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Rivera-Pérez A, Garrido Frenich A. Comparison of data processing strategies using commercial vs. open-source software in GC-Orbitrap-HRMS untargeted metabolomics analysis for food authentication: thyme geographical differentiation and marker identification as a case study. Anal Bioanal Chem 2024:10.1007/s00216-024-05347-0. [PMID: 38805060 DOI: 10.1007/s00216-024-05347-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/13/2024] [Accepted: 05/15/2024] [Indexed: 05/29/2024]
Abstract
Untargeted analysis of gas chromatography-high-resolution mass spectrometry (GC-HRMS) data is a key and time-consuming challenge for identifying metabolite markers in food authentication applications. Few studies have been performed to evaluate the capability of untargeted data processing tools for feature extraction, metabolite annotation, and marker selection from untargeted GC-HRMS data since most of them are focused on liquid chromatography (LC) analysis. In this framework, this study provides a comprehensive evaluation of data analysis tools for GC-Orbitrap-HRMS plant metabolomics data, including the open-source MS-DIAL software and commercial Compound Discoverer™ software (designed for Orbitrap data processing), applied for the geographical discrimination and search for thyme markers (Spanish vs. Polish differentiation) as the case study. Both approaches showed that the feature detection process is highly affected by unknown metabolites (Levels 4-5 of identification confidence), background signals, and duplicate features that must be carefully assessed before further multivariate data analysis for reliable putative identification of markers. As a result, Compound Discoverer™ and MS-DIAL putatively annotated 52 and 115 compounds at Level 2, respectively. Further multivariate data analysis allowed the identification of differential compounds, showing that the putative identification of markers, especially in challenging untargeted analysis, heavily depends on the data processing parameters, including available databases used during compound annotation. Overall, this method comparison pointed out both approaches as good options for untargeted analysis of GC-Orbitrap-HRMS data, and it is presented as a useful guide for users to implement these data processing approaches in food authenticity applications depending on their availability.
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Affiliation(s)
- Araceli Rivera-Pérez
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, 04120, Almeria, Spain.
| | - Antonia Garrido Frenich
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, 04120, Almeria, Spain
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2
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Mariod AA, Tahir HE. Metabolic and elemental profiling as potential discriminating features among the black mahlab seeds (Monechma ciliatum) grown in three different regions. PHYTOCHEMICAL ANALYSIS : PCA 2024. [PMID: 38431984 DOI: 10.1002/pca.3341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 01/01/2024] [Accepted: 02/09/2024] [Indexed: 03/05/2024]
Abstract
INTRODUCTION Black mahlab (Monechma ciliatum) seed is a rich source of metabolites and minerals and is usually believed to have a similar composition between different areas of cultivation. Until now, no studies have assessed changes in black mahlab seeds (BMSs) to determine those constituents that help to discriminate them according to geographical origin. OBJECTIVES The present study attempted to compare the metabolomics and elemental profiles of BMSs of different geographical origins and identified the potential markers using ultrahigh-performance liquid chromatography quadrupole Orbitrap tandem mass spectrometry (UHPLC-Q-Orbitrap-MS2 ), and inductively coupled plasma mass spectrometry (ICP-MS) techniques and established the chemometric model to identify the potential markers and discriminate them according to cultivation sites. MATERIAL AND METHODS In this work, data from metabolites analysis by UHPLC-Q-Orbitrap-MS2 and multi-elemental data obtained from ICP-MS were combined with chemometrics for tracing the geographical origin of BMSs. Principal component analysis (PCA) was used to evaluate the overall grouping of samples. In contrast, partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed for authentication. RESULTS PLS-DA and OPLS-DA models were fully validated (R2 Y and Q2 values > 0.5). Variable importance of various projections was applied to obtain valuable data about differential elements (seven markers were identified) and metabolites (23 markers were identified) with high discrimination potential. The outcomes presented in this study serve as an appropriate framework for developing novel discrimination approaches in food origin screening.
