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      Salivary metabolomics profile of patients with recurrent aphthous ulcer as revealed by liquid chromatography–tandem mass spectrometry

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          Abstract

          Objective

          We compared the salivary nontargeted metabolite profiles between patients with recurrent aphthous ulcer (RAU) and healthy individuals to investigate the metabolic alterations associated with RAU.

          Methods

          Saliva samples were collected from 45 patients with RAU and 49 healthy individuals, and the salivary metabolites were quantified using liquid chromatography–tandem mass spectrometry. The metabolomic profiles were then analyzed using multivariate and univariate statistical methods, and enrichment of the metabolites in various biological pathways was assessed.

          Results

          In total, 206 significant differentiating metabolites (Wilcoxon test, false discovery rate [FDR] of <0.05) were identified between patients with RAU and healthy individuals. These metabolites were implicated in tryptophan metabolism, steroid hormone biosynthesis, and other metabolic pathways. Two commonly circulating steroids, estrone sulfate and dehydroepiandrosterone sulfate, were significantly lower in the saliva of patients with RAU (Wilcoxon test, FDR < 0.05, power > 0.9). Principal component analysis and partial least-squares discriminant analysis revealed metabolic perturbations involving RAU, and receiver operating characteristic curve analysis with several metabolites showed good diagnostic ability for RAU.

          Conclusions

          The results of this study indicate that patients with RAU are characterized by metabolic imbalances. Psychogenic factors, endocrinopathies, and immunosuppression may contribute to the onset of RAU.

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          Most cited references29

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          Discovery and characterization of gut microbiota decarboxylases that can produce the neurotransmitter tryptamine.

          Several recent studies describe the influence of the gut microbiota on host brain and behavior. However, the mechanisms responsible for microbiota-nervous system interactions are largely unknown. Using a combination of genetics, biochemistry, and crystallography, we identify and characterize two phylogenetically distinct enzymes found in the human microbiome that decarboxylate tryptophan to form the β-arylamine neurotransmitter tryptamine. Although this enzymatic activity is exceedingly rare among bacteria more broadly, analysis of the Human Microbiome Project data demonstrate that at least 10% of the human population harbors at least one bacterium encoding a tryptophan decarboxylase in their gut community. Our results uncover a previously unrecognized enzymatic activity that can give rise to host-modulatory compounds and suggests a potential direct mechanism by which gut microbiota can influence host physiology, including behavior. Copyright © 2014 Elsevier Inc. All rights reserved.
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            metaX: a flexible and comprehensive software for processing metabolomics data

            Background Non-targeted metabolomics based on mass spectrometry enables high-throughput profiling of the metabolites in a biological sample. The large amount of data generated from mass spectrometry requires intensive computational processing for annotation of mass spectra and identification of metabolites. Computational analysis tools that are fully integrated with multiple functions and are easily operated by users who lack extensive knowledge in programing are needed in this research field. Results We herein developed an R package, metaX, that is capable of end-to-end metabolomics data analysis through a set of interchangeable modules. Specifically, metaX provides several functions, such as peak picking and annotation, data quality assessment, missing value imputation, data normalization, univariate and multivariate statistics, power analysis and sample size estimation, receiver operating characteristic analysis, biomarker selection, pathway annotation, correlation network analysis, and metabolite identification. In addition, metaX offers a web-based interface (http://metax.genomics.cn) for data quality assessment and normalization method evaluation, and it generates an HTML-based report with a visualized interface. The metaX utilities were demonstrated with a published metabolomics dataset on a large scale. The software is available for operation as either a web-based graphical user interface (GUI) or in the form of command line functions. The package and the example reports are available at http://metax.genomics.cn/. Conclusions The pipeline of metaX is platform-independent and is easy to use for analysis of metabolomics data generated from mass spectrometry. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1579-y) contains supplementary material, which is available to authorized users.
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              ROC-ing along: Evaluation and interpretation of receiver operating characteristic curves.

              It is vital for clinicians to understand and interpret correctly medical statistics as used in clinical studies. In this review, we address current issues and focus on delivering a simple, yet comprehensive, explanation of common research methodology involving receiver operating characteristic (ROC) curves. ROC curves are used most commonly in medicine as a means of evaluating diagnostic tests.
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                Author and article information

                Journal
                J Int Med Res
                J. Int. Med. Res
                IMR
                spimr
                The Journal of International Medical Research
                SAGE Publications (Sage UK: London, England )
                0300-0605
                1473-2300
                14 January 2018
                March 2018
                : 46
                : 3
                : 1052-1062
                Affiliations
                [1 ]BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China
                [2 ]Sports Genomics Institute, BGI-Shenzhen, China
                [3 ]BGI-Shenzhen, Shenzhen, China
                [4 ]Institute of Advanced Technology, University of Science and Technology of China, Hefei, China
                Author notes
                [*]

                These authors contributed equally to this work.

                [*]Daoming Wang, BGI Education Center, University of Chinese Academy of Sciences, Building 11, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China. Email: wangdaoming15@ 123456mails.ucas.ac.cn
                Article
                10.1177_0300060517745388
                10.1177/0300060517745388
                5972264
                29332424
                e4c914d1-926d-4e59-90e1-2c4dd54dfac8
                © The Author(s) 2018

                Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 12 August 2017
                : 7 November 2017
                Categories
                Research Reports

                recurrent aphthous ulcer,saliva,metabolomics,tryptophan metabolism,hormone,liquid chromatography–tandem mass spectrometry

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