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: Very limited evidence has been reported on host T cell responses to the pandemic H1N1 swine-origin influenza A virus (S-OIV) infection in humans. Therefore, we investigated the proportions of peripheral T cell subsets and analyzed the relationship of T helper subset changes with T cell activation during this infection. We found that these S-OIV-infected patients exhibited rapid lymphopenia, T cell activation and preferential loss of Th17 subset at the early stage of acute infection. Statistical analysis indicated that CD4 depletion and loss of Th17 cells, rather than Th1 or Treg cells, were correlated with CD4 T cell activation. More importantly, upregulated IFN- likely contributed to the functional loss of Th17 cells. Thus, rapidly generalized lymphopenia, preferential loss of Th17 population and T cell activation presented as characteristics of the early immune response in S-OIV-infected patients. These findings, therefore, may be helpful for an earlier diagnosis and further studies of immune pathogenesis of S-OIV infection.
Title: Preferential loss of Th17 cells is associated with CD4 T cell activation in patients with 2009 pandemic H1N1 swine-origin influenza A infection
Example Output: True

Example Input: Paragraph: Brazzein protein comes from an edible fruit, which has a long history of being a staple in the local human diet in Africa. The attractive features of brazzein as a potential commercial sweetener include its small size (53 amino acid residues), its stability over wide ranges of temperature and pH, and the similarity of its sweetness to sucrose. Heterologous production of brazzein is complicated by the fact that the protein contains four disulfide bridges and requires a specific N-terminal sequence. Our previous protocol for producing the protein from Escherichia coli involved several steps with low overall yield: expression as a fusion protein, denaturation and renaturation, oxidation of the cysteines, and cleavage by cyanogen bromide at an engineered methionine adjacent to the desired N-terminus. The new protocol described here, which is much faster and leads to a higher yield of native protein, involves the production of brazzein in E. coli as a fusion with SUMO. The isolated protein product contains the brazzein domain folded with correct disulfide bonds formed and is then cleaved with a specific SUMO protease to liberate native brazzein. This protocol represents an important advancement that will enable more efficient research into the interaction between brazzein and the receptor as well as investigations to test the potential of brazzein as a commercially viable natural low calorie sweetener.
Title: Efficient and rapid protein expression and purification of small high disulfide containing sweet protein brazzein in E. coli
Example Output: True

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 235 (95% CI 115-477) 1 week before travel restrictions were introduced on Jan 23, 2020, to 105 (041-239) 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