Evidence map›Paper›PMID 41324752›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2025

Complementarity assessment of NMR and LC-HRMS profiling in natural products: an application on mastic leaves.

Christodoulos Anagnostou, Stavros Beteinakis, Theodora Nikou, Eleni V Mikropoulou, Anastasia Papachristodoulou, Maria Halabalaki

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In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Christodoulos AnagnostouDivision of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, 157 71, Athens, Greece.
Stavros BeteinakisDivision of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, 157 71, Athens, Greece.
Theodora NikouDivision of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, 157 71, Athens, Greece.
Eleni V MikropoulouDivision of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, 157 71, Athens, Greece.
Anastasia PapachristodoulouDivision of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, 157 71, Athens, Greece.
Maria HalabalakiDivision of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, 157 71, Athens, Greece. mariahal@pharm.uoa.gr.

Funding

HORIZON EUROPE Marie Sklodowska-Curie Actions 101131346
6 · The paper itself

Abstract

introductionMetabolomics has proven to be a powerful tool in the natural products' field for the investigation of plant extracts and the exploration of compounds with eminent biological and pharmacological properties. To that end, there is an ongoing discussion between NMR and LC-MS as the analytical platform of choice. Pistacia lentiscus L. var. Chia leaves (mastic leaves), an agricultural waste of pruning, possess a wide range of pharmacological properties, while limited data exist regarding their phytochemical profile.

objectivesThe aim of the present study was to assess the complementarity of these two main platforms in the study of natural products. As a case study, this approach was applied in the profiling of P. lentiscus leaves for the first time.

methodsTwo different untargeted methodologies were developed, utilizing NMR and UPLC-HRMS, for the detailed metabolite profile characterization of P. lentiscus leaves. Multivariate analysis (MVA) along with other statistical tools like Statistical Total Correlation SpectroscopY (STOCSY) and Statistical HeterospectroscopY (SHY) were employed for data analysis. RESULTS AND

conclusionsThe two methodologies were compared during all steps and the advantages of each technique were emphasized throughout the experimental and analytical stages of the study, making evident the synergy of the two platforms in the analysis of natural products. Specific biomarkers, related to the classification of the leaves with the different studied parameters were identified. STOCSY and SHY proved to be a valuable aid towards biomarkers assignment and results' interpretation.

Indexed as

Biological ProductsMetabolomicsPistaciaPlant LeavesChromatography, LiquidMagnetic Resonance SpectroscopyMass SpectrometryPlant ExtractsBiological ProductsPlant Extracts1H NMRLC-MSNatural products metabolomicsPistacia lentiscus L. var. Chia leavesSHYSTOCSY

Identifiers

PMID41324752

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.