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Affiliation(s)
- Abdalbasit Adam Mariod
- College of Sciences and Arts - Alkamil, University of Jeddah, Alkamil, Saudi Arabia
- Indigenous Knowledge and Heritage Center at Ghibaish College of Science and Technology in Ghibaish, Ghibaish, Sudan
| | - Haroon Elrasheid Tahir
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
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3
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Cui YW, Liu LX, Zhang LY, Liu J, Gao CJ, Liu YG. Geographical differentiation of garlic based on HS-GC-IMS combined with multivariate statistical analysis. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:465-473. [PMID: 38167895 DOI: 10.1039/d3ay01802d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Garlic is famous for its unique flavor and health benefits. An effective means of authenticating garlic's origin is through the implementation of the Protected Geographical Indication (PGI) scheme. However, the prevalence of fraudulent behavior raises concerns regarding the reliability of this system. In this study, garlic samples from six distinct production areas (G1: Cangshan garlic, G2: Qixian garlic, G3: Dali single clove garlic, G4: Jinxiang garlic, G5: Yongnian garlic, and G6: Badong garlic) underwent analysis using HS-GC-IMS. A total of 26 VOCs were detected in the samples. The differences in VOCs among the different garlic samples were visually presented in a two-dimensional topographic map and fingerprint map. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to demonstrate the capacity of the HS-GC-IMS method for effectively distinguishing garlic samples from different geographical sources. Further screening based on the p-value and VIP score threshold identified 12 different aroma substances, which can be utilized for the identification of garlic from different producing areas. The fusion of HS-GC-IMS with multivariate statistical analysis proved to be a rapid, intuitive, and efficient approach for identifying and categorizing garlic VOCs, offering a novel strategy for ascertaining garlic origin and ensuring quality control.
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Affiliation(s)
- Ya-Wei Cui
- College of Life Sciences, Linyi University, Linyi, Shandong 276000, China.
- College of Life Science and Technology, Xinjiang University, Urumqi, Xinjiang 830002, China
| | - Ling-Xiao Liu
- Linyi Academy of Agricultural Sciences, Linyi, Shandong 276000, China
| | - Le-Yi Zhang
- Shandong Medical College, Linyi, Shandong 276000, China
| | - Jun Liu
- College of Life Science and Technology, Xinjiang University, Urumqi, Xinjiang 830002, China
| | - Cui-Juan Gao
- College of Life Sciences, Linyi University, Linyi, Shandong 276000, China.
| | - Yun-Guo Liu
- College of Life Sciences, Linyi University, Linyi, Shandong 276000, China.
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Kim H, Shin J, Yang J, Sim Y, Yang JY. Biomarker Development for Identifying Mud Loach ( Misgurnus mizolepis) Origin Country Using Untargeted Metabolite Profiling. Life (Basel) 2023; 13:2149. [PMID: 38004289 PMCID: PMC10671872 DOI: 10.3390/life13112149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/22/2023] [Accepted: 10/27/2023] [Indexed: 11/26/2023] Open
Abstract
Mud loach (Misgurnus mizolepis) has long been consumed in Korea. Recently, Chinese mud loaches were replaced with expensive Korean mud loaches, owing to taste and preference. Such issues occur in aquatic food distribution processes, leading to inferior food delivery. Previously, a study was conducted to confirm the origin of mud loaches using genetic analysis. However, untargeted metabolites profiling of mud loaches has not been reported. Untargeted metabolomics provides information on the overall metabolic profiling of a sample, allowing the identification of new metabolites. Here, we analyzed the metabolites of mud loaches of different geographical origins using liquid chromatography (LC)-quadrupole-time-of-flight mass spectrometry (MS). Orthogonal partial least squares discriminant analysis from LC/MS datasets showed a clear distinction between Korean and Chinese mud loaches, and univariate statistical analysis showed significantly different metabolites between them. N-acetylhistidine and anserine were selected as biomarkers for geographical origin discrimination using the receiver operating characteristic curve. N-acetylhistidine and anserine levels were significantly higher in Chinese than in Korean mud loaches. These results indicate that metabolic analysis can be used to discriminate between the geographical origins of mud loaches, curtailing the inadvertent substitution of mud loaches from different regions.
