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".

Paragraph: Metagenomics is currently the only generic method for pathogen detection. Starting from RNA allows the assessment of the whole sample community including RNA viruses. Here we present our modular concerted protocol for sample processing for diagnostic metagenomics analysis of human, animal, and food samples. The workflow does not rely on dedicated amplification steps at any stage in the process and, in contrast to published methods, libraries prepared accordingly will yield only minute amounts of unclassifiable reads. We confirmed the performance of the approach using a spectrum of pathogen/ matrix-combinations showing it has the potential to become a commonly usable analytical framework. Diagnostic metagenomics with high-throughput sequencing (HTS) techniques continuously gains importance for broad and swift identification of pathogens in human, animal, and food samples 1 . While for known pathogens, highly sensitive and specific diagnostic methods like real-time quantitative PCR (qPCR) are in routine use and deliver reliable results, the identification of unrecognized pathogens, meaning unexpected or newly emerging pathogens or pathogens that are only distantly related with known ones, can be very difficult. In this respect, metagenomics using HTS are much more promising than routine diagnostics. Unrecognized pathogens, especially newly emerging zoonoses, may cause serious infectious diseases, and a delay of medical treatment or development of vaccines might have fatal consequences for the affected patients and animal stocks. Such delays can be caused by performing numerous laborious screening tests until the potential pathogen is found instead of a single comprehensive screening test. Prominent cases of emerging infectious diseases caused by novel or varying viruses for instance are the discovery of the Middle East respiratory syndrome (MERS) coronavirus in 2012 2 , the tremendous Ebola outbreak in 2014 3 , the report on a novel zoonotic bornavirus 4 , or the detection of the new Schmallenberg virus 5 affecting domestic and wild ruminants. However, infectious diseases with clinical signs like high fever, diarrhoea, or encephalitis − often life-threatening − can be caused by very different infectious agents 6,7 , not only viruses. In such puzzling cases, a generic approach that works likewise successful and efficient for all pathogen groups, as sketched in Fig. 1 , is essential. In a number of review articles 1,8-12 , valuable considerations for this approach have been summarized. In addition to the overall workflow outlined in Fig. 1 , after metagenomic analysis, it is desirable to confirm the initial sequencing-based suspicion by other methods and in the ideal case by fulfilling the Henle-Loeffler-Koch postulates 13 as for example done in case of the Schmallenberg virus 5 . Metagenomics for generic pathogen detection, so-called diagnostic metagenomics, in its pure form is a broad and undirected approach to find gene sequences or sequence fragments of infectious agents within sequence data sets of the whole community of a sample generated by high-throughput sequencing. A crucial point when handling diagnostic sequencing approaches is to explicitly distinguish between i) high-throughput well-standardisable routine diagnostics for expected known pathogens and ii) diagnostic metagenomics for all including unrecognized pathogens. The first approach is easier to design based on the spectrum of known sequences, testing with specific oligonucleotide primers for pathogens of known identity 14,15 , known tropism, and maybe also of a known proportion within a sample. The latter one − used for unrecognized pathogens like in the case of Schmallenberg virus 5 − should be a generic approach that can ideally be applied to all samples and pathogens. This approach can indeed be developed and tested using samples of known origin and pathogen content. In case of an emergency, however, there might be no information about nature and proportion of the pathogen and only clinical data could be available, and the sample is a closed book. For these cases, metagenomics Published: xx xx xxxx OPEN www.nature.com/scientificreports/ 
 Title: A Versatile Sample Processing Workflow for Metagenomic Pathogen Detection OPEN
False

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
True

Paragraph: with the pathological structure of BPD, as seen in the lungs of preterm infants who died and in animal models (3, 7). As the authors note, this study was limited in that the subjects with BPD were stable outpatients younger than 3 years who did not require oxygen therapy at the time of the study. Whether their findings hold true in infants with persistent severe BPD, including those with chronic ventilator-dependent hypoxemic respiratory failure, is not clear. In addition, BPD classification was based on clinical decision making, rather than a physiologic assessment such as the oxygen reduction test (11). In an earlier article, members of this group studied DL CO and its components, DM and Vc, in full-term infants without lung disease and showed that DL CO and Vc (but not DM) correlated with the level of proangiogenic circulating hematopoietic stem/progenitor cells (pCHSPCs) (12). However, this study did not include preterm infants with or without BPD. Both pCHSPCs, also referred to as circulating progenitor cells, as well as late-outgrowth endothelial colony-forming cells, are decreased in the cord blood of preterm infants who later develop moderate or severe BPD (13, 14) . Together, these findings suggest that early disruptions in the number and function of angiogenic progenitor cells, possibly by maternal complications of pregnancy known to be associated with BPD risk, may lead to impaired development of the pulmonary vasculature and sustained impaired gas exchange in preterm infants with BPD. This study shows how a physiologic assessment, such as infant pulmonary function testing, may be used in the clinical setting to provide an estimation of impaired gas exchange in preterm infants with varying degrees of lung injury. Combining functional assays such as this with measurement of pCHSPCs and other angiogenic biomarkers in the cord blood, as well as novel imaging techniques such as quantitative pulmonary magnetic resonance imaging (15), will lead to improved disease phenotyping of preterm infants at risk for BPD. Given the spectrum of disease severity among infants with severe BPD (as determined by the currently accepted diagnostic criteria), novel methods such as these will help identify preterm neonates more accurately, permit targeted therapies for the most severely affected infants, and provide quantitative evidence of the efficacy of these interventions in young children after preterm birth (16). n 
 Title: Jobe AH, Bancalari E. Bronchopulmonary dysplasia

True