Malondialdehyde (MDA) was selected to represent a secondary by-product of lipid peroxidation during rice ageing. This study aimed to investigate the effects of MDA modification on the structural characteristics of rice protein. The results showed that as MDA concentration increased, rice protein carbonyl and disulphide groups increased, but sulphydryl content decreased. The blue shift of maximum fluorescence peak, the decrease of rice protein intrinsic fluorescence intensity and the reduction of surface hydrophobicity indicated the formation of protein aggregates caused by MDA oxidative modification. The results of molecular weight distribution and particle size distribution showed that MDA modification resulted in the formation of soluble protein aggregates, and the decrease of rice protein solubility indicated that insoluble protein aggregates were formed. Results of protein electrophoresis showed that MDA modification contributed to rice protein aggregation via non-disulphide covalent bonds. The results showed that rice protein gradually aggregated with increasing MDA concentration. 相似文献
Nano Research - Insufficient intratumoral penetration greatly hurdles the anticancer performance of nanomedicine. To realize highly efficient tumor penetration in a precisely and spatiotemporally... 相似文献
Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANNFCM-GRN. In MANNFCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANNFCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANNFCM-GRN and show that MANNFCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANNFCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.
Magnetic Resonance Materials in Physics, Biology and Medicine - To investigate the value of using diffusion-weighted imaging (DWI) and intravoxel incoherent motion DWI (IVIM-DWI) to assess the... 相似文献