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Affiliation(s)
- Hyunsuk Kim
- Department of Food Science & Technology, Pukyong National University, Busan 48513, Republic of Korea
| | - Jiyoung Shin
- Department of Food Science & Technology, Pukyong National University, Busan 48513, Republic of Korea
| | - Junho Yang
- Department of Food Science & Technology, Pukyong National University, Busan 48513, Republic of Korea
| | - Yikang Sim
- Department of Food Science & Technology, Pukyong National University, Busan 48513, Republic of Korea
| | - Ji-Young Yang
- Department of Food Science & Technology, Pukyong National University, Busan 48513, Republic of Korea
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Zacometti C, Massaro A, di Gioia T, Lefevre S, Frégière-Salomon A, Lafeuille JL, Fiordaliso Candalino I, Suman M, Piro R, Tata A. Thermal desorption direct analysis in real-time high-resolution mass spectrometry and machine learning allow the rapid authentication of ground black pepper and dried oregano: A proof-of-concept study. JOURNAL OF MASS SPECTROMETRY : JMS 2023; 58:e4953. [PMID: 37401136 DOI: 10.1002/jms.4953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 05/12/2023] [Accepted: 06/01/2023] [Indexed: 07/05/2023]
Abstract
Thermal desorption direct analysis in real-time high-resolution mass spectrometry (TD-DART-HRMS) approaches have gained popularity for fast screening of a variety of samples. With rapid volatilization of the sample at increasing temperatures outside the mass spectrometer, this technique can provide a direct readout of the sample content with no sample preparation. In this study, TD-DART-HRMS's utility for establishing spice authenticity was examined. To this aim, we directly analyzed authentic (typical) and adulterated (atypical) samples of ground black pepper and dried oregano in positive and negative ion modes. We analyzed a set of authentic ground black pepper samples (n = 14) originating from Brazil, Sri Lanka, Madagascar, Ecuador, Vietnam, Costa Rica, Indonesia, Cambodia, and adulterated samples (n = 25) consisting of mixtures of ground black pepper with this spice's nonfunctional by-products (pinheads or spent) or with different exogenous materials (olive kernel, green lentils, black mustard seeds, red beans, gypsum plaster, garlic, papaya seeds, chili, green aniseed, or coriander seeds). TD-DART-HRMS facilitated the capture of informative fingerprinting of authentic dried oregano (n = 12) originating from Albania, Turkey, and Italy and those spiked (n = 12) with increasing percentages of olive leaves, sumac, strawberry tree leaves, myrtle, and rock rose. A predictive LASSO classifier was built, after merging by low-level data fusion, the positive and negative datasets for ground black pepper. Fusing multimodal data allowed retrieval of more comprehensive information from both datasets. The resultant classifier achieved on the withheld test set accuracy, sensitivity, and specificity of 100%, 75%, and 90%, respectively. On the contrary, the sole TD-(+)DART-HRMS spectra of the oregano samples allowed construction of a LASSO classifier that predicted the adulteration of the oregano with excellent statistical indicators. This classifier achieved, on the withheld test set, 100% each for accuracy, sensitivity, and specificity.
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Affiliation(s)
- Carmela Zacometti
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
| | - Andrea Massaro
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
| | - Tommaso di Gioia
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
| | - Stephane Lefevre
- Food Integrity Laboratory, Global Quality and Food Safety Center of Excellence, McCormick & Co., Inc., Carpentras, France
| | - Aline Frégière-Salomon
- Food Integrity Laboratory, Global Quality and Food Safety Center of Excellence, McCormick & Co., Inc., Carpentras, France
| | - Jean-Louis Lafeuille
- Global Quality and Food Safety Center of Excellence, McCormick & Co., Inc., Carpentras, France
| | | | - Michele Suman
- Advanced Laboratory Research, Barilla G. e R. Fratelli S.p.A., Parma, Italy
- Department for Sustainable Food Process, Catholic University Sacred Heart, Piacenza, Italy
| | - Roberto Piro
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
| | - Alessandra Tata
- Laboratorio di Chimica Sperimentale, Istituto Zooprofilattico Sperimentale delle Venezie, Vicenza, Italy
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Abraham EJ, Wallace ED, Kellogg JJ. A comparison of high- and low-resolution gas chromatography-mass spectrometry for herbal product classification: A case study with Ocimum essential oils. PHYTOCHEMICAL ANALYSIS : PCA 2023; 34:680-691. [PMID: 37393908 DOI: 10.1002/pca.3258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 04/17/2023] [Accepted: 06/12/2023] [Indexed: 07/04/2023]
Abstract
