instruction:
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".
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Paragraph: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is one of the major threats to the healthcare systems in some countries, especially in the Arabian Peninsula. MERS-CoV is considered an ideal example of the One Health concept. This is due to the animals, especially dromedary camels, play important roles in the transmission and sustainability of the virus, and the virus can be transmitted through aerosols of infected patients into the environment. However, there is some debate regarding the origin of MERS-CoV either from bats or other unknown reservoirs. The dromedary camel is the only identified animal reservoir to date. These animals play important roles in sustaining the virus in certain communities and may act as an amplifier of the virus by secreting it in their body fluids, especially in nasal and rectal discharges. MERS-CoV has been detected in the nasal and rectal secretions of infected camels, and MERS-CoV of this origin has full capacity to infect human airway epithelium in both in vitro and in vivo models. Other evidence confirms the direct transmission of MERS-CoV from camels to humans, though the role of camel meat and milk products has yet to be well studied. Human-to-human transmission is well documented through contact with an active infected patient or some silently infected persons. Furthermore, there are some significant risk factors of individuals in close contact with a positive MERS-CoV patient, including sleeping in the same patient room, removing patient waste (urine, stool, and sputum), and touching respiratory secretions from the index case. Outbreaks within family clusters have been reported, whereby some blood relative patients were infected through their wives in the same house were not infected. Some predisposing genetic factors favor MERS-CoV infection in some patients, which is worth investigating in the near future. The presence of other comorbidities may be another factor. Overall, there are many unknown/confirmed aspects of the virus/human/animal network. Here, the most recent advances in this context are discussed, and the possible reasons behind the emergence and sustainability of MERS-CoV in certain regions are presented. Identification of the exact mechanism of transmission of MERS-CoV from camels to humans and searching for new reservoir/s are of high priority. This will reduce the shedding of the virus into the environment, and thus the risk of human infection can be mitigated. 
 Title: Middle East Respiratory Syndrome Coronavirus and the One Health concept
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False


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Paragraph: The replicase of mouse hepatitis virus strain JHM (MHV-JHM) is encoded by two overlapping open reading frames, ORF1a and ORF1b, which are translated to produce a 750-kDa precursor polyprotein. The polyprotein is proposed to be processed by viral proteinases to generate the functional replicase complex. To date, only the MHV-JHM amino-terminal proteins p28 and p72, which is processed to p65, have been identified. To further elucidate the biogenesis of the MHV-JHM replicase, we cloned and expressed five regions of ORF1a in bacteria and prepared rabbit antisera to each region. Using the immune sera to immunoprecipitate radiolabeled proteins from MHV-JHM infected cells, we determined that the MHV-JHM ORF1a is initially processed to generate p28, p72, p250, and p150. Pulse±chase analysis revealed that these intermediates are further processed to generate p65, p210, p40, p27, the MHV 3C-like proteinase, and p15. A putative replicase complex consisting of p250, p210, p40, p150, and a large protein (Ͼ300 kDa) coprecipitate from infected cells disrupted with NP-40, indicating that these proteins are closely associated even after initial proteolytic processing. Immunofluorescence studies revealed punctate labeling of ORF1a proteins in the perinuclear region of infected cells, consistent with a membrane-association of the replicase complex. Furthermore, in vitro transcription/translation studies of the MHV-JHM 3Cpro and flanking hydrophobic domains confirm that 3C protease activity is significantly enhanced in the presence of canine microsomal membranes. Overall, our results demonstrate that the MHV-JHM ORF1a polyprotein: (1) is processed into more than 10 protein intermediates and products, (2) requires membranes for efficient biogenesis, and (3) is detected in discrete membranous regions in the cytoplasm of infected cells. 
 Title: Processing of the Coronavirus MHV-JHM Polymerase Polyprotein: Identification of Precursors and Proteolytic Products Spanning 400 Kilodaltons of ORF1a
answer:
False


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Paragraph: Health planners use forecasts of key metrics associated with influenza-like illness (ILI); near-term weekly incidence, week of season onset, week of peak, and intensity of peak. Here, we describe our participation in a weekly prospective ILI forecasting challenge for the United States for the 2016-17 season and subsequent evaluation of our performance. We implemented a metapopulation model framework with 32 model variants. Variants differed from each other in their assumptions about: the force-of-infection (FOI); use of uninformative priors; the use of discounted historical data for not-yet-observed time points; and the treatment of regions as either independent or coupled. Individual model variants were chosen subjectively as the basis for our weekly forecasts; however, a subset of coupled models were only available part way through the season. Most frequently, during the 2016-17 season, we chose; FOI variants with both school vacations and humidity terms; uninformative priors; the inclusion of discounted historical data for not-yet-observed time points; and coupled regions (when available). Our near-term weekly forecasts substantially over-estimated incidence early in the season when coupled models were not available. However, our forecast accuracy improved in absolute terms and relative to other teams once coupled solutions were available. In retrospective analysis, we found that the 2016-17 season was not typical: on average, coupled models performed better when fit without historically augmented data. Also, we tested a simple ensemble model for the 2016-17 season and found that it underperformed our subjective choice for all forecast targets. In this study, we were able to improve accuracy during a prospective forecasting exercise by coupling dynamics between regions. Although reduction of forecast subjectivity should be a long-term goal, some degree of human intervention is likely to improve forecast accuracy in the mediumterm in parallel with the systematic consideration of more sophisticated ensemble approaches. It is estimated that there are between 3 and 5 million worldwide annual seasonal cases of severe influenza illness, and between 290 000 and 650 000 respiratory deaths. Influenzalike illness (ILI) describes a set of symptoms and is a practical way for health-care workers PLOS Computational Biology | https://doi.to easily estimate likely influenza cases. The Centers for Disease Control and Prevention (CDC) collects and disseminates ILI information, and has, for the last several years, run a forecasting challenge (the CDC Flu Challenge) for modelers to predict near-term weekly incidence, week of season onset, week of peak, and intensity of peak. We have developed a modeling framework that accounts for a range of mechanisms thought to be important for influenza transmission, such as climatic conditions, school vacations, and coupling between different regions. In this study we describe our forecast procedure for the 2016-17 season and highlight which features of our models resulted in better or worse forecasts. Most notably, we found that when the dynamics of different regions are coupled together, the forecast accuracy improves. We also found that the most accurate forecasts required some level of forecaster interaction, that is, the procedure could not be completely automated without a reduction in accuracy. Influenza forecasting PLOS Computational Biology | https://doi. 
 Title: Forecasting national and regional influenza- like illness for the USA
answer:

True