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This study was performed in order to explore the correlation between the monosaccharide composition and hypoglycemic activity of Berberi dasystachya polysaccharides (BDPs). BDPs were extracted with hot water from B. dasystachya fruit from five regions of Qinghai province (I–V). The chemical compositions and primary structures of BDPs were determined, and their in vitro hypoglycemic activity was evaluated in terms of α-glucosidase and α-amylase inhibitory activities, and their protective effect against apoptosis induced by glucolipotoxicity (GLTy) in RIN-m5F cells was assessed. The results showed that BDPs were heteropolysaccharides connected by β-glycosidic bonds that had apyranose backbone without a triple-helix conformation, and exhibited excellent thermal stability at temperatures below 200 ℃. In addition, the monosaccharide composition and molecular mass of BDPs varied significantly depending on geographical origin. BDP-I showed good hypoglycemic activity in vitro, and the inhibitory rate of BDP-I on α-amylase was as high as 67.41% (P < 0.05). BDPs exhibited good protective effects on GLTY-induced apoptosis in RIN-m5F cells, and BDP-I had the best cell proliferation-promoting activity, which effectively decreased the levels of reactive oxygen species (ROS) and tumor necrosis factor-α (TNF-α). Finally, correlation analysis showed that monosaccharides such as glucose (Glc), galactose (Gal), rhamnose (Rha) exhibited a strongly positive correlation with hypoglycemic activity in vitro, and there was a strongly negative correlation between mannose (Man) and ROS levels. This study provides a theoretical basis for the utilization and development of B. dasystachya Maxim. berry in terms of hypoglycemic activity.

To investigate the effects of three preservatives (lysozyme, tea polyphenols, and licorice antioxidants) at different concentrations on the shelf life of vacuum-packaged cooked Tibetan sheep meat, Tibetan sheep cooked products were treated with lysozyme, tea polyphenols, and licorice antioxidants, respectively, and stored at 4 °C. The edible quality, physicochemical properties, nutritional quality, and volatile flavor substances of the Tibetan sheep cooked products were measured during storage to determine the optimal preservative. Results showed that as the refrigeration time increased (63 days), the total bacterial count of Tibetan sheep cooked products preserved with 0.4% lysozyme increased the least (P < 0.05), with the least loss of soluble protein content and moisture content (P < 0.05). The color was well maintained, and the amino acid and fatty acid contents were abundant (P < 0.05), with low levels of undesirable flavor substances (P < 0.05). Tibetan sheep cooked products preserved with 0.25% tea polyphenols had a relatively abundant amino acid content and high umami amino acid content (P < 0.05). Tibetan sheep cooked products preserved with 0.15% licorice antioxidants had a high content of polyunsaturated fatty acids (P < 0.05). Based on comprehensive analysis, all three natural preservatives can extend the shelf life of Tibetan sheep cooked products to more than 63 days. Among them, the 0.4% lysozyme preserved products exhibited the best preservation effect, effectively delaying the decay and deterioration of cooked sheep meat. [ABSTRACT FROM AUTHOR]

This article has been retracted. A retraction notice can be found at . [ABSTRACT FROM AUTHOR]

The artificial neural network is a massively parallel distribution information processing system consisting of simple processing units. It has the ability to learn and build nonlinear complex relational models. Once trained by data set samples, it can predict the output. In recent years, it has been used in various extrapolations of nuclear physics and solved many complex problems. All the results point to the fact that the neural network approach is a very useful tool to further improve the accuracy of nuclea mass models, and can predict those unknown but critical nuclear data. Based on two representative macroscopic microscopic mass models: the finite-range droplet model (FRDM) and the Weizs-cker-Skyrme model (WS4), the results of the model were optimized using the artificial neural network approach. After adding the neural network approach, the root mean square deviations of the binding energy of the two models are improved in varying degrees. The root mean square deviation between the binding energy data given by FRDM and 2 095 experimental data decreases from 0.579 MeV to 0.354 MeV, and the root mean square deviation between the binding energy data given by WS4 and 2 095 experimental data decreases from 0.292 MeV to 0.210 MeV. The one-neutron separation energy can reflect the accuracy of the nuclear mass model to a certain extent. Thus, based on the optimized data, the oneneutron separation energy of Z=82 isotope chain was calculated. The root mean square deviations of the oneneutron separation energy of FRDM and WS4 are 39.9 keV and 40.8 keV, respectively. In addition, accurate binding energy data of superheavy nuclei is very important for studying the synthesis of superheavy nuclei. In recent years, to find the exact position of the island of stability and extend the periodic table, many theoretical models for studying the synthesizing mechanism of superheavy nuclei are being developed. To accurately reproduce the experimental data of superheavy nuclear synthesis and reasonably predict the evaporation residual cross section of unknown superheavy nuclear synthesis, all models have encountered the same problem: basic nuclear data, such as neutron separation energy, must be reliable to some extent. In this work, combined with the binding energy data calculated by the original model, the binding energy data were extrapolated, and the ability of the extrapolation data of the two models to describe the one-neutron separation energy of superheavy nuclei was compared. The root mean square deviations of the one-neutron separation energy of FRDM and WS4 in the superheavy nuclear region are 40.1 keV and 188.1 keV, respectively. The results show that the FRDM has better performance in the superheavy nuclear region than the WS4. In order to synthesize new elements, it is theoretically necessary to study the synthesis mechanism of new elements Z=119 and Z=120. Thus, the oneneutron separation energy of the new elements Z=119 and Z=120 isotope chains were predicted. The predicted results show that the one-neutron separation energy of Z=119 and Z=120 isotope chains has an obvious odd-even effect, and the difference of one-neutron separation energy given by the two optimization models is about 300 keV.