov (United States)

    O'Gorman, Aoife; Gibbons, Helena; Brennan, Lorraine

    2013-01-01

    Traditional methods for assessing dietary exposure can be unreliable, with under reporting one of the main problems. In an attempt to overcome such problems there is increasing interest in identifying biomarkers of dietary intake to provide a more accurate measurement. Metabolomics is an analytical technique that aims to identify and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics coupled with statistical analysis for the identification of dietary biomarkers, with a number of putative biomarkers identified. This minireview focuses on metabolomics based approaches and highlights some of the key successes.

  12. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

    Directory of Open Access Journals (Sweden)

    Yufeng Jane Tseng

    2013-05-01

    Full Text Available Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

  13. Monolithic columns in plant proteomics and metabolomics.

    Science.gov (United States)

    Rigobello-Masini, Marilda; Penteado, José Carlos Pires; Masini, Jorge Cesar

    2013-03-01

    Since "omics" techniques emerged, plant studies, from biochemistry to ecology, have become more comprehensive. Plant proteomics and metabolomics enable the construction of databases that, with the help of genomics and informatics, show the data obtained as a system. Thus, all the constituents of the system can be seen with their interactions in both space and time. For instance, perturbations in a plant ecosystem as a consequence of application of herbicides or exposure to pollutants can be predicted by using information gathered from these databases. Analytical chemistry has been involved in this scientific evolution. Proteomics and metabolomics are emerging fields that require separation, identification, and quantification of proteins, peptides, and small molecules of metabolites in complex biological samples. The success of this work relies on efficient chromatographic and electrophoretic techniques, and on mass spectrometric detection. This paper reviews recent developments in the use of monolithic columns, focusing on their applications in "top-down" and "bottom-up" approaches, including their use as supports for immobilization of proteolytic enzymes and their use in two-dimensional and multidimensional chromatography. Whereas polymeric columns have been predominantly used for separation of proteins and polypeptides, silica-based monoliths have been more extensively used for separation of small molecules of metabolites. Representative applications in proteomics and in analysis of plant metabolites are given and summarized in tables.

  14. Serum Metabolomics of Burkitt Lymphoma Mouse Models

    Science.gov (United States)

    Yang, Fengmin; Du, Jie; Zhang, Hong; Ruan, Guorui; Xiang, Junfeng; Wang, Lixia; Sun, Hongxia; Guan, Aijiao; Shen, Gang; Liu, Yan; Guo, Xiaomeng; Li, Qian; Tang, Yalin

    2017-01-01

    Burkitt lymphoma (BL) is a rare and highly aggressive type of non-Hodgkin lymphoma. The mortality rate of BL patients is very high due to the rapid growth rate and frequent systemic spread of the disease. A better understanding of the pathogenesis, more sensitive diagnostic tools and effective treatment methods for BL are essential. Metabolomics, an important aspect of systems biology, allows the comprehensive analysis of global, dynamic and endogenous biological metabolites based on their nuclear magnetic resonance (NMR) and mass spectrometry (MS). It has already been used to investigate the pathogenesis and discover new biomarkers for disease diagnosis and prognosis. In this study, we analyzed differences of serum metabolites in BL mice and normal mice by NMR-based metabolomics. We found that metabolites associated with energy metabolism, amino acid metabolism, fatty acid metabolism and choline phospholipid metabolism were altered in BL mice. The diagnostic potential of the metabolite differences was investigated in this study. Glutamate, glycerol and choline had a high diagnostic accuracy; in contrast, isoleucine, leucine, pyruvate, lysine, α-ketoglutarate, betaine, glycine, creatine, serine, lactate, tyrosine, phenylalanine, histidine and formate enabled the accurate differentiation of BL mice from normal mice. The discovery of abnormal metabolism and relevant differential metabolites may provide useful clues for developing novel, noninvasive approaches for the diagnosis and prognosis of BL based on these potential biomarkers. PMID:28129369

  15. Structural integrity of hierarchical composites

    Directory of Open Access Journals (Sweden)

    Marco Paggi

    2012-01-01

    Full Text Available Interface mechanical problems are of paramount importance in engineering and materials science. Traditionally, due to the complexity of modelling their mechanical behaviour, interfaces are often treated as defects and their features are not explored. In this study, a different approach is illustrated, where the interfaces play an active role in the design of innovative hierarchical composites and are fundamental for their structural integrity. Numerical examples regarding cutting tools made of hierarchical cellular polycrystalline materials are proposed, showing that tailoring of interface properties at the different scales is the way to achieve superior mechanical responses that cannot be obtained using standard materials

  16. GASIS demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Vidas, E.H. [Energy and Environmental Analysis, Inc., Arlington, VA (United States)

    1995-04-01

    A prototype of the GASIS database and retrieval software has been developed and is the subject of this poster session and computer demonstration. The prototype consists of test or preliminary versions of the GASIS Reservoir Data System and Source Directory datasets and the software for query and retrieval. The prototype reservoir database covers the Rocky Mountain region and contains the full GASIS data matrix (all GASIS data elements) that will eventually be included on the CD-ROM. It is populated for development purposes primarily by the information included in the Rocky Mountain Gas Atlas. The software has been developed specifically for GASIS using Foxpro for Windows. The application is an executable file that does not require Foxpro to run. The reservoir database software includes query and retrieval, screen display, report generation, and data export functions. Basic queries by state, basin, or field name will be assisted by scrolling selection lists. A detailed query screen will allow record selection on the basis of any data field, such as depth, cumulative production, or geological age. Logical operators can be applied to any-numeric data element or combination of elements. Screen display includes a {open_quotes}browse{close_quotes} display with one record per row and a detailed single record display. Datasets can be exported in standard formats for manipulation with other software packages. The Source Directory software will allow record retrieval by database type or subject area.

  17. Synthesis strategies in the search for hierarchical zeolites.

    Science.gov (United States)

    Serrano, D P; Escola, J M; Pizarro, P

    2013-05-07

    formation of organic-inorganic composites that, upon calcination, are transformed into hierarchical zeolites. However, in spite of this impressive progress in novel strategies for the preparation of hierarchical zeolites, significant challenges are still ahead. The overall one is the development of methods that are versatile in terms of zeolite structures and compositions, capable of tuning the secondary porosity properties, and being scaled up in a cost-effective way. Recent works have demonstrated that it is possible to scale-up easily the synthesis of hierarchical zeolites by desilication. Economic aspects may become a significant bottleneck for the commercial application of hierarchical zeolites since most of the synthesis strategies so far developed imply the use of more expensive procedures and reagents compared to conventional zeolites. Nevertheless, the use of hierarchical zeolites as efficient catalysts for the production of high value-added compounds could greatly compensate these increased manufacturing costs.

  18. Hierarchically structured superoleophobic surfaces with ultralow contact angle hysteresis.

    Science.gov (United States)

    Kota, Arun K; Li, Yongxin; Mabry, Joseph M; Tuteja, Anish

    2012-11-14

    Hierarchically structured, superoleophobic surfaces are demonstrated that display one of the lowest contact angle hysteresis values ever reported - even with extremely low-surface-tension liquids such as n-heptane. Consequently, these surfaces allow, for the first time, even ≈2 μL n-heptane droplets to bounce and roll-off at tilt angles. ≤ 2°.

  19. Hierarchical Data Structures in Adventure Education and Therapy

    Science.gov (United States)

    Russell, Keith; Sibthorp, Jim

    2004-01-01

    Hierarchical linear modeling (HIM) is an approach used in data analysis to better understand how program outcomes are affected by the "nested" nature of data collected in many studies. An outcome can be considered variables such as an individual's self-efficacy, social skills, or more targeted outcomes such as demonstrated reading and mathematical…

  20. Sensory Hierarchical Organization and Reading.

    Science.gov (United States)

    Skapof, Jerome

    The purpose of this study was to judge the viability of an operational approach aimed at assessing response styles in reading using the hypothesis of sensory hierarchical organization. A sample of 103 middle-class children from a New York City public school, between the ages of five and seven, took part in a three phase experiment. Phase one…

  1. Memory Stacking in Hierarchical Networks.

    Science.gov (United States)

    Westö, Johan; May, Patrick J C; Tiitinen, Hannu

    2016-02-01

    Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

  2. Time is ripe: maturation of metabolomics in chronobiology.

    Science.gov (United States)

    Rhoades, Seth D; Sengupta, Arjun; Weljie, Aalim M

    2017-02-01

    Sleep and circadian rhythms studies have recently benefited from metabolomics analyses, uncovering new connections between chronobiology and metabolism. From untargeted mass spectrometry to quantitative nuclear magnetic resonance spectroscopy, a diversity of analytical approaches has been applied for biomarker discovery in the field. In this review we consider advances in the application of metabolomics technologies which have uncovered significant effects of sleep and circadian cycles on several metabolites, namely phosphatidylcholine species, medium-chain carnitines, and aromatic amino acids. Study design and data processing measures essential for detecting rhythmicity in metabolomics data are also discussed. Future developments in these technologies are anticipated vis-à-vis validating early findings, given metabolomics has only recently entered the ring with other systems biology assessments in chronometabolism studies.

  3. Metabolomic determinants of necrotizing enterocolitis in preterm piglets

    Science.gov (United States)

    Studies in premature infants and animals show that carbohydrate malabsorption and gut microbiota colonisation are key elements for triggering necrotizing enterocolitis (NEC). Our aim was to determine how dietary carbohydrate composition affects the metabolomic profile and whether unique metabolite s...

  4. Evaluating plant immunity using mass spectrometry-based metabolomics workflows

    Science.gov (United States)

    Heuberger, Adam L.; Robison, Faith M.; Lyons, Sarah Marie A.; Broeckling, Corey D.; Prenni, Jessica E.

    2014-01-01

    Metabolic processes in plants are key components of physiological and biochemical disease resistance. Metabolomics, the analysis of a broad range of small molecule compounds in a biological system, has been used to provide a systems-wide overview of plant metabolism associated with defense responses. Plant immunity has been examined using multiple metabolomics workflows that vary in methods of detection, annotation, and interpretation, and the choice of workflow can significantly impact the conclusions inferred from a metabolomics investigation. The broad range of metabolites involved in plant defense often requires multiple chemical detection platforms and implementation of a non-targeted approach. A review of the current literature reveals a wide range of workflows that are currently used in plant metabolomics, and new methods for analyzing and reporting mass spectrometry (MS) data can improve the ability to translate investigative findings among different plant-pathogen systems. PMID:25009545

  5. NMR metabolomics of human blood and urine in disease research.

    Science.gov (United States)

    Duarte, Iola F; Diaz, Sílvia O; Gil, Ana M

    2014-05-01

    This paper reviews the main applications of NMR metabolomics of blood and urine in disease research, over the last 5 years. The broad range of disease types addressed attests the increasing interest within the academic and medical communities to explore the recognised potential of metabolomics to (1) provide insight into underlying disease pathogenesis and (2) unveil new metabolic markers for disease diagnosis and follow up. Importantly, most recent studies reveal an increasing awareness of possible limitations and pitfalls of the metabolomics approach, together with efforts for improved study design and statistical validation, which are crucial requisites for the sound development of NMR metabolomics and its progress into the clinical setting. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Plant single-cell and single-cell-type metabolomics.

    Science.gov (United States)

    Misra, Biswapriya B; Assmann, Sarah M; Chen, Sixue

    2014-10-01

    In conjunction with genomics, transcriptomics, and proteomics, plant metabolomics is providing large data sets that are paving the way towards a comprehensive and holistic understanding of plant growth, development, defense, and productivity. However, dilution effects from organ- and tissue-based sampling of metabolomes have limited our understanding of the intricate regulation of metabolic pathways and networks at the cellular level. Recent advances in metabolomics methodologies, along with the post-genomic expansion of bioinformatics knowledge and functional genomics tools, have allowed the gathering of enriched information on individual cells and single cell types. Here we review progress, current status, opportunities, and challenges presented by single cell-based metabolomics research in plants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Dissemination of metabolomics results: role of MetaboLights and COSMOS.

    Science.gov (United States)

    Salek, Reza M; Haug, Kenneth; Steinbeck, Christoph

    2013-05-17

    With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information.

  8. Hierarchical honeycomb auxetic metamaterials.

    Science.gov (United States)

    Mousanezhad, Davood; Babaee, Sahab; Ebrahimi, Hamid; Ghosh, Ranajay; Hamouda, Abdelmagid Salem; Bertoldi, Katia; Vaziri, Ashkan

    2015-12-16

    Most conventional materials expand in transverse directions when they are compressed uniaxially resulting in the familiar positive Poisson's ratio. Here we develop a new class of two dimensional (2D) metamaterials with negative Poisson's ratio that contract in transverse directions under uniaxial compressive loads leading to auxeticity. This is achieved through mechanical instabilities (i.e., buckling) introduced by structural hierarchy and retained over a wide range of applied compression. This unusual behavior is demonstrated experimentally and analyzed computationally. The work provides new insights into the role of structural organization and hierarchy in designing 2D auxetic metamaterials, and new opportunities for developing energy absorbing materials, tunable membrane filters, and acoustic dampeners.

  9. Metabolomics approach for discovering disease biomarkers and understanding metabolic pathway

    Directory of Open Access Journals (Sweden)

    Jeeyoun Jung

    2011-12-01

    Full Text Available Metabolomics, the multi-targeted analysis of endogenous metabolites from biological samples, can be efficiently applied to screen disease biomarkers and investigate pathophysiological processes. Metabolites change rapidly in response to physiological perturbations, making them the closest link to disease phenotypes. This study explored the role of metabolomics in gaining mechanistic insight into disease processes and in searching for novel biomarkers of human diseases

  10. Plant metabolomics is not ripe for environmental risk assessment.

    Science.gov (United States)

    Hall, Robert D; de Maagd, Ruud A

    2014-08-01

    Metabolomics separates and detects small molecules and helps determine the composition of plant materials. This makes it appear to be a possible contributor to environmental risk assessment (ERA) of transgenic plants. Here we argue that, despite important advances in the technology, limited annotation and our limited knowledge of the role of metabolites in plant-environment interactions means that metabolomics is not yet ripe for ERA. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Metabolomic Biomarkers in the Progression to Type 1 Diabetes

    DEFF Research Database (Denmark)

    Overgaard, Anne Julie; Kaur, Simranjeet; Pociot, Flemming

    2016-01-01

    Metabolomics is the snapshot of all detectable metabolites and lipids in biological materials and has potential in reflecting genetic and environmental factors contributing to the development of complex diseases, such as type 1 diabetes. The progression to seroconversion to development of type 1...... at seroconversion, and triglycerides are increased at seroconversion and associated to microbiome diversity, indicating an association between the metabolome and microbiome in type 1 diabetes progression....

  12. Pediatric obesity: could metabolomics be a useful tool?

    OpenAIRE

    Angelica Dessì; Vassilios Fanos

    2013-01-01

    Pediatric obesity represents an important health issue. In recent years applications of metabolomics have led to evaluation of responses to the various nutrients (nutrigenomics), in particular to lipids, in diseases such as obesity and diabetes. The experimental data and the studies in pediatrics  that evaluated the metabolic condition in infant obesity are presented. It is thus to be hoped that future progress in connection with this new technique, together with a metabolomic study of mother...

  13. Auction-based resource allocation game under a hierarchical structure

    Science.gov (United States)

    Cui, Yingying; Zou, Suli; Ma, Zhongjing

    2016-01-01

    This paper studies a class of auction-based resource allocation games under a hierarchical structure, such that each supplier is assigned a certain amount of resource from a single provider and allocates it to its buyers with auction mechanisms. To implement the efficient allocations for the underlying hierarchical system, we first design an auction mechanism, for each local system composed of a supplier and its buyers, which inherits the advantages of the progressive second price mechanism. By employing a dynamic algorithm, each local system converges to its own efficient Nash equilibrium, at which the efficient resource allocation is achieved and the bidding prices of all the buyers in this local system are identical with each other. After the local systems reach their own equilibria respectively, the resources assigned to suppliers are readjusted via a dynamic hierarchical algorithm with respect to the bidding prices associated with the implemented equilibria of local systems. By applying the proposed hierarchical process, the formulated hierarchical system can converge to the efficient allocation under certain mild conditions. The developed results in this work are demonstrated with simulations.

  14. Adaptive color visualization for dichromats using a customized hierarchical palette

    Science.gov (United States)

    Rodríguez-Pardo, Carlos E.; Sharma, Gaurav

    2011-01-01

    We propose a user-centric methodology for displaying digital color documents, that optimizes color representations in an observer specific and adaptive fashion. We apply our framework to situations involving viewers with common dichromatic color vision deficiencies, who face challenges in perceiving information presented in color images and graphics designed for color normal individuals. For situations involving qualitative data visualization, we present a computationally efficient solution that combines a customized observer-specific hierarchical palette with "display time" selection of the number of colors to generate renderings with colors that are easily discriminated by the intended viewer. The palette design is accomplished via a clustering algorithm, that arranges colors in a hierarchical tree based on their perceived differences for the intended viewer. A desired number of highly discriminable colors are readily obtained from the hierarchical palette via a simple truncation. As an illustration, we demonstrate the application of the methodology to Ishihara style images.

  15. A novel load balancing method for hierarchical federation simulation system

    Science.gov (United States)

    Bin, Xiao; Xiao, Tian-yuan

    2013-07-01

    In contrast with single HLA federation framework, hierarchical federation framework can improve the performance of large-scale simulation system in a certain degree by distributing load on several RTI. However, in hierarchical federation framework, RTI is still the center of message exchange of federation, and it is still the bottleneck of performance of federation, the data explosion in a large-scale HLA federation may cause overload on RTI, It may suffer HLA federation performance reduction or even fatal error. Towards this problem, this paper proposes a load balancing method for hierarchical federation simulation system based on queuing theory, which is comprised of three main module: queue length predicting, load controlling policy, and controller. The method promotes the usage of resources of federate nodes, and improves the performance of HLA simulation system with balancing load on RTIG and federates. Finally, the experiment results are presented to demonstrate the efficient control of the method.

  16. Ultrasound: a subexploited tool for sample preparation in metabolomics.

    Science.gov (United States)

    Luque de Castro, M D; Delgado-Povedano, M M

    2014-01-02

    Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. Recent advances in metabolomics in neurological disease, and future perspectives.

    Science.gov (United States)

    Zhang, Ai-hua; Sun, Hui; Wang, Xi-jun

    2013-10-01

    Discovery of clinically relevant biomarkers for diseases has revealed metabolomics has potential advantages that classical diagnostic approaches do not. The great asset of metabolomics is that it enables assessment of global metabolic profiles of biofluids and discovery of biomarkers distinguishing disease status, with the possibility of enhancing clinical diagnostics. Most current clinical chemistry tests rely on old technology, and are neither sensitive nor specific for a particular disease. Clinical diagnosis of major neurological disorders, for example Alzheimer's disease and Parkinson's disease, on the basis of current clinical criteria is unsatisfactory. Emerging metabolomics is a powerful technique for discovering novel biomarkers and biochemical pathways to improve diagnosis, and for determination of prognosis and therapy. Identifying multiple novel biomarkers for neurological diseases has been greatly enhanced with recent advances in metabolomics that are more accurate than routine clinical practice. Cerebrospinal fluid (CSF), which is known to be a rich source of small-molecule biomarkers for neurological and neurodegenerative diseases, and is in close contact with diseased areas in neurological disorders, could potentially be used for disease diagnosis. Metabolomics will drive CSF analysis, facilitate and improve the development of disease treatment, and result in great benefits to public health in the long-term. This review covers different aspects of CSF metabolomics and discusses their significance in the postgenomic era, emphasizing the potential importance of endogenous small-molecule metabolites in this emerging field.

  18. Metabolomics: current state and evolving methodologies and tools.

    Science.gov (United States)

    Oldiges, Marco; Lütz, Stephan; Pflug, Simon; Schroer, Kirsten; Stein, Nadine; Wiendahl, Christiane

    2007-09-01

    In recent years, metabolomics developed to an accepted and valuable tool in life sciences. Substantial improvements of analytical hardware allow metabolomics to run routinely now. Data are successfully used to investigate genotype-phenotype relations of strains and mutants. Metabolomics facilitates metabolic engineering to optimise mircoorganisms for white biotechnology and spreads to the investigation of biotransformations and cell culture. Metabolomics serves not only as a source of qualitative but also quantitative data of intra-cellular metabolites essential for the model-based description of the metabolic network operating under in vivo conditions. To collect reliable metabolome data sets, culture and sampling conditions, as well as the cells' metabolic state, are crucial. Hence, application of biochemical engineering principles and method standardisation efforts become important. Together with the other more established omics technologies, metabolomics will strengthen its claim to contribute to the detailed understanding of the in vivo function of gene products, biochemical and regulatory networks and, even more ambitious, the mathematical description and simulation of the whole cell in the systems biology approach. This knowledge will allow the construction of designer organisms for process application using biotransformation and fermentative approaches making effective use of single enzymes, whole microbial and even higher cells.

  19. Potential biomarkers of fatigue identified by plasma metabolome analysis in rats.

    Directory of Open Access Journals (Sweden)

    Satoshi Kume

    Full Text Available In the present study, prior to the establishment of a method for the clinical diagnosis of chronic fatigue in humans, we validated the utility of plasma metabolomic analysis in a rat model of fatigue using capillary electrophoresis-mass spectrometry (CE-MS. In order to obtain a fatigued animal group, rats were placed in a cage filled with water to a height of 2.2 cm for 5 days. A food-restricted group, in which rats were limited to 10 g/d of food (around 50% of the control group, was also assessed. The food-restricted group exhibited weight reduction similar to that of the fatigued group. CE-MS measurements were performed to evaluate the profile of food intake-dependent metabolic changes, as well as the profile in fatigue loading, resulting in the identification of 48 metabolites in plasma. Multivariate analyses using hierarchical clustering and principal component analysis revealed that the plasma metabolome in the fatigued group showed clear differences from those in the control and food-restricted groups. In the fatigued group, we found distinctive changes in metabolites related to branched-chain amino acid metabolism, urea cycle, and proline metabolism. Specifically, the fatigued group exhibited significant increases in valine, leucine, isoleucine, and 2-oxoisopentanoate, and significant decreases in citrulline and hydroxyproline compared with the control and food-restricted groups. Plasma levels of total nitric oxide were increased in the fatigued group, indicating systemic oxidative stress. Further, plasma metabolites involved in the citrate cycle, such as cis-aconitate and isocitrate, were reduced in the fatigued group. The levels of ATP were significantly decreased in the liver and skeletal muscle, indicative of a deterioration in energy metabolism in these organs. Thus, this comprehensive metabolic analysis furthered our understanding of the pathophysiology of fatigue, and identified potential diagnostic biomarkers based on fatigue

  20. Potential biomarkers of fatigue identified by plasma metabolome analysis in rats.

    Science.gov (United States)

    Kume, Satoshi; Yamato, Masanori; Tamura, Yasuhisa; Jin, Guanghua; Nakano, Masayuki; Miyashige, Yukiharu; Eguchi, Asami; Ogata, Yoshiyuki; Goda, Nobuhito; Iwai, Kazuhiro; Yamano, Emi; Watanabe, Yasuyoshi; Soga, Tomoyoshi; Kataoka, Yosky

    2015-01-01

    In the present study, prior to the establishment of a method for the clinical diagnosis of chronic fatigue in humans, we validated the utility of plasma metabolomic analysis in a rat model of fatigue using capillary electrophoresis-mass spectrometry (CE-MS). In order to obtain a fatigued animal group, rats were placed in a cage filled with water to a height of 2.2 cm for 5 days. A food-restricted group, in which rats were limited to 10 g/d of food (around 50% of the control group), was also assessed. The food-restricted group exhibited weight reduction similar to that of the fatigued group. CE-MS measurements were performed to evaluate the profile of food intake-dependent metabolic changes, as well as the profile in fatigue loading, resulting in the identification of 48 metabolites in plasma. Multivariate analyses using hierarchical clustering and principal component analysis revealed that the plasma metabolome in the fatigued group showed clear differences from those in the control and food-restricted groups. In the fatigued group, we found distinctive changes in metabolites related to branched-chain amino acid metabolism, urea cycle, and proline metabolism. Specifically, the fatigued group exhibited significant increases in valine, leucine, isoleucine, and 2-oxoisopentanoate, and significant decreases in citrulline and hydroxyproline compared with the control and food-restricted groups. Plasma levels of total nitric oxide were increased in the fatigued group, indicating systemic oxidative stress. Further, plasma metabolites involved in the citrate cycle, such as cis-aconitate and isocitrate, were reduced in the fatigued group. The levels of ATP were significantly decreased in the liver and skeletal muscle, indicative of a deterioration in energy metabolism in these organs. Thus, this comprehensive metabolic analysis furthered our understanding of the pathophysiology of fatigue, and identified potential diagnostic biomarkers based on fatigue pathophysiology.

