Quantitative and qualitative determination of LiuweiDihuang preparations by ultra high performance liquid chromatography in dual-wavelength fingerprinting mode and random forest

A Rapid and Efficient Strategy for Quality Control of Clinopodii herba Encompassing Optimized Ultrasound-Assisted Extraction Coupled with Sensitive Variable Wavelength Detection

Clinopodii herba is a folk herbal medicine for treatments of hemorrhagic disorders. However, there is not even a quantitative standard for clinopodii herba deposited in the Chinese Pharmacopoeia. The development of a strategy for rapid and efficient extraction and simultaneous detection of multiple components in clinopodii herba is therefore of great value for its quality evaluation. Here, a variable wavelength strategy was firstly applied to quantity multiple components by segmental monitoring by UHPLC with diode array detector following ultrasound-assisted extraction. The parameters of ultrasound-assisted extraction were optimized using single factor optimization experiments and response surface methodology by a Box–Behnken design combined with overall desirability. Subsequently, a rapid, efficient, and sensitive method was applied for simultaneous determination of eleven compounds, which represented the major and main types of components in clinopodii herba. Moreover, the performance of the validated method was successfully applied for the quality control of various batches of clinopodii herba and provided sufficient supporting data for the optimum harvest time. The Box-Behnken-optimized ultrasound-assisted extraction coupled with variable wavelength detection strategy established in this work not only improves the quality control of clinopodii herba, but also serves as a powerful approach that can be extended to quality evaluation of other traditional Chinese medicines.

An integrated approach to uncover anti-tumor active materials of Curcumae Rhizoma-Sparganii Rhizoma based on spectrum-effect relationship, molecular docking, and ADME evaluation

ETHNOPHARMACOLOGICAL RELEVANCE

Curcumae Rhizoma-Sparganii Rhizoma (CR-SR), an ancient and classical herbal couple, has been extensively used for tumor treatment in clinic of traditional Chinese medicines (TCMs).

AIM OF THE STUDY

The study aimed to uncover the anti-tumor active materials of CR-SR water decoction (CR:SR = 1:1) via an integrated approach of spectrum-effect relationship, molecular docking, and ADME evaluation.

MATERIALS AND METHODS

The anti-tumor activities toward A549, HepG2, Hela, BGC-823, and MCF-7 cells of the different polar elution fractions (DPEFs) of CR, SR, and CR-SR were determined by Cell Counting Kit-8 (CCK-8) assay. Likewise, the DPEFs' combinations of CR and SR were also tested. The chemical fingerprints of these fractions were profiled by HPLC. Meanwhile, HPLC-ESI-Q-TOF-MS/MS was applied for the identification of chemical components. The main effect-related compounds were screened out by spectrum-effect relationship and molecular docking method. The oral bioavailability and druggability of these active components were subsequently evaluated. Finally, five monomeric compounds were validated experimentally using HepG2 cells.

RESULTS

The 80% ethanol elution fraction of CR, SR, and CR-SR showed strong anti-tumor effects toward five cells. Also, the combinations with the 80% ethanol elution fraction of CR and SR showed stronger tumor inhibition effects among the DPEFs' combinations of CR and SR. By spectrum-effect relationship, HPLC-MS, and molecular docking analysis, 24 main effect-related compounds seemed to have potential anti-tumor effects. ADME evaluation showed rutin performed low oral bioavailability and druggability. Therefore, we suppose that 23 compounds (including 4 unknown compounds) are the primary anti-tumor active components of CR-SR water decoction. Among them, zederone, curcumol, chlorogenic acid, calycosin, and curcumenol were validated successfully with good tumor inhibition effects.

CONCLUSIONS

In summary, this study demonstrated that the multi-components of CR-SR contribute to its anti-tumor effects. It established a rapid and useful strategy to explore the active material basis of traditional Chinese herbal couples with a multi-technology integrated approach in practice, including chromatography, mass spectrometry, machine algorithm models, online databases, and in vitro cell experiments.

