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Meunier M, Schinkovitz A, Derbré S. Current and emerging tools and strategies for the identification of bioactive natural products in complex mixtures. Nat Prod Rep 2024. [PMID: 39291767 DOI: 10.1039/d4np00006d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
Covering: up to 2024The prompt identification of (bio)active natural products (NPs) from complex mixtures poses a significant challenge due to the presence of numerous compounds with diverse structures and (bio)activities. Thus, this review provides an overview of current and emerging tools and strategies for the identification of (bio)active NPs in complex mixtures. Traditional approaches of bioassay-guided fractionation (BGF), followed by nuclear magnetic resonance (NMR) and mass spectrometry (MS) analysis for compound structure elucidation, continue to play an important role in the identification of active NPs. However, recent advances (2018-2024) have led to the development of novel techniques such as (bio)chemometric analysis, dereplication and combined approaches, which allow efficient prioritization for the elucidation of (bio)active compounds. For researchers involved in the search for bioactive NPs and who want to speed up their discoveries while maintaining accurate identifications, this review highlights the strengths and limitations of each technique and provides up-to-date insights into their combined use to achieve the highest level of confidence in the identification of (bio)active natural products from complex matrices.
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Affiliation(s)
- Manon Meunier
- Univ. Angers, SONAS, SFR QUASAV, F-49000 Angers, France.
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2
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Bjørstorp S, Malmstrøm J. Quantitative 31P NMR Spectroscopy Platform Method for the Assay of Oligonucleotides as Pure Drug Substances and in Drug Product Formulations Using the Internal Standard Method. Anal Chem 2024; 96:11198-11204. [PMID: 38943563 DOI: 10.1021/acs.analchem.4c00419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2024]
Abstract
One of the most widely used techniques for the quantification of small interfering ribonucleic acid (siRNA) is the ultraviolet (UV) spectroscopy method. However, due to uncertainties in the extinction coefficient affecting the accuracy of the method and a sample preparation including several dilution steps, the purpose of this study was to explore the possibility of determining the content of siRNA by a platform method using quantitative 31P nuclear magnetic resonance (31P-qNMR) and the internal standard method. In this paper, acquisition time, selection of a suitable internal certified reference material, signal selection used for quantification, relaxation delay, and precision are discussed. In addition, the robustness of the method and the ability to apply this platform method to both drug substance (DS) and drug product samples is also discussed. Quantifications of siRNA determined by the 31P-qNMR platform method were on average 98.5%w/w when adjusting for the sodium and water contents. The data confirmed the applicability of 31P-qNMR in siRNA content determinations. The quantifications were compared to quantifications determined by the traditional UV spectroscopy method by F- and t-tests. The statistical tests showed that the platform 31P-qNMR method provided more accurate results (mass balance close to 100% w/w) compared to the traditional UV spectroscopy method when analyzing DS samples.
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Affiliation(s)
- Simone Bjørstorp
- Department of CMC Analytical Support, Novo Nordisk A/S, Novo Nordisk Park 1, 2760 Måløv, Denmark
- Department of Drug Design and Pharmacology, University of Copenhagen, Universitetsparken 2, 2100 Copenhagen Ø, Denmark
| | - Joan Malmstrøm
- Department of CMC Analytical Support, Novo Nordisk A/S, Novo Nordisk Park 1, 2760 Måløv, Denmark
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Malashin I, Daibagya D, Tynchenko V, Gantimurov A, Nelyub V, Borodulin A. Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach. Polymers (Basel) 2024; 16:1204. [PMID: 38732673 PMCID: PMC11085799 DOI: 10.3390/polym16091204] [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: 03/02/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
Nafion, a versatile polymer used in electrochemistry and membrane technologies, exhibits complex behaviors in saline environments. This study explores Nafion membrane's IR spectra during soaking and subsequent drying processes in salt solutions at various concentrations. Utilizing the principles of Fick's second law, diffusion coefficients for these processes are derived via exponential approximation. By harnessing machine learning (ML) techniques, including the optimization of neural network hyperparameters via a genetic algorithm (GA) and leveraging various regressors, we effectively pinpointed the optimal model for predicting diffusion coefficients. Notably, for the prediction of soaking coefficients, our model is composed of layers with 64, 64, 32, and 16 neurons, employing ReLU, ELU, sigmoid, and ELU activation functions, respectively. Conversely, for drying coefficients, our model features two hidden layers with 16 and 12 neurons, utilizing sigmoid and ELU activation functions, respectively.
