Scholarlink

Introduction <p>Metabolomics 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. <i>Pistacia lentiscus</i> L. var. <i>Chia</i> leaves (mastic leaves), an agricultural waste of pruning, possess a wide range of pharmacological properties, while limited data exist regarding their phytochemical profile.</p> Objectives <p>The 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 <i>P. lentiscus</i> leaves for the first time.</p> Methods <p>Two different untargeted methodologies were developed, utilizing NMR and UPLC-HRMS, for the detailed metabolite profile characterization of <i>P. lentiscus</i> leaves. Multivariate analysis (MVA) along with other statistical tools like Statistical Total Correlation SpectroscopY (STOCSY) and Statistical HeterospectroscopY (SHY) were employed for data analysis.</p> Results and conclusions <p>The 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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 发表日期：

    2025年12月1日

查看全文
  • Christodoulos Anagnostou,
  • Stavros Beteinakis,
  • Theodora Nikou,
  • Eleni V. Mikropoulou,
  • Anastasia Papachristodoulou,
  • Maria Halabalaki

摘要

Introduction

Metabolomics 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.

Objectives

The 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.

Methods

Two 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 conclusions

The 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.