Henan University of Technology

About: Henan University of Technology is a education organization based out in Zhengzhou, China. It is known for research contribution in the topics: Catalysis & Chemistry. The organization has 7648 authors who have published 6503 publications receiving 73067 citations. The organization is also known as: Hénán Gōngyè Dàxué.

Hepatic Lipidomics Analysis Reveals the Antiobesity and Cholesterol-Lowering Effects of Tangeretin in High-Fat Diet-Fed Rats

Abstract: Tangeretin (TAN) exhibited antilipogenic, antidiabetic, and lipid-lowering effects. However, the lipid biomarkers and the underlying mechanisms for antiobesity and cholesterol-lowering effects of TAN have not been sufficiently investigated. Herein, we integrated biochemical analysis with lipidomics to elucidate its efficacy and mechanisms in high-fat diet-fed rats. TAN at supplementation levels of 0.04 and 0.08% not only significantly decreased body weight gain, serum total cholesterol, and low-density lipoprotein cholesterol levels but also ameliorated hepatic steatosis. These beneficial effects were associated with the declining levels of fatty acids, diacylglycerols (DGs), triacylglycerols, ceramides, and cholesteryl esters by hepatic lipidomics analysis, which were attributed to downregulating lipogenesis-related genes and upregulating lipid oxidation- and bile acid biosynthesis-related genes. Additionally, 21 lipids were identified as potential lipid biomarkers, such as DGs and phosphatidylethanolamines. These findings indicated that the modulation of lipid homeostasis might be the key pathways for the mechanisms of TAN in the antiobesity and cholesterol-lowering effects.

A Study on Subunit Groups of Soybean Protein Extracts under SDS-PAGE

Abstract: Protein extracts of 640 soybean cultivars and landraces, mainly from China and a few from the US, were analyzed for their components and subunits based on distribution patterns of bands with varying molecular weights (MW) under SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel electrophoresis). The number and molecular weight of the bands in SDS-PAGE varied among materials and showed a tendency of continuous distribution. Accordingly, the SDS-PAGE patterns of the soybean protein extracts were divided into two regions: the region of bands with MW < 44 KDa and that with MW ≥ 44 KDa. The first region containing mainly 11S proteins was divided into four parts, called subunit groups, i.e. 11S-1 (14.4–22 KDa), 11S-2 (22–26 KDa), 11S-3 (26–34 KDa) and 11S-4 (34–44 KDa). The second region containing mainly 7S protein was divided into six subunit groups, i.e. 7S-1 (44–49 KDa), 7S-2 (49–55 KDa), 7S-3 (55–67 KDa), 7S-4 (67–73 KDa), 7S-5 (73–82 KDa) and 7S-6 (82–91 KDa). The sum of relative contents of 11S-1–11S-4 was obtained as the relative content of 11S protein, those of 7S-1–7S-6 as that of 7S protein, and therefore, the 11S/7S ratio obtained. The proposed criteria were demonstrated to be simple, stable and feasible. Among the 640 tested materials, 39 lacked 11S-1 but none lacked the other 11S subunit groups, while deficiencies existed in all the six subunit groups of 7S, indicating a great potential for the genetic variation of protein components and subunits for breeding for the improvement of protein qualities.

Quantitative Proteomic Analysis of Wheat Seeds during Artificial Ageing and Priming Using the Isobaric Tandem Mass Tag Labeling.

Abstract: Wheat (Triticum aestivum L.) is an important crop worldwide. The physiological deterioration of seeds during storage and seed priming is closely associated with germination, and thus contributes to plant growth and subsequent grain yields. In this study, wheat seeds during different stages of artificial ageing (45°C; 50% relative humidity; 98%, 50%, 20%, and 1% Germination rates) and priming (hydro-priming treatment) were subjected to proteomics analysis through a proteomic approach based on the isobaric tandem mass tag labeling. A total of 162 differentially expressed proteins (DEPs) mainly involved in metabolism, energy supply, and defense/stress responses, were identified during artificial ageing and thus validated previous physiological and biochemical studies. These DEPs indicated that the inability to protect against ageing leads to the incremental decomposition of the stored substance, impairment of metabolism and energy supply, and ultimately resulted in seed deterioration. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the up-regulated proteins involved in seed ageing were mainly enriched in ribosome, whereas the down-regulated proteins were mainly accumulated in energy supply (starch and sucrose metabolism) and stress defense (ascorbate and aldarate metabolism). Proteins, including hemoglobin 1, oleosin, agglutinin, and non-specific lipid-transfer proteins, were first identified in aged seeds and might be regarded as new markers of seed deterioration. Of the identified proteins, 531 DEPs were recognized during seed priming compared with unprimed seeds. In contrast to the up-regulated DEPs in seed ageing, several up-regulated DEPs in priming were involved in energy supply (tricarboxylic acid cycle, glycolysis, and fatty acid oxidation), anabolism (amino acids, and fatty acid synthesis), and cell growth/division. KEGG and protein-protein interaction analysis indicated that the up-regulated proteins in seed priming were mainly enriched in amino acid synthesis, stress defense (plant-pathogen interactions, and ascorbate and aldarate metabolism), and energy supply (oxidative phosphorylation and carbon metabolism). Therefore, DEPs associated with seed ageing and priming can be used to characterize seed vigor and optimize germination enhancement treatments. This work reveals new proteomic insights into protein changes that occur during seed deterioration and priming.

Cluster Heads Election Analysis for Multi-hop Wireless Sensor Networks Based on Weighted Graph and Particle Swarm Optimization

Abstract: Continued advances of wireless communication technologies have enabled the deployment of large scale wireless sensor networks. The sensors' limited power makes energy consumption a critical issue. In single-hop wireless sensor networks, cluster heads election method based on residual energy can obtain better energy efficiency than the method in which cluster heads are elected in turns or by probabilities. Is it the same in multi-hop wireless sensor networks? In this paper we proposed and evaluated a routing optimization scheme based on graph theory and particle swarm optimization algorithm for multi-hop wireless sensor network. Our algorithm synthesized the intuitionist advantages of graph theory and optimal search capability of PSO. The result in multi-hop networks is completely different from that in single-hop wireless sensor networks. The result shows that there is very little difference from these methods. The reason is discussed in detail.