Automated derivatization and analysis of malondialdehyde using column switching sample preparation HPLC with fluorescence detection

被引:16
作者
Lord, Heather L. [1 ]
Rosenfeld, Jack [1 ]
Raha, Sandeep [2 ]
Hamadeh, Mazen J. [3 ]
机构
[1] McMaster Univ, Dept Pathol & Mol Med, Hamilton, ON L8N 3Z5, Canada
[2] McMaster Univ, Dept Pediat, Hamilton, ON, Canada
[3] York Univ, Sch Kinesiol & Hlth Sci, Toronto, ON M3J 2R7, Canada
关键词
column-switching; derivatization; fluorescence; detection; HPLC; malondialdehyde; SOLID-PHASE MICROEXTRACTION; PERFORMANCE LIQUID-CHROMATOGRAPHY; ISCHEMIA-REPERFUSION INJURY; EXHALED BREATH CONDENSATE; OXIDATIVE STRESS; MASS-SPECTROMETRY; LIPID-PEROXIDATION; CAPILLARY-ELECTROPHORESIS; CARBONYL-COMPOUNDS; PLASMA;
D O I
10.1002/jssc.200700390
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Analyte derivatization is advantageous for the analysis of malondialdehyde (MDA) as a biomarker of oxidative stress in biological samples. Conventionally, however, derivatization is time consuming, error-prone and has limited options for automation. We have addressed these challenges for the solid phase analytical derivatization of MDA from small volume tissue homogenate samples. A manual derivatization method was first developed using Amberlite XAD-2 (12 mg) as the solid phase. Subsequently an automated column switching process was developed that provided simultaneous derivatization and extraction of the MDA-DH hydrazone product on a cartridge packed with XAD-2, followed by quantitative elution of the product to an analytical LC column (Waters NovoPak C18, 3.9 x 150 mm). The LOD was 0.02 mu g/mL and recovery was quantitative. The method was linear (r(2) >0.999) with precision < 5 % from the LOQ (0.06 mu g/mL) to at least 3 5 mu g/mL. The method was successfully applied to the analysis of small volume (30 mu L) mouse tissue homogenate samples. Endogenous levels of MDA in the tissues ranged from 20 to 40 nmol/g tissue (ca. 0.1 - 0.2 mu g/ml, homogenate). Compared to conventional MDA analyses, the current method has advantages in automation, selectivity, precision and sensitivity for analysis from very small sample volumes.
引用
收藏
页码:387 / 401
页数:15
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