Chemical image moments and their applications

An exhaustive analysis of the use of image moments for second-order calibration. A comparison with multivariate curve resolution-alternating least-squares

BACKGROUND

the chemometric processing of second-order chromatographic-spectral data is usually carried out with the aid of multivariate curve resolution-alternating least-squares (MCR-ALS). Recently, an alternative procedure was described based on the estimation of image moments for each data matrix and subsequent application of multiple linear regression after suitable variable selection.

RESULTS

The analysis of both simulated and experimental data leads to the conclusion that the image moment method, although can cope with chromatographic lack of reproducibility across injections, it only performs well in the absence of uncalibrated interferents. MCR-ALS, on the other hand, provides good analytical results in all studied situations, whether the test samples contain uncalibrated interferents or not.

SIGNIFICANCE

The results are useful to assess the real usefulness of newly proposed methodologies for second-order calibration in the case of chromatographic-spectral data sets, especially when samples contain unexpected chemical constituents.

Chemical fingerprint analysis and quality assessment of Tibetan medicine Triphala from different origins by high-performance liquid chromatography

INTRODUCTION

Although the Tibetan medicine Triphala (THL) is widely used in many countries, insufficient progress has been made in quality control.

OBJECTIVES

The present study aimed to propose a methodology for quality control of THL based on HPLC fingerprinting combined with an orthogonal array design.

METHODS

Seven identified peaks were used as indicators to examine the effects of temperature, extraction time, and solid-liquid ratio on the dissolution of active ingredients in THL. Fingerprint analysis was performed on 20 batches of THL from four geographical areas (China, Laos, Thailand, and Vietnam). For further chemometric assessment, analysis techniques including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discrimination analysis (OPLS-DA) were used to classify the 20 batches of samples.

RESULTS

Fingerprints were established and 19 common peaks were identified. The similarity of 20 batches of THL was more than 0.9 and the batches were divided into two clusters. Four differential components of THL were identified based on OPLS-DA, including chebulinic acid, chebulagic acid, and corilagin. The optimal extraction conditions were an extraction time of 30 min, a temperature of 90°C, and a solid-liquid ratio of 30 mL/g.

CONCLUSION

HPLC fingerprinting combined with an orthogonal array design could be used for comprehensive evaluation and quality assessment of THL, providing a theoretical basis for further development and utilization of THL.

Quantitative analysis of terahertz signals using CWT-based spectrogram and Zernike image moments

The combination of terahertz (THz) spectroscopic measurements and multivariate calibration techniques has become a well-established technique in many research fields. However, intentional or unintentional changes in environmental conditions, THz instruments and/or of the substance itself make the established calibration model becoming insufficient and inadequate for the further application. In this article, we introduce, discuss, and evaluate a new multivariate calibration method, the CWT-ZM, that combines the merits of the Zernike moment (ZM) invariance and the continuous wavelet transform (CWT) time-frequency analysis. With the help of a wavelet time-frequency analysis, the THz pulse is expanded into a two-dimensional (2D) time-frequency plane that provides richer and more direct characteristic information in the time and frequency domain simultaneously. In addition, Zernike moments provide linearly independent descriptors for the 2D time-frequency intensity image and are invariant to THz signal affine transformations, such as peak shifting, baseline drifting, and scaling. In this manner, we obtain a set of features that exhibit a high capability to capture the concentrations of the target compounds and a high invariance of the different measuring instruments and the variable environment. This approach results in a more robust regression system with improved generalization properties with respect to standard methods. Experiments were then conducted on a THz dataset of pharmaceutical tablets acquired by two different THz instruments, and these confirmed the effectiveness of the proposed approach. Furthermore, CWT-ZM is an extensible framework that can be combined with various spectral qualitative and quantitative analysis algorithms.

A simple approach to the prediction of soil sorption of organophosphorus pesticides

Organophosphorus pesticides (OP) affect the crops and environments, and the reliable approach to the prediction of soil sorption of pesticides is required. In this respect, we proposed a simple Chemometrics approach, in which the Tchebichef image moment (TM) method was used to extract useful information from the greyscale images of molecular structures and the quantitative model was established by stepwise regression to predict the soil sorption of OPs. Different squared correlation coefficients including the leave-one-out cross-validation (LOO-CV) (Q²) that concerns the training set and the (R²_test) which concerns the external independent test set are more than 0.96. This reflects that the established model has considerably high accuracy and reliability. Compared with the literature on the strategies of quantitative structure-property relationship (QSPR), the proposed method is more suitable, in which the established model shows a high predictive ability. Our study provides another effective approach to predict the soil sorption of OPs and also extends the innovative pathway of QSPR modelling.

