PubMed

A Small Molecule Solution to the Vexing Problem of Restenosis: Predicting Restenosis. JACC Cardiovasc Interv. 2017 Jun 07;: Authors: Quyyumi AA, Samman Tahhan A, Jones DP PMID: 28624382 [PubMed - as supplied by publisher]

Plasma Phospholipids and Sphingolipids Identify Stent Restenosis After Percutaneous Coronary Intervention. JACC Cardiovasc Interv. 2017 Jun 07;: Authors: Cui S, Li K, Ang L, Liu J, Cui L, Song X, Lv S, Mahmud E Abstract OBJECTIVES: The aim of this study was to evaluate the diagnostic utility of plasma metabolomic biomarkers for in-stent restenosis (ISR). BACKGROUND: ISR remains an issue for patients after percutaneous coronary intervention. Identification of biomarkers to predict ISR could be invaluable for patient care. METHODS: Next-generation metabolomic profiling was performed in the discovery phase from the plasma of 400 patients undergoing percutaneous coronary intervention. In the validation phase, targeted analysis was conducted using stable isotope dilution-multiple reaction monitoring mass spectrometry in another independent group of 500 participants. RESULTS: A set of 6 plasma metabolites was discovered and validated for the diagnosis of ISR as early as 1 month after percutaneous coronary intervention. This biomarker panel classified patients with ISR and control subjects with sensitivity of 91% and specificity of 90% in the discovery phase. The diagnostic accuracy in the independent validation phase was 90% (95% confidence interval: 87% to 100%). The defined 6 metabolites all belong to sphingolipid and phospholipid metabolism, including phosphatidylcholine diacyl C36:0, phosphatidylcholine diacyl C34:2, phosphatidylinositol diacyl C36:4, phosphatidic acid C34:1, ceramide, and sphingomyelin diacyl 18:1/20:1. These biomarkers play essential roles in cell signaling that regulates the proliferation and migration of vascular smooth muscle cells. CONCLUSIONS: Next-generation metabolomics demonstrates powerful diagnostic value in estimating ISR-related metabolic disturbance. The defined plasma biomarkers provide better early diagnostic value compared with conventional imaging techniques. PMID: 28624380 [PubMed - as supplied by publisher]

Differential urinary metabolites related with the severity of major depressive disorder. Behav Brain Res. 2017 Jun 14;: Authors: Chen JJ, Zhou CJ, Zheng P, Cheng K, Wang HY, Li J, Zeng L, Xie P Abstract Major depressive disorder (MDD) is a common mental disorder that affects a person's general health. However, there is still no objective laboratory test for diagnosing MDD. Here, an integrated analysis of data from our previous studies was performed to identify the differential metabolites in the urine of moderate and severe MDD patients. A dual platform approach (NMR spectroscopy and GC-MS) was used. Consequently, 14 and 22 differential metabolites responsible for separating moderate and severe MDD patients, respectively, from their respective healthy controls (HCs) were identified. Meanwhile, the moderate MDD-specific panel (N-Methylnicotinamide, Acetone, Choline, Citrate, vanillic acid and azelaic acid) and severe MDD-specific panel (indoxyl sulphate, Taurine, Citrate, 3-hydroxyphenylacetic acid, palmitic acid and Lactate) could discriminate moderate and severe MDD patients, respectively, from their respective HCs with high accuracy. Moreover, the differential metabolites in severe MDD were significantly involved in three metabolic pathways and some biofunctions. These results showed that there were divergent urinary metabolic phenotypes in moderate and severe MDD patients, and the identified potential urinary biomarkers might be useful for future developing objective diagnostic tests for MDD diagnosis. Our results could also be helpful for researchers to study the pathogenesis of MDD. PMID: 28624318 [PubMed - as supplied by publisher]

