在非目标查中,实验投影方法是否超过保留时间预测模型? 一个关于LC/HRMS实验室间比较数据的案例研究
Louise Malm1, Anneli Kruve1,2
1Department of Materials and Environmental Chemistry, Stockholm University, 11418 Stockholm, Sweden. anneli.kruve@su.se.
The Analyst
|July 17, 2025
概括
在非目标查 (NTS) 中使用液态染色学高分辨率质谱法 (LC-HRMS) 估计保留时间 (RTs) 是至关重要的. 投影和预测模型显示了与染色体系统相似性相关的准确性,移动相 pH 和柱体化学是关键因素.
科学领域:
- 分析化学 分析化学
- 环境科学 环境科学
- 质谱测量质量谱测量
背景情况:
- 保留时间 (RT) 对于在非目标查 (NTS) 中使用液态染色学高分辨率质谱学 (LC-HRMS) 的结构阐明至关重要.
- 现有的RT估计方法包括投影和预测方法,由于源/训练色谱系统 (CS源/CS训练) 和NTS系统 (CSNTS) 之间的差异,这些方法可能面临挑战.
研究的目的:
- 评估RT投影和预测模型在NTS中常用的各种染色学系统 (CSs) 中的概括性.
- 确定影响这些RT估计方法准确性的关键染色学参数.
主要方法:
- 利用了来自NORMAN实验室间比较的数据,涉及41种校准化学品和45种可疑物质,在37种不同的CS中进行了分析.
- 评估了与实验RT相比的RT投影和机器学习 (ML) 预测模型的性能.
主要成果:
- 投影和预测模型的准确性与色谱系统之间的相似性直接相关.
- 移动相 pH 和柱体化学被确定为影响 RT 估计准确性的最重要因素.
- 当CS培训与CSNTS相似时,预测模型的性能与投影模型相比,即使CS源有显著差异.
结论:
- RT估计模型的概括性高度依赖于色谱系统的相似性,特别是移动相 pH 和列化学.
- 用于RT预测的机器学习模型应该包含移动相和列化学参数,以提高准确性.
- 在投影和预测模型之间进行选择时,应考虑训练/源和NTS染色系统之间的相似性.
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