Characterization of radix rehmanniae processing procedure using FT-IR spectroscopy through nonnegative independent component analysis

A method is proposed for monitoring the radix rehmanniae proparate processing procedure and determining the endpoint of the process using attenuated total reflectance (ATR) FT-IR through nonnegative independent component analysis (ICA). In the proposed method, ATR FT-IR spectra of the samples were firstly measured at different steaming periods. Then, nonnegative ICA was used for direct estimation of the feature spectra of the pure components in the mixture without pre-separation and other prior information. The estimated independent components (ICs) and their variation of the relative concentrations were used to characterize the processing procedure and determine the endpoint. The results show that the estimated three ICs are consistent with that of the chemical components in the mixtures, i.e. catalpol/rehmaionoside, glucose, and other compounds that nearly keep invariant during the processing procedure. The endpoint determined by the IR-ICA method is 15 h, which was located in the range obtained by expert sensory analysis, whereas the endpoint determined by the traditional sensory analysis is 14 ∼ 17 h and even 14 ∼ 20 h, which showed the significant deviation of the endpoints determined by different operators. Figure Characterisation of radix rehmanniae processing procedure using FT-IR spectroscopy through nonnegative independent component analysis     

Estimation of source infrared spectra profiles of acetylspiramycin active components from troches using kernel independent component analysis

Kernel independent component analysis (KICA), a kind of independent component analysis (ICA) algorithms based on kernel, was preliminarily investigated for blind source separation (BSS) of source spectra profiles from troches. The robustness of different ICA algorithms (KICA, FastICA and Infomax) was first checked by using them in the retrieval of source infrared (IR), ultraviolet (UV) and mass spectra (MS) from synthetic mixtures. It was found that KICA is the most robust method for retrieval of source spectra profiles. KICA algorithm is subsequently adopted in the analysis of diffuse reflection IR of acetylspiramycin (ASPM) troches. It is observed that KICA is able to isolate the theoretically predicted spectral features corresponding to the ASPM active components, excipients and other minor components as different independent (spectral) component. A troche can be authenticated and semi-quantified using the estimated ICs. KICA is an useful method for estimation of source spectral features of molecules with different geometry and stoichiometry, while features belonging to very similar molecules remain grouped.     

Determination of endpoint of procedure for radix rehmanniae steamed based on ultraviolet spectrophotometry combination with continuous wavelet transform and kernel independent component analysis

A method for determination of the endpoint of the procedure for radix rehmanniae steamed was proposed based on UV spectrophotometry combination with continuous wavelet transform and kernel independent component analysis (UV-CWT-KICA). In the proposed method, the raw UV spectra of the rehmanniae samples during steamed procedure were measured. The raw UV spectral data were firstly pretreated by CWT for elimination of the noise signal and enrichment of the spectral resolution, then the independent components (ICs) were estimated from the mixed CWT coefficient matrix. The results show that the ICs are chemical significance with their relative concentrations gradually decreasing or increasing during the first steamed period, and the endpoint of the steamed procedure can be determined by inspection of the relative concentration profiles, at which the ICs should be approached maximum or minimum. Furthermore, the estimated ICs of rehmanniae samples from different areas or with different grades are similar, and the relative concentration of the similar ICs in different groups are increasing or decreasing before the first 14 h, and nearly steady or some decreasing after 16 h. Based on the variations of the relative concentration profiles of the ICs, the endpoint of the steamed procedure can be determined as 15 h, while that determined by sensory analysis is 14-20 h. The proposed UV-CWT-KICA method can avoid the higher deviations of the endpoints that were determined by sensory analysis. It provides an alternative approach for determination of the endpoint of the procedure for processing traditional Chinese medicine (TCM).     

