TASK DEFINITION: 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.
PROBLEM: Background: Influenza is a zoonotic disease that infects millions of people each year resulting in hundreds of thousands of deaths, and in turn devastating pandemics. Influenza is caused by influenza viruses, including influenza A virus (IAV). There are many subtypes of IAV but only a few seem to be able to adapt to humans and to cause disease. In 2013, an H7N9 IAV subtype emerged in China that does not cause clinical symptoms in its chicken host but leads to severe infections when transmitted into humans. Since 2013, there have been six epidemic waves of H7N9 with 1567 laboratory-confirmed human infections and 615 deaths. Pathogenicity of IAV is complex, but a crucial feature contributing to virulence is the activation of the hemagglutinin (HA) fusion protein by host proteases that triggers membrane fusion and leads to subsequent virus propagation. : 293T, VERO, and MDCK cells were used to conduct Western blot analysis, immunofluorescence assays, and pseudoparticle and live virus infections, and to evaluate H7N9 HA cleavage-activation. Results/Conclusions: We show that human matriptase/ST 14 is able to cleave H7N9 HA. Cleavage of H7N9 HA expressed in cell culture results in fusogenic HA and syncytia formation. In infection studies with viral pseudoparticles carrying matriptase/ ST 14-activated H7N9 HA, we observed a high infectivity of cells. Finally, human matriptase/ST 14 also activated H7N9 live virus which resulted in high infectivity. Our data demonstrate that human matriptase/ST 14 is a likely candidate protease to promote H7N9 infections in humans.

SOLUTION: Human matriptase/ST 14 proteolytically cleaves H7N9 hemagglutinin and facilitates the activation of influenza A/Shanghai/2/2013 virus in cell culture

PROBLEM: | The ancient biological 'arms race' between microbial pathogens and humans has shaped genetic variation in modern populations, and this has important implications for the growing field of medical genomics. As humans migrated throughout the world, populations encountered distinct pathogens, and natural selection increased the prevalence of alleles that are advantageous in the new ecosystems in both host and pathogens. This ancient history now influences human infectious disease susceptibility and microbiome homeostasis, and contributes to common diseases that show geographical disparities, such as autoimmune and metabolic disorders. Using new high-throughput technologies, analytical methods and expanding public data resources, the investigation of natural selection is leading to new insights into the function and dysfunction of human biology. www.nature.com/reviews/genetics

SOLUTION: Natural selection and infectious disease in human populations

PROBLEM: Mathematical models that describe the global spread of infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) often consider a sample of international airports as a network supporting disease spread. However, there is no consensus on how many cities should be selected or on how to select those cities. Using airport flight data that commercial airlines reported to the Official Airline Guide (OAG) in 2000, we have examined the network characteristics of network samples obtained under different selection rules. In addition, we have examined different size samples based on largest flight volume and largest metropolitan populations. We have shown that although the bias in network characteristics increases with the reduction of the sample size, a relatively small number of areas that includes the largest airports, the largest cities, the most-connected cities, and the most central cities is enough to describe the dynamics of the global spread of influenza. The analysis suggests that a relatively small number of cities (around 200 or 300 out of almost 3000) can capture enough network information to adequately describe the global spread of a disease such as influenza. Weak traffic flows between small airports can contribute to noise and mask other means of spread such as the ground transportation. Citation: Bobashev G, Morris RJ, Goedecke DM (2008) Sampling for Global Epidemic Models and the Topology of an International Airport Network. PLoS ONE 3(9): e3154.

SOLUTION:
Sampling for Global Epidemic Models and the Topology of an International Airport Network