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Extraction and Analysis of Cortisol from Human and Monkey Hair
Published on: January 24, 2014
Development and validation of a cost-effective and reliable HPLC-FLD method for cortisol determination in human hair
Mohamed A Gab-Allah1, Hyojin Hwang2, Maryam Adelipour3
1Department of Chemistry, Chungnam National University, Daejeon, Republic of Korea; Organic Analysis Laboratory, National Institute of Standards, Giza, Egypt.
Abstract:
Hair analysis is increasingly employed to assess long-term exposure to endogenous and exogenous substances, particularly steroid hormones. This study presents a simple, robust, and cost-effective high-performance liquid chromatography with fluorescence detection (HPLC-FLD) method for the determination of cortisol in human hair. Cortisol was extracted with methanol and derivatized using a sulfuric acid/ethanol (70:30, v/v) reagent at 70 °C. The sample extract was then neutralized with 1 M ammonium bicarbonate to eliminate residual acidity and purified by solid-phase extraction (SPE) cartridges. Two different SPE cartridges, including Oasis HLB and Bond Elut C18, were comparatively evaluated with respect to cortisol recovery and matrix clean-up efficiency. Derivatization parameters and chromatographic conditions were systematically optimized to maximize analytical performance. The method was validated according to ICH M10 bioanalytical guidelines over a concentration range of 5-200 pg/mg. Matrix-matched calibration exhibited excellent linearity (R2 > 0.999), with limits of detection and quantification of 1.1 and 3.5 pg/mg, respectively. Average recoveries ranged from 89% to 108%, while intra- and inter-day precision remained below 6% and 9%, respectively. Matrix effects were minimal (15.1%), and greenness assessment using four complementary metrics confirmed the environmentally favorable characteristics of the method. Overall, the proposed HPLC-FLD method provides a practical and accessible alternative to LC-MS/MS for routine hair cortisol analysis, combining simplified sample preparation, adequate sensitivity, reduced solvent consumption, and lower operational costs.

