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Guo Z, Fan Y, Yu C, Lu H, Zhang Z. GCMSFormer: A Fully Automatic Method for the Resolution of Overlapping Peaks in Gas Chromatography-Mass Spectrometry. Anal Chem 2024; 96:5878-5886. [PMID: 38560891 DOI: 10.1021/acs.analchem.3c05772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Gas chromatography-mass spectrometry (GC-MS) is one of the most important instruments for analyzing volatile organic compounds. However, the complexity of real samples and the limitations of chromatographic separation capabilities lead to coeluting compounds without ideal separation. In this study, a Transformer-based automatic resolution method (GCMSFormer) is proposed to resolve mass spectra from GC-MS peaks in an end-to-end manner, predicting the mass spectra of components directly from the raw overlapping peaks data. Furthermore, orthogonal projection resolution (OPR) was integrated into GCMSFormer to resolve minor components. The GCMSFormer model was trained, validated, and tested using 100,000 augmented data. It achieves 99.88% of the bilingual evaluation understudy (BLEU) value on the test set, significantly higher than the 97.68% BLEU value of the baseline sequence-to-sequence model long short-term memory (LSTM). GCMSFormer was also compared with two nondeep learning resolution tools (MZmine and AMDIS) and two deep learning resolution tools (PARAFAC2 with DL and MSHub/GNPS) on a real plant essential oil GC-MS data set. Their resolution results were compared on evaluation metrics, including the number of compounds resolved, mass spectral match score, correlation coefficient, explained variance, and resolution speed. The results demonstrate that GCMSFormer has better resolution performance, higher automation, and faster resolution speed. In summary, GCMSFormer is an end-to-end, fast, fully automatic, and accurate method for analyzing GC-MS data of complex samples.
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Affiliation(s)
- Zixuan Guo
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Yingjie Fan
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Chuanxiu Yu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Zhimin Zhang
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
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Flexible Implementation of the Trilinearity Constraint in Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) of Chromatographic and Other Type of Data. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27072338. [PMID: 35408738 PMCID: PMC9000239 DOI: 10.3390/molecules27072338] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 03/29/2022] [Accepted: 04/02/2022] [Indexed: 11/16/2022]
Abstract
Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) can analyze three-way data under the assumption of a trilinear model using the trilinearity constraint. However, the rigid application of this constraint can produce unrealistic solutions in practice due to the inadequacy of the analyzed data to the characteristics and requirements of the trilinear model. Different methods for the relaxation of the trilinear model data requirements have been proposed, like in the PARAFAC2 and in the direct non-trilinear decomposition (DNTD) methods. In this work, the trilinearity constraint of MCR-ALS is adapted to different data scenarios where the profiles of all or some of the components of the system are shifted (not equally synchronized) or even change their shape among different slices in one of their data modes. This adaptation is especially useful in gas and liquid chromatography (GC and LC) and in Flow Injection Analysis (FIA) with multivariate spectroscopic detection. In a first data example, a synthetic LC-DAD dataset is built to investigate the possibilities of the proposed method to handle systematic changes (shifts) in the retention times of the elution profiles and the results are compared with those obtained using alternative methods like ATLD, PARAFAC, PARAFAC2 and DNTD. In a second data example, multiple wine samples were simultaneously analyzed by GC-MS where elution profiles presented large deviations (shifts) in their peak retention times, although they still preserve the same peak shape. Different modelling scenarios are tested and the results are also compared. Finally, in the third example, sample mixtures of acid compounds were analyzed by FIA under a pH gradient and monitored by UV spectroscopy and also examined by different chemometric methods using a different number of components. In this case, however, the departure of the trilinear model comes from the acid base speciation of the system depending on the pH more than from the shifting of the FIA diffusion profiles.
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3
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Designing an interactive molecular autoburette for quantification approach of pharmaceuticals by MCR-ALS. Microchem J 2022. [DOI: 10.1016/j.microc.2021.107096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Souza Guedes L, Santana CC, Rutledge DN, Pinto L, Jardim ICSF, Melo LV, Beppu MM, Breitkreitz MC. Quantification of palm oil bioactive compounds by ultra‐high‐performance supercritical fluid chromatography and chemometrics. CAN J CHEM ENG 2021. [DOI: 10.1002/cjce.23969] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
| | | | - Douglas Neil Rutledge
- Université Paris‐Saclay, INRAE, AgroParisTech, UMR SayFood Paris France
- National Wine and Grape Industry Centre Charles Sturt University Wagga Wagga Australia
| | - Licarion Pinto
- Department of Fundamental Chemistry Federal University of Pernambuco Recife Brazil
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Nagai Y, Katayama K. Multivariate curve resolution combined with estimation by cosine similarity mapping of analytical data. Analyst 2021; 146:5045-5054. [PMID: 34263889 DOI: 10.1039/d1an00362c] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
We developed a multivariate curve resolution (MCR) calculation combined with the mapping of cosine similarity (cos-s) for estimating multiple mixture spectra of chemicals. The cos-s map was obtained by calculating the similarities of the variation of the signal intensities at each scanning parameter, such as the wavelength. The cos-s map was utilized for the initial estimation of the spectra of pure chemicals and also for the restriction of the iterative least-squares calculation of the MCR. These calculations were performed without arbitrary parameters by introducing soft clustering to the cos-s map. The chemically meaningful initial estimation could prevent the convergence at an incorrect local minimum, which frequently happens for the wrong initial estimation of spectra far away from the real answer. Herein, we demonstrated the robustness of this calculation method by applying it for UV/Vis spectra and XRD patterns of multiple unknown chemical mixtures, whose shapes were totally different (broad overlapped peaks and multiple complicated peaks). Pure spectra/patterns were recovered as >84% consistency with the reference spectra, and <6% accuracy of the concentration ratios was demonstrated.
