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".

[EX Q]: Paragraph: In Sindbis, Venezuelan equine encephalitis and related alphaviruses, the polymerase is translated as a fusion with other non-structural proteins via readthrough of a UGA stop codon. Surprisingly, earlier work reported that the signal for efficient readthrough comprises a single cytidine residue 3 0 -adjacent to the UGA. However, analysis of variability at synonymous sites revealed strikingly enhanced conservation within the $150 nt 3 0 -adjacent to the UGA, and RNA folding algorithms revealed the potential for a phylogenetically conserved stem-loop structure in the same region. Mutational analysis of the predicted structure demonstrated that the stem-loop increases readthrough by up to 10-fold. The same computational analysis indicated that similar RNA structures are likely to be relevant to readthrough in certain plant virus genera, notably Furovirus, Pomovirus, Tobravirus, Pecluvirus and Benyvirus, as well as the Drosophilia gene kelch. These results suggest that 3 0 RNA stimulatory structures feature in a much larger proportion of readthrough cases than previously anticipated, and provide a new criterion for assessing the large number of cellular readthrough candidates that are currently being revealed by comparative sequence analysis. 
 Title: Stimulation of stop codon readthrough: frequent presence of an extended 3 0 RNA structural element
[EX A]: False

[EX Q]: Paragraph: Primary human airway epithelial cell (hAEC) cultures represent a universal platform to propagate respiratory viruses and characterize their host interactions in authentic target cells. To further elucidate specific interactions between human respiratory viruses and important host factors in the airway epithelium, it is important to make hAEC cultures amenable to genetic modification. However, the short and finite lifespan of primary cells in cell culture creates a bottleneck for the genetic modification of these cultures. In the current study, we show that the incorporation of the Rho-associated protein kinase (ROCK) inhibitor (Y-27632) during cell propagation extends the life span of primary human cells in vitro and thereby facilitates the incorporation of lentivirus-based expression systems. Using fluorescent reporters for fluorescence-activated cell sorting (FACS)-based sorting, we generated homogenously fluorescent hAEC cultures that differentiate normally after lentiviral transduction. As a proof-of-principle, we demonstrate that host gene expression can be modulated post-differentiation via inducible short hairpin (sh)RNA-mediated knockdown. Importantly, functional characterization of these transgenic hAEC cultures with exogenous poly (I:C), as a proxy for virus infection, demonstrates that such modifications do not influence the host innate immune response. Moreover, the propagation kinetics of both human coronavirus 229E (HCoV-229E) and human respiratory syncytial virus (hRSV) were not affected. Combined, these results validate our newly established protocol for the genetic modification of hAEC cultures, thereby unlocking a unique potential for detailed molecular characterization of virus-host interactions in human respiratory epithelium. 
 Title: Establishment of Primary Transgenic Human Airway Epithelial Cell Cultures to Study Respiratory Virus-Host Interactions
[EX A]: False

[EX Q]: Paragraph: Over the past few decades, global metapopulation epidemic simulations built with worldwide air-transportation data have been the main tool for studying how epidemics spread from the origin to other parts of the world (e.g., for pandemic influenza, SARS, and Ebola). However, it remains unclear how disease epidemiology and the air-transportation network structure determine epidemic arrivals for different populations around the globe. Here, we fill this knowledge gap by developing and validating an analytical framework that requires only basic analytics from stochastic processes. We apply this framework retrospectively to the 2009 influenza pandemic and 2014 Ebola epidemic to show that key epidemic parameters could be robustly estimated in real-time from public data on local and global spread at very low computational cost. Our framework not only elucidates the dynamics underlying global spread of epidemics but also advances our capability in nowcasting and forecasting epidemics. 
 Title: Characterizing the dynamics underlying global spread of epidemics
[EX A]:
True