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Affiliation(s)
- Ivan Malashin
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia (A.G.); (V.N.); (A.B.)
| | - Daniil Daibagya
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia (A.G.); (V.N.); (A.B.)
- P.N. Lebedev Physical Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
| | - Vadim Tynchenko
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia (A.G.); (V.N.); (A.B.)
| | - Andrei Gantimurov
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia (A.G.); (V.N.); (A.B.)
| | - Vladimir Nelyub
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia (A.G.); (V.N.); (A.B.)
- Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia
| | - Aleksei Borodulin
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia (A.G.); (V.N.); (A.B.)
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Li W, Zhang X, Wang S, Gao X, Zhang X. Research Progress on Extraction and Detection Technologies of Flavonoid Compounds in Foods. Foods 2024; 13:628. [PMID: 38397605 PMCID: PMC10887530 DOI: 10.3390/foods13040628] [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: 12/30/2023] [Revised: 02/13/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
Flavonoid compounds have a variety of biological activities and play an essential role in preventing the occurrence of metabolic diseases. However, many structurally similar flavonoids are present in foods and are usually in low concentrations, which increases the difficulty of their isolation and identification. Therefore, developing and optimizing effective extraction and detection methods for extracting flavonoids from food is essential. In this review, we review the structure, classification, and chemical properties of flavonoids. The research progress on the extraction and detection of flavonoids in foods in recent years is comprehensively summarized, as is the application of mathematical models in optimizing experimental conditions. The results provide a theoretical basis and technical support for detecting and analyzing high-purity flavonoids in foods.
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Affiliation(s)
- Wen Li
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Xiaoping Zhang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Shuanglong Wang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Xiaofei Gao
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Xinglei Zhang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
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Yang J, Lu Y, Pan Y, Shi Y, Xie X, Pan J, Qu H. Pharmaceutical process-omics for quality control of traditional Chinese medicine preparations: A 1H-qNMR assisted case study of Guanxinning injection. J Pharm Biomed Anal 2024; 238:115793. [PMID: 37883890 DOI: 10.1016/j.jpba.2023.115793] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/07/2023] [Accepted: 10/10/2023] [Indexed: 10/28/2023]
Abstract
Guanxinning injection (GXNI) is a traditional Chinese medicine preparation derived from Salviae Miltiorrhizae Radix et Rhizoma and Chuanxiong Rhizoma. It is produced through a series of processes involving water extraction, ethanol precipitation, and other techniques. GXNI is primarily used for treating angina pectoris in coronary heart disease, and it has shown remarkable efficacy in clinical practice. One of the key components responsible for its pharmacological effects is salvianolic acids. However, these components are known for their poor stability and susceptibility to pH and temperature variations. Therefore, it is crucial to focus on ensuring the quality and stability of salvianolic acids in GXNI. In this study, we employed Proton nuclear magnetic resonance (1H NMR) to analyze the intermediate products formed during the manufacturing of GXNI. We thoroughly examined the spectra of these intermediates and developed a precise 1H-qNMR method for the accurate quantification of various classes of chemical components present in GXNI. Additionally, we applied this method to investigate how the composition of GXNI evolves and transfers throughout the entire production process. To further enhance our understanding, we employed Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) to identify critical steps in the production process and to identify potential quality markers (Q-markers) associated with these processes. Our study sheds light on the dynamic changes in composition that occur during the production of GXNI. This research serves as a foundation for establishing a comprehensive quality evaluation system for GXNI, ensuring its efficacy and safety in clinical applications.