Importance of optimizing chromatographic conditions and mass spectrometric parameters for supercritical fluid chromatography/mass spectrometry. J Chromatogr A. 2017 Jun 02;: Authors: Fujito Y, Hayakawa Y, Izumi Y, Bamba T Abstract Supercritical fluid chromatography/mass spectrometry (SFC/MS) has great potential in high-throughput and the simultaneous analysis of a wide variety of compounds, and it has been widely used in recent years. The use of MS for detection provides the advantages of high sensitivity and high selectivity. However, the sensitivity of MS detection depends on the chromatographic conditions and MS parameters. Thus, optimization of MS parameters corresponding to the SFC condition is mandatory for maximizing performance when connecting SFC to MS. The aim of this study was to reveal a way to decide the optimum composition of the mobile phase and the flow rate of the make-up solvent for MS detection in a wide range of compounds. Additionally, we also showed the basic concept for determination of the optimum values of the MS parameters focusing on the MS detection sensitivity in SFC/MS analysis. To verify the versatility of these findings, a total of 441 pesticides with a wide polarity range (logPow from -4.21 to 7.70) and pKa (acidic, neutral and basic). In this study, a new SFC-MS interface was used, which can transfer the entire volume of eluate into the MS by directly coupling the SFC with the MS. This enabled us to compare the sensitivity or optimum MS parameters for MS detection between LC/MS and SFC/MS for the same sample volume introduced into the MS. As a result, it was found that the optimum values of some MS parameters were completely different from those of LC/MS, and that SFC/MS-specific optimization of the analytical conditions is required. Lastly, we evaluated the sensitivity of SFC/MS using fully optimized analytical conditions. As a result, we confirmed that SFC/MS showed much higher sensitivity than LC/MS when the analytical conditions were fully optimized for SFC/MS; and the high sensitivity also increase the number of the compounds that can be detected with good repeatability in real sample analysis. This result indicates that SFC/MS has potential for practical use in the multiresidue analysis of a wide range of compounds that requires high sensitivity. PMID: 28624150 [PubMed - as supplied by publisher]

One-carbon metabolism, cognitive impairment and CSF measures of Alzheimer pathology: homocysteine and beyond. Alzheimers Res Ther. 2017 Jun 17;9(1):43 Authors: Dayon L, Guiraud SP, Corthésy J, Da Silva L, Migliavacca E, Tautvydaitė D, Oikonomidi A, Moullet B, Henry H, Métairon S, Marquis J, Descombes P, Collino S, Martin FJ, Montoliu I, Kussmann M, Wojcik J, Bowman GL, Popp J Abstract BACKGROUND: Hyperhomocysteinemia is a risk factor for cognitive decline and dementia, including Alzheimer disease (AD). Homocysteine (Hcy) is a sulfur-containing amino acid and metabolite of the methionine pathway. The interrelated methionine, purine, and thymidylate cycles constitute the one-carbon metabolism that plays a critical role in the synthesis of DNA, neurotransmitters, phospholipids, and myelin. In this study, we tested the hypothesis that one-carbon metabolites beyond Hcy are relevant to cognitive function and cerebrospinal fluid (CSF) measures of AD pathology in older adults. METHODS: Cross-sectional analysis was performed on matched CSF and plasma collected from 120 older community-dwelling adults with (n = 72) or without (n = 48) cognitive impairment. Liquid chromatography-mass spectrometry was performed to quantify one-carbon metabolites and their cofactors. Least absolute shrinkage and selection operator (LASSO) regression was initially applied to clinical and biomarker measures that generate the highest diagnostic accuracy of a priori-defined cognitive impairment (Clinical Dementia Rating-based) and AD pathology (i.e., CSF tau phosphorylated at threonine 181 [p-tau181]/β-Amyloid 1-42 peptide chain [Aβ1-42] >0.0779) to establish a reference benchmark. Two other LASSO-determined models were generated that included the one-carbon metabolites in CSF and then plasma. Correlations of CSF and plasma one-carbon metabolites with CSF amyloid and tau were explored. LASSO-determined models were stratified by apolipoprotein E (APOE) ε4 carrier status. RESULTS: The diagnostic accuracy of cognitive impairment for the reference model was 80.8% and included age, years of education, Aβ1-42, tau, and p-tau181. A model including CSF cystathionine, methionine, S-adenosyl-L-homocysteine (SAH), S-adenosylmethionine (SAM), serine, cysteine, and 5-methyltetrahydrofolate (5-MTHF) improved the diagnostic accuracy to 87.4%. A second model derived from plasma included cystathionine, glycine, methionine, SAH, SAM, serine, cysteine, and Hcy and reached a diagnostic accuracy of 87.5%. CSF SAH and 5-MTHF were associated with CSF tau and p-tau181. Plasma one-carbon metabolites were able to diagnose subjects with a positive CSF profile of AD pathology in APOE ε4 carriers. CONCLUSIONS: We observed significant improvements in the prediction of cognitive impairment by adding one-carbon metabolites. This is partially explained by associations with CSF tau and p-tau181, suggesting a role for one-carbon metabolism in the aggregation of tau and neuronal injury. These metabolites may be particularly critical in APOE ε4 carriers. PMID: 28623948 [PubMed - in process]