  1. Relationship between the metabolite profile and technological properties of bovine milk from two dairy breeds elucidated by NMR-based metabolomics.

    Science.gov (United States)

    Sundekilde, Ulrik Kræmer; Frederiksen, Pernille Dorthea; Clausen, Morten Rahr; Larsen, Lotte Bach; Bertram, Hanne Christine

    2011-07-13

    The aim of the present study was to investigate the relationship between the metabolite profile of milk and important technological properties by using nuclear magnetic resonance (NMR)-based metabolomics. The metabolomics approach was introduced for the metabolic profiling of a set of milk samples from two dairy breeds representing a wide span in coagulation properties. The milk metabolite profiles obtained by proton and carbon NMR spectroscopy could be correlated to breed and, more interestingly, also with the coagulation profile, as established by traditional methods by using principal component analysis (PCA). The metabolites responsible for the separation into breed could mainly be ascribed to carnitine and lactose, whereas the metabolites varying in the samples with respect to coagulation properties included citrate, choline, carnitine, and lactose. The results found in the present study demonstrated a promising potential of NMR-based metabolomics for a rapid analysis and classification of milk samples, both of which are useful for the dairy industry.

  2. Plant bioassay to assess the effects of allelochemicals on the metabolome of the target species Aegilops geniculata by an NMR-based approach.

    Science.gov (United States)

    D'Abrosca, Brigida; Scognamiglio, Monica; Fiumano, Vittorio; Esposito, Assunta; Choi, Young Hae; Verpoorte, Robert; Fiorentino, Antonio

    2013-09-01

    A metabolomic-based approach for the study of allelopathic interactions in the Mediterranean area is proposed using Aegilops geniculata Roth (Poaceae), a Mediterranean herbaceous plant, as test species. Its metabolome has been elucidated by 1D and 2D NMR experiments. Hydroponic plant cultures of A. geniculata were treated with specific compounds of known allelopathic potential: catechol, coumarin, p-coumaric acid, p-hydroxybenzoic acid, ferulic acid and juglone. The metabolic variations due to the presence of allelochemicals have been analyzed and measured. All of the compounds showed the strongest effects at the highest concentration, with coumarin and juglone as the most active compounds, causing an increase of several metabolites. The metabolome changes in test plants confirmed the allelochemicals' reported modes of action. The results demonstrated that the proposed method is a promising tool. It can be applied to plant extracts, making it possible to evidence the metabolites responsible for the activity, as well as their mechanisms of action.

  3. Brain Region Mapping using Global Metabolomics

    Science.gov (United States)

    Ivanisevic, Julijana; Epstein, Adrian; Kurczy, Michael E.; Benton, H. Paul; Uritboonthai, Winnie; Fox, Howard S.; Boska, Michael D.; Gendelman, Howard E.; Siuzdak, Gary

    2014-01-01

    SUMMARY Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present a novel untargeted mass spectrometry-based metabolomics approach that has successfully uncovered differences in broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed unique water-soluble and lipid metabolite patterns between brain regions. Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric and sialic acid whose physiological roles in brain metabolism are poorly understood. This study lays important groundwork by defining regional homeostasis for the normal mouse brain to give context to the reaction to pathological events. PMID:25457182

  4. Metabolomics study of Populus type propolis.

    Science.gov (United States)

    Anđelković, Boban; Vujisić, Ljubodrag; Vučković, Ivan; Tešević, Vele; Vajs, Vlatka; Gođevac, Dejan

    2017-02-20

    Herein, we propose rapid and simple spectroscopic methods to determine the chemical composition of propolis derived from various Populus species using a metabolomics approach. In order to correlate variability in Populus type propolis composition with the altitude of its collection, NMR, IR, and UV spectroscopy followed by OPLS was conducted. The botanical origin of propolis was established by comparing propolis spectral data to those of buds of various Populus species. An O2PLS method was utilized to integrate two blocks of data. According to OPLS and O2PLS, the major compounds in propolis samples, collected from temperate continental climate above 500m, were phenolic glycerides originating from P. tremula buds. Flavonoids were predominant in propolis samples collected below 400m, originating from P. nigra and P. x euramericana buds. Samples collected at 400-500m were of mixed origin, with variable amounts of all detected metabolites. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Metabolomic phenotyping of a cloned pig model

    DEFF Research Database (Denmark)

    Clausen, Morten Rahr; Christensen, Kirstine Lykke; Hedemann, Mette Skou

    2011-01-01

    and possibly also phenotypes and this offer an extra level of experimental control which could possibly make them a desirable tool for intervention studies. Therefore, in the present study, we address how phenotype and phenotypic variation is affected by cloning, through comparison of cloned pigs and normal...... outbred pigs. Results The metabolic phenotype of cloned pigs (n = 5) was for the first time elucidated by nuclear magnetic resonance (NMR)-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n...... = 6) by multivariate data analysis, which revealed differences in the metabolic phenotypes. Plasma lactate was higher for cloned vs control pigs, while multiple metabolites were altered in the bile. However a lower inter-individual variability for cloned pigs compared with control pigs could...

  6. Microfluidics meets metabolomics to reveal the impact of Campylobacter jejuni infection on biochemical pathways.

    Science.gov (United States)

    Mortensen, Ninell P; Mercier, Kelly A; McRitchie, Susan; Cavallo, Tammy B; Pathmasiri, Wimal; Stewart, Delisha; Sumner, Susan J

    2016-06-01

    Microfluidic devices that are currently being used in pharmaceutical research also have a significant potential for utilization in investigating exposure to infectious agents. We have established a microfluidic device cultured with Caco-2 cells, and utilized metabolomics to investigate the biochemical responses to the bacterial pathogen Campylobacter jejuni. In the microfluidic devices, Caco-2 cells polarize at day 5, are uniform, have defined brush borders and tight junctions, and form a mucus layer. Metabolomics analysis of cell culture media collected from both Caco-2 cell culture systems demonstrated a more metabolic homogenous biochemical profile in the media collected from microfluidic devices, compared with media collected from transwells. GeneGo pathway mapping indicated that aminoacyl-tRNA biosynthesis was perturbed by fluid flow, suggesting that fluid dynamics and shear stress impacts the cells translational quality control. Both microfluidic device and transwell culturing systems were used to investigate the impact of Campylobacter jejuni infection on biochemical processes. Caco-2 cells cultured in either system were infected at day 5 with C. jejuni 81-176 for 48 h. Metabolomics analysis clearly differentiated C. jejuni 81-176 infected and non-infected medias collected from the microfluidic devices, and demonstrated that C. jejuni 81-176 infection in microfluidic devices impacts branched-chain amino acid metabolism, glycolysis, and gluconeogenesis. In contrast, no distinction was seen in the biochemical profiles of infected versus non-infected media collected from cells cultured in transwells. Microfluidic culturing conditions demonstrated a more metabolically homogenous cell population, and present the opportunity for studying host-pathogen interactions for extended periods of time.

  7. Hierarchical Prisoner's Dilemma in Hierarchical Public-Goods Game

    CERN Document Server

    Fujimoto, Yuma; Kaneko, Kunihiko

    2016-01-01

    The dilemma in cooperation is one of the major concerns in game theory. In a public-goods game, each individual pays a cost for cooperation, or to prevent defection, and receives a reward from the collected cost in a group. Thus, defection is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individual players also play games. To study such a multi-level game, we introduce a hierarchical public-goods (HPG) game in which two groups compete for finite resources by utilizing costs collected from individuals in each group. Analyzing this HPG game, we found a hierarchical prisoner's dilemma, in which groups choose the defection policy (say, armaments) as a Nash strategy to optimize each group's benefit, while cooperation optimizes the total benefit. On the other hand, for each individual within a group, refusing to pay the cost (say, tax) is a Nash strategy, which turns to be a cooperation policy for the group, thus leading to a hierarchical d...

  8. Efficient scalable algorithms for hierarchically semiseparable matrices

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shen; Xia, Jianlin; Situ, Yingchong; Hoop, Maarten V. de

    2011-09-14

    Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the superfast direct solvers for both dense and sparse linear systems. Here, we develope a set of novel parallel algorithms for the key HSS operations that are used for solving large linear systems. These include the parallel rank-revealing QR factorization, the HSS constructions with hierarchical compression, the ULV HSS factorization, and the HSS solutions. The HSS tree based parallelism is fully exploited at the coarse level. The BLACS and ScaLAPACK libraries are used to facilitate the parallel dense kernel operations at the ne-grained level. We have appplied our new parallel HSS-embedded multifrontal solver to the anisotropic Helmholtz equations for seismic imaging, and were able to solve a linear system with 6.4 billion unknowns using 4096 processors, in about 20 minutes. The classical multifrontal solver simply failed due to high demand of memory. To our knowledge, this is the first successful demonstration of employing the HSS algorithms in solving the truly large-scale real-world problems. Our parallel strategies can be easily adapted to the parallelization of the other rank structured methods.

  9. Proteomics and Metabolomics for In Situ Monitoring of Wound Healing

    Science.gov (United States)

    Kalkhof, Stefan; Förster, Yvonne; Schmidt, Johannes; Schulz, Matthias C.; Baumann, Sven; Weißflog, Anne; Gao, Wenling; Hempel, Ute; Eckelt, Uwe; Rammelt, Stefan; von Bergen, Martin

    2014-01-01

    Wound healing of soft tissue and bone defects is a complex process in which cellular differentiation and adaption are regulated by internal and external factors, among them are many different proteins. In contrast to insights into the significance of various single proteins based on model systems, the knowledge about the processes at the actual site of wound healing is still limited. This is caused by a general lack of methods that allow sampling of extracellular factors, metabolites, and proteins in situ. Sampling of wound fluids in combination with proteomics and metabolomics is one of the promising approaches to gain comprehensive and time resolved data on effector molecules. Here, we describe an approach to sample metabolites by microdialysis and to extract proteins simultaneously by adsorption. With this approach it is possible (i) to collect, enrich, and purify proteins for a comprehensive proteome analysis; (ii) to detect more than 600 proteins in different defects including more than 100 secreted proteins, of which many proteins have previously been demonstrated to have diagnostic or predictive power for the wound healing state; and (iii) to combine continuous sampling of cytokines and metabolites and discontinuous sampling of larger proteins to gain complementary information of the same defect. PMID:25162036

  10. Applications of NMR-based metabolomics in biological and environmental research

    Science.gov (United States)

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used by biologists to study the dynamic response of biological systems (cells, tissues, or whole organisms) under diverse physiological or pathological conditions. Metabolomics deals with the qu...

  11. Hierarchical structure of biological systems

    Science.gov (United States)

    Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

    2014-01-01

    A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

  12. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  13. Intuitionistic fuzzy hierarchical clustering algorithms

    Institute of Scientific and Technical Information of China (English)

    Xu Zeshui

    2009-01-01

    Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.

  14. Hierarchical Formation of Galactic Clusters

    CERN Document Server

    Elmegreen, B G

    2006-01-01

    Young stellar groupings and clusters have hierarchical patterns ranging from flocculent spiral arms and star complexes on the largest scale to OB associations, OB subgroups, small loose groups, clusters and cluster subclumps on the smallest scales. There is no obvious transition in morphology at the cluster boundary, suggesting that clusters are only the inner parts of the hierarchy where stars have had enough time to mix. The power-law cluster mass function follows from this hierarchical structure: n(M_cl) M_cl^-b for b~2. This value of b is independently required by the observation that the summed IMFs from many clusters in a galaxy equals approximately the IMF of each cluster.

  15. Hierarchical matrices algorithms and analysis

    CERN Document Server

    Hackbusch, Wolfgang

    2015-01-01

    This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

  16. Hierarchical Cont-Bouchaud model

    CERN Document Server

    Paluch, Robert; Holyst, Janusz A

    2015-01-01

    We extend the well-known Cont-Bouchaud model to include a hierarchical topology of agent's interactions. The influence of hierarchy on system dynamics is investigated by two models. The first one is based on a multi-level, nested Erdos-Renyi random graph and individual decisions by agents according to Potts dynamics. This approach does not lead to a broad return distribution outside a parameter regime close to the original Cont-Bouchaud model. In the second model we introduce a limited hierarchical Erdos-Renyi graph, where merging of clusters at a level h+1 involves only clusters that have merged at the previous level h and we use the original Cont-Bouchaud agent dynamics on resulting clusters. The second model leads to a heavy-tail distribution of cluster sizes and relative price changes in a wide range of connection densities, not only close to the percolation threshold.

  17. Hierarchical Clustering and Active Galaxies

    CERN Document Server

    Hatziminaoglou, E; Manrique, A

    2000-01-01

    The growth of Super Massive Black Holes and the parallel development of activity in galactic nuclei are implemented in an analytic code of hierarchical clustering. The evolution of the luminosity function of quasars and AGN will be computed with special attention paid to the connection between quasars and Seyfert galaxies. One of the major interests of the model is the parallel study of quasar formation and evolution and the History of Star Formation.

  18. Hybrid and hierarchical composite materials

    CERN Document Server

    Kim, Chang-Soo; Sano, Tomoko

    2015-01-01

    This book addresses a broad spectrum of areas in both hybrid materials and hierarchical composites, including recent development of processing technologies, structural designs, modern computer simulation techniques, and the relationships between the processing-structure-property-performance. Each topic is introduced at length with numerous  and detailed examples and over 150 illustrations.   In addition, the authors present a method of categorizing these materials, so that representative examples of all material classes are discussed.

  19. Treatment Protocols as Hierarchical Structures

    Science.gov (United States)

    Ben-Bassat, Moshe; Carlson, Richard W.; Puri, Vinod K.; Weil, Max Harry

    1978-01-01

    We view a treatment protocol as a hierarchical structure of therapeutic modules. The lowest level of this structure consists of individual therapeutic actions. Combinations of individual actions define higher level modules, which we call routines. Routines are designed to manage limited clinical problems, such as the routine for fluid loading to correct hypovolemia. Combinations of routines and additional actions, together with comments, questions, or precautions organized in a branching logic, in turn, define the treatment protocol for a given disorder. Adoption of this modular approach may facilitate the formulation of treatment protocols, since the physician is not required to prepare complex flowcharts. This hierarchical approach also allows protocols to be updated and modified in a flexible manner. By use of such a standard format, individual components may be fitted together to create protocols for multiple disorders. The technique is suited for computer implementation. We believe that this hierarchical approach may facilitate standarization of patient care as well as aid in clinical teaching. A protocol for acute pancreatitis is used to illustrate this technique.

  20. Metabolomic profiling in LRRK2-related Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Krisztina K Johansen

    Full Text Available BACKGROUND: Mutations in LRRK2 gene represent the most common known genetic cause of Parkinson's disease (PD. METHODOLOGY/PRINCIPAL FINDINGS: We used metabolomic profiling to identify biomarkers that are associated with idiopathic and LRRK2 PD. We compared plasma metabolomic profiles of patients with PD due to the G2019S LRRK2 mutation, to asymptomatic family members of these patients either with or without G2019S LRRK2 mutations, and to patients with idiopathic PD, as well as non-related control subjects. We found that metabolomic profiles of both idiopathic PD and LRRK2 PD subjects were clearly separated from controls. LRRK2 PD patients had metabolomic profiles distinguishable from those with idiopathic PD, and the profiles could predict whether the PD was secondary to LRRK2 mutations or idiopathic. Metabolomic profiles of LRRK2 PD patients were well separated from their family members, but there was a slight overlap between family members with and without LRRK2 mutations. Both LRRK2 and idiopathic PD patients showed significantly reduced uric acid levels. We also found a significant decrease in levels of hypoxanthine and in the ratios of major metabolites of the purine pathway in plasma of PD patients. CONCLUSIONS/SIGNIFICANCE: These findings show that LRRK2 patients with the G2019S mutation have unique metabolomic profiles that distinguish them from patients with idiopathic PD. Furthermore, asymptomatic LRRK2 carriers can be separated from gene negative family members, which raises the possibility that metabolomic profiles could be useful in predicting which LRRK2 carriers will eventually develop PD. The results also suggest that there are aberrations in the purine pathway in PD which may occur upstream from uric acid.

  1. Towards Improving Point-of-Care Diagnosis of Non-malaria Febrile Illness: A Metabolomics Approach.

    Directory of Open Access Journals (Sweden)

    Saskia Decuypere

    2016-03-01

    Full Text Available Non-malaria febrile illnesses such as bacterial bloodstream infections (BSI are a leading cause of disease and mortality in the tropics. However, there are no reliable, simple diagnostic tests for identifying BSI or other severe non-malaria febrile illnesses. We hypothesized that different infectious agents responsible for severe febrile illness would impact on the host metabolome in different ways, and investigated the potential of plasma metabolites for diagnosis of non-malaria febrile illness.We conducted a comprehensive mass-spectrometry based metabolomics analysis of the plasma of 61 children with severe febrile illness from a malaria-endemic rural African setting. Metabolite features characteristic for non-malaria febrile illness, BSI, severe anemia and poor clinical outcome were identified by receiver operating curve analysis.The plasma metabolome profile of malaria and non-malaria patients revealed fundamental differences in host response, including a differential activation of the hypothalamic-pituitary-adrenal axis. A simple corticosteroid signature was a good classifier of severe malaria and non-malaria febrile patients (AUC 0.82, 95% CI: 0.70-0.93. Patients with BSI were characterized by upregulated plasma bile metabolites; a signature of two bile metabolites was estimated to have a sensitivity of 98.1% (95% CI: 80.2-100 and a specificity of 82.9% (95% CI: 54.7-99.9 to detect BSI in children younger than 5 years. This BSI signature demonstrates that host metabolites can have a superior diagnostic sensitivity compared to pathogen-detecting tests to identify infections characterized by low pathogen load such as BSI.This study demonstrates the potential use of plasma metabolites to identify causality in children with severe febrile illness in malaria-endemic settings.

  2. Normalization method for metabolomics data using optimal selection of multiple internal standards

    Directory of Open Access Journals (Sweden)

    Yetukuri Laxman

    2007-03-01

    Full Text Available Abstract Background Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task. Results With the aim to remove unwanted systematic variation, we present an approach that utilizes variability information from multiple internal standard compounds to find optimal normalization factor for each individual molecular species detected by metabolomics approach (NOMIS. We demonstrate the method on mouse liver lipidomic profiles using Ultra Performance Liquid Chromatography coupled to high resolution mass spectrometry, and compare its performance to two commonly utilized normalization methods: normalization by l2 norm and by retention time region specific standard compound profiles. The NOMIS method proved superior in its ability to reduce the effect of systematic error across the full spectrum of metabolite peaks. We also demonstrate that the method can be used to select best combinations of standard compounds for normalization. Conclusion Depending on experiment design and biological matrix, the NOMIS method is applicable either as a one-step normalization method or as a two-step method where the normalization parameters, influenced by variabilities of internal standard compounds and their correlation to metabolites, are first calculated from a study conducted in repeatability conditions. The method can also be used in analytical development of metabolomics methods by helping to select best combinations of standard compounds for a particular biological matrix and analytical platform.

  3. Hierarchical Carbon Fibers with ZnO Nanowires for Volatile Sensing in Composite Curing (Postprint)

    Science.gov (United States)

    2014-07-01

    AFRL-RX-WP-JA-2014-0171 HIERARCHICAL CARBON FIBERS WITH ZnO NANOWIRES FOR VOLATILE SENSING IN COMPOSITE CURING (POSTPRINT) Gregory...REPORT TYPE Interim 3. DATES COVERED (From – To) 16 April 2012 – 02 June 2014 4. TITLE AND SUBTITLE HIERARCHICAL CARBON FIBERS WITH ZnO NANOWIRES...needed to demonstrate the use of Zinc Oxide ( ZnO ) nanowire coated carbon fibers as a volatile sensor. ZnO nanowires are demonstrated to function as

  4. Comprehensive analysis of the metabolome of Pseudomonas putida S12 grown on different carbon sources

    NARCIS (Netherlands)

    Werf, M.J. van der; Overkamp, K.M.; Muilwijk, B.; Koek, M.M.; Werff van der - Vat, B.J.C. van der; Jellema, R.H.; Coulier, L.; Hankemeier, T.

    2008-01-01

    Metabolomics is an emerging, powerful, functional genomics technology that involves the comparative non-targeted analysis of the complete set of metabolites in an organism. We have set-up a robust quantitative metabolomics platform that allows the analysis of 'snapshot' metabolomes. In this study, w

  5. Hierarchical manifold learning for regional image analysis.

    Science.gov (United States)

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Joseph V; Rueckert, Daniel

    2014-02-01

    We present a novel method of hierarchical manifold learning which aims to automatically discover regional properties of image datasets. While traditional manifold learning methods have become widely used for dimensionality reduction in medical imaging, they suffer from only being able to consider whole images as single data points. We extend conventional techniques by additionally examining local variations, in order to produce spatially-varying manifold embeddings that characterize a given dataset. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate the utility of our method in two very different settings: 1) to learn the regional correlations in motion within a sequence of time-resolved MR images of the thoracic cavity; 2) to find discriminative regions of 3-D brain MR images associated with neurodegenerative disease.

  6. Image Segmentation Using Hierarchical Merge Tree

    Science.gov (United States)

    Liu, Ting; Seyedhosseini, Mojtaba; Tasdizen, Tolga

    2016-10-01

    This paper investigates one of the most fundamental computer vision problems: image segmentation. We propose a supervised hierarchical approach to object-independent image segmentation. Starting with over-segmenting superpixels, we use a tree structure to represent the hierarchy of region merging, by which we reduce the problem of segmenting image regions to finding a set of label assignment to tree nodes. We formulate the tree structure as a constrained conditional model to associate region merging with likelihoods predicted using an ensemble boundary classifier. Final segmentations can then be inferred by finding globally optimal solutions to the model efficiently. We also present an iterative training and testing algorithm that generates various tree structures and combines them to emphasize accurate boundaries by segmentation accumulation. Experiment results and comparisons with other very recent methods on six public data sets demonstrate that our approach achieves the state-of-the-art region accuracy and is very competitive in image segmentation without semantic priors.

  7. A new approach for modeling generalization gradients: A case for Hierarchical Models

    Directory of Open Access Journals (Sweden)

    Koen eVanbrabant

    2015-05-01

    Full Text Available A case is made for the use of hierarchical models in the analysis of generalization gradients. Hierarchical models overcome several restrictions that are imposed by repeated measures analysis-of-variance (rANOVA, the default statistical method in current generalization research. More specifically, hierarchical models allow to include continuous independent variables and overcomes problematic assumptions such as sphericity. We focus on how generalization research can benefit from this added flexibility. In a simulation study we demonstrate the dominance of hierarchical models over rANOVA. In addition, we show the lack of efficiency of the Mauchly's sphericity test in sample sizes typical for generalization research, and confirm how violations of sphericity increase the probability of type I errors. A worked example of a hierarchical model is provided, with a specific emphasis on the interpretation of parameters relevant for generalization research.

