{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:13:11Z","timestamp":1772118791073,"version":"3.50.1"},"reference-count":34,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2020,9,22]],"date-time":"2020-09-22T00:00:00Z","timestamp":1600732800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Reson in Chemistry"],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Lipid profiling by\n                    <jats:sup>1<\/jats:sup>\n                    H\u2010NMR has gained increasing utility in many fields because of its intrinsically quantitative, nondestructive nature and the ability to differentiate small molecules based on their spectral location. Most nuclear magnetic resonance (NMR) techniques for metabolite quantification use frequency domain analysis that involves many user\u2010dependent steps such as phase and baseline correction and quantification by either manual integration or peak fitting. Recently, Bayesian analysis of time\u2010domain NMR data has been shown to reduce operator bias and increase automation in NMR spectroscopy. In this study, we demonstrate the use of CRAFT (complete reduction to amplitude\u2013frequency table), a Bayesian\u2010based approach to automate processing in NMR\u2010based lipidomics using lipid standards and tissue samples of healthy and tumor\u2010bearing mice supplemented with leucine. Complex mixtures of lipid standards were prepared and examined using CRAFT to validate it against conventional Fourier transform (FT)\u2010NMR and derive a fingerprint to be used for analyzing lipid profiles of serum and liver samples. CRAFT and FT\u2010NMR were comparable in accuracy, with CRAFT achieving higher correlation in quantifying several lipid species. Analysis of the serum lipidome of tumor\u2010bearing mice revealed hyperlipidemia and no signs of hepatic triglyceride accumulation compared with that of the healthy group demonstrating that the tumor\u2010bearing mice were in a state of precachexia. Leucine\u2010supplementation was associated with minimal changes in the lipid profile in both tissues. In conclusion, our study demonstrates that the CRAFT method can accurately identify and quantify lipids in complex lipid mixtures and murine tissue samples and, hence, will increase automation and reproducibility in NMR\u2010based lipidomics.\n                  <\/jats:p>","DOI":"10.1002\/mrc.5092","type":"journal-article","created":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T03:20:12Z","timestamp":1600831212000},"page":"138-146","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["CRAFT for NMR lipidomics: Targeting lipid metabolism in leucine\u2010supplemented tumor\u2010bearing mice"],"prefix":"10.1002","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9945-195X","authenticated-orcid":false,"given":"Hayden","family":"Johnson","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering The University of Memphis  Memphis TN USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3826-0003","authenticated-orcid":false,"given":"Melissa","family":"Puppa","sequence":"additional","affiliation":[{"name":"College of Health Sciences The University of Memphis  Memphis TN USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5683-4790","authenticated-orcid":false,"given":"Marie","family":"van der Merwe","sequence":"additional","affiliation":[{"name":"College of Health Sciences The University of Memphis  Memphis TN USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3246-8711","authenticated-orcid":false,"given":"Aaryani","family":"Tipirneni\u2010Sajja","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering The University of Memphis  Memphis TN USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,9,22]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.analchem.7b04148"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.3390\/metabo10010009"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/molecules22101663"},{"key":"e_1_2_7_5_1","doi-asserted-by":"crossref","DOI":"10.1007\/s11306-018-1360-x","volume":"14","author":"Marchand J.","year":"2018","journal-title":"Metabolomics"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cbi.2014.06.029"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.plipres.2017.09.003"},{"key":"e_1_2_7_8_1","volume-title":"Guideline For qNMR Analysis","author":"Schoenberger T.","year":"2020"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trac.2012.02.007"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2364(90)90287-J"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.3390\/ht8010002"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/metabo10040155"},{"key":"e_1_2_7_13_1","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1016\/0022-2364(90)90288-K","volume":"88","author":"Bretthorst G. 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