25 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/06/18PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

19 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/06/16PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

18 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/06/15PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

18 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/06/14PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample. J Vis Exp. 2017 Jun 01;(124): Authors: Salem M, Bernach M, Bajdzienko K, Giavalisco P Abstract Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually determined by transcriptomic, proteomic, metabolomics and lipidomic measurements. In this protocol, we introduce a simple method for the reproducible extraction of metabolites, lipids and proteins from biological tissues using a single aliquot per sample. The extraction method is based on a methyl tert-butyl ether: methanol: water system for liquid: liquid partitioning of hydrophobic and polar metabolites into two immiscible phases along with the precipitation of proteins and other macromolecules as a solid pellet. This method, therefore, provides three different fractions of specific molecular composition, which are fully compatible with common high throughput 'omics' technologies such as liquid chromatography (LC) or gas chromatography (GC) coupled to mass spectrometers. Even though the method was initially developed for the analysis of different plant tissue samples, it has proved to be fully compatible for the extraction and analysis of biological samples from systems as diverse as algae, insects, and mammalian tissues and cell cultures. PMID: 28605387 [PubMed - in process]

Targeted metabolomics analysis of aromatic amino acids and their gut microbiota-host co-metabolites in rat serum and urine by liquid chromatography with tandem mass spectrometry. J Sep Sci. 2017 Jun 12;: Authors: Zeng Y, Luo L, Hou W, Lu B, Gong J, Chen J, Zhang X, Han B, Xie Z, Liao Q Abstract Gut microbiota-host co-metabolites are closely related to various diseases. Monitoring dynamic changes of co-metabolites can provide a more comprehensive understanding of pathophysiology. Here, a novel liquid chromatography-tandem mass spectrometry method was performed for the analysis of aromatic amino acids and their gut microbiota-host co-metabolites in rat serum and urine. In the developed method, seven key gut microbiota-host co-metabolites were chromatographically separated on a Kinetex Phenyl-Hexyl column by gradient elution, and the run time was 6 min. Serum and urine were extracted by protein precipitation. This method was linear between 10.20 and 1000.00 ng/mL for phenylalanine and p-cresyl sulfate; 25.60-2500.00 ng/mL for tryptophan; 51.20-5000.00 ng/mL for tyrosine, indole and indoxyl sulfate; and 75.50-7500.00 ng/mL for p-cresol. The linearity, accuracy, precision and recovery of seven analytes were all satisfactory. The method was sufficiently sensitive and robust. It was successfully applied to characterize the alterations of gut microbiota-host co-metabolites in inflammatory disorders. All of these results suggest that the developed method is able to simultaneously monitor aromatic amino acids and their gut microbiota-host co-metabolites. This method will be expected to be a valuable tool for clinical researches and comprehensive studies of the pathophysiological roles. This article is protected by copyright. All rights reserved. PMID: 28605162 [PubMed - as supplied by publisher]

