Min Li Xu

An approach to the simultaneous quantitative analysis of metabolites in table wines by 1H NMR self-constructed three-dimensional spectra

Wine consists of several hundred components with different concentrations, including water, ethanol, glycerol, organic acids and sugars. Accurate quantification of target compounds in such complex samples is a difficult task based on conventional (1)H NMR spectra due to some challenges. In this paper, the three-dimensional spectrum was constructed firstly by simply repeating (1)H NMR spectrum itself so as to extract the features of target compounds by Tchebichef moment method. A proof-of-concept model system, the determination of five metabolites in wines was utilized to evaluate the performance of the proposed strategy. The results indicate that the proposed approach can provide accurate and reliable concentration predictions, probably the best results ever achieved using PLS and interval-PLS methods. Our novel strategy has not only good performance but also does not require laborious multi-step and subjective pretreatments. Therefore, it is expected that the proposed method could extend the application of conventional (1)H NMR.

Krawtchouk image moment method for the simultaneous determination of three drugs in human plasma based on fluorescence three-dimensional spectra

The interference signals and overlapped peaks are common phenomena in fluorescence determination, which seriously influence the accuracy and reliability of analytical results. In this paper, Krawtchouk image moment method was introduced to the analysis of fluorescence three-dimensional (3D) spectra and applied to the quantitative analysis of three drugs including nicotinic acid, metoprolol and amlodipine in human plasma. Without any pretreatment to the obtained spectra, Krawtchouk moments were directly calculated on the grayscale images of 3D spectra, and the quantitative linear models for the three drugs were established by stepwise regression, respectively. The determination coefficients (R) were more than 0.9906. The correlation coefficients of leave-one-out cross-validation (Rcv) were more than 0.9256. The precisions (RSD, %) of inter-day and intra-day variations were less than 8.4% and 3.1%, separately. The recovery was from 101.84% to 107.88%. The limit of quantification and the limit of detection were 0.12μgmL-1 and 0.43μgmL-1, respectively. All the statistical parameters supported that the obtained models performed well and the proposed method was accurate and reliable. Our study indicates that Krawtchouk image moments with the powerful abilities of multi-resolution and extracting local information can be applied to the simultaneous determination of multi-target compounds in plasma based on fluorescence 3D spectra.

Quantitative analysis of multiple components based on liquid chromatography with mass spectrometry in full scan mode

Although liquid chromatography with mass spectrometry in full scan mode can obtain all the signals simultaneously in a large range and low cost, it is rarely used in quantitative analysis due to several problems such as chromatographic drifts and peak overlap. In this paper, we propose a Tchebichef moment method for the simultaneous quantitative analysis of three active compounds in Qingrejiedu oral liquid based on three-dimensional spectra in full scan mode of liquid chromatography with mass spectrometry. After the Tchebichef moments were calculated directly from the spectra, the quantitative linear models for three active compounds were established by stepwise regression. All the correlation coefficients were more than 0.9978. The limits of detection and limits of quantitation were less than 0.11 and 0.49 μg/mL, respectively. The intra- and interday precisions were less than 6.54 and 9.47%, while the recovery ranged from 102.56 to 112.15%. Owing to the advantages of multi-resolution and inherent invariance properties, Tchebichef moments could provide favorable results even in the situation of peaks shifting and overlapping, unknown interferences and noise signals, so it could be applied to the analysis of three-dimensional spectra in full scan mode of liquid chromatography with mass spectrometry.

Prediction of phosphorylation sites based on Krawtchouk image moments

Protein phosphorylation is one of the most pervasive post‐translational modifications and regulates diverse cellular processes in organisms. Under the catalysis of protein kinases, protein phosphorylation usually occurred in the residues serine (S), threonine (T), or tyrosine (Y). In this contribution, we proposed a novel scheme (named KMPhos) for the theoretical prediction of protein phosphorylation sites. First, the numerical matrix was obtained from a protein sequence fragment by replacing the characters of the residues with the chemical descriptors of amino acid molecules to approximately describe the chemical environment of the protein fragment, which was turned to the grayscale image. Then the Krawtchouk image moments were calculated and used to establish the support vector machine models. The accuracies of 10‐fold cross validation for the obtained models on the training set are up to 89.7%, 88.6%, and 90.1% for the residues S, Y, and T, respectively. For the independent test set, the prediction accuracies are up to 90.7% (S), 87.8% (T), and 89.3% (Y). The results of ROC and other evaluations are also satisfactory. Compared with several specialized prediction tools, KMPhos provided the higher accuracy and reliability. An available KMPhos package is provided and can be used directly for phosphorylation sites prediction.