Estimation of source spectra profiles and simultaneous determination of polycomponent in mixtures from ultraviolet spectra data using kernel independent component analysis and support vector regression

A method that use kernel independent component analysis (KICA) and support vector regression (SVR) was proposed for estimation of source ultraviolet (UV) spectra profiles and simultaneous determination of polycomponents in mixtures. In KICA-SVR procedure, the UV source spectra profiles were estimated using KICA, then the mixing matrix of the components were calculated using the estimated sources, and the calibration model was build using SVR based on the calculated mixing matrix. A simulated UV dataset of three-component mixtures was used to test the ability of KICA for estimating source spectra profiles from spectra data of mixtures. It was found that KICA has the potential power to estimate pure UV spectra profiles, and correlation coefficient of estimated sources correspond to the real adopted ones are better compared with that by FastICA and Infomax ICA. An UV dataset of polycomponent vitamin B was processed using the proposed KICA-SVR method. The results show that the estimated source spectra profiles are correlative with the real UV spectra of the components and chemically interpretable, and accurate results were obtained.     

Independent component analysis and its applications in signal processing for analytical chemistry

Independent component analysis (ICA) is a statistical method the goal of which is to find a linear representation of non-Gaussian data so that the components are statistically independent, or as independent as possible. In an ICA procedure, the estimated independent components (ICs) are identical to or highly correlated to the spectral profiles of the chemical components in mixtures under certain circumstances, so the latent variables obtained are chemically interpretable and useful for qualitative analysis of mixtures without prior information about the sources or reference materials, and the calculated demixing matrix is useful for simultaneous determination of polycomponents in mixtures. We review commonly used ICA algorithms and recent ICA applications in signal processing for qualitative and quantitative analysis. Furthermore, we also review the preprocessing method for ICA applications and the robustness of different ICA algorithms, and we give the empirical criterion for selection of ICA algorithms in signal processing for analytical chemistry.     

Profiling and analysis of multiple compounds in rhubarb decoction after processing by wine steaming using UHPLC–Q‐TOF‐MS coupled with multiple statistical strategies

Rhubarb is one of the most popular traditional Chinese medicines and has been used for thousands of years in many Asian countries. Prepared rhubarb is obtained by steaming raw rhubarb with glutinous rice wine until it turned black in appearance both inside and outside. After processing, the therapeutic effects of prepared rhubarb change a lot. To find out the exact compound changes of the chemical profile in a decoction of rhubarb after processing and to clarify the material basis of the changed therapeutic effects, an ultra‐high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry method coupled with automated data analysis software and statistical strategy was developed. As a result, 63 peaks in raw rhubarb and 54 peaks in prepared rhubarb were detected, and a total of 45 chemical compounds were identified. The analysis data were subjected to a principle component analysis and a t‐test. Based on the results, 16 peaks were found to be the main contributors to the significant difference (p < 0.05) between raw and prepared rhubarb. Compared with raw rhubarb, the content of 15 components in prepared rhubarb was lower, while only rhein (1,8‐dihydroxy‐3‐carboxy anthraquinone) showed a higher intensity.     

Standardless multicomponent qNMR analysis of compounds with overlapped resonances based on the combination of ICA and PULCON

A fast and reliable nuclear magnetic resonance (NMR) method for quantitative analysis of targeted compounds with overlapped signals in complex mixtures has been established. The method is based on the combination of chemometric treatment for spectra deconvolution and the PULCON principle (pulse length based concentration determination) for quantification. Independent component analysis (ICA) (mutual information least dependent component analysis (MILCA) algorithm) was applied for spectra deconvolution in up to six component mixtures with known composition. The resolved matrices (independent components, ICs and ICA scores) were used for identification of analytes, calculating their relative concentrations and absolute integral intensity of selected resonances. The absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated using the PULCON principle. Instead of conventional application of absolute integral intensity in case of undisturbed signals, the multiplication of resolved IC absolute integral and its relative concentration in the mixture for each component was used. Correction factors that are required for quantification and are unique for each analyte were also estimated. The proposed method was applied for analysis of up to five components in lemon and orange juice samples with recoveries between 90% and 111%. The total duration of analysis is approximately 45 min including measurements, spectra decomposition and quantification. The results demonstrated that the proposed method is a promising tool for rapid simultaneous quantification of up to six components in case of spectral overlap and the absence of reference materials. Copyright © 2015 John Wiley & Sons, Ltd.     

Simultaneous spectrophotometric determination of furazolidone and berberine in tablet form

Two spectrophotometric procedures are suggested for the analysis of mixtures of furazolidone and berberine in tablets. No preliminary separation step is required. The first procedure is based on the use of the modified Vierordt equation as developed by Glenn. The second depends on the spectral changes induced for both components by reduction with zinc and hydrochloric acid. The methods have been applied to the assay of mixtures of the two compounds in tablets and the results obtained compared favourably with those obtained by other methods, but the proposed methods are more accurate and precise and less time-consuming.     

