Ligand-aided 1H Nuclear Magnetic Resonance Spectroscopy for Non-destructive Estimation of Sulfate Content in Sulfated Saccharides

Rapid estimation approach for glycosylated serum protein of human serum based on the combination of deep learning and TD-NMR technology

Rapid and precise estimation of glycosylated serum protein (GSP) of human serum is of great importance for the treatment and diagnosis of diabetes mellitus. In this study, we propose a novel method for estimation of GSP level based on the combination of deep learning and time domain nuclear magnetic resonance (TD-NMR) transverse relaxation signal of human serum. Specifically, a principal component analysis (PCA)-enhanced one-dimensional convolutional neural network (1D-CNN) is proposed to analyze the TD-NMR transverse relaxation signal of human serum. The proposed algorithm is proved by accurate estimation of GSP level for the collected serum samples. Furthermore, the proposed algorithm is compared with 1D-CNN without PCA, long short-term memory network (LSTM) and some conventional machine learning algorithms. The results indicate that PCA-enhanced 1D-CNN (PC-1D-CNN) has the minimum error. This study proves that proposed method is feasible and superior to estimate GSP level of human serum using TD-NMR transverse relaxation signals.

Quantitative 1H NMR with global spectral deconvolution approach for the determination of gamma-aminobutyric acid in Chinese yam (Dioscorea polystachya Turczaninow)

We developed a quantitative proton nuclear magnetic resonance (qNMR) with global spectral deconvolution (GSD) method to determine the gamma-aminobutyric acid content in Chinese yam with the proton signal at δ_H 2.30. Trimethylsilyl-2,2,3,3-tetradeuteropropionic acid sodium salt was set as the internal standard. The method was validated and showed admissible stability, repeatability, and precision. Compared to the traditional high-performance liquid chromatography method, this method did not involve tedious pre-treatment and expensive standard. Compared to ordinary qNMR, GSD algorithm could effectively remove the effect of noise, baseline distortions and signal overlapping. Overall, qNMR with GSD method is a rapid, simple and reliable method to quantitatively determine functional metabolites even overlapped with other compounds in herbs or foods.

Identification of the Principle of Taste Sensors to Detect Non-Charged Bitter Substances by 1H-NMR Measurement

A taste sensor with lipid/polymer membranes is attracting attention as a method to evaluate taste objectively. However, due to the characteristic of detecting taste by changes in membrane potential, taste sensors cannot measure non-charged bitter substances. Many foods and medicines contain non-charged bitter substances, and it is necessary to quantify these tastes with sensors. Therefore, we have been developing taste sensors to detect bitter tastes caused by non-charged substances such as caffeine. In previous studies, a sensor for detecting bitterness caused by caffeine and theobromine, theophylline, was developed, using a membrane modified with hydroxybenzoic acid (HBA) as the sensing part. The sensor was designed to form intramolecular hydrogen bonds (H-bonds) between the hydroxy group and carboxy group of HBA and to successively cause the intermolecular H-bonds between HBA and caffeine molecules to be measured. However, whether this sensing principle is correct or not cannot be confirmed from the results of taste sensor measurements. Therefore, in this study, we explored the interaction between HBA and caffeine by ¹H-nuclear magnetic resonance spectroscopy (NMR). By the ¹H NMR detection, we confirmed that both the substances interact with each other. Furthermore, the nuclear Overhauser effect (NOE) of intermolecular spatial conformation in solution was measured, by which 2,6-dihydroxybenzoic acid (2,6-DHBA) preferably interacted with caffeine via the H-bonding and stacking configuration between aromatic rings. Identifying the binding form of 2,6-DHBA to caffeine was estimated to predict how the two substances interact.

Quantification of Cathinone Analogues without Reference Standard Using 1H Quantitative NMR

Synthetic cathinones are a type of new psychoactive substances (NPS) that have been seriously abused. Owing to the rapid variation in their structures, the absence of reference standards poses a challenge in quantitative investigations. In this study, a ¹H quantitative nuclear magnetic resonance (¹H qNMR) method was established using maleic acid as the internal standard and the shared signal (i.e., the methylidyne hydrogen) on the parent synthetic cathinones structure as the quantitative peak. Taking 3-methoxy-2-(methylamino)-1-(4-methylphenyl)propan-1-one (mexedrone) as an example, this study optimized the acquisition parameters and conducted method validation, including an evaluation of the specificity, linearity, accuracy, precision, and robustness. Using this ¹H qNMR method, the contents of mexedrone and its analogues, including 1-(3-chlorophenyl)-2-(ethylamino)-propan-1-one (3-CEC), 4-chloro-α-pyrroli-dinopropiophenone (4-Cl-α-PVP), 1-(3,4-methylenedioxy-phenyl)-2-propylamino-propan-1-one (propylone), and methcathinone, were obtained. The obtained results showed that the method was accurate, rapid, versatile, and can be used to address the qualitative and quantitative issues related to similar substances.

Quantitative 1H NMR for the Direct Quantification of Saikosaponins in Bupleurum chinense DC

Saikosaponin a and saikosaponin d are used as chemical standards for the quality evaluation of Bupleurum chinense DC. by the high-performance liquid chromatography method in current Chinese Pharmacopoeia. However, other saikosaponins, such as saikosaponin c and saikosaponin b₂, also possess pharmaceutical activity, but are not used as chemical standards. In this study, a quantitative proton nuclear magnetic resonance (¹H NMR) method was developed to determine the total mass percentage (mg/g) of SSa, SSb₁, SSb₂ and SSd in B. chinense DC., using the H-24 (δ_H 0.71) signal. Furthermore, the molality (mol/kg) of type I saikosaponins (epoxy-ether structure) was also determined by quantitative ¹H NMR in the area of H-11 (δ_H 5.95) for a more accurate quality evaluation. Validation of the method confirmed that it has acceptable selectivity, precision, stability, and repeatability. The results indicated that this method has the potential to be a reliable method for the quantification of saikosaponins in Bupleurum scorzonerifolium Willd., vinegar baked B. chinense DC. and B. scorzonerifolium Willd., Chaihu Koufuye (oral liquid of Chaihu).