Maffeis Viviana, Otter Andrea, Düsterloh André, Kind Lucy, Palivan Cornelia, Saxer Sina S
University of Basel, Department of Chemistry, Mattenstrasse 22, 4002 Basel BS, Switzerland.
NCCR-Molecular Systems Engineering, 4002 Basel, Switzerland.
ACS Omega. 2024 Apr 9;9(16):17966-17976. doi: 10.1021/acsomega.3c09459. eCollection 2024 Apr 23.
The addition of nanomaterials to improve product properties has become a matter of course for many commodities: e.g., detergents, cosmetics, and food products. While this practice improves product characteristics, the increasing exposure and potential impact of nanomaterials (<100 nm) raise concerns regarding both the human body and the environment. Special attention should be taken for vulnerable individuals such as those who are ill, elder, or newborns. But detecting and quantifying nanoparticles in complex food matrices like early life nutrition (ELN) poses a significant challenge due to the presence of additional particles, emulsion-droplets, or micelles. There is a pressing demand for standardized protocols for nanoparticle quantification and the specification of "nanoparticle-free" formulations. To address this, silica nanoparticles (SiNPs), commonly used as anticaking agents (AA) in processed food, were employed as a model system to establish characterization methods with different levels of accuracy and sensitivity versus speed, sample handling, and automatization. Different acid treatments were applied for sample digestion, followed by size exclusion chromatography. Morphology, size, and number of NPs were measured by transmission electron microscopy, and the amount of Si was determined by microwave plasma atomic emission spectrometry. This successfully enabled distinguishing SiNP content in ELN food formulations with 2-4% AA from AA-free formulations and sorting SiNPs with diameters of 20, 50, and 80 nm. Moreover, the study revealed the significant influence of the ELN matrix on sample preparation, separation, and characterization steps, necessitating method adaptations compared to the reference (SiNP in water). In the future, we expect these methods to be implemented in standard quality control of formulation processes, which demand high-throughput analysis and automated evaluation.
例如洗涤剂、化妆品和食品。虽然这种做法改善了产品特性，但纳米材料（<100纳米）暴露的增加及其潜在影响引发了对人体和环境的担忧。对于弱势群体，如病人、老年人或新生儿，应给予特别关注。但是，由于存在额外的颗粒、乳液滴或胶束，在早期生命营养（ELN）等复杂食品基质中检测和定量纳米颗粒构成了重大挑战。迫切需要用于纳米颗粒定量的标准化方案以及“无纳米颗粒”配方的规范。为了解决这个问题，在加工食品中常用作抗结块剂（AA）的二氧化硅纳米颗粒（SiNP）被用作模型系统，以建立具有不同准确度和灵敏度水平与速度、样品处理和自动化程度相对应的表征方法。对样品消化采用不同的酸处理，随后进行尺寸排阻色谱法。通过透射电子显微镜测量纳米颗粒的形态、尺寸和数量，并通过微波等离子体原子发射光谱法测定硅的含量。这成功地实现了区分含有2 - 4%抗结块剂的ELN食品配方中的SiNP含量与不含抗结块剂的配方，并对直径为20、50和80纳米的SiNP进行分类。此外，该研究揭示了ELN基质对样品制备、分离和表征步骤的重大影响，与参考物（水中的SiNP）相比需要对方法进行调整。未来，我们期望这些方法能够应用于配方过程的标准质量控制中，这需要高通量分析和自动化评估。
