Determination of fenthion in urine samples using molecularly imprinted nanoparticles: modelling and optimisation by response surface methodology

In the present study, a molecularly imprinted solid-phase extraction (MISPE) technique coupled with high-performance liquid chromatography was applied for selective extraction and recognition of fenthion insecticide in the biological sample. The nanoparticles of fenthion imprinted polymer were prepared by precipitation polymerisation using methacrylic acid (MAA) as functional monomer, ethylene glycol dimethacrylate (EGDMA) as cross-linker, and 70 mL of chloroform. Morphological and structural characterisation was achieved by scanning electron microscopy and infrared spectrometry. The optimisation of parameters being effective on extraction yield was carried out by employing the central composite design (CCD). The empirical models were developed to link the output response and input variables and the proposed models were tested for significance through analysis of variance (ANOVA). The optimum conditions leading to the maximum efficiency of MISPE were sorbent mass of 8.61 mg, sample pH 4.93, sample flow rate of 2.07 mLmin(-1), as well as 1.94 mL of methanol/acetic acid (95.7:4.3, v/v) at the flow rate of 1 mLmin(-1)as elution solvent. Under the optimised conditions, a linear range of 20-120 mu gL(-1)was obtained and the limit of detection was found to be 4.58 mu gL(-1). Analysis of spiked urine samples demonstrated the satisfactory efficiency of the designed protocol ranging from 92.69 to 95.64% and the relative standard deviation (RSD) was calculated to be lower than 3.75%.

Automated summary

In this study, a molecularly imprinted solid-phase extraction (MISPE) technique coupled with high-performance liquid chromatography was used to selectively extract and recognize fenthion insecticide in biological samples. The optimized conditions for maximum extraction efficiency were determined and applied to spiked urine samples, resulting in satisfactory efficiency and low relative standard deviation. The developed method provides a promising approach for the analysis of fenthion insecticide in biological samples.