Effect of Broussonetia papyrifera L. (paper mulberry) silage on dry matter intake, milk composition, antioxidant capacity and milk fatty acid profile in dairy cows

Si, Bingwen,Tao, Hui,Zhang, Xiaoli,Guo, Jiangpeng,Cui, Kai,Tu, Yan,Diao, Qiyu Asian Australasian Association of Animal Productio 2018 Animal Bioscience Vol.31 No.8

Objective: This study was carried out to investigate the possible application of Broussonetia papyrifera (B. papyrifera) silage as a functional feeding stuff in dairy cattle. Methods: Seventy-two Holstein cows were divided into four groups randomly and allocated to 6 pens with 3 individuals in each group and fed the original total mixed ratio (TMR) in the dairy farm or the new TMR with 5%, 10%, and 15% B. papyrifera silage, separately. Feed intake were recorded, milk and blood samples were collected, and milk composition, blood metabolites and milk fatty acids composition were measure at the end of the experiment. Results: Dry matter intake of cows decreased when they fed on diet with B. papyrifera, but no differences were observed in body condition score, milk yield, milk protein and lactose, feed efficiency and serum metabolites between groups. Both 10% or 15% of B. papyrifera silage in the diet significantly increased the immunoglobulin A (IgA) and IgG in serum, 15% of B. papyrifera silage increased the content of serum catalase, superoxide dismutase, total antioxidant capacity, and decreased the content of 8-hydroxy-2'-deoxyguanosine. Furthermore, 10% or 15% of B. papyrifera silage resulted in a significant decrease in the milk somatic cell count, and increased the polyunsaturated fatty acids content in the milk. Conclusion: The diets with 10% to 15% of B. papyrifera silage might enhance the immune and antioxidant function of dairy cows and increase the polyunstaturated fatty acid concentration in the milk.

Proteomic analyses on the browning of shade-dried Thompson seedless grape

Liu Fengjuan,Huang Wenshu,Feng Zuoshan,Tao Yongxia,Fan Yingying,He Weizhong,Li XiaoLi,Fang Xiaotong,Wang Cheng,Bai Yujia 한국응용생명화학회 2021 Applied Biological Chemistry (Appl Biol Chem) Vol.64 No.3

China is one of the main producers in the worldwide raisin market. Most China’s raisins are produced in Xinjiang where the Thompson seedless grape ( Vitis vinifera L.cv.Thompson seedless) is the main variety of green raisin. However, the browning of Thompson seedless grape during drying has been well-acknowledged as the primary factor affecting the development of the raisin industry. Data independent acquisition (DIA)-based protein profiling was performed on fresh and shade-dried Thompson seedless grapes. As a result, 5431 proteins were identified, among which the amounts of 739 proteins in fresh grape were found to be significantly different with those in dried grape. The functional annotation based on the Blast2GO showed that the ‘organic substance metabolic process’, ‘regulation of molecular function’, ‘enzyme regulator activity’, and ‘isomerase activity’ related proteins became very active during browning. Further analyses revealed that the browning-related proteins, which with significant different amounts in fresh and in dried grapes, are primarily involved in the phenylpropanoid biosynthesis, tyrosine metabolism, phenylalanine metabolism, oxidative phosphorylation metabolism, plutathione metabolism, peroxisome pathway, and fatty acid degradation. And five random differential proteins were verified with parallel reaction monitoring (PRM). The PRM results were in agreement with the DIA data. The main browning-related proteins of Thompson seedless grape were identified in this study. Their properties were tested, and their roles in the browning mechanism were indicated. This will lay base to a better understanding on the enzymatic browning of Thompson seedless grape, and it will also provide guidance for controlling the quality of Thompson seedless grapes in industry.

Transcription factor Sp1 is necessary and functional in regulating expression of oncogene ZNF703

Xiaolin Liao,Yongjie Lu,Junbao Yang,Tao Kuang,Lilin Jiang,Yanjun Wang,Huiqun Kang,Bo Jiang,Xiaoli Zhou,Sheng He 한국유전학회 2017 Genes & Genomics Vol.39 No.10

Zinc finger protein 703 (ZNF703) is a putative oncogene in patients with the luminal B molecular subtype of breast cancer. Although the exact function of ZNF703 protein remains largely unknown, its expression and regulation have been implicated in several physiological and pathological processes. In the current study, for the first time, we identified and characterized the human ZNF703 gene promoter region. As a means of characterizing the transcription elements required for expression of ZNF703 protein at different stages, we cloned the promoter region of ZNF703 then created chimeric reporter plasmids for use in luciferase assays. A progressive deletion analysis of the ZNF703 gene’s 5′ and 3′ -flanking regions revealed that the core promoter is located in a 256-bp region ranging from nt-539 to nt-283. Next, we examined the effects of sitespecific mutations and treatment with mithramycin A to identify the functional Sp1 binding site, which was found to be located in a 447 bp region that ranged from nt-509 to nt-76, displayed the characteristics of a CpG island, and overlapped with the promoter region. In conclusion, our data suggest that ZNF703 transcription is regulated by transcription factor Sp1. This finding should facilitate future studies of the mechanism which regulates expression of this important gene.

