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Development of a multi-matrix LC-MS/MS method for urea quantitation and its application in human respiratory disease studies.

Authors :
Wang J
Gao Y
Dorshorst DW
Cai F
Bremer M
Milanowski D
Staton TL
Cape SS
Dean B
Ding X
Source :
Journal of pharmaceutical and biomedical analysis [J Pharm Biomed Anal] 2017 Jan 30; Vol. 133, pp. 96-104. Date of Electronic Publication: 2016 Nov 02.
Publication Year :
2017

Abstract

In human respiratory disease studies, liquid samples such as nasal secretion (NS), lung epithelial lining fluid (ELF), or upper airway mucosal lining fluid (MLF) are frequently collected, but their volumes often remain unknown. The lack of volume information makes it hard to estimate the actual concentration of recovered active pharmaceutical ingredient or biomarkers. Urea has been proposed to serve as a sample volume marker because it can freely diffuse through most body compartments and is less affected by disease states. Here, we report an easy and reliable LC-MS/MS method for cross-matrix measurement of urea in serum, plasma, universal transfer medium (UTM), synthetic absorptive matrix elution buffer 1 (SAMe1) and synthetic absorptive matrix elution buffer 2 (SAMe2) which are commonly sampled in human respiratory disease studies. The method uses two stable-isotope-labeled urea isotopologues, [ <superscript>15</superscript> N <subscript>2</subscript> ]-urea and [ <superscript>13</superscript> C, <superscript>15</superscript> N <subscript>2</subscript> ]-urea, as the surrogate analyte and the internal standard, respectively. This approach provides the best measurement consistency across different matrices. The analyte extraction was individually optimized in each matrix. Specifically in UTM, SAMe1 and SAMe2, the unique salting-out assisted liquid-liquid extraction (SALLE) not only dramatically reduces the matrix interferences but also improves the assay recovery. The use of an HILIC column largely increases the analyte retention. The typical run time is 3.6min which allows for high throughput analysis.<br /> (Copyright © 2016 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1873-264X
Volume :
133
Database :
MEDLINE
Journal :
Journal of pharmaceutical and biomedical analysis
Publication Type :
Academic Journal
Accession number :
27825650
Full Text :
https://doi.org/10.1016/j.jpba.2016.11.001