In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Ex Input:
Porcine epidemic diarrhoea (PED) is a contagious enteric disease of pigs caused by a coronavirus. A double antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) based on the use of monoclonal antibodies was developed for the detection of porcine epidemic diarrhoea virus (PEDV). The DAS-ELISA was compared with RT-PCR in the examination of 506 specimens collected during 2006-2007 from pigs originating from different farms located in the Po valley. Both faecal samples obtained directly from the rectum of live animals showing clinical signs and intestinal samples collected from the caecum of deceased pigs were included in the study. The correlation between the two methods was higher when testing faecal samples (K = 0.97, 95% CI: 0.94-1.00) than testing intestinal samples (K = 0.62, 95% CI: 0.35-0.89). The use of ELISA technology provided an efficient and effective mean of evaluating the presence of coronavirus PED antigen in field samples and indicates that this procedure is a very useful tool in epidemiological studies.

Ex Output:
Comparison of enzyme-linked immunosorbent assay and RT-PCR for the detection of porcine epidemic diarrhoea virus


Ex Input:
The baculovirus expression vector system (BEVS) is a versatile and powerful platform for protein expression in insect cells. With the ability to approach similar post-translational modifications as in mammalian cells, the BEVS offers a number of advantages including high levels of expression as well as an inherent safety during manufacture and of the final product. Many BEVS products include proteins and protein complexes that require expression from more than one gene. This review examines the expression strategies that have been used to this end and focuses on the distinguishing features between those that make use of single polycistronic baculovirus (co-expression) and those that use multiple monocistronic baculoviruses (co-infection). Three major areas in which researchers have been able to take advantage of co-expression/co-infection are addressed, including compound structure-function studies, insect cell functionality augmentation, and VLP production. The core of the review discusses the parameters of interest for co-infection and co-expression with time of infection (TOI) and multiplicity of infection (MOI) highlighted for the former and the choice of promoter for the latter. In addition, an overview of modeling approaches is presented, with a suggested trajectory for future exploration. The review concludes with an examination of the gaps that still remain in co-expression/co-infection knowledge and practice.

Ex Output:
Co-expression vs. co-infection using baculovirus expression vectors in insect cell culture: Benefits and drawbacks


Ex Input:
Low cost, high throughput, easy quantitation, and rich descriptions have made gene expression profiling generated by DNA microarrays an optimal approach for describing host transcriptional responses (HTRs). However, efforts to characterize the landscape of HTRs to diverse pathogens are far from offering a comprehensive view. Here, we developed an HTR Connectivity Map based on systematic assessment of pairwise similarities of HTRs to 50 clinically important human pathogens using 1353 gene-expression profiles generated from >60 human cells/tissues. These 50 pathogens were further partitioned into eight robust "HTR communities" (i.e., groups with more consensus internal HTR similarities). These communities showed enrichment in specific infection attributes and differential gene expression patterns. Using query signatures of HTRs to external pathogens, we demonstrated four distinct modes of HTR associations among different pathogens types/class, and validated the reliability of the HTR community divisions for differentiating and categorizing pathogens from a host-oriented perspective. These findings provide a first-generation HTR Connectivity Map of 50 diverse pathogens, and demonstrate the potential for using annotated HTR community to detect functional associations among infectious pathogens.

Ex Output:

Inferring Infection Patterns Based on a Connectivity Map of Host Transcriptional Responses