Jian-bo Chen

Application of Mid-Infrared Spectroscopy in the Quality Control of Traditional Chinese Medicines

Chinese herbal medicines are often referred to as Chinese materia medica (CMM). Composite formulae containing mixtures of CMM are prescribed for treatment and prevention of diseases in the practice of traditional Chinese medicine (TCM). Some of the well-known CMM formulae (Fufang in Chinese) are manufactured and marketed as proprietary Chinese medicines (PCM). Quality assessment and assurance of these products are difficult; they are a challenging task. Mid-infrared spectroscopy, a classic molecular structure analysis method, has been innovatively applied in the quality control of TCM, and has gained significant impact and advancement in analytical fields. Infrared fingerprinting features appear particularly suitable for the identification of multicomponent matrices in samples whose chemical integrity has not been altered or destroyed because no extraction procedure is needed. This review summarizes and gives an overall view on the application of mid-infrared and two-dimensional correlation infrared (2D-IR) spectroscopy as well as chemometric techniques in the identification of CMM, investigation of TCM processing procedures, and analysis of herb extracts and preparations.

Quantitative Classification of Two-Dimensional Correlation Spectra

Two-dimensional (2D) correlation spectroscopy, which takes advantage of the apparent enhancement of spectral resolution, is known to be useful in qualitative discrimination of seemingly similar samples. The possibility of quantitative classification of 2D correlation spectra is even more desirable. Two useful parameters, namely Euclidian distance and correlation coefficient between 2D correlation spectra, are introduced for this purpose. Dry and sweet red wine samples are used to demonstrate the utility of these parameters. The distances between the 2D infrared (IR) spectra of sweet and dry red wines are roughly proportional to the differences of sugar contents in them. The result shows that the two parameters are useful measures for the quantitative evaluation of the similarity among the samples and their corresponding 2D correlation spectra.

Data-driven signal-resolving approaches of infrared spectra to explore the macroscopic and microscopic spatial distribution of organic and inorganic compounds in plant

The nondestructive and label-free infrared (IR) spectroscopy is a direct tool to characterize the spatial distribution of organic and inorganic compounds in plant. Since plant samples are usually complex mixtures, signal-resolving methods are necessary to find the spectral features of compounds of interest in the signal-overlapped IR spectra. In this research, two approaches using existing data-driven signal-resolving methods are proposed to interpret the IR spectra of plant samples. If the number of spectra is small, “tri-step identification” can enhance the spectral resolution to separate and identify the overlapped bands. First, the envelope bands of the original spectrum are interpreted according to the spectra–structure correlations. Then the spectrum is differentiated to resolve the underlying peaks in each envelope band. Finally, two-dimensional correlation spectroscopy is used to enhance the spectral resolution further. For a large number of spectra, “tri-step decomposition” can resolve the spectra by multivariate methods to obtain the structural and semi-quantitative information about the chemical components. Principal component analysis is used first to explore the existing signal types without any prior knowledge. Then the spectra are decomposed by self-modeling curve resolution methods to estimate the spectra and contents of significant chemical components. At last, targeted methods such as partial least squares target can explore the content profiles of specific components sensitively. As an example, the macroscopic and microscopic distribution of eugenol and calcium oxalate in the bud of clove is studied.

Direct observation of bulk and surface chemical morphologies of Ginkgo biloba leaves by Fourier transform mid- and near-infrared microspectroscopic imaging.

AbstractFourier transform infrared microspectroscopy is a powerful tool to obtain knowledge about the spatial and/or temporal distributions of the chemical compositions of plants for better understanding of their biological properties. However, the chemical morphologies of plant leaves in the plane of the blade are barely studied, because sections in this plane for mid-infrared transmission measurements are difficult to obtain. Besides, native compositions may be changed by chemical reagents used when plant samples are microtomed. To improve methods for direct infrared microspectroscopic imaging of plant leaves in the plane of the blade, the bulk and surface chemical morphologies of nonmicrotomed Ginkgo biloba leaves were characterized by near-infrared transmission and mid-infrared attenuated total reflection microspectroscopic imaging. A new self-modeling curve resolution procedure was proposed to extract the spectral and concentration information of pure compounds. Primary and secondary metabolites of secretory cavities, veins, and mesophylls of Ginkgo biloba leaf blades were analyzed, and the distributions of cuticle, protein, calcium oxalate, cellulose, and ginkgolic acids on the adaxial surface were determined. By the integration of multiple infrared microspectroscopic imaging and chemometrics methods, it is possible to analyze nonmicrotomed leaves and other plant samples directly to understand their native chemical morphologies in detail. Graphical abstractVisible and infrared microspectroscopic images of a Ginkgo biloba leaf blade. PC-1 score image shows the physical morphology, while the positive and negative part of PC-2 score image shows the distribution of dichotomous branching veins and secretory cavities, respectively

