x射线荧光光谱法分析长效杀虫蚊帐中杀虫剂及其与生物功效的相关性

Melanie Koinari, Nakei Bubun, David Wilson, Evodia Anetul, Lincoln Timinao, Petrina Johnson, Norelle L. Daly, Moses Laman, Tim Freeman, Stephan Karl
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摘要

背景:长效杀虫蚊帐是用于预防疟疾的一种关键病媒控制工具。活性成分(AI)的测量是评价其质量和疗效的必要条件。本研究的主要目的是确定x射线荧光(XRF)光谱作为一种合适的现场可部署工具,用于LLINs的人工智能总量定量。方法从运往巴布亚新几内亚(PNG)的批次中提取含有溴氰菊酯(PermaNet®2.0,n = 35)和高效氯氰菊酯(SafeNet®,n = 43)的新样品和未使用的LLIN样品进行批量分配。采用简单提取技术提取杀虫剂,并采用液相色谱质谱法(LC-MS)进行定量分析。LC-MS结果与XRF光谱测量结果具有相关性。作业人员对网的类型一无所知。使用世卫组织锥体生物测定法检测LLIN样品的生物功效,检测结果与总AI含量相关。结果定量XRF与LC-MS具有良好的相关性。有趣的是,在PermaNet®2.0中,总AI含量与生物功效呈负相关(特别是在最近生产的蚊帐中)。相反,AI含量与SafeNet®的生物功效呈正相关。这些结果表明,产前检验中的化学成分分析并不总是能预测生物功效。结论x射线荧光光谱是一种很有前途的现场定量工具,可用于溴氰菊酯包被和高效氯氰菊酯包被llin的定量。由于总AI含量并不总是LLINs杀灭蚊子功效的预测指标,因此生物功效测量应包括在分娩前检查中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of insecticides in long-lasting insecticidal nets using X-ray fluorescence spectroscopy and correlation with bioefficacy
Background Long-lasting insecticidal nets (LLINs) are a key vector control tool used for the prevention of malaria. Active ingredient (AI) measurements in LLINs are essential for evaluating their quality and efficacy. The main aim of the present study was to determine the utility of X-ray fluorescence (XRF) spectroscopy as a suitable field-deployable tool for total AI quantification in LLINs. Methods New and unused LLIN samples containing deltamethrin (PermaNet® 2.0, n = 35) and alpha-cypermethrin (SafeNet®, n = 43) were obtained from batches delivered to Papua New Guinea (PNG) for mass distribution. Insecticides were extracted from the LLINs using a simple extraction technique and quantified using liquid chromatography mass spectrometry (LC-MS). The LC-MS results were correlated with XRF spectroscopy measurements on the same nets. Operators were blinded regarding the type of net. Bioefficacy of the LLIN samples was tested using WHO cone bioassays and test results were correlated with total AI content. Results The results indicate correlation between quantitative XRF and LC-MS. Interestingly, the total AI content was negatively correlated with bioefficacy in PermaNet® 2.0 (especially in recently manufactured nets). In contrast, AI content was positively correlated with bioefficacy in SafeNet®. These results indicate that the chemical content analysis in predelivery inspections does not always predict bioefficacy. Conclusion XRF is a promising field-deployable tool for quantification of both deltamethrin- and alpha-cypermethrin-coated LLINs. Because total AI content is not always a predictor of the efficacy of LLINs to kill mosquitoes, bioefficacy measurements should be included in predelivery inspections.
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