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22 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 2019/03/07PubMed 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.

20 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 2019/03/06PubMed 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.

162 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 2019/03/05PubMed 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.

Related Articles Metabolomics profiling and pathway analysis of human plasma and urine reveal further insights into the multifactorial nature of Coronary Artery Disease (CAD). Clin Chim Acta. 2019 Feb 28;: Authors: Amin AM, Mostafa H, Arif NH, Kader MASKA, Hay YK Abstract BACKGROUND: Coronary artery disease (CAD) claims lives yearly. Nuclear magnetic resonance (1H NMR) metabolomics analysis is efficient in identifying metabolic biomarkers which lend credence to diagnosis. We identified CAD metabotypes and its implicated pathways using 1H NMR analysis. METHODS: We analysed plasma and urine samples of 50 stable CAD patients and 50 healthy controls using 1H NMR. Orthogonal partial least square discriminant analysis (OPLS-DA) followed by multivariate logistic regression (MVLR) models were developed to indicate the discriminating metabotypes. RESULTS: Both plasma and urine OPLS-DA models had specificity, sensitivity and accuracy of 100%, 96% and 98%, respectively. Plasma MVLR model had specificity, sensitivity, accuracy and AUROC of 92%, 86%, 89% and 0.96, respectively. The MVLR model of urine had specificity, sensitivity, accuracy and AUROC of 90%, 80%, 85% and 0.92, respectively. 35 and 12 metabolites were identified in plasma and urine metabotypes, respectively. Metabolic pathway analysis revealed that urea cycle, aminoacyl-tRNA biosynthesis and synthesis and degradation of ketone bodies pathways were significantly disturbed in plasma, while methylhistidine metabolism and galactose metabolism pathways were significantly disturbed in urine. The enrichment over representation analysis against SNPs-associated-metabolite sets library revealed that 85 SNPs were significantly enriched in plasma metabotype. CONCLUSIONS: Cardiometabolic diseases, dysbiotic gut-microbiota and genetic variabilities are largely implicated in the pathogenesis of CAD. PMID: 30826371 [PubMed - as supplied by publisher]

Related Articles Environmental cadmium exposure induces alterations in the urinary metabolic profile of pregnant women. Int J Hyg Environ Health. 2019 Feb 27;: Authors: Li H, Huang K, Jin S, Peng Y, Liu W, Wang M, Zhang H, Zhang B, Xia W, Li Y, Lu S, Xu S Abstract Cadmium (Cd) is a well-recognized, hazardous toxic heavy metal, and the adverse effects of high-level Cd exposure on human health have been well documented. However, little is known about the health effects of low-level environmental Cd exposure on pregnant women. The objective of this study was to assess urinary metabolic alterations in pregnant women exposed to environmental Cd, and to identify informative biomarkers. Urine samples from 246 pregnant women in the first trimester of pregnancy were collected, and urinary Cd concentrations were quantified using inductively coupled plasma mass spectrometry (ICP-MS). Urinary metabolomics was analyzed by ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). Cd-related metabolic biomarkers were examined by comparing the samples of the first and third tertiles of Cd exposure classifications, using a partial least-squares discriminant (PLS-DA) model. Five putative biomarkers were identified, including L-cystine, L-tyrosine, dityrosine, histamine, and uric acid, all of which were related to oxidative stress and nephrotoxic effects induced by Cd exposure. The results show that low-level environmental Cd exposure could induce metabolite profile alterations in pregnant women, which might be associated with adverse health effects. Our findings provide new insights into the early molecular events following Cd exposure, and may be valuable for the health risk assessment of Cd exposure during pregnancy. PMID: 30826206 [PubMed - as supplied by publisher]

