Static headspace-multicapillary column with gas chromatography coupled to ion mobility spectrometry as a simple approach for the discrimination of crude and processed traditional Chinese medicines

Application of digital-intelligence technology in the processing of Chinese materia medica

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Application of digital-intelligence technology in the processing of Chinese materia medica

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Neural network classification of mobility spectra for volatile organic compounds using tandem differential mobility spectrometry with field induced fragmentation

A spectral library of field induced fragmentation (FIF) spectra for 45 oxygen-containing volatile organic compounds from 5 chemical classes was obtained using tandem differential mobility spectrometry (DMS). Protonated monomers were mobility isolated in a first DMS stage, fragmented with electric fields >10,000 V/cm in a middle (or reactive) stage, and mobility characterized in a second DMS stage. Other spectral libraries were obtained for protonated monomers and for complete mobility spectra from a single DMS stage. Neural networks from Python/Tensorflow software, prepared in-house, and from commercial NeuralWorks Professional II/PLUS were trained to assign spectra into a chemical class. The success at classification was determined for familiar and unfamiliar spectra from these three libraries. Classification test scores were best with FIF spectra with >0.99 for familiar compounds and 0.52 for unfamiliar compounds and were consistent with neural network learning of structural information from fragment ions when compared to other spectral libraries. Radar charts are introduced as measures of classification and as a tool to explore mis-classification. This work shows that ion fragmentation with multi-stage tandem DMS portends molecular identification with the portability and robustness of ambient pressure ion mobility analyzers.

Strategy for the multi-component characterization and quality evaluation of volatile organic components in Kaixin San by correlating the analysis by headspace gas chromatography/ion mobility spectrometry and headspace gas chromatography/mass spectrometry

RATIONALE

Kaixin San (KXS) is a prescription traditional Chinese medicine (TCM) with the effects of "tonifying the kidney and brain" and "improving memory". The volatile organic compounds (VOCs) in KXS could effectively improve senile dementia and depression, but only few studies have focused on the overall characterization of VOCs in KXS and the quantitative study of the main active components.

METHODS

We have developed a strategy to correlate the results from headspace gas chromatography/ion mobility spectrometry (HS-GC/IMS) and headspace gas chromatography/mass spectrometry (HS-GC/MS) for the comprehensive characterization of VOCs in KXS and the quantitative analysis of the main pharmacodynamic substances.

RESULTS

A totsal of 68 low molecular weight VOCs were identified in KXS by HS-GC/IMS at room temperature and atmospheric pressure; 117 VOCs were identified and 10 components (isocalamenediol, α-asarone, β-asarone, methyl eugenol, isoeugenol methyl ether, camphor, anethol, 2,4-di-tert-butylphol, linalool, asarylaldehyde) as the quality markers of KXS based on HS-GC/MS.

CONCLUSIONS

This results from this study provide a foundation for quality control, pharmacodynamic mechanism research and further development of KXS, and provides more convincing data supporting the VOCs of other natural products.

Characteristic Volatile Fingerprints and Odor Activity Values in Different Citrus-Tea by HS-GC-IMS and HS-SPME-GC-MS

Citrus tea is an emerging tea drink produced from tea and the pericarp of citrus, which consumers have increasingly favored due to its potential health effects and unique flavor. This study aimed to simultaneously combine the characteristic volatile fingerprints with the odor activity values (OAVs) of different citrus teas for the first time by headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Results showed that the establishment of a citrus tea flavor fingerprint based on HS-GC-IMS data can provide an effective means for the rapid identification and traceability of different citrus varieties. Moreover, 68 volatile compounds (OAV > 1) were identified by HS-SPME-GC-MS, which reflected the contribution of aroma compounds to the characteristic flavor of samples. Amongst them, the contribution of linalool with sweet flower fragrance was the highest. Odorants such as decanal, β-lonone, β-ionone, β-myrcene and D-limonene also contributed significantly to all samples. According to principal component analysis, the samples from different citrus teas were significantly separated. Visualization analysis based on Pearson correlation coefficients suggested that the correlation between key compounds was clarified. A comprehensive evaluation of the aroma of citrus tea will guide citrus tea flavor quality control and mass production.

Gas chromatographic-ion mobility spectrometry combined with a multivariate analysis model exploring the characteristic changes of odor components during the processing of black sesame

Black sesame (Sesamum indicum L.) is a Chinese dietary herb that has been widely used in the medical and healthcare fields in China. According to the theory of Traditional Chinese medicine processing, reasonable processing (steaming and drying many times) can increase the tonic effect and reduce the adverse factors generated during long-term use. At present, the processing degree of black sesame is mainly judged based on subjective experience. However, due to the lack of objective and quantitative control indicators, quality fluctuations easily occur. Therefore, for better application, its processing technology needs scientific monitoring methods. Herein a gas chromatography-ion mobility spectrometry (GC-IMS) technique was applied as a monitoring method to differentiate the processed products of black sesame in different processing stages. The response data of volatile components obtained from the samples were processed by the built-in data processing software in the instrument to identify the different components for further principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). From fingerprint comparison, 70 differential signal peaks were screened, 32 of which were qualitatively identified, mainly monomers and dimers of 20 compounds. On this basis, the PCA model shows that there was a significant difference between the raw product (S1) and the processed products (H1-9); moreover, there was a certain correlation between the differential changes of samples in different processing stages (H1-9) and the processing times. The OPLS-DA model specifically shows the differential components in the processing with potential characteristics peaks of 41, 105, n-nonanal, 2 and ethanol can discriminate whether the BS has undergone the first processed. And the dynamic changes of the three characteristic peaks of 1-hexanol, acetic acid and 107 can determine the specific degree of processing of BS. The research proves that GC-IMS combined with a multivariate analysis model can provide scientific data for identifying the characteristic odor components of black sesame.

Advancement in the chemical analysis of Paeoniae Radix (Shaoyao)

Paeoniae Radix Alba (baishao or white peony root) and Paeoniae Radix Rubra (chishao or red peony root) are two highly valuable traditional Chinese medicines (TCMs) usually indicated for painful conditions, menstrual disorders and viral infections. These two TCMs are collectively referred to as shaoyao (Paeoniae Radix) due to their close origins and similar chemical compositions. Modern research indicates that monoterpene glycosides, polyphenols and paeonols are the three main types of compounds related to the pharmacological activities of Paeoniae Radix. This review summarizes recent advances in the chemical analysis of Paeoniae Radix and the related traditional Chinese medicine formulas/preparations, including methods used for sample pretreatment, qualitative analysis, quantitative analysis and biological sample analysis. More than 120 papers are discussed in this review, focusing on the chemical analysis of Paeoniae Radix, and various analytical techniques (such as HPLC, LC-MS, IR, near IR and quantitative NMR), as well as their advantages/disadvantages, are described. It is our hope that this paper can provide necessary information for improving the quality evaluation methods currently available for Paeoniae Radix and offer a scientific basis for the future in-depth study of the pharmacokinetics and pharmacodynamics of Paeoniae Radix.