As a natural flavonolignan, silibinin is reported to possess multiple biological activities, while the inhibitory potential of silibinin on carbohydrate-hydrolyzing enzymes is still unclear. Therefore, in this study, the inhibitory effect and underlying mechanism of silibinin against α-amylase/α-glucosidase were investigated. The results indicated that silibinin showed a strong inhibitory efficiency against α-amylase/α-glucosidase in noncompetitive manners and exhibited synergistic inhibition against αglucosidase with acarbose. However, interestingly, the inhibitory effect of silibinin was significantly hindered in various milk proteinrich environments, but this phenomenon disappeared after simulated gastrointestinal digestion of milk proteins in vitro. Furthermore, silibinin could combine with the inactive site of α-amylase/α-glucosidase and change the microenvironment and secondary structure of the enzymes, thereby influencing the catalytic efficiency of enzymes. This research suggested that silibinin could be used as a novel carbohydrate-hydrolyzing enzyme inhibitor, and milk beverages rich in silibinin had the potential for further application in antidiabetic dietary or medicine.
In this paper, we focus on a network system which describes spatiotemporal dynamics of single species population at different patches since species can have different features in various life stages and different behaviors in various spatial environments. With the effect of time delay and spatial dispersion, homogenous, periodic and spatiotemporally nonhomogeneous distributions are identified. The stability analysis is carried out for the discrete-space and continuous-time network on single species with time delay and the Hopf bifurcation of the single species population model in a network is explored. Formulas for determining the direction of Hopf bifurcation are derived by using the center manifold method and the normal form theorem. It is found that the network can generate spatial patterns only when time delay is present. Finally, numerical simulations are performed which agree well with our theoretical result, i.e. this discrete-space and continuous-time model admits regular temporal patterns since the delay induces Hopf bifurcations with network structure.
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