کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1213883 966907 2011 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Development and validation of a sensitive LC/MS/MS method for the simultaneous determination of naloxone and its metabolites in mouse plasma
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
Development and validation of a sensitive LC/MS/MS method for the simultaneous determination of naloxone and its metabolites in mouse plasma
چکیده انگلیسی

A rapid, specific, and reliable LC–MS/MS based bioanalytical method was developed and validated for the simultaneous determination of naloxone (NLX) and its two metabolites, 6β-naloxol (NLL) and naloxone-3β-d-glucuronide (NLG) in mouse plasma. The optimal chromatographic behavior of these analytes was achieved on an Aquasil C18 column (50 mm × 2.1 mm, 5 μm) using reversed phase chromatography. The total LC analysis time per injection was 2.5 min with a flow rate of 1.0 mL/min with gradient elution. Sample preparation via protein precipitation with acetonitrile in a 96-well format was applied for analyses of these analytes. The analytes were monitored by electrospray ionization in positive ion multiple reaction monitoring (MRM) mode. Modification of collision energy besides chromatographic separation was applied to further eliminate interference peaks for NLL and NLG. The method validation was conducted over the curve range of 0.200/0.400/0.500 to 100/200/250 ng/mL for NLX/NLL/NLG, respectively, using 0.0250 mL of plasma sample. The intra- and inter-day precision and accuracy of the quality control samples at low, medium, and high concentration levels showed ≤6.5% relative standard deviation (RSD) and −8.3 to −2.5% relative error (RE). The method was successfully applied to determine the concentrations of NLX, NLL, and NLG in incurred mouse plasma samples.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Chromatography B - Volume 879, Issue 25, 1 September 2011, Pages 2663–2668
نویسندگان
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