Role of transcription factors in porcine reproductive and respiratory syndrome virus infection: A review

Porcine reproductive and respiratory syndrome (PRRS) is an infectious disease caused by the PRRS virus that leads to reproductive disorders and severe dyspnoea in pigs, which has serious economic impacts. One of the reasons PRRSV cannot be effectively controlled is that it has developed countermeasures against the host immune response, allowing it to survive and replicate for long periods. Transcription Factors acts as a bridge in the interactions between the host and PRRSV. PRRSV can create an environment conducive to PRRSV replication through transcription factors acting on miRNAs, inflammatory factors, and immune cells. Conversely, some transcription factors also inhibit PRRSV proliferation in the host. In this review, we systematically described how PRRSV uses host transcription factors such as SP1, CEBPB, STATs, and AP-1 to escape the host immune system. Determining the role of transcription factors in immune evasion and understanding the pathogenesis of PRRSV will help to develop new treatments for PRRSV

Correlation between serum esterase polymorphism and production performance of Yuxi fat-tailed sheep

The polymorphism of serum esterase (Es) of Henan Yuxi fat-tailed sheep was detected through polyacrylamide gel electrophoresis (PAGE), and the correlation between serum esterase and productivity was analyzed. The research result indicated that there are two alleles on the Es loci of Henan Yuxi fat-tailed sheep: Es+ and Es-. The gene frequencies of Es+ and Es- were 0.55 and 0.45, respectively. Besides, the frequencies of three genotypes (Es++, Es+- and Es--) are 0.425, 0.250 and 0.325, respectively. The recommended height of Es++ genotype is significantly higher than that of Es+- genotype (P<0.05), but the above two produce indistinctive difference in recommended height with Es-- genotype (P>0.05). The chest circumference of Es++ genotype is significantly higher than that of Es-- (P<0.05), but the above two produce indistinctive difference in chest circumference with Es+- genotype (P>0.05). Es exerts no significant impact on other indexes (P>0.05).Keywords: Henan Yuxi fat-tailed sheep, serum esterase (Es), polymorphismAfrican Journal of Biotechnology Vol. 12(9), pp. 986-98

A body map of super-enhancers and their function in pig

IntroductionSuper-enhancers (SEs) are clusters of enhancers that act synergistically to drive the high-level expression of genes involved in cell identity and function. Although SEs have been extensively investigated in humans and mice, they have not been well characterized in pigs.MethodsHere, we identified 42,380 SEs in 14 pig tissues using chromatin immunoprecipitation sequencing, and statistics of its overall situation, studied the composition and characteristics of SE, and explored the influence of SEs characteristics on gene expression.ResultsWe observed that approximately 40% of normal enhancers (NEs) form SEs. Compared to NEs, we found that SEs were more likely to be enriched with an activated enhancer and show activated functions. Interestingly, SEs showed X chromosome depletion and short interspersed nuclear element enrichment, implying that SEs play an important role in sex traits and repeat evolution. Additionally, SE-associated genes exhibited higher expression levels and stronger conservation than NE-associated genes. However, genes with the largest SEs had higher expression levels than those with the smallest SEs, indicating that SE size may influence gene expression. Moreover, we observed a negative correlation between SE gene distance and gene expression, indicating that the proximity of SEs can affect gene activity. Gene ontology enrichment and motif analysis revealed that SEs have strong tissue-specific activity. For example, the CORO2B gene with a brain-specific SE shows strong brain-specific expression, and the phenylalanine hydroxylase gene with liver-specific SEs shows strong liver-specific expression.DiscussionIn this study, we illustrated a body map of SEs and explored their functions in pigs, providing information on the composition and tissue-specific patterns of SEs. This study can serve as a valuable resource of gene regulatory and comparative analyses to the scientific community and provides a theoretical reference for genetic control mechanisms of important traits in pigs

Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review.

Due to importantly beneficial effects on physical and mental health and strong association with many rehabilitation programs, Physical Activity Recognition and Monitoring (PARM) have been considered as a key paradigm for smart healthcare. Traditional methods for PARM focus on controlled environments with the aim of increasing the types of identifiable activity subjects complete and improving recognition accuracy and system robustness by means of novel body-worn sensors or advanced learning algorithms. The emergence of the Internet of Things (IoT) enabling technology is transferring PARM studies to open and connected uncontrolled environments by connecting heterogeneous cost-effective wearable devices and mobile apps. Little is currently known about whether traditional PARM technologies can tackle the new challenges of IoT environments and how to effectively harness and improve these technologies. In an effort to understand the use of IoT technologies in PARM studies, this paper will give a systematic review, critically examining PARM studies from a typical IoT layer-based perspective. It will firstly summarize the state-of-the-art in traditional PARM methodologies as used in the healthcare domain, including sensory, feature extraction and recognition techniques. The paper goes on to identify some new research trends and challenges of PARM studies in the IoT environments, and discusses some key enabling techniques for tackling them. Finally, this paper consider some of the successful case studies in the area and look at the possible future industrial applications of PARM in smart healthcare

