ArticleAnalytical and bioanalytical chemistry2020
Identification of adulteration in botanical samples with untargeted metabolomics.
Article in Analytical and bioanalytical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Assessing Transporter-Mediated Natural Product-Drug Interactions Via In vitro-In Vivo Extrapolation: Clinical Evaluation With a Probe Cocktail.Clinical pharmacology and therapeutics · 2021Trial
- Multi-Platform Metabolomics for Fraud Detection in Spices and Botanical Food Supplements: From Fingerprint Acquisition to Decision-Grade Evidence.Molecules (Basel, Switzerland) · 2026Review
- Article
- Cultivar to chemotype: characterizing complex botanicals with mass spectrometry metabolomics.Natural product reports · 2026Review
- Phylogenomic and metabolomic approaches to provide insight for species delimitation of cultivatedFrontiers in plant science · 2026Article
- A gut response: Application of human enteroid monolayers to probe the mechanism of the goldenseal-mediated inhibition of metformin intestinal absorption.The Journal of pharmacology and experimental therapeutics · 2025Article
- LC-MS-based metabolomics for detecting adulteration inFood chemistry: X · 2025Article
- Adulteration of Brain Health (Cognitive, Mood, and Sleep Enhancement) Food Supplements by the Addition of Pharmaceutical Drugs: A Comprehensive Review of Analytical Approaches and Trends.Foods (Basel, Switzerland) · 2024Review
- Non-targeted chemical analysis of consumer botanical products labeled as blue cohosh (Caulophyllum thalictroides), goldenseal (Hydrastis canadensis), or yohimbe bark (Pausinystalia yohimbe) by NMR and MS.Analytical and bioanalytical chemistry · 2024Article
- An Integrative Approach to Elucidate Mechanisms Underlying the Pharmacokinetic Goldenseal-Midazolam Interaction: Application of In Vitro Assays and Physiologically Based Pharmacokinetic Models to Understand Clinical Observations.The Journal of pharmacology and experimental therapeutics · 2023Article
- Hopomics:Metabolites · 2022Article
- Study on plasma metabolomics for HIV/AIDS patients treated by HAART based on LC/MS-MS.Frontiers in pharmacology · 2022Article
- Phytochemistry in the Ethnopharmacology of North and Central America.Frontiers in pharmacology · 2022Review
- Improved One-Class Modeling of High-Dimensional Metabolomics Data via Eigenvalue-Shrinkage.Metabolites · 2021Article
- Chemometric-Guided Approaches for Profiling and Authenticating Botanical Materials.Frontiers in nutrition · 2021Review
- Chemical Authentication of Botanical Ingredients: A Review of Commercial Herbal Products.Frontiers in pharmacology · 2021Review
- Analytical Challenges and Metrological Approaches to Ensuring Dietary Supplement Quality: International Perspectives.Frontiers in pharmacology · 2021Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Adulteration remains an issue in the dietary supplement industry, including botanical supplements. While it is common to employ a targeted analysis to detect known adulterants, this is difficult when little is known about the sample set. With this study, untargeted metabolomics using liquid chromatography coupled to ultraviolet-visible spectroscopy (LC-UV) or high-resolution mass spectrometry (LC-MS) was employed to detect adulteration in botanical dietary supplements. A training set was prepared by combining Hydrastis canadensis L. with a known adulterant, Coptis chinensis Franch., in ratios ranging from 5 to 95% adulteration. The metabolomics datasets were analyzed using both unsupervised (principal component analysis and composite score) and supervised (SIMCA) techniques. Palmatine, a known H. canadensis metabolite, was quantified as a targeted analysis comparison. While the targeted analysis was the most sensitive method tested in detecting adulteration, statistical analyses of the untargeted metabolomics datasets detected adulteration of the goldenseal samples, with SIMCA providing the greatest discriminating potential. Graphical abstract.
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Registered trials
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