The aim of this study was to investigate the effect of low-frequency ultrasound on the enzymolysis of corn protein. A L 9 (3 4 ) orthogonal design was used to optimize ultrasound pretreatment conditions. Degree hydrolysis (DH), conversion rate of protein (CR), and DPPH IC 50 were selected as analytical indicators. Under the optimal ultrasound conditions (5 W/L power, 2 s/2 s on/off time, 50 ∘ C temperature, and 25 min time), the DH, CR, and radical (DPPH • ,• OH) scavenging capacities were significantly increased. Molecular weight distribution and amino acid profile analysis showed that ultrasound pretreatment enhanced the formation of short-chain peptides with molecular weight of 200-3000 Da, especially the peptides containing hydrophobic amino acids. Moreover, 40 potential antioxidant peptides were purified by C18 semipreparative column and identified by UPLC-ESI-MS. The results suggest that the optimal ultrasonic-assisted enzymolysis technology could be useful for preparation of antioxidant peptides from corn.
The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a continuous jumping between different partially synchronized states in the absence of external stimuli. It is thought to be an important mechanism for dealing with sensory novelty and to allow for efficient coding of information in an ever-changing surrounding environment. Many advances have been made to understand how network topology, connection delays, and noise can contribute to building this dynamic. Little or no attention, however, has been paid to the difference between local chaotic and stochastic influences on the switching between different network states. Using a conductance-based neural model that can have chaotic dynamics, we showed that a network can show multistable dynamics in a certain range of global connectivity strength and under deterministic conditions. In the present work, we characterize the multistable dynamics when the networks are, in addition to chaotic, subject to ion channel stochasticity in the form of multiplicative (channel) or additive (current) noise. We calculate the Functional Connectivity Dynamics matrix by comparing the Functional Connectivity (FC) matrices that describe the pair-wise phase synchronization in a moving window fashion and performing clustering of FCs. Moderate noise can enhance the multistable behavior that is evoked by chaos, resulting in more heterogeneous synchronization patterns, while more intense noise abolishes multistability. In networks composed of nonchaotic nodes, some noise can induce multistability in an otherwise synchronized, nonchaotic network. Finally, we found the same results regardless of the multiplicative or additive nature of noise.
The effects of alternate dual-frequency ultrasound (ADFU) pretreatment on the degree of hydrolysis (DH) of wheat gluten (WG) and angiotensin I-converting enzyme (ACE) inhibitory activity were investigated in this research. The surface topography, nano-mechanics and secondary structure of WG were also determined using atomic force microscope (AFM) and circular dichroism (CD). The correlations of ACE inhibitory activity and DH with surface topography, nano-mechanics and secondary structure of WG were determined using Pearson's correlation analysis. The results showed that with an increase in either pretreatment duration or power, the ACE inhibitory activity of the hydrolysate also increases, reaching maximum at 10 min and 150 W/L, respectively, and then decreases thereafter. Similarly, AFM analysis showed that as the pretreatment duration or power increases, the surface roughness also increase and again a decrease occurs thereafter. As the pretreatment duration or power increased, the Young's modulus and adhesion of WG also increased and then declined. Young's modulus and adhesions average values were compared with ACE inhibitory activity reversely. The result of the CD spectra analysis exhibited losses in the relative percentage of α-helix of WG. Pearson's correlation analysis showed that the average values of Young's modulus and the relative percentage of α-helix correlated with ACE inhibitory activity of the hydrolysates linearly and significantly (P<0.05); the relative percentage of β-sheet correlated linearly with DH of WG significantly (P<0.05). In conclusion, ADFU pretreatment is an efficient method in proteolysis due to its physical and chemical effect on the Young's modulus, α-helix and β-sheet of WG.
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