An analysis of the key safety technologies for natural gas hydrate exploitation

Natural Gas Hydrate (NGH) is a high combustion efficiency clean energy and its reserve is twice as that of natural gas and petroleum, so NGH is the potential resource which could overcome the increasing energy assumption. One of the essential aspects during the exploitation of NGH is to avoid risk, and here in this work, we summarized the relevant management experience to study the critical safety risk in the exploitation of natural gas hydrate. The problems that must be resolved during NGH exploitation were identified through the research on the comparison of the characteristics of conventional gas hydrate mining methods and potential drilling engineering risks and stratum damages in the processes of exploitation. Combined with typical case analysis of gas hydrate mining, it is concluded that the key for safe NGH exploitation is the changes of stratum stress caused by hydrate decomposition; and all safety management experiences should be based on steady drilling and reasonable exploitation to prevent environment, equipment, persons and other aspects damages from layering and stress changes.Cited as: Yang, Y., He, Y., Zheng, Q. An analysis of the key safety technologies for natural gas hydrate exploitation. Advances in Geo-Energy Research, 2017, 1(2): 100-104, doi: 10.26804/ager.2017.02.0

Path-Planning Strategy for Lane Changing Based on Adaptive-Grid Risk-Fields of Autonomous Vehicles

The quantification and effective representation of safety risks for scenarios in structured road traffic environments of autonomous driving are currently being investigated in an active way. Based on artificial potential fields, a risk-field model for the traffic environment that considers the motion state of an obstacle vehicle is established, and an adaptive-grid risk-field method is proposed for autonomous vehicles. In this method, the traffic environment is meshed initially, and adaptive-grid division is performed using a quadtree grid-dividing strategy for root grids where the grid risk values are within the division interval, which allows for a more accurate quantification of traffic environment risk values. Adding adaptive-grid risk-field parameters to the cost function of the path-planning algorithm improves the accuracy of path safety risk assessment and completes the evaluation and selection of the optimal lane-change path. Simulation results show that the adaptive-grid risk-field established in this paper can effectively express the safety risks of the traffic environment, and the path-planning algorithm incorporating the adaptive-grid risk-field can obtain better paths for lane change compared with the traditional path-planning algorithm, while ensuring the safety of lane change

Path-Planning Strategy for Lane Changing Based on Adaptive-Grid Risk-Fields of Autonomous Vehicles

The quantification and effective representation of safety risks for scenarios in structured road traffic environments of autonomous driving are currently being investigated in an active way. Based on artificial potential fields, a risk-field model for the traffic environment that considers the motion state of an obstacle vehicle is established, and an adaptive-grid risk-field method is proposed for autonomous vehicles. In this method, the traffic environment is meshed initially, and adaptive-grid division is performed using a quadtree grid-dividing strategy for root grids where the grid risk values are within the division interval, which allows for a more accurate quantification of traffic environment risk values. Adding adaptive-grid risk-field parameters to the cost function of the path-planning algorithm improves the accuracy of path safety risk assessment and completes the evaluation and selection of the optimal lane-change path. Simulation results show that the adaptive-grid risk-field established in this paper can effectively express the safety risks of the traffic environment, and the path-planning algorithm incorporating the adaptive-grid risk-field can obtain better paths for lane change compared with the traditional path-planning algorithm, while ensuring the safety of lane change

A Fault-Tolerant Location Approach for Transient Voltage Disturbance Source Based on Information Fusion

This paper proposed a fault-tolerant approach based on information fusion (IF) to automatically locate the transient voltage disturbance source (TVDS) in smart distribution grids. We first defined three credibility factors that will influence the reliability of the direction-judgments at each power quality monitor (PQM). Then we proposed two rules of influence and a verification factor for the distributed generation (DG) integration. Based on the two sets of direction-judgment criteria, a novel decision-making method with fault tolerance based on the IF theory is proposed for automatic location of the TVDS. Three critical schemes, including credibility fusion, conflict weakening, and correction for DG integration, have been integrated in the proposed fusion method, followed by a reliability evaluation of the location results. The proposed approach was validated on the IEEE 13-node test feeder, and the TVDS location results demonstrated the effectiveness and fault tolerance of the IF based approach

Online energy flow control for residential microgrids with URGs: An event-driven approach

Energy flow control (EFC) of residential microgrids (RMGs) equipped with renewable generations (RGs) is an essential component for the future smart grid that contributes to enhance renewable energy consumption and reduce cost. Different from most existing papers that devote to offline EFC to against the uncertainties caused by RGs and local load demand in RMGs, this paper focuses on online EFC framework for achieving optimal operations of a RMG. This framework is based on an event-driven approach that maximizes RGs utilization and maintains supply-demand balance considering the schedulable ability of active loads and the uncertainties of RMG. An event-driven EFC architecture for RMG is developed, and the events analysis are presented. Based on this architecture, the state machine is adopted to trigger the execution of the online EFC. Furthermore, an online algorithm is designed for communal energy server platform to determine scheduling plans for active loads. Finally, the performance analysis of the online algorithm is evaluated. Simulation results illustrate the basic characteristics and the advantages of the proposed approach