{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T18:52:39Z","timestamp":1760986359599,"version":"build-2065373602"},"reference-count":27,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T00:00:00Z","timestamp":1594166400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100008762","name":"Genome Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008762","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Mass Spectrom"],"published-print":{"date-parts":[[2021,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Metabolomics study of a biological system often involves the analysis of many comparative samples over a period of several days or weeks. This process of long\u2010term sample runs can encounter unexpected instrument drifts such as small leaks in liquid chromatography\u2010mass spectrometry (LC\u2010MS), degradation of column performance, and MS signal intensity change. A robust analytical method should ideally tolerate these instrumental drifts as much as possible. In this work, we report a case study to demonstrate the high tolerance of differential chemical isotope labeling (CIL) LC\u2010MS method for quantitative metabolome analysis. In a study of using a rat model to examine the metabolome changes during rheumatoid arthritis (RA) disease development and treatment, over 468 samples were analyzed over a period of 15 days in three batches. During the sample runs, a small leak in LC was discovered after a batch of analyses was completed. Reanalysis of these samples was not an option as sample amounts were limited. To overcome the problem caused by the small leak, we applied a method of retention time correction to the LC\u2010MS data to align peak pairs from different runs with different degrees of leak, followed by peak ratio calculation and analysis. Herein, we illustrate that using <jats:sup>12<\/jats:sup>C\u2010\/<jats:sup>13<\/jats:sup>C\u2010peak pair intensity values in CIL LC\u2010MS as a measurement of concentration changes in different samples could tolerate the signal drifts, while using the absolute intensity values (ie, <jats:sup>12<\/jats:sup>C\u2010peak as in conventional LC\u2010MS) was not as reliable. We hope that the case study illustrated and the method of overcoming the small\u2010leak\u2010caused signal drifts can be helpful to others who may encounter this kind of situation in long\u2010term sample runs.<\/jats:p>","DOI":"10.1002\/jms.4589","type":"journal-article","created":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T20:58:51Z","timestamp":1591909131000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["High tolerance to instrument drifts by differential chemical isotope labeling LC\u2010MS: A case study of the effect of LC leak in long\u2010term sample runs on quantitative metabolome analysis"],"prefix":"10.1002","volume":"56","author":[{"given":"Deying","family":"Chen","sequence":"first","affiliation":[{"name":"State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and 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