Local covariance order diffusion-ordered spectroscopy: a powerful tool for mixture analysis

Diffusion-ordered spectroscopy (DOSY) is an important tool in NMR mixture analysis that has found use in most areas of chemistry, including organic synthesis, drug discovery, and supramolecular chemistry. Typically the aim is to disentangle the overlaid, and often overlapped, NMR spectra of individual mixture components and/or to obtain size and interaction information from their respective diffusion coefficients. The most common processing method, high-resolution DOSY, breaks down where component spectra overlap; here multivariate methods can be very effective, but only for small numbers (2-5) of components. In this study, we present a hybrid method, local covariance order DOSY (LOCODOSY), that breaks a spectral data set into suitable windows and analyzes each individually before combining the results. This approach uses a multivariate algorithm (e.g., SCORE or DECRA) to resolve only a small number of components in any given window. Because a small spectral region should contain signals from only a few components, even when the spectrum as a whole contains many more, the total number of resolvable chemical components rises dramatically. It is demonstrated here that complete resolution of component spectra can be achieved for mixtures that are much more complex than could previously be analyzed with DOSY. Thus, LOCODOSY is a powerful, flexible tool for processing NMR diffusion data of complex mixtures.     

大黄中鞣质成分的分离与液相色谱/质谱联用分析

研究了大黄中鞣质类成分的提取、分离与分析方法。优化了大黄原药材中鞣质类物质的提取方法;建立了大黄鞣质类成分的梯度洗脱反相高效液相色谱(HPLC)分析方法,使鞣质类成分得到了良好的分离;采用液相色谱-质谱(LC-MS)对大黄中主要的鞣质类化合物进行了结构分析,并总结了一部分鞣质类化合物在高效液相色谱-电喷雾质谱(HPLC-ESI-MS)谱图上的裂解规律。     

Can the dodecahedral water cluster naturally form in methane aqueous solutions? A molecular dynamics study on the hydrate nucleation mechanisms

By performing a large scale of molecular dynamics simulations, we analyze 60 x 10(6) hydration shells of methane to examine whether the dodecahedral water cluster (DWC) can naturally form in methane aqueous solutions--a fundamental question relevant to the nucleation mechanisms of methane hydrate. The analyzing method is based on identifying the incomplete cages (ICs) from the hydration shells and quantifying their cagelike degrees (zetaC=0-1). Here, the zetaC is calculated according to the H-bond topological network of IC and reflects how the IC resembles the complete polyhedral cage. In this study, we obtain the zetaC distributions of ICs in methane solutions and find the occurrence probabilities of ICs reduce with zetaC very rapidly. The ICs with zetaC>or=0.65 are studied, which can be regarded as the acceptable cagelike structures in appearance. Both increasing the methane concentration and lowering the temperature can increase their occurrence probabilities through slowing down the water molecules. Their shapes, cage-maker numbers, and average radii are also discussed. About 13-14 of these ICs are face saturated, meaning that every edges are shared by two faces. The face-saturated ICs have the potential to act as precursors of hydrate nucleus because they can prevent the encaged methane from directly contacting other dissolved methane when an event of methane aggregation occurs. The complete cages, i.e., the ICs with zetaC=1, form only in the solutions with high methane concentration, and their occurrence probabilities are about 10(-6). Most of their shapes are different from the known hydrate cages, but we indeed observe a standard 5(12)6(2) hydrate cage. We do not find the expected DWC, and its occurrence probability is estimated to be far less than 10(-7). Additionally, the IC analysis proposed in this work is also very useful in other studies not only on the formation, dissociation, and structural transition of hydrates but also on the hydrophobic hydration of apolar solutes.     

