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: 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

Output: True


Input: Consider Input: Paragraph: Background 3 In silico bacterial, viral, and human truth datasets were generated to evaluate available metagenomics 4 algorithms. Sequenced datasets include background organisms, creating ambiguity in the true 5 source organism for each read. Bacterial and viral datasets were created with even and staggered 6 coverage to evaluate organism identification, read mapping, and gene identification capabilities of 7 available algorithms. These truth datasets are provided as a resource for the development and 8 refinement of metagenomic algorithms. Algorithm performance on these truth datasets can inform 9 decision makers on strengths and weaknesses of available algorithms and how the results may be best 10 leveraged for bacterial and viral organism identification and characterization. 11 12 Source organisms were selected to mirror communities described in the Human Microbiome Project as 13 well as the emerging pathogens listed by the National Institute of Allergy and Infectious Diseases. The 14 six in silico datasets were used to evaluate the performance of six leading metagenomics algorithms: 15 MetaScope, Kraken, LMAT, MetaPhlAn, MetaCV, and MetaPhyler. 16 Results Algorithms were evaluated on runtime, true positive organisms identified to the genus and species 19 levels, false positive organisms identified to genus and species level, read mapping, relative abundance 20 estimation, and gene calling. No algorithm out performed the others in all categories, and the 21 algorithm or algorithms of choice strongly depends on analysis goals. MetaPhlAn excels for bacteria 22 and LMAT for viruses. The algorithms were ranked by overall performance using a normalized 23 weighted sum of the above metrics, and MetaScope emerged as the overall winner, followed by Kraken 24 and LMAT. 25 Conclusions 27 Simulated FASTQ datasets with well--characterized truth data about microbial community composition 28 reveal numerous insights about the relative strengths and weaknesses of the metagenomics algorithms 29 evaluated. The simulated datasets are available to download from the Sequence Read Archive 30 (SRP062063). 31 32 
 Title: Evaluating performance of metagenomic characterization algorithms using in silico datasets generated with FASTQSim

Output: False


Input: Consider Input: Paragraph: pediatric patients admitted to hospital because of acute respiratory infections were examined for presence of respiratory viruses by either direct fluorescent staining using monoclonal antibodies or RT-PCR during three consecutive winter-spring seasons. On the whole, 336 (42%) patients were detected as positive for one or more respiratory viruses. The most widely circulating virus was human respiratory syncytial virus (hRSV) infecting 50% of positive patients, followed by human metapneumovirus (hMPV) found in 13% of patients, and then by influenza virus type A, human parainfluenzaviruses and coinfections. Significant variations in the circulation rate of hRSV, hMPV and influenzavirus type A were observed during the individual seasons. In addition, the circulation rates of the different types of hMPV changed yearly. In 2001 hMPV circulated at a significant lower proportion than hRSV, while in 2003-2004 the circulation rates of the two viruses were closer. In conclusion, the 4 hMPV subtypes circulated yearly in Northern Italy flanking hRSV as major respiratory pathogens in the infantile patient population. * Human metapneumovirus (hMPV), the most recently identified human respiratory viral pathogen [17] along with the new human coronaviruses (hCoVs) Sars-CoV, NL63 and New Haven virus [6, 21] , is the etiologic agent of upper and lower respiratory tract infections in both the immunocompetent and the immunocompromised hosts [1, 4, 5, 7, 11, 20, 22] . In particular, infants and 2366 G. Gerna et al. 
 Title: Changing circulation rate of human metapneumovirus strains and types among hospitalized pediatric patients during three consecutive winter-spring seasons Brief Report


Output: True