在线式中空纤维增强碳纳米纤维介导的液相微萃取，采用 3D 打印萃取平台作为液相色谱前端，实现自动样品制备和分析：概念验证研究。
In-line carbon nanofiber reinforced hollow fiber-mediated liquid phase microextraction using a 3D printed extraction platform as a front end to liquid chromatography for automatic sample preparation and analysis: A proof of concept study.
机构信息
Chemical Approaches for Food Applications Research Group, Department of Chemistry, Faculty of Science, Chulalongkorn University, Phayathai Rd., Pathumwan, Bangkok 10330, Thailand.
FI-TRACE group, Department of Chemistry, University of the Balearic Islands, Carretera de Valldemossa, km 7.5, E-07122 Palma de Mallorca, Spain.
出版信息
Talanta. 2018 Aug 1;185:611-619. doi: 10.1016/j.talanta.2018.04.007. Epub 2018 Apr 4.
A novel concept for automation of nanostructured hollow-fiber supported microextraction, combining the principles of liquid-phase microextraction (LPME) and sorbent microextraction synergically, using mesofluidic platforms is proposed herein for the first time, and demonstrated with the determination of acidic drugs (namely, ketoprofen, ibuprofen, diclofenac and naproxen) in urine as a proof-of-concept applicability. Dispersed carbon nanofibers (CNF) are immobilized in the pores of a single-stranded polypropylene hollow fiber (CNF@HF) membrane, which is thereafter accommodated in a stereolithographic 3D-printed extraction chamber without glued components for ease of assembly. The analytical method involves continuous-flow extraction of the acidic drugs from a flowing stream donor (pH 1.7) into an alkaline stagnant acceptor (20 mmol L NaOH) containing 10% MeOH (v/v) across a dihexyl ether impregnated CNF@HF membrane. The flow setup features entire automation of the microextraction process including regeneration of the organic film and on-line injection of the analyte-laden acceptor phase after downstream neutralization into a liquid chromatograph (LC) for reversed-phase core-shell column-based separation. Using a 12-cm long CNF@HF and a sample volume of 6.4 mL, linear dynamic ranges of ketoprofen, naproxen, diclofenac and ibuprofen, taken as models of non-steroidal anti-inflammatory drugs, spanned from ca. 5-15 µg L to 500 µg L with enhancement factors of 43-97 (against a direct injection of 10 µL standards into LC), and limits of detection from 1.6 to 4.3 µg L. Relative recoveries in real urine samples ranged from 97% to 105%, thus demonstrating the reliability of the automatic CNF@HF-LPME method for in-line matrix clean-up and determination of drugs in urine at therapeutically relevant concentrations.
一种新颖的自动化纳米中空纤维支撑微萃取概念，将液相微萃取（LPME）和吸附微萃取的原理协同结合，首次在中流形平台上提出，并以尿液中酸性药物（即酮洛芬、布洛芬、双氯芬酸和萘普生）的测定为例，证明了其概念适用性。将分散的碳纤维（CNF）固定在单股聚丙烯中空纤维（CNF@HF）膜的孔中，然后将其容纳在立体光刻 3D 打印的萃取室中，无需胶合部件，便于组装。分析方法涉及从流动的供体（pH 1.7）中连续流动萃取酸性药物到含有 10%甲醇（v/v）的碱性停滞受体（20 mmol L NaOH）中，跨越浸渍二己基醚的 CNF@HF 膜。流动设置完全自动化微萃取过程，包括在下游中和后在线注射含有分析物的受体相，然后将其注入液相色谱仪（LC），用于基于反相核壳柱的分离，以及有机膜的再生。使用 12 厘米长的 CNF@HF 和 6.4 毫升样品体积，酮洛芬、萘普生、双氯芬酸和布洛芬的线性动态范围，作为非甾体抗炎药的模型，从约 5-15µg L 到 500µg L 不等，增强因子为 43-97（与直接注入 10µL 标准品进入 LC 相比），检测限从 1.6 到 4.3µg L。在真实尿液样品中的相对回收率范围为 97%至 105%，因此证明了自动 CNF@HF-LPME 方法在线基质净化和治疗相关浓度下尿液中药物测定的可靠性。
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