  8. A new approach for modeling generalization gradients: a case for hierarchical models.

    Science.gov (United States)

    Vanbrabant, Koen; Boddez, Yannick; Verduyn, Philippe; Mestdagh, Merijn; Hermans, Dirk; Raes, Filip

    2015-01-01

    A case is made for the use of hierarchical models in the analysis of generalization gradients. Hierarchical models overcome several restrictions that are imposed by repeated measures analysis-of-variance (rANOVA), the default statistical method in current generalization research. More specifically, hierarchical models allow to include continuous independent variables and overcomes problematic assumptions such as sphericity. We focus on how generalization research can benefit from this added flexibility. In a simulation study we demonstrate the dominance of hierarchical models over rANOVA. In addition, we show the lack of efficiency of the Mauchly's sphericity test in sample sizes typical for generalization research, and confirm how violations of sphericity increase the probability of type I errors. A worked example of a hierarchical model is provided, with a specific emphasis on the interpretation of parameters relevant for generalization research.

  9. Metabolomic profiles are gender, disease and time specific in the interleukin-10 gene-deficient mouse model of inflammatory bowel disease.

    Directory of Open Access Journals (Sweden)

    Victor K Tso

    Full Text Available Metabolomic profiling can be used to study disease-induced changes in inflammatory bowel diseases (IBD. The aim of this study was to investigate the difference in the metabolomic profile of males and females as they developed IBD. Using the IL-10 gene-deficient mouse model of IBD and wild-type mice, urine at age 4, 6, 8, 12, 16, and 20 weeks was collected and analyzed by nuclear magnetic resonance (NMR spectroscopy. Multivariate data analysis was employed to assess differences in metabolomic profiles that occurred as a consequence of IBD development and severity (at week 20. These changes were contrasted to those that occurred as a consequence of gender. Our results demonstrate that both IL-10 gene-deficient and wild-type mice exhibit gender-related changes in urinary metabolomic profile over time. Some male-female separating metabolites are common to both IL-10 gene-deficient and control wild-type mice and, therefore, appear to be related predominantly to gender maturation. In addition, we were able to identify gender-separating metabolites that are unique for IL-10 gene-deficient and wild-type mice and, therefore, may be indicative of a gender-specific involvement in the development and severity of the intestinal inflammation. The comparison of the gender-separating metabolomic profile from IL-10 gene-deficient mice and wild-type mice during the development of IBD allowed us to identify changes in profile patterns that appear to be imperative in the development of intestinal inflammation, but yet central to gender-related differences in IBD development. The knowledge of metabolomic profile differences by gender and by disease severity has potential clinical implications in the design of both biomarkers of disease as well as the development of optimal therapies.

  10. Mixing omics: combining genetics and metabolomics to study rheumatic diseases.

    Science.gov (United States)

    Menni, Cristina; Zierer, Jonas; Valdes, Ana M; Spector, Tim D

    2017-03-01

    Metabolomics is an exciting field in systems biology that provides a direct readout of the biochemical activities taking place within an individual at a particular point in time. Metabolite levels are influenced by many factors, including disease status, environment, medications, diet and, importantly, genetics. Thanks to their dynamic nature, metabolites are useful for diagnosis and prognosis, as well as for predicting and monitoring the efficacy of treatments. At the same time, the strong links between an individual's metabolic and genetic profiles enable the investigation of pathways that underlie changes in metabolite levels. Thus, for the field of metabolomics to yield its full potential, researchers need to take into account the genetic factors underlying the production of metabolites, and the potential role of these metabolites in disease processes. In this Review, the methodological aspects related to metabolomic profiling and any potential links between metabolomics and the genetics of some of the most common rheumatic diseases are described. Links between metabolomics, genetics and emerging fields such as the gut microbiome and proteomics are also discussed.

  11. Recent advances in the application of metabolomics to Alzheimer's Disease.

    Science.gov (United States)

    Trushina, Eugenia; Mielke, Michelle M

    2014-08-01

    The pathophysiological changes associated with Alzheimer's Disease (AD) begin decades before the emergence of clinical symptoms. Understanding the early mechanisms associated with AD pathology is, therefore, especially important for identifying disease-modifying therapeutic targets. While the majority of AD clinical trials to date have focused on anti-amyloid-beta (Aβ) treatments, other therapeutic approaches may be necessary. The ability to monitor changes in cellular networks that include both Aβ and non-Aβ pathways is essential to advance our understanding of the etiopathogenesis of AD and subsequent development of cognitive symptoms and dementia. Metabolomics is a powerful tool that detects perturbations in the metabolome, a pool of metabolites that reflects changes downstream of genomic, transcriptomic and proteomic fluctuations, and represents an accurate biochemical profile of the organism in health and disease. The application of metabolomics could help to identify biomarkers for early AD diagnosis, to discover novel therapeutic targets, and to monitor therapeutic response and disease progression. Moreover, given the considerable parallel between mouse and human metabolism, the use of metabolomics provides ready translation of animal research into human studies for accelerated drug design. In this review, we will summarize current progress in the application of metabolomics in both animal models and in humans to further understanding of the mechanisms involved in AD pathogenesis. © 2013.

  12. The Progress of Metabolomics Study in Traditional Chinese Medicine Research.

    Science.gov (United States)

    Wang, Pengcheng; Wang, Qiuhong; Yang, Bingyou; Zhao, Shan; Kuang, Haixue

    2015-01-01

    Traditional Chinese medicine (TCM) has played important roles in health protection and disease treatment for thousands of years in China and has gained the gradual acceptance of the international community. However, many intricate issues, which cannot be explained by traditional methods, still remain, thus, new ideas and technologies are needed. As an emerging system biology technology, the holistic view adopted by metabolomics is similar to that of TCM, which allows us to investigate TCM with complicated conditions and multiple factors in depth. In this paper, we tried to give a timely and comprehensive update about the methodology progression of metabolomics, as well as its applications, in different fields of TCM studies including quality control, processing, safety and efficacy evaluation. The herbs investigated by metabolomics were selected for detailed examination, including Anemarrhena asphodeloides Bunge, Atractylodes macrocephala Kidd, Pinellia ternate, etc.; furthermore, some valuable results have been obtained and summarized. In conclusion, although the study of metabolomics is at the early phase and requires further scrutiny and validation, it still provides bright prospects to dissect the synergistic action of multiple components from TCM. Overall, with the further development of analytical techniques, especially multi-analysis techniques, we expect that metabolomics will greatly promote TCM research and the establishment of international standards, which is beneficial to TCM modernization.

  13. Can NMR solve some significant challenges in metabolomics?

    Science.gov (United States)

    Nagana Gowda, G. A.; Raftery, Daniel

    2015-11-01

    The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.

  14. Study of the cardiotoxicity of Venenum Bufonis in rats using an 1H NMR-based metabolomics approach.

    Directory of Open Access Journals (Sweden)

    Ge Dong

    Full Text Available Venenum Bufonis, a well-known traditional Chinese medicine, has been widely used in Asia and has gained popularity in Western countries over the last decade. Venenum Bufonis has obvious side effects that have been observed in clinical settings, but few studies have reported on its cardiotoxicity. In this work, the cardiotoxicity of Venenum Bufonis was investigated using a 11H NMR-based metabolomics approach. The 1H NMR profiles of the serum, myocardial extracts and liver extracts of specific-pathogen-free rats showed that Venenum Bufonis produced significant metabolic perturbations dose-dependently with a distinct time effect, peaking at 2 hr after dosing and attenuating gradually. Clinical chemistry, electrocardiographic recordings, and histopathological evaluation provided additional evidence of Venenum Bufonis-induced cardiac damage that complemented and supported the metabolomics findings. The combined results demonstrated that oxidative stress, mitochondrial dysfunction, and energy metabolism perturbations were associated with the cardiac damage that results from Venenum Bufonis.

  15. Comparative metabolomics reveals endogenous ligands of DAF-12, a nuclear hormone receptor, regulating C. elegans development and lifespan.

    Science.gov (United States)

    Mahanti, Parag; Bose, Neelanjan; Bethke, Axel; Judkins, Joshua C; Wollam, Joshua; Dumas, Kathleen J; Zimmerman, Anna M; Campbell, Sydney L; Hu, Patrick J; Antebi, Adam; Schroeder, Frank C

    2014-01-07

    Small-molecule ligands of nuclear hormone receptors (NHRs) govern the transcriptional regulation of metazoan development, cell differentiation, and metabolism. However, the physiological ligands of many NHRs remain poorly characterized, primarily due to lack of robust analytical techniques. Using comparative metabolomics, we identified endogenous steroids that act as ligands of the C. elegans NHR, DAF-12, a vitamin D and liver X receptor homolog regulating larval development, fat metabolism, and lifespan. The identified molecules feature unexpected chemical modifications and include only one of two DAF-12 ligands reported earlier, necessitating a revision of previously proposed ligand biosynthetic pathways. We further show that ligand profiles are regulated by a complex enzymatic network, including the Rieske oxygenase DAF-36, the short-chain dehydrogenase DHS-16, and the hydroxysteroid dehydrogenase HSD-1. Our results demonstrate the advantages of comparative metabolomics over traditional candidate-based approaches and provide a blueprint for the identification of ligands for other C. elegans and mammalian NHRs.

  16. Nuclear magnetic resonance-based metabolomics reveals that dairy protein fractions affect urinary urea excretion differently in overweight adolescents

    DEFF Research Database (Denmark)

    Zheng, Hong; Yde, Christian Clement; Dalsgaard, Trine Kastrup

    2015-01-01

    was investigated by using NMR-based urine metabolomics. Overweight adolescents (n = 192; age = 12–15 years; BMI = 25.4 ± 2.3 kg/m2) were randomly assigned to 1 L/day of casein (citrate content: 3.27 mol/L), whey (citrate content: 0.04 mol/L), skim milk, or water for 12 weeks. A significant increase in the urinary...... excretion of urea was found after the 12-week casein and skim milk interventions, while the 12-week whey intervention had no significant effect on the urea excretion. In addition, NMR-based metabolomics revealed a decreased urinary citrate excretion in the whey group and thereby demonstrated its potential...

  17. Comparative metabolomics in Glycine max and Glycine soja under salt stress to reveal the phenotypes of their offspring.

    Science.gov (United States)

    Lu, Yonghai; Lam, Honming; Pi, Erxu; Zhan, Qinglei; Tsai, Sauna; Wang, Chunmei; Kwan, Yiuwa; Ngai, Saiming

    2013-09-11

    Metabolomics is developing as an important functional genomics tool for understanding plant systems' response to genetic and environmental changes. Here, we characterized the metabolic changes of cultivated soybean C08 (Glycine max L. Merr) and wild soybean W05 (Glycine soja Sieb.et Zucc.) under salt stress using MS-based metabolomics, in order to reveal the phenotypes of their eight hybrid offspring (9H0086, 9H0124, 9H0391, 9H0736, 9H0380, 9H0400, 9H0434, and 9H0590). Total small molecule extracts of soybean seedling leaves were profiled by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-Fourier transform mass spectrometry (LC-FT/MS). We found that wild soybean contained higher amounts of disaccharides, sugar alcohols, and acetylated amino acids than cultivated soybean, but with lower amounts of monosaccharides, carboxylic acids, and unsaturated fatty acids. Further investigations demonstrated that the ability of soybean to tolerate salt was mainly based on synthesis of compatible solutes, induction of reactive oxygen species (ROS) scavengers, cell membrane modifications, and induction of plant hormones. On the basis of metabolic phenotype, the salt-tolerance abilities of 9H0086, 9H0124, 9H0391, 9H0736, 9H0380, 9H0400, 9H0434, and 9H0590 were discriminated. Our results demonstrated that MS-based metabolomics provides a fast and powerful approach to discriminate the salt-tolerance characteristics of soybeans.

  18. A metabolomic strategy defines the regulation of lipid content and global metabolism by Δ9 desaturases in Caenorhabditis elegans

    Directory of Open Access Journals (Sweden)

    Castro Cecilia

    2012-01-01

    Full Text Available Abstract Background Caenorhabditis elegans provides a genetically tractable model organism to investigate the network of genes involved in fat metabolism and how regulation is perturbed to produce the complex phenotype of obesity. C. elegans possess the full range of desaturases, including the Δ9 desaturases expressed by fat-5, fat-6 and fat-7. They regulate the biosynthesis of monounsaturated fatty acids, used for the synthesis of lipids including phospholipids, triglycerides and cholesteryl esters. Results Liquid chromatography mass spectrometry (LC-MS, gas chromatography mass spectrometry (GC-MS and nuclear magnetic resonance (NMR spectroscopy were used to define the metabolome of all the possible knock-outs for the Δ9 desaturases, including for the first time intact lipids. Despite the genes having similar enzymatic roles, excellent discrimination was achievable for all single and viable double mutants highlighting the distinctive roles of fat-6 and fat-7, both expressing steroyl-CoA desaturases. The metabolomic changes extend to aqueous metabolites demonstrating the influence Δ9 desaturases have on regulating global metabolism and highlighting how comprehensive metabolomics is more discriminatory than classically used dyes for fat staining. Conclusions The propagation of metabolic changes across the network of metabolism demonstrates that modification of the Δ9 desaturases places C.elegans into a catabolic state compared with wildtype controls.

  19. Effect of acute stresses on zebra fish (Danio rerio) metabolome measured by NMR-based metabolomics.

    Science.gov (United States)

    Mushtaq, Mian Yahya; Marçal, Rosilene Moretti; Champagne, Danielle L; van der Kooy, Frank; Verpoorte, Robert; Choi, Young Hae

    2014-09-01

    We applied an acute stress model to zebra fish in order to measure the changes in the metabolome due to biological stress. This was done by submitting the fish to fifteen minutes of acute confinement (netting) stress, and then five minutes for the open field and light/dark field tests. A polar extract of the zebra fish was then subjected to (1)H nuclear magnetic spectroscopy. Multivariate data analysis of the spectra showed a clear separation associated to a wide range of metabolites between zebra fish that were submitted to open field and light/dark field tests. Alanine, taurine, adenosine, creatine, lactate, and histidine were high in zebra fish to which the light/dark field test was applied, regardless of stress, while acetate and isoleucine/lipids appeared to be higher in zebra fish exposed to the open field test. These results show that any change in the environment, even for a small period of time, has a noticeable physiological impact. This research provides an insight of how different mechanisms are activated under different environments to maintain the homeostasis of the body. It should also contribute to establish zebra fish as a model for metabolomics studies.

  20. Hierarchical Control for Smart Grids

    DEFF Research Database (Denmark)

    Trangbæk, K; Bendtsen, Jan Dimon; Stoustrup, Jakob

    2011-01-01

    This paper deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high level MPC controller, a second level of so-called aggregators, which reduces the computational and communication-related load on the high-level control, and a lower level...... of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The objective is to accommodate the load variation on the grid, arising...

  1. PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

    Directory of Open Access Journals (Sweden)

    Renata Bujak

    2016-07-01

    Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

  2. A Conversation on Data Mining Strategies in LC-MS Untargeted Metabolomics: Pre-Processing and Pre-Treatment Steps.

    Science.gov (United States)

    Tugizimana, Fidele; Steenkamp, Paul A; Piater, Lizelle A; Dubery, Ian A

    2016-11-03

    Untargeted metabolomic studies generate information-rich, high-dimensional, and complex datasets that remain challenging to handle and fully exploit. Despite the remarkable progress in the development of tools and algorithms, the "exhaustive" extraction of information from these metabolomic datasets is still a non-trivial undertaking. A conversation on data mining strategies for a maximal information extraction from metabolomic data is needed. Using a liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomic dataset, this study explored the influence of collection parameters in the data pre-processing step, scaling and data transformation on the statistical models generated, and feature selection, thereafter. Data obtained in positive mode generated from a LC-MS-based untargeted metabolomic study (sorghum plants responding dynamically to infection by a fungal pathogen) were used. Raw data were pre-processed with MarkerLynx(TM) software (Waters Corporation, Manchester, UK). Here, two parameters were varied: the intensity threshold (50-100 counts) and the mass tolerance (0.005-0.01 Da). After the pre-processing, the datasets were imported into SIMCA (Umetrics, Umea, Sweden) for more data cleaning and statistical modeling. In addition, different scaling (unit variance, Pareto, etc.) and data transformation (log and power) methods were explored. The results showed that the pre-processing parameters (or algorithms) influence the output dataset with regard to the number of defined features. Furthermore, the study demonstrates that the pre-treatment of data prior to statistical modeling affects the subspace approximation outcome: e.g., the amount of variation in X-data that the model can explain and predict. The pre-processing and pre-treatment steps subsequently influence the number of statistically significant extracted/selected features (variables). Thus, as informed by the results, to maximize the value of untargeted metabolomic data, understanding

  3. Metabolomic phenotyping of a cloned pig model

    Directory of Open Access Journals (Sweden)

    Callesen Henrik

    2011-08-01

    Full Text Available Abstract Background Pigs are widely used as models for human physiological changes in intervention studies, because of the close resemblance between human and porcine physiology and the high degree of experimental control when using an animal model. Cloned animals have, in principle, identical genotypes and possibly also phenotypes and this offer an extra level of experimental control which could possibly make them a desirable tool for intervention studies. Therefore, in the present study, we address how phenotype and phenotypic variation is affected by cloning, through comparison of cloned pigs and normal outbred pigs. Results The metabolic phenotype of cloned pigs (n = 5 was for the first time elucidated by nuclear magnetic resonance (NMR-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n = 6 by multivariate data analysis, which revealed differences in the metabolic phenotypes. Plasma lactate was higher for cloned vs control pigs, while multiple metabolites were altered in the bile. However a lower inter-individual variability for cloned pigs compared with control pigs could not be established. Conclusions From the present study we conclude that cloned and normal outbred pigs are phenotypically different. However, it cannot be concluded that the use of cloned animals will reduce the inter-individual variation in intervention studies, though this is based on a limited number of animals.

  4. Extraction parameters for metabolomics from cell extracts

    Science.gov (United States)

    Ser, Zheng; Liu, Xiaojing; Tang, Ngoc Nu; Locasale, Jason W

    2015-01-01

    The successful extraction of metabolites is a critical step in metabolite profiling. By optimizing metabolite extraction, the range and quantitative capacity of metabolomics studies can be improved. We considered eight separate extraction protocols for the preparation of a metabolite extract from cultured mammalian cells. Parameters considered included temperature, pH, and cell washing before extraction. The effects on metabolite recovery were studied using a high resolution liquid chromatography mass spectrometry (LC-HRMS) platform that measures metabolites of diverse chemical classes including among others amino acids, lipids, and sugar derivatives. The temperature considered during the extraction or the presence of formic acid, a commonly used additive, was shown to have minimal effects on the measured ion intensities of metabolites. However, washing of samples before metabolite extraction whether with water or PBS (both commonly considered practices) exhibited dramatic effects on measured intensities of both intra- and extra-cellular metabolites. Together these findings present a systematic assessment of extraction conditions for metabolite profiling. PMID:25613493

  5. Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases.

    Science.gov (United States)

    Gomez-Casati, Diego F; Zanor, Maria I; Busi, María V

    2013-01-01

    In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

  6. Diurnal effects of anoxia on the metabolome of the seagrass Zostera marina

    DEFF Research Database (Denmark)

    Hasler-Sheetal, Harald; Holmer, Marianne; Weckwerth, Wolfram

    2014-01-01

    Environmental metabolomics has become interesting in marine ecological studies. One example is the revealing of new insights in stress response of Zostera marina. This is essential to understand how, at which level and to what extend aquatic plants adapt, tolerate and react to environmental...... stressors. We exposed Z. marina to water column anoxia and assessed the diurnal metabolomic response by GC-TOF-MS based metabolomics identifying 109 known and 217 unknown metabolites. During day time photosynthetic oxygen production prevents severe effects of anoxia on the metabolome (complete set of small...... the applicability of metabolomics to assess environmental stress responses of Zostera marina....

  7. High-resolution quantitative metabolome analysis of urine by automated flow injection NMR.

    Science.gov (United States)

    Da Silva, Laeticia; Godejohann, Markus; Martin, François-Pierre J; Collino, Sebastiano; Bürkle, Alexander; Moreno-Villanueva, María; Bernhardt, Jürgen; Toussaint, Olivier; Grubeck-Loebenstein, Beatrix; Gonos, Efstathios S; Sikora, Ewa; Grune, Tilman; Breusing, Nicolle; Franceschi, Claudio; Hervonen, Antti; Spraul, Manfred; Moco, Sofia

    2013-06-18

    Metabolism is essential to understand human health. To characterize human metabolism, a high-resolution read-out of the metabolic status under various physiological conditions, either in health or disease, is needed. Metabolomics offers an unprecedented approach for generating system-specific biochemical definitions of a human phenotype through the capture of a variety of metabolites in a single measurement. The emergence of large cohorts in clinical studies increases the demand of technologies able to analyze a large number of measurements, in an automated fashion, in the most robust way. NMR is an established metabolomics tool for obtaining metabolic phenotypes. Here, we describe the analysis of NMR-based urinary profiles for metabolic studies, challenged to a large human study (3007 samples). This method includes the acquisition of nuclear Overhauser effect spectroscopy one-dimensional and J-resolved two-dimensional (J-Res-2D) (1)H NMR spectra obtained on a 600 MHz spectrometer, equipped with a 120 μL flow probe, coupled to a flow-injection analysis system, in full automation under the control of a sampler manager. Samples were acquired at a throughput of ~20 (or 40 when J-Res-2D is included) min/sample. The associated technical analysis error over the full series of analysis is 12%, which demonstrates the robustness of the method. With the aim to describe an overall metabolomics workflow, the quantification of 36 metabolites, mainly related to central carbon metabolism and gut microbial host cometabolism, was obtained, as well as multivariate data analysis of the full spectral profiles. The metabolic read-outs generated using our analytical workflow can therefore be considered for further pathway modeling and/or biological interpretation.

  8. The impact of ambient air pollution on the human blood metabolome.

    Science.gov (United States)

    Vlaanderen, J J; Janssen, N A; Hoek, G; Keski-Rahkonen, P; Barupal, D K; Cassee, F R; Gosens, I; Strak, M; Steenhof, M; Lan, Q; Brunekreef, B; Scalbert, A; Vermeulen, R C H

    2017-07-01

    Biological perturbations caused by air pollution might be reflected in the compounds present in blood originating from air pollutants and endogenous metabolites influenced by air pollution (defined here as part of the blood metabolome). We aimed to assess the perturbation of the blood metabolome in response to short term exposure to air pollution. We exposed 31 healthy volunteers to ambient air pollution for 5h. We measured exposure to particulate matter, particle number concentrations, absorbance, elemental/organic carbon, trace metals, secondary inorganic components, endotoxin content, gaseous pollutants, and particulate matter oxidative potential. We collected blood from the participants 2h before and 2 and 18h after exposure. We employed untargeted metabolite profiling to monitor 3873 metabolic features in 493 blood samples from these volunteers. We assessed lung function using spirometry and six acute phase proteins in peripheral blood. We assessed the association of the metabolic features with the measured air pollutants and with health markers that we previously observed to be associated with air pollution in this study. We observed 89 robust associations between air pollutants and metabolic features two hours after exposure and 118 robust associations 18h after exposure. Some of the metabolic features that were associated with air pollutants were also associated with acute health effects, especially changes in forced expiratory volume in 1s. We successfully identified tyrosine, guanosine, and hypoxanthine among the associated features. Bioinformatics approach Mummichog predicted enriched pathway activity in eight pathways, among which tyrosine metabolism. This study demonstrates for the first time the application of untargeted metabolite profiling to assess the impact of air pollution on the blood metabolome. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Metabolomic response of Calotropis procera growing in the desert to changes in water availability.