Quality assessment of Traditional Chinese Medicine using HPLC-PAD combined with Tchebichef image moments.

Traditional Chinese medicines have gotten growing attention and the product quality also became uneven. In this paper, Tchebichef image moments coupled with high performance liquid chromatography with photodiode array detector were proposed to the similarity analysis of the fourteen batches of Pudilan Xiaoyan tablets (Chinese medicine complex), which were based on the grayscale images of three dimensional (3D) fingerprint spectra. Hierarchical cluster analysis was used for displaying the classification results. As a comparison, traditional principal component analysis (PCA) method based on the chromatograms under single-fixed wavelength was carried out on the same samples. The analytical results indicated that the proposed approach could provide more accurate and reasonable results owing to its powerful invariant and multi-resolution capability of image moments.

Simultaneous quantitative analysis of three components in mixture samples based on NIR spectra with temperature effect

The temperature effect is usually regarded as one of the interference parameters in the routine analysis of near infrared (NIR) spectra. In this paper, the Tchebichef image moment (TM) method was proposed and applied to the quantitative analysis of three components in mixture samples based on their raw NIR three-dimensional (3D) spectra with temperature effect. After the NIR 3D spectra were converted to their grayscale image, TMs with different orders were calculated as independent variants and employed to establish quantitative models by stepwise regression. The correlation coefficients of leave-one-out cross-validation (Rloo-cv2) for the three obtained models based on the calibration set were from 0.9952 to 0.9992 and the predictive correlation coefficients (Rp2) for the prediction set were from 0.9926 to 0.9977. Compared with the conventional partial least squares regression method, the proposed method has obvious advantages such as simplicity, reliability and accuracy, and may be a promising alternative approach for the simultaneous quantitative analysis of multiple target components in mixture samples by using NIR 3D spectra with temperature effect.

A fast chemometrics approach to quantitative analysis of metformin hydrochloride, enalapril maleate, and captopril in tablets based on HPLC-PAD spectra

Diabetes mellitus and concurrent hypertension disorder are dreadful all over the world and are often managed by some drugs, such as metformin hydrochloride (MFH), enalapril maleate (ENM), and capto...

The multi-resolution capability of Tchebichef moments and its applications to the analysis of fluorescence excitation-emission spectra

Fluorescence spectroscopy with an excitation-emission matrix (EEM) is a fast and inexpensive technique and has been applied to the detection of a very wide range of analytes. However, serious scattering and overlapping signals hinder the applications of EEM spectra. In this contribution, the multi-resolution capability of Tchebichef moments was investigated in depth and applied to the analysis of two EEM data sets (data set 1 consisted of valine-tyrosine-valine, tryptophan-glycine and phenylalanine, and data set 2 included vitamin B1, vitamin B2 and vitamin B6) for the first time. By means of the Tchebichef moments with different orders, the different information in the EEM spectra can be represented. It is owing to this multi-resolution capability that the overlapping problem was solved, and the information of chemicals and scatterings were separated. The obtained results demonstrated that the Tchebichef moment method is very effective, which provides a promising tool for the analysis of EEM spectra. It is expected that the applications of Tchebichef moment method could be developed and extended in complex systems such as biological fluids, food, environment and others to deal with the practical problems (overlapped peaks, unknown interferences, baseline drifts, and so on) with other spectra.

Application of image moments in MIA-QSAR: Application of image moments

Owing to the presence of some significant chemical information, the conventional images of molecular structures have been used in the studies of quantitative structure‐activity relationship by multivariate image analysis (MIA‐QSAR). In this contribution, we suggest that the Tchebichef moments (TMs) calculated directly from the grayscale images of molecular structures are used as molecular descriptors to build linear QSAR models by stepwise regression. The proposed approach was applied to QSAR research on a series of HIV‐1 non‐nucleoside reverse transcriptase inhibitors, and satisfactory results were obtained. Compared with several published methods, the results indicate that the TM method possesses higher accuracy and reliability. The TMs effectively decompose the image information of molecular structures at different levels without any pretreatment owing its very favorable multiresolution, holographic, and inherent invariance properties. Our study successfully extends the application of image moments to MIA‐QSAR research.