Research Progress of NMR in Natural Product Quantification

Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach

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.

Research Progress on Extraction and Detection Technologies of Flavonoid Compounds in Foods

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.

Pharmaceutical process-omics for quality control of traditional Chinese medicine preparations: A 1H-qNMR assisted case study of Guanxinning injection

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.

Phytochemical Profile, Antioxidant Potential, Antimicrobial Activity, and Cytotoxicity of Dry Extract from Rosa damascena Mill

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.

Natural compounds as lactate dehydrogenase inhibitors: potential therapeutics for lactate dehydrogenase inhibitors-related diseases

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.

Plasma metabolomics of oral squamous cell carcinomas based on NMR and MS approaches provides biomarker identification and survival prediction

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.

Head-to-Head Comparison of High-Performance Liquid Chromatography versus Nuclear Magnetic Resonance for the Quantitative Analysis of Carbohydrates in Yiqi Fumai Lyophilized Injection

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.

Advancing quantification methods for polyphenols in brown seaweeds-applying a selective qNMR method compared with the TPC assay

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.

Simultaneous quantification of cellulose and pectin in tobacco using a robust solid-state NMR method

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.

Accelerating quantitative 13C NMR spectra using an EXtended ACquisition Time (EXACT) method

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.

Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures

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.

Direct Quantitation of Phytocannabinoids by One-Dimensional 1H qNMR and Two-Dimensional 1H-1H COSY qNMR in Complex Natural Mixtures

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.

Characterization and Quantification of Tryptophan and Tyrosine- Derived Hydroperoxides

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.