Literature DB >> 8855143

GC-MS profiling of urinary organic acids evaluated as a quantitative method.

P Duez1, A Kumps, Y Mardens.   

Abstract

We assessed the quantitative performances of a classical method for profiling urinary organic acids: ethyl acetate extraction/oxime-trimethylsilyl derivatization/GC-MS. Twenty-seven acids were quantified on the basis of specific ions in both scan and selected-ion monitoring modes. We found that the tuning of the mass detector severely affects the calibration factors, being critical to achieve quantitative results, and we propose a practical procedure for reproducible tuning. Of seven compounds tested, tropic acid was retained as the internal standard suitable for most of the acids of clinical interest; a second internal standard, 2-ketocaproic acid, was used in quantifying keto-acids. The within-day and total relative standard deviations (CVs), estimated from scan-mode analyses of urine, ranged from 2.6% to 12.7% and from 4.2% to 11.8%, respectively. Curvilinear relationships between analytical response and concentration were observed for most of the acids investigated.

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Year:  1996        PMID: 8855143

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  10 in total

1.  Assessment of an electron-impact GC-MS method for organic acids and glycine conjugates in amniotic fluid.

Authors:  A Kumps; E Vamos; Y Mardens; M Abramowicz; J Genin; P Duez
Journal:  J Inherit Metab Dis       Date:  2004       Impact factor: 4.982

Review 2.  Microbial metabolomics: replacing trial-and-error by the unbiased selection and ranking of targets.

Authors:  Mariët J van der Werf; Renger H Jellema; Thomas Hankemeier
Journal:  J Ind Microbiol Biotechnol       Date:  2005-05-14       Impact factor: 3.346

3.  Liquid-Liquid Extraction and Solid Phase Extraction for Urinary Organic Acids: A Comparative Study from a Resource Constraint Setting.

Authors:  Chandrawati Kumari; Bijo Varughese; Siddarth Ramji; Seema Kapoor
Journal:  Indian J Clin Biochem       Date:  2016-02-11

Review 4.  Review of recent developments in GC-MS approaches to metabolomics-based research.

Authors:  David J Beale; Farhana R Pinu; Konstantinos A Kouremenos; Mahesha M Poojary; Vinod K Narayana; Berin A Boughton; Komal Kanojia; Saravanan Dayalan; Oliver A H Jones; Daniel A Dias
Journal:  Metabolomics       Date:  2018-11-17       Impact factor: 4.290

5.  A Description of Reference Ranges for Organic Acids in Urine Samples from A Pediatric Population in Iran.

Authors:  Fatemeh Keyfi; Zoltan Lukacs; Abdolreza Varasteh
Journal:  Rep Biochem Mol Biol       Date:  2017-10

6.  Validation of a dual LC-HRMS platform for clinical metabolic diagnosis in serum, bridging quantitative analysis and untargeted metabolomics.

Authors:  Ilya Gertsman; Jon A Gangoiti; Bruce A Barshop
Journal:  Metabolomics       Date:  2014-04-04       Impact factor: 4.290

7.  High-resolution metabolic phenotyping of genetically and environmentally diverse potato tuber systems. Identification of phenocopies.

Authors:  U Roessner; L Willmitzer; A R Fernie
Journal:  Plant Physiol       Date:  2001-11       Impact factor: 8.340

8.  Analysis of optimal phenotypic space using elementary modes as applied to Corynebacterium glutamicum.

Authors:  Kalyan Gayen; K V Venkatesh
Journal:  BMC Bioinformatics       Date:  2006-10-12       Impact factor: 3.169

9.  Application of metabolomics: Focus on the quantification of organic acids in healthy adults.

Authors:  Dimitris Tsoukalas; Athanasios Alegakis; Persefoni Fragkiadaki; Evangelos Papakonstantinou; Dragana Nikitovic; Aikaterini Karataraki; Alexander E Nosyrev; Emmanouel G Papadakis; Demetrios A Spandidos; Nikolaos Drakoulis; Aristides M Tsatsakis
Journal:  Int J Mol Med       Date:  2017-05-10       Impact factor: 4.101

10.  Laboratory analysis of organic acids, 2018 update: a technical standard of the American College of Medical Genetics and Genomics (ACMG).

Authors:  Renata C Gallagher; Laura Pollard; Anna I Scott; Suzette Huguenin; Stephen Goodman; Qin Sun
Journal:  Genet Med       Date:  2018-03-15       Impact factor: 8.822

  10 in total

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