Discrimination of crude and processed rhubarb products using a chemometric approach based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry

Crude rhubarb subjected to different processing procedures will produce different therapeutic effects that are possibly due to processing‐induced variation in chemical composition. In this study, a chemometric approach based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry was established to systematically investigate the chemical variations of rhubarb induced by different processing methods. The approach was validated based on pooled quality‐control samples from two perspectives: the individual properties of variables and the bulk properties of samples. Orthogonal partial least squares discriminant analysis was introduced to compare the differences between crude and processed rhubarb products. A total of 20 significantly different markers were screened out and unambiguously/tentatively characterized. This research proved that a chemometric method based on ultra fast liquid chromatography with ion trap/time‐of‐flight mass spectrometry can comprehensively analyze the chemical variation of herbal medicine and provide evidence for a deeper understanding of the pharmacological activities of processed rhubarb products.     

Creation of novel polymer materials by processing with inclusion compounds

The processing of polymer materials from their inclusion compounds (ICs) formed with urea (U) and cyclodextrin (CD) hosts is described. Several examples are presented and serve to demonstrate the fabrication of unique polymer‐polymer composites and blends, including intimate blends of normally incompatible polymers, and the delivery of additives to polymers by means of embedding polymer‐ or additive‐U and CD‐ ICs into carrier polymer films and fibers, followed by coalescence of the IC guest, or by coalescence of two polymers or a polymer and an additive from their common CD‐IC crystals.     

Global detection and identification of components from crude and processed traditional Chinese medicine by liquid chromatography connected with hybrid ion trap and time‐of‐flight‐mass spectrometry

We herein present a chemical profiling method to efficiently process the information acquired by ultra fast liquid chromatography (UFLC)‐electrospray ionization source in combination with hybrid ion trap and high‐resolution time‐of‐flight mass spectrometry (UFLC‐(ESI)‐IT‐TOF/MS), facilitating the structural determination of serial components contained in crude or processed traditional Chinese medicine (TCM). Under the optimized UFLC and IT‐TOF‐MSⁿ conditions, over 39 compounds were separated and detected in crude or processed Fructus corni within 25 min. The components were identified by comparing the mass spectra and retention time with reference compounds, or tentatively assigned by elucidating low‐energy collision‐induced dissociation (CID) fragment ions and matching empirical molecular formula with that of the published compounds. Several factors in the processing procedure were examined. The experimental results demonstrate that the chemical reactions that occurred in the processing procedure can be used to elucidate the processed mechanism of F. corni, which is regularly affected by the processing conditions. This study provides a novel approach and methodology to identify the complicated components from various complex mixtures such as crude TCM, processed TCM, and biological samples. It can be used as a valid analytical method for further understanding the processing mechanism of TCM, along with the intrinsic quality control of TCM and its processed product.     

A new regression method based on independent component analysis

Based on independent component analysis (ICA), a new regression method, independent component regression (ICR), was developed to build the model of NIR spectra and the routine components of plant samples. It is found that ICR and principal component regression (PCR) are completely equivalent when they are applied in quantitative prediction. However, independent components (ICs) can give more chemical explanation than principal components (PCs) because independence is a high-order statistic that is a much stronger condition than orthogonality. Three ICs are obtained by ICA from the NIR spectra of plant samples; it is found that they are strongly correlated to the NIR spectra of water, hydrocarbons and organonitrogen compounds, respectively. Therefore, ICA may be a promising tool to retrieve both quantitative and qualitative information from complex chemical data sets.     

Studies on the Components of Crude and Processed Fructus Corni by ESI-MSn

The components of crude and processed Fructus Corni were investigated by means of electrospray ionization-tandem mass spectrometry(ESI-MSn) technique in the negative ion mode. Compared with those of crude Fructus Corni, the chemical components of the processed Fructus Corni were changed both in quality and in quantity.From the ESI-MS spectra of the crude and processed Fructus Corni, six peaks were selected to establish the characteristic ESI-MS peaks. Several factors in the processing procedure were examined. The experimental results demonstrate that the chemical reactions that occurred in the processing procedure can be used for the elucidation of the processed mechanism of Fructus Corni, which is regularly affected by the processing conditions. The present article provides both the chemistry evidence for the understanding of the processing procedure of Fructus Corni and the specific methodology for the research of the processing procedure and quality identification of traditional Chinese medicine.     