INTRODUCTION Selection of marker compounds for targeted chemical analysis is complicated when considering varying instrumentation and closely related plant species. High-resolution gas chromatography-mass spectrometry (GC-MS), via orbitrap detection, has yet to be evaluated for improved marker compound selection. OBJECTIVE This study directly compares high- and low-resolution GC-MS for botanical maker compound selection using Ocimum tenuiflorum L. (OT) and Ocimum gratissimum L. (OG) for botanical ingredient authentication. METHODS The essential oils of OT and OG were collected via hydrodistillation before untargeted chemical analysis with gas chromatography coupled to single-quadrupole (GC-SQ) and orbitrap (GC-Orbitrap) detectors. The Global Natural Products Social Molecular Networking (GNPS) software was used for compound annotation, and a manual search was used to find the 41 most common Ocimum essential oil metabolites. RESULTS The GC-Orbitrap resulted in 1.7-fold more metabolite detection and increased dynamic range compared to the GC-SQ. Spectral matching and manual searching were improved with GC-Orbitrap data. Each instrument had differing known compound concentrations; however, there was an overlap of six compounds with higher abundance in OG than OT and three compounds with a higher abundance in OT than OG, suggesting consistent detection of the most variable compounds. An unsupervised principal component analysis (PCA) could not discern the two species with either dataset. CONCLUSION GC-Orbitrap instrumentation improves compound detection, dynamic range, and feature annotation in essential oil analysis. However, considering both high- and low-resolution data may improve reliable marker compound selection, as GC-Orbitrap analysis alone did not improve unsupervised separation of two Ocimum species compared to GC-SQ data.
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Affiliation(s)
- Evelyn J Abraham
- Intercollege Graduate Degree Program in Plant Biology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - E Diane Wallace
- Mass Spectrometry Lab, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Joshua J Kellogg
- Intercollege Graduate Degree Program in Plant Biology, Pennsylvania State University, University Park, Pennsylvania, USA
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, Pennsylvania, USA
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Hong Y, Birse N, Quinn B, Li Y, Jia W, McCarron P, Wu D, da Silva GR, Vanhaecke L, van Ruth S, Elliott CT. Data fusion and multivariate analysis for food authenticity analysis. Nat Commun 2023; 14:3309. [PMID: 37291121 PMCID: PMC10250487 DOI: 10.1038/s41467-023-38382-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 04/27/2023] [Indexed: 06/10/2023] Open
Abstract
A mid-level data fusion coupled with multivariate analysis approach is applied to dual-platform mass spectrometry data sets using Rapid Evaporative Ionization Mass Spectrometry and Inductively Coupled Plasma Mass Spectrometry to determine the correct classification of salmon origin and production methods. Salmon (n = 522) from five different regions and two production methods are used in the study. The method achieves a cross-validation classification accuracy of 100% and all test samples (n = 17) have their origins correctly determined, which is not possible with single-platform methods. Eighteen robust lipid markers and nine elemental markers are found, which provide robust evidence of the provenance of the salmon. Thus, we demonstrate that our mid-level data fusion - multivariate analysis strategy greatly improves the ability to correctly identify the geographical origin and production method of salmon, and this innovative approach can be applied to many other food authenticity applications.
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Affiliation(s)
- Yunhe Hong
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Nicholas Birse
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Brian Quinn
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Yicong Li
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Wenyang Jia
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Philip McCarron
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Di Wu
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Gonçalo Rosas da Silva
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Lynn Vanhaecke
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom
- Laboratory of Integrative Metabolomics, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Saskia van Ruth
- Food Quality and Design Group, Wageningen University and Research, Wageningen, The Netherlands
- School of Agriculture and Food Science, University College Dublin, Dublin 4, Ireland
| | - Christopher T Elliott
- National Measurement Laboratory: Centre of Excellence in Agriculture and Food Integrity, Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, United Kingdom.
- School of Food Science and Technology, Faculty of Science and Technology, Thammasat University, 99 Mhu 18, Pahonyothin Road, Khong Luang, Pathum Thani, 12120, Thailand.