Chemometrics-assisted simultaneous voltammetric determination of multiple neurotransmitters in human serum

An electrochemical method combining chemometrics was developed for simultaneous quantification of multiple neurotransmitters including Dopamine (DA), Epinephrine (EP), Norepinephrine (NE) and serotonin (5-hydroxytryptamine, 5-HT) in human blood serum. A reduced graphene oxide modified glassy carbon electrode (RGO/GCE) was prepared via electrodeposition method. Differential pulse voltammetry (DPV) measurement of the four neurotransmitters showed that the voltammetric signals of the four targets overlapped significantly. To facilitate the simultaneous determination of the neurotransmitters, a chemometric tool of Tchebichef curve moment (TcM) method was proposed. The TcMs calculated from the voltammograms were used to establish the quantitative models by stepwise regression. The intra-day and inter-day precisions of the proposed method were less than 3.5% and 8.1%, respectively, and the recoveries were from 87.4% to 124%. The limit of detection (LOD) for DA, EP, NE and 5-HT were 74 nM, 104 nM, 84 nM and 97 nM, respectively. The above results indicated that the proposed approach is simple and reliable for the simultaneous determination of multiple neurotransmitters in human serum.

An effective approach to the early diagnosis of colorectal cancer based on three-dimensional fluorescence spectra of human blood plasma

Colorectal cancer (CRC) is a common malignancy in the gastrointestinal tract, and its screening rates remain relatively low in the general population due to the lack of specific symptoms and effective methods. It is still in urgent need to develop rapid and reliable approach to the early diagnosis of CRC. Herein, based on the three-dimensional (3D) fluorescence spectra of human blood plasma, a combination strategy of Tchebichef image moments coupled with partial least squares-discriminate analysis (TM-PLS-DA) was proposed for the detection of CRC from three classes (CRC samples, adenomas samples and non-malignant findings). The established TM-PLS-DA classification model provided an 84 % correct classification for CRC prediction. Venetian blinds 10-fold cross validation was carried out. The error rates both in cross validation and test sets were less than 0.16. Sensitivity and specificity for CRC prediction were 0.95 and 0.88, respectively. At the same time, the diagnostic capacity of the proposed method was tested by receiver operating characteristics (ROC) analysis with area under the curve (AUC) of 0.94 for CRC diagnosis. These results demonstrate that the proposed TM-PLS-DA method based on the 3D fluorescence spectra of blood plasma has great advantage for the accurate CRC detection, which will provide a potential alternative approach for cancer diagnostics.

Novel Approach to the Analysis of Chemical Third-Order Data

For the more complex samples, chemical higher-order data can be collected from various information sources, which become the necessary foundation of accurate analysis. In this article, the Tchebichef cubic moment (TCM) was developed for the analysis of chemical third-order data for the first time. Then, the proposed TCM approach was applied to the fluorescence excitation-emission time data for the analysis of adrenaline and noradrenaline in urinary samples (Data I) and the data fusion of the excitation-emission matrix (EEM), NMR, and liquid chromatography-mass spectrometry (LC-MS) spectra for the determination of the five target components (Data II). For Data I, all of the cross-validation correlation coefficients (R_cv²) of the obtained linear models on the calibration set were more than 0.9937 and the prediction root-mean-square errors (RMSE_p) of the external independent test samples were less than 0.0250 μM. For Data II, all of the R_cv² were higher than 0.9846 and RMSE_p were less than 0.2267 μM. Compared with several conventional methods, the proposed method was more convenient and accurate. This study provides another effective approach to the analysis of complex samples based on their chemical third-order data.

A Preferable Approach for the Quality Control of Xiaoer Chiqiao Qingre Granules Based on the Combination of Chromatographic Fingerprints and Chemometrics

A preferable approach of a combination of a multiwavelength fusion HPLC fingerprint and chemometrics for the quality control of Xiaoer Chiqiao Qingre granules (XCQG) was established in this study. A single-wavelength HPLC fingerprint was performed to identify 18 peaks as common peaks in the beginning, and 12 of them were recognized by HPLC-Q/TOF-MS. To overcome the limitation of the single-wavelength HPLC fingerprint, a three-wavelength (230 nm, 250 nm, and 330 nm) fusion fingerprint was established for a more thorough quality assessment. Six main active ingredients (geniposide, paeoniflorin, forsythin, forsythoside A, baicalin, and wogonoside) were selected as chemical markers for simultaneous quantitative analysis, while the results indicated that the content of other five ingredients except forsythoside A presented comparatively stable. Chemometrics including hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to evaluate the homogeneity and heterogeneity of sixteen batches of XCQG. The results of the multiwavelength fingerprint were clearly classified into two clusters by HCA, whereas the single-wavelength fingerprint showed no distinct difference between them. OPLS-DA was further employed to prove that the above six main active ingredients made great contributions to clustering. In summary, this integrated analysis provided a better promoted and more comprehensive method to control the quality of XCQG.