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Affiliation(s)
- Jiayu Yang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yuting Lu
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yingfeng Pan
- Chiatai Qingchunbao Pharmaceutical Co., Ltd., Hangzhou 313200, China
| | - Yingting Shi
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Xinyuan Xie
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jianyang Pan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Haibin Qu
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
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Trendafilova A, Staleva P, Petkova Z, Ivanova V, Evstatieva Y, Nikolova D, Rasheva I, Atanasov N, Topouzova-Hristova T, Veleva R, Moskova-Doumanova V, Dimitrov V, Simova S. Phytochemical Profile, Antioxidant Potential, Antimicrobial Activity, and Cytotoxicity of Dry Extract from Rosa damascena Mill. Molecules 2023; 28:7666. [PMID: 38005389 PMCID: PMC10674922 DOI: 10.3390/molecules28227666] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 11/09/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023] Open
Abstract
Dry rose extract (DRE) obtained industrially by aqueous ethanol extraction from R. damascena flowers and its phenolic-enriched fraction, obtained by re-extraction with ethyl acetate (EAE) were the subject of this study. 1H NMR of DRE allowed the identification and quantitation of fructose and glucose, while the combined use of HPLC-DAD-ESIMS and HPLC-HRMS showed the presence of 14 kaempferol glycosides, 12 quercetin glycosides, 4 phenolic acids and their esters, 4 galloyl glycosides, 7 ellagitannins, and quinic acid. In addition, the structures of 13 of the flavonoid glycosides were further confirmed by NMR. EAE was found to be richer in TPC and TFC and showed better antioxidant activity (DPPH, ABTS, and FRAP) compared to DRE. Both extracts displayed significant activity against Propionibacterium acnes, Staphylococcus aureus, and S. epidermidis, but showed no activity against Candida albicans. Toxicity tests on normal human skin fibroblasts revealed low toxicity for both extracts with stronger effects observed at 24 hours of treatment that were compensated for over the following two days. Human hepatocarcinoma (HepG2) cells exhibited an opposite response after treatment with a concentration above 350 µg/mL for EAE and 500 µg/mL for DRE, showing increased toxicity after the third day of treatment. Lower concentrations were non-toxic and did not significantly affect the cell cycle parameters of either of the cell lines.
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Affiliation(s)
- Antoaneta Trendafilova
- Laboratory Chemistry of Natural Products, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria;
| | - Plamena Staleva
- Laboratory Organic Chemistry and Spectroscopy, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria; (P.S.); (Z.P.); (V.D.)
- Research and Development and Innovation Consortium, Sofia Tech Park, 1784 Sofia, Bulgaria
| | - Zhanina Petkova
- Laboratory Organic Chemistry and Spectroscopy, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria; (P.S.); (Z.P.); (V.D.)
| | - Viktoria Ivanova
- Laboratory Chemistry of Natural Products, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria;
| | - Yana Evstatieva
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria; (Y.E.); (D.N.); (I.R.); (N.A.); (T.T.-H.); (R.V.); (V.M.-D.)
| | - Dilyana Nikolova
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria; (Y.E.); (D.N.); (I.R.); (N.A.); (T.T.-H.); (R.V.); (V.M.-D.)
| | - Iliyana Rasheva
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria; (Y.E.); (D.N.); (I.R.); (N.A.); (T.T.-H.); (R.V.); (V.M.-D.)
| | - Nikola Atanasov
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria; (Y.E.); (D.N.); (I.R.); (N.A.); (T.T.-H.); (R.V.); (V.M.-D.)
| | - Tanya Topouzova-Hristova
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria; (Y.E.); (D.N.); (I.R.); (N.A.); (T.T.-H.); (R.V.); (V.M.-D.)
| | - Ralitsa Veleva
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria; (Y.E.); (D.N.); (I.R.); (N.A.); (T.T.-H.); (R.V.); (V.M.-D.)