Determining the Levels of Four Phenylethanoid Glycosides and Five Triterpene Acids in Liuwei Dihuang Capsule Using Solid Phase Extraction with HPLC-UV

In this study, we used quantitative high-performance liquid chromatography equipped with an ultraviolet detector (HPLC-UV) and solid phase extraction (SPE) to determine the levels of four phenylethanoid glycosides and five triterpene acids in Liuwei Dihuang capsules (LDCs). LDCs were methanol-extracted and purified using a 500 mg/6 mL silica-based C18 SPE cartridge. Two elutions were analyzed on a ChromCore C18 column under two HPLC conditions. To improve the pretreatment clean-up, an array of silica- and polymer-based SPE cartridges were compared. Both wash and elution steps were also optimized to achieve the highest removal of impurities. Under optimal chromatographic conditions, good linearity was achieved for all compounds (correlation coefficient of r ≥ 0.999), with a quantification limit ranging from 0.0076 to 0.418 μg/mL. The method had satisfactory efficiency and reproducibility with recovery rates ranging from 91.6 to 99.3% with a relative standard deviation below 1.5%. Taken together, this demonstrated SPE as a suitable extension of HPLC-UV for the determination of phenylethanoid glycosides and triterpene acids in complex LDCs.

Research progress on classical traditional Chinese medicine formula Liuwei Dihuang pills in the treatment of type 2 diabetes

In traditional Chinese medicine (TCM), type 2 diabetes mellitus (T2DM) is regarded as Xiao Ke disease. Liuwei Dihuang pills (LWP), a classical TCM formula, with the function of nourishing kidney yin, has been used for treating Xiao Ke disease in clinic. In this review, we systematically highlighted recent evidence on LWP and T2DM data from clinical and animal studies, summarized the clinical application, pharmacological mechanism and the active compounds of LWP for the treatment of T2DM. This systematic review will provide an insightful understanding of TCM formulas, pharmacological mechanisms, medicinal-disease interactions, and will lay a foundation for the development of new drug therapy for T2DM.

Recent development in liquid chromatography stationary phases for separation of Traditional Chinese Medicine components

Traditional Chinese Medicine (TCM) is an ancient medical practice which has been used to prevent and cure diseases for thousands of years. TCMs are frequently multi-component systems with mainly unidentified constituents. The study of the chemical compositions of TCMs remains a hotspot of research. Different strategies have been developed to manage the significant complexity of TCMs, in an attempt to determine their constituents. Reversed-phase liquid chromatography (RPLC) is still the method of choice for the separation of TCMs, but has many problems related to limited selectivity. Recently, enormous efforts have been concentrated on the development of efficient liquid chromatography (LC) methods for TCMs, based on selective stationary phases. This can improve the resolution and peak capacity considerably. In addition, high-efficiency stationary phases have been applied in the analysis of TCMs since the invention of ultra high-performance liquid chromatography (UHPLC). This review describes the advances in LC methods in TCM research from 2010 to date, and focuses on novel stationary phases. Their potential in the separation of TCMs using relevant applications is also demonstrated.

Five-descriptor model to predict the chromatographic sequence of natural compounds

Despite the recent introduction of mass detection techniques, ultraviolet detection is still widely applied in the field of the chromatographic analysis of natural medicines. Here, a neural network cascade model consisting of nine small artificial neural network units was innovatively developed to predict the chromatographic sequence of natural compounds by integrating five molecular descriptors as the input. A total of 117 compounds of known structure were collected for model building. The order of appearance of each compound was determined in gradient chromatography. Strong linear correlation was found between the predicted and actual chromatographic position orders (Spearman's rho = 0.883, p < 0.0001). Application of the model to the external validation set of nine natural compounds was shown to dramatically increase the prediction accuracy of the real chromatographic order of multiple compounds. A case study shows that chromatographic sequence prediction based on a neural network cascade facilitated compound identification in the chromatographic fingerprint of Radix Salvia miltiorrhiza. For natural medicines of known compound composition, our method provides a feasible means for identifying the constituents of interest when only ultraviolet detection is available.