New 3D-printed sorbent for extraction of steroids from human plasma preceding LC-MS analysis

In recent years, there has been an increasing worldwide interest in the use of alternative sample preparation methods that are proceeded by separation techniques. Fused deposition modeling (FDM) is a 3D printing technique that is based the consecutive layering of softened/melted thermoplastic materials. In this study, a group of natural steroids and sexual hormones - namely, aldosterone, cortisol, beta-estradiol, testosterone, dihydrotestosterone, and synthetic methyltestosterone and betamethasone were separated and determined using an optimized high-performance liquid chromatography coupled to mass spectrometry (LC-MS) method in positive ionization mode. 3D-printed sorbents were selected as the pre-concentration technique because they are generally low cost, fast, and simple to make and automate. Furthermore, the use of 3D-printed sorbents helps to minimize potential errors due to their repeatability and reproducibility, and their ability to eliminate carry over by using one printed sorbent for a single extraction of steroids from biological matrices. The extraction procedure was optimized and the parameters influencing 3D-printed Layfomm 60 (R) based sorbent and LC-MS were studied, including the type of extraction solvent used, sorption and desorption times, temperature, and the salting-out effect. To demonstrate this method's applicability for biological sample analysis, the SPME-LC-MS method was validated for its ability to simultaneously quantify endogenous steroids. This evaluation confirmed good linearity and an R-2 that was between 0.9970 and 0.9990. The recovery rates for human plasma samples were 86.34-93.6% for the studied steroids with intra- and inter-day RSDs of 1.44-7.42% and 1.44-9.46%, respectively. To our knowledge, this study is the first time that 3D-printed sorbents have been used to extract trace amounts of endogenous low-molecular-weight compounds, such as steroids, from biological samples, such as plasma. (C) 2018 Elsevier B.V. All rights reserved.