Metabolomics driven analysis of 11 Portulaca leaf taxa as analysed via UPLC-ESI-MS/MS and chemometrics. Phytochemistry. 2019 Feb 27;161:117-129 Authors: Farag MA, Shakour ZTA Abstract Portulaca oleracea, commonly known as purslane, is a popular plant of considerable value for its nutritive composition as well as traditional medicinal uses. P. oleracea is reported to possess neuroprotective, antimicrobial, antidiabetic, antioxidant, anti-inflammatory, antiulcerogenic, and anticancer activities. Three taxa of P. oleracea L. (P. oleracea, P. rausii and P. granulatostellulata) are grown as mixed populations in several locations in Egypt. The close morphological similarities among these taxa warrants development of methods for their correct identification or classification. We aimed in this study to assess metabolome differences among three P. oleracea taxa via ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) in the context of their genetic diversity and/or geographical origin. A total of 85 metabolites were identified including 6 amino acids, 22 phenolic compounds, 16 alkaloids, and 11 fatty acids characterized based on their MSn and UV spectra. Methoxylated flavone glycosides, O-flavonoids, C-flavonoids and four previously undescribed cyclodopa alkaloids are reported in P. oleracea for the first time. Multivariate data analyses were used for samples classification and revealing that cyclodopa alkaloids (oleracein A, C, K and N) contributed the most for accessions classification. To the best of our knowledge, this study presents the first metabolite profile of Portulaca and its compositional differences that provide chemical based evidence for its nutritive and/or health benefits. PMID: 30825706 [PubMed - as supplied by publisher]

Related Articles The role of neurotransmitters and neuromodulators in the pathogenesis of cluster headache: a review. Neurol Sci. 2019 Mar 02;: Authors: D'Andrea G, Gucciardi A, Perini F, Leon A Abstract The pathogenesis underlying cluster headache remains an unresolved issue. Although both the autonomic system and the hypothalamus play a central role, the modality of their involvement remains largely unknown. It is, also, unknown why the duration of the pain attacks is so brief and why their onset and termination are abrupt and extremely painful. This review summarizes the evidence to date accumulated in favor of a possible role of anomalies in the metabolism of tyrosine, tryptophan, and arginine in these unresolved issues. PMID: 30825019 [PubMed - as supplied by publisher]

Related Articles Time-resolved decoding of metabolic signatures of in vitro growth of the hemibiotrophic pathogen Colletotrichum sublineolum. Sci Rep. 2019 Mar 01;9(1):3290 Authors: Tugizimana F, Djami-Tchatchou AT, Fahrmann JF, Steenkamp PA, Piater LA, Dubery IA Abstract Metabolomics has emerged as a powerful approach to comprehensively interrogate cellular biochemistry. As such, we applied an untargeted liquid chromatography-mass spectrometry metabolomic strategy to elucidate metabolome changes in the anthracnose-causing hemibiotrophic sorghum pathogen, Colletotrichum sublineolum. An in vitro batch culture study model with different carbon sources, glucose, arabinose and rhamnose, were used to support fungal growth over a period of twelve days. Metabolites representing the intracellular and extracellular (secreted) metabolomes were extracted with methanol and subjected to LC-MS analyses. Chemometric modelling revealed a metabolic variation trajectory, comprising three distinct stages that metabolically describe the adaptation of the fungus to diminishing nutrients. Selected marker gene expression indicated stage one (0-3 d.p.i) as corresponding to the early logarithmic phase. Stage two can be interpreted as an intermediate transitionary stage with stage three corresponding to the stationary phase (9-12 d.p.i). Stage one was characterised by up-regulation of endo-metabolites such as ferricrocin, fatty acids and flavone-conjugates, while stage three was characterised by the secretion of phytotoxins, including colletotrichin and colletotric acid. Ultimately, results from our in vitro model reveal previously unknown insights into the dynamic aspects of metabolome reprogramming in the growth phases of Colletotrichum spp as determined by nutrients obtainable from plant cell walls. PMID: 30824820 [PubMed - in process]

Related Articles Luigi Maiuri: un Grande Uomo - a Great Spirit. Cell Death Dis. 2019 Mar 01;10(3):209 Authors: Piacentini M, Kroemer G Abstract PMID: 30824687 [PubMed - in process]

Related Articles Twenty Years on: Metabolomics in Helminth Research. Trends Parasitol. 2019 Feb 26;: Authors: Kokova D, Mayboroda OA Abstract This contribution makes a critical assessment of the metabolomics application to helminthic infection research. To ensure a cross-comparison of the results published by different laboratories over a period of almost two decades, we restrict the discussion to only the publications where nuclear magnetic resonance (NMR) spectroscopy is used as the analytical platform. We review the metabolites consistently reported for the body fluids of animals infected with the parasitic helminths and the characteristic metabolic patterns, arguing that the field needs a complete integration of metabolomics into research lines that examine host-helminth interactions. PMID: 30824203 [PubMed - as supplied by publisher]

