A novel aminopeptidase with potential debittering properties in casein and soybean protein hydrolysates

Peng Song,Lei Cheng,Kangming Tian,Meng Zhang,Suren Singh,Dandan Niu,Bernard Prior,Nokuthula Peace Mchunu,Zheng-Xiang Wang 한국식품과학회 2020 Food Science and Biotechnology Vol.29 No.11

A new aminopeptidase (An-APa) was identified and biochemically characterized from Aspergillus niger CICIM F0215. It had maximal activity at 40 °C and pH 7.0 and exhibited a broad substrate specificity both on hydrophilic and hydrophobic amino acid residues at N-terminals. With An-APa hydrolysis for 1 h, the casein-pepsin and soybean protein isolates (SPI)-pepsin hydrolysates released both hydrophilic and hydrophobic amino acids and the hydrophobic amino acids having Q values (degree of hydrophobicity) greater than 1500 cal/mol were remarkably released. Leu, Ile, Phe, Tyr, Trp, Pro, Val and Lys in the casein hydrolysate after treatment with An-APa increased 18.61, 0.84, 11.35, 13.18, 3.34, 6.30, 7.46, and 8.19 mg/100 mL, respectively, and 19.72, 1.47, 18.37, 11.72, 4.61, 4.10, 8.13, and 5.85 mg/100 mL, respectively, in the SPI hydrolysate. Both accounted for 65.0% and 64.4% of total released free amino acids from casein and SPI hydrolysates, respectively. This indicated that An-APa could be potentially applicable in debittering protein hydrolysates.

Metallothionein MT1M Suppresses Carcinogenesis of Esophageal Carcinoma Cells through Inhibition of the Epithelial-Mesenchymal Transition and the SOD1/PI3K Axis

Li, Dandan,Peng, Weiyan,Wu, Bin,Liu, Huan,Zhang, Ruizhen,Zhou, Ruiqin,Yao, Lijun,Ye, Lin Korean Society for Molecular and Cellular Biology 2021 Molecules and cells Vol.44 No.4

Metallothionein (MT1M) belongs to a family of cysteinerich cytosolic protein and has been reported to be a tumor suppressor gene in multiple cancers. However, its role in esophageal carcinoma carcinogenesis remains unclear. In this study, MT1M expression was correlated with tumor type, stage, drinking and smoking history, as well as patient survival. We also studied the regulation and biological function of MT1M in esophageal squamous cell carcinoma (ESCC). We have found that MT1M is significantly downregulated in ESCC tissues compared with adjacent non-cancer tissues. Furthermore, restoration of expression by treatment with the demethylation agent A + T showed that MT1M downregulation might be closely related to hypermethylation in its promoter region. Over-expression of MT1M in ESCC cells significantly altered cell morphology, induced apoptosis, and reduced colony formation, cell viability, migration and epithelial-mesenchymal transition. Moreover, based on reactive oxygen species (ROS) levels, a superoxide dismutase 1 (SOD1) activity assay and protein analysis, we verified that the tumor-suppressive function of MT1M was at least partially caused by its upregulation of ROS levels, downregulation of SOD1 activity and phosphorylation of the SOD1 downstream pathway PI3K/AKT. In conclusion, our results demonstrated that MT1M was a novel tumor-suppressor in ESCC and may be disrupted by promoter CpG methylation during esophageal carcinogenesis.

Can Managerial Military Experience Affect Corporate Innovation? : Evidence from an Emerging Market

Lang, Xiangxiang,You, Dandan,Cui, Li,Peng, Zhe Institute of Management Research 2020 Journal of East Asia Management Vol.1 No.1

