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: Interleukin-11 (IL-11), a well-known anti-inflammatory factor, provides protection from intestinal epithelium damage caused by physical or chemical factors. However, little is known of the role of IL-11 during viral infections. In this study, IL-11 expression at mRNA and protein levels were found to be high in Vero cells and the jejunum of piglets during porcine epidemic diarrhea virus (PEDV) infection, while IL-11 expression was found to be positively correlated with the level of viral infection. Pretreatment with recombinant porcine IL-11 (pIL-11) was found to suppress PEDV replication in Vero E6 cells, while IL-11 knockdown promoted viral infection. Furthermore, pIL-11 was found to inhibit viral infection by preventing PEDV-mediated apoptosis of cells by activating the IL-11/STAT3 signaling pathway. Conversely, application of a STAT3 phosphorylation inhibitor significantly antagonized the anti-apoptosis function of pIL-11 and counteracted its inhibition of PEDV. Our data suggest that IL-11 is a newfound PEDV-inducible cytokine, and its production enhances the anti-apoptosis ability of epithelial cells against PEDV infection. The potential of IL-11 to be used as a novel therapeutic against devastating viral diarrhea in piglets deserves more attention and study. 
 Title: Antiviral activity of interleukin-11 as a response to porcine epidemic diarrhea virus infection
[EX A]: True

[EX Q]: Paragraph: Coronaviruses have large positive-strand RNA genomes that are 5′ capped and 3′ polyadenylated. The 5′-terminal two-thirds of the genome contain two open reading frames (ORFs), 1a and 1b, that together make up the viral replicase gene and encode two large polyproteins that are processed by viral proteases into 15-16 nonstructural proteins, most of them being involved in viral RNA synthesis. ORFs located in the 3′-terminal one-third of the genome encode structural and accessory proteins and are expressed from a set of 5′ leader-containing subgenomic mRNAs that are synthesized by a process called discontinuous transcription. Coronavirus protein synthesis not only involves cap-dependent translation mechanisms but also employs regulatory mechanisms, such as ribosomal frameshifting. Coronavirus replication is known to affect cellular translation, involving activation of stress-induced signaling pathways, and employing viral proteins that affect cellular mRNA translation and RNA stability. This chapter describes our current understanding of the mechanisms involved in coronavirus mRNA translation and changes in host mRNA translation observed in coronavirus-infected cells. 
 Title: Viral and Cellular mRNA Translation in Coronavirus-Infected Cells
[EX A]: False

[EX Q]: Paragraph: Introduction: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important predictors in models for infectious disease forecasts. Various approaches have been proposed in the literature to produce accurate and timely predictions and potentially improve public health response. Methods: We assessed how the machine learning LASSO method may be useful in providing useful forecasts for different pathogens in countries with different climates. Separate LASSO models were constructed for different disease/country/forecast window with different model complexity by including different sets of predictors to assess the importance of different predictors under various conditions. Results: There was a more apparent cyclicity for both climatic variables and incidence in regions further away from the equator. For most diseases, predictions made beyond 4 weeks ahead were increasingly discrepant from the actual scenario. Prediction models were more accurate in capturing the outbreak but less sensitive to predict the outbreak size. In different situations, climatic variables have different levels of importance in prediction accuracy. Conclusions: For LASSO models used for prediction, including different sets of predictors has varying effect in different situations. Short term predictions generally perform better than longer term predictions, suggesting public health agencies may need the capacity to respond at short-notice to early warnings. 
 Title: The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison
[EX A]:
False