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
| | - Veselina Moskova-Doumanova
- Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria; (Y.E.); (D.N.); (I.R.); (N.A.); (T.T.-H.); (R.V.); (V.M.-D.)
| | - Vladimir Dimitrov
- Laboratory Organic Chemistry and Spectroscopy, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria; (P.S.); (Z.P.); (V.D.)
| | - Svetlana Simova
- Bulgarian NMR Centre, Institute of Organic Chemistry with Centre of Phytochemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
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Han JH, Lee EJ, Park W, Ha KT, Chung HS. Natural compounds as lactate dehydrogenase inhibitors: potential therapeutics for lactate dehydrogenase inhibitors-related diseases. Front Pharmacol 2023; 14:1275000. [PMID: 37915411 PMCID: PMC10616500 DOI: 10.3389/fphar.2023.1275000] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 09/27/2023] [Indexed: 11/03/2023] Open
Abstract
Lactate dehydrogenase (LDH) is a crucial enzyme involved in energy metabolism and present in various cells throughout the body. Its diverse physiological functions encompass glycolysis, and its abnormal activity is associated with numerous diseases. Targeting LDH has emerged as a vital approach in drug discovery, leading to the identification of LDH inhibitors among natural compounds, such as polyphenols, alkaloids, and terpenoids. These compounds demonstrate therapeutic potential against LDH-related diseases, including anti-cancer effects. However, challenges concerning limited bioavailability, poor solubility, and potential toxicity must be addressed. Combining natural compounds with LDH inhibitors has led to promising outcomes in preclinical studies. This review highlights the promise of natural compounds as LDH inhibitors for treating cancer, cardiovascular, and neurodegenerative diseases.
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Affiliation(s)
- Jung Ho Han
- Korean Medicine (KM)-Application Center, Korea Institute of Oriental Medicine (KIOM), Daegu, Republic of Korea
| | - Eun-Ji Lee
- Korean Medicine (KM)-Application Center, Korea Institute of Oriental Medicine (KIOM), Daegu, Republic of Korea
| | - Wonyoung Park
- Korean Convergence Medical Science Major, KIOM Campus, University of Science and Technology (UST), Daegu, Republic of Korea
| | - Ki-Tae Ha
- Korean Convergence Medical Science Major, KIOM Campus, University of Science and Technology (UST), Daegu, Republic of Korea
| | - Hwan-Suck Chung
- Korean Medicine (KM)-Application Center, Korea Institute of Oriental Medicine (KIOM), Daegu, Republic of Korea
- Department of Korean Medical Science, School of Korean Medicine, Pusan National University, Yangsan, Republic of Korea
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Polachini GM, de Castro TB, Smarra LFS, Henrique T, de Paula CHD, Severino P, López RVM, Carvalho AL, de Mattos Zeri AC, Silva IDCG, Tajara EH. Plasma metabolomics of oral squamous cell carcinomas based on NMR and MS approaches provides biomarker identification and survival prediction. Sci Rep 2023; 13:8588. [PMID: 37237049 DOI: 10.1038/s41598-023-34808-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023] Open
Abstract
Metabolomics has proven to be an important omics approach to understand the molecular pathways underlying the tumour phenotype and to identify new clinically useful markers. The literature on cancer has illustrated the potential of this approach as a diagnostic and prognostic tool. The present study aimed to analyse the plasma metabolic profile of patients with oral squamous cell carcinoma (OSCC) and controls and to compare patients with metastatic and primary tumours at different stages and subsites using nuclear magnetic resonance and mass spectrometry. To our knowledge, this is the only report that compared patients at different stages and subsites and replicates collected in diverse institutions at different times using these methodologies. Our results showed a plasma metabolic OSCC profile suggestive of abnormal ketogenesis, lipogenesis and energy metabolism, which is already present in early phases but is more evident in advanced stages of the disease. Reduced levels of several metabolites were also associated with an unfavorable prognosis. The observed metabolomic alterations may contribute to inflammation, immune response inhibition and tumour growth, and may be explained by four nonexclusive views-differential synthesis, uptake, release, and degradation of metabolites. The interpretation that assimilates these views is the cross talk between neoplastic and normal cells in the tumour microenvironment or in more distant anatomical sites, connected by biofluids, signalling molecules and vesicles. Additional population samples to evaluate the details of these molecular processes may lead to the discovery of new biomarkers and novel strategies for OSCC prevention and treatment.