Vehicle Detection in Aerial Images Based on Hyper Feature Map in Deep Convolutional Network

( Jiaquan Shen ),( Ningzhong Liu ),( Han Sun ),( Xiaoli Tao ),( Qiangyi Li ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.4

Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.

Different distribution patterns of microorganisms between aquaculture pond sediment and water

Dai Lili,Liu Chengqing,Peng Liang,Song Chaofeng,Li Xiaoli,Tao Ling,Li Gu 한국미생물학회 2021 The journal of microbiology Vol.59 No.4

Aquatic microorganisms in the sediment and water column are closely related; however, their distribution patterns between these two habitats still remain largely unknown. In this study, we compared sediment and water microeukaryotic and bacterial microorganisms in aquaculture ponds from different areas in China, and analyzed the influencing environmental factors as well as the inter-taxa relationships. We found that bacteria were significantly more abundant than fungi in both sediment and water, and the bacterial richness and diversity in sediment were higher than in water in all the sampling areas, but no significant differences were found between the two habitats for microeukaryotes. Bacterial taxa could be clearly separated through cluster analysis between the sediment and water, while eukaryotic taxa at all classification levels could not. Spirochaetea, Deltaproteobacteria, Nitrospirae, Ignavibacteriae, Firmicutes, Chloroflexi, and Lentimicrobiaceae were more abundantly distributed in sediment, while Betaproteobacteria, Alphaproteobacter, Cyanobacteria, Roseiflexaceae, Dinghuibacter, Cryomorphaceae, and Actinobacteria were more abundant in water samples. For eukaryotes, only Cryptomonadales were found to be distributed differently between the two habitats. Microorganisms in sediment were mainly correlated with enzymes related to organic matter decomposition, while water temperature, pH, dissolved oxygen, and nutrient levels all showed significant correlation with the microbial communities in pond water. Intensive interspecific relationships were also found among eukaryotes and bacteria. Together, our results indicated that eukaryotic microorganisms are distributed less differently between sediment and water in aquaculture ponds compared to bacteria. This study provides valuable data for evaluating microbial distributions in aquatic environments, which may also be of practical use in aquaculture pond management.

Low beta superconducting cavity system design for HIAF iLinac

Mengxin Xu,Yuan He,Shengxue Zhang,Lubei Liu,Tiancai Jiang,Zehua Liang,Tong Liu,Yue Tao,Chunlong Li,Qitong Huang,Fengfeng Wang,Hao Guo,Feng Bai,Xianbo Xu,Shichun Huang,Xiaoli Li,Zhijun Wang,Shenghu Zha Korean Nuclear Society 2023 Nuclear Engineering and Technology Vol.55 No.7

A superconducting ion-Linac (iLinac), which is supposed to work as the injector in the High Intensity heavy-ion Accelerator Facility project, is under development at the Institute of Modern Physics (IMP), Chinese Academy of Sciences. The iLinac is a superconducting heavy ion linear accelerator approximately 100 meters long and contains 96 superconducting cavities in two types of 17 cyromodules. Two types of superconducting resonators (quarter-wave resonators with a frequency of 81.25 MHz and an optimal beta β = v/c = 0.07 called QWR007 and half-wave resonators with a frequency of 162.5 MHz and an optimal beta β = 0.15 called HWR015) have been investigated. The cavity design included extensive multi-parameter electromagnetic simulations and mechanical analysis, and its results are described in details. The fundamental power coupler and cavity dynamic tuner designs are also presented in this article. The prototypes are under manufacturing and expected to be ready in 2023.

Adaptive Parameter Identification Based on Dead-Time Compensation for Permanent Magnet Synchronous Machines for the 2011 11th International Conference on Control, Automation and Systems

Xiao Li,Tao Wang,Wei Fan 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

The objective of this paper is to investigate an accurate on-line parameters identification method for PMSM. Because a majority of controllers are based on motor models, the parameters of stator resistance and dq-axis inductances play important roles for achieving high-performance control. However, voltage drop between the reference and output voltage in a pulsewidth-modulation (PWM) voltage source inverter affects the accuracy of identification. In this paper a model-reference adaptive identification method is proposed with a simple method for compensating the voltage drop of inverter in the driven system. The global stability of adaptive laws is proved by the Popov’s hyper-stability theory. Simulation results proved that the estimated stator resistance and dq-axis inductances converge to the constant after the rotor speed becomes stable. The compensation method introduced in the MRAS is easy to implement without any additional circuits. Experimental results demonstrate the effectiveness of the proposed identified method and the compensation method.