    Directory of Open Access Journals (Sweden)

    Ahmed Ramadan

    Full Text Available Water availability is a major limitation for agricultural productivity. Plants growing in severe arid climates such as deserts provide tools for studying plant growth and performance under extreme drought conditions. The perennial species Calotropis procera used in this study is a shrub growing in many arid areas which has an exceptional ability to adapt and be productive in severe arid conditions. We describe the results of studying the metabolomic response of wild C procera plants growing in the desert to a one time water supply. Leaves of C. procera plants were taken at three time points before and 1 hour, 6 hours and 12 hours after watering and subjected to a metabolomics and lipidomics analysis. Analysis of the data reveals that within one hour after watering C. procera has already responded on the metabolic level to the sudden water availability as evidenced by major changes such as increased levels of most amino acids, a decrease in sucrose, raffinose and maltitol, a decrease in storage lipids (triacylglycerols and an increase in membrane lipids including photosynthetic membranes. These changes still prevail at the 6 hour time point after watering however 12 hours after watering the metabolomics data are essentially indistinguishable from the prewatering state thus demonstrating not only a rapid response to water availability but also a rapid response to loss of water. Taken together these data suggest that the ability of C. procera to survive under the very harsh drought conditions prevailing in the desert might be associated with its rapid adjustments to water availability and losses.

  10. Application of metabolomics on diagnosis and treatment of patients with psoriasis in traditional Chinese medicine.

    Science.gov (United States)

    Lu, Chuanjian; Deng, Jingwen; Li, Li; Wang, Dongmei; Li, Guozheng

    2014-01-01

    Traditional Chinese medicine (TCM) is one of the oldest forms of medical system. With syndrome as the core of diagnosis and therapy in TCM, it has the advantage of collecting macroscopic information of patients for diagnosis. To understand the in vivo mechanism of TCM, a metabolomics approach was used to investigate the global biological characterization of the urine of psoriasis patients with Blood Stasis Syndrome and the therapeutic metabolomics mechanism of the Optimized Yinxieling formula. A total of 41 cases of psoriasis patients with Blood Stasis Syndrome and 19 healthy volunteers were enrolled in this study. Fasting urine samples from patients with consecutive Optimized Yinxieling intake after 0, 4, 8 and 12 weeks and from healthy volunteers were analyzed by Orthogonal Projection on Latent Structures Discriminant Analysis (OPLS-DA), which was utilized for High Performance Liquid Chromatography (HPLC) analysis and temporal metabolic changes identification. For psoriasis group, the scores of PASI of patients decreased after 12 weeks of Optimized Yinxieling treating. The metabolic variations visualized not only in the healthy group and psoriasis group, but also in the psoriasis group before and after Optimized Yinxieling treatment, demonstrated that the metabolic characteristics of the two groups were significantly different. The optimized complex structure of the target proteins from Protein Data Bank was analyzed by software package Discovery Studio. With docking score of original inhibitor and the receptor as the threshold values, two compounds from Chinese medicinal chemical database were predicted to have good interactions with the target proteins. The Metabolomics technique combining molecular docking analysis enhanced our current understanding of the metabolic response to Blood Stasis Syndrome of Psoriasis and the action mechanism of Optimized Yinxieling. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology

  11. Serum metabolomic response of myasthenia gravis patients to chronic prednisone treatment.

    Science.gov (United States)

    Sengupta, Manjistha; Cheema, Amrita; Kaminski, Henry J; Kusner, Linda L

    2014-01-01

    Prednisone is often used for the treatment of autoimmune and inflammatory diseases but they suffer from variable therapeutic responses and significant adverse effects. Serum biological markers that are modulated by chronic corticosteroid use have not been identified. Myasthenia gravis is an autoimmune neuromuscular disorder caused by antibodies directed against proteins present at the post-synaptic surface of neuromuscular junction resulting in weakness. The patients with myasthenia gravis are primarily treated with prednisone. We analyzed the metabolomic profile of serum collected from patients prior to and after 12 weeks of prednisone treatment during a clinical trial. Our aim was to identify metabolites that may be treatment responsive and be evaluated in future studies as potential biomarkers of efficacy or adverse effects. Ultra-performance liquid chromatography coupled with electro-spray quadrupole time of flight mass spectrometry was used to obtain comparative metabolomic and lipidomic profile. Untargeted metabolic profiling of serum showed a clear distinction between pre- and post-treatment groups. Chronic prednisone treatment caused upregulation of membrane associated glycerophospholipids: phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, 1, 2-diacyl-sn glycerol 3 phosphate and 1-Acyl-sn-glycero-3-phosphocholine. Arachidonic acid (AA) and AA derived pro-inflammatory eicosanoids such as 18-carboxy dinor leukotriene B4 and 15 hydroxyeicosatetraenoic acids were reduced. Perturbations in amino acid, carbohydrate, vitamin and lipid metabolism were observed. Chronic prednisone treatment caused increase in membrane associated glycerophospholipids, which may be associated with certain adverse effects. Decrease of AA and AA derived pro-inflammatory eicosanoids demonstrate that immunosuppression by corticosteroid is via suppression of pro-inflammatory pathways. The study identified metabolomic fingerprints that can now be validated as prednisone

  12. AICAR stimulation metabolome widely mimics electrical contraction in isolated rat epitrochlearis muscle.

    Science.gov (United States)

    Miyamoto, Licht; Egawa, Tatsuro; Oshima, Rieko; Kurogi, Eriko; Tomida, Yosuke; Tsuchiya, Koichiro; Hayashi, Tatsuya

    2013-12-15

    Physical exercise has potent therapeutic and preventive effects against metabolic disorders. A number of studies have suggested that 5'-AMP-activated protein kinase (AMPK) plays a pivotal role in regulating carbohydrate and lipid metabolism in contracting skeletal muscles, while several genetically manipulated animal models revealed the significance of AMPK-independent pathways. To elucidate significance of AMPK and AMPK-independent signals in contracting skeletal muscles, we conducted a metabolomic analysis that compared the metabolic effects of 5-aminoimidazole-4-carboxamide-1-β-D-ribonucleoside (AICAR) stimulation with the electrical contraction ex vivo in isolated rat epitrochlearis muscles, in which both α1- and α2-isoforms of AMPK and glucose uptake were equally activated. The metabolomic analysis using capillary electrophoresis time-of-flight mass spectrometry detected 184 peaks and successfully annotated 132 small molecules. AICAR stimulation exhibited high similarity to the electrical contraction in overall metabolites. Principal component analysis (PCA) demonstrated that the major principal component characterized common effects whereas the minor principal component distinguished the difference. PCA and a factor analysis suggested a substantial change in redox status as a result of AMPK activation. We also found a decrease in reduced glutathione levels in both AICAR-stimulated and contracting muscles. The muscle contraction-evoked influences related to the metabolism of amino acids, in particular, aspartate, alanine, or lysine, are supposed to be independent of AMPK activation. Our results substantiate the significance of AMPK activation in contracting skeletal muscles and provide novel evidence that AICAR stimulation closely mimics the metabolomic changes in the contracting skeletal muscles.

  13. Atmo-metabolomics: a new measurement approach for investigating aerosol composition and ecosystem functioning.

    Science.gov (United States)

    Rivas-Ubach, A.; Liu, Y.; Sardans, J.; Tfaily, M. M.; Kim, Y. M.; Bourrianne, E.; Paša-Tolić, L.; Penuelas, J.; Guenther, A. B.

    2016-12-01

    Aerosols play crucial roles in the processes controlling the composition of the atmosphere and the functioning of ecosystems. Gaining a deeper understanding of the chemical composition of aerosols is one of the major challenges for atmospheric and climate scientists and is beginning to be recognized as important for ecological research. Better comprehension of aerosol chemistry can potentially provide valuable information on atmospheric processes such as oxidation of organics and the production of cloud condensation nuclei as well as provide an approximation of the general status of an ecosystem through the measurement of certain stress biomarkers. In this study, we describe an efficient aerosol sampling method, the metabolite extraction and the analytical procedures for the chemical characterization of aerosols, namely, the atmo-metabolome. We used mass spectrometry (MS) coupled to liquid chromatography (LC-MS), gas chromatography (GC-MS) and Fourier transform ion cyclotron resonance (FT-ICR-MS) to characterize the atmo-metabolome of two marked seasons; spring and summer. Our sampling and extraction methods demonstrated to be suitable for aerosol chemical characterization with any of the analytical platforms used in this study. The atmo-metabolome between spring and summer showed overall statistically differences. We identified several metabolites that can be attributed to pollen and other plant-related aerosols. Spring aerosols exhibit higher concentrations of metabolites linked to higher plant activity while summer samples had higher concentrations of metabolites that may reflect certain oxidative stresses in primary producers. Moreover, the elemental composition of aerosols showed clear different between seasons. Summer aerosols were generally higher in molecular weight and with higher O/C ratios, indicating higher oxidation levels and condensation of compounds relative to spring. Our method represents an advanced approach for characterizing the composition of

  14. Serum metabolomic profiles from patients with acute kidney injury: a pilot study.

    Science.gov (United States)

    Sun, Jinchun; Shannon, Melissa; Ando, Yosuke; Schnackenberg, Laura K; Khan, Nasim A; Portilla, Didier; Beger, Richard D

    2012-04-15

    Low sensitivity of current clinical markers (serum creatinine and blood urea nitrogen (BUN)) in early stages of the development of acute kidney injury (AKI) limits their utility. Rapid LC/MS-based metabolic profiling of serum demonstrated in a pilot study that metabolomics could provide novel indicators of AKI. Metabolic profiles of serum samples from seventeen hospitalized patients with newly diagnosed AKI were compared with the profiles of serum from age-matched subjects with normal kidney function. Increases in acylcarnitines and amino acids (methionine, homocysteine, pyroglutamate, asymmetric dimethylarginine (ADMA), and phenylalanine) and a reduction in serum levels of arginine and several lysophosphatidyl cholines were observed in patients with AKI compared to healthy subjects. Increases in homocysteine, ADMA and pyroglutamate have been recognized as biomarkers of cardiovascular and renal disease, and acylcarnitines represent biomarkers of defective fatty acid oxidation. The results of this pilot study demonstrate the utility of metabolomics in the discovery of novel serum biomarkers that can facilitate the diagnosis and determine prognosis of AKI in hospitalized patients.

  15. Urinary 1H-NMR Metabolomics Can Distinguish Pancreatitis Patients from Healthy Controls

    Science.gov (United States)

    Lusczek, Elizabeth R; Paulo, Joao A; Saltzman, John R; Kadiyala, Vivek; Banks, Peter A; Beilman, Greg; Conwell, Darwin L

    2015-01-01

    Context The characterization of the urinary metabolome may yield biomarkers indicative of pancreatitis. Objectives We establish a non-invasive technique to compare urinary metabolic profiles in patients with acute and chronic pancreatitis to healthy controls. Methods Urine was obtained from healthy controls (HC, n=5), in patients with mild acute pancreatitis (AP, n=5), and outpatients with chronic pancreatitis (CP, n=5). Proton nuclear magnetic resonance spectra were obtained for each sample. Metabolites were identified and quantified in each spectrum; resulting concentrations were normalized to account for differences in dilution among samples. Kruskal-Wallis test, post-hoc Mann-Whitney U tests, and principal component analysis were performed to identify metabolites that discriminate healthy controls, acute pancreatitis, and chronic pancreatitis. Results Sixty metabolites were identified and quantified; five were found to differ significantly (P<0.05) among the three groups. Of these, citrate and adenosine remained significant after validation by random permutation. Principal component analysis demonstrated that healthy control urine samples can be differentiated from patients with chronic pancreatitis or acute pancreatitis; chronic pancreatitis patients could not be distinguished from acute pancreatitis patients. Conclusions This metabolomic investigation demonstrates that this non-invasive technique offers insight into the metabolic states of pancreatitis. Although the identified metabolites cannot conclusively be defined as biomarkers of disease, future studies will validate our findings in larger patient cohorts. PMID:23474563

  16. Nutritional metabolomics: progress in addressing complexity in diet and health.

    Science.gov (United States)

    Jones, Dean P; Park, Youngja; Ziegler, Thomas R

    2012-08-21

    Nutritional metabolomics is rapidly maturing to use small-molecule chemical profiling to support integration of diet and nutrition in complex biosystems research. These developments are critical to facilitate transition of nutritional sciences from population-based to individual-based criteria for nutritional research, assessment, and management. This review addresses progress in making these approaches manageable for nutrition research. Important concept developments concerning the exposome, predictive health, and complex pathobiology serve to emphasize the central role of diet and nutrition in integrated biosystems models of health and disease. Improved analytic tools and databases for targeted and nontargeted metabolic profiling, along with bioinformatics, pathway mapping, and computational modeling, are now used for nutrition research on diet, metabolism, microbiome, and health associations. These new developments enable metabolome-wide association studies (MWAS) and provide a foundation for nutritional metabolomics, along with genomics, epigenomics, and health phenotyping, to support the integrated models required for personalized diet and nutrition forecasting.

  17. The metabolomic profile of red non-V. vinifera genotypes

    DEFF Research Database (Denmark)

    Ruocco, Silvia; Stefanini, Marco; Stanstrup, Jan

    2017-01-01

    composition of their grapes has not been widely investigated. This study aimed to explore in detail the metabolomic profile in terms of simple phenolic, proanthocyanidin, anthocyanin and lipid compounds in two hybrids and five American genotypes. The results were compared with those of two V. vinifera...... cultivars. A multi-targeted metabolomics approach using a combination of LC-MS and LC-DAD methods was used to identify and quantify 124 selected metabolites. The genotypes studied showed considerable variability in the metabolomic profile according to the grape composition of V. vinifera and other Vitis......-chain polymers. The analysis of lipids in wild Vitis genotypes, here reported for the first time, showed the existence of a certain diversity in their composition suggesting a strong influence of the environmental conditions on the general lipid pattern....

  18. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science.

    Science.gov (United States)

    Hong, Jun; Yang, Litao; Zhang, Dabing; Shi, Jianxin

    2016-06-01

    As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

  19. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

    Directory of Open Access Journals (Sweden)

    Jun Hong

    2016-06-01

    Full Text Available As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

  20. Serum Metabolomics in Rats after Acute Paraquat Poisoning.

    Science.gov (United States)

    Wang, Zhiyi; Ma, Jianshe; Zhang, Meiling; Wen, Congcong; Huang, Xueli; Sun, Fa; Wang, Shuanghu; Hu, Lufeng; Lin, Guanyang; Wang, Xianqin

    2015-01-01

    Paraquat is one of the most widely used herbicides in the world and is highly toxic to humans and animals. In this study, we developed a serum metabolomic method based on GC/MS to evaluate the effects of acute paraquat poisoning on rats. Pattern recognition analysis, including both principal component analysis and partial least squares-discriminate analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the level of octadecanoic acid, L-serine, L-threonine, L-valine, and glycerol in the acute paraquat poisoning group (36 mg/kg) increased, while the levels of hexadecanoic acid, D-galactose, and decanoic acid decreased. These findings provide an overview of systematic responses to paraquat exposure and metabolomic insight into the toxicological mechanism of paraquat. Our results indicate that metabolomic methods based on GC/MS may be useful to elucidate the mechanism of acute paraquat poisoning through the exploration of biomarkers.

  1. Metabolomics in the Rhizosphere: Tapping into Belowground Chemical Communication.

    Science.gov (United States)

    van Dam, Nicole M; Bouwmeester, Harro J

    2016-03-01

    The rhizosphere is densely populated with a variety of organisms. Interactions between roots and rhizosphere community members are mostly achieved via chemical communication. Root exudates contain an array of primary and secondary plant metabolites that can attract, deter, or kill belowground insect herbivores, nematodes, and microbes, and inhibit competing plants. Metabolomics of root exudates can potentially help us to better understand this chemical dialogue. The main limitations are the proper sampling of the exudate, the sensitivity of the metabolomics platforms, and the multivariate data analysis to identify causal relations. Novel technologies may help to generate a spatially explicit metabolome of the root and its exudates at a scale that is relevant for the rhizosphere community.

  2. Metabolomic-based identification of clusters that reflect dietary patterns.

    Science.gov (United States)

    Gibbons, Helena; Carr, Eibhlin; McNulty, Breige A; Nugent, Anne P; Walton, Janette; Flynn, Albert; Gibney, Michael J; Brennan, Lorraine

    2017-06-06

    Classification of subjects into dietary patterns generally relies on self-reporting dietary data which are prone to error. The aim of the present study was to develop a model for objective classification of people into dietary patterns based on metabolomic data. Dietary and urinary metabolomic data from the National Adult Nutrition Survey (NANS) was used in the analysis (n = 567). Two-step cluster analysis was applied to the urinary data to identify clusters. The subsequent model was used in an independent cohort to classify people into dietary patterns. Two distinct dietary patterns were identified. Cluster 1 was characterized by significantly higher intakes of breakfast cereals, low fat and skimmed milks, potatoes, fruit, fish and fish dishes (p patterns based on metabolomics data. Future applications of this approach could be developed for rapid and objective assignment of subjects into dietary patterns. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Fabrication and analysis of gecko-inspired hierarchical polymer nanosetae.

    Science.gov (United States)

    Ho, Audrey Yoke Yee; Yeo, Lip Pin; Lam, Yee Cheong; Rodríguez, Isabel

    2011-03-22

    A gecko's superb ability to adhere to surfaces is widely credited to the large attachment area of the hierarchical and fibrillar structure on its feet. The combination of these two features provides the necessary compliance for the gecko toe-pad to effectively engage a high percentage of the spatulae at each step to any kind of surface topography. With the use of multi-tiered porous anodic alumina template and capillary force assisted nanoimprinting, we have successfully fabricated a gecko-inspired hierarchical topography of branched nanopillars on a stiff polymer. We also demonstrated that the hierarchical topography improved the shear adhesion force over a topography of linear structures by 150%. A systematic analysis to understand the phenomenon was performed. It was determined that the effective stiffness of the hierarchical branched structure was lower than that of the linear structure. The reduction in effective stiffness favored a more efficient bending of the branched topography and a better compliance to a test surface, hence resulting in a higher area of residual deformation. As the area of residual deformation increased, the shear adhesion force emulated. The branched pillar topography also showed a marked increase in hydrophobicity, which is an essential property in the practical applications of these structures for good self-cleaning in dry adhesion conditions.

  4. Hierarchical Structures in Hypertext Learning Environments

    NARCIS (Netherlands)

    Bezdan, Eniko; Kester, Liesbeth; Kirschner, Paul A.

    2011-01-01

    Bezdan, E., Kester, L., & Kirschner, P. A. (2011, 9 September). Hierarchical Structures in Hypertext Learning Environments. Presentation for the visit of KU Leuven, Open University, Heerlen, The Netherlands.

  5. Navigating freely-available software tools for metabolomics analysis.

    Science.gov (United States)

    Spicer, Rachel; Salek, Reza M; Moreno, Pablo; Cañueto, Daniel; Steinbeck, Christoph

    2017-01-01

    The field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools. To compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics. The most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for. A comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary. This review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.

  6. Overview of mass spectrometry-based metabolomics: opportunities and challenges.

    Science.gov (United States)

    Gowda, G A Nagana; Djukovic, Danijel

    2014-01-01

    The field of metabolomics has witnessed an exponential growth in the last decade driven by important applications spanning a wide range of areas in the basic and life sciences and beyond. Mass spectrometry in combination with chromatography and nuclear magnetic resonance are the two major analytical avenues for the analysis of metabolic species in complex biological mixtures. Owing to its inherent significantly higher sensitivity and fast data acquisition, MS plays an increasingly dominant role in the metabolomics field. Propelled by the need to develop simple methods to diagnose and manage the numerous and widespread human diseases, mass spectrometry has witnessed tremendous growth with advances in instrumentation, experimental methods, software, and databases. In response, the metabolomics field has moved far beyond qualitative methods and simple pattern recognition approaches to a range of global and targeted quantitative approaches that are now routinely used and provide reliable data, which instill greater confidence in the derived inferences. Powerful isotope labeling and tracing methods have become very popular. The newly emerging ambient ionization techniques such as desorption ionization and rapid evaporative ionization have allowed direct MS analysis in real time, as well as new MS imaging approaches. While the MS-based metabolomics has provided insights into metabolic pathways and fluxes, and metabolite biomarkers associated with numerous diseases, the increasing realization of the extremely high complexity of biological mixtures underscores numerous challenges including unknown metabolite identification, biomarker validation, and interlaboratory reproducibility that need to be dealt with for realization of the full potential of MS-based metabolomics. This chapter provides a glimpse at the current status of the mass spectrometry-based metabolomics field highlighting the opportunities and challenges.

  7. Connecting extracellular metabolomic measurements to intracellular flux states in yeast

    Directory of Open Access Journals (Sweden)

    Herrgård Markus J

    2009-03-01

    Full Text Available Abstract Background Metabolomics has emerged as a powerful tool in the quantitative identification of physiological and disease-induced biological states. Extracellular metabolome or metabolic profiling data, in particular, can provide an insightful view of intracellular physiological states in a noninvasive manner. Results We used an updated genome-scale metabolic network model of Saccharomyces cerevisiae, iMM904, to investigate how changes in the extracellular metabolome can be used to study systemic changes in intracellular metabolic states. The iMM904 metabolic network was reconstructed based on an existing genome-scale network, iND750, and includes 904 genes and 1,412 reactions. The network model was first validated by comparing 2,888 in silico single-gene deletion strain growth phenotype predictions to published experimental data. Extracellular metabolome data measured in response to environmental and genetic perturbations of ammonium assimilation pathways was then integrated with the iMM904 network in the form of relative overflow secretion constraints and a flux sampling approach was used to characterize candidate flux distributions allowed by these constraints. Predicted intracellular flux changes were consistent with published measurements on intracellular metabolite levels and fluxes. Patterns of predicted intracellular flux changes could also be used to correctly identify the regions of the metabolic network that were perturbed. Conclusion Our results indicate that integrating quantitative extracellular metabolomic profiles in a constraint-based framework enables inferring changes in intracellular metabolic flux states. Similar methods could potentially be applied towards analyzing biofluid metabolome variations related to human physiological and disease states.

  8. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action.

    Science.gov (United States)

    Vincent, Isabel M; Ehmann, David E; Mills, Scott D; Perros, Manos; Barrett, Michael P

    2016-04-01

    Deciphering the mode of action (MOA) of new antibiotics discovered through phenotypic screening is of increasing importance. Metabolomics offers a potentially rapid and cost-effective means of identifying modes of action of drugs whose effects are mediated through changes in metabolism. Metabolomics techniques also collect data on off-target effects and drug modifications. Here, we present data from an untargeted liquid chromatography-mass spectrometry approach to identify the modes of action of eight compounds: 1-[3-fluoro-4-(5-methyl-2,4-dioxo-pyrimidin-1-yl)phenyl]-3-[2-(trifluoromethyl)phenyl]urea (AZ1), 2-(cyclobutylmethoxy)-5'-deoxyadenosine, triclosan, fosmidomycin, CHIR-090, carbonyl cyanidem-chlorophenylhydrazone (CCCP), 5-chloro-2-(methylsulfonyl)-N-(1,3-thiazol-2-yl)-4-pyrimidinecarboxamide (AZ7), and ceftazidime. Data analysts were blind to the compound identities but managed to identify the target as thymidylate kinase for AZ1, isoprenoid biosynthesis for fosmidomycin, acyl-transferase for CHIR-090, and DNA metabolism for 2-(cyclobutylmethoxy)-5'-deoxyadenosine. Changes to cell wall metabolites were seen in ceftazidime treatments, although other changes, presumably relating to off-target effects, dominated spectral outputs in the untargeted approach. Drugs which do not work through metabolic pathways, such as the proton carrier CCCP, have no discernible impact on the metabolome. The untargeted metabolomics approach also revealed modifications to two compounds, namely, fosmidomycin and AZ7. An untreated control was also analyzed, and changes to the metabolome were seen over 4 h, highlighting the necessity for careful controls in these types of studies. Metabolomics is a useful tool in the analysis of drug modes of action and can complement other technologies already in use.

  9. [Application and research advances of metabolomics in the field of orthopedics].

