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非目标代谢和可解释的人工智能:处理和颜色对Eucommiae皮层中基化水平的影响

Yijing Pan¹, Kehong Ming¹, Dongmei Guo¹

¹Hubei Provincial Engineering Technology Research Center for Chinese Medicine Processing, School of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China; Hubei Shizhen Laboratory, Wuhan 430065, China.

|August 1, 2024

概括

这项研究优化了传统中医药的生-Eucommiae皮层 (G-EC) 处理. 代谢学和人工智能将颜色确定为含有烯 (CFA) 含量的可靠指标,这对于质量控制至关重要.

科学领域:

药理学是指药理学,它是指药理学.
传统中国医药传统中国医药
分析化学分析化学
化学测量化学测量化学测量

背景情况:

乌科米亚 (Eucommia ulmoides,Eucommiae Cortex,EC) 是中国传统医药 (TCM) 中的一种有价值的药用植物.
用生汁加工生-Eucommiae皮层 (G-EC) 提高了EC的有效性,味道和保质期.
由于G-EC缺乏标准化的质量控制,这阻碍了其工业和临床应用.

研究的目的:

为了优化生-Eucommiae皮层 (G-EC) 的处理方法.
为G-EC.建立可靠的质量控制指标.
使用先进的分析技术,研究G-EC加工过程中的化学变化.

主要方法:

优化G-EC处理,使用CRITIC (标准重要性通过标准间相关性) 方法和盒式设计.
代谢分析以比较原料和加工的G-EC的化学特征.
可解释的人工智能 (XAI) 的应用,以将色度数据与甲基 (CFA) 含量相关联.

主要成果:

确定了G-EC的优化处理参数.
代谢学在原始和加工的G-EC之间发现了517种化学变化,其中可见的增加是烯二 (CFA).
可解释的AI表明G-EC颜色和CFA内容之间存在强烈的相关性,这表明颜色是潜在的质量指标.

结论:

该研究成功优化了G-EC处理,并确定了关键的化学转化.
由XAI指导的色度分析为G-EC的质量控制提供了一种可行且非破坏性的方法.
建立G-EC的质量标准将促进其更广泛的临床和工业应用.

关键词:

颜色识别功能颜色识别功能康尼菲尔 aldehyde 的使用方法内容预测内容预测在Eucommiae皮层.生-Eucommiae皮质的皮层.分子网络是分子网络.非向的代谢基因组.谢普利添加剂的解释

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