利用单颗粒电感耦合等离子体质谱法验证监测贻贝中纳米颗粒的方法。

Are Bruvold, Stig Valdersnes, Katrin Loeschner, André Marcel Bienfait
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引用次数: 0

摘要

背景:确定海洋生物中纳米颗粒的浓度对于评估其对环境的影响和对人类健康的潜在食品安全风险非常重要:目前的工作旨在开发一种基于单颗粒电感耦合等离子体质谱的内部方法,适用于监测贻贝中的纳米颗粒:方法:利用一种新的低成本、简单的蛋白酶混合物进行样品消化,并使用一种新的开源数据处理方法,在统计基础上利用假阳性和假阴性概率确定检测限。该方法对添加到贻贝(海鲜的替代品)中的 30 纳米和 60 纳米金颗粒进行了验证:颗粒质量浓度的回收率为 76-77%,颗粒数量浓度的回收率为 94-101%。颗粒质量浓度的中间精度为 8-9%,颗粒数量浓度为 7-8%。粒径的检测限为 18 nm,浓度的检测限为 1.7 ng/g 和 4.2 x 105 颗粒/g 蚌组织:与食典标准相比,该方法的性能特征令人满意。此外,该方法还适用于贻贝中的钛、铬和铜基质颗粒:亮点:该方法展示了一种新的实用且具有成本效益的样品处理方法,以及简化、透明且可重复的数据处理方法,可用于贻贝中非蛋白氮的常规监测。
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Validation of a Method for Surveillance of Nanoparticles in Mussels Using Single-Particle Inductively Coupled Plasma-Mass Spectrometry.

Background: Determining the concentration of nanoparticles (NPs) in marine organisms is important for evaluating their environmental impact and to assess potential food safety risks to human health.

Objective: The current work aimed at developing an in-house method based on single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) suitable for surveillance of NPs in mussels.

Methods: A new low-cost and simple protease mixture was utilized for sample digestion, and novel open-source data processing was used, establishing detection limits on a statistical basis using false-positive and false-negative probabilities. The method was validated for 30 and 60 nm gold NPs spiked to mussels as a proxy for seafood.

Results: Recoveries were 76-77% for particle mass concentration and 94-101% for particle number concentration. Intermediate precision was 8-9% for particle mass concentration and 7-8% for particle number concentration. The detection limit for size was 18 nm, for concentration 1.7 ng/g, and 4.2 × 105 particles/g mussel tissue.

Conclusion: The performance characteristics of the method were satisfactory compared with numeric Codex criteria. Further, the method was applied to titanium-, chromium- and copper-based particles in mussels.

Highlights: The method demonstrates a new practical and cost-effective sample treatment, and streamlined, transparent, and reproducible data treatment for the routine surveillance of NPs in mussels.

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