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.

Input: Consider Input: Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) was originally identified in Saudi Arabia in 2012. It has caused MERS outbreaks with high mortality in the Middle East and Europe, raising a serious concern about its pandemic potential. Therefore, development of effective vaccines is crucial for preventing its further spread and future pandemic. Our previous study has shown that subcutaneous (s.c.) vaccination of a recombinant protein containing receptor-binding domain (RBD) of MERS-CoV S fused with Fc of human IgG (RBD-Fc) induced strong systemic neutralizing antibody responses in vaccinated mice. Here, we compared local and systemic immune responses induced by RBD-Fc via intranasal (i.n.) and s.c. immunization pathways. We found that i.n. vaccination of MERS-CoV RBD-Fc induced systemic humoral immune responses comparable to those induced by s.c. vaccination, including neutralizing antibodies, but more robust systemic cellular immune responses and significantly higher local mucosal immune responses in mouse lungs. This study suggests the potential of developing MERS-CoV RBD protein into an effective and safe mucosal candidate vaccine for prevention of respiratory tract infections caused by MERS-CoV.

Output: Intranasal vaccination with recombinant receptor-binding domain of MERS-CoV spike protein induces much stronger local mucosal immune responses than subcutaneous immunization: Implication for designing novel mucosal MERS vaccines


Input: Consider Input: The development of high-throughput molecular technologies and associated bioinformatics has dramatically changed the capacities of scientists to produce, handle, and analyze large amounts of genomic, transcriptomic, and proteomic data. A clear example of this step-change is represented by the amount of DNA sequence data that can be now produced using next-generation sequencing (NGS) platforms. Similarly, recent improvements in protein and peptide separation effi ciencies and highly accurate mass spectrometry have promoted the identifi cation and quantifi cation of proteins in a given sample. These advancements in biotechnology have increasingly been applied to the study of animal infectious diseases and are beginning to revolutionize the way that biological and evolutionary processes can be studied at the molecular level. Studies have demonstrated the value of NGS technologies for molecular characterization, ranging from metagenomic characterization of unknown pathogens or microbial communities to molecular epidemiology and evolution of viral quasispecies. Moreover, high-throughput technologies now allow detailed studies of hostpathogen interactions at the level of their genomes (genomics), transcriptomes (transcriptomics), or proteomes (proteomics). Ultimately, the interaction between pathogen and host biological networks can be questioned by analytically integrating these levels (integrative OMICS and systems biology). The application of high-throughput biotechnology platforms in these fi elds and their typical low-cost per information content has revolutionized the resolution with which these processes can now be studied. The aim of this chapter is to provide a current and prospective view on the opportunities and challenges associated with the application of massive parallel sequencing technologies to veterinary medicine, with particular focus on applications that have a potential impact on disease control and management.

Output: Chapter 30 Next-Generation Sequencing in Veterinary Medicine: How Can the Massive Amount of Information Arising from High- Throughput Technologies Improve Diagnosis, Control, and Management of Infectious Diseases?


Input: Consider Input: Hospitals develop nurse schedules that cover a period of 4-6 weeks and are posted several weeks in advance. Once posted, changes to the schedule require voluntary participation by the nurses, making it difficult for hospitals to respond to changes in nursing needs and availability of nurses. At the same time, nursing needs' forecasts developed several weeks in advance are often wrong. In each hospital setting, there may exist several promising strategies to enhance scheduling flexibility and reduce the mismatch between the nursing needs and the availability of nurses. However, methodologies to evaluate such strategies, before testing them in expensive pilot implementation, do not exist. We demonstrate how such evaluations can be carried out using historical data. Furthermore, we demonstrate the use of our approach by evaluating the benefits of a strategy where nurses are divided into two cohorts and schedules are phase shifted for the two cohorts. Staggering schedules allows nursing unit managers to benefit from more frequent updating of needs' assessments without having to change work rules. Upon applying our approach to data from a large urban hospital, we discovered that in this example staggering did not improve the performance of nurse schedules. We discuss possible reasons for this result, its implications for hospital managers, and other potential uses of our approach.


Output: On evaluating the impact of flexibility enhancing strategies on the performance of nurse schedules