Phenotyping of gut microbiota: Focus on capillary electrophoresis. Electrophoresis. 2017 Jun 12;: Authors: Ferrer M, Raczkowska BA, Martínez-Martínez M, Barbas C, Rojo D Abstract The analysis of the microbial metabolome is crucial to fully understand the symbiotic relation between humans and microbes. That is why an explosion of metabolomics took place in the area. So far, at least several hundreds of microbial metabolites have been shown to be statistically altered when humans undergo a plethora of commonly faced perturbations. NMR and MS, usually coupled with GC, LC and CE have revealed their identities. CE is a robust analytical platform for the analysis of polar and ionic metabolites that are essential in order to assess the cells' activity. Due to its novelty, only 5 % of the metabolomics studies investigate gut microbiota using CE, even though the metabolites found by CE as being significantly altered in human microbiota represent around 23 % of the total number of metabolites identified by metabolomics tools. Herein, we discuss the advances of metabolomics in the frame of other OMICS techniques for human gut microbiota analysis. Afterwards, we focus on sample treatment, analytical methods and data processing in CE coupled to any detector that have been reported to date in order to enhance metabolite coverage in the art, and to identify metabolite markers that cannot be covered by other platforms but are of key importance for determining microbial activity and human health. This article is protected by copyright. All rights reserved. PMID: 28605027 [PubMed - as supplied by publisher]

Related Articles Crimean-Congo Hemorrhagic Fever: Tick-Host-Virus Interactions. Front Cell Infect Microbiol. 2017;7:213 Authors: Papa A, Tsergouli K, Tsioka K, Mirazimi A Abstract Crimean-Congo hemorrhagic fever virus (CCHFV) is transmitted to humans by bite of infected ticks or by direct contact with blood or tissues of viremic patients or animals. It causes to humans a severe disease with fatality up to 30%. The current knowledge about the vector-host-CCHFV interactions is very limited due to the high-level containment required for CCHFV studies. Among ticks, Hyalomma spp. are considered the most competent virus vectors. CCHFV evades the tick immune response, and following its replication in the lining of the tick's midgut, it is disseminated by the hemolymph in the salivary glands and reproductive organs. The introduction of salivary gland secretions into the host cells is the major route via which CCHFV enters the host. Following an initial amplification at the site of inoculation, the virus is spread to the target organs. Apoptosis is induced via both intrinsic and extrinsic pathways. Genetic factors and immune status of the host may affect the release of cytokines which play a major role in disease progression and outcome. It is expected that the use of new technology of metabolomics, transcriptomics and proteomics will lead to improved understanding of CCHFV-host interactions and identify potential targets for blocking the CCHFV transmission. PMID: 28603698 [PubMed - in process]

Related Articles Association of amine biomarkers with incident dementia and Alzheimer's disease in the Framingham Study. Alzheimers Dement. 2017 Jun 08;: Authors: Chouraki V, Preis SR, Yang Q, Beiser A, Li S, Larson MG, Weinstein G, Wang TJ, Gerszten RE, Vasan RS, Seshadri S Abstract INTRODUCTION: The identification of novel biomarkers associated with Alzheimer's disease (AD) could provide key biological insights and permit targeted preclinical prevention. We investigated circulating metabolites associated with incident dementia and AD using metabolomics. METHODS: Plasma levels of 217 metabolites were assessed in 2067 dementia-free Framingham Offspring Cohort participants (mean age = 55.9 ± 9.7 years; 52.4% women). We studied their associations with future dementia and AD risk in multivariate Cox models. RESULTS: Ninety-three participants developed incident dementia (mean follow-up = 15.6 ± 5.2 years). Higher plasma anthranilic acid levels were associated with greater risk of dementia (hazard ratio [HR] = 1.40; 95% confidence interval [CI] = [1.15-1.70]; P = 8.08 × 10(-4)). Glutamic acid (HR = 1.38; 95% CI = [1.11-1.72]), taurine (HR = 0.74; 95% CI = [0.60-0.92]), and hypoxanthine (HR = 0.74; 95% CI = [0.60-0.92]) levels also showed suggestive associations with dementia risk. DISCUSSION: We identified four biologically plausible, candidate plasma biomarkers for dementia. Association of anthranilic acid implicates the kynurenine pathway, which modulates glutamate excitotoxicity. The associations with hypoxanthine and taurine strengthen evidence that uric acid and taurine may be neuroprotective. PMID: 28602601 [PubMed - as supplied by publisher]