Related Articles Transcriptomic and metabolomic analysis of ZmYUC1 mutant reveals the role of auxin during early endosperm formation in maize. Plant Sci. 2019 Apr;281:133-145 Authors: Bernardi J, Battaglia R, Bagnaresi P, Lucini L, Marocco A Abstract Kernel size in cereal is an important agronomic trait controlled by the interaction of genetic and environmental factors. The endosperm occupies most of the kernel area; for this reason, the endosperm cells dimension, number and metabolic content strongly influence kernel properties. This paper presents the transcriptomic and metabolomic analysis of the maize defective endosperm 18 (de18) mutant, where auxin accumulation in the endosperm is impaired. This mutation, involving the ZmYuc1 gene, leads to a reduced kernel size compared to the wild-type line B37. Our results mainly indicate that IAA concentration controls sugar and protein metabolism during kernel differentiation and it is necessary for BETL formation. Furthermore, a fine tuning of different auxin conjugates is reported as the main mechanism to counteract the auxin deficit. Some candidates as master regulators of endosperm transcriptional regulation mediated by auxin are found between MYB and MADS-box gene families. A link between auxin and storage protein accumulation is highlighted, suggesting that IAA directly or indirectly, through CK or ABA, regulates the transcription of zein coding genes. This study represents a move forward with respect to the current knowledge about the role of auxin during maize endosperm differentiation thus revealing the genes that are modulated by auxin and that control agronomic traits as kernel size and metabolic composition. PMID: 30824046 [PubMed - in process]

Related Articles Metabolomics analysis of a mouse model for chronic exposure to ambient PM2.5. Environ Pollut. 2019 Apr;247:953-963 Authors: Xu Y, Wang W, Zhou J, Chen M, Huang X, Zhu Y, Xie X, Li W, Zhang Y, Kan H, Ying Z Abstract Chronic ambient fine particulate matter (PM2.5) exposure correlates with various adverse health outcomes. Its impact on the circulating metabolome-a comprehensive functional readout of the interaction between an organism's genome and environment-has not however been fully understood. This study thus performed metabolomics analyses using a chronic PM2.5 exposure mouse model. C57Bl/6J mice (female) were subjected to inhalational concentrated ambient PM2.5 (CAP) or filtered air (FA) exposure for 10 months. Their sera were then analyzed by liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). These analyses identified 2570 metabolites in total, and 148 of them were significantly different between FA- and CAP-exposed mice. The orthogonal partial least-squares discriminant analysis (OPLS-DA) and heatmap analyses displayed evident clustering of FA- and CAP-exposed samples. Pathway analyses identified 6 perturbed metabolic pathways related to amino acid metabolism. In contrast, biological characterization revealed that 71 differential metabolites were related to lipid metabolism. Furthermore, our results showed that CAP exposure increased stress hormone metabolites, 18-oxocortisol and 5a-tetrahydrocortisol, and altered the levels of circadian rhythm biomarkers including melatonin, retinal and 5-methoxytryptophol. PMID: 30823350 [PubMed - in process]

