Saponins have been extensively used in the food and pharmaceutical industries because of their potent bioactive and pharmacological functions including hypolipidemic, anti-inflammatory, expectorant, antiulcer and androgenic properties. A lot of saponins-containing foods are recommended as nutritional supplements for diabetic patients. As a medicine and food homologous material, Corni Fructus (CF) contains various active ingredients and has the effect of treating diabetes. However, whether and how CF saponins attenuate diabetes is still largely unknown. Here, we isolated total saponins from CF (TSCF) using ultrasonic microwave-assisted extraction combined with response surface methodology. The extract was further purified by a nonpolar copolymer styrene type macroporous resin (HPD-300), with the yield of TSCF elevated to 13.96 mg/g compared to 10.87 mg/g obtained via unassisted extraction. When used to treat high-fat diet and streptozotocin-induced diabetic mice, TSCF significantly improved the glucose and lipid metabolisms of T2DM mice. Additionally, TSCF clearly ameliorated inflammation and oxidative stress as well as pancreas and liver damages in the diabetic mice. Mechanistically, TSCF potently regulated insulin receptor (INSR)-, glucose transporter 4 (GLUT4)-, phosphatidylinositol 3-kinase (PI3K)-, and protein kinase B (PKB/AKT)-associated signaling pathways. Thus, our data collectively demonstrated that TSCF could be a promising functional food ingredient for diabetes improvement.

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Corni Fructus (CF) is a traditional medicine and beneficial food with multifaceted protective effects against diabetes and its complications. Since alpha-glucosidase inhibitors (GI) are promising first choice oral antihyperglycemic drugs...

The stability of section coal pillars is one of the most important factors affecting the stability of coal rock systems in the stope and roadway. This study aimed to develop an artificial intelligence methodology to predict and evaluate coal pillar stability. Data from 125 published coal pillar historical cases were collected to build a sample dataset. Meanwhile, a mean impact value-genetic algorithm-back propagation neural network (MIV-GA-BP) fusion model was established to predict the stability of section coal pillars. MIV tests indicated that the main factors influencing coal pillar stability are (in order of decreasing importance): the coal seam buried depth > coal seam thickness > working face length > coal elastic modulus > cohesion > tensile strength > internal friction angle > Poisson’s ratio > volume weight > coal seam dip angle. The relative weights of mine design parameters are generally greater than those of the physical and mechanical parameters of coal and rock mass. After the BP model was optimized by GA, the relative error, R value, and mean squared error were 5%, 0.95, and 0.13, respectively. These results confirm that the machine learning model has significant potential for improving coal pillar stability evaluations. The developed prediction model was applied to two field cases to verify its effectiveness, and the results indicated that the innovative method can be extended for use in similar geological conditions or other mining and geaological engineering fields.

As a recognized special resource, tar-rich coal can extract the country 's scarce oil and gas resources and generate semi-coke that can replace anthracite and coking coal. The tar-rich coal in northern Shaanxi is prominent, but due to the dense structure and high strength of tar-rich coal, it is easy to cause frequent dynamic disasters in coal mining. Therefore, the realization of pressure relief and disaster reduction has become the primary problem in mining tar-rich coal. There are many shortcomings in conventional pressure relief methods, so a new method of microwave weakening coal is proposed. Through different water saturation treatment of tar-rich coal samples, the longitudinal wave velocity degradation trend and surface crack expansion law of water-bearing coal after microwave irradiation were analyzed, and the strength softening characterization and energy evolution relationship under the combined action of microwave and water were studied. Fractal dimension and its internal correlation based on the equivalent side length-mass of coal sample fragments. The experimental results show that : (1) Under the same microwave radiation condition, with the increase of water saturation, the deterioration trend of physical and mechanical parameters such as longitudinal wave velocity and peak strength is obvious. (2) After microwave radiation, the uniaxial compression results show that the coal sample is damaged by load, there is still a high residual strength, the ratio of elastic energy to dissipation energy decreases, and the possibility of rockburst of coal sample decreases. The strength softening degree of coal specimen under the codegradation of microwave and water is the highest, followed by microwave and water. (3) The fractal dimension is inversely proportional to the moisture content and microwave radiation intensity, and the fractal dimension has a significant positive correlation with the peak intensity and longitudinal wave velocity. The mechanical damage law of water-bearing tar-rich coal under microwave action is revealed, which aims to solve the problem of weakening and reducing impact of hard coal on site to a certain extent, ensure the safety of working face and improve the mining efficiency of tar-rich coal. It provides basic theoretical support for microwave-assisted hydraulic fracturing technology and effective weakening measures for hard roof treatment.