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Affiliation(s)
- Giovana Mussi Polachini
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Tialfi Bergamin de Castro
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Luis Fabiano Soares Smarra
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil
| | - Tiago Henrique
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Carlos Henrique Diniz de Paula
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil
| | - Patricia Severino
- Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | | | - André Lopes Carvalho
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, SP, Brazil
| | | | | | - Eloiza H Tajara
- Department of Molecular Biology, School of Medicine of São José Do Rio Preto - FAMERP, Av. Brigadeiro Faria Lima, 5416, Vila São Pedro, São José do Rio Preto, SP, CEP 15090-000, Brazil.
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil.
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Head-to-Head Comparison of High-Performance Liquid Chromatography versus Nuclear Magnetic Resonance for the Quantitative Analysis of Carbohydrates in Yiqi Fumai Lyophilized Injection. MOLECULES (BASEL, SWITZERLAND) 2023; 28:molecules28020765. [PMID: 36677822 PMCID: PMC9860785 DOI: 10.3390/molecules28020765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/06/2023] [Accepted: 01/09/2023] [Indexed: 01/15/2023]
Abstract
Carbohydrate analysis can be used as a standard analysis for quality control of industries of plants, foods and pharmaceuticals. Quantitative 1H NMR spectroscopy (qNMR) is an excellent alternative to chromatography-based mixture analysis. However, the application of qNMR in sugar analysis has rarely been reported. In this study, the performance of qNMR in sugar analysis was investigated and compared with the results from HPLC analysis. A head-to-head comparison of qNMR (internal and external standard methods) versus HPLC (PMP pre-column derivatization HPLC, HPLC-RID and HPLC-ELSD) based on quantitative analysis of four carbohydrates (fructose, glucose, sucrose and maltose) in Yiqi Fumai lyophilized injection (YQFM) is presented. Both assays showed similar performance characteristics, including linearity range, accuracy, precision and recovery, and analysis times of less than 30 min/sample. After methodological validation, both qNMR and HPLC have good accuracy, precision and stability. Indeed, the qNMR method is simple, sensitive and rapid in quantifying the four sugars. By analysis of variance (ANOVA) for sugar content with HPLC and qNMR methods, we demonstrated that the two analytical methods had no significant difference and could be used interchangeably for the quantitative analysis of carbohydrates.
