Semi-Preparative Scale Separation of Emodin from Plant Extract by Using Molecularly Imprinted Polymer as Stationary Phase

Automatic Segmentation of Magnetic Resonance Images of Severe Patients with Advanced Liver Cancer and the Molecular Mechanism of Emodin-Induced Apoptosis of HepG2 Cells under the Deep Learning

To improve the accuracy of clinical diagnosis of severe patients with advanced liver cancer and enhance the effect of chemotherapy treatment, the U-Net model was optimized by introducing the batch normalization (BN) layer and the dropout layer, and the segmentation training and verification of the optimized model were realized by the magnetic resonance (MR) image data. Subsequently, HepG2 cells were taken as the research objects and treated with 0, 10, 20, 40, 60, 80, and 100 μmol/L emodin (EMO), respectively. The methyl thiazolyl tetrazolium (MTT) method was used to explore the changes in cell viability, the acridine orange (AO)/ethidium bromide (EB) and 4',6-diamidino-2-phenylindole (DAPI) were used for staining, the Annexin V fluorescein isothiocyanate (FITC)/propidium iodide (PI) (Annexin V-FITC/PI) was adopted to detect the apoptosis after EMO treatment, and the Western blot (WB) method was used with the purpose of exploring the changes in protein expression levels of PARP, Bcl-2, and p53 in the cells after treatment. It was found that compared with the original U-Net model, the introduction of the BN layer and the dropout layer can improve the robustness of the U-Net model, and the optimized U-Net model had the highest dice similarity coefficient (DSC) (98.45%) and mean average precision (MAP) (0.88) for the liver tumor segmentation.

Molecularly Imprinted Polymer (MIP) Applications in Natural Product Studies Based on Medicinal Plant and Secondary Metabolite Analysis

Characterization and extraction of plant secondary metabolites are important in agriculture, pharmaceutical, and food industry. In this regard, the applied analytical methods are mostly costly and time-consuming; therefore, choosing a suitable approach is essential for optimum results and economic suitability. One of the recently considered methods used to characterize new types of materials is MIPs. Among the various applications of MIPs is the identification and separation of various plant-derived compounds, such as secondary metabolites, chemical residues, and pesticides. The present review describes the application of MIPs as a tool in medicinal plant material analysis, focusing on plant secondary metabolism.

System-level study on synergism and antagonism of active ingredients in traditional Chinese medicine by using molecular imprinting technology

In this work, synergism and antagonism among active ingredients of traditional Chinese medicine (TCM) were studied at system-level by using molecular imprinting technology. Reduning Injection (RDNI), a TCM injection, was widely used to relieve fever caused by viral infection diseases in China. Molecularly imprinted polymers (MIPs) synthesized by sol-gel method were used to separate caffeic acid (CA) and analogues from RDNI without affecting other compounds. It can realize the preparative scale separation. The inhibitory effects of separated samples of RDNI and sample combinations in prostaglandin E2 biosynthesis in lipopolysaccharide-induced RAW264.7 cells were studied. The combination index was calculated to evaluate the synergism and antagonism. We found that components which had different scaffolds can produce synergistic anti-inflammatory effect inside and outside the RDNI. Components which had similar scaffolds exhibited the antagonistic effect, and the antagonistic effects among components could be reduced to some extent in RDNI system. The results indicated MIPs with the characteristics of specific adsorption ability and large scale preparation can be an effective approach to study the interaction mechanism among active ingredients of complex system such as TCM at system-level. And this work would provide a new idea to study the interactions among active ingredients of TCM.