Adropin treatment restores cardiac glucose oxidation in pre-diabetic obese mice. J Mol Cell Cardiol. 2019 Feb 26;: Authors: Thapa D, Xie B, Zhang M, Stoner MW, Manning JR, Huckestein BR, Edmunds LR, Mullett SJ, McTiernan CF, Wendell SG, Jurczak MJ, Scott I Abstract Exposure to a high fat (HF) diet promotes increased fatty acid uptake, fatty acid oxidation and lipid accumulation in the heart. These maladaptive changes impact cellular energy metabolism and may promote the development of cardiac dysfunction. Attempts to increase cardiac glucose utilization have been proposed as a way to reverse cardiomyopathy in obese and diabetic individuals. Adropin is a nutrient-regulated metabolic hormone shown to promote glucose oxidation over fatty acid oxidation in skeletal muscle homogenates in vitro. The focus of the current study was to investigate whether adropin can regulate substrate metabolism in the heart following prolonged exposure to a HF diet in vivo. Mice on a long-term HF diet received serial intraperitoneal injections of vehicle or adropin over three days. Cardiac glucose oxidation was significantly reduced in HF animals, which was rescued by acute adropin treatment. Significant decreases in cardiac pyruvate dehydrogenase activity were observed in HF animals, which were also reversed by adropin treatment. In contrast to previous studies, this change was unrelated to Pdk4 expression, which remained elevated in both vehicle- and adropin-treated HF mice. Instead, we show that adropin modulated the expression of the mitochondrial acetyltransferase enzyme GCN5L1, which altered the acetylation status and activity of fuel metabolism enzymes to favor glucose utilization. Our findings indicate that adropin exposure leads to increased cardiac glucose oxidation under HF conditions, and may provide a future therapeutic avenue in the treatment of diabetic cardiomyopathy. PMID: 30822408 [PubMed - as supplied by publisher]

Assessment of NAD+metabolism in human cell cultures, erythrocytes, cerebrospinal fluid and primate skeletal muscle. Anal Biochem. 2019 Feb 26;: Authors: Demarest TG, Truong GTD, Lovett J, Mohanty JG, Mattison JA, Mattson MP, Ferrucci L, Bohr VA, Moaddel R Abstract The reduction-oxidation state of NAD+/NADH is critical for cellular health with NAD+ and its metabolites playing critical roles in aging and pathologies. Given the inherent autooxidation of reduced dinucleotides (i.e. NADH/NADPH), and the well-established differential stability, the accurate measurement of NAD+ and its metabolites is technically challenging. Moreover, sample processing, normalization and measurement strategies can profoundly alter results. Here we developed a rapid and sensitive liquid chromatography mass spectrometry-based method to quantify the NAD+ metabolome with careful consideration of these intrinsic chemical instabilities. Utilizing this method we assess NAD+ metabolite stabilities and determine the presence and concentrations of NAD+ metabolites in clinically relevant human samples including cerebrospinal fluid, erythrocytes, and primate skeletal muscle. PMID: 30822397 [PubMed - as supplied by publisher]

Serum metabolomics analysis of the effect of exercise on nonalcoholic fatty liver disease. Endocr Connect. 2019 Mar 01;: Authors: Li J, Zhao Y, Huang C, Chen Z, Shi X, Li L, Chen Z, Li X Abstract OBJECTIVE: Exercise benefits people with nonalcoholic fatty liver disease (NAFLD). The aim of this study was to identify a panel of biomarkers and to provide the possible mechanism for the effect of exercise on NAFLD patients via an untargeted mass spectrometry-based serum metabolomics study. METHODS: NAFLD patients were classified randomly into a control group (n=74) and a 6-month vigorous exercise (n=68) group. Differences in serum metabolic profiles were analyzed using untargeted ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to validate differences between these two groups, and altered metabolites were obtained by ANOVA (fold change<2, P<0.05) and identified with the online database Metlin and an in-house database. RESULTS: Metabolic profiling and multiple statistical analyses of the serum samples indicated significant differences between the NAFLD patients in the control and the 6-month vigorous exercise groups. Finally, 36 metabolites were identified between the control vs exercise groups. These metabolites were mainly associated with glycerophospholipid- and sphingolipid-related pathways. CONCLUSION: Our study demonstrates that glycerophospholipid and sphingolipid alterations may contribute to the mechanism underlying the effect of exercise on NAFLD patients. A LC-MS-based metabolomics approach has potential value for screening exercise-induced biomarkers. PMID: 30822271 [PubMed - as supplied by publisher]