    Science.gov (United States)

    Sun, Zhijian; Qiu, Guixing; Zhao, Yu

    2015-06-01

    Metabolomics is a subject of systematic, qualitative and quantitative analysis of all metabolites in all organisms, which is applied to finding biomarkers and studying pathogenesis of diseases. Study procedures of metabolomics include data acquisition by spectroscopic/spectrometric techniques, multivariate statistical analysis and projection of the acquired metabolomic information. In recent years, metabolomics have gained popularity in orthopedic field. Metabolomic study of osteoarthritis was firstly conducted and widely developed. Metabolite profiles of different samples, including serum/plasma, urine, synovial fluid and synovial tissue, were studied and dozens of differential metabolites and several disturbed metabolic pathways were found. In addition, metabolomic studies of osteoporosis, ankylosing spondylitis and bone tumors were also conducted, which identified many potential biomarkers and made further understanding of pathogenesis of corresponding disease. However, metabolomic studies in orthopedic field just begin. More orthopedic diseases will be researched thank to the satisfactory results of previous reports.

  10. Dynamic Organization of Hierarchical Memories.

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2016-01-01

    In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a "dynamic categorization"; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity.

  11. Hierarchical structures in fully developed turbulence

    Science.gov (United States)

    Liu, Li

    Analysis of the probability density functions (PDFs) of the velocity increment dvl and of their deformation is used to reveal the statistical structure of the intermittent energy cascade dynamics of turbulence. By analyzing a series of turbulent data sets including that of an experiment of fully developed low temperature helium turbulent gas flow (Belin, Tabeling, & Willaime, Physica D 93, 52, 1996), of a three-dimensional isotropic Navier-Stokes simulation with a resolution of 2563 (Cao, Chen, & She, Phys. Rev. Lett. 76, 3711, 1996) and of a GOY shell model simulation (Leveque & She, Phys. Rev. E 55, 1997) of a very big sample size (up to 5 billions), the validity of the Hierarchical Structure model (She & Leveque, Phys. Rev. Lett. 72, 366, 1994) for the inertial-range is firmly demonstrated. Furthermore, it is shown that parameters in the Hierarchical Structure model can be reliably measured and used to characterize the cascade process. The physical interpretations of the parameters then allow to describe differential changes in different turbulent systems so as to address non-universal features of turbulent systems. It is proposed that the above study provides a framework for the study of non-homogeneous turbulence. A convergence study of moments and scaling exponents is also carried out with detailed analysis of effects of finite statistical sample size. A quantity Pmin is introduced to characterize the resolution of a PDF, and hence the sample size. The fact that any reported scaling exponent depends on the PDF resolution suggests that the validation (or rejection) of a model of turbulence needs to carry out a resolution dependence analysis on its scaling prediction.

  12. Metabolomics kan potentielt forbedre lægemiddelterapien

    DEFF Research Database (Denmark)

    Stage, Claus; Jürgens, Gesche; Dalhoff, Kim Peder

    2014-01-01

    Until now drug therapy has primarily been controlled by dose titration on the basis of effects and side effects. However, a lot of people being treated with a drug experience too little effect or too many side effects. Therefore it will be advantageous to improve drug therapy and make it even mor...... "individualized". In this chase metabolomics is a hot topic. The aim of this paper is to review the concepts of metabolomics and the possible applications in regard to drug development, drug therapy and diagnosis, prognosis and monitoring of diseases....

  13. Metabolomics has the potential to improve drug therapy

    DEFF Research Database (Denmark)

    Stage, Claus; Jürgens, Gesche; Dalhoff, Kim Peder

    2014-01-01

    Until now drug therapy has primarily been controlled by dose titration on the basis of effects and side effects. However, a lot of people being treated with a drug experience too little effect or too many side effects. Therefore it will be advantageous to improve drug therapy and make it even mor...... "individualized". In this chase metabolomics is a hot topic. The aim of this paper is to review the concepts of metabolomics and the possible applications in regard to drug development, drug therapy and diagnosis, prognosis and monitoring of diseases....

  14. Human gut microbes impact host serum metabolome and insulin sensitivity

    DEFF Research Database (Denmark)

    Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Nielsen, Henrik Bjørn

    2016-01-01

    -resistant individuals is characterized by increased levels of branched-chain amino acids (BCAAs), which correlate with a gut microbiome that has an enriched biosynthetic potential for BCAAs and is deprived of genes encoding bacterial inward transporters for these amino acids. Prevotella copri and Bacteroides vulgatus......Insulin resistance is a forerunner state of ischaemic cardiovascular disease and type 2 diabetes. Here we show how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals. The serum metabolome of insulin...

  15. Pediatric obesity: could metabolomics be a useful tool?

    Directory of Open Access Journals (Sweden)

    Angelica Dessì

    2013-06-01

    Full Text Available Pediatric obesity represents an important health issue. In recent years applications of metabolomics have led to evaluation of responses to the various nutrients (nutrigenomics, in particular to lipids, in diseases such as obesity and diabetes. The experimental data and the studies in pediatrics  that evaluated the metabolic condition in infant obesity are presented. It is thus to be hoped that future progress in connection with this new technique, together with a metabolomic study of mother's milk and formula milk, will lead to the creation of better personalized nutritional therapies to prevent infantile obesity and the chronic pathologies of adults connected with it.

  16. Recent applications of metabolomics to advance microbial biofuel production.

    Science.gov (United States)

    Martien, Julia I; Amador-Noguez, Daniel

    2017-02-01

    Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers. Copyright © 2016. Published by Elsevier Ltd.

  17. The potential biomarkers of drug addiction: proteomic and metabolomics challenges.

    Science.gov (United States)

    Wang, Lv; Wu, Ning; Zhao, Tai-Yun; Li, Jin

    2016-07-28

    Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.

  18. Hierarchical Semiconductor Oxide Photo catalyst:A Case of the SnO2 Microflower

    Institute of Scientific and Technical Information of China (English)

    Yang Liu; Yang Jiao; Bosi Yin; Siwen Zhang; Fengyu Qu; Xiang Wu∗

    2013-01-01

    Hierarchically assembled SnO2 microflowers were synthesized by a facile hydrothermal process. Field emission scanning electron microscope results showed these hierarchical nanostructures were built from two dimensional nanosheets with the thicknesses of about 50 nm. Photoluminescence spectrum of the as-obtained products demonstrated a strong visual emission peak at 564 nm. The photochemical measurement results indicated that the as-prepared sample exhibits excellent photocatalytic performance. These three di-mensional SnO2 hierarchical nanostructures may have potential applications in waste water purification.

  19. Constrained hierarchical least square nonlinear equation solvers. [for indefinite stiffness and large structural deformations

    Science.gov (United States)

    Padovan, J.; Lackney, J.

    1986-01-01

    The current paper develops a constrained hierarchical least square nonlinear equation solver. The procedure can handle the response behavior of systems which possess indefinite tangent stiffness characteristics. Due to the generality of the scheme, this can be achieved at various hierarchical application levels. For instance, in the case of finite element simulations, various combinations of either degree of freedom, nodal, elemental, substructural, and global level iterations are possible. Overall, this enables a solution methodology which is highly stable and storage efficient. To demonstrate the capability of the constrained hierarchical least square methodology, benchmarking examples are presented which treat structure exhibiting highly nonlinear pre- and postbuckling behavior wherein several indefinite stiffness transitions occur.

  20. Liquid phase epitaxial growth of heterostructured hierarchical MOF thin films

    KAUST Repository

    Chernikova, Valeriya

    2017-05-10

    Precise control of epitaxial growth of MOF-on-MOF thin films, for ordered hierarchical tbo-type structures is demonstrated. The heterostructured MOF thin film was fabricated by successful sequential deposition of layers from two different MOFs. The 2-periodic layers, edge-transitive 4,4-square lattices regarded as supermolecular building layers, were commendably cross-linked using a combination of inorganic/organic and organic pillars.

  1. Bio-effectors from waste materials as growth promoters, an agronomic and metabolomic study

    Science.gov (United States)

    Alwanney, Deaa; Chami, Ziad Al; Angelica De Pascali, Sandra; Cavoski, Ivana; Fanizzi, Francesco Paolo

    2014-05-01

    low application doses; (vi) regarding plant metabolomics study, all treatments showed a different metabolites in respect to Ctrl- treatment. BSG, LPR and Ctrl+ treatments had similar metabolic profile. Finally, Metabolomic study provided an efficient tool and a key reporter about bio-effectors impact on plants. The visible effect and measured agronomical parameters was emphasized and demonstrated by metabolic profiling which offer insights into the affected plant metabolic pathways. As conclusion, our results supported the prediction that plant derived materials may interfere again in plant production regardless their nutritional content. Keywords: Bio-effectors; Metabolomics; Nuclear Magnetic Resonance (NMR); Barley; Fennel; Lemon; Tomato.

  2. To Aggregate or Not and Potentially Better Questions for Clustered Data: The Need for Hierarchical Linear Modeling in CTE Research

    Science.gov (United States)

    Nimon, Kim

    2012-01-01

    Using state achievement data that are openly accessible, this paper demonstrates the application of hierarchical linear modeling within the context of career technical education research. Three prominent approaches to analyzing clustered data (i.e., modeling aggregated data, modeling disaggregated data, modeling hierarchical data) are discussed…

  3. Synthesis of New Dynamic Movement Primitives Through Search in a Hierarchical Database of Example Movements

    Directory of Open Access Journals (Sweden)

    Miha Deniša

    2015-10-01

    Full Text Available This paper presents a novel approach to discovering motor primitives in a hierarchical database of example trajectories. An initial set of example trajectories is obtained by human demonstration. The trajectories are clustered and organized in a binary tree-like hierarchical structure, from which transition graphs at different levels of granularity are constructed. A novel procedure for searching in this hierarchical structure is presented. It can exploit the interdependencies between movements and can discover new series of partial paths. From these partial paths, complete new movements are generated by encoding them as dynamic movement primitives. In this way, the number of example trajectories that must be acquired with the assistance of a human teacher can be reduced. By combining the results of the hierarchical search with statistical generalization techniques, a complete representation of new, not directly demonstrated, movement primitives can be generated.

  4. Identification of metabolites with anticancer properties by computational metabolomics

    Directory of Open Access Journals (Sweden)

    Bowen Nathan J

    2008-06-01

    Full Text Available Abstract Background Certain endogenous metabolites can influence the rate of cancer cell growth. For example, diacylglycerol, ceramides and sphingosine, NAD+ and arginine exert this effect by acting as signaling molecules, while carrying out other important cellular functions. Metabolites can also be involved in the control of cell proliferation by directly regulating gene expression in ways that are signaling pathway-independent, e.g. by direct activation of transcription factors or by inducing epigenetic processes. The fact that metabolites can affect the cancer process on so many levels suggests that the change in concentration of some metabolites that occurs in cancer cells could have an active role in the progress of the disease. Results CoMet, a fully automated Computational Metabolomics method to predict changes in metabolite levels in cancer cells compared to normal references has been developed and applied to Jurkat T leukemia cells with the goal of testing the following hypothesis: Up or down regulation in cancer cells of the expression of genes encoding for metabolic enzymes leads to changes in intracellular metabolite concentrations that contribute to disease progression. All nine metabolites predicted to be lowered in Jurkat cells with respect to lymphoblasts that were examined (riboflavin, tryptamine, 3-sulfino-L-alanine, menaquinone, dehydroepiandrosterone, α-hydroxystearic acid, hydroxyacetone, seleno-L-methionine and 5,6-dimethylbenzimidazole, exhibited antiproliferative activity that has not been reported before, while only two (bilirubin and androsterone of the eleven tested metabolites predicted to be increased or unchanged in Jurkat cells displayed significant antiproliferative activity. Conclusion These results: a demonstrate that CoMet is a valuable method to identify potential compounds for experimental validation, b indicate that cancer cell metabolism may be regulated to reduce the intracellular concentration of

  5. Evaluation of Pacific White Shrimp (Litopenaeus vannamei) Health during a Superintensive Aquaculture Growout Using NMR-Based Metabolomics

    Science.gov (United States)

    Schock, Tracey B.; Duke, Jessica; Goodson, Abby; Weldon, Daryl; Brunson, Jeff; Leffler, John W.; Bearden, Daniel W.

    2013-01-01

    Success of the shrimp aquaculture industry requires technological advances that increase production and environmental sustainability. Indoor, superintensive, aquaculture systems are being developed that permit year-round production of farmed shrimp at high densities. These systems are intended to overcome problems of disease susceptibility and of water quality issues from waste products, by operating as essentially closed systems that promote beneficial microbial communities (biofloc). The resulting biofloc can assimilate and detoxify wastes, may provide nutrition for the farmed organisms resulting in improved growth, and may aid in reducing disease initiated from external sources. Nuclear magnetic resonance (NMR)-based metabolomic techniques were used to assess shrimp health during a full growout cycle from the nursery phase through harvest in a minimal-exchange, superintensive, biofloc system. Aberrant shrimp metabolomes were detected from a spike in total ammonia nitrogen in the nursery, from a reduced feeding period that was a consequence of surface scum build-up in the raceway, and from the stocking transition from the nursery to the growout raceway. The biochemical changes in the shrimp that were induced by the stressors were essential for survival and included nitrogen detoxification and energy conservation mechanisms. Inosine and trehalose may be general biomarkers of stress in Litopenaeus vannamei. This study demonstrates one aspect of the practicality of using NMR-based metabolomics to enhance the aquaculture industry by providing physiological insight into common environmental stresses that may limit growth or better explain reduced survival and production. PMID:23555690

  6. Evaluation of Pacific white shrimp (Litopenaeus vannamei) health during a superintensive aquaculture growout using NMR-based metabolomics.

    Science.gov (United States)

    Schock, Tracey B; Duke, Jessica; Goodson, Abby; Weldon, Daryl; Brunson, Jeff; Leffler, John W; Bearden, Daniel W

    2013-01-01

    Success of the shrimp aquaculture industry requires technological advances that increase production and environmental sustainability. Indoor, superintensive, aquaculture systems are being developed that permit year-round production of farmed shrimp at high densities. These systems are intended to overcome problems of disease susceptibility and of water quality issues from waste products, by operating as essentially closed systems that promote beneficial microbial communities (biofloc). The resulting biofloc can assimilate and detoxify wastes, may provide nutrition for the farmed organisms resulting in improved growth, and may aid in reducing disease initiated from external sources. Nuclear magnetic resonance (NMR)-based metabolomic techniques were used to assess shrimp health during a full growout cycle from the nursery phase through harvest in a minimal-exchange, superintensive, biofloc system. Aberrant shrimp metabolomes were detected from a spike in total ammonia nitrogen in the nursery, from a reduced feeding period that was a consequence of surface scum build-up in the raceway, and from the stocking transition from the nursery to the growout raceway. The biochemical changes in the shrimp that were induced by the stressors were essential for survival and included nitrogen detoxification and energy conservation mechanisms. Inosine and trehalose may be general biomarkers of stress in Litopenaeus vannamei. This study demonstrates one aspect of the practicality of using NMR-based metabolomics to enhance the aquaculture industry by providing physiological insight into common environmental stresses that may limit growth or better explain reduced survival and production.

  7. Exploring the Process of Energy Generation in Pathophysiology by Targeted Metabolomics: Performance of a Simple and Quantitative Method

    Science.gov (United States)

    Riera-Borrull, Marta; Rodríguez-Gallego, Esther; Hernández-Aguilera, Anna; Luciano, Fedra; Ras, Rosa; Cuyàs, Elisabet; Camps, Jordi; Segura-Carretero, Antonio; Menendez, Javier A.; Joven, Jorge; Fernández-Arroyo, Salvador

    2016-01-01

    Abnormalities in mitochondrial metabolism and regulation of energy balance contribute to human diseases. The consequences of high fat and other nutrient intake, and the resulting acquired mitochondrial dysfunction, are essential to fully understand common disorders, including obesity, cancer, and atherosclerosis. To simultaneously and noninvasively measure and quantify indirect markers of mitochondrial function, we have developed a method based on gas chromatography coupled to quadrupole-time of flight mass spectrometry and an electron ionization interface, and validated the system using plasma from patients with peripheral artery disease, human cancer cells, and mouse tissues. This approach was used to increase sensibility in the measurement of a wide dynamic range and chemical diversity of multiple intermediate metabolites used in energy metabolism. We demonstrate that our targeted metabolomics method allows for quick and accurate identification and quantification of molecules, including the measurement of small yet significant biological changes in experimental samples. The apparently low process variability required for its performance in plasma, cell lysates, and tissues allowed a rapid identification of correlations between interconnected pathways. Our results suggest that delineating the process of energy generation by targeted metabolomics can be a valid surrogate for predicting mitochondrial dysfunction in biological samples. Importantly, when used in plasma, targeted metabolomics should be viewed as a robust and noninvasive source of biomarkers in specific pathophysiological scenarios.

  8. Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS) Magnetic Resonance Spectroscopy (MRS).

    Science.gov (United States)

    Fuss, Taylor L; Cheng, Leo L

    2016-03-22

    According to World Health Organization (WHO) estimates, cancer is responsible for more deaths than all coronary heart disease or stroke worldwide, serving as a major public health threat around the world. High resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) has demonstrated its usefulness in the identification of cancer metabolic markers with the potential to improve diagnosis and prognosis for the oncology clinic, due partially to its ability to preserve tissue architecture for subsequent histological and molecular pathology analysis. Capable of the quantification of individual metabolites, ratios of metabolites, and entire metabolomic profiles, HRMAS MRS is one of the major techniques now used in cancer metabolomic research. This article reviews and discusses literature reports of HRMAS MRS studies of cancer metabolomics published between 2010 and 2015 according to anatomical origins, including brain, breast, prostate, lung, gastrointestinal, and neuroendocrine cancers. These studies focused on improving diagnosis and understanding patient prognostication, monitoring treatment effects, as well as correlating with the use of in vivo MRS in cancer clinics.

  9. Evaluation of Pacific white shrimp (Litopenaeus vannamei health during a superintensive aquaculture growout using NMR-based metabolomics.

    Directory of Open Access Journals (Sweden)

    Tracey B Schock

    Full Text Available Success of the shrimp aquaculture industry requires technological advances that increase production and environmental sustainability. Indoor, superintensive, aquaculture systems are being developed that permit year-round production of farmed shrimp at high densities. These systems are intended to overcome problems of disease susceptibility and of water quality issues from waste products, by operating as essentially closed systems that promote beneficial microbial communities (biofloc. The resulting biofloc can assimilate and detoxify wastes, may provide nutrition for the farmed organisms resulting in improved growth, and may aid in reducing disease initiated from external sources. Nuclear magnetic resonance (NMR-based metabolomic techniques were used to assess shrimp health during a full growout cycle from the nursery phase through harvest in a minimal-exchange, superintensive, biofloc system. Aberrant shrimp metabolomes were detected from a spike in total ammonia nitrogen in the nursery, from a reduced feeding period that was a consequence of surface scum build-up in the raceway, and from the stocking transition from the nursery to the growout raceway. The biochemical changes in the shrimp that were induced by the stressors were essential for survival and included nitrogen detoxification and energy conservation mechanisms. Inosine and trehalose may be general biomarkers of stress in Litopenaeus vannamei. This study demonstrates one aspect of the practicality of using NMR-based metabolomics to enhance the aquaculture industry by providing physiological insight into common environmental stresses that may limit growth or better explain reduced survival and production.

  10. Metabolomics approach reveals metabolic disorders and potential biomarkers associated with the developmental toxicity of tetrabromobisphenol A and tetrachlorobisphenol A

    Science.gov (United States)

    Ye, Guozhu; Chen, Yajie; Wang, Hong-Ou; Ye, Ting; Lin, Yi; Huang, Qiansheng; Chi, Yulang; Dong, Sijun

    2016-10-01

    Tetrabromobisphenol A and tetrachlorobisphenol A are halogenated bisphenol A (H-BPA), and has raised concerns about their adverse effects on the development of fetuses and infants, however, the molecular mechanisms are unclear, and related metabolomics studies are limited. Accordingly, a metabolomics study based on gas chromatography-mass spectrometry was employed to elucidate the molecular developmental toxicology of H-BPA using the marine medaka (Oryzias melastigmas) embryo model. Here, we revealed decreased synthesis of nucleosides, amino acids and lipids, and disruptions in the TCA (tricarboxylic acid) cycle, glycolysis and lipid metabolism, thus inhibiting the developmental processes of embryos exposed to H-BPA. Unexpectedly, we observed enhanced neural activity accompanied by lactate accumulation and accelerated heart rates due to an increase in dopamine pathway and a decrease in inhibitory neurotransmitters following H-BPA exposure. Notably, disorders of the neural system, and disruptions in glycolysis, the TCA cycle, nucleoside metabolism, lipid metabolism, glutamate and aspartate metabolism induced by H-BPA exposure were heritable. Furthermore, lactate and dopa were identified as potential biomarkers of the developmental toxicity of H-BPA and related genetic effects. This study has demonstrated that the metabolomics approach is a useful tool for obtaining comprehensive and novel insights into the molecular developmental toxicity of environmental pollutants.

  11. (1)H NMR based metabolomics approach to study the toxic effects of herbicide butachlor on goldfish (Carassius auratus).

    Science.gov (United States)

    Xu, Hua-Dong; Wang, Jun-Song; Li, Ming-Hui; Liu, Yan; Chen, Ting; Jia, Ai-Qun

    2015-02-01

    Butachlor, one of the most widely used herbicides in agriculture, has been reported with high ecotoxicity to aquatic plants and animals. In this study, a (1)H NMR based metabolomics approach combined with histopathological examination and biochemical assays was applied to comprehensively investigate the toxic effects of butachlor on four important organs (gill, brain, liver and kidney) of goldfish (Carassius auratus) for the first time. After 10 days' butachlor exposure at two dosages of 3.2 and 0.64 μmol/L, fish tissues (gill, brain, liver and kidney) and serum were collected. Histopathological inspection revealed severe impairment of gill filaments and obvious cellular edema in livers and kidneys. The increase of glutathione peroxidase (GSH-Px) activity in gill and methane dicarboxylic aldehyde (MDA) level in four tissues reflected the disturbance of antioxidative system in the intoxicated goldfish. Serum lactate dehydrogenase (LDH) activity and creatinine (CRE) level were increased in butachlor exposure groups, suggesting liver and kidney injuries induced by butachlor. Orthogonal signal correction partial least-squares discriminant analysis (OSC-PLS-DA) of NMR profiles disclosed metabolic changes that were related to the toxic effects of butachlor including oxidative stress, disorder of energy metabolism and amino acids metabolism, and disturbance of neurotransmitter balance in butachlor exposed goldfish. This integrated metabolomics approach provided a molecular basis underlying the toxicity of butachlor and demonstrated that metabolomics was a powerful and highly effective approach to elucidate the toxicity and underlying mechanisms of herbicides and pesticides, applicable for their risk assessment.

  12. Anti-hierarchical evolution of the AGN space density in a hierarchical universe

    CERN Document Server

    Enoki, Motohiro; Kobayashi, Masakazu A R; Nagashima, Masahiro

    2014-01-01

    Recent observations show that the space density of luminous active galactic nuclei (AGN) peaks at higher redshifts than that of faint AGN. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos and the AGN life time scaling with the dynamical time scale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by st...

  13. Comparison of peak-picking workflows for untargeted liquid chromatography/high-resolution mass spectrometry metabolomics data analysis.

