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".

Input: Consider Input: Paragraph: Baculovirus has been widely used for the production of recombinant proteins in insect cells. Since the finding that baculovirus can efficiently transduce mammalian cells, the applications of baculovirus have been greatly expanded. The prospects and drawbacks of baculovirus-mediated gene expression, either in insect or in mammalian cells, are reviewed. Recent progresses in expanding the applications to studies of gene regulation, viral vector preparation, in vivo and ex vivo gene therapy studies, generation of vaccine vectors, etc are discussed and the efforts directed towards overcoming the existing bottlenecks are particularly emphasized. 
 Title: Baculovirus as a highly efficient expression vector in insect and mam- malian cells

Output: False


Input: Consider Input: Paragraph: Although Middle East respiratory syndrome coronavirus (MERS-CoV) has a recorded 5 years of circulation in 27 countries worldwide, there is no international study to assess whether there is variation in mortality by region. Neither has there been a comprehensive study detailing how the disease characteristics of MERS-CoV influence mortality in patients presenting symptoms. This study aimed to assess how region, patient and disease characteristics influence 14-and 45-day mortality in MERS patients. The author utilised publically available data on MERS-CoV. The study included 883 MERS patients reported between 5 January 2015 and 10 March 2017. Data on patient and disease characteristics were collected. The mean age at MERS-CoV diagnosis was 54.3 years: 69.1% were male, and 86.7% of the cases were reported from Saudi Arabia. About 40% of MERS patients studied were over the age of 60. The study estimated 14-and 45-day survival rates after initial onset of symptoms: 83.67% and 65.9%, respectively. Saudi Arabian MERS patients exhibited 4.1 and 5.0 times higher 14-day (adjusted hazard risk (aHR) = 4.1; 95% confidence interval (CI) 1.012-16.921) and 45-day (aHR = 5.0; 95% CI 1.856-13.581) mortality risk compared with MERS patients in the Republic of Korea or other countries. Similarly, Middle Eastern MERS patients showed 5.3 and 4.1 times higher 14-day (aHR = 5.3; 95% CI 1.070-25.902) and 45-day (aHR = 4.1; 95% CI 1.288-113.076) mortality risk compared with MERS patients in the Republic of Korea or other countries. The results demonstrated a link between mortality and geography, disease and patient factors such as regions, symptoms, source of infections, underlying medical conditions, modes of transmission, non-healthcare workers and those of older age. Educational programmes, access to healthcare and early diagnosis could be implemented as modifiable factors to reduce the higher mortality rates in MERS patients. 
 Title: Epidemiology and Infection Estimating survival rates in MERS-CoV patients 14 and 45 days after experiencing symptoms and determining the differences in survival rates by demographic data, disease characteristics and regions: a worldwide study

Output: False


Input: Consider Input: Paragraph: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe acute respiratory illness with a case fatality rate (CFR) of 35,5%. The highest number of MERS-CoV cases are from Saudi-Arabia, the major worldwide hotspot for this disease. In the absence of neither effective treatment nor a ready-to-use vaccine and with yet an incomplete understanding of its epidemiological cycle, prevention and containment measures can be derived from mathematical models of disease epidemiology. We constructed 2-strain models to predict past outbreaks in the interval 2012-2016 and derive key epidemiological information for Macca, Madina and Riyadh. We approached variability in infection through three different disease incidence functions capturing social behavior in response to an epidemic (e.g. Bilinear, BL; Non-monotone, NM; and Saturated, SAT models). The best model combination successfully anticipated the total number of MERS-CoV clinical cases for the 2015-2016 season and accurately predicted both the number of cases at the peak of seasonal incidence and the overall shape of the epidemic cycle. The evolution in the basic reproduction number (R 0 ) warns that MERS-CoV may easily take an epidemic form. The best model correctly captures this feature, indicating a high epidemic risk (1�R 0 �2,5) in Riyadh and Macca and confirming the alleged co-circulation of more than one strain. Accurate predictions of the future MERS-CoV peak week, as well as the number of cases at the peak are now possible. These results indicate public health agencies should be aware that measures for strict containment are urgently needed before new epidemics take off in the region. There is currently no way to anticipate MERS-CoV epidemic outbreaks and strategies for disease prediction and containment are largely undermined by the limited knowledge of its epidemiological cycle. Not an effective treatment nor a vaccine for MERS-CoV exist to date. Instead, using three two-strain mathematical models that incorporate human social behavior as different disease incidence functions (e.g. bilinear, non-monotone and PLOS Neglected Tropical Diseases | https://doi. 
 Title: A realistic two-strain model for MERS-CoV infection uncovers the high risk for epidemic propagation


Output: True