Related Articles Impact of primary carbon sources on microbiome shaping and biotransformation of pharmaceuticals and personal care products. Biodegradation. 2019 Feb 28;: Authors: Rossmassler K, Kim S, Broeckling CD, Galloway S, Prenni J, De Long SK Abstract Knowledge of the conditions that promote the growth and activity of pharmaceutical and personal care product (PPCP)-degrading microorganisms within mixed microbial systems are needed to shape microbiomes in biotreatment reactors and manage process performance. Available carbon sources influence microbial community structure, and specific carbon sources could potentially be added to end-of-treatment train biotreatment systems (e.g., soil aquifer treatment [SAT]) to select for the growth and activity of a range of microbial phylotypes that collectively degrade target PPCPs. Herein, the impacts of primary carbon sources on PPCP biodegradation and microbial community structure were explored to identify promising carbon sources for PPCP biotreatment application. Six types of primary carbon sources were investigated: casamino acids, two humic acid and peptone mixtures (high and low amounts of humic acid), molasses, an organic acids mixture, and phenol. Biodegradation was tracked for five PPCPs (diclofenac, 5-fluorouracil, gemfibrozil, ibuprofen, and triclosan). Primary carbon sources were found to differentially impact microbial community structures and rates and efficiencies of PPCP biotransformation. Of the primary carbon sources tested, casamino acids, organic acids, and phenol showed the fastest biotransformation; however, on a biomass-normalized basis, both humic acid-peptone mixtures showed comparable or superior biotransformation. By comparing microbial communities for the different primary carbon sources, abundances of unclassified Beijerinckiaceae, Beijerinckia, Sphingomonas, unclassified Sphingomonadaceae, Flavobacterium, unclassified Rhizobiales, and Nevskia were statistically linked with biotransformation of specific PPCPs. PMID: 30820709 [PubMed - as supplied by publisher]

Related Articles Identification of potential human urinary biomarkers for tomato juice intake by mass spectrometry-based metabolomics. Eur J Nutr. 2019 Feb 28;: Authors: Hövelmann Y, Jagels A, Schmid R, Hübner F, Humpf HU Abstract PURPOSE: Dietary biomarkers allow the accurate and objective determination of the dietary intake of humans and can thus be valuable for investigating the relation between consumption of foods and biochemical as well as physiological responses. The objective of this study was the identification of potential urinary biomarkers for consumption of tomato juice. METHODS: In the course of a dietary intervention study, the human urine metabolome of a study cohort was compared between a tomato-free diet and after intake of tomato juice by application of an LC-HRMS-based metabolomics approach. The data acquisition was achieved using an orbitrap mass spectrometer, followed by multistage data processing and univariate as well as multivariate statistical analysis to identify discriminating features. RESULTS: Statistical analysis revealed several unique features detectable after tomato juice intake. The most discriminating markers were putatively identified as hydroxylated and sulfonated metabolites of esculeogenin B, aglycone of the steroidal glycoalkaloid esculeoside B recently found in tomato juice. Furthermore, the β-carboline alkaloids tangutorid E and F and glucuronidated derivatives thereof were identified in urine. CONCLUSIONS: Steroidal glycoalkaloids in tomato juice are cleaved after ingestion, and hydroxylated and sulfonated metabolites of their aglycones might serve as urinary biomarkers for tomato juice intake. Similarly, β-carboline alkaloids and glucuronidated derivatives were identified as potential urinary biomarkers. Both the aglycones of the steroidal alkaloids and the β-carboline alkaloids might exhibit biological activities worth investigating. PMID: 30820652 [PubMed - as supplied by publisher]

Related Articles Metabolic characteristics revealing cell differentiation of nasopharyngeal carcinoma by combining NMR spectroscopy with Raman spectroscopy. Cancer Cell Int. 2019;19:37 Authors: Chen Y, Chen Z, Su Y, Lin D, Chen M, Feng S, Zou C Abstract Background: The staging system of nasopharyngeal carcinoma (NPC) has close relationship with the degree of cell differentiation, but most NPC patients remain undiagnosed until advanced phases. Novel metabolic markers need to be characterized to support diagnose at an early stage. Methods: Metabolic characteristics of nasopharyngeal normal cell NP69 and two types of NPC cells, including CNE1 and CNE2 associated with high and low differentiation degrees were studied by combining 1H NMR spectroscopy with Raman spectroscopy. Statistical methods were also utilized to determine potential characteristic metabolites for monitoring differentiation progression. Results: Metabolic profiles of NPC cells were significantly different according to differentiation degrees. Various characteristic metabolites responsible for different differentiated NPC cells were identified, and then disordered metabolic pathways were combed according to these metabolites. We found disordered pathways mainly included amino acids metabolisms like essential amino acids metabolisms, as well as altered lipid metabolism and TCA cycle, and abnormal energy metabolism. Thus our results provide evidence about close relationship between differentiation degrees of NPC cells and the levels of intracellular metabolites. Moreover, Raman spectrum analysis also provided complementary and confirmatory information about intracellular components in single living cells. Eight pathways were verified to that in NMR analysis, including amino acids metabolisms, inositol phosphate metabolism, and purine metabolism. Conclusions: Methodology of NMR-based metabolomics combining with Raman spectroscopy could be powerful and straightforward to reveal cell differentiation development and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and therapeutic evaluation. PMID: 30820190 [PubMed]