Enantioselective bioaccumulation following exposure of adult zebrafish (Danio rerio) to epoxiconazole and its effects on metabolomic profile as well as genes expression. Environ Pollut. 2017 Jun 07;229:264-271 Authors: Wang Y, Teng M, Wang D, Yan J, Miao J, Zhou Z, Zhu W Abstract Although epoxiconazole is the worldwidely used fungicide, limited information is known about its toxic effects and bioaccumulation behavior in freshwater ecosystems. In this study, zebrafish were exposed to epoxiconazole at concentrations of 100 and 1000 μg L(-1) for 21 d. (1)H NMR-based metabolomics analysis showed that low- and high-dose epoxiconazole exposure resulted in two similar but not identical patterns for the change of endogenous metabolites related to energy, lipid and amino acid metabolism. The expression of genes associated with mitochondrial respiratory chain, ATP synthesis and fatty acid β-oxidation were further measured to explore the reason for the disturbed energy metabolism, finding epoxiconazole had an inhibition effect on the genes expression of the above ways. Significant enantioselectivity was observed with (+)-epoxiconazole enrichment in the bioaccumulation process. These results will be of great importance in understanding the toxic effects induced by epoxiconazole and provide important basis for its comprehensive environmental assessment. PMID: 28601015 [PubMed - as supplied by publisher]

Related Articles Application of omics in predicting anti-TNF efficacy in rheumatoid arthritis. Clin Rheumatol. 2017 Jun 10;: Authors: Xie X, Li F, Li S, Tian J, Chen JW, Du JF, Mao N, Chen J Abstract Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by progressive joint erosion. Tumor necrosis factor (TNF) antagonists are the most widely used biological disease-modifying anti-rheumatic drug in RA. However, there continue to be one third of RA patients who have poor or no response to TNF antagonists. Following consideration of the uncertainty of therapeutic effects and the high price of TNF antagonists, it is worthy to predict the treatment responses before anti-TNF therapy. According to the comparisons between the responders and non-responders to TNF antagonists by omic technologies, such as genomics, transcriptomics, proteomics, and metabolomics, rheumatologists are eager to find significant biomarkers to predict the effect of TNF antagonists in order to optimize the personalized treatment in RA. PMID: 28600618 [PubMed - as supplied by publisher]

Related Articles Validation of onchocerciasis biomarker N-acetyltyramine-O-glucuronide (NATOG). Bioorg Med Chem Lett. 2017 May 29;: Authors: Globisch D, Eubanks LM, Shirey RJ, Pfarr KM, Wanji S, Debrah AY, Hoerauf A, Janda KD Abstract The Neglected Tropical Disease onchocerciasis is a parasitic disease. Despite many control programmes by the World Health Organization (WHO), large communities in West and Central Africa are still affected. Besides logistic challenges during biannual mass drug administration, the lack of a robust, point-of-care diagnostic is limiting successful eradication of onchocerciasis. Towards the implementation of a non-invasive and point-of-care diagnostic, we have recently reported the discovery of the biomarker N-acetyltyramine-O-glucuronide (NATOG) in human urine samples using a metabolomics-mining approach. NATOG's biomarker value was enhanced during an investigation in a rodent model. Herein, we further detail the specificity of NATOG in active onchocerciasis infections as well as the co-infecting parasites Loa loa and Mansonella perstans. Our results measured by liquid chromatography coupled with mass spectrometry (LC-MS) reveal elevated NATOG values in mono- and co-infection samples only in the presence of the nematode Onchocerca volvulus. Metabolic pathway investigation of l-tyrosine/tyramine in all investigated nematodes uncovered an important link between the endosymbiotic bacterium Wolbachia and O. volvulus for the biosynthesis of NATOG. Based on these extended studies, we suggest NATOG as a biomarker for tracking active onchocerciasis infections and provide a threshold concentration value of NATOG for future diagnostic tool development. PMID: 28600214 [PubMed - as supplied by publisher]

