Optimization and mechanism of postponing aging of polysaccharides from Chinese herbal medicine formula

Research trends in functionalized Fe3O4 composites based on affinity recognition systems for targeted extraction of natural products

In recent years, target-specific affinity recognition systems based on Fe3O4-based composites have proven to be an effective method for screening natural products. Herbal medicines contain a wide range of natural products and are considered to be a major source for the development of novel drugs. However, the process of isolating and obtaining these bioactive components for the production of novel drugs is complex. Meanwhile, the complexity and diversity of herbal constituents have posed a great challenge to the screening studies of herbal active ingredients. Currently, traditional extraction and screening studies of active ingredients in herbal medicine include extraction and chromatographic separation technology development, serum medicinal chemistry, metabolomics and computerized virtual screening. In order to achieve integrated targeting of Fe3O4 for extraction and separation of natural products from herbs, various Fe3O4-based composites need to be synthesized so that the composites can be further functionalized and modified. Composites such as Fe3O4@SiO2, Fe3O4-based magnetic graphene oxide and Fe3O4-based magnetic carbon nanotubes were used to achieve targeted extraction and isolation of natural products from herbal medicines. The main extraction techniques involved based on these Fe3O4-based composites are molecularly imprinted techniques, immobilized ligand fishing techniques, and cell membrane-coated bionanotechnology methods. This article will present recent advances in the synthesis and modification of Fe3O4 composites and their applications for the extraction of natural products in conjunction with molecular imprinting, immobilization-targeted fishing, and cell-membrane-coated biomimetic techniques, as well as the future goals and challenges of functionalized modification of Fe3O4 composites for the targeted extraction of natural products, like protein overexpression modification, doping of fluorescent substances and genetic engineering development. A deeper understanding of the multi-level, multidisciplinary, and applied studies in materials science and phytochemistry will be provided by this article.

Formulation Optimization and Performance Prediction of Red Mud Particle Adsorbents Based on Neural Networks

Red mud (RM), a bauxite residue, contains hazardous radioactive wastes and alkaline material and poses severe surface water and groundwater contamination risks, necessitating recycling. Pretreated RM can be used to make adsorbents for water treatment. However, its performance is affected by many factors, resulting in a nonlinear correlation and coupling relationship. This study aimed to identify the best formula for an RM adsorbent using a mathematical model that examines the relationship between 11 formulation types (e.g., pore-assisting agent, component modifier, and external binder) and 9 properties (e.g., specific surface area, wetting angle, and Zeta potential). This model was built using a back-propagation neural network (BP) based on single-factor experimental data and orthogonal experimental data. The model trained and predicted the established network structure to obtain the optimal adsorbent formula. The RM particle adsorbents had a pH of 10.16, specific surface area (BET) of 48.92 m2·g-1, pore volume of 2.10 cm3·g-1, compressive strength (ST) of 1.12 KPa, and 24 h immersion pulverization rate (ηm) of 3.72%. In the removal of total phosphorus in flotation tailings backwater, it exhibited a good adsorption capacity (Q) and total phosphorous removal rate (η) of 48.63 mg·g-1 and 95.13%, respectively.

Study on semi-bionic extraction of Astragalus polysaccharide and its anti-aging activity in vivo

Astragalus membranaceus (A. membranaceus) is a homologous plant with high medicinal and edible value. Therefore, the extraction methods of Astragalus polysaccharide (APS) have attracted the attention of many research groups, but the yield of the active components is still not high. The aim of this study was to extract APS by a semi-bionic extraction method, optimize the extraction process, and evaluate the anti-aging activities of APS in vivo. The results showed that the APS yield was 18.23% when extracted by the semi-bionic extraction method. Anti-aging evaluation in rats showed that APS extracted by this method significantly decreased the malondialdehyde (MDA) content and increased superoxide dismutase (SOD) activity to cope with D-galactose-induced aging. Serum metabolomic analysis indicated that a total of 48 potential biomarkers showed significant differences, mainly involving 5 metabolic pathways. These altered metabolic pathways were mainly related to energy metabolism, amino acid metabolism, and lipid metabolism. These results indicated that the semi-bionic extraction method can effectively improve the yield of APS, and the extracted APS exhibited anti-aging activity in rats. Our study provided a novel and effective method to extract APS and indicated that APS can be used as functional food and natural medicine to delay aging and prevent its complications.