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Twenty cultivars were categorized into four species, and the most appropriate discriminative marker m/z value for identifying each cultivar was selected statistically. Components extracted based on DI-EI-MS analyses could be used to construct a model to predict ATL cell bioactivity. These data suggest that the novel DI-EI-MS metabolomics method is suitable for identifying species of natural materials and predicting their pharmacologic activity. This approach could enhance public health by facilitating evaluations of pharmacologic activ
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