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: 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

Ex Output:
False

Ex Input:
Paragraph: During viral entry, enveloped viruses require the fusion of their lipid envelope with host cell membranes. For coronaviruses, this critical step is governed by the virally-encoded spike (S) protein, a class I viral fusion protein that has several unique features. Coronavirus entry is unusual in that it is often biphasic in nature, and can occur at or near the cell surface or in late endosomes. Recent advances in structural, biochemical and molecular biology of the coronavirus S protein has shed light on the intricacies of coronavirus entry, in particular the molecular triggers of coronavirus S-mediated membrane fusion. Furthermore, characterization of the coronavirus fusion peptide (FP), the segment of the fusion protein that inserts to a target lipid bilayer during membrane fusion, has revealed its particular attributes which imparts some of the unusual properties of the S protein, such as Ca 2+ -dependency. These unusual characteristics can explain at least in part the biphasic nature of coronavirus entry. In this review, using severe acute respiratory syndrome coronavirus (SARS-CoV) as model virus, we give an overview of advances in research on the coronavirus fusion peptide with an emphasis on its role and properties within the biological context of host cell entry.
Title: Physiological and molecular triggers for SARS-CoV membrane fusion and entry into host cells

Ex Output:
True

Ex Input:
Paragraph: The Golgi apparatus and its resident proteins are utilized and regulated by viruses to facilitate their proliferation. In this study, we investigated Classical swine fever virus (CSFV) proliferation when the function of the Golgi was disturbed. Golgi function was disturbed using chemical inhibitors, namely, brefeldin A (BFA) and golgicide A (GCA), and RNA interfering targets, such as the Golgi-specific BFA-resistance guanine nucleotide exchange factor 1 (GBF1) and Rab2 GTPases. CSFV proliferation was significantly inhibited during RNA replication and viral particle generation after BFA and GCA treatment. CSFV multiplication dynamics were retarded in cells transfected with GBF1 and Rab2 shRNA. Furthermore, CSFV proliferation was promoted by GBF1 and Rab2 overexpression using a lentiviral system. Hence, Golgi function is important for CSFV multiplication, and GBF1 and Rab2 participate in CSFV proliferation. Further studies must investigate Golgi-resident proteins to elucidate the mechanism underlying CSFV replication. [Liang W, Zheng M, Bao C and Zhang Y 2017 CSFV proliferation is associated with GBF1 and Rab2. J.
Title: CSFV proliferation is associated with GBF1 and Rab2

Ex Output:
False