Identification Using Classification Analysis of Flunitrazepam in Necrophagous Larvae via Differential Pulse Voltammetry and Fluorescence Excitation-Emission Matrix (EEM) Spectroscopy

The use of insects to identify drugs in a cadaver has often been explored in the field of entomotoxicology. There are accurate methods; however, they require a high cost and are very time-consuming. The objective of this study was to develop two methods based on differential pulse voltammetry (DPV) and fluorescence excitation-emission matrix (EEM) spectroscopy to classify necrophagous larvae (Chrysomya megacephala, C. albiceps, Lucilia sp. and Cochliomyia macellaria) containing flunitrazepam. The voltammograms of larval extract samples were analyzed by principal component analysis (PCA), successive projection algorithm (SPA) and genetic algorithm (GA): linear and quadratic discriminant analysis (LDA and QDA). The EEM fluorescence data from larval extract samples were analyzed by 2D and parallel factor analysis (PARAFAC) with LDA. These results suggest that DPV and EEM combined with chemometrics can be used as tools for the classification of flunitrazepam in fly larvae presenting innovative applications.

昆虫毒理学（entomotoxicology）领域中，利用昆虫鉴定尸体内残留药物的研究方向已得到广泛探索。目前虽已存在精准的检测方法，但此类方法普遍存在成本高昂、耗时冗长的缺陷。本研究旨在开发两种分析手段，分别基于差分脉冲伏安法（differential pulse voltammetry, DPV）与荧光激发发射矩阵（fluorescence excitation-emission matrix, EEM）光谱法，以对含有氟硝西泮（flunitrazepam）的食尸性幼虫（necrophagous larvae）进行分类识别，所涉幼虫物种包括大头金蝇（Chrysomya megacephala）、C. albiceps、丽蝇属物种（Lucilia sp.）以及美洲钝眼蛆蝇（Cochliomyia macellaria）。
针对幼虫提取物样本的伏安图，本研究采用主成分分析（principal component analysis, PCA）、连续投影算法（successive projection algorithm, SPA）与遗传算法（genetic algorithm, GA）结合线性判别分析（linear discriminant analysis, LDA）及二次判别分析（quadratic discriminant analysis, QDA）进行建模分析；而幼虫提取物样本的EEM荧光数据，则通过二维分析与平行因子分析（parallel factor analysis, PARAFAC）结合LDA进行处理。
研究结果显示，将DPV、EEM技术与化学计量学（chemometrics）方法相结合，可作为识别蝇类幼虫体内氟硝西泮的有效工具，具备创新性应用前景。