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Lavigne L, Choisnard L, Peyrin E, Oukacine F. Quantification of Ions and Organic Molecules, in Nanoliter Samples, in the Absence of Reference Materials. Anal Chem 2022; 94:15546-15552. [DOI: 10.1021/acs.analchem.2c03104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Laura Lavigne
- Université Grenoble Alpes, DPM, CNRS UMR 5063, F-38041Grenoble, France
| | - Luc Choisnard
- Université Grenoble Alpes, DPM, CNRS UMR 5063, F-38041Grenoble, France
| | - Eric Peyrin
- Université Grenoble Alpes, DPM, CNRS UMR 5063, F-38041Grenoble, France
| | - Farid Oukacine
- Université Grenoble Alpes, DPM, CNRS UMR 5063, F-38041Grenoble, France
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11
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Wekre ME, Hellesen Brunvoll S, Jordheim M. Advancing quantification methods for polyphenols in brown seaweeds-applying a selective qNMR method compared with the TPC assay. PHYTOCHEMICAL ANALYSIS : PCA 2022; 33:1099-1110. [PMID: 35796295 PMCID: PMC9796469 DOI: 10.1002/pca.3162] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 06/15/2022] [Accepted: 06/15/2022] [Indexed: 06/15/2023]
Abstract
INTRODUCTION Brown seaweeds are a sustainable biomass with a potential for various industrial applications. Polyphenols are an important contributor to this potential. OBJECTIVE The aim was total quantification of polyphenols in brown seaweeds from different tidal zones, using a selective 1 H quantitative NMR (qNMR) method, comparing the results with the colorimetric Folin-Ciocalteu total phenolic content (TPC) assay. METHOD qNMR was performed with integration of selected peaks in the aromatic region (7-5.5 ppm). Deselection of non-polyphenolic 1 H signals was based on information from 2D (1 H-13 C, 1 H-15 N) NMR spectra. 13 C NMR phlorotannin characterisation facilitated the average number of protons expected to be found per aromatic ring used for the 1 H quantification. RESULTS Selective qNMR and the TPC assay showed similar results for the three sublittoral growing species from the Laminariaceae; lower amounts for Laminaria hyperborea and Laminaria digitata (qNMR: 0.4%-0.6%; TPC: 0.6%-0.8%, phloroglucinol equivalents (PGE), dry weight (DW)) and higher amounts for Saccharina latissima (qNMR: 1.2%; TPC: 1.5%, PGE, DW). For the eulittoral Fucaceae, Fucus vesiculosus (qNMR: 1.1%; TPC: 4.1%; PGE, DW) and Ascophyllum nodosum (qNMR: 0.9%; TPC: 2.0%; PGE, DW), the TPC results were found to be up to three times higher than the qNMR results. The 13 C NMR characterisation showed the highest phlorotannin polymerisation degree for F. vesiculosus. CONCLUSION The TPC assay provided similar polyphenolic amounts to the selective qNMR method for sublittoral species. For eulittoral growing species, the TPC method showed amounts up to three times higher than the qNMR method-most likely illustrating the lack of selectivity in the TPC assay.
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Affiliation(s)
- Marie Emilie Wekre
- Department of ChemistryUniversity of BergenBergenNorway
- Alginor ASAHaugesundNorway
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Yang M, Liu Z, Zhang J, Zhu X, Xie W, Lan H, Huang Y, Ye X, Yang J. Simultaneous quantification of cellulose and pectin in tobacco using a robust solid-state NMR method. Carbohydr Res 2022; 521:108676. [PMID: 36126413 DOI: 10.1016/j.carres.2022.108676] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/03/2022] [Accepted: 09/05/2022] [Indexed: 11/30/2022]
Abstract
Cellulose and pectin are the important components of tobacco (Nicotiana tabacum L.) cell wall, which affect the formation of undesirable compounds. Their contents are closely related to the harmfulness of tobacco. But the simultaneous quantitative analysis of cellulose and pectin is hard to be achieved for traditional analytical methods. A solid-state 13C cross-polarization by multiple contact periods (multiCP) NMR method was developed for the simultaneous quantification of cellulose and pectin in tobacco. The multiCP spectrum at optimal parameters agreed well with the direct polarization (DP) spectrum within one-thirtieth of the measurement time and provided satisfactory signal to noise ratio (SNR). After three simple procedures of sample preparation and spectra deconvolution, simultaneous quantification of cellulose and pectin extracted from tobacco was effectively achieved. Compared with the chemical method, this interesting method was rapid, practicable, and very promising, which provided the technical support for the simultaneous quantification of cell wall substances in biological sample.
