一种简单高效扩增人杯状病毒ORF2区RT-PCR方法的建立及其意义

The capsid protein encoded by ORF2 of human calicivirus(HuCV) expressed in the baculovirus expression system can self-assembled into virus-like particles(VLPs),which would be important for the development of improving diagnostic methods.The RT-PCR procedures routinely used to amplify the RNA polymerase region have usually been inefficient for amplification of ORF2,which would bring obstacle for the development of new diagnostic reagents.Through optimization of RT-PCR conditions,we established a simple and high performance RT-PCR method to amplify ORF2,and by which demonstrated a corresponding relationship between the genotype and the antigenic type.It provides conditions for developing diagnostic reagent which accommodates to diagnosis of HuCVs prevailing in China,and also provides the basis for studying the genetic variance and the pathogenesis of HuCV.

Total plant performance evaluation based on big data: Visualization analysis of TE process

The performance evaluation of the process industry, which has been a popular topic nowadays, can not only find the weakness and verify the resilience and reliability of the process, but also provide some suggestions to improve the process benefits and efficiency. Nevertheless, the performance assessment principally concentrates upon some parts of the entire system at present, for example the controller assessment. Although some researches focus on the whole process, they aim at discovering the relationships between profit, society, policies and so forth, instead of relations between overall performance and some manipulated variables, that is, the total plant performance. According to the big data of different performance statuses, this paper proposes a hierarchical framework to select some structured logic rules from monitored variables to estimate the current state of the process. The variables related to safety and profits are regarded as key factors to performance evaluation. To better monitor the process state and observe the performance variation trend of the process, a classificationvisualization method based on kernel principal component analysis(KPCA) and self-organizing map(SOM) is established. The dimensions of big data produced by the process are first reduced by KPCA and then the processed data will be mapped into a two-dimensional grid chart by SOM to evaluate the performance status. The monitoring method is applied to the Tennessee Eastman process. Monitoring results indicate that off-line and on-line performance status can be well detected in a two-dimensional diagram.

Highly stable and antifouling graphene oxide membranes prepared by bio-inspired modification for water purification

Graphene oxide(GO)membranes show great potential in molecular separation for water treatment.However,the inferior stability of GO membranes is a major bottleneck for practical applications.In this study,bio-inspired polydopamine(PDA)deposition is reported for enhancing the stability of GO membranes.Through simple and mild immersion,PDA is self-polymerized on GO membranes.The blocking of PDA chains to membrane defects improves the rejections for various molecules.Because the inherently strong adhesion and crosslinking of PDA greatly strengthen the interactions of substrates to GO layers and the binding force of GO nanosheets,the prepared PDA-GO membranes exhibit impressive long-te rm stability in cross-flow filtration,and maintain good nanofiltration perfo rmance at various feed pressures,tangential velocities,and eve n after external scratching.Moreover,because the deposited PDA layers obstruct the direct contact between GO and contaminants,the antifouling property of the PDA-GO membranes increases substantially,with recovery ratio about 98%.