A simple approach to the determination of three curcuminoids with similar chemical structures in different substrates

The determination of curcuminoids in mixtures is more difficult due to their similar chemical structures as well as serious interferences, thus the complex pretreatments of samples and the optimization of experimental conditions are often required. Here, owing to the mathematical separation of chemical signals by Tchebichef image moments, a simple and effective approach to the simultaneous quantitative analysis was proposed, and applied to the determination of the three curcuminoids in turmeric and curry based on their raw fluorescence 3D spectra. For the established linear models, the leave-one-out correlation coefficients (R _loo-cv) were more than 0.9816 within the linear ranges, and the predictive correlation coefficients (R _p) for the external independent samples were more than 0.9897. The intra- and inter-day precision (less than 6.82%, RSD), average spiked recovery (89.9% ~ 100.8%), LOD (less than 0.07 μg/mL) and LOQ (less than 0.23 μg/mL) suggest that the proposed approach is accurate and reliable. Compared with N-PLS and MCR-ALS methods, our method can obtain more satisfactory results. This study provides a convenient pathway for the rapid analysis of multi-target components with similar chemical structures in mixture of different substrates.

Terahertz spectroscopy technology as an innovative technique for food: Current state-of-the-Art research advances

With the dramatic development of source and detector components, terahertz (THz) spectroscopy technology has recently shown a renaissance in various fields such as medical, material, biosensing and pharmaceutical industry. As a rapid and noninvasive technology, it has been extensively exploited to evaluate food quality and ensure food safety. In this review, the principles and processes of THz spectroscopy are first discussed. The current state-of-the-art applications of THz and imaging technologies focused on foodstuffs are then discussed. The advantages and challenges are also covered. This review offers detailed information for recent efforts dedicated to THz for monitoring the quality and safety of various food commodities and the feasibility of its widespread application. THz technology, as an emerging and unique method, is potentially applied for detecting food processing and maintaining quality and safety.

A Simple Approach to the Toxicity Prediction of Anilines and Phenols Towards Aquatic Organisms

Chemicals pollution in the environment has attracted attention all over the world, and the toxicity prediction of chemical pollutants has become quite important. In this paper, we introduce a simple approach to predict the toxicity of some chemical components, in which the Tchebichef image moment (TM) method was employed to extract useful chemical information from the images of molecular structures to establish quantitative structure-activity relationship (QSAR) prediction models. The proposed approach was applied to predict the toxicity of anilines and phenols for the aquatic organisms of P. subcapitata and V. fischeri, in which the obtained TMs were defined as the independent variables, while the biological toxicity (pEC₅₀) was regarded to be the dependent variable. Then, the predictive models were established by stepwise regression, respectively. The obtained squared correlation coefficients of leave-one-out cross-validation (Q²) for training sets and the predictive squared correlation coefficients (R_p²) for test sets of the two groups of data were higher than 0.79 and 0.75, respectively, which indicated that the obtained models possessed satisfactory accuracy and reliability. Compared with several reported methods, the proposed approach was more convenient and has a higher predictive capability. Our study provides another perspective in QSAR research.

The activity prediction of indole inhibitors against HCV NS5B polymerase

Non-structural viral protein 5B (NS5B) is a viral protein in hepatitis C virus. Although various inhibitors against NS5B have been found, the activity prediction of similar untested inhibitors is still highly desirable. In this respect, the Tchebichef moments (TMs) calculated from the images of molecular structures were regarded as the independent variables while the inhibitory activity (pIC₅₀ ) was the dependent variable, and the predictive model was established by means of stepwise regression. The R-squared of leave-one-out cross-validation (Q² ) for the training set and the R-squared of prediction ( R p 2 ) for external independent test set were 0.919 and 0.927, respectively. The obtained model was also evaluated strictly. Compared with the multivariate curve resolution with alternating least squares (MCR-ALS) and the QSAR approaches derived from the literature, the proposed method is more accurate and reliable. This study not only provides an effective approach to predict the biological activity of RNA replication's inhibitors, but also extends the QSAR modeling technique.

A New Red-Emitting Fluorescence Probe for Rapid and Effective Visualization of Bisulfite in Food Samples and Live Animals

The development of new methods for rapid and effective detection of bisulfite (HSO₃^-) in food samples and imaging of HSO₃^- intake in animals is of significant importance due to the key roles of HSO₃^- in food quality assurance and community health. In this work, a new responsive fluorescence probe, EQC, is reported for the quantitative detection of HSO₃^- in food samples and visualization of HSO₃^- intake in animals. Upon addition of HSO₃^-, the UV-vis absorption and red emission of EQC were significantly decreased within 120 s. The changes in absorption and emission spectra of EQC were rationalized by theoretical computations. The proposed reaction mechanism of EQC with HSO₃^- was confirmed by high-resolution mass spectrometry (HRMS) and spectroscopic titration measurements. EQC has the advantages of high sensitivity, selectivity (a detection limit of 18.1 nM), and fast response toward HSO₃^-, which enable rapid and effective HSO₃^- detection in buffer solution. The practical applications of EQC were demonstrated by the detection of HSO₃^- in food samples and the imaging of HSO₃^- intake in live animals.

Simultaneous quantification of multiple endogenous biothiols in cancer cells based on a multi-signal fluorescent probe

The feature information was extracted from the 3D spectrum by the TM method, and the simultaneous quantification of intracellular thiols was realized.