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Naumann L, Haun A, Höchsmann A, Mohr M, Novák M, Flottmann D, Neusüß C. Augmented region of interest for untargeted metabolomics mass spectrometry (AriumMS) of multi-platform-based CE-MS and LC-MS data. Anal Bioanal Chem 2023:10.1007/s00216-023-04715-6. [PMID: 37225900 DOI: 10.1007/s00216-023-04715-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/16/2023] [Accepted: 04/20/2023] [Indexed: 05/26/2023]
Abstract
In mass spectrometry (MS)-based metabolomics, there is a great need to combine different analytical separation techniques to cover metabolites of different polarities and apply appropriate multi-platform data processing. Here, we introduce AriumMS (augmented region of interest for untargeted metabolomics mass spectrometry) as a reliable toolbox for multi-platform metabolomics. AriumMS offers augmented data analysis of several separation techniques utilizing a region-of-interest algorithm. To demonstrate the capabilities of AriumMS, five datasets were combined. This includes three newly developed capillary electrophoresis (CE)-Orbitrap MS methods using the recently introduced nanoCEasy CE-MS interface and two hydrophilic interaction liquid chromatography (HILIC)-Orbitrap MS methods. AriumMS provides a novel mid-level data fusion approach for multi-platform data analysis to simplify and speed up multi-platform data processing and evaluation. The key feature of AriumMS lies in the optimized data processing strategy, including parallel processing of datasets and flexible parameterization for processing of individual separation methods with different peak characteristics. As a case study, Saccharomyces cerevisiae (yeast) was treated with a growth inhibitor, and AriumMS successfully differentiated the metabolome based on the augmented multi-platform CE-MS and HILIC-MS investigation. As a result, AriumMS is proposed as a powerful tool to improve the accuracy and selectivity of metabolome analysis through the integration of several HILIC-MS/CE-MS techniques.
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Affiliation(s)
- Lukas Naumann
- Department of Chemistry, Aalen University, Beethovenstraße 1, 73430, Aalen, Germany
| | - Adrian Haun
- Department of Chemistry, Aalen University, Beethovenstraße 1, 73430, Aalen, Germany
| | - Alisa Höchsmann
- Department of Chemistry, Aalen University, Beethovenstraße 1, 73430, Aalen, Germany
| | - Michael Mohr
- Department of Chemistry, Aalen University, Beethovenstraße 1, 73430, Aalen, Germany
| | - Martin Novák
- Department of Chemistry, Aalen University, Beethovenstraße 1, 73430, Aalen, Germany
| | - Dirk Flottmann
- Department of Chemistry, Aalen University, Beethovenstraße 1, 73430, Aalen, Germany
| | - Christian Neusüß
- Department of Chemistry, Aalen University, Beethovenstraße 1, 73430, Aalen, Germany.
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Rivera-Pérez A, García-Pérez P, Romero-González R, Garrido Frenich A, Lucini L. UHPLC-QTOF-HRMS metabolomics insight on the origin and processing authentication of thyme by comprehensive fingerprinting and chemometrics. Food Chem 2023; 407:135123. [PMID: 36493482 DOI: 10.1016/j.foodchem.2022.135123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/03/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022]
Abstract
The metabolic composition of thyme, one of the most used aromatic herbs, is influenced by environmental and post-harvest processing factors, presenting the possibility of exploiting thyme fingerprint to assess its authenticity. In this study, a comprehensive UHPLC-QTOF-HRMS fingerprinting approach was applied with a dual objective: (1) tracing thyme from three regions of production (Spain, Morocco, and Poland) and (2) evaluating the metabolic differences in response to processing, considering sterilized thyme samples. Multivariate statistics reveal 37 and 33 key origin and processing differentiation compounds, respectively. The findings highlighted the remarkable "terroir" influence on thyme fingerprint, noticing flavonoids, amino acids, and peptides among the most discriminant chemical classes. Thyme sterilization led to an overall metabolite enrichment, most likely due to the facilitated compound accessibility as a result of processing. The findings provide a comprehensive metabolomics insight into the origin and processing effect on thyme composition for product traceability and quality assessment.
