In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

[Q]: Paragraph: The spread of the COVID-19 caused by the SARS-CoV-2 outbreak has been growing since its first identification in December 2019. The publishing of the first SARS-CoV-2 genome made a valuable source of data to study the details about its phylogeny, evolution, and interaction with the host. Protein-protein binding assays have confirmed that Angiotensin-converting enzyme 2 (ACE2) is more likely to be the cell receptor via which the virus invades the host cell. In the present work, we provide an insight into the interaction of the viral spike Receptor Binding Domain (RBD) from different coronavirus isolates with host ACE2 protein. By calculating : bioRxiv preprint 2 the binding energy between RBD and ACE2, we highlighted the putative jump in the affinity from a progenitor form of SARS-CoV-2 to the current virus responsible for COVID-19 outbreak. Our result was consistent with the phylogeny analysis and corroborates the opinion that the interface segment of the spike protein RBD might be acquired by SARS-CoV-2 via a complex evolutionary process rather than mutation accumulation. We also highlighted the relevance of Q493 and P499 amino acid residues of SARS-CoV-2 RBD for binding to hACE2 and maintaining the stability of the interface. Moreover, we show from the structural analysis that it is unlikely for the interface residues to be the result of human engineering. Finally, we studied the impact of eight different variants located at the interaction surface of ACE2, on the complex formation with SARS-CoV-2 RBD. We found that none of them is likely to disrupt the interaction with the viral RBD of SARS-CoV-2.
Title: Interaction of the spike protein RBD from SARS-CoV-2 with ACE2: similarity with SARS-CoV, hot-spot analysis and effect of the receptor polymorphism
[A]: False

[Q]: Paragraph: Newcastle disease (ND) is a contagious disease that affects most species of birds. Its causative pathogen, Newcastle disease virus (NDV), also exhibits considerable oncolytic activity against mammalian cancers. A better understanding of the pathogenesis of NDV will help us design efficient vaccines and novel anticancer strategies. GW3965, a widely used synthetic ligand of liver X receptor (LXR), induces the expression of LXRs and its downstream genes, including ATP-binding cassette transporter A1 (ABCA1). ABCA1 regulates cellular cholesterol homeostasis. Here, we found that GW3965 inhibited NDV infection in DF-1 cells. It also inhibited NF-jB activation and reduced the upregulation of proinflammatory cytokines induced by the infection. Further studies showed that GW3965 exerted its inhibitory effects on virus entry and replication. NDV infection increased the mRNA levels of several lipogenic genes but decreased the ABCA1 mRNA level. Overexpression of ABCA1 inhibited NDV infection and reduced the cholesterol content in DF-1 cells, but when the cholesterol was replenished, NDV infection was restored. GW3965 treatment prevented cholesterol accumulation in the perinuclear area of the infected cells. In summary, our studies suggest that GW3965 inhibits NDV infection, probably by affecting cholesterol homeostasis.
Title: The LXR ligand GW3965 inhibits Newcastle disease virus infection by affecting cholesterol homeostasis
[A]: True

[Q]: Paragraph: Airports are important drivers of economic development and thus under tremendous pressure from emerging competitors. However, few studies have analysed the operational efficiency of AsiaePacific airports. This study therefore evaluated the operational efficiency of 21 AsiaePacific airports between 2002 and 2011. A two-stage method was used: Data Envelopment Analysis (DEA) to assess airport efficiency, followed by the second-stage regression analysis to identify the key determinants of airport efficiency. The first-stage DEA results indicated that Adelaide, Beijing, Brisbane, Hong Kong, Melbourne, and Shenzhen are the efficient airports. The second-stage regression analysis suggested that percentage of international passengers handled by an airport, airport hinterland population size, dominant airline(s) of an airport when entering global airline strategic alliance, and an increase in GDP per capita are significant in explaining variations in airport efficiency.
Title: Operational efficiency of AsiaePacific airports
[A]:
True