可视化
解吸电喷雾电离
计算机科学
代谢组学
质谱成像
中医药
代谢组
数据科学
计算生物学
数据挖掘
质谱法
生物信息学
化学
医学
生物
病理
色谱法
化学电离
离子
有机化学
电离
替代医学
作者
Binjie Xu,Lirun Chen,Fengqi Lv,Yuan Pan,Xing Fu,Zhaoqing Pei
摘要
The medicinal use of traditional Chinese medicine is mainly due to its secondary metabolites. Visualization of the distribution of these metabolites has become a crucial topic in plant science. Mass spectrometry imaging can extract huge volumes of data and provide spatial distribution information about these by analyzing tissue slices. With the advantage of high throughput and higher accuracy, desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is often used in biological research and in the study of traditional Chinese medicine. However, the procedures used in this research are complicated and not affordable. In this study, we optimized sectioning and DESI imaging procedures and developed a more cost-effective method to identify the distribution of metabolites and categorize these compounds in plant tissues, with a special focus on traditional Chinese medicines. The study will promote the utilization of DESI in metabolite analysis and standardization of traditional Chinese medicine/ethnic medicine for research-related technologies.
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