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

[EX Q]: The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period, in a naïve, uninfected population. It is well-known that the estimation of this number may vary due to several methodological issues, including different assumptions and choice of parameters, utilized models, used datasets and estimation period. With the spreading of the novel coronavirus (2019-nCoV) infection, the reproduction number has been found to vary, reflecting the dynamics of transmission of the coronavirus outbreak as well as the case reporting rate. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies that have been rapidly improved, enabling to shorten the time from infection/symptoms onset to diagnosis, leading to faster confirmation of the new coronavirus cases, our previous estimations on the transmission risk of the 2019-nCoV need to be revised. By using time-dependent contact and diagnose rates, we refit our previously proposed dynamics transmission model to the data available until January 29th , 2020 and re-estimated the effective daily reproduction ratio that better quantifies the evolution of the interventions. We estimated when the effective daily reproduction ratio has fallen below 1 and when the epidemics will peak. Our updated findings suggest that the best measure is persistent and strict self-isolation. The epidemics will continue to grow, and can peak soon with the peak time depending highly on the public health interventions practically implemented.
[EX A]: An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

[EX Q]: Methods We actively surveyed arriving travellers at all 272 international entry-exit ports in mainland China. Suspected cases were detected through fever screening, medical inspection, self-declaration, and reporting by on-board staff. Participants completed a standardised questionnaire with questions about demographics, their travel itinerary (including detailed information about all countries or regions visited), and clinical manifestations. Nasopharyngeal swabs, sputum samples, faecal samples, vomitus, blood, and serum were collected as appropriate for diagnoses. Diagnosis was made by specific laboratory tests according to the national technical guidelines. Infections were classified as respiratory, gastrointestinal, vector-borne, blood-transmitted and sex-transmitted, or mucocutaneous. We divided arriving travellers into two groups: travellers coming from countries other than China, and travellers coming from Hong Kong, Macau, and Taiwan. We integrated surveillance data for 2014-16, calculated incidences of travel-related infections, and compared the frequency of infections among subgroups. Findings Between Jan 1, 2014, and Dec 31, 2016, 22 797 cases were identified among 805 993 392 arriving travellersan overall incidence of 28·3 per million. 45 pathogens were detected in participants: 18 respiratory (19 662 cases), ten gastrointestinal (189 cases), seven vector-borne (831 cases), seven blood-transmitted and sex-transmitted (1531 cases), and three mucocutaneous (584 cases). Both the overall number and incidence of infection were more than five times higher in 2016 than in 2014. Case numbers and incidences also varied substantially by province, autonomous region, and municipality. Overall, 17 643 (77%) infections were detected by fever screening, but 753 (49%) blood-transmitted and sex-transmitted infections were identified through medical inspection. 14 305 (73%) cases of respiratory infection and 96 (51%) of gastrointestinal infections were in tourists. Tuberculosis, hepatitis A virus, vector-borne, and blood-transmitted and sex-transmitted infections were common among Chinese labourers who worked abroad. Dengue and malaria were most commonly diagnosed in travellers arriving from Africa. 12 126 (93%) of the 12 985 cases arriving from Hong Kong, Macau, or Taiwan were respiratory infections. Hand, foot, and mouth disease accounted for 2·90% of infections in travellers from Hong Kong, Macau, or Taiwan and 0·31% of infections in international travellers. Interpretation This report is the first to characterise the profile of travel-related infections among arriving travellers in mainland China. Our findings should increase public awareness of the potential risk of imported infections, and help health-care providers to make evidence-based health recommendations to travellers.
[EX A]:
Articles Travel-related infections in mainland China, 2014-16: an active surveillance study