Comprehensive Analysis of Bile Medicines Based on UHPLC-QTOF-MS and Machine Learning.

Based on UHPLC-QTOF-MS analysis and quantized processing, combined with machine learning algorithms, data modeling was carried out to realize digital identification of bear bile powder (BBP), chicken bile powder (CIBP), duck bile powder (DBP), cow bile powder (CBP), sheep bile powder (SBP), pig bile powder (PBP), snake bile powder (SNBP), rabbit bile powder (RBP), and goose bile powder (GBP). First, 173 batches of bile samples were analyzed by UHPLC-QTOF-MS to obtain the retention time-exact mass (RTEM) data pair to identify bile acid-like chemical components. Then, the data were modeled by combining support vector machine (SVM), random forest (RF), artificial neural network (ANN), gradient boosting (GB), AdaBoost (AB), and Naive Bayes (NB), and the models were evaluated by the parameters of accuracy (Acc), precision (P), and area under the curve (AUC).

Identification Analysis of and Based on Quantized "Digital Identity" and UHPLC-QTOF-MS Analysis.

(ASR) and (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.

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

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-MS 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).

Quantification of "Cold-Hot" Medicinal Properties of Chinese Medicines Based on Primary Metabolites and Fisher's Analysis.

Background: Chinese medicinal properties (CMP) are an important part of the basic theory of traditional Chinese medicines (TCMs). Quantitative research on the properties of TCMs is of great significance to deepen the understanding and application of the theory of drug properties and promoting the modernization of TCMs. However, these studies are limited to strong subjectivity or distinguish different drug properties based on certain indicators since CMP studies are diverse.

Quantitative prediction model for affinity of drug-target interactions based on molecular vibrations and overall system of ligand-receptor.

Background: The study of drug-target interactions (DTIs) affinity plays an important role in safety assessment and pharmacology. Currently, quantitative structure-activity relationship (QSAR) and molecular docking (MD) are most common methods in research of DTIs affinity. However, they often built for a specific target or several targets, and most QSAR and MD methods were based either on structure of drug molecules or on structure of receptors with low accuracy and small scope of application.

TCM-ISP: A Comprehensive Intelligent Service Platform for Industry Chain of Traditional Chinese Medicines.

In order to promote information interaction, intelligent regulation, and scale management in Chinese medicines industry, in this paper, a Chinese medicines intelligent service platform with characteristics of flexibility, versatility, and individuation was designed under the guidance of theoretical model of intelligent manufacturing of Chinese medicines (TMIM). TCM-ISP is a comprehensive intelligent service platform that can be flexibly applied to all links of Chinese medicines industry chain, which realizes data integration and real-time transmission as well as intelligent-flexible scheduling of equipment in response to different demand. The platform took logical framework of data flow as the core and adopts the modular design in which microcontroller and sensor module are independent to obtain overall design scheme of TCM-ISP that contains the diagram of overall framework, hardware structure, and software technology.