Zhou Xinguang, Zhu Anwei, Shi Guoyue
School of Chemistry and Molecular Engineering, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China.
School of Chemistry and Molecular Engineering, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China.
J Chromatogr A. 2015 Aug 28;1409:125-31. doi: 10.1016/j.chroma.2015.07.040. Epub 2015 Jul 14.
Concentration of blood catecholamines (CAs) is linked to a host of cardiovascular diseases, including hypertension and stenocardia. The matrix interferences and low concentration require tedious sample pretreatment methods before quantitative analysis by the gold standard method of high-performance liquid chromatography-electrochemical detector (HPLC-ECD). Solid phase extraction (SPE) has been widely used as the pretreatment technique. Here, a facile polymeric ionic liquid (PIL)-diphenylboric acid (DPBA)-packed capillary column was prepared to selectively extract dopamine (DA), noradrenaline (NE) and epinephrine (E) prior to their quantitative analysis by a fast separation in HPLC-ECD method, while microdialysis sampling method was applied to get the analysis sample. Parameters that influenced desorption efficiency, such as pH, salt concentration, acetonitrile content and wash time, were examined and optimized. The proposed method, combining microdialysis sampling technique, SPE and HPLC-ECD system, was successfully applied to detect CAs in rat blood microdialysate with high sensitivity and selectivity in small sample volumes (5-40μl) and a short analysis time (8min), yielding good reproducibility (RSD 6.5-7.7%) and spiked recovery (91-104.4%).
血液中儿茶酚胺(CAs)的浓度与许多心血管疾病相关,包括高血压和心绞痛。由于存在基质干扰且浓度较低,在采用高效液相色谱 - 电化学检测器(HPLC - ECD)这一金标准方法进行定量分析之前,需要繁琐的样品预处理方法。固相萃取(SPE)已被广泛用作预处理技术。在此,制备了一种简便的聚合物离子液体(PIL)-二苯基硼酸(DPBA)填充毛细管柱,用于在通过HPLC - ECD方法进行快速分离定量分析之前,选择性萃取多巴胺(DA)、去甲肾上腺素(NE)和肾上腺素(E),同时采用微透析采样方法获取分析样品。考察并优化了影响解吸效率的参数,如pH值、盐浓度、乙腈含量和清洗时间。所提出的方法,结合微透析采样技术、SPE和HPLC - ECD系统,成功应用于检测大鼠血液微透析液中的CAs,在小样本体积(5 - 40μl)下具有高灵敏度和选择性,分析时间短(8分钟),重现性良好(RSD 6.5 - 7.7%),加标回收率为91 - 104.4%。