In vivo and in vitro chemical composition and biological activity of traditional vs. dispensing granule decoctions of Coptidis Rhizoma: A comparative study.

Coptidis Rhizoma (CR) holds significant clinical importance. In this study, we conducted a comparative analysis of CR's dispensing granule decoction (DGD) and traditional decoction (TD) to establish a comprehensive evaluation method for the quality of DGD. We selected nine batches of DGD (three from each of manufacturers A, B and C) and 10 batches of decoction pieces for analysis. We determined the content of representative components using high-performance liquid chromatography and assessed the content of blood components in vivo post-administration using ultra-performance liquid chromatography-mass spectrometry. The antibacterial activity was measured using the drug-sensitive tablet method. To evaluate the overall consistency of DGD and TD, we employed the CRITIC method and Grey relational analysis method. Our CRITIC results indicated no significant difference between the CRITIC scores of DGD-B and TD, with DGD-B exhibiting the highest consistency and overall quality. However, DGD-A and DGD-C showed variations in CRITIC scores compared with TD. After equivalent correction, the quality of DGD-A and DGD-C approached that of TD. Furthermore, our Grey relational analysis results supported the findings of the CRITIC method. This study offers a novel approach to evaluate the consistency between DGD and TD, providing insights into improving the quality of DGD.

Quality consistency evaluation of chemical composition and pharmacology of Shaoyao-Gancao decoction dispensing granules and traditional decoction.

Dispensing granules of Chinese medicine (DGCM) have emerged as a more convenient alternative to traditional decoction (TD) of Chinese medicine, gaining popularity in recent years. However, the debate surrounding the consistency of DGCM compared to TD remains unresolved. In this study, three batches of Baishao and Gancao DGCM were obtained from manufacturers A, B, and C, and 15 batches of crude drugs were procured from hospital pharmacies for the preparation of dispensing granule decoction (DGD) and TD of Shaoyao-Gancao decoction (SGD). The HPLC-UV method was employed to determine the levels of gallic acid, paeoniflorin, albiflorin, liquiritin, liquiritin apioside, isoliquiritin apioside, isoliquiritin, glycyrrhizic acid, and isoliquiritigenin. The analgesic and antispasmodic effects were assessed using the hot plate and acetic acid writhing test in mice. To evaluate the consistency of chemical constituents and pharmacological effects between the two decoctions, the Criteria Importance Though Intercriteria Correlation (CRITIC) method combined with chemometrics was employed. Grey relation analysis (GRA) was used to assess the comprehensive quality consistency of the two decoctions. The CRITIC results revealed certain differences in chemical constituents and pharmacological effects between the selected DGCM and TD. Notably, DGD-A/C exhibited a significant difference from TD (p > 0.05), whereas DGD-B demonstrated no significant difference from TD (p > 0.05). The GRA analysis demonstrated that the overall quality consistency between DGD-B and TD was the highest among the three manufacturers. This study presents a method for evaluating the quality consistency of DGCM and TD of SGD, offering novel insights into the evaluation of consistency between DGCM and TD.

Identification of Bletilla striata and related decoction pieces: a data fusion method combining electronic nose, electronic tongue, electronic eye, and high-performance liquid chromatography data.

Introduction: We here describe a new method for distinguishing authentic Bletilla striata from similar decoctions (namely, Gastrodia elata, Polygonatum odoratum, and Bletilla ochracea schltr). Methods: Preliminary identification and analysis of four types of decoction pieces were conducted following the Chinese Pharmacopoeia and local standards. Intelligent sensory data were then collected using an electronic nose, an electronic tongue, and an electronic eye, and chromatography data were obtained via high-performance liquid chromatography (HPLC). Partial least squares discriminant analysis (PLS-DA), support vector machines (SVM), and back propagation neural network (BP-NN) models were built using each set of single-source data for authenticity identification (binary classification of B. striata vs. other samples) and for species determination (multi-class sample identification). Features were extracted from all datasets using an unsupervised approach [principal component analysis (PCA)] and a supervised approach (PLS-DA). Mid-level data fusion was then used to combine features from the four datasets and the effects of feature extraction methods on model performance were compared. Results and Discussion: Gas chromatography-ion mobility spectrometry (GC-IMS) showed significant differences in the types and abundances of volatile organic compounds between the four sample types. In authenticity determination, the PLS-DA and SVM models based on fused latent variables (LVs) performed the best, with 100% accuracy in both the calibration and validation sets. In species identification, the PLS-DA model built with fused principal components (PCs) or fused LVs had the best performance, with 100% accuracy in the calibration set and just one misclassification in the validation set. In the PLS-DA and SVM authenticity identification models, fused LVs performed better than fused PCs. Model analysis was used to identify PCs that strongly contributed to accurate sample classification, and a PC factor loading matrix was used to assess the correlation between PCs and the original variables. This study serves as a reference for future efforts to accurately evaluate the quality of Chinese medicine decoction pieces, promoting medicinal formulation safety.