ArticleAnalytical and bioanalytical chemistry2024
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.
Article in Analytical and bioanalytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Integrating NMR and MS for Improved Metabolomic Analysis: From Methodologies to Applications.Molecules (Basel, Switzerland) · 2025Review
- Combined Exposures and Mixtures Research: An Enduring NIEHS Priority.Environmental health perspectives · 2024Article
- Advancing botanical safety: A strategy for selecting, sourcing, and characterizing botanicals for developing toxicological tools.Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Consumers have unprecedented access to botanical dietary supplements through online retailers, making it difficult to ensure product quality and authenticity. Therefore, methods to survey and compare chemical compositions across botanical products are needed. Nuclear magnetic resonance (NMR) spectroscopy and non-targeted mass spectrometry (MS) were used to chemically analyze commercial products labeled as containing one of three botanicals: blue cohosh, goldenseal, and yohimbe bark. Aqueous and organic phase extracts were prepared and analyzed in tandem with NMR followed by MS. We processed the non-targeted data using multivariate statistics to analyze the compositional similarity across extracts. In each case, there were several product outliers that were identified using principal component analysis (PCA). Evaluation of select known constituents proved useful to contextualize PCA subgroups, which in some cases supported or refuted product authenticity. The NMR and MS data reached similar conclusions independently but were also complementary.
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