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Affiliation(s)
- Yuya Nagai
- Department of Applied Chemistry, Chuo University, Tokyo 112-8551, Japan.
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Güzel R, Ertekin ZC, Dinç E. A New Application of PARAFAC Model to UPLC Dataset for the Quantitative Resolution of a Tri-Component Drug Mixture. J Chromatogr Sci 2021; 59:361-370. [PMID: 33454729 DOI: 10.1093/chromsci/bmaa119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Indexed: 11/12/2022]
Abstract
In the presented work, a three-way analysis of ultra-performance liquid chromatography-photodiode array (UPLC-PDA) dataset was performed by parallel factor analysis (PARAFAC) for quantitatively resolving a ternary mixture containing paracetamol and methocarbamol with indapamide selected as an internal standard in their co-eluted chromatographic conditions. Paracetamol and methocarbamol were quantified in the working range between 3-24 and 5-50 μg/mL by applying PARAFAC decomposition to UPLC-PDA data array obtained under unresolved chromatographic peak conditions. To compare the experimental results provided by co-eluted UPLC-PARAFAC method, an ordinary UPLC method was developed ensuring proper separation of the peaks. The performance of both PARAFAC and ordinary UPLC methods were assessed by quantifying independent test samples, intra- and inter-day samples and spiked samples of pharmaceutical preparations. Then, both methods were applied for quantitative estimation of the related drugs in a commercial pharmaceutical preparation. In this study, PARAFAC method was proved to be a very powerful alternative for the quality control of pharmaceutical preparations containing paracetamol and methocarbamol even in their co-eluted chromatograms with high precision and accuracy in a short chromatographic runtime of 1.2 min.
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Affiliation(s)
- Remziye Güzel
- Department of Science, Dicle University, Sur, Diyarbakır 21280, Turkey
| | - Zehra Ceren Ertekin
- Department of Analytical Chemistry, Ankara University, Degol St. No:4, Ankara 06560, Turkey
| | - Erdal Dinç
- Department of Analytical Chemistry, Ankara University, Degol St. No:4, Ankara 06560, Turkey
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Pérez-Cova M, Jaumot J, Tauler R. Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116207] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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8
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Processing multi-way chromatographic data for analytical calibration, classification and discrimination: A successful marriage between separation science and chemometrics. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2020.116128] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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Wu HL, Wang T, Yu RQ. Recent advances in chemical multi-way calibration with second-order or higher-order advantages: Multilinear models, algorithms, related issues and applications. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.115954] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Zhang XH, Zhou Q, Liu Z, Qing XD, Zheng JJ, Mu ST, Liu PH. Comparison of three second-order multivariate calibration methods for the rapid identification and quantitative analysis of tea polyphenols in Chinese teas using high-performance liquid chromatography. J Chromatogr A 2020; 1618:460905. [PMID: 32008825 DOI: 10.1016/j.chroma.2020.460905] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2019] [Revised: 01/09/2020] [Accepted: 01/20/2020] [Indexed: 01/28/2023]
Affiliation(s)
- Xiao-Hua Zhang
- Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety of Henan Province, Food and Bioengineering College, Xuchang University, Xuchang 461000, PR China.
| | - Qian Zhou
- Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety of Henan Province, Food and Bioengineering College, Xuchang University, Xuchang 461000, PR China
| | - Zhi Liu
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products/Institute of Quality and Standards for Agricultural Products, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, PR China.
| | - Xiang-Dong Qing
- Hunan Provincial Key Laboratory of Dark Tea and Jin-hua, College of Materials and Chemical Engineering, Hunan City University, Yiyang, 413049, PR China
| | - Jing-Jing Zheng
- Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety of Henan Province, Food and Bioengineering College, Xuchang University, Xuchang 461000, PR China
| | - Shu-Ting Mu
- Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety of Henan Province, Food and Bioengineering College, Xuchang University, Xuchang 461000, PR China
| | - Pan-Hua Liu
- Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety of Henan Province, Food and Bioengineering College, Xuchang University, Xuchang 461000, PR China
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Bayat M, Marín-García M, Ghasemi JB, Tauler R. Application of the area correlation constraint in the MCR-ALS quantitative analysis of complex mixture samples. Anal Chim Acta 2020; 1113:52-65. [DOI: 10.1016/j.aca.2020.03.057] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 03/26/2020] [Accepted: 03/29/2020] [Indexed: 12/13/2022]
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