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".

Ex Input:
Paragraph: This paper reviews how immunomodulation through active vaccination has evolved in the past 25 years. Although initially it progressed isolated from the main stream of immunological research and vaccine development, lately it merged with this main stream and is taking full advantage of the newest developments in vaccinology. The first immunomodulation vaccine is already on the market, while various others are close to it. Not in the least because one of the major stumbling blocks of immunomodulation through active vaccination, the inherent low immunogenicity of 'self' antigens, has in a number of other cases been solved. Most progress has been made in veterinary applications and has helped to formulate practical rules, necessary to break immunotolerance. It is not unlikely that these rules will be used to design better immunomodulation vaccines to be used in humans; notably to control fertility or combat tumours. 
 Title: Basic aspects of immunomodulation through active immunization

Ex Output:
True


Ex 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

Ex Output:
False


Ex Input:
Paragraph: Rapid and accurate detection and identification of viruses causing respiratory tract infections is important for patient care and disease control. Despite the fact that several assays are available, identification of an etiological agent is not possible in ,30% of patients suffering from respiratory tract diseases. Therefore, the aim of the current study was to develop a diagnostic set for the detection of respiratory viruses with sensitivity as low as 1-10 copies per reaction. Evaluation of the assay using a training clinical sample set showed that viral nucleic acids were identified in ,76% of cases. To improve assay performance and facilitate the identification of novel species or emerging strains, cultures of fully differentiated human airway epithelium were used to pre-amplify infectious viruses. This additional step resulted in the detection of pathogens in all samples tested. Based on these results it can be hypothesized that the lack of an etiological agent in some clinical samples, both reported previously and observed in the present study, may result not only from the presence of unknown viral species, but also from imperfections in the detection methods used. 
 Title: Use of Sensitive, Broad-Spectrum Molecular Assays and Human Airway Epithelium Cultures for Detection of Respiratory Pathogens

Ex Output:

True