Related Articles compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC-MS Data Sets. Anal Chem. 2017 04 04;89(7):3919-3928 Authors: Edmands WM, Petrick L, Barupal DK, Scalbert A, Wilson MJ, Wickliffe JK, Rappaport SM Abstract A long-standing challenge of untargeted metabolomic profiling by ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is efficient transition from unknown mass spectral features to confident metabolite annotations. The compMS2Miner (Comprehensive MS2 Miner) package was developed in the R language to facilitate rapid, comprehensive feature annotation using a peak-picker-output and MS2 data files as inputs. The number of MS2 spectra that can be collected during a metabolomic profiling experiment far outweigh the amount of time required for pain-staking manual interpretation; therefore, a degree of software workflow autonomy is required for broad-scale metabolite annotation. CompMS2Miner integrates many useful tools in a single workflow for metabolite annotation and also provides a means to overview the MS2 data with a Web application GUI compMS2Explorer (Comprehensive MS2 Explorer) that also facilitates data-sharing and transparency. The automatable compMS2Miner workflow consists of the following steps: (i) matching unknown MS1 features to precursor MS2 scans, (ii) filtration of spectral noise (dynamic noise filter), (iii) generation of composite mass spectra by multiple similar spectrum signal summation and redundant/contaminant spectra removal, (iv) interpretation of possible fragment ion substructure using an internal database, (v) annotation of unknowns with chemical and spectral databases with prediction of mammalian biotransformation metabolites, wrapper functions for in silico fragmentation software, nearest neighbor chemical similarity scoring, random forest based retention time prediction, text-mining based false positive removal/true positive ranking, chemical taxonomic prediction and differential evolution based global annotation score optimization, and (vi) network graph visualizations, data curation, and sharing are made possible via the compMS2Explorer application. Metabolite identities and comments can also be recorded using an interactive table within compMS2Explorer. The utility of the package is illustrated with a data set of blood serum samples from 7 diet induced obese (DIO) and 7 nonobese (NO) C57BL/6J mice, which were also treated with an antibiotic (streptomycin) to knockdown the gut microbiota. The results of fully autonomous and objective usage of compMS2Miner are presented here. All automatically annotated spectra output by the workflow are provided in the Supporting Information and can alternatively be explored as publically available compMS2Explorer applications for both positive and negative modes ( https://wmbedmands.shinyapps.io/compMS2_mouseSera_POS and https://wmbedmands.shinyapps.io/compMS2_mouseSera_NEG ). The workflow provided rapid annotation of a diversity of endogenous and gut microbially derived metabolites affected by both diet and antibiotic treatment, which conformed to previously published reports. Composite spectra (n = 173) were autonomously matched to entries of the Massbank of North America (MoNA) spectral repository. These experimental and virtual (lipidBlast) spectra corresponded to 29 common endogenous compound classes (e.g., 51 lysophosphatidylcholines spectra) and were then used to calculate the ranking capability of 7 individual scoring metrics. It was found that an average of the 7 individual scoring metrics provided the most effective weighted average ranking ability of 3 for the MoNA matched spectra in spite of potential risk of false positive annotations emerging from automation. Minor structural differences such as relative carbon-carbon double bond positions were found in several cases to affect the correct rank of the MoNA annotated metabolite. The latest release and an example workflow is available in the package vignette ( https://github.com/WMBEdmands/compMS2Miner ) and a version of the published application is available on the shinyapps.io site ( https://wmbedmands.shinyapps.io/compMS2Example ). PMID: 28225587 [PubMed - indexed for MEDLINE]

22 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 2019/03/01PubMed 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.