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 Q]: We describe the first genome isolation of Middle East respiratory syndrome coronavirus (MERS-CoV) in Kenya. This fatal zoonotic pathogen was first described in the Kingdom of Saudi Arabia in 2012. Epidemiological and molecular evidence revealed zoonotic transmission from camels to humans and between humans. Currently, MERS-CoV is classified by the WHO as having high pandemic potential requiring greater surveillance. Previous studies of MERS-CoV in Kenya mainly focused on site-specific and archived camel and human serum samples for antibodies. We conducted active nationwide cross-sectional surveillance of camels and humans in Kenya, targeting both nasal swabs and plasma samples from 1,163 camels and 486 humans collected from January 2016 to June 2018. A total of 792 camel plasma samples were positive by ELISA. Seroprevalence increased with age, and the highest prevalence was observed in adult camels (82.37%, 95% confidence interval (CI) 79.50-84.91). More female camels were significantly seropositive (74.28%, 95% CI 71.14-77.19) than male camels (P \ 0.001) (53.74%, 95% CI 48.48-58.90). Only 11 camel nasal swabs were positive for MERS-CoV by reverse transcription-quantitative PCR. Phylogenetic analysis of whole genome sequences showed that Kenyan MERS-CoV clustered within sub-clade C2, which is associated with the African clade, but did not contain signature deletions of orf4b in African viruses. None of the human plasma screened contained neutralizing antibodies against MERS-CoV. This study confirms the geographically widespread occurrence of MERS-CoV in Kenyan camels. Further one-health surveillance approaches in camels, wildlife, and human populations are needed.
[EX A]: Genetic Evidence of Middle East Respiratory Syndrome Coronavirus (MERS-Cov) and Widespread Seroprevalence among Camels in Kenya

[EX Q]: Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community.
[EX A]: Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

[EX Q]: Severe acute respiratory syndrome-coronavirus (SARS-CoV) causes an infectious disease through respiratory route. Diagnosing the disease effectively and accurately at early stage is essential for preventing the disease transmission and performing antiviral treatment. In this study, we raised monoclonal antibodies (mAbs) against the nucleocapsid (N) protein of SARS-CoV and mapped epitopes by using different truncated N protein fragments. The mapping of those epitopes was valuable for constructing pair-Abs used in serological diagnosis. The results showed that all of the six raised mAbs were divided into two groups recognizing the region of amino acids 249-317 (A group) or 317-395 (B group). This region spanning amino acids 249-395 contains predominant B cell epitopes located at the C-terminus of N protein. One pair-Abs, consisting of N protein-specific rabbit polyclonal antibody and SARS-CoV N protein-specific mAb, was selected to construct a sandwich ELISA-kit. The kit was able to specifically detect SARS-CoV N proteins in serum samples.
[EX A]:
Characterization and application of monoclonal antibodies against N protein of SARS-coronavirus