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Affiliation(s)
- Araceli Rivera-Pérez
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain; Department for Sustainable Food Process - DiSTAS, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy
| | - Pascual García-Pérez
- Department for Sustainable Food Process - DiSTAS, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy; Nutrition and Bromatology Group, Analytical and Food Chemistry Department, Faculty of Food Science and Technology, Univesidade de Vigo, Ourense Campus, 32004 Ourense, Spain
| | - Roberto Romero-González
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain
| | - Antonia Garrido Frenich
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain
| | - Luigi Lucini
- Department for Sustainable Food Process - DiSTAS, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy.
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Rivera-Pérez A, Romero-González R, Garrido Frenich A. Untargeted 1H NMR-based metabolomics and multi-technique data fusion: A promising combined approach for geographical and processing authentication of thyme by multivariate statistical analysis. Food Chem 2023; 420:136156. [PMID: 37075575 DOI: 10.1016/j.foodchem.2023.136156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 04/09/2023] [Accepted: 04/11/2023] [Indexed: 04/21/2023]
Abstract
Thyme is a culinary herb highly susceptible to increasing mislabeling occurring in the spice industry. In this study, proton nuclear magnetic resonance spectroscopy (1H NMR) combined with multivariate statistics was successfully applied with two authenticity purposes: (1) tracing thyme metabolic differences among three relevant geographical regions (Morocco, Spain, and Poland), and (2) assessing the influence of sterilization processing on the metabolic fingerprint. Multivariate data analysis provided six and seven key geographical and processing markers, respectively, including thymol, organic acids, chlorogenic acid, and some carbohydrates (e.g., sucrose). Additionally, for the first time, a mid-level data fusion approach was tested for thyme authenticity combining three complementary and synergic analytical platforms: gas and liquid chromatography coupled with high-resolution mass spectrometry, and 1H NMR spectroscopy, providing a comprehensive metabolomics insight into the origin and processing effects on thyme fingerprinting, and opening the path to new metabolomics approaches for quality control in the spice industry.
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Affiliation(s)
- Araceli Rivera-Pérez
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain.
| | - Roberto Romero-González
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain.
| | - Antonia Garrido Frenich
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain.
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11
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Peng Y, Zheng C, Guo S, Gao F, Wang X, Du Z, Gao F, Su F, Zhang W, Yu X, Liu G, Liu B, Wu C, Sun Y, Yang Z, Hao Z, Yu X. Metabolomics integrated with machine learning to discriminate the geographic origin of Rougui Wuyi rock tea. NPJ Sci Food 2023; 7:7. [PMID: 36928372 PMCID: PMC10020150 DOI: 10.1038/s41538-023-00187-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/03/2023] [Indexed: 03/18/2023] Open
Abstract
The geographic origin of agri-food products contributes greatly to their quality and market value. Here, we developed a robust method combining metabolomics and machine learning (ML) to authenticate the geographic origin of Wuyi rock tea, a premium oolong tea. The volatiles of 333 tea samples (174 from the core region and 159 from the non-core region) were profiled using gas chromatography time-of-flight mass spectrometry and a series of ML algorithms were tested. Wuyi rock tea from the two regions featured distinct aroma profiles. Multilayer Perceptron achieved the best performance with an average accuracy of 92.7% on the training data using 176 volatile features. The model was benchmarked with two independent test sets, showing over 90% accuracy. Gradient Boosting algorithm yielded the best accuracy (89.6%) when using only 30 volatile features. The proposed methodology holds great promise for its broader applications in identifying the geographic origins of other valuable agri-food products.
