化学学报 ›› 2008, Vol. 66 ›› Issue (8): 947-952. 上一篇    下一篇

研究论文

荧光动力学二阶校正法定量分析人血浆样中去甲肾上腺素

李淑芳,吴海龙*,夏阿林,朱绍华,聂瑾芳,边英超,刘佳,俞汝勤   

  1. (湖南大学化学化工学院 化学生物传感与计量学国家重点实验室 长沙 410082)
  • 投稿日期:2007-06-25 修回日期:2007-11-15 发布日期:2008-04-28
  • 通讯作者: 吴海龙

Quantitative Analysis of Noradrenaline in Human Plasma Samples Using Kinetic Fluorometric Methods Coupled with Second-Order Calibration

LI Shu-Fang WU Hai-Long* XIA A-Lin ZHU Shao-Hua NIE Jin-Fang BIAN Ying-Chao LIU Jia YU Ru-Qin   

  1. (State Key Laboratory for Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082)
  • Received:2007-06-25 Revised:2007-11-15 Published:2008-04-28
  • Contact: WU Hai-Long

提出了荧光动力学结合二阶校正算法实现人血浆样中去甲肾上腺素的间接定量测定新方法. 去甲肾上腺素本身荧光较弱, 在碱性溶液中可以被氧化生成强荧光化合物. 利用这一特性, 在pH值为9.06的硼酸缓冲液作用下采用铁氰化钾为氧化剂、抗坏血酸为抗氧化剂研究这一氧化反应过程. 设定激发波长为390 nm, 在发射波长为439~550 nm的范围内测定一段时间内连续时间点的该动力学反应中间物的荧光光谱, 构建三维响应数据阵, 然后运用三线性分解算法进行解析. 组分数N取3时, 采用基于平行因子分析(PARAFAC)算法的二阶校正法获得的平均回收率(AR)为(102.0±4.1)%, 预测残差平方根(RMSEP)为0.0197; 采用基于满秩平行因子分析(FRA-PARAFAC)算法的二阶校正法获得的平均回收率(AR)和预测残差平方根(RMSEP)分别为(102.4±4.0)%和0.0207. 两种算法可以得到相似且满意的结果.

关键词: 去甲肾上腺素, 反应动力学, 荧光定量测定, 三线性分解, 二阶校正, 平行因子分析(PARAFAC), 满秩平行因子分析(FRA-PARAFAC)

A novel method for quantitative analysis of noradrenaline in human plasma samples by combining kinetic fluorescence spectra with second-order calibration based on the alternating least-squares principle was proposed. Noradrenaline, a weak fluorescent substance, can be transformed into a highly fluorescent product by oxidation in alkaline solution. This paper studied the oxidation of noradrenaline by reaction with potassium hexacyanoferrate(III) in the presence of boric buffer (pH 9.06) and ascorbic acid. Fluorescence spectra were measured at consecutive time points in an emission range of 439~550 nm for every sample when a constant 390 nm excitation wavelength was used, hence, creating a three-way response data array which was then analyzed by trilinear decomposition method. Second-order calibration methods based on parallel factor analysis (PARAFAC) and full rank parallel factor analysis (FRA-PARAFAC) algorithms were employed for the quantification of noradrenaline in human plasma samples. The results for PARAFAC and FRA-PARAFAC were very similar with average recovery (AR) and root-mean-squared error of prediction (RMSEP). When the component number was chosen to 3, the obtained average recoveries were (102.0±4.1)% for PARAFAC and (102.4±4.0)% for FRA-PARAFAC, respectively. The root-mean-squared errors of prediction were 0.0197 for PARAFAC and 0.0207 for FRA-PARAFAC, respectively.

Key words: noradrenaline, kinetic fluorometric method, trilinear decomposition, second-order calibration, parallel factor analysis (PARAFAC), full rank parallel factor analysis (FRA-PARAFAC)