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".

Example Input: Paragraph: Objective: The aim of this study was to further clarify clinical characteristics and predict mortality risk among patients with viral pneumonia. Methods: A total of 528 patients with viral pneumonia at RuiJin hospital in Shanghai from May 2015 to May 2019 were recruited. Multiplex real-time RT-PCR was used to detect respiratory viruses. Demographic information, comorbidities, routine laboratory examinations, immunological indexes, etiological detections, radiological images and treatment were collected on admission. Results: 76 (14.4%) patients died within 90 days in hospital. A predictive MuLBSTA score was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included multilobular infiltrates (OR = 5.20, 95% CI 1.41-12.52, p = 0.010; 5 points), lymphocyte ≤ 0.8 * 10 9 /L (OR = 4.53, 95% CI 2.55-8.05, p < 0.001; 4 points), bacterial coinfection (OR = 3.71, 95% CI 2.11-6.51, p < 0.001; 4 points), acute-smoker (OR = 3.19, 95% CI 1.34-6.26, p = 0.001; 3 points), quit-smoker (OR = 2.18, 95% CI 0.99-4.82, p = 0.054; 2 points), hypertension (OR = 2.39, 95% CI 1.55-4.26, p = 0.003; 2 points) and age ≥60 years (OR = 2.14, 95% CI 1.04-4.39, p = 0.038; 2 points). 12 points was used as a cut-off value for mortality risk stratification. This model showed sensitivity of 0.776, specificity of 0.778 and a better predictive ability than CURB-65 (AUROC = 0.773 vs. 0.717, p < 0.001). Conclusion: Here, we designed an easy-to-use clinically predictive tool for assessing 90-day mortality risk of viral pneumonia. It can accurately stratify hospitalized patients with viral pneumonia into relevant risk categories and could provide guidance to make further clinical decisions. 
 Title: Citation: Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score
Example Output: False

Example Input: Paragraph: Here we describe a new technical solution for optimization of Pichia pastoris shake flask cultures with the example of production of stable human type II collagen. Production of recombinant proteins in P. pastoris is usually performed by controlling gene expression with the strong AOX1 promoter, which is induced by addition of methanol. Optimization of processes using the AOX1 promoter in P. pastoris is generally done in bioreactors by fed-batch fermentation with a controlled continuous addition of methanol for avoiding methanol toxification and carbon/energy starvation. The development of feeding protocols and the study of AOX1-controlled recombinant protein production have been largely made in shake flasks, although shake flasks have very limited possibilities for measurement and control. Results: By applying on-line pO 2 monitoring we demonstrate that the widely used pulse feeding of methanol results in long phases of methanol exhaustion and consequently low expression of AOX1 controlled genes. Furthermore, we provide a solution to apply the fed-batch strategy in shake flasks. The presented solution applies a wireless feeding unit which can be flexibly positioned and allows the use of computer-controlled feeding profiles. By using the human collagen II as an example we show that a quasi-continuous feeding profile, being the simplest way of a fed-batch fermentation, results in a higher production level of human collagen II. Moreover, the product has a higher proteolytic stability compared to control cultures due to the increased expression of human collagen prolyl 4hydroxylase as monitored by mRNA and protein levels. The recommended standard protocol for methanol addition in shake flasks using pulse feeding is nonoptimal and leads to repeated long phases of methanol starvation. The problem can be solved by applying the fed-batch technology. The presented wireless feeding unit, together with an on-line monitoring system offers a flexible, simple, and low-cost solution for initial optimization of the production in shake flasks which can be performed in parallel. By this way the fed-batch strategy can be applied from the early screening steps also in laboratories which do not have access to highcost and complicated bioreactor systems. 
 Title: Improved production of human type II procollagen in the yeast Pichia pastoris in shake flasks by a wireless-controlled fed-batch system
Example Output: False

Example Input: Paragraph: Background An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95 333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced. Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January, 2020, and February, 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. To estimate the early dynamics of transmission in Wuhan, we fitted a stochastic transmission dynamic model to multiple publicly available datasets on cases in Wuhan and internationally exported cases from Wuhan. The four datasets we fitted to were: daily number of new internationally exported cases (or lack thereof), by date of onset, as of Jan 26, 2020; daily number of new cases in Wuhan with no market exposure, by date of onset, between Dec 1, 2019, and Jan 1, 2020; daily number of new cases in China, by date of onset, between Dec 29, 2019, and Jan 23, 2020; and proportion of infected passengers on evacuation flights between Jan 29, 2020, and Feb 4, 2020. We used an additional two datasets for comparison with model outputs: daily number of new exported cases from Wuhan (or lack thereof) in countries with high connectivity to Wuhan (ie, top 20 most at-risk countries), by date of confirmation, as of Feb 10, 2020; and data on new confirmed cases reported in Wuhan between Jan 16, 2020, and Feb 11, 2020. Findings We estimated that the median daily reproduction number (R t ) in Wuhan declined from 2·35 (95% CI 1·15-4·77) 1 week before travel restrictions were introduced on Jan 23, 2020, to 1·05 (0·41-2·39) 1 week after. Based on our estimates of R t , assuming SARS-like variation, we calculated that in locations with similar transmission potential to Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population. Interpretation Our results show that COVID-19 transmission probably declined in Wuhan during late January, 2020, coinciding with the introduction of travel control measures. As more cases arrive in international locations with similar transmission potential to Wuhan before these control measures, it is likely many chains of transmission will fail to establish initially, but might lead to new outbreaks eventually. 
 Title: Articles Early dynamics of transmission and control of COVID-19: a mathematical modelling study
Example Output:
True