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Affiliation(s)
- Mingyu Yang
- Department of Chemistry, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, People's Republic of China
| | - Zechun Liu
- Technology Center, China Tobacco Fujian Industrial Co. Ltd., 298 Binshui Road, Xiamen, 361001, People's Republic of China.
| | - Jianping Zhang
- Technology Center, China Tobacco Fujian Industrial Co. Ltd., 298 Binshui Road, Xiamen, 361001, People's Republic of China
| | - Xiaolan Zhu
- Department of Chemistry, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, People's Republic of China
| | - Wei Xie
- Technology Center, China Tobacco Fujian Industrial Co. Ltd., 298 Binshui Road, Xiamen, 361001, People's Republic of China
| | - Hongqiao Lan
- Technology Center, China Tobacco Fujian Industrial Co. Ltd., 298 Binshui Road, Xiamen, 361001, People's Republic of China
| | - Yanjun Huang
- Technology Center, China Tobacco Fujian Industrial Co. Ltd., 298 Binshui Road, Xiamen, 361001, People's Republic of China
| | - Xin Ye
- Department of Chemistry, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, People's Republic of China
| | - Jun Yang
- Department of Chemistry, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, People's Republic of China.
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Al-Aasmi ZH, Shchukina A, Butts CP. Accelerating quantitative 13C NMR spectra using an EXtended ACquisition Time (EXACT) method. Chem Commun (Camb) 2022; 58:7781-7784. [PMID: 35731109 DOI: 10.1039/d2cc01768g] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Accurate quantitative 13C NMR spectra can be accelerated by using EXACT (EXtended ACquisition Time) NMR methods which reduce Nuclear Overhauser Enhancement (NOE) during the FID. This allows 30-50% shorter experiment times to be used when achieving a given level of quantitative accuracy.
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Affiliation(s)
- Zahra H Al-Aasmi
- School of Chemistry, University of Bristol, Cantocks Close, Bristol, BS8 1TS, UK.
| | | | - Craig P Butts
- School of Chemistry, University of Bristol, Cantocks Close, Bristol, BS8 1TS, UK.
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Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27123653. [PMID: 35744782 PMCID: PMC9227391 DOI: 10.3390/molecules27123653] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 06/03/2022] [Accepted: 06/05/2022] [Indexed: 11/16/2022]
Abstract
Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible, which provides us a powerful tool to analyze mixtures consisting of small molecules. However, the compound identification in NMR spectra of mixtures is highly challenging because of chemical shift variations of the same compound in different mixtures and peak overlapping among molecules. Here, we present a pseudo-Siamese convolutional neural network method (pSCNN) to identify compounds in mixtures for NMR spectroscopy. A data augmentation method was implemented for the superposition of several NMR spectra sampled from a spectral database with random noises. The augmented dataset was split and used to train, validate and test the pSCNN model. Two experimental NMR datasets (flavor mixtures and additional flavor mixture) were acquired to benchmark its performance in real applications. The results show that the proposed method can achieve good performances in the augmented test set (ACC = 99.80%, TPR = 99.70% and FPR = 0.10%), the flavor mixtures dataset (ACC = 97.62%, TPR = 96.44% and FPR = 2.29%) and the additional flavor mixture dataset (ACC = 91.67%, TPR = 100.00% and FPR = 10.53%). We have demonstrated that the translational invariance of convolutional neural networks can solve the chemical shift variation problem in NMR spectra. In summary, pSCNN is an off-the-shelf method to identify compounds in mixtures for NMR spectroscopy because of its accuracy in compound identification and robustness to chemical shift variation.
