Comprehensive multicomponent characterization and quality assessment of Xiaoyao Wan by UPLC-Q-Orbitrap-MS, HS-SPME-GC-MS and HS-GC-IMS.

Xiaoyao Wan (XYW) is a prescription medicine of traditional Chinese medicine (TCM) with the effects of "soothing the liver and relieving depression," and "strengthening spleen and nourishing blood". XYW has been widely concerned in the treatment of depression and has become one of the commonly used classic formulas in clinical practice. However, the pharmacodynamic substance basis and the quality control studies of XYW are hitherto quite limited. Here, we aim to fully utilize an advanced ultra - performance liquid chromatography-quadrupole - Orbitrap mass spectrometry (UPLC-Q-Orbitrap-MS), headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) technique to deep characterization of the pharmacological substance basis and quantitatively evaluate the quality of XYW. Firstly, 299 compounds were identified or tentatively characterized, including 198 non-volatile organic compounds (n-VOCs) and 101 volatile organic compounds (VOCs). Secondly, principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to analyze quality differences in XYW at different manufacturers. Thirdly, a parallel reaction monitoring (PRM) method was established and validated to quantify the fourteen major effective substances in different manufacturers of XYW, which were chosen as the benchmarked substances to evaluate the quality of XYW. In conclusion, this study shows that the strategy provides a useful method for quality control of TCM and offers a practical workflow for exploring the quality consistency of TCM.

Laser-induced breakdown spectroscopy (LIBS) for the detection of exogenous contamination of metal elements in lily bulbs.

Natural products with the underground edible part have the risk of excessive heavy metals due to the influence of the growing environment. In this study, the content of five metal elements in lily bulbs was detected by laser-induced breakdown spectroscopy (LIBS). In view of the mutual interference among elements, multivariable analysis models were established to effectively eliminate the interference. The partial least squares regression (PLSR) multivariate analysis model was evaluated by combining different data preprocessing with variable selection methods to achieve the best fit. The results show that the best regression model for Cu, Pb, Zn, Al, and Mg content achieved the coefficients determination of prediction (Rp2) values of 0.9920, 0.9737, 0.9835, 0.9723 and 0.9939, respectively, and root mean square error of prediction (RMSEP) values of 3.2386 mg/kg, 5.8559 mg/kg, 4.6334 mg/kg, 6.0073 mg/kg and 2.8103 mg/kg, respectively. Comprehensively comparing the accuracy, robustness, and number of variables of each model, it can be found that the PLSR model on the least absolute shrinkage and selection operator (LASSO) achieved good results in the quantitative prediction model of three kinds of metal elements. This indicates the superiority of the LASSO-PLSR algorithm framework and confirms the feasibility of LIBS technology for the detection of various metal elements in natural products.

Emerging biotechnology applications in natural product and synthetic pharmaceutical analyses.

Pharmaceutical analysis is a discipline based on chemical, physical, biological, and information technologies. At present, biotechnological analysis is a short branch in pharmaceutical analysis; however, bioanalysis is the basis and an important part of medicine. Biotechnological approaches can provide information on biological activity and even clinical efficacy and safety, which are important characteristics of drug quality. Because of their advantages in reflecting the overall biological effects or functions of drugs and providing visual and intuitive results, some biotechnological analysis methods have been gradually applied to pharmaceutical analysis from raw material to manufacturing and final product analysis, including DNA super-barcoding, DNA-based rapid detection, multiplex ligation-dependent probe amplification, hyperspectral imaging combined with artificial intelligence, 3D biologically printed organoids, omics-based artificial intelligence, microfluidic chips, organ-on-a-chip, signal transduction pathway-related reporter gene assays, and the zebrafish thrombosis model. The applications of these emerging biotechniques in pharmaceutical analysis have been discussed in this review.

A feasibility study on improving the non-invasive detection accuracy of bottled Shuanghuanglian oral liquid using near infrared spectroscopy.

The ultimate goal of the study is to present a strategy to improve the accuracy of near-infrared spectroscopy detection of Shuanghuanglian oral liquid in glass bottles without damaging the primary packaging. we adopted the multi-position spectral modeling (MPSM) method to correct the spectral variation caused by the difference of bottle and measuring position, so as to improve the measurement accuracy and find the best site combination for measuring Shuanghuanglian oral liquid. Baicalin, total flavonoids and soluble solid contents were considered as the quality indicators of the oral liquid, and partial least squares (PLS) models were employed for the single-position and multi-position spectra, respectively. The root mean square error of the validation set (RMSEP) of the optimum multi-position models are 0.7412 mg/mL for baicalin, 1.1259 mg/mL for total flavonoids and 0.9491% for soluble solids contents. Compared with the traditional single-position spectral modeling method (SPSM method), MPSM method improved the prediction accuracy of baicalin, total flavonoids and soluble solid contents by 26.84%, 31.97% and 58.14% respectively. The results showed that the MPSM method can improve the measurement accuracy of bottled oral liquid and is an effective method to eliminate the uncertainty of measurement conditions.

[Moisture content measurement model of whole package of Chinese medicinal materials based on microwave transmission technology].

In view of the relatively low representativeness of manual sampling inspection, and long time-consuming in oven detection of moisture content, which delayed the subsequent production period, this paper proposed a scheme for rapid moisture quantitative detection for Chinese medicinal materials by microwave transmission technology, and took 8 different types of Chinese medicinal mate-rials as examples to analyze the feasibility and reliability of the scheme for the detection results of moisture content of the whole package of Chinese medicine. In the experiment, the least square method was used to establish the measurement model of microwave absorption rate-moisture content for each kind of medicinal material. The results showed that the microwave transmission measurement of moisture content achieved high-precision measurement of the moisture content of Schisandrae Chinensis Fructus, Ziziphi Spinosae Semen, Poria, Pheretima, Lilii Bulbus, Scutellariae Radix, and Galli Gigerii Endothelium Corneum. The measurement model of Ziziphi Spinosae Semen had the highest accuracy, and the R~2 and root mean square error of the validation set were 0.951 5 and 0.15%, respectively. At the same time, this study found that the microwave absorption intensity of animal medicines including Pheretima and Galli Gigerii Endothelium Corneum was much weaker than that of plant medicines such as Schisandrae Chinensis Fructus, but there was also a good linear relationship between microwave absorption and moisture content, which proved the universality of this method. However, this method was not suitable for Phellodendri Chinensis Cortex because its package contained iron wire. For the whole package of medicinal materials with uniform density and no metal inside, the microwave transmission technology for moisture content measurement can be used to detect the moisture content, which is an effective alternative method to detect the moisture content of medicinal materials.