Military experience has a great impact on a soldier ability to handle risks. Therefore, when those soldiers become managers, they may behave differently in making risky corporate decisions, especially in activities like the R&D investment. However, studies on how military experience affect R&D have been largely missing in the largest emerging economy, i.e. China, despite that the country hires a higher percentage of military managers than the US. In addition, it remains a question whether military managers affect the state-owned enterprises (SOEs) in China, as many of the corporate decisions are made by the government. This paper tries to address these questions. The imprinting theory and the upper echelon theory suggest that managers' personal experience can affect their behaviour, which in turn influences their corporate decisions. In this paper, we examine whether managers with military experience lead to higher R&D investment and whether such an effect exists in state-owned enterprises. Based on a sample of listed firms in China's A-share market over 2008-2017, we make two findings. First, companies with military managers have high R&D investment. By dividing managers' military positions into high and low rank, we find that companies tend to have higher (lower) R&D investment if their managers hold a high-rank (low-rank) position. Second, the effect of high-rank military managers on R&D investment is more pronounced if the manager is also the founder and the company is a non-state-owned enterprise. For low-ranking military managers, a stronger effect on R&D investment is also observed if they are also the founder, but whether their companies are state-owned or not has no impact on R&D investment. This study identifies managers' military experience as a contributing factors to corporate R&D investment in the largest emerging economy. This paper tests an implication of the imprinting theory and the upper echelon theory, i.e., managers' personal experience can affect their behaviour, which in turn influences their corporate decisions. Specifically, we focus on one aspect of personal experience - military experience - and look at whether it is beneficial to firms' technological innovation, therefore enriches the literature of managerial heterogeneity. Our findings on the influence of managers' military experience on firms' technological innovation can help us better understand the role of managers play in corporate decision making, and how managers' individual traits interact with the firm's characteristics.

Sequence Analysis of cytb Gene in Echinococcus granulosus from Western China

Xiuqin Zhong,Ning Wang,Dandan Hu,Jiahai Wang,Tianyu Liu,Xiaobin Gu,Shuxian Wang,Xuerong Peng,Guangyou Yang 대한기생충학열대의학회 2014 The Korean Journal of Parasitology Vol.52 No.2

Echinococcus granulosus is the causative agent of cystic echinococcosis with medical and veterinary importance in China. Our main objective was to discuss the genotypes and genetic diversity of E. granulosus present in domestic animals and humans in western China. A total of 45 hydatid cyst samples were collected from sheep, humans, and a yak and subjected to an analysis of the sequences of mitochondrial cytochrome b (cytb) gene. The amplified PCR product for all samples was a 1,068 bp band. The phylogenetic analysis showed that all 45 samples were identified as E. granulosus (genotype G1). Ten haplotypes were detected among the samples, with the main haplotype being H1. The haplotype diversity was 0.626, while the nucleotide diversity was 0.001. These results suggested that genetic diversity was low among our samples collected from the west of China based on cytb gene analysis. These findings may provide more information on molecular characteristics of E. granulosus from this Chinese region.

A ResNet based multiscale feature extraction for classifying multi-variate medical time series

Junke Zhu,Le Sun,Yilin Wang,Sudha Subramani,Dandan Peng,Shangwe Charmant Nicolas 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.5

We construct a deep neural network model named ECGResNet. This model can diagnosis diseases based on 12-lead ECG data of eight common cardiovascular diseases with a high accuracy. We chose the 16 Blocks of ResNet50 as the main body of the model and added the Squeeze-and-Excitation module to learn the data information between channels adaptively. We modified the first convolutional layer of ResNet50 which has a convolutional kernel of 7 to a superposition of convolutional kernels of 8 and 16 as our feature extraction method. This way allows the model to focus on the overall trend of the ECG signal while also noticing subtle changes. The model further improves the accuracy of cardiovascular and cerebrovascular disease classification by using a fully connected layer that integrates factors such as gender and age. The ECGResNet model adds Dropout layers to both the residual block and SE module of ResNet50, further avoiding the phenomenon of model overfitting. The model was eventually trained using a five-fold cross-validation and Flooding training method, with an accuracy of 95% on the test set and an F1-score of 0.841.We design a new deep neural network, innovate a multi-scale feature extraction method, and apply the SE module to extract features of ECG data.