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使用环境电离质谱和机器学习进行快速代谢分析和验证Cordyceps的真实性

Wenbo Ma¹, Mengyang Song¹, Zhenyang Ji¹

¹State Key Laboratory of High-Efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, 750021, China.

Analytical and bioanalytical chemistry

|February 11, 2025

概括

假冒的Cordyceps sinensis会欺骗消费者,但质谱和神经网络可以识别真正的药用真菌. 这项技术能够准确地在现场检测出正宗的Cordyceps,保护消费者并保持传统医学的完整性.

科学领域:

分析化学分析化学
代谢学代谢学代谢学
传统中国医药传统中国医药

背景情况:

在传统中医药中, Cordyceps sinensis 是一种有价值的药用真菌,由于广泛的假冒,它面临着重大的市场挑战.
对Cordyceps物种的错误识别导致经济损失并损害治疗效果.
准确的真实验证方法对于确保 Cordyceps 药物产品的质量和安全至关重要.

研究的目的:

开发和验证一种快速分析方法,以区分真正的Cordyceps sinensis与其假冒.
研究不同Cordyceps物种中的代谢概况和代谢物分布.
评估便携式质谱仪在现场验证Cordyceps真实性的可行性.

主要方法:

环境电离质谱法用于对四种Cordyceps类型的代谢分析.
进行了81种代谢物的初步鉴定.
为了分类,开发了一个神经网络模型,并使用了一种手持的纳米电子喷雾电离源与微型质谱仪相结合,用于现场检测.

主要成果:

在野生型Cordyceps sinensis和假冒样本之间发现了显著的代谢差异.
埃尔戈西奥内因及其前体赫辛因在斯特罗玛中发现更为丰富.
神经网络在盲目测试中实现了90.3%的分类准确率,现场检测给出了与基板系统相似的结果.

结论:

环境电离质谱有效地区分真正的Cordyceps sinensis与基于代谢资料的假冒.
该研究强调了便携式质谱仪在快速,现场验证药用真菌的潜力.
这项技术可以帮助打击假冒产品,并确保Cordyceps市场的完整性.

关键词:

科尔迪塞普斯 (Cordyceps) 是一种植物.环境的电离化环境.验证身份验证验证身份验证机器学习是机器学习.代谢过程中的代谢.

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