Vibrational microspectroscopic identification of powdered traditional medicines: chemical micromorphology of Poria observed by infrared and Raman microspectroscopy.

Microscopic identification using optical microscopes is a simple and effective method to identify powdered traditional medicines made from plants, animals and fungi. Sometimes, the criteria based on physical properties of the microscopic characteristics of drug powder may be ambiguous, which makes the microscopic identification method subjective and empirical to some extent. In this research, the vibrational microspectroscopic identification method is proposed for more explicit discrimination of powdered traditional medicines. The chemical micromorphology, i.e., chemical compositions and related physical morphologies, of the drug powder can be profiled objectively and quantitatively by infrared and Raman microspectroscopy, leading to better understanding about the formation mechanisms of microscopic characteristics and more accurate identification criteria. As an example, the powder of Poria, which is one of the most used traditional Chinese medicines, is studied in this research. Three types of hyphae are classified according to their infrared spectral features in the region from 1200 to 900 cm(-1). Different kinds of polysaccharides indicate that these hyphae may be in different stages of the growth. The granular and branched clumps observed by the optical microscope may be formed from the aggregation of the mature hyphae with β-D-glucan reserves. The newfound spherical particles may originate from the exuded droplets in the fresh Poria because they are both composed of α-D-glucan. The results are helpful to understand the development of the hyphae and the formation of active polysaccharides in Poria and to establish accurate microspectroscopic identification criteria.

Discrimination of different genera Astragalus samples via quantitative symmetry analysis of two-dimensional hetero correlation spectra.

It has been proved to be a very useful method to distinguish similar samples by two-dimensional correlation spectroscopy when they are hardly distinguished by the conventional one-dimensional spectroscopy. To acquire the quantitative description of the differences between samples, the similarity of the series dynamic spectra, which reflects the similarity of the samples themselves if obtained under the same perturbation condition, is evaluated by the symmetry of hetero 2DCOS map. Two parameters, the Euclidian distance and correlation coefficient between the upper left and lower right triangular parts of a hetero 2DCOS map, are introduced for the quantitative measure of the symmetry, which in turn characterizes the similarity of the responses of samples to a given perturbation. The above method is used to discriminate one genus of Astragalus from the others to ensure the medicinal efficacy and safety of the herb. Hypothesis tests show that the inter-distances between samples from different genera are significantly larger than the intra-ones within the same genera, while the inter-correlation coefficients are smaller than the intra-ones. The excellent result of the identification for all samples carried out by a t-test based on the distances indicates that this method provides an efficient technique for the quantitative evaluation of similarity between samples.

Exploring the chemical mechanism of thermal processing of herbal materials by temperature-resolved infrared spectroscopy and two-dimensional correlation analysis

Before their medical use, thermal processing methods are frequently utilized to treat the traditional Chinese herbal materials to improve their efficacy or reduce their side effects. Understanding the temperature-dependent chemical reactions of herbal materials is necessary to explore the mechanisms and optimize the procedures of thermal processing. Being a quick, label-free, and nondestructive analytical technique, infrared (IR) spectroscopy can be used to in situ monitor the changes of herbal materials as the temperature increases continually. In this research, the thermal processing of Gardeniae fructus (the ripe fruit of Gardenia jasminoides Ellis) was studied by thermogravimetry-infrared spectroscopy (TG-IR) and heated transmission IR spectroscopy. In summary, the decrease in organic acids (chlorogenic acid, quinic acid, ursolic acid, etc.) is the main reason why thermal processing can reduce the side effects of Gardeniae fructus on intestines and stomach. Stir-baking to yellow at 125–145 °C can reduce the amount of the organic acids remarkably, while most iridoids such as geniposide remain to retain the medical functions of Gardeniae fructus in clearing pathogenic heat, lessening the virulence of pathogens, reducing blood pressure, etc. Stir-baking to brown at 145–165 °C can further reduce the organic acids, but the iridoids also decompose significantly. Stir-baking to scorch at 165–190 °C will destroy most iridoids, but the tannins change the function of Gardeniae fructus into hemostasis.

