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Plants produce numerous secondary metabolites with diverse physicochemical properties. Because different parts of a single plant produce various components, several spectroscopic methods are necessary to inspect their chemical profiles. Mass spectral data are recognized as one of the most useful tools for analyzing components with a wide range of polarities. However, interpreting mass spectral data generated from positive and negative ionization modes is a challenging task because of the diverse chemical profiles of secondary metabolites. Herein, we combine and analyze mass spectral data generated in two ionization modes to detect as many metabolites as possible using the molecular networking approach. We selected different parts of a single plant, (Moraceae), which are used in the functional food and medicinal herb industries. The mass spectral data generated from two ionization modes were combined and analyzed using various molecular networking workflows. We confirmed that our approach could be applied to simultaneously analyze the different types of secondary metabolites with different physicochemical properties.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8398940 | PMC |
http://dx.doi.org/10.3390/plants10081711 | DOI Listing |
MAbs
December 2025
Office of Pharmaceutical Quality Research, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
The analytical comparability of biologic products and their biosimilars, including higher-order structure (HOS) assessment, ensures product quality and is required for regulatory approval. In this study, nuclear magnetic resonance (NMR) spectroscopy was used to evaluate the HOS of Humira (adalimumab) and its biosimilars under normal and photo-stressed conditions. Under normal conditions, 1D and 2D NMR spectra showed strong structural similarity among all products.
View Article and Find Full Text PDFFood Res Int
November 2025
Department of Food Analysis and Nutrition, Faculty of Food and Biochemical Technology, University of Chemistry and Technology Prague, Technická 5, 166 28, Prague 6 - Dejvice, Prague, Czech Republic.
Chili peppers have been under the spotlight of bioactivity research as they feature a diverse and rich phytochemical profile with multiple health promoting effects. These beneficial properties are related to the chemical composition of chili peppers and is of utmost importance to identify varieties with the strongest bioprospecting potential. In this study, 19 chili pepper varieties were investigated originating from Capsicum annuum L.
View Article and Find Full Text PDFNat Protoc
September 2025
Pharmacomicrobiomics Research Center and College of Pharmacy, Hanyang University, Ansan, Republic of Korea.
Metabolism is a fundamental process that shapes the pharmacological and toxicological profiles of drugs, making metabolite identification and analysis critical in drug development and biological research. Global Natural Products Social Networking (GNPS) is a community-driven infrastructure for mass spectrometry data analysis, storage and knowledge dissemination. GNPS2 is an improved version of the platform offering higher processing speeds, improved data analysis tools and a more intuitive user interface.
View Article and Find Full Text PDFTalanta
September 2025
Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Oslo, 0371, Oslo, Norway; Hybrid Technology Hub - Centre of Excellence, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0315, Oslo, Norway. Electronic address:
Dried blood spots (DBS) offer a practical and relatively non-invasive method for sample collection. Here, we evaluate the feasibility of applying H NMR spectroscopy to metabolomic analysis of DBS. Various solvent suppression techniques and extraction protocols were tested using aqueous and methanolic solvents.
View Article and Find Full Text PDFAnal Chem
September 2025
Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
In this Article, we present a novel data analysis method for the determination of copolymer composition from low-resolution mass spectra, such as those recorded in the linear mode of time-of-flight (TOF) mass analyzers. Our approach significantly extends the accessible molecular weight range, enabling reliable copolymer composition analysis even in the higher mass regions. At low resolution, the overlapping mass peaks in the higher mass range hinder a comprehensive characterization of the copolymers.
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