    Science.gov (United States)

    Rafiei, Atefeh; Sleno, Lekha

    2015-01-15

    Data analysis is a key step in mass spectrometry based untargeted metabolomics, starting with the generation of generic peak lists from raw liquid chromatography/mass spectrometry (LC/MS) data. Due to the use of various algorithms by different workflows, the results of different peak-picking strategies often differ widely. Raw LC/HRMS data from two types of biological samples (bile and urine), as well as a standard mixture of 84 metabolites, were processed with four peak-picking softwares: Peakview®, Markerview™, MetabolitePilot™ and XCMS Online. The overlaps between the results of each peak-generating method were then investigated. To gauge the relevance of peak lists, a database search using the METLIN online database was performed to determine which features had accurate masses matching known metabolites as well as a secondary filtering based on MS/MS spectral matching. In this study, only a small proportion of all peaks (less than 10%) were common to all four software programs. Comparison of database searching results showed peaks found uniquely by one workflow have less chance of being found in the METLIN metabolomics database and are even less likely to be confirmed by MS/MS. It was shown that the performance of peak-generating workflows has a direct impact on untargeted metabolomics results. As it was demonstrated that the peaks found in more than one peak detection workflow have higher potential to be identified by accurate mass as well as MS/MS spectrum matching, it is suggested to use the overlap of different peak-picking workflows as preliminary peak lists for more rugged statistical analysis in global metabolomics investigations. Copyright © 2014 John Wiley & Sons, Ltd.

  14. Defects in mitochondrial dynamics and metabolomic signatures of evolving energetic stress in mouse models of familial Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Eugenia Trushina

    Full Text Available BACKGROUND: The identification of early mechanisms underlying Alzheimer's Disease (AD and associated biomarkers could advance development of new therapies and improve monitoring and predicting of AD progression. Mitochondrial dysfunction has been suggested to underlie AD pathophysiology, however, no comprehensive study exists that evaluates the effect of different familial AD (FAD mutations on mitochondrial function, dynamics, and brain energetics. METHODS AND FINDINGS: We characterized early mitochondrial dysfunction and metabolomic signatures of energetic stress in three commonly used transgenic mouse models of FAD. Assessment of mitochondrial motility, distribution, dynamics, morphology, and metabolomic profiling revealed the specific effect of each FAD mutation on the development of mitochondrial stress and dysfunction. Inhibition of mitochondrial trafficking was characteristic for embryonic neurons from mice expressing mutant human presenilin 1, PS1(M146L and the double mutation of human amyloid precursor protein APP(Tg2576 and PS1(M146L contributing to the increased susceptibility of neurons to excitotoxic cell death. Significant changes in mitochondrial morphology were detected in APP and APP/PS1 mice. All three FAD models demonstrated a loss of the integrity of synaptic mitochondria and energy production. Metabolomic profiling revealed mutation-specific changes in the levels of metabolites reflecting altered energy metabolism and mitochondrial dysfunction in brains of FAD mice. Metabolic biomarkers adequately reflected gender differences similar to that reported for AD patients and correlated well with the biomarkers currently used for diagnosis in humans. CONCLUSIONS: Mutation-specific alterations in mitochondrial dynamics, morphology and function in FAD mice occurred prior to the onset of memory and neurological phenotype and before the formation of amyloid deposits. Metabolomic signatures of mitochondrial stress and altered energy

  15. Discovering hierarchical structure in normal relational data

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Herlau, Tue; Mørup, Morten

    2014-01-01

    Hierarchical clustering is a widely used tool for structuring and visualizing complex data using similarity. Traditionally, hierarchical clustering is based on local heuristics that do not explicitly provide assessment of the statistical saliency of the extracted hierarchy. We propose a non-param...

  16. Discursive Hierarchical Patterning in Economics Cases

    Science.gov (United States)

    Lung, Jane

    2011-01-01

    This paper attempts to apply Lung's (2008) model of the discursive hierarchical patterning of cases to a closer and more specific study of Economics cases and proposes a model of the distinct discursive hierarchical patterning of the same. It examines a corpus of 150 Economics cases with a view to uncovering the patterns of discourse construction.…

  17. A Model of Hierarchical Key Assignment Scheme

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhigang; ZHAO Jing; XU Maozhi

    2006-01-01

    A model of the hierarchical key assignment scheme is approached in this paper, which can be used with any cryptography algorithm. Besides, the optimal dynamic control property of a hierarchical key assignment scheme will be defined in this paper. Also, our scheme model will meet this property.

  18. Galaxy formation through hierarchical clustering

    Science.gov (United States)

    White, Simon D. M.; Frenk, Carlos S.

    1991-01-01

    Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

  19. Groups possessing extensive hierarchical decompositions

    CERN Document Server

    Januszkiewicz, T; Leary, I J

    2009-01-01

    Kropholler's class of groups is the smallest class of groups which contains all finite groups and is closed under the following operator: whenever $G$ admits a finite-dimensional contractible $G$-CW-complex in which all stabilizer groups are in the class, then $G$ is itself in the class. Kropholler's class admits a hierarchical structure, i.e., a natural filtration indexed by the ordinals. For example, stage 0 of the hierarchy is the class of all finite groups, and stage 1 contains all groups of finite virtual cohomological dimension. We show that for each countable ordinal $\\alpha$, there is a countable group that is in Kropholler's class which does not appear until the $\\alpha+1$st stage of the hierarchy. Previously this was known only for $\\alpha= 0$, 1 and 2. The groups that we construct contain torsion. We also review the construction of a torsion-free group that lies in the third stage of the hierarchy.

  20. Quantum transport through hierarchical structures.

    Science.gov (United States)

    Boettcher, S; Varghese, C; Novotny, M A

    2011-04-01

    The transport of quantum electrons through hierarchical lattices is of interest because such lattices have some properties of both regular lattices and random systems. We calculate the electron transmission as a function of energy in the tight-binding approximation for two related Hanoi networks. HN3 is a Hanoi network with every site having three bonds. HN5 has additional bonds added to HN3 to make the average number of bonds per site equal to five. We present a renormalization group approach to solve the matrix equation involved in this quantum transport calculation. We observe band gaps in HN3, while no such band gaps are observed in linear networks or in HN5. We provide a detailed scaling analysis near the edges of these band gaps.

  1. Hierarchical networks of scientific journals

    CERN Document Server

    Palla, Gergely; Mones, Enys; Pollner, Péter; Vicsek, Tamás

    2015-01-01

    Scientific journals are the repositories of the gradually accumulating knowledge of mankind about the world surrounding us. Just as our knowledge is organised into classes ranging from major disciplines, subjects and fields to increasingly specific topics, journals can also be categorised into groups using various metrics. In addition to the set of topics characteristic for a journal, they can also be ranked regarding their relevance from the point of overall influence. One widespread measure is impact factor, but in the present paper we intend to reconstruct a much more detailed description by studying the hierarchical relations between the journals based on citation data. We use a measure related to the notion of m-reaching centrality and find a network which shows the level of influence of a journal from the point of the direction and efficiency with which information spreads through the network. We can also obtain an alternative network using a suitably modified nested hierarchy extraction method applied ...

  2. Adaptive Sampling in Hierarchical Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R

    2007-07-09

    We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.

  3. Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset.

    Science.gov (United States)

    Watson, Nathanial E; Parsons, Brendon A; Synovec, Robert E

    2016-08-12

    Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified.

  4. Metabolomics analysis of the effect of dissolved oxygen on spinosad production by Saccharopolyspora spinosa.

    Science.gov (United States)

    Lu, Chunzhe; Yin, Jing; Zhao, Fanglong; Li, Feng; Lu, Wenyu

    2017-05-01

    Spinosad, a universal bio-pesticide, is obtained from the soil actinomycete Saccharopolyspora spinosa. Dissolved oxygen, an important contributing factor in aerobic microbial fermentation, however, is not always available in sufficient amounts. To alleviate oxygen limitation in spinosad production, three different oxygen vectors, namely oleic acid, toluene, and n-dodecane, were added into early fermentation. Results indicated that n-dodecane was the optimal oxygen vector. Spinosad yield was increased by 44.2% compared to that in the control group in the presence of 0.5% n-dodecane, added after 120 h of incubation. Yields of the test group reached 6.52 mg/g dry cell weight (DCW), while that of the control group was limited to 4.52 mg/g DCW. Metabolomics analysis by gas chromatography coupled to mass spectrometry was performed to demonstrate the metabolism mechanism in the presence and absence of oxygen vector. In total, 78 principal intracellular metabolites in S. spinosa were detected and quantified in the presence and absence of n-dodecane. Levels of some metabolites that were related to the tricarboxylic acid cycle and pentose phosphate pathway varied significantly. Aspartic acid and glucose-1-phosphate levels varied significantly and contributed most in the distinction of the fermentation conditions and phases. The above findings give new insights into the improvement and the metabolomic characteristics of industrial spinosad production.

  5. Biodiversity, Anti-Trypanosomal Activity Screening, and Metabolomic Profiling of Actinomycetes Isolated from Mediterranean Sponges.

    Directory of Open Access Journals (Sweden)

    Cheng Cheng

    Full Text Available Marine sponge-associated actinomycetes are considered as promising sources for the discovery of novel biologically active compounds. In the present study, a total of 64 actinomycetes were isolated from 12 different marine sponge species that had been collected offshore the islands of Milos and Crete, Greece, eastern Mediterranean. The isolates were affiliated to 23 genera representing 8 different suborders based on nearly full length 16S rRNA gene sequencing. Four putatively novel species belonging to genera Geodermatophilus, Microlunatus, Rhodococcus and Actinomycetospora were identified based on a 16S rRNA gene sequence similarity of < 98.5% to currently described strains. Eight actinomycete isolates showed bioactivities against Trypanosma brucei brucei TC221 with half maximal inhibitory concentration (IC50 values <20 μg/mL. Thirty four isolates from the Milos collection and 12 isolates from the Crete collection were subjected to metabolomic analysis using high resolution LC-MS and NMR for dereplication purposes. Two isolates belonging to the genera Streptomyces (SBT348 and Micromonospora (SBT687 were prioritized based on their distinct chemistry profiles as well as their anti-trypanosomal activities. These findings demonstrated the feasibility and efficacy of utilizing metabolomics tools to prioritize chemically unique strains from microorganism collections and further highlight sponges as rich source for novel and bioactive actinomycetes.

  6. Advances in the genomics and metabolomics of dairy lactobacilli: A review.

    Science.gov (United States)

    Stefanovic, Ewelina; Fitzgerald, Gerald; McAuliffe, Olivia

    2017-02-01

    The Lactobacillus genus represents the largest and most diverse genera of all the lactic acid bacteria (LAB), encompassing species with applications in industrial, biotechnological and medical fields. The increasing number of available Lactobacillus genome sequences has allowed understanding of genetic and metabolic potential of this LAB group. Pangenome and core genome studies are available for numerous species, demonstrating the plasticity of the Lactobacillus genomes and providing the evidence of niche adaptability. Advancements in the application of lactobacilli in the dairy industry lie in exploring the genetic background of their commercially important characteristics, such as flavour development potential or resistance to the phage attack. The integration of available genomic and metabolomic data through the generation of genome scale metabolic models has enabled the development of computational models that predict the behaviour of organisms under specific conditions and present a route to metabolic engineering. Lactobacilli are recognised as potential cell factories, confirmed by the successful production of many compounds. In this review, we discuss the current knowledge of genomics, metabolomics and metabolic engineering of the prevalent Lactobacillus species associated with the production of fermented dairy foods. In-depth understanding of their characteristics opens the possibilities for their future knowledge-based applications.

  7. Vinegar Metabolomics: An Explorative Study of Commercial Balsamic Vinegars Using Gas Chromatography-Mass Spectrometry

    Science.gov (United States)

    Pinu, Farhana R.; de Carvalho-Silva, Samuel; Trovatti Uetanabaro, Ana Paula; Villas-Boas, Silas G.

    2016-01-01

    Balsamic vinegar is a popular food condiment produced from cooked grape must by two successive fermentation (anaerobic and aerobic) processes. Although many studies have been performed to determine the composition of major metabolites, including sugars and aroma compounds, no study has been undertaken yet to characterize the comprehensive metabolite composition of balsamic vinegars. Here, we present the first metabolomics study of commercial balsamic vinegars by gas chromatography coupled to mass spectrometry (GC-MS). The combination of three GC-MS methods allowed us to detect >1500 features in vinegar samples, of which 123 metabolites were accurately identified, including 25 amino acids, 26 carboxylic acids, 13 sugars and sugar alcohols, four fatty acids, one vitamin, one tripeptide and over 47 aroma compounds. Moreover, we identified for the first time in vinegar five volatile metabolites: acetin, 2-methylpyrazine, 2-acetyl-1-pyroline, 4-anisidine and 1,3-diacetoxypropane. Therefore, we demonstrated the capability of metabolomics for detecting and identifying large number of metabolites and some of them could be used to distinguish vinegar samples based on their origin and potentially quality. PMID:27455339

  8. Metabolomic and Transcriptomic Comparison of Solid-State and Submerged Fermentation of Penicillium expansum KACC 40815.

    Directory of Open Access Journals (Sweden)

    Hyang Yeon Kim

    Full Text Available Penicillium spp. are known to harbor a wide array of secondary metabolites with cryptic bioactivities. However, the metabolomics of these species is not well-understood in terms of different fermentation models and conditions. The present study involved metabolomics profiling and transcriptomic analysis of Penicillium expansum 40815 under solid-state fermentation (SSF and submerged fermentation (SmF. Metabolite profiling was carried out using ultra-performance liquid chromatography quadruple time-of-flight mass spectrometry with multivariate analysis, followed by transcriptomic analyses of differentially expressed genes. In principal component analysis, the metabolite profiling data was studied under different experimental sets, including SSF and SmF. The significantly different metabolites such as polyketide metabolites (agonodepside B, rotiorin, verrucosidin, and ochrephilone and corresponding gene transcripts (polyketide synthase, aromatic prenyltransferase, and terpenoid synthase were primarily detected under SmF conditions. In contrast, the meroterpenoid compounds (andrastin A and C and their genes transcripts were exclusively detected under SSF conditions. We demonstrated that the metabolite production and its corresponding gene expression levels in P. expansum 40815 were significantly influenced by the varying growth parameters and the immediate environment. This study further provides a foundation to produce specific metabolites by regulating fermentation conditions.

  9. A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress.

    Science.gov (United States)

    Mahdavi, Vahideh; Farimani, Mahdi Moridi; Fathi, Fariba; Ghassempour, Alireza

    2015-06-01

    Diazinon insecticide is widely applied throughout rice (Oryza sativa L.) fields in Iran. However, concerns are now being raised about its potential adverse impacts on rice fields. In this study, a time-course metabolic change in rice plants was investigated after diazinon treatment using gas chromatography-mass spectrometry (GC-MS), and subsequently the statistical strategy of random forest (RF) was performed in order to find the stress-associated effects. According to the results, a wide range of metabolites were dynamically varied as a result of the plant response to diazinon such as biosynthesis and metabolism of sugars, amino acids, organic acids, and phenylpropanoids, all correlating with the exposure time. Plant response was involved in multiple metabolic pathways, most of which were correlated with the exposure time. In this study, RF was explored as a potential multivariate method for GC-MS analysis of metabolomics data of rice (O. sativa L.) plants under diazinon stress; more than 31 metabolites were quantitatively determined, and time-course metabolic response of the plant during different days after treatment was measured. Results demonstrated RF as a potential multivariate method for GC-MS analysis of changes in plant metabolome under insecticide stress.

  10. Expanding the Described Metabolome of the Marine Cyanobacterium Moorea producens JHB through Orthogonal Natural Products Workflows.

    Directory of Open Access Journals (Sweden)

    Paul D Boudreau

    Full Text Available Moorea producens JHB, a Jamaican strain of tropical filamentous marine cyanobacteria, has been extensively studied by traditional natural products techniques. These previous bioassay and structure guided isolations led to the discovery of two exciting classes of natural products, hectochlorin (1 and jamaicamides A (2 and B (3. In the current study, mass spectrometry-based 'molecular networking' was used to visualize the metabolome of Moorea producens JHB, and both guided and enhanced the isolation workflow, revealing additional metabolites in these compound classes. Further, we developed additional insight into the metabolic capabilities of this strain by genome sequencing analysis, which subsequently led to the isolation of a compound unrelated to the jamaicamide and hectochlorin families. Another approach involved stimulation of the biosynthesis of a minor jamaicamide metabolite by cultivation in modified media, and provided insights about the underlying biosynthetic machinery as well as preliminary structure-activity information within this structure class. This study demonstrated that these orthogonal approaches are complementary and enrich secondary metabolomic coverage even in an extensively studied bacterial strain.

  11. Optimized experimental workflow for tandem mass spectrometry molecular networking in metabolomics.

    Science.gov (United States)

    Olivon, Florent; Roussi, Fanny; Litaudon, Marc; Touboul, David

    2017-07-31

    New omics sciences generate massive amounts of data, requiring to be sorted, curated, and statistically analyzed by dedicated software. Data-dependent acquisition mode including inclusion and exclusion rules for tandem mass spectrometry is routinely used to perform such analyses. While acquisition parameters are well described for proteomics, no general rule is currently available to generate reliable metabolomic data for molecular networking analysis on the Global Natural Product Social Molecular Networking platform (GNPS). Following on from an exploration of key parameters influencing the quality of molecular networks, universal optimal acquisition conditions for metabolomic studies are suggested in the present paper. The benefit of data pre-clustering before initiating large datasets for GNPS analyses is also demonstrated. Moreover, an efficient workflow dedicated to Agilent Technologies instruments is described, making the dereplication process easier by unambiguously distinguishing isobaric isomers eluted at different retention times, annotating the molecular networks with chemical formulas, and giving access to semi-quantitative data. This specific workflow foreshadows future developments of the GNPS platform.

  12. Aromatic L-amino acid decarboxylase deficiency diagnosed by clinical metabolomic profiling of plasma.

    Science.gov (United States)

    Atwal, Paldeep S; Donti, Taraka R; Cardon, Aaron L; Bacino, C A; Sun, Qin; Emrick, L; Reid Sutton, V; Elsea, Sarah H

    2015-01-01

    Aromatic L-amino acid decarboxylase (AADC) deficiency is an inborn error of metabolism affecting the biosynthesis of serotonin, dopamine, and catecholamines. We report a case of AADC deficiency that was detected using the Global MAPS platform. This is a novel platform that allows for parallel clinical testing of hundreds of metabolites in a single plasma specimen. It uses a state-of-the-art mass spectrometry platform, and the resulting spectra are compared against a library of ~2500 metabolites. Our patient is now a 4 year old boy initially seen at 11 months of age for developmental delay and hypotonia. Multiple tests had not yielded a diagnosis until exome sequencing revealed compound heterozygous variants of uncertain significance (VUS), c.286G>A (p.G96R) and c.260C>T (p.P87L) in the DDC gene, causal for AADC deficiency. CSF neurotransmitter analysis confirmed the diagnosis with elevated 3-methoxytyrosine (3-O-methyldopa). Metabolomic profiling was performed on plasma and revealed marked elevation in 3-methoxytyrosine (Z-score +6.1) consistent with the diagnosis of AADC deficiency. These results demonstrate that the Global MAPS platform is able to diagnose AADC deficiency from plasma. In summary, we report a novel and less invasive approach to diagnose AADC deficiency using plasma metabolomic profiling.

  13. Metabolomic and Transcriptomic Comparison of Solid-State and Submerged Fermentation of Penicillium expansum KACC 40815.

    Science.gov (United States)

    Kim, Hyang Yeon; Heo, Do Yeon; Park, Hye Min; Singh, Digar; Lee, Choong Hwan

    2016-01-01

    Penicillium spp. are known to harbor a wide array of secondary metabolites with cryptic bioactivities. However, the metabolomics of these species is not well-understood in terms of different fermentation models and conditions. The present study involved metabolomics profiling and transcriptomic analysis of Penicillium expansum 40815 under solid-state fermentation (SSF) and submerged fermentation (SmF). Metabolite profiling was carried out using ultra-performance liquid chromatography quadruple time-of-flight mass spectrometry with multivariate analysis, followed by transcriptomic analyses of differentially expressed genes. In principal component analysis, the metabolite profiling data was studied under different experimental sets, including SSF and SmF. The significantly different metabolites such as polyketide metabolites (agonodepside B, rotiorin, verrucosidin, and ochrephilone) and corresponding gene transcripts (polyketide synthase, aromatic prenyltransferase, and terpenoid synthase) were primarily detected under SmF conditions. In contrast, the meroterpenoid compounds (andrastin A and C) and their genes transcripts were exclusively detected under SSF conditions. We demonstrated that the metabolite production and its corresponding gene expression levels in P. expansum 40815 were significantly influenced by the varying growth parameters and the immediate environment. This study further provides a foundation to produce specific metabolites by regulating fermentation conditions.

  14. Metabolomics and proteomics reveal impacts of chemically mediated competition on marine plankton

    Science.gov (United States)

    Poulson-Ellestad, Kelsey L.; Jones, Christina M.; Roy, Jessie; Viant, Mark R.; Fernández, Facundo M.; Kubanek, Julia; Nunn, Brook L.

    2014-01-01

    Competition is a major force structuring marine planktonic communities. The release of compounds that inhibit competitors, a process known as allelopathy, may play a role in the maintenance of large blooms of the red-tide dinoflagellate Karenia brevis, which produces potent neurotoxins that negatively impact coastal marine ecosystems. K. brevis is variably allelopathic to multiple competitors, typically causing sublethal suppression of growth. We used metabolomic and proteomic analyses to investigate the role of chemically mediated ecological interactions between K. brevis and two diatom competitors, Asterionellopsis glacialis and Thalassiosira pseudonana. The impact of K. brevis allelopathy on competitor physiology was reflected in the metabolomes and expressed proteomes of both diatoms, although the diatom that co-occurs with K. brevis blooms (A. glacialis) exhibited more robust metabolism in response to K. brevis. The observed partial resistance of A. glacialis to allelopathy may be a result of its frequent exposure to K. brevis blooms in the Gulf of Mexico. For the more sensitive diatom, T. pseudonana, which may not have had opportunity to evolve resistance to K. brevis, allelopathy disrupted energy metabolism and impeded cellular protection mechanisms including altered cell membrane components, inhibited osmoregulation, and increased oxidative stress. Allelopathic compounds appear to target multiple physiological pathways in sensitive competitors, demonstrating that chemical cues in the plankton have the potential to alter large-scale ecosystem processes including primary production and nutrient cycling. PMID:24889616

  15. Diagnosis of adenylosuccinate lyase deficiency by metabolomic profiling in plasma reveals a phenotypic spectrum

    Directory of Open Access Journals (Sweden)

    Taraka R. Donti

    2016-09-01

    Full Text Available Adenylosuccinate lyase (ADSL deficiency is a rare autosomal recessive neurometabolic disorder that presents with a broad-spectrum of neurological and physiological symptoms. The ADSL gene produces an enzyme with binary molecular roles in de novo purine synthesis and purine nucleotide recycling. The biochemical phenotype of ADSL deficiency, accumulation of SAICAr and succinyladenosine (S-Ado in biofluids of affected individuals, serves as the traditional target for diagnosis with targeted quantitative urine purine analysis employed as the predominate method of detection. In this study, we report the diagnosis of ADSL deficiency using an alternative method, untargeted metabolomic profiling, an analytical scheme capable of generating semi-quantitative z-score values for over 1000 unique compounds in a single analysis of a specimen. Using this method to analyze plasma, we diagnosed ADSL deficiency in four patients and confirmed these findings with targeted quantitative biochemical analysis and molecular genetic testing. ADSL deficiency is part of a large a group of neurometabolic disorders, with a wide range of severity and sharing a broad differential diagnosis. This phenotypic similarity among these many inborn errors of metabolism (IEMs has classically stood as a hurdle in their initial diagnosis and subsequent treatment. The findings presented here demonstrate the clinical utility of metabolomic profiling in the diagnosis of ADSL deficiency and highlights the potential of this technology in the diagnostic evaluation of individuals with neurologic phenotypes.

