A ternary solvent system-based air-assisted liquid-liquid microextraction procedure was developed for the extraction of three surfactants from exhaled breath condensate samples prior to their determination by high performance liquid chromatography-tandem mass spectrometry. In this approach, different deep eutectic solvents were synthesized based on phosphocholine chloride and fatty acids and their mixtures were used as the extraction solvents to effective extraction of the analytes. To obtain the optimum composition of the extraction solvents, a simplex centroid design approach was used. Then the effective parameters were studied by response surface methodology using central composite design. The obtained data after optimization showed that 6 times was the best extraction time for the developed procedure. When the sample solution pH was adjusted at 3.7, the method reached to higher extraction efficiency which can be related to the fact that the analytes were in the protonated forms. Increasing the sample solution temperature up to 50 °C enhanced the migration rate of the analytes into the extraction solvent and the method efficacy was increased. Also addition of sodium chloride at 2.8% (w/v) had a positive effect on the method efficiency which can be related to decreasing the analytes solubility in the sample solution. Under optimal conditions, the method showed satisfactory coefficient of determination (≥0.9979), low limit of detection (0.12-0.23 ng mL) and quantification (0.39-0.76 ng mL), acceptable repeatability in deionized water (relative standard deviation ≤ 8.2%) and in exhaled breath condensate (relative standard deviation ≤ 7.2%), and acceptable extraction recovery (75-86%) and enrichment factor (71-86). Considering these results, the developed method provided a quick and efficient way to determine surfactants in the exhaled breath condensate collected from expiratory circuit of the mechanical ventilator. It can be used in drug monitoring and clinical studies.

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http://dx.doi.org/10.1016/j.jchromb.2022.123289DOI Listing

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