The bioavailability of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) depends on their chemical forms. This study investigated the long-term effects of DHA-bound triglyceride (TG-DHA), DHA-bound phospholipid (PL-DHA), and the combination of TG-DHA and egg yolk phospholipid (Egg-PL) on lipid metabolism in mice fed with a high-fat diet (fat levels of 22.5%). Male C57BL/6J mice were fed with different formulations containing 0.5% DHA, including TG-DHA, PL-DHA, and the combination of TG-DHA and Egg-PL, for 6 weeks. Serum, hepatic, and cerebral lipid concentrations and the fatty acid compositions of the liver and brain were determined. The concentrations of serum total triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), and hepatic TG in the PL-DHA group and the combination group were significantly lower than those in the high-fat (HF) group (P < 0.05). Atherogenic index (AI) of the PL-DHA group was significantly lower than that of the combination group (P < 0.05). Hepatic TC level in the combination group was significantly lower than that in the HF group (P < 0.05), but no significant difference was observed between the combination group and the PL-DHA group. Both the PL-DHA and the combination groups showed significantly increased DHA levels in the liver compared with the HF group (P < 0.05). However, there were no obvious increases in the cerebral DHA levels in all DHA diet groups. These results suggest that PL-DHA was superior to the combination of TG-DHA and Egg-PL in decreasing the AI. Long-term dietary supplementation with low amount of DHA (0.5%) may improve hepatic DHA levels, although cerebral DHA levels may not be enhanced. 相似文献
In this study, the Alaska pollock protein isolate(APPI) was hydrolyzed by Neutrase for 20, 40, 80, 120, 160, 200, and 240 min. Hydrolysates with different molecular weights were produced and they were named as H1–H7. Furthermore, the effects of hydrolysis on the average molecular weights, functional properties(solubility, oil-holding capacities, foaming activities, and emulsifying properties), and antioxidant activities(1, 1-diphenyl-2-picrylhydrazyl, superoxide, and hydroxyl free radical-scavenging activities) were determined. It was found that when the degree of hydrolysis(DH) increased, the average molecular weights of the hydrolysates decreased significantly. The functional properties of APPI were also significantly improved. The hydrolysates of APPI exhibited better solubility, emulsifying activities, and foaming activities. Hydrolysates with low molecular weights(1 kDa) had better solubility, oil-holding capacities, and emulsifying activities, while hydrolysates with higher molecular weights(1 kDa) had better foaming activities. In addition, the hydrolysates exhibited excellent antioxidant properties, while the inhibition values of 1, 1-diphenyl-2-picryl hydroxyl(DPPH), superoxide, and hydroxyl free radical-scavenging activities, were 85.22%, 53.56%, and 75.00% respectively, when the concentration of the hydrolysates was 5.0 mg mL~(-1). The lower the average molecular weight was, the higher was the antioxidant activity. These results indicated that hydrolysis with Neutrase is an effective method for improving the functional and antioxidant properties of APPI. The hydrolysates of APPI displayed great potentials to be used as natural antioxidants in protein-rich aqueous foods such as nutrient supplements and sports beverages. 相似文献
Sea ice can attenuate wave energy significantly when waves propagate through ice covers.In this study,a third-generation wave model called simulating wave nearshore(SWAN)was advanced to include damping of wave energy due to friction in the boundary layer below the ice.With the addition of an eddy viscosity wave-ice model,the resulting new SWAN model was applied to simulate wave height in the Bohai Sea during the freezing winter.Its performance was validated with available buoy data near the ice edge,and the new model showed an improvement in accuracy because it considered the ice effect on waves.We then performed a wave hindcast for the Bohai Sea during a freezing period in the winter of 2016 that had the severest ice conditions in recent years and found that the mean significant wave height changed by approximately 16.52%.In the Liaodong Bay,where sea ice concentration is highest,the change reached 32.57%,compared with the most recent SWAN model version.The average influence of sea ice on wave height simulation was also evaluated over a five-year(2013-2017)hindcast during January and February.We found that the wave height decrease was more significant in storm conditions even the eddy viscosity wave-ice model itself showed no advantage on damping stronger waves. 相似文献
High concentrations of PM2.5 are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM2.5 concentrations for regional air quality control and management. In this study, PM2.5 data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM2.5 concentration in China were evaluated. The main results are as follows. (1) In general, the average concentration of PM2.5 in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 μg/m3. (2) PM2.5 is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM2.5 concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM2.5. (3) The center of gravity of PM2.5 has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM2.5 concentrations have moved eastward, while low-value PM2.5 has moved westward. (4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The “High-High” PM2.5 agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The “Low-Low” PM2.5 agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands. (5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM2.5 concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM2.5 concentration in China.