  16. A Metabolomics Approach to Stratify Patients Diagnosed with Diabetes Mellitus into Excess or Deficiency Syndromes

    Directory of Open Access Journals (Sweden)

    Tao Wu

    2015-01-01

    Full Text Available The prevalence of type 2 diabetes continuously increases globally. The traditional Chinese medicine (TCM can stratify the diabetic patients based on their different TCM syndromes and, thus, allow a personalized treatment. Metabolomics is able to provide metabolite biomarkers for disease subtypes. In this study, we applied a metabolomics approach using an ultraperformance liquid chromatography (UPLC coupled with quadruple-time-of-flight (QTOF mass spectrometry system to characterize the metabolic alterations of different TCM syndromes including excess and deficiency in patients diagnosed with diabetes mellitus (DM. We obtained a snapshot of the distinct metabolic changes of DM patients with different TCM syndromes. DM patients with excess syndrome have higher serum 2-indolecarboxylic acid, hypotaurine, pipecolic acid, and progesterone in comparison to those patients with deficiency syndrome. The excess patients have more oxidative stress as demonstrated by unique metabolite signatures than the deficiency subjects. The results provide an improved understanding of the systemic alteration of metabolites in different syndromes of DM. The identified serum metabolites may be of clinical relevance for subtyping of diabetic patients, leading to a personalized DM treatment.

  17. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Science.gov (United States)

    Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

    2013-11-01

    This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

  18. A neural signature of hierarchical reinforcement learning.

    Science.gov (United States)

    Ribas-Fernandes, José J F; Solway, Alec; Diuk, Carlos; McGuire, Joseph T; Barto, Andrew G; Niv, Yael; Botvinick, Matthew M

    2011-07-28

    Human behavior displays hierarchical structure: simple actions cohere into subtask sequences, which work together to accomplish overall task goals. Although the neural substrates of such hierarchy have been the target of increasing research, they remain poorly understood. We propose that the computations supporting hierarchical behavior may relate to those in hierarchical reinforcement learning (HRL), a machine-learning framework that extends reinforcement-learning mechanisms into hierarchical domains. To test this, we leveraged a distinctive prediction arising from HRL. In ordinary reinforcement learning, reward prediction errors are computed when there is an unanticipated change in the prospects for accomplishing overall task goals. HRL entails that prediction errors should also occur in relation to task subgoals. In three neuroimaging studies we observed neural responses consistent with such subgoal-related reward prediction errors, within structures previously implicated in reinforcement learning. The results reported support the relevance of HRL to the neural processes underlying hierarchical behavior.

  19. Hierarchical Identity-Based Lossy Trapdoor Functions

    CERN Document Server

    Escala, Alex; Libert, Benoit; Rafols, Carla

    2012-01-01

    Lossy trapdoor functions, introduced by Peikert and Waters (STOC'08), have received a lot of attention in the last years, because of their wide range of applications in theoretical cryptography. The notion has been recently extended to the identity-based scenario by Bellare et al. (Eurocrypt'12). We provide one more step in this direction, by considering the notion of hierarchical identity-based lossy trapdoor functions (HIB-LTDFs). Hierarchical identity-based cryptography generalizes identitybased cryptography in the sense that identities are organized in a hierarchical way; a parent identity has more power than its descendants, because it can generate valid secret keys for them. Hierarchical identity-based cryptography has been proved very useful both for practical applications and to establish theoretical relations with other cryptographic primitives. In order to realize HIB-LTDFs, we first build a weakly secure hierarchical predicate encryption scheme. This scheme, which may be of independent interest, is...

  20. Hierarchically nanostructured materials for sustainable environmental applications

    Science.gov (United States)

    Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

    2013-01-01

    This review presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions, and multiple functionalities toward water remediation, biosensing, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing, and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology. PMID:24790946

  1. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Directory of Open Access Journals (Sweden)

    Zheng eRen

    2013-11-01

    Full Text Available This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

  2. Hierarchical characterization procedures for dimensional metrology

    Science.gov (United States)

    MacKinnon, David; Beraldin, Jean-Angelo; Cournoyer, Luc; Carrier, Benjamin

    2011-03-01

    We present a series of dimensional metrology procedures for evaluating the geometrical performance of a 3D imaging system that have either been designed or modified from existing procedures to ensure, where possible, statistical traceability of each characteristic value from the certified reference surface to the certifying laboratory. Because there are currently no internationally-accepted standards for characterizing 3D imaging systems, these procedures have been designed to avoid using characteristic values provided by the vendors of 3D imaging systems. For this paper, we focus only on characteristics related to geometric surface properties, dividing them into surface form precision and surface fit trueness. These characteristics have been selected to be familiar to operators of 3D imaging systems that use Geometrical Dimensioning and Tolerancing (GD&T). The procedures for generating characteristic values would form the basis of either a volumetric or application-specific analysis of the characteristic profile of a 3D imaging system. We use a hierarchical approach in which each procedure builds on either certified reference values or previously-generated characteristic values. Starting from one of three classes of surface forms, we demonstrate how procedures for quantifying for flatness, roundness, angularity, diameter error, angle error, sphere-spacing error, and unidirectional and bidirectional plane-spacing error are built upon each other. We demonstrate how these procedures can be used as part of a process for characterizing the geometrical performance of a 3D imaging system.

  3. Automated LC-HRMS(/MS) approach for the annotation of fragment ions derived from stable isotope labeling-assisted untargeted metabolomics.

    Science.gov (United States)

    Neumann, Nora K N; Lehner, Sylvia M; Kluger, Bernhard; Bueschl, Christoph; Sedelmaier, Karoline; Lemmens, Marc; Krska, Rudolf; Schuhmacher, Rainer

    2014-08-05

    Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native (12)C- and uniformly (13)C (U-(13)C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-(13)C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research.

  4. A Metadata description of the data in "A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human."

    Directory of Open Access Journals (Sweden)

    Griffin Julian L

    2011-07-01

    Full Text Available Abstract Background Metabolomics is a rapidly developing functional genomic tool that has a wide range of applications in diverse fields in biology and medicine. However, unlike transcriptomics and proteomics there is currently no central repository for the depositing of data despite efforts by the Metabolomics Standard Initiative (MSI to develop a standardised description of a metabolomic experiment. Findings In this manuscript we describe how the MSI description has been applied to a published dataset involving the identification of cross-species metabolic biomarkers associated with type II diabetes. The study describes sample collection of urine from mice, rats and human volunteers, and the subsequent acquisition of data by high resolution 1H NMR spectroscopy. The metadata is described to demonstrate how the MSI descriptions could be applied in a manuscript and the spectra have also been made available for the mouse and rat studies to allow others to process the data. Conclusions The intention of this manuscript is to stimulate discussion as to whether the MSI description is sufficient to describe the metadata associated with metabolomic experiments and encourage others to make their data available to other researchers.

  5. Tailored sensitivity reduction improves pattern recognition and information recovery with a higher tolerance to varied sample concentration for targeted urinary metabolomics.

    Science.gov (United States)

    Yan, Zhixiang; Yan, Ru

    2016-04-22

    Variation in total metabolite concentration among different samples has been a major challenge for urinary metabolomics. Here we investigated the potential of tailored sensitivity reduction of high abundance metabolites for improved targeted urinary metabolomics. Two levels of sensitivity reduction of the 21 predominant urinary metabolites were assessed by employing less sensitive transition or collision energy with level 1 (reduced 1) and 2 (reduced 2) exhibiting 30-90% and 2-20% of the optimal sensitivity, respectively. Five postacquisition normalization methods were compared including no normalization, probabilistic quotient normalization, and normalization to sample median, creatinine intensity, and total intensity. Normalization to total intensity with reduced 2 gave the best pattern recognition and information recovery with a higher tolerance to varied sample concentration. Pareto scaling could improve the performance of tailored sensitivity reduction (reduced 2) for targeted urinary metabolomics while data transformation and autoscaling were susceptible to varied sample concentration. Using controlled spike-in experiments, we demonstrated that tailored sensitivity reduction revealed more differentially expressed markers with higher accuracy than did the conventional optimal sensitivity. This was particularly true when the differences between the sample groups are small. This work also served as an introductory guideline for handling targeted metabolomics data using the open-source software MetaboAnalyst.

  6. Metabolomics Analysis of Health Functions of Physalis Pubescens L. using by Ultra-performance Liquid Chromatography/Electrospray Ionization Quadruple Time-of-Flight Mass Spectrometry

    Institute of Scientific and Technical Information of China (English)

    Hang Chu; Hui Sun; Guang-Li Yan; Ai-Hua Zhang; Chang Liu; Hui Dong; Xiang-Cai Meng; Xi-Jun Wang

    2015-01-01

    Herbal medicines may benefit from metabolomics studies, and applying metabolomics may provide answers about which herbal interventions may be effective for individuals, which metabolic processes are triggered, and the subsequent chemical pathways of activity. Physalis pubescens L (PPL) is an herbal fruit for one year living plant and has been developed into healthy function’s food. However, the mechanisms of health functions are still unclear. To comprehensively and holistically assess its anti-fatigue and antioxidant effects, a novel integrative metabolomics approach was applied. In this study, we present metabolomics analysis applying ultra performance liquid chromatography coupled to quadrupole with time-of-flight mass spectrometry (UPLC-Q/TOF-MS) to determine metabolite alterations after oral administration PPL to rats. Fifteen metabolites in urine were identified as potential biomarkers. Pattern analysis of the UPLC-Q/TOF-MS data disclosed that PPL could relieve fatigue rats by ameliorating the disturbance in amino acids metabolism and energy metabolism, alleviating the oxidative stress from reactive oxygen species and the inflammatory damage, and recovering the destructed regulation. Based on these results, we demonstrated that PPL is a promising source of natural anti-fatigue and antioxidants material for use in functional foods and medicines.

  7. The potential of metabolomic analysis techniques for the characterisation of α1-adrenergic receptors in cultured N1E-115 mouse neuroblastoma cells.

    Science.gov (United States)

    Wenner, Maria I; Maker, Garth L; Dawson, Linda F; Drummond, Peter D; Mullaney, Ian

    2016-08-01

    Several studies of neuropathic pain have linked abnormal adrenergic signalling to the development and maintenance of pain, although the mechanisms underlying this are not yet fully understood. Metabolomic analysis is a technique that can be used to give a snapshot of biochemical status, and can aid in the identification of the mechanisms behind pathological changes identified in cells, tissues and biological fluids. This study aimed to use gas chromatography-mass spectrometry-based metabolomic profiling in combination with reverse transcriptase-polymerase chain reaction and immunocytochemistry to identify functional α1-adrenergic receptors on cultured N1E-115 mouse neuroblastoma cells. The study was able to confirm the presence of mRNA for the α1D subtype, as well as protein expression of the α1-adrenergic receptor. Furthermore, metabolomic data revealed changes to the metabolite profile of cells when exposed to adrenergic pharmacological intervention. Agonist treatment with phenylephrine hydrochloride (10 µM) resulted in altered levels of several metabolites including myo-inositol, glucose, fructose, alanine, leucine, phenylalanine, valine, and n-acetylglutamic acid. Many of the changes observed in N1E-115 cells by agonist treatment were modulated by additional antagonist treatment (prazosin hydrochloride, 100 µM). A number of these changes reflected what is known about the biochemistry of α1-adrenergic receptor activation. This preliminary study therefore demonstrates the potential of metabolomic profiling to confirm the presence of functional receptors on cultured cells.

  8. Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

    DEFF Research Database (Denmark)

    He, W.; Min, D.D.; Zhang, X.D.

    2014-01-01

    Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...

  9. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    CERN Document Server

    Perotti, Juan Ignacio; Caldarelli, Guido

    2015-01-01

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\\it hierarchical mutual information}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\\it normalized} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies, and on the hierarchical ...

  10. Independent component analysis in non-hypothesis driven metabolomics

    DEFF Research Database (Denmark)

    Li, Xiang; Hansen, Jakob; Zhao, Xinjie

    2012-01-01

    In a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS). Since independent component analysis (ICA) does not need a priori...

  11. Emerging Applications of Metabolomics in Studying Chemopreventive Phytochemicals

    OpenAIRE

    2013-01-01

    Phytochemicals from diet and herbal medicines are under intensive investigation for their potential use as chemopreventive agents to block and suppress carcinogenesis. Chemical diversity of phytochemicals, together with complex metabolic interactions between phytochemicals and biological system, can overwhelm the capacity of traditional analytical platforms, and thus pose major challenges in studying chemopreventive phytochemicals. Recent progresses in metabolomics have transformed it to beco...

  12. Liver metabolomics analysis associated with feed efficiency on steers

    Science.gov (United States)

    The liver represents a metabolic crossroad regulating and modulating nutrients available from digestive tract absorption to the peripheral tissues. To identify potential differences in liver function that lead to differences in feed efficiency, liver metabolomic analysis was conducted using ultra-pe...

  13. Advances in metabolomic applications in plant genetics and breeding

    Science.gov (United States)

    Metabolomics is a systems biology discipline wherein abundances of endogenous metabolites from biological samples are identified and quantitatively measured across a large range of metabolites and/or a large number of samples. Since all developmental, physiological and response to the environment ph...

  14. Metabolomic Biomarker Identification in Presence of Outliers and Missing Values.

    Science.gov (United States)

    Kumar, Nishith; Hoque, Md Aminul; Shahjaman, Md; Islam, S M Shahinul; Mollah, Md Nurul Haque

    2017-01-01

    Metabolomics is the sophisticated and high-throughput technology based on the entire set of metabolites which is known as the connector between genotypes and phenotypes. For any phenotypic changes, potential metabolite (biomarker) identification is very important because it provides diagnostic as well as prognostic markers and can help to develop new biomolecular therapy. Biomarker identification from metabolomics data analysis is hampered by the use of high-throughput technology that provides high dimensional data matrix which contains missing values as well as outliers. However, missing value imputation and outliers handling techniques play important role in identifying biomarker correctly. Although several missing value imputation techniques are available, outliers deteriorate the accuracy of imputation as well as the accuracy of biomarker identification. Therefore, in this paper we have proposed a new biomarker identification technique combining the groupwise robust singular value decomposition, t-test, and fold-change approach that can identify biomarkers more correctly from metabolomics dataset. We have also compared the performance of the proposed technique with those of other traditional techniques for biomarker identification using both simulated and real data analysis in absence and presence of outliers. Using our proposed method in hepatocellular carcinoma (HCC) dataset, we have also identified the four upregulated and two downregulated metabolites as potential metabolomic biomarkers for HCC disease.

  15. Nuclear magnetic resonance metabolomics of iron deficiency in soybean leaves

    Science.gov (United States)

    Iron (Fe) deficiency is an important agricultural concern leading to lower yields and crop quality. A better understanding of the condition, at the metabolome level, could contribute to the design of strategies to ameliorate Fe deficiency problems. Fe-sufficient and Fe-deficient soybean leaf extract...

  16. The effects of gliadin on urine metabolome in mice

    DEFF Research Database (Denmark)

    Roager, Henrik Munch; Zhang, Li; Frandsen, Henrik Lauritz

    Gliadin, a proline-rich protein of gluten, is thought to modulate the gut microbiota and affect the intestinal permeability and immune system. However, little is known about the long-term effects of gliadin on the host and microbial metabolism. To study this, we compared the urine metabolome of two...

  17. Leakage-free rapid quenching technique for yeast metabolomics

    NARCIS (Netherlands)

    Canelas, A.B.; Ras, C.; Ten Pierick, A.; Van Dam, J.C.; Heijnen, J.J.; Van Gulik, W.M.

    2008-01-01

    Accurate determination of intracellular metabolite levels requires reliable, reproducible techniques for sampling and sample treatment. Quenching in 60% (v/v) methanol at −40°C is currently the standard method for sub-second arrest of metabolic activity in microbial metabolomics but there have been

  18. Integration of metabolome data with metabolic networks reveals reporter reactions

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen;

    2006-01-01

    Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...

  19. Metabolomics: Insulin Resistance and Type 2 Diabetes Mellitus

    Science.gov (United States)

    Type 2 diabetes mellitus (T2DM) develops over many years, providing an opportunity to consider early prognostic tools that guide interventions to thwart disease. Advancements in analytical chemistry enable quantitation of hundreds of metabolites in biofluids and tissues (metabolomics), providing in...

  20. Metabolomics approaches and applications in prostate cancer research.

    Science.gov (United States)

    Zhang, Aihua; Yan, Guangli; Han, Ying; Wang, Xijun

    2014-09-01

    Prostate cancer is a leading cause of cancer deaths in men worldwide. Although prostate-specific antigen (PSA) has been extensively used as a serum biomarker to detect prostate cancer, this screening method has suffered from a lack of specificities and sensitivities. The successful prevention and treatment of prostate cancer relies on the early and accurate detection of the disease; therefore, more sensitive biomarkers are urgently needed. Prostate has long been known to exhibit unique metabolite profiles, fortunately, metabolomics, the study of all metabolites produced in the body, can be considered most closely related to a patient's phenotype. It may provide clinically useful biomarkers applied toward identifying metabolic alterations in prostate cancer and has introduced new insights into the pathology of prostate cancer. This advanced bioanalytic method may now open door for diagnostics. Metabolomics has a great and largely potential in the field of disease, and the analysis of the cancer metabolome to identify novel biomarkers and targets can now be undertaken in many research laboratories. In this review, we take a closer look at the metabolomics in the field of prostate cancer and highlight the interesting publications as references for the interested reader.

  1. Method validation strategies involved in non-targeted metabolomics.

    Science.gov (United States)

    Naz, Shama; Vallejo, Maria; García, Antonia; Barbas, Coral

    2014-08-01

    Non-targeted metabolomics is the hypothesis generating, global unbiased analysis of all the small-molecule metabolites present within a biological system, under a given set of conditions. It includes several common steps such as selection of biological samples, sample pre-treatment, analytical conditions set-up, acquiring data, data analysis by chemometrics, database search and biological interpretation. Non-targeted metabolomics offers the potential for a holistic approach in the area of biomedical research in order to improve disease diagnosis and to understand its pathological mechanisms. Various analytical methods have been developed based on nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) coupled with different separation techniques. The key points in any analytical method development are the validation of every step to get a reliable and reproducible result and non-targeted metabolomics is not beyond this criteria, although analytical challenges are completely new and different to target methods. This review paper will describe the available validation strategies that are being used and as well will recommend some steps to consider during a non-targeted metabolomics analytical method development. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Metabolomics in diagnosis and biomarker discovery of colorectal cancer.

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Han, Ying; Wang, Xijun

    2014-04-01

    Colorectal cancer (CRC), a major public health concern, is the second leading cause of cancer death in developed countries. There is a need for better preventive strategies to improve the patient outcome that is substantially influenced by cancer stage at the time of diagnosis. Patients with early stage colorectal have a significant higher 5-year survival rates compared to patients diagnosed at late stage. Although traditional colonoscopy remains the effective means to diagnose CRC, this approach generally suffers from poor patient compliance. Thus, it is important to develop more effective methods for early diagnosis of this disease process, also there is an urgent need for biomarkers to diagnose CRC, assess disease severity, and prognosticate course. Increasing availability of high-throughput methodologies open up new possibilities for screening new potential candidates for identifying biomarkers. Fortunately, metabolomics, the study of all metabolites produced in the body, considered most closely related to a patient's phenotype, can provide clinically useful biomarkers applied in CRC, and may now open new avenues for diagnostics. It has a largely untapped potential in the field of oncology, through the analysis of the cancer metabolome to identify marker metabolites defined here as surrogate indicators of physiological or pathophysiological states. In this review we take a closer look at the metabolomics used within the field of colorectal cancer. Further, we highlight the most interesting metabolomics publications and discuss these in detail; additional studies are mentioned as a reference for the interested reader. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  3. Improved drug therapy: triangulating phenomics with genomics and metabolomics

    Science.gov (United States)

    2014-01-01

    Embracing the complexity of biological systems has a greater likelihood to improve prediction of clinical drug response. Here we discuss limitations of a singular focus on genomics, epigenomics, proteomics, transcriptomics, metabolomics, or phenomics—highlighting the strengths and weaknesses of each individual technique. In contrast, ‘systems biology’ is proposed to allow clinicians and scientists to extract benefits from each technique, while limiting associated weaknesses by supplementing with other techniques when appropriate. Perfect predictive modeling is not possible, whereas modeling of intertwined phenomic responses using genomic stratification with metabolomic modifications may greatly improve predictive values for drug therapy. We thus propose a novel-integrated approach to personalized medicine that begins with phenomic data, is stratified by genomics, and ultimately refined by metabolomic pathway data. Whereas perfect prediction of efficacy and safety of drug therapy is not possible, improvements can be achieved by embracing the complexity of the biological system. Starting with phenomics, the combination of linking metabolomics to identify common biologic pathways and then stratifying by genomic architecture, might increase predictive values. This systems biology approach has the potential, in specific subsets of patients, to avoid drug therapy that will be either ineffective or unsafe. PMID:25181945

  4. The Muscle Metabolome Differs between Healthy and Frail Older Adults

    NARCIS (Netherlands)

    Fazelzadeh, P.; Hangelbroek, R.W.J.; Tieland, M.; de Groot, C.P.G.M.; Verdijk, L.B.; van Loon, L.J.C.; Smilde, A.K.; Alves, R.D.A.M.; Vervoort, J.; Müller, M.; van Duynhoven, J.P.M.; Boekschoten, M.V.

    2016-01-01

    Populations around the world are aging rapidly. Age-related loss of physiological functions negatively affects quality of life. A major contributor to the frailty syndrome of aging is loss of skeletal muscle. In this study we assessed the skeletal muscle biopsy metabolome of healthy young, healthy

  5. Metabolomic approach for improving ethanol stress tolerance in Saccharomyces cerevisiae.

    Science.gov (United States)

    Ohta, Erika; Nakayama, Yasumune; Mukai, Yukio; Bamba, Takeshi; Fukusaki, Eiichiro

    2016-04-01

    The budding yeast Saccharomyces cerevisiae is widely used for brewing and ethanol production. The ethanol sensitivity of yeast cells is still a serious problem during ethanol fermentation, and a variety of genetic approaches (e.g., random mutant screening under selective pressure of ethanol) have been developed to improve ethanol tolerance. In this study, we developed a strategy for improving ethanol tolerance of yeast cells based on metabolomics as a high-resolution quantitative phenotypic analysis. We performed gas chromatography-mass spectrometry analysis to identify and quantify 36 compounds on 14 mutant strains including knockout strains for transcription factor and metabolic enzyme genes. A strong relation between metabolome of these mutants and their ethanol tolerance was observed. Data mining of the metabolomic analysis showed that several compounds (such as trehalose, valine, inositol and proline) contributed highly to ethanol tolerance. Our approach successfully detected well-known ethanol stress related metabolites such as trehalose and proline thus, to further prove our strategy, we focused on valine and inositol as the most promising target metabolites in our study. Our results show that simultaneous deletion of LEU4 and LEU9 (leading to accumulation of valine) or INM1 and INM2 (leading to reduction of inositol) significantly enhanced ethanol tolerance. This study shows the potential of the metabolomic approach to identify target genes for strain improvement of S. cerevisiae with higher ethanol tolerance. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  6. Metabolomic Characterization of the Salt Stress Response in Streptomyces coelicolor

    NARCIS (Netherlands)

    Kol, Stefan; Merlo, M. Elena; Scheltema, Richard A.; de Vries, Marcel; Vonk, Roel J.; Kikkert, Niels A.; Dijkhuizen, Lubbert; Breitling, Rainer; Takano, Eriko

    2010-01-01

    The humicolous actinomycete Streptomyces coelicolor routinely adapts to a wide variety of habitats and rapidly changing environments. Upon salt stress, the organism is also known to increase the levels of various compatible solutes. Here we report the results of the first high-resolution metabolomic

  7. Probabilistic assignment of formulas to mass peaks in metabolomics experiments

    NARCIS (Netherlands)

    Rogers, Simon; Scheltema, Richard A.; Girolami, Mark; Breitling, Rainer

    2009-01-01

    Motivation: High-accuracy mass spectrometry is a popular technology for high-throughput measurements of cellular metabolites (metabolomics). One of the major challenges is the correct identification of the observed mass peaks, including the assignment of their empirical formula, based on the

  8. Genetic algorithm based two-mode clustering of metabolomics data

    NARCIS (Netherlands)

    Hageman, J.A.; Berg, R.A. van den; Westerhuis, J.A.; Werf, M.J. van der; Smilde, A.K.

