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.

Example Input: The coronavirus avian Infectious bronchitis virus (IBV) poses economic threats to poultry farms worldwide, affecting the performance of both meat-type and egg-laying birds. To define the evolution of recent IBVs in Iran, a genetic analysis based on hypervariable nucleotide sequences of S1 gene was carried out. Tracheal swab samples were collected from 170 Broiler flocks during 2017. Ten tracheal swabs from each flock pooled. From a total number of 170 flocks tested, 84.71% found to be positive. Phylogenetic tree analysis revealed the presence of D274 as a first time in Iran. IS/1494/06 was showed to be dominant IBV type circulating in broiler farms with a significantly higher prevalence than other four genotypes. Considering fluctuations in QX-type prevalence in recent years, continuous monitoring is necessary to reduce economic consequences in layer and broiler farms. The findings highlight the importance of using modified vaccination strategies that are adapted to the changing disease scenario.
Example Output: Genotyping of avian infectious bronchitis virus in Iran: Detection of D274 and changing in the genotypes rate

Example Input: Keywords: interferon, interferon-stimulated genes, tumor necrosis factor-related apoptosis-inducing ligand, acute lung injury, innate immunity, influenza, respiratory syncytial virus, coronavirus FiGURe 1 | PRRs and their downstream signaling pathways in virus-induced iFN induction. In viral infection, type I IFNs are induced by TLR, RLR, CLR, and cytosolic nucleic acid sensors. Cell membrane-located TLRs ligate to viral envelope proteins (e.g., TLR2/herpes simplex virus), upon which they recruit MyD88. MyD88 interacts with IRAK kinase (IRAK-1, -2, or -4) that either directly activate IRF1 or interact with TRAF6, which induces IRF7 or assembles with TAK1. TAK1 forms a complex with TAB-1/-2 and -3 and subsequently either activates the MAPK kinases p38 and JNK, leading to AP-1 phosphorylation and nuclear translocation, or induces ubiquitination of NEMO followed by IκB degradation and NFκB activation. Endosomal TLRs recognizing viral nucleic acid and signal via the adaptor protein MyD88 (for TLR7/8/9) or interact with TRIF (for TLR3) followed by TRAF3, TANK, and TBK1 activation. TBK1 and IKKε then phosphorylate and activate IRF3 and IRF7. Additionally, TRIF can interact with TRAF6 to initiate TAK1 signaling. Both RLRs, RIG-I and MDA-5, recognize nucleic acid contents in the cytoplasm and stimulate the mitochondrial anchored IPS-1 for dimerization followed by TRADD recruitment that acts via TRAF3 on IRF3 and IRF7. Additionally, IPS-1 can interact with FADD and RIP1 to activate NFκB via IKK activated by caspase-8 and -10. Also PKR signaling results in NFκB activation and nuclear translocation. The dsDNA sensor cGAS produces cGAMP that activates ER-located STING that via TBK1 induces IRF3 translocation and type I IFN production. CLRs play a minor role in viral recognition; however, DC-SIGN activates the small GTPase Ras and Raf protein kinase, followed by NFκB activation. Type III IFN are induced by TLR3, TLR9, and via RIG-I and peroxisomal-resident IPS-1. Especially IRF1, but also NFκB, IRF3, and IRF7 are implicated in IFN-λ production, with the latter being stabilized by Med23.
Example Output: The impact of the interferon/TNF- Related Apoptosis-inducing Ligand Signaling Axis on Disease Progression in Respiratory viral infection and Beyond

Example Input: Background: Extraordinary infection control measures limited access to medical care in the Greater Toronto Area during the 2003 Severe Acute Respiratory Syndrome (SARS) outbreak. The objective of this study was to determine if the period of these infection control measures was associated with changes in overall population mortality due to causes other than SARS. Methods: Observational study of death registry data, using Poisson regression and interrupted time-series analysis to examine all-cause mortality rates (excluding deaths due to SARS) before, during, and after the SARS outbreak. The population of Ontario was grouped into the Greater Toronto Area (N = 2.9 million) and the rest of Ontario (N = 9.3 million) based upon the level of restrictions on delivery of clinical services during the SARS outbreak. : There was no significant change in mortality in the Greater Toronto Area before, during, and after the period of the SARS outbreak in 2003 compared to the corresponding time periods in 2002 and 2001. The rate ratio for all-cause mortality during the SARS outbreak was 0.99 [95% Confidence Interval (CI) 0.93-1.06] compared to 2002 and 0.96 [95% CI 0.90-1.03] compared to 2001. An interrupted time series analysis found no significant change in mortality rates in the Greater Toronto Area associated with the period of the SARS outbreak. Conclusion: Limitations on access to medical services during the 2003 SARS outbreak in Toronto had no observable impact on short-term population mortality. Effects on morbidity and long-term mortality were not assessed. Efforts to contain future infectious disease outbreaks due to influenza or other agents must consider effects on access to essential health care services.
Example Output:
Address: 1 Centre for Research on Inner City Health, the Keenan Research Centre in the Li Ka Shing Knowledge