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".

Q: Paragraph: • The M2 protein of influenza A is a proton-gated proton channel that is required for viral replication • Current influenza strains are resistant to licensed M2 antivirals, so new therapies that target M2 are needed • The structure and function of M2, rise of drug resistance mutations, and current antiviral strategies are discussed The ongoing threat of seasonal and pandemic influenza to human health requires antivirals that can effectively supplement existing vaccination strategies. The M2 protein of influenza A virus (IAV) is a proton-gated, proton-selective ion channel that is required for virus replication and is an established antiviral target. While licensed adamantane-based M2 antivirals have been historically used, M2 mutations that confer major adamantane resistance are now so prevalent in circulating virus strains that these drugs are no longer recommended. Here we review the current understanding of IAV M2 structure and function, mechanisms of inhibition, the rise of drug resistance mutations, and ongoing efforts to develop new antivirals that target resistant forms of M2. 
 Title: Journal Pre-proof Put a cork in it: Plugging the M2 viral ion channel to sink influenza Put a cork in it: Plugging the M2 viral ion channel to sink influenza

A: False
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Q: 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

A: False
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Q: Paragraph: Background: The New Zealand (NZ) Government has made a strong commitment to reduce the incidence of rheumatic fever (RF) by two thirds, to 1.4 cases per 100,000, by mid-2017. We reviewed the NZ RF surveillance sector, aiming to identify potential improvements which would support optimal RF control and prevention activities. Methods: This review used a recently developed surveillance sector review method. Interviews with 36 key informants were used to describe the sector, assess it and identify its gaps. Priorities for improvement and implementation strategies were determined following discussion with these key informants, with policy advisors and within the research team. Results: Key improvements identified included the need for a comprehensive RF surveillance strategy, integrated reporting and an online national RF register. At a managerial level this review provided evidence for system change and built support for this across the surveillance sector. Conclusions: The surveillance sector review approach can be added to the small set of tools currently available for developing and evaluating surveillance systems. This new approach is likely to prove useful as we confront the challenges of combating new emerging infectious diseases, responding to global environmental changes, and reducing health inequalities. 
 Title: Improving rheumatic fever surveillance in New Zealand: results of a surveillance sector review

A:
False
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