    2008-01-01

    Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering metho

  9. Genetic and metabolomic approaches for coronary heart disease risk prediction

    NARCIS (Netherlands)

    Vaarhorst, Anika Antoinette Maria

    2014-01-01

    The prediction of coronary heart disease (CHD) risk is currently based on traditional risk factors (TRFs) like age, sex, lipid levels, blood pressure. Here we investigated, using the CAREMA cohort, whether this prediction can potentially be improved by applying a metabolomics approach and by includi

  10. Probabilistic assignment of formulas to mass peaks in metabolomics experiments

    NARCIS (Netherlands)

    Rogers, Simon; Scheltema, Richard A.; Girolami, Mark; Breitling, Rainer

    2009-01-01

    Motivation: High-accuracy mass spectrometry is a popular technology for high-throughput measurements of cellular metabolites (metabolomics). One of the major challenges is the correct identification of the observed mass peaks, including the assignment of their empirical formula, based on the measure

  11. Alterations of red blood cell metabolome in overhydrated hereditary stomatocytosis.

    NARCIS (Netherlands)

    Darghouth, D.; Koehl, B.; Heilier, J.F.; Madalinski, G.; Bovee, P.H.; Bosman, G.J.C.G.M.; Delaunay, J.; Junot, C.; Romeo, P.H.

    2011-01-01

    Overhydrated hereditary stomatocytosis, clinically characterized by hemolytic anemia, is a rare disorder of the erythrocyte membrane permeability to monovalent cations, associated with mutations in the Rh-associated glycoprotein gene. We assessed the red blood cell metabolome of 4 patients with this

  12. The muscle metabolome differs between healthy and frail older adults

    NARCIS (Netherlands)

    Fazelzadeh, P.; Hangelbroek, R.W.J.; Tieland, C.A.B.; Groot, de C.P.G.M.; Verdijk, L.; Loon, van L.J.C.; Smilde, A.K.; Alves Rolo, Rodrigo; Vervoort, J.J.M.; Müller, M.R.; Duynhoven, van J.P.M.; Boekschoten, M.V.

    2016-01-01

    Populations around the world are aging rapidly. Age-related loss of physiological functions negatively affects quality of life. A major contributor to the frailty syndrome of aging is loss of skeletal muscle. In this study we assessed the skeletal muscle biopsy metabolome of healthy young, healthy o

  13. Metabolomics-driven nutraceutical evaluation of diverse green tea cultivars.

    Directory of Open Access Journals (Sweden)

    Yoshinori Fujimura

    Full Text Available BACKGROUND: Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity of diverse Japanese green tea cultivars. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC in human umbilical vein endothelial cells (HUVECs. This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6 and Sunrouge (SR strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS. Multivariate statistical analyses, principal component analysis (PCA and orthogonal partial least-squares-discriminant analysis (OPLS-DA, revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive

  14. Distinct urine metabolome after Asian ginseng and American ginseng intervention based on GC-MS metabolomics approach

    Science.gov (United States)

    Yang, Liu; Yu, Qing-Tao; Ge, Ya-Zhong; Zhang, Wen-Song; Fan, Yong; Ma, Chung-Wah; Liu, Qun; Qi, Lian-Wen

    2016-01-01

    Ginseng occupies a prominent position in the list of best-selling natural products worldwide. Asian ginseng (Panax ginseng) and American ginseng (Panax quinquefolius) show different properties and medicinal applications in pharmacology, even though the main active constituents of them are both thought to be ginsenosides. Metabolomics is a promising method to profile entire endogenous metabolites and monitor their fluctuations related to exogenous stimulus. Herein, an untargeted metabolomics approach was applied to study the overall urine metabolic differences between Asian ginseng and American ginseng in mice. Metabolomics analyses were performed using gas chromatography-mass spectrometry (GC-MS) together with multivariate statistical data analysis. A total of 21 metabolites related to D-glutamine and D-glutamate metabolism, glutathione metabolism, TCA cycle and glyoxylate and dicarboxylate metabolism, differed significantly under the Asian ginseng treatment; 34 metabolites mainly associated with glyoxylate and dicarboxylate metabolism, TCA cycle and taurine and hypotaurine metabolism, were significantly altered after American ginseng treatment. Urinary metabolomics reveal that Asian ginseng and American ginseng can benefit organism physiological and biological functions via regulating multiple metabolic pathways. The important pathways identified from Asian ginseng and American ginseng can also help to explore new therapeutic effects or action targets so as to broad application of these two ginsengs. PMID:27991533

  15. Nonlinear robust hierarchical control for nonlinear uncertain systems

    Directory of Open Access Journals (Sweden)

    Leonessa Alexander

    1999-01-01

    Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.

  16. Disturbance observer based hierarchical control of coaxial-rotor UAV.

    Science.gov (United States)

    Mokhtari, M Rida; Cherki, Brahim; Braham, Amal Choukchou

    2017-03-01

    This paper propose an hierarchical controller based on a new disturbance observer with finite time convergence (FTDO) to solve the path tracking of a small coaxial-rotor-typs Unmanned Aerial Vehicles (UAVs) despite of unknown aerodynamic efforts. The hierarchical control technique is used to separate the flight control problem into an inner loop that controls attitude and an outer loop that controls the thrust force acting on the vehicle. The new disturbance observer with finite time convergence is intergated to online estimate the unknown uncertainties and disturbances and to actively compensate them in finite time.The analysis further extends to the design of a control law that takes the disturbance estimation procedure into account. Numerical simulations are carried out to demonstrate the efficiency of the proposed control strategy.

  17. Hierarchically porous carbon nanosheets from waste coffee grounds for supercapacitors.

    Science.gov (United States)

    Yun, Young Soo; Park, Min Hong; Hong, Sung Ju; Lee, Min Eui; Park, Yung Woo; Jin, Hyoung-Joon

    2015-02-18

    The nanostructure design of porous carbon-based electrode materials is key to improving the electrochemical performance of supercapacitors. In this study, hierarchically porous carbon nanosheets (HP-CNSs) were fabricated using waste coffee grounds by in situ carbonization and activation processes using KOH. Despite the simple synthesis process, the HP-CNSs had a high aspect ratio nanostructure (∼20 nm thickness to several micrometers in lateral size), a high specific surface area of 1945.7 m(2) g(-1), numerous heteroatoms, and good electrical transport properties, as well as hierarchically porous characteristics (0.5-10 nm in size). HP-CNS-based supercapacitors showed a specific energy of 35.4 Wh kg(-1) at 11250 W kg(-1) and of 23 Wh kg(-1) for a 3 s charge/discharge current rate corresponding to a specific power of 30000 W kg(-1). Additionally, the HP-CNS supercapacitors demonstrated good cyclic performance over 5000 cycles.

  18. Optimization of Hierarchical Modulation for Use of Scalable Media

    Directory of Open Access Journals (Sweden)

    Heneghan Conor

    2010-01-01

    Full Text Available This paper studies the Hierarchical Modulation, a transmission strategy of the approaching scalable multimedia over frequency-selective fading channel for improving the perceptible quality. An optimization strategy for Hierarchical Modulation and convolutional encoding, which can achieve the target bit error rates with minimum global signal-to-noise ratio in a single-user scenario, is suggested. This strategy allows applications to make a free choice of relationship between Higher Priority (HP and Lower Priority (LP stream delivery. The similar optimization can be used in multiuser scenario. An image transport task and a transport task of an H.264/MPEG4 AVC video embedding both QVGA and VGA resolutions are simulated as the implementation example of this optimization strategy, and demonstrate savings in SNR and improvement in Peak Signal-to-Noise Ratio (PSNR for the particular examples shown.

  19. Inborn Errors of Metabolism: the metabolome is our world. Presidential address for the 11th International Congress of Inborn Errors of Metabolism (ICIEM).

    Science.gov (United States)

    McCabe, Edward R B

    2010-05-01

    Thank you for honoring me by allowing me to serve as president of the 11th International Congress of Inborn Errors of Metabolism (ICIEM). The science brought by the IEM community to the Congress was quite impressive and demonstrated the quality of research within this community. In this address, I will consider briefly the history of IEMs to determine how we have arrived where we are, and will spend more time ascertaining our place in the current biomedical community and our role in determining the future of personalized medicine. In the 1950s-1970s new tools were added to expand our ability to interrogate the metabolome and the result was an explosive increase in the number of IEMs. This set the stage for expanded newborn screening (NBS) by tandem mass spectrometry (MS/MS) to identify these patients and to intervene pre-symptomatically. The complexity of the metabolome has led us to utilize the mathematical algorithms of systems biology to reduce high dimensionality data to low dimensionality output. However, the metabolome does not exist in isolation and we must learn how to integrate the metabolome with other xomics. The metabolome is our world and the IEM community has much to share with the broader xomics communities by integrating what we have learned with the other xomics communities. They are seeking access to the metabolome as a closer measure of phenotype, and we are already extremely comfortable and competent in the metabolomic space. But we should not be insular in our occupation of this space. NBS should be the model for personalized medicine, because it is already functioning as testing system for predictive, preventive and personalized care. We have been working in the area of NBS for nearly a half century and have many lessons learned that will be valuable to the practitioners of personalized medicine - lessons that they should not have to rediscover. We must embrace the international IEM community to meet population trends and to improve the care

  20. Hierarchically structured, nitrogen-doped carbon membranes

    KAUST Repository

    Wang, Hong

    2017-08-03

    The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced on a large-scale approach. The unique HNDCM holds great promise as components in separation and advanced carbon devices because they could offer unconventional fluidic transport phenomena on the nanoscale. Overall, the invention set forth herein covers a hierarchically structured, nitrogen-doped carbon membranes and methods of making and using such a membranes.

  1. A Model for Slicing JAVA Programs Hierarchically

    Institute of Scientific and Technical Information of China (English)

    Bi-Xin Li; Xiao-Cong Fan; Jun Pang; Jian-Jun Zhao

    2004-01-01

    Program slicing can be effectively used to debug, test, analyze, understand and maintain objectoriented software. In this paper, a new slicing model is proposed to slice Java programs based on their inherent hierarchical feature. The main idea of hierarchical slicing is to slice programs in a stepwise way, from package level, to class level, method level, and finally up to statement level. The stepwise slicing algorithm and the related graph reachability algorithms are presented, the architecture of the Java program Analyzing Tool (JATO) based on hierarchical slicing model is provided, the applications and a small case study are also discussed.

  2. Hierarchical analysis of acceptable use policies

    Directory of Open Access Journals (Sweden)

    P. A. Laughton

    2008-01-01

    Full Text Available Acceptable use policies (AUPs are vital tools for organizations to protect themselves and their employees from misuse of computer facilities provided. A well structured, thorough AUP is essential for any organization. It is impossible for an effective AUP to deal with every clause and remain readable. For this reason, some sections of an AUP carry more weight than others, denoting importance. The methodology used to develop the hierarchical analysis is a literature review, where various sources were consulted. This hierarchical approach to AUP analysis attempts to highlight important sections and clauses dealt with in an AUP. The emphasis of the hierarchal analysis is to prioritize the objectives of an AUP.

  3. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  4. Analytical methods in untargeted metabolomics: state of the art in 2015

    Directory of Open Access Journals (Sweden)

    Arnald eAlonso

    2015-03-01

    Full Text Available Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile –the metabolome- has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance (NMR and mass spectrometry (MS are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high throughput biotechnologies is also reviewed.

  5. Numerical simulation of strained Si/SiGe devices: the hierarchical approach

    Science.gov (United States)

    Meinerzhagen, B.; Jungemann, C.; Neinhüs, B.; Bartels, M.

    2004-03-01

    Performance predictions for 25 nm strained Si CMOS devices which are based on full-band Monte Carlo (FBMC) device simulations and which are in good agreement with the most recent experimental trends are presented. The FBMC simulator itself is part of a hierarchical device simulation system which allows to perform time-efficient hierarchical hydrodynamic (HD) device simulations of modern SiGe HBTs. As demonstrated below, the accuracy of a such a hydrodynamic-based dc, ac, transient, and noise analysis is comparable to FBMC device simulations. In addition, the new hierarchical numerical noise simulation method is experimentally verified based on a modern rf-CMOS technology of Philips Research. The MC-enhanced simulation accuracy of the hierarchical hydrodynamic and drift diffusion (DD) models can be also exploited for mixed-mode circuit simulations, which is shown by typical power sweep simulations of an industrial rf power amplifier.

  6. Curved hierarchically micro-micro structured polypropylene surfaces by injection molding

    Science.gov (United States)

    Mielonen, K.; Suvanto, M.; Pakkanen, T. A.

    2017-01-01

    Structural hierarchy of polymer surfaces has been of central interest due to its diverse surface functionalities. However, the research on hierarchically structured polymer surfaces has been focused on planar surfaces even though applications may also be variously curved. This study demonstrates the fabrication of curved rigid polymer surfaces with precisely controlled hierarchical microstructures. The surface structuration was made on an aluminum foil with a microworking robot, and polypropylene replicas were produced by injection molding. Depending on the mold structuration procedure, the curved mold can have either radially or vertically oriented structures. Both convex and concave curvatures were here applied to spherically and cylindrically curved surfaces. A simple structure protection technique was applied to support the structures during mechanical bending of the foil. The planar hierarchically microstructured polypropylene surfaces were characterized to exhibit superhydrophobicity, and similar structures were obtained on the curved surfaces. Introducing the curvature to the hierarchically structured surfaces may further widen the applicability of functionalized polymer surfaces.

  7. Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data

    CERN Document Server

    Truyen, Tran The; Bui, Hung H; Venkatesh, Svetha

    2010-01-01

    Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirectedMarkov chains tomodel complex hierarchical, nestedMarkov processes. It is parameterised in a discriminative framework and has polynomial time algorithms for learning and inference. Importantly, we consider partiallysupervised learning and propose algorithms for generalised partially-supervised learning and constrained inference. We demonstrate the HSCRF in two applications: (i) recognising human activities of daily living (ADLs) from indoor surveillance cameras, and (ii) noun-phrase chunking. We show that the HSCRF is capable of learning rich hierarchical models with reasonable accuracy in both fully and partially observed data cases.

  8. Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

    Science.gov (United States)

    Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

    2014-12-01

    This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

  9. HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Michael D.; Dawson, William A. [Lawrence Livermore National Laboratory, Livermore, CA 94551 (United States); Hogg, David W. [Center for Cosmology and Particle Physics, New York University, New York, NY 10003 (United States); Marshall, Philip J.; Bard, Deborah J. [SLAC National Accelerator Laboratory, Menlo Park, CA 94025 (United States); Meyers, Joshua [Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, 452 Lomita Mall, Stanford, CA 94035 (United States); Lang, Dustin, E-mail: schneider42@llnl.gov [Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213 (United States)

    2015-07-01

    Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.

  10. HIDEN: Hierarchical decomposition of regulatory networks

    Directory of Open Access Journals (Sweden)

    Gülsoy Günhan

    2012-09-01

    Full Text Available Abstract Background Transcription factors regulate numerous cellular processes by controlling the rate of production of each gene. The regulatory relations are modeled using transcriptional regulatory networks. Recent studies have shown that such networks have an underlying hierarchical organization. We consider the problem of discovering the underlying hierarchy in transcriptional regulatory networks. Results We first transform this problem to a mixed integer programming problem. We then use existing tools to solve the resulting problem. For larger networks this strategy does not work due to rapid increase in running time and space usage. We use divide and conquer strategy for such networks. We use our method to analyze the transcriptional regulatory networks of E. coli, H. sapiens and S. cerevisiae. Conclusions Our experiments demonstrate that: (i Our method gives statistically better results than three existing state of the art methods; (ii Our method is robust against errors in the data and (iii Our method’s performance is not affected by the different topologies in the data.

  11. Hierarchical structure and biomineralization in cricket tooth

    CERN Document Server

    Xing, Xueqing; Cai, Quan; Mo, Guang; Du, Rong; Chen, Zhongjun; Wu, Zhonghua

    2012-01-01

    Cricket is a truculent insect with stiff and sharp teeth as a fighting weapon. The structure and possible biomineralization of the cricket teeth are always interested. Synchrotron radiation X-ray fluorescence, X-ray diffraction and small angle X-ray scattering techniques were used to probe the element distribution, possible crystalline structures and size distribution of scatterers in cricket teeth. Scanning electron microscope was used to observe the nanoscaled structure. The results demonstrate that Zn is the main heavy element in cricket teeth. The surface of the cricket teeth has a crystalline compound like ZnFe2(AsO4)2(OH)2(H2O)4. While, the interior of the teeth has a crystalline compound like ZnCl2, which is from the biomineralization. The ZnCl2-like biomineral forms nanoscaled microfibrils and their axial direction points at the top of tooth cusp. The microfibrils aggregate random into intermediate filaments, forming a hierarchical structure. A sketch map of the cricket tooth cusp was proposed and a d...

  12. Image meshing via hierarchical optimization

    Institute of Scientific and Technical Information of China (English)

    Hao XIE; Ruo-feng TONG‡

    2016-01-01

    Vector graphic, as a kind of geometric representation of raster images, has many advantages, e.g., defi nition independence and editing facility. A popular way to convert raster images into vector graphics is image meshing, the aim of which is to fi nd a mesh to represent an image as faithfully as possible. For traditional meshing algorithms, the crux of the problem resides mainly in the high non-linearity and non-smoothness of the objective, which makes it difficult to fi nd a desirable optimal solution. To ameliorate this situation, we present a hierarchical optimization algorithm solving the problem from coarser levels to fi ner ones, providing initialization for each level with its coarser ascent. To further simplify the problem, the original non-convex problem is converted to a linear least squares one, and thus becomes convex, which makes the problem much easier to solve. A dictionary learning framework is used to combine geometry and topology elegantly. Then an alternating scheme is employed to solve both parts. Experiments show that our algorithm runs fast and achieves better results than existing ones for most images.

  13. Image meshing via hierarchical optimization*

    Institute of Scientific and Technical Information of China (English)

    Hao XIE; Ruo-feng TONGS

    2016-01-01

    Vector graphic, as a kind of geometric representation of raster images, has many advantages, e.g., definition independence and editing facility. A popular way to convert raster images into vector graphics is image meshing, the aim of which is to find a mesh to represent an image as faithfully as possible. For traditional meshing algorithms, the crux of the problem resides mainly in the high non-linearity and non-smoothness of the objective, which makes it difficult to find a desirable optimal solution. To ameliorate this situation, we present a hierarchical optimization algorithm solving the problem from coarser levels to finer ones, providing initialization for each level with its coarser ascent. To further simplify the problem, the original non-convex problem is converted to a linear least squares one, and thus becomes convex, which makes the problem much easier to solve. A dictionary learning framework is used to combine geometry and topology elegantly. Then an alternating scheme is employed to solve both parts. Experiments show that our algorithm runs fast and achieves better results than existing ones for most images.

  14. Hierarchical Bayes Ensemble Kalman Filtering

    CERN Document Server

    Tsyrulnikov, Michael

    2015-01-01

    Ensemble Kalman filtering (EnKF), when applied to high-dimensional systems, suffers from an inevitably small affordable ensemble size, which results in poor estimates of the background error covariance matrix ${\\bf B}$. The common remedy is a kind of regularization, usually an ad-hoc spatial covariance localization (tapering) combined with artificial covariance inflation. Instead of using an ad-hoc regularization, we adopt the idea by Myrseth and Omre (2010) and explicitly admit that the ${\\bf B}$ matrix is unknown and random and estimate it along with the state (${\\bf x}$) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components ${\\bf P}$ and ${\\bf Q}$ of the ${\\bf B}$ matrix into the extended control vector $({\\bf x},{\\bf P},{\\bf Q})$. Similarly, we break the traditional backgrou...

  15. Exploring the mode of action of dithranol therapy for psoriasis: a metabolomic analysis using HaCaT cells.

    Science.gov (United States)

    Hollywood, Katherine A; Winder, Catherine L; Dunn, Warwick B; Xu, Yun; Broadhurst, David; Griffiths, Christopher E M; Goodacre, Royston

    2015-08-01

    Psoriasis is a common, immune-mediated inflammatory skin disease characterized by red, heavily scaled plaques. The disease affects over one million people in the UK and causes significant physical, psychological and societal impact. There is limited understanding regarding the exact pathogenesis of the disease although it is believed to be a consequence of genetic predisposition and environmental triggers. Treatments vary from topical therapies, such as dithranol, for disease of limited extent (biologic therapies for severe psoriasis. Dithranol (also known as anthralin) is a topical therapy for psoriasis believed to work by inhibiting keratinocyte proliferation. To date there have been no metabolomic-based investigations into psoriasis. The HaCaT cell line is a model system for the epidermal keratinocyte proliferation characteristic of psoriasis and was thus chosen for study. Dithranol was applied at therapeutically relevant doses to HaCaT cells. Following the optimisation of enzyme inactivation and metabolite extraction, gas chromatography-mass spectrometry was employed for metabolomics as this addresses central metabolism. Cells were challenged with 0-0.5 μg mL(-1) in 0.1 μg mL(-1) steps and this quantitative perturbation generated data that were highly amenable to correlation analysis. Thus, we used a combination of traditional principal components analysis, hierarchical cluster analysis, along with correlation networks. All methods highlighted distinct metabolite groups, which had different metabolite trajectories with respect to drug concentration and the interpretation of these data established that cellular metabolism had been altered significantly and provided further clarification of the proposed mechanism of action of the drug.

  16. Proteomics and Metabolomics: two emerging areas for legume improvement

    Directory of Open Access Journals (Sweden)

    Abirami eRamalingam

    2015-12-01

    Full Text Available The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important source of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signalling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signalling in legumes. In

  17. An Automatic Hierarchical Delay Analysis Tool

    Institute of Scientific and Technical Information of China (English)

    FaridMheir-El-Saadi; BozenaKaminska

    1994-01-01

    The performance analysis of VLSI integrated circuits(ICs) with flat tools is slow and even sometimes impossible to complete.Some hierarchical tools have been developed to speed up the analysis of these large ICs.However,these hierarchical tools suffer from a poor interaction with the CAD database and poorly automatized operations.We introduce a general hierarchical framework for performance analysis to solve these problems.The circuit analysis is automatic under the proposed framework.Information that has been automatically abstracted in the hierarchy is kept in database properties along with the topological information.A limited software implementation of the framework,PREDICT,has also been developed to analyze the delay performance.Experimental results show that hierarchical analysis CPU time and memory requirements are low if heuristics are used during the abstraction process.

  18. Packaging glass with hierarchically nanostructured surface

    KAUST Repository

    He, Jr-Hau

    2017-08-03

    An optical device includes an active region and packaging glass located on top of the active region. A top surface of the packaging glass includes hierarchical nanostructures comprised of honeycombed nanowalls (HNWs) and nanorod (NR) structures extending from the HNWs.

  19. Generation of hierarchically correlated multivariate symbolic sequences

    CERN Document Server

    Tumminello, Mi; Mantegna, R N

    2008-01-01

    We introduce an algorithm to generate multivariate series of symbols from a finite alphabet with a given hierarchical structure of similarities. The target hierarchical structure of similarities is arbitrary, for instance the one obtained by some hierarchical clustering procedure as applied to an empirical matrix of Hamming distances. The algorithm can be interpreted as the finite alphabet equivalent of the recently introduced hierarchically nested factor model (M. Tumminello et al. EPL 78 (3) 30006 (2007)). The algorithm is based on a generating mechanism that is different from the one used in the mutation rate approach. We apply the proposed methodology for investigating the relationship between the bootstrap value associated with a node of a phylogeny and the probability of finding that node in the true phylogeny.

  20. Hierarchical modularity in human brain functional networks

    CERN Document Server

    Meunier, D; Fornito, A; Ersche, K D; Bullmore, E T; 10.3389/neuro.11.037.2009

    2010-01-01

    The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at ...