Journal
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
Volume 386, Issue 2, Pages 391-397Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s00216-006-0631-y
Keywords
automated silylation; nonylphenol; octylphenol; diethylstilbestrol; steroid hormones; water and biological samples
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A fully automated method using direct immersion solid-phase microextraction (DI-SPME) and headspace on-fiber silylation for simultaneous determinations of exogenous endocrine-disrupting chemicals (EDCs) and endogenous steroid hormones in environmental aqueous and biological samples by gas chromatography-mass spectrometry (GC-MS) was developed and compared to a previously reported manual method. Three EDCs and five endocrine steroid hormones were selected to evaluate this method. The extraction and derivatization time, ion strength, pH, incubation temperature, sample volume, and extraction solvent were optimized. Satisfactory results in pure water were obtained in terms of linearity of calibration curve (R-2=0.9932-1.0000), dynamic range (3 orders of magnitude), precision (4-9% RSD), as well as LOD (0.001-0.124 mu g L-1) and LOQ (0.004-0.413 mu g L-1), respectively. These results were similar to those obtained using a manual method, and moreover, the precision was improved. This new automated method has been applied to the determinations of target compounds in real samples used in our previous study on a manual SPME method. Exogenous octylphenol (OP), technical grade nonylphenol (t-NP), and diethylstilbestrol (DES) were at 0.13, 5.03, and 0.02 mu g L-1 in river water and 3.76, 13.25, and 0.10 mu g L-1 in fish serum, respectively. Natural steroid hormones estrone (E-1), 17 beta-estradiol (E-2), and testosterone (T) were at 0.19, 0.11, and 6.22 mu g L-1 in river water; and in female fish serum E-1, E-2, and pregnenolone (PREG) were at 1.37, 1.95, and 6.25 mu g L-1, respectively. These results were confirmed by the manual method. The developed fully automated SPME and on-fiber silylation procedures showed satisfactory applications in environmental analysis and the performances show improved precision and a reduced analysis time compared to the manual method.
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