Infrared microspectroscopic identification of marker ingredients in the finished herbal products based on the inherent heterogeneity of natural medicines

AbstractFinished herbal products (FHPs) are preparations made from one or more herbs. The first stage in assuring the quality, safety, and efficacy of FHPs is to identify the herbs in the products. A new simple and quick method is developed in this research to detect the marker ingredients in FHPs. The inherent chemical heterogeneity of herbs and FHPs makes it possible to resolve different ingredients, without any additional separation or labeling, by infrared microspectroscopic imaging. Therefore, multiple marker ingredients in FHPs can be recognized directly and simultaneously by the infrared microspectroscopic identification method. As an example, all six kinds of herbs in Liuwei Dihuang Wan are identified through the following steps: (1) Each herb is characterized by infrared spectroscopic imaging, then the spectra of the main ingredients are calculated by the combination of principal component analysis, independent component analysis, and alternating least squares. (2) One marker ingredient is chosen for each herb. Ten typical pixels, the spectra of which best match the calculated spectrum of the marker ingredient, are selected by partial least squares target. The average spectrum of the typical pixels is taken as the marker spectrum. (3) Correlation coefficients between the typical pixel spectra and the marker spectrum are calculated. The acceptance correlation threshold is determined through the beta distribution function and then validated by positive and negative samples. (4) Using the above marker spectra and correlation criteria, herbs in the model mixture and the commercial product are identified. Good recognition results reveal the potential of the infrared microspectroscopic identification method in the quality control of herbs and FHPs. FigureMarker ingredients in finished herbal products can be identified by infrared microspectroscopic images and correlation thresholds

Direct and simultaneous detection of organic and inorganic ingredients in herbal powder preparations by Fourier transform infrared microspectroscopic imaging

Herbal powder preparation is a kind of widely-used herbal product in the form of powder mixture of herbal ingredients. Identification of herbal ingredients is the first and foremost step in assuring the quality, safety and efficacy of herbal powder preparations. In this research, Fourier transform infrared (FT-IR) microspectroscopic identification method is proposed for the direct and simultaneous recognition of multiple organic and inorganic ingredients in herbal powder preparations. First, the reference spectrum of characteristic particles of each herbal ingredient is assigned according to FT-IR results and other available information. Next, a statistical correlation threshold is determined as the lower limit of correlation coefficients between the reference spectrum and a larger number of calibration characteristic particles. After validation, the reference spectrum and correlation threshold can be used to identify herbal ingredient in mixture preparations. A herbal ingredient is supposed to be present if correlation coefficients between the reference spectrum and some sample particles are above the threshold. Using this method, all kinds of herbal materials in powder preparation Kouqiang Kuiyang San are identified successfully. This research shows the potential of FT-IR microspectroscopic identification method for the accurate and quick identification of ingredients in herbal powder preparations.

Chemical morphology of Areca nut characterized directly by Fourier transform near-infrared and mid-infrared microspectroscopic imaging in reflection modes

Fourier transform near-infrared (NIR) and mid-infrared (MIR) imaging techniques are essential tools to characterize the chemical morphology of plant. The transmission imaging mode is mostly used to obtain easy-to-interpret spectra with high signal-to-noise ratio. However, the native chemical compositions and physical structures of plant samples may be altered when they are microtomed for the transmission tests. For the direct characterization of thick plant samples, the combination of the reflection NIR imaging and the attenuated total reflection (ATR) MIR imaging is proposed in this research. First, the reflection NIR imaging method can explore the whole sample quickly to find out typical regions in small sizes. Next, each small typical region can be measured by the ATR-MIR imaging method to reveal the molecular structures and spatial distributions of compounds of interest. As an example, the chemical morphology of Areca nut section is characterized directly by the above approach.