Copolymer-cyclodextrin inclusion complexes in water and in the solid state. A physico-chemical study

The formation of inclusion complexes (ICs) composed of cyclodextrins (CDs) and poly(ethylene oxides)-poly(propylene oxides)-poly(ethylene oxides) (PEO-PPO-PEO) was studied. To this purpose, native and hydroxypropyl cyclodextrins with different cavity size were chosen. The PEO-PPO-PEO copolymers were selected to study the role of the molecular weight, keeping constant the hydrophilic/hydrophobic ratio, and the hydrophilicity. The volumetric studies at 25 degrees C allowed to determine the equilibrium constant and the volume change for the IC formation in water as well as the IC stoichiometry. Surface tension experiments evidenced that the copolymer and the CD interfacial behavior is controlled by the formation of ICs taking place in the bulk phase. It was proved that the differential scanning calorimetry (DSC) is a valid method to describe quantitatively the IC in the solid state. The combination of volumes, DSC and FTIR techniques together with the geometric information highlighted the following points: (1) the included copolymer is in the amorphous state; (2) the IC composed of native CDs adopts a channel structure with two EO units incorporated into one CD molecule; (3) the IC composed of hydroxypropyl-cyclodextrin is a polymeric structure like a necklace decorated with CD rings. Finally, TGA experiments showed that the thermal stability of the IC depends on the nature of both components.     

Molecular mixing of incompatible polymers through formation of and coalescence from their common crystalline cyclodextrin inclusion compounds

We describe the successful mixing of polymer pairs and triplets that are normally incompatible to form blends that possess molecular‐level homogeneity. This is achieved by the simultaneous formation of crystalline inclusion compounds (ICs) between host cyclodextrins (CDs) and two or more guest polymers, followed by coalescing the included guest polymers from their common CD–ICs to form blends. Several such CD–IC fabricated blends, including both polymer1/polymer2 binary and polymer1/ polymer2/polymer3 ternary blends, are described and examined by means of X‐ray diffraction, differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, and solid‐state NMR to probe their levels of mixing. It is generally observed that homogeneous blends with a molecular‐level mixing of blend components is achieved, even when the blend components are normally immiscible by the usual solution and melt blending techniques. In addition, when block copolymers composed of inherently immiscible blocks are coalesced from their CD–ICs, significant suppression of their normal phase‐segregated morphologies generally occurs. Preliminary observations of the thermal and temporal stabilities of the CD–IC coalesced blends and block copolymers are reported, and CD–IC fabrication of polymer blends and reorganization of block copolymers are suggested as a potentially novel means to achieve a significant expansion of the range of useful polymer materials. © 2004 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 42: 4207–4224, 2004     

Expert system for interpretation of the infrared spectra of environmental mixtures

A program for the identification of the principal components of mixtures through interpretation of the infrared mixture spectrum (IntIRpret) was developed. This program, which was developed as a preliminary screening tool for unknown organic mixtures, has five main subroutines: the interferogram processing and peak-selection subroutine (PUSHSUB), the automated knowledge-acquisition subroutine (AUTOGEN), the system optimization subroutine (STO), the interpretation subroutine (PAIRS), and final processing subroutine to subtract spectral similarity (PAIRSPLUS). Principal advantages of this system compared to earlier systems are speed, flexibility and accuracy.     

Multi‐component analysis: blind extraction of pure components mass spectra using sparse component analysis

The paper presents sparse component analysis (SCA)‐based blind decomposition of the mixtures of mass spectra into pure components, wherein the number of mixtures is less than number of pure components. Standard solutions of the related blind source separation (BSS) problem that are published in the open literature require the number of mixtures to be greater than or equal to the unknown number of pure components. Specifically, we have demonstrated experimentally the capability of the SCA to blindly extract five pure components mass spectra from two mixtures only. Two approaches to SCA are tested: the first one based on ?₁ norm minimization implemented through linear programming and the second one implemented through multilayer hierarchical alternating least square nonnegative matrix factorization with sparseness constraints imposed on pure components spectra. In contrast to many existing blind decomposition methods no a priori information about the number of pure components is required. It is estimated from the mixtures using robust data clustering algorithm together with pure components concentration matrix. Proposed methodology can be implemented as a part of software packages used for the analysis of mass spectra and identification of chemical compounds. Copyright © 2009 John Wiley & Sons, Ltd.