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Affiliation(s)
- Yifei Peng
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.,FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Chao Zheng
- FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Shuang Guo
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.,FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Fuquan Gao
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.,FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Xiaxia Wang
- FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Zhenghua Du
- FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Feng Gao
- Fujian Farming Technology Extension Center, Fuzhou, 350003, China
| | - Feng Su
- Fujian Farming Technology Extension Center, Fuzhou, 350003, China
| | - Wenjing Zhang
- Fujian Farming Technology Extension Center, Fuzhou, 350003, China
| | - Xueling Yu
- Fujian Farming Technology Extension Center, Fuzhou, 350003, China
| | - Guoying Liu
- Wuyishan Institute of Agricultural Sciences, Wuyishan, 354300, China
| | - Baoshun Liu
- Wuyishan Tea Bureau, Wuyishan, 354300, China
| | - Chengjian Wu
- Fujian Vocational College of Agriculture, Fuzhou, 350119, China
| | - Yun Sun
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Zhenbiao Yang
- FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
| | - Zhilong Hao
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
| | - Xiaomin Yu
- FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
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Rivera-Pérez A, García-Pérez P, Romero-González R, Garrido Frenich A, Lucini L. An untargeted strategy based on UHPLC-QTOF-HRMS metabolomics to identify markers revealing the terroir and processing effect on thyme phenolic profiling. Food Res Int 2022; 162:112081. [DOI: 10.1016/j.foodres.2022.112081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 10/18/2022] [Accepted: 10/22/2022] [Indexed: 11/24/2022]
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13
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Rivera-Pérez A, Romero-González R, Garrido Frenich A. Fingerprinting based on gas chromatography-Orbitrap high-resolution mass spectrometry and chemometrics to reveal geographical origin, processing, and volatile markers for thyme authentication. Food Chem 2022; 393:133377. [PMID: 35691070 DOI: 10.1016/j.foodchem.2022.133377] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/28/2022] [Accepted: 05/31/2022] [Indexed: 11/17/2022]
Abstract
Thyme is an aromatic herb traditionally used for food purposes due to its organoleptic characteristics and medicinal properties, which is highly susceptible to food fraud. In this study, GC-HRMS-based fingerprinting was applied for the first time to determine the geographical traceability of thyme based on different origins (Spain, Poland, and Morocco), as well as to assess its processing by comparing sterilized vs. non-sterilized thyme. Unsupervised chemometric methods (PCA and HCA) revealed a predominant influence of the geographical origin on thyme fingerprints rather than processing effects. Supervised PLS-DA and OPLS-DA were used for discrimination purposes, revealing high predictive ability for further samples (100%), and allowing the identification of differential compounds (markers). A total of 24 markers were putatively identified (13 metabolites were confirmed) belonging to different classes: monoterpenoids, diterpenoids, sesquiterpenoids, alkenylbenzenes, and other miscellaneous compounds. This study outlines the potential of combining untargeted analysis by GC-HRMS with chemometrics for thyme authenticity and traceability.
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Affiliation(s)
- Araceli Rivera-Pérez
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain.
| | - Roberto Romero-González
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain.
| | - Antonia Garrido Frenich
- Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain.
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14
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Newerli-Guz J, Śmiechowska M. Health Benefits and Risks of Consuming Spices on the Example of Black Pepper and Cinnamon. Foods 2022; 11:foods11182746. [PMID: 36140874 PMCID: PMC9498169 DOI: 10.3390/foods11182746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 11/22/2022] Open
Abstract
The aim of this study is to present the benefits and risks associated with the consumption of black pepper and cinnamon, which are very popular spices in Poland. The article presents the current state of knowledge about health properties and possible dangers, such as liver damage, associated with their consumption. The experimental part presents the results of the research on the antioxidant properties against the DPPH radical, which was 80.85 ± 3.84–85.42 ± 2.34% for black pepper, and 55.52 ± 7.56–91.87 ± 2.93% for cinnamon. The total content of polyphenols in black pepper was 10.67 ± 1.30–32.13 ± 0.24 mg GAE/g, and in cinnamon 52.34 ± 0.96–94.71 ± 3.34 mg GAE/g. In addition, the content of piperine and pepper oil in black pepper was determined, as well as the content of coumarin in cinnamon. The content of piperine in the black pepper samples was in the range of 3.92 ± 0.35–9.23 ± 0.05%. The tested black pepper samples contained 0.89 ± 0.08–2.19 ± 0.15 mL/100 g d.m. of essential oil. The coumarin content in the cinnamon samples remained in the range of 1027.67 ± 50.36–4012.00 ± 79.57 mg/kg. Taking into account the content of coumarin in the tested cinnamon samples, it should be assumed that the majority of cinnamon available in Polish retail is Cinnamomum cassia (L.) J. Presl.
