Antarctic krill is a potential and attractive resource for consumption. However, most Antarctic krill meat is used to produce primary products with low commercial value, with few highly processed products. This study aimed to evaluate and improve the gelling properties of Antarctic krill surimi, with Pacific white shrimp surimi as control. Compared with Pacific white shrimp surimi, the lower β-sheet content and protein aggregation degree had a severe impact on the formation of the gel network of Antarctic krill surimi, which resulted in weaker breaking force, gel strength, and viscoelasticity (p < 0.05). Moreover, water retention capacity and molecular forces had a positive effect on the stability of the gel matrix of shrimp surimi. Thus, the high α-helix/β-sheet ratio, weak intermolecular interactions, and low level of protein network cross-linkage were the main reasons for the poor quality of Antarctic krill surimi. On this basis, the effects of six polysaccharides on the texture properties of Antarctic krill surimi were studied. Chitosan, konjac glucomannan, sodium carboxyl methyl cellulose, and waxy maize starch resulted in no significant improvement in the texture properties of Antarctic krill surimi (p > 0.05). However, the addition of ι-carrageenan (2%) or κ-carrageenan (1~2%) is an effective way to improve the texture properties of Antarctic krill surimi (p < 0.05). These findings will contribute to the development of reconstituted Antarctic krill surimi products with high nutritional quality and the promotion of deep-processing products of Antarctic krill meat.

With the current study, we aimed to determine the characteristics and calcium absorption capacity of egg white peptide–calcium complex (EWP-Ca) and determine the effect of sterilization on EWP-Ca to study the possibility of EWP-Ca as a new potential calcium supplement. The results of SEM and EDS showed a high calcium chelating ability between EWP and calcium, and the structure of EWP-Ca was clustered spherical particles due its combination with calcium. The FTIR and Raman spectrum results showed that EWP could chelate with calcium by carboxyl, phosphate, and amino groups, and peptide bonds may also participate in peptide–calcium binding. Moreover, the calcium absorption of EWP-Ca measured by the intestinal everted sac model in rats was 32.38 ± 6.83 μg/mL, significantly higher than the sample with CaCl_2, and the mixture of EWP and Ca (p < 0.05) revealed appropriate calcium absorption capacity. The fluorescence spectra and CD spectra showed that sterilization caused a decrease in the content of α-helix and β-sheet and a significant increase in β-turn (p < 0.05). Sterilization changed the EWP-Ca structure and decreased its stability; the calcium-binding capacity of EWP-Ca after sterilization was decreased to 41.19% (p < 0.05). Overall, these findings showed that EWP could bind with calcium, form a peptide–calcium chelate, and serve as novel carriers for calcium supplements.

Egg yolk forms have several health and industrial applications, but their storage characteristics and gel mechanisms have not been thoroughly studied. In order to investigate the relationship between the changes in structure and properties of egg yolk gel and egg yolk powder during storage, in this paper, egg yolk powder was stored at 37 °C for 0, 1, 3, and 6 months in an accelerated storage experiment, and the influence of storage time on the gel properties of egg yolk powder was analyzed. The results showed that the contents of protein carbonylation and sulfhydryl in the yolk decreased gradually with the extension of storage time. Circular dichroism and fluorescence spectra showed that the ordered structure and structural stability of egg yolk proteins decreased gradually. Oxidation led to the formation of intermolecular crosslinking in the egg yolk proteins and oxidized aggregates, resulting in a decrease in surface hydrophobicity, which affected the gel properties of the egg yolk powder after rehydration, resulting in the phenomenon of lipid migration and gel degradation. The results provide a theoretical basis for improving egg yolk powder’s overall quality and storage stability.

Multiple sclerosis (MS) is an autoimmune disease for which it is difficult to find exact disease-related genes. Effectively identifying disease-related genes would contribute to improving the treatment and diagnosis of multiple sclerosis. Current methods for identifying disease-related genes mainly focus on the hypothesis of guilt-by-association and pay little attention to the global topological information of the whole protein-protein-interaction (PPI) network. Besides, network representation learning (NRL) has attracted a huge amount of attention in the area of network analysis because of its promising performance in node representation and many downstream tasks. In this paper, we try to introduce NRL into the task of disease-related gene prediction and propose a novel framework for identifying the disease-related genes multiple sclerosis. The proposed framework contains three main steps: capturing the topological structure of the PPI network using NRL-based methods, encoding learned features into low-dimensional space using a stacked autoencoder, and training a support vector machine (SVM) classifier to predict disease-related genes. Compared with three state-of-the-art algorithms, our proposed framework shows superior performance on the task of predicting disease-related genes of multiple sclerosis.