A global profiling strategy for identification of the total constituents in Chinese herbal medicine based on online comprehensive two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry combined with intelligentized chemical classification guidance.

A comprehensive strategy for effective identification of total constituents in Chinese patent medicine has been advanced applying full scan-preferred parent ions capture-static and active exclusion (FS-PIC-SAE) acquisition coupled with intelligent deep-learning supported mass defect filter (MDF) process, with Naoxintong capsule (NXT) as a case. Online comprehensive two-dimensional liquid chromatography (2DLC) coupled with Q-TOF-MS/MS system was established for obtaining the excellent separation and detection performance of total components, which could exhibit excellent peak capacity with 1052 and orthogonality with 0.69. In addition, a total of 901 unknown compounds could be classified into nine chemical classes rapidly and effectively, based on the intelligent deep-learning algorithm supported MDF model with 96.4% accuracy. Consequently, 276 compounds were successfully identified from NXT, especially including 44 flavonoids, 27 phenolic acids, 25 fatty acids, 17 saponins, 21 phthalocyanines, 20 triterpenes, 10 monoterpenes, 13 diterpenoid ketones, 14 amino acids, and others. It is concluded that the proposed program is an effective and practical strategy enabling the in-depth chemical profiling of complex herbal and biological samples.

An efficient method for qualitation and quantitation of multi-components of the herbal medicine Qingjin Yiqi Granules.

Qingjin Yiqi Granules (QJYQ) is a Traditional Chinese Medicines (TCMs) prescription for the patients with post-COVID-19 condition. It is essential to carry out the quality evaluation of QJYQ. A comprehensive investigation was conducted by establishing deep-learning assisted mass defect filter (deep-learning MDF) mode for qualitative analysis, ultra-high performance liquid chromatography and scheduled multiple reaction monitoring method (UHPLC-sMRM) for precise quantitation to evaluate the quality of QJYQ. Firstly, a deep-learning MDF was used to classify and characterize the whole phytochemical components of QJYQ based on the mass spectrum (MS) data of ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF/MS). Secondly, the highly sensitive UHPLC-sMRM data-acquisition method was established to quantify the multi-ingredients of QJYQ. Totally, nine major types of phytochemical compounds in QJYQ were intelligently classified and 163 phytochemicals were initially identified. Furthermore, fifty components were rapidly quantified. The comprehensive evaluation strategy established in this study would provide an effective tool for accurately evaluating the quality of QJYQ as a whole.

An online stepwise background subtraction-based ultra-high pressure liquid chromatography quadrupole time of flight tandem mass spectrometry dynamic detection integrated with metabolic molecular network strategy for intelligent characterization of the absorbed chemical-fingerprint of QiangHuoShengShi decoction in vivo.

QiangHuoShengShi decoction (QHSS) was an ancient and classical traditional Chinese medicine (TCM) prescription. In the previous study, its phytochemical fingerprint had been comprehensively characterized. However, no reports were available on its absorbed prototypes and the related metabolites in rat plasma samples. In this study, an intelligent and innovate analysis strategy was built for characterizing metabolic chemical-fingerprint in rat plasma after oral administration of QHSS extract. Firstly, a very simple and highly efficient online stepwise background subtraction (BS)-based ultra-high pressure liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF-MS/MS) dynamic detection method was established to analyze the plasma samples. Secondly, the intelligent metabolic molecular network (MMN) technology was developed and used for rapidly screening out the metabolites of interest, which was followed by prediction of chemical types using the modified deep-learning assisted mass defect filter (MDF) analysis. Thirdly, the screened metabolites with identification features (metabolic pathways and chemical classification) were deeply characterized based on the MS/MS datasets. Finally, 58 prototypes of QHSS were successfully acquired and subsequently identified, including coumarins, chromones, phthalides, phenolic acids, flavonoids, and saponins. A total of 111 metabolites of the coumarins, chromones, phthalides were filtered to be tentatively characterized. This developed qualitative strategy was very helpful to quickly target medicine-related metabolites in the complex bio-matrix and, importantly, it could further visualize medicine-metabolic pathways hidden in the messy mass spectrum datasets. In all, the innovate strategy would provide a powerful tool for effectively acquiring and decode complex metabolic fingerprint of natural products in vivo.

A strategy for intelligent chemical profiling-guided precise quantitation of multi-components in traditional Chinese medicine formulae-QiangHuoShengShi decoction.

Due to the tremendous clinical value, more and more Traditional Chinese Medicines (TCMs) and their formulae are attracted by world's attention. QiangHuoShengShi (QHSS) decoction is one of classic TCM formulae, which is clinically used for treating various rheumatic diseases. However, the phytochemical constituents of QHSS have rarely been reported. A simple, intelligent, and comprehensive strategy was developed to characterize the phytochemical-fingerprint and quantify the chemical-markers for precise quality evaluation of QHSS. Firstly, a new deep-learning assisted mass defect filter (MDF) method was built for rapid and accurate classification of mass spectrum (MS) ions acquired by ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF/MS). Subsequently, herb species-specific chemical-category and characteristic identification were used for further characterization of multi-components. As the result, seven major types of compounds in QHSS were intelligently differentiated and 183 phytochemical compounds were tentatively identified. Finally, a sensitive scheduled multiple reaction monitoring (sMRM) detection method was applied to precisely quantify 37 target analytes in QHSS decoction. This integrated strategy would provide an alternative method for chemical-material basis study of more herbal medicine or natural products.

Corrigendum to "Monitoring unbound warfarin in drug combination therapy by pharmacokinetics and fluorospectrometry" [Chinese Herbal Medicines 11 (2019) 92-97].

[This corrects the article DOI: 10.1016/j.chmed.2018.10.002.].

An environmentally friendly sodium dodecyl sulfate-synergistic microwave-assisted extraction followed by ultra-high-performance liquid chromatography with photodiode array method for the simultaneous extraction and determination of iridoids, phenylpropanoids, and lignans from Eucommiae Cortex.

A simple and green sodium dodecyl sulfate-synergistic microwave-assisted extraction method was developed to extract and determine the iridoids, phenylpropanoids, and lignans in Eucommiae Cortex followed by ultra-high-performance liquid chromatography with photodiode array detection. The biodegradable solution (sodium dodecyl sulfate) was used as a promising alternative to organic solvents. The response surface methodology provided the optimum extraction conditions (2 mg/mL sodium dodecyl sulfate, 1100 W microwave power, and 6 min extraction time). The recoveries of three types of components ranged from 95.0 to 105% (RSDs < 5%). The intra- and inter-day precision and accuracy were less than 3.40% and within the range of 97.1-105%, respectively. Compared with other extraction methods, this newly established method was more efficient and environmental friendly. The results demonstrated that sodium dodecyl sulfate-synergistic microwave-assisted extraction followed by ultra-high-performance liquid chromatography with photodiode array method was applicable for the simultaneous extraction and determination of these three types of compounds for quality evaluation of Eucommiae Cortex.