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Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology—A Review. Molecules 2022; 27:molecules27154846. [PMID: 35956791 PMCID: PMC9369811 DOI: 10.3390/molecules27154846] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 12/03/2022] Open
Abstract
The release of the FDA’s guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.
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Mollik M, Rahman MH, Al-Shaeri M, Ashraf GM, Alexiou A, Gafur MA. Isolation, characterization and in vitro antioxidant activity screening of pure compound from black pepper (Piper nigrum). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:52220-52232. [PMID: 35260981 DOI: 10.1007/s11356-022-19403-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 02/19/2022] [Indexed: 06/14/2023]
Abstract
The present study's aims of isolation, characterization and in vitro antioxidant activity screening of pure compound from Black pepper (Piper nigrum) were investigated. Nowadays, scientific exploration of medicinal plants from natural sources has become the prime concern globally. All the crude drugs that have been isolated from natural plant origin (herbs, root, stem, bark, fruit and flower) have great significance in drug discovery as well as a lead compound to demonstrate great synergistic effect on pharmacology. For this research work, methanol was selected as a mother solvent, and the crude methanolic extract of black pepper was partitioned in between the solvent chloroform and di-ethyl-ether. A crystal fraction has been eradicated from the chloroform extract of black pepper (Piper nigrum). The crystal compound (C1) was isolated and purified by using thin layer chromatography (TLC) and recrystallization technique. The purified crystal compound (C1) isolated from black pepper possesses a strong in vitro antioxidant activity. The IC50 value of crystal compound (C1) was 4.1 µg/ml where the standard one had 3.2 µg/ml. Physical, phytochemical and chromatographical characterization of pure crystal compound (C1) has been explored, and from the analysis of all characteristics, it was found that, crystal compound (C1) might have resembling features of the standard Piperine of black pepper. The overall research work was really remarkable and introduced a convenient way of isolating pure compound from the natural source which will be a great referential resource in isolating crude drugs for future analysis.
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Affiliation(s)
- Murshida Mollik
- Department of Pharmacy, Rajshahi University, Rajshahi, 6205, Bangladesh
| | - Md Habibur Rahman
- Department of Global Medical Science, Wonju College of Medicine, Yonsei University, Wonju, 26426, Republic of Korea.
- Department of Pharmacy, Southeast University, Banani Street, Dhaka, 1213, Bangladesh.
| | - Majed Al-Shaeri
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ghulam Md Ashraf
- Pre-Clinical Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
| | - Athanasios Alexiou
- Novel Global Community Educational Foundation, NSW, Hebersham, Australia
- AFNP Med Austria, Haidingergasse 29, 1030, Wien, Austria
| | - Md Abdul Gafur
- Department of Pharmacy, Rajshahi University, Rajshahi, 6205, Bangladesh.
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17
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pyAIR-A New Software Tool for Breathomics Applications-Searching for Markers in TD-GC-HRMS Analysis. Molecules 2022; 27:molecules27072063. [PMID: 35408461 PMCID: PMC9000534 DOI: 10.3390/molecules27072063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/16/2022] [Accepted: 03/17/2022] [Indexed: 11/16/2022] Open
Abstract
Volatile metabolites in exhaled air have promising potential as diagnostic biomarkers. However, the combination of low mass, similar chemical composition, and low concentrations introduces the challenge of sorting the data to identify markers of value. In this paper, we report the development of pyAIR, a software tool for searching for volatile organic compounds (VOCs) markers in multi-group datasets, tailored for Thermal-Desorption Gas-Chromatography High Resolution Mass-Spectrometry (TD-GC-HRMS) output. pyAIR aligns the compounds between samples by spectral similarity coupled with retention times (RT), and statistically compares the groups for compounds that differ by intensity. This workflow was successfully tested and evaluated on gaseous samples spiked with 27 model VOCs at six concentrations, divided into three groups, down to 0.3 nL/L. All analytes were correctly detected and aligned. More than 80% were found to be significant markers with a p-value < 0.05; several were classified as possibly significant markers (p-value < 0.1), while a few were removed due to background level. In all group comparisons, low rates of false markers were found. These results showed the potential of pyAIR in the field of trace-level breathomics, with the capability to differentially examine several groups, such as stages of illness.
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