ArticleTalanta2020
A surface-enhanced Raman spectroscopy database of 63 metabolites.
Article in Talanta, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- SERS Cheminformatics: Opportunities for Data-Driven Discovery and Applications.ACS central science · 2025Review
- Raman analysis of lipids in cells: Current applications and future prospects.Journal of pharmaceutical analysis · 2025Review
- Surface-Enhanced Raman Scattering Monitoring of Tryptophan Dynamics in 3D Pancreatic Tumor Models.ACS sensors · 2024Article
- Decoding the metabolic response ofProceedings of the National Academy of Sciences of the United States of America · 2023Article
- Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives.Frontiers in molecular biosciences · 2021Review
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Metabolomics, the study of metabolic profiles in a biological sample, has seen rapid growth due to advances in measurement technologies such as mass spectrometry (MS). While MS metabolite reference libraries have been generated for metabolomics applications, mass spectra alone are unable to unambiguously identify many metabolites in a sample; these unidentified compounds are typically annotated as "features". Surface-enhanced Raman spectroscopy (SERS) is an interesting technology for metabolite identification based on vibrational spectra. However, no reports have been published that present SERS metabolite spectra from chemical libraries. In this paper, we demonstrate that an untargeted approach utilizing citrate-capped silver nanoparticles yields SERS spectra for 20% of 80 compounds chosen randomly from a commercial metabolite library. Furthermore, prescreening of the metabolites according to chemical functionality allowed for the efficient identification of samples within the library that yield distinctive SERS spectra under our experimental conditions. Last, we present a reference database of 63 metabolite SERS spectra for use as an identification tool in metabolomics studies; this set includes 30 metabolites that have not had previously published SERS spectra.
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Registered trials
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