在没有分析标准的非定位分析中对化学品的量化 - - 了解电子喷雾电离的机制并做出预测
Trevor A Johnson1, Dimitri P Abrahamsson1
1Division of Environmental Pediatrics, Department of Pediatrics, Grossman School of Medicine, New York University.
Current opinion in environmental science & health
|February 5, 2024
概括
非目标分析 (NTA) 的新方法旨在在没有分析标准的情况下识别和量化环境化学品. 机器学习的进步正在改善化合物检测和量化,提高对新出现污染物的NTA的信心.
科学领域:
- 环境化学环境化学
- 分析化学 分析化学
- 计算化学计算化学
背景情况:
- 新型化学品不断释放到环境中,超过了分析标准的可用性.
- 新出现的污染物带来风险,需要先进的分析技术来检测和表征.
- 目前的分析方法在没有参考标准的情况下努力识别和量化未知的化合物.
研究的目的:
- 审查目前的非目标分析 (NTA) 的现状,用于在没有分析标准的情况下量化未知的化合物.
- 突出机器学习在推进NTA能力方面的作用.
- 评估在环境监测中验证的定量NTA方法的潜力.
主要方法:
- 综述最近非定向分析 (NTA) 技术的进展.
- 探索用于响应估计的机器学习算法和化学描述符.
- 分析使用MS和MS/MS数据进行结构识别的方法.
主要成果:
- 在使用机器学习来估计未知化合物的仪器响应方面取得了进展.
- NTA方法正在发展,以提供更广泛的化学覆盖和结构识别.
- 现实世界样本的验证研究仍然有限,但对进步至关重要.
结论:
- 精细的数据处理和机器学习工具正在增强NTA的能力.
- 没有分析标准的定量NTA对全面的环境分析有希望.
- 需要进一步验证,以增加定量NTA方法的信心和有用性.
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