A MS-feature-based medicinal plant database-driven strategy for ingredient identification of Chinese medicine prescriptions

Digital identification and adulteration analysis of Codonopsis Radix and Stellariae Radix based on the "digital identity" of chemical compositions

Introduction

Under the background of digitalization of traditional Chinese medicine (TCM), this study aimed to realize the digital identification and adulteration analysis of Codonopsis Radix (CR) and Stellariae Radix (SR) based on chemical analysis.

Methods

This study combined digitalization concepts and chemical analysis and conducted a chemical analysis of CR and SR from different batches based on UHPLC-QTOF-MSE. Furthermore, the shared ions were extracted from different batches of CR and SR as their "ion characterization" after digital quantization. Then, the data matrices of unique ions of CR relative to SR and SR relative to CR were screened out, and the top-N ions were outputted as the "digital identities" of CR and SR, sorted by ionic strength. Finally, the above "digital identities" of CR and SR were used as benchmarks for matching positive samples and market samples to provide feedback on the matching credibility (MC) for identification and adulteration analysis.

Results

The results showed that based on the "digital identities" of CR and SR, the digital identification of CR, SR, and positive samples can be realized at the individual level of TCM efficiently and accurately, even if 3% of SR in the mixed samples can still be identified efficiently and accurately. Moreover, 1 of the 12 batches of market samples was identified as an adulterated sample.

Conclusion

It proved that the identification and adulteration analysis of two herbs can be realized efficiently and quickly through the "digital identities" of chemical compositions. It has important reference significance for developing the digital identification of CR and SR at the individual level of Chinese medicine based on the "digital identity" of chemical compositions, which was beneficial to the construction of digital quality control of CR and SR.

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized "Digital Identity" and UHPLC-QTOF-MSE Analysis

Angelicae sinensis radix (ASR) and Angelicae pubescentis radix (APR), as traditional herbal medicines, are often confused and doped in the material market. However, the traditional identification method is to characterize the whole herb with a single or a few components, which do not have representation and cannot realize the effective utilization of unknown components. Consequently, the result is not convincing. In addition, the whole process is time-consuming and labor-intensive. To avoid the confusion and adulteration of ASR and APR as well as to strengthen quality control and improve identification efficiency, in this study, a UHPLC-QTOF-MSE method was used to analyze ASR and APR. Based on digital representation, the shared data with high ionic strength were extracted from different batches of the same herbal medicine as their "digital identity". Further, the above "digital identity" was used as the benchmark for matching and identifying unknown samples to feedback on matching credibility (MC). The results showed that based on the "digital identities" of ASR and APR, the digital identification of two herbal samples can be realized efficiently and accurately at the individual level. And the matching credibility (MC) was higher than 94.00%, even if only 1% of APR or ASR in the mixed samples can still be identified efficiently and accurately. The study is of great practical significance for improving the efficiency of the identification of ASR and APR, cracking down on adulterated and counterfeit drugs, and strengthening the quality control of ASR and APR. In addition, it has important reference significance for developing nontargeted digital identification of herbal medicines at the individual level based on UHPLC-QTOF-MSE and "digital identity", which is beneficial to the construction of digital Chinese medicine and digital quality control.

Digital identification and adulteration analysis of Pulsatilla Radix and Pulsatilla Cernua based on "digital identity" and UHPLC-QTOF-MSE

Under the background of digitalization of traditional Chinese medicine (TCM), to realize the quick identification and adulteration analysis of Pulsatilla Radix (PR), adhering to digital conviction, this study conducted UHPLC-QTOF-MSE analysis on PR and its adulterant-Pulsatilla Cernua (PC) from different batches and based on digital conversion, the shared ions were extracted from different batches of PR and PC as their "ions representation", respectively. Further, the data set of unique ions of PR relative to PC and PC relative to PR were screened out as the "digital identities" of PR and PC respectively. Further, above the "digital identities" of PR and PC were used as the benchmarks for matching and identifying to feedback give a matching credibility (MC). The results showed that based on the "digital identities" of PR and PC, the digital identification of two herbal samples can be realized efficiently and accurately at the individual level with the MC≥70.00 %, even if 5 % of PC in the mixed samples can still be identified efficiently and accurately. The study is of great practical significance for improving the identification efficiency of PR and PC, cracking down on adulterated and counterfeit drugs, and strengthening the quality control of PR. In addition, it has important reference significance for developing non-targeted digital identification of herbal medicines at the individual level based on UHPLC-QTOF-MSE and the "digital identity", which was beneficial to the construction of digital Chinese medicine and digital quality control.

Unveiling the Chemical Composition of Sulfur-Fumigated Herbs: A Triple Synthesis Approach Using UHPLC-LTQ-Orbitrap MS-A Case Study on Steroidal Saponins in Ophiopogonis Radix

Ophiopogonis Radix (OR) is a traditional Chinese medicine. In recent years, in order to achieve the purpose of drying, bleaching, sterilizing and being antiseptic, improving appearance, and easy storage, people often use sulfur fumigation for its processing. However, changes in the chemical composition of medicinal herbs caused by sulfur fumigation can lead to the transformation and loss of potent substances. Therefore, the development of methods to rapidly reveal the chemical transformation of medicinal herbs induced by sulfur fumigation can guarantee the safe clinical use of medicines. In this study, a combined full scan-parent ions list-dynamic exclusion acquisition-diagnostic product ions analysis strategy based on UHPLC-LTQ-Orbitrap MS was proposed for the analysis of steroidal saponins and their transformed components in sulfur-fumigated Ophiopogonis Radix (SF-OR). Based on precise mass measurements, chromatographic behavior, neutral loss ions, and diagnostic product ions, 286 constituents were screened and identified from SF-OR, including 191 steroidal saponins and 95 sulfur-containing derivatives (sulfates or sulfites). The results indicated that the established strategy was a valuable and effective analytical tool for comprehensively characterizing the material basis of SF-OR, and also provided a basis for potential chemical changes in other sulfur-fumigated herbs.

Surface-enhanced Raman spectroscopy as a powerful method for the analysis of Chinese herbal medicines

Chinese herbal medicines (CHMs) derived from nature have received increasing attention and become more popular. Due to their diverse production processes, complex ingredients, and different storage conditions, it is highly desirable to develop simple, rapid, efficient and trace detection methods to ensure the drug quality. Surface-enhanced Raman spectroscopy has the advantages of being time-saving, non-destructive, usable in aqueous environments, and highly compatible with various biomolecular samples, providing a promising analytical method for CHM. In this review, we outline the major advances in the application of SERS to the identification of raw materials, detection of bioactive constituents, characterization of adulterants, and detection of contaminants. This clearly shows that SERS has strong potential in the quality control of CHM, which greatly promotes the modernization of CHM.