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15
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Direct Quantitation of Phytocannabinoids by One-Dimensional 1H qNMR and Two-Dimensional 1H- 1H COSY qNMR in Complex Natural Mixtures. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27092965. [PMID: 35566314 PMCID: PMC9103933 DOI: 10.3390/molecules27092965] [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: 03/27/2022] [Revised: 04/30/2022] [Accepted: 05/03/2022] [Indexed: 12/24/2022]
Abstract
The widespread use of phytocannabinoids or cannabis extracts as ingredients in numerous types of products, in combination with the legal restrictions on THC content, has created a need for the development of new, rapid, and universal analytical methods for their quantitation that ideally could be applied without separation and standards. Based on previously described qNMR studies, we developed an expanded 1H qNMR method and a novel 2D-COSY qNMR method for the rapid quantitation of ten major phytocannabinoids in cannabis plant extracts and cannabis-based products. The 1H qNMR method was successfully developed for the quantitation of cannabidiol (CBD), cannabidiolic acid (CBDA), cannabinol (CBN), cannabichromene (CBC), cannabichromenic acid (CBCA), cannabigerol (CBG), cannabigerolic acid (CBGA), Δ9-tetrahydrocannabinol (Δ9-THC), Δ9-tetrahydrocannabinolic acid (Δ9-THCA), Δ8-tetrahydrocannabinol (Δ8-THC), cannabielsoin (CBE), and cannabidivarin (CBDV). Moreover, cannabidivarinic acid (CBDVA) and Δ9-tetrahydrocannabivarinic acid (Δ9-THCVA) can be distinguished from CBDA and Δ9-THCA respectively, while cannabigerovarin (CBGV) and Δ8-tetrahydrocannabivarin (Δ8-THCV) present the same 1H-spectra as CBG and Δ8-THC, respectively. The COSY qNMR method was applied for the quantitation of CBD, CBDA, CBN, CBG/CBGA, and THC/THCA. The two methods were applied for the analysis of hemp plants; cannabis extracts; edible cannabis medium-chain triglycerides (MCT); and hemp seed oils and cosmetic products with cannabinoids. The 1H-NMR method does not require the use of reference compounds, and it requires only a short time for analysis. However, complex extracts in 1H-NMR may have a lot of signals, and quantitation with this method is often hampered by peak overlap, with 2D NMR providing a solution to this obstacle. The most important advantage of the COSY NMR quantitation method was the determination of the legality of cannabis plants, extracts, and edible oils based on their THC/THCA content, particularly in the cases of some samples for which the determination of THC/THCA content by 1H qNMR was not feasible.
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16
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Jayme SB, Prado FM, Massafera MP, Ronsein GE, Di Mascio P. Characterization and Quantification of Tryptophan and Tyrosine- Derived Hydroperoxides. Photochem Photobiol 2022; 98:678-686. [PMID: 35363890 DOI: 10.1111/php.13623] [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: 03/10/2022] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 11/28/2022]
Abstract
The reaction of 1 O2 with the amino acids tryptophan and tyrosine, either free or inserted in peptides or proteins, gives rise to hydroperoxides. To understand the impact of these hydroperoxides in complex biological systems, methods allowing their characterization and accurate quantification must be available. In this work, hydroperoxides derived from tryptophan, tyrosine and from peptides containing these amino acids were synthesized by photooxidation, and characterized by high-resolution mass spectrometry. In addition, experiments were carried out to compare two colorimetric methods commonly used for quantification of peroxides, namely the iodometric and the ferric-xylenol orange assays. For the tryptophan hydroperoxide, the quantifications obtained by colorimetric methods were then compared to that obtained by NMR. The results showed that for the ferric-xylenol orange, the stoichiometry between peroxide and Fe3+ ions vary considerably. On the other hand, for the iodometric assay, the stoichiometry peroxide : I3 - ions is always 1:1. However, the kinetics of the reactions of peroxides with I- vary, and the assay must be perfomed in anaerobic conditions. Thus, the iodometric method is more appropriate for precise quantification of a given peroxide. The characterization and accurate quantification of biological peroxides is key to understand the mechanisms involved in redox processes.
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Affiliation(s)
- Stella Boutris Jayme
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, 05508-000, Brazil
| | - Fernanda Manso Prado
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, 05508-000, Brazil
| | - Mariana Pereira Massafera
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, 05508-000, Brazil
| | - Graziella Eliza Ronsein
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, 05508-000, Brazil
| | - Paolo Di Mascio
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, 05508-000, Brazil
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