{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T14:34:33Z","timestamp":1747146873304,"version":"3.40.5"},"reference-count":33,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2021,4,9]],"date-time":"2021-04-09T00:00:00Z","timestamp":1617926400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["iubmb.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BioFactors"],"published-print":{"date-parts":[[2021,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Diabetes is considered one of the most important health emergencies worldwide and Egypt has 8.2 million diabetic patients according to the International Diabetes Federation report in 2017. The objective of this study was to monitor the time\u2010course variation in the metabolic profile of diabetic rats to detect urinary metabolic biomarkers using the metabolomics approach. Type 2 diabetes was induced in male Wistar albino rats using a single intraperitoneal injection of 40\u2009mg\/kg of streptozotocin following oral administration of 10% fructose in drinking water for 3\u2009weeks. Then, urine was collected for 24\u2009h from rats at three time points (0, 2, and 4\u2009weeks after confirmation of diabetes), and were analyzed by nuclear magnetic resonance (H<jats:sup>1<\/jats:sup>\u2010NMR), followed by multivariate data analysis. The results from H<jats:sup>1<\/jats:sup>\u2010NMR pointed out that <jats:sc>d<\/jats:sc>\u2010glucose, taurine, <jats:sc>l<\/jats:sc>\u2010carnitine, <jats:sc>l<\/jats:sc>\u2010fucose, 1,5\u2010anhydrosorbitol, and <jats:sc>d<\/jats:sc>\u2010galactose levels showed consistent significant variation (<jats:italic>p<\/jats:italic>\u00a0&lt;\u20090.05) between the positive (diabetic) and negative (normal) controls during the whole experimental period. Also, with the disease progression, myoinositol, and <jats:sc>l<\/jats:sc>\u2010phenylalanine levels were significantly altered (<jats:italic>p<\/jats:italic>\u00a0&lt;\u20090.05) after 2\u2009weeks and this alteration was maintained till the end of the 4\u2010week experimental period in the positive control group. From the results of the present study, it could be concluded that we cannot depend only on glucose levels for prognostic purposes since there are other metabolic disturbances in diabetes which need to be tracked for better disease prognosis.<\/jats:p>","DOI":"10.1002\/biof.1731","type":"journal-article","created":{"date-parts":[[2021,4,9]],"date-time":"2021-04-09T16:25:54Z","timestamp":1617985554000},"page":"645-657","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Time\u2010based investigation of urinary metabolic markers for Type 2 diabetes: Metabolomics approach for diabetes management"],"prefix":"10.1002","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2367-7327","authenticated-orcid":false,"given":"Moataz M.","family":"Hanafy","sequence":"first","affiliation":[{"name":"Therapeutic Chemistry Department, Pharmaceutical and Drug Industries Research Division National Research Centre  Cairo 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