Untargeted Metabolomics for Profiling of Cascara, Senna, Rhubarb, and Frangula Metabolites
This work provides a chemistry-centred metabolomic fingerprint of four HAD-containing herbal drugs using graph-based neural networks for natural product classification, supporting future studies on the pharmacological potential, bioavailability and safety of their metabolites.
Authors
- Laura Salvini (ORCID: https://orcid.org/0000-0002-2923-8157)
- Filippo Costanti (ORCID: https://orcid.org/0000-0002-1668-9557)
- Laura Tinti (ORCID: https://orcid.org/0000-0002-0607-6212)
- Paola Nezi (ORCID: https://orcid.org/0009-0003-2972-0028)
- Vittoria Cicaloni (ORCID: https://orcid.org/0000-0002-8329-1565)
- Alessia Lucia Prete (ORCID: https://orcid.org/0009-0008-3605-0700)
- Monica Bianchini (ORCID: https://orcid.org/0000-0002-8206-8142)
- Mattia Cicogni
Institutions
- University of Siena (IT)
- Toscana Life Sciences (IT)
Publication Details
- Journal
- Metabolites
- Published
- 2025-12-03
- DOI
- https://doi.org/10.3390/metabo15120779
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00