Transgenic plant cell cultures for the production of biopharmaceuticals including monoclonal antibodies, recombinant proteins have been regarded as an alternative platform in addition to traditional microbial fermentation and mammalian cell cultures. Plant-made pharmaceuticals (PMPs) have several advantages such as safety, cost-effectiveness, scalability and possibility of complex post-translational modifications. Increasing demand for the quantity and diversity of pharmaceutical proteins may accelerate the industrialization of PMP technology. Up to date, there is no plant-made recombinant protein approved by USFDA (Food and Drug Administration) for human therapeutic uses due to the technological bottlenecks of low expression level and slight differences in glycosylation. Regarding expression levels, it is possible to improve the productivity by using stronger promoter and optimizing culture processes. In terms of glycosylation, humanization has been attempted in many ways to reduce immune responses and to enhance the efficacy as well as stability. In this review article, all these respects of transgenic plant cell cultures were summarized. In addition, we also discuss the general characteristics of plant cell suspension cultures related with bioreactor design and operation to achieve high productivity in large scale which could be a key to successful commercialization of PMPs.
This study aims to extract meaningful information through a social network analysis based on Big data in order to investigate if a tourist’s awareness of destination image favorably affects competitiveness of tourist destination. A web crawler was employed to gather online review data from 117 destinations and tourism products in Seoul, Korea using Tripadvisor. This web crawler is representative of the online travel community used throughout global tourism industry. Specifically, 23 image factors and 200 components composing two aspects of cognitive and affective images were derived using a system of text mining analysis. This study tried to identify and enhance destination competitiveness by investigating a tourist’s awareness in terms of their destination image. This was measured using indicators of network analysis that were degree centrality, closeness centrality, between centrality and eigenvector centrality. The following results were found: First) 7 image components help to create a positive image of tourist awareness in terms of destination image. Second) 14 image components feel psychologically close to tourists in terms of destination image. Third) 8 image components favorable influence and enhance the competitiveness of destination. Fourth) 11 image components have a greater impact greater than the others when tourists have a perceived destination image. Implications and suggestions are presented along with the findings of the study, which will contribute to the theoretical framework by suggesting a new perspective for measuring destination image based on Big data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.