Related Articles MetabolitePredict: a de-novo human metabolomics prediction system and its applications in rheumatoid arthritis. J Biomed Inform. 2017 Jun 06;: Authors: Wang Q, Xu R Abstract Human metabolomics has great potential in disease mechanism understanding, early diagnosis, and therapy. Existing metabolomics studies are often based on profiling patient biofluids and tissue samples and are difficult owing to the challenges of sample collection and data processing. Here, we report an alternative approach and developed a computation-based prediction system, MetabolitePredict, for disease metabolomics biomarker prediction. We applied MetabolitePredict to identify metabolite biomarkers and metabolite targeting therapies for rheumatoid arthritis (RA), a last-lasting complex disease with multiple genetic and environmental factors involved. MetabolitePredict is a de-novo prediction system. It first constructs a disease-specific genetic profile using genes and pathways data associated with an input disease. It then constructs genetic profiles for a total of 259,170 chemicals/metabolites using known chemical genetics and human metabolomic data. MetabolitePredict prioritizes metabolites for a given disease based on the genetic profile similarities between disease and metabolites. We evaluated MetabolitePredict using 63 known RA-associated metabolites. MetabolitePredict found 24 of the 63 metabolites (recall: 0.38) and ranked them highly (mean ranking: top 4.13%, median ranking: top 1.10%, P-value: 5.08E-19). MetabolitePredict performed better than an existing metabolite prediction system, PROFANCY, in predicting RA-associated metabolites (PROFANCY: recall: 0.31, mean ranking: 20.91%, median ranking: 16.47%, P-value: 3.78E-7). Short-chain fatty acids (SCFAs), the abundant metabolites of gut microbiota in the fermentation of fiber, ranked highly (butyrate, 0.03%; acetate, 0.05%; propionate, 0.38%). Finally, we established MetabolitePredict's potential in novel metabolite targeting for disease treatment: MetabolitePredict ranked highly three known metabolite inhibitors for RA treatments (methotrexate:0.25%; leflunomide: 0.56%; sulfasalazine: 0.92%). MetabolitePredict is a generalizable disease metabolite prediction system. The only required input to the system is a disease name or a set of disease-associated genes. The web-based MetabolitePredict is available at: http://xulab. CASE: edu/MetabolitePredict. PMID: 28600026 [PubMed - as supplied by publisher]

Related Articles Quantification of metabolites in dried blood spots by direct infusion high resolution mass spectrometry. Anal Chim Acta. 2017 Aug 01;979:45-50 Authors: de Sain-van der Velden MGM, van der Ham M, Gerrits J, Prinsen HCMT, Willemsen M, Pras-Raves ML, Jans JJ, Verhoeven-Duif NM Abstract Diagnosis and treatment of inborn errors of metabolism (IEM) require the analysis of a variety of metabolites. These compounds are usually quantified by targeted platforms. High resolution mass spectrometry (HRMS) has the potential to detect hundreds to thousands of metabolites simultaneously. A chip-based nanoelectrospray source (chip-based nanoESI) enables the direct infusion of biological samples. Major advantages of this system include high sample throughput, no sample carryover, and low sample consumption. The combination, chip-based nanoESI-HRMS enables untargeted metabolomics of biological samples but its potential for quantification of metabolites has not been reported. We investigated whether chip-based nanoESI-HRMS is suitable for quantification of metabolites in dried blood spots (DBS). After addition of internal standards, metabolites were extracted with methanol. Aliquots of each extract were analysed by chip-based nanoESI-HRMS operating in both positive and negative mode with an m/z window of 70-600 and a resolution of 140,000. Total run time was 4.5 min per sample and a full report could be generated within 40 min. Concentrations of all 21 investigated diagnostic metabolites in DBS as quantified by chip-based nanoESI-HRMS correlated well with those obtained by targeted liquid chromatography-tandem mass spectrometry. We conclude that chip-based nanoESI-HRMS is suitable for quantification. PMID: 28599708 [PubMed - in process]

17 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/06/10PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.