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: 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
[A]: False


[Q]: Paragraph: Ebola virus is the causative agent of Ebola virus disease in humans. The lethality of Ebola virus infection is about 50%, supporting the urgent need to develop anti-Ebola drugs. Glycoprotein (GP) is the only surface protein of the Ebola virus, which is functionally critical for the virus to attach and enter the host cells, and is a promising target for anti-Ebola virus drug development. In this study, using the recombinant HIV-1/Ebola pseudovirus platform we previously established, we evaluated a small molecule library containing various quinoline compounds for anti-Ebola virus entry inhibitors. Some of the quinoline compounds specifically inhibited the entry of the Ebola virus. Among them, compound SYL1712 was the most potent Ebola virus entry inhibitor with an IC 50 of~1 µM. The binding of SYL1712 to the vial glycoprotein was computationally modeled and was predicted to interact with specific residues of GP. We used the time of the addition assay to show that compound SYL1712 blocks Ebola GP-mediated entry. Finally, consistent with being an Ebola virus entry inhibitor, compound SYL1712 inhibited infectious Ebola virus replication in tissue culture under biosafety level 4 containment, with an IC 50 of 2 µM. In conclusion, we identified several related molecules with a diaryl-quinoline scaffold as potential anti-EBOV entry inhibitors, which can be further optimized for anti-Ebola drug development. 
 Title: Identification of Diaryl-Quinoline Compounds as Entry Inhibitors of Ebola Virus
[A]: True


[Q]: Paragraph: Community-acquired pneumonia is still a significant cause of morbidity and mortality and is often misdiagnosed and inappropriately treated. Although it can be caused by a wide variety of micro-organisms, the pneumococcus, atypicals, such as Mycoplasma pneumoniae and Chlamydophila pneumoniae, Staphylococcus aureus and certain Gram-negative rods are the usual pathogens encountered. The site-of-care decision is critical in determining the site and type of care as well as the extent of diagnostic workup. Antimicrobial therapy should be started as soon as possible particularly in those requiring admission to hospital, but typically the physician does not know with any degree of certainty the identity of the etiologic pathogen. A number of national guidelines have been published to help the physician with this choice. The initial drug(s) can be modified if necessary if the pathogen and its antimicrobial susceptibility pattern becomes known. Adjunctive therapy such as pressors and fluid replacement are of value and macrolides appear to help as well, likely secondary to their immunomodulatory effects. Recent data also suggest a role for steroids. 
 Title: Community-acquired pneumonia: An overview
[A]:
True