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: Human immunodeficiency virus type 1 (HIV-1) Tat plays an important role in HIV-associated neuropathogenesis; the underlying mechanisms are still evolving. We have recently shown that HIV-1 Tat induces expression of glial fibrillary acidic protein (GFAP), a characteristic of HIV-1 infection of the central nervous system (CNS). We have also shown that the Tat-induced GFAP expression in astrocytes is regulated by p300, and that deletion of the early growth response 1 (Egr-1) cis-transacting element within the p300 promoter abolishes Tat-induced GFAP expression. In this study, we further examined the relationship between Tat and Egr-1 in astrocytes. We found increased Egr-1 protein expression in Tat-expressing human astrocytoma cells and mouse primary astrocytes. Using the Egr-1 promoter-driven firefly luciferase reporter gene assay and the sitedirected mutagenesis, we demonstrated that Tat increased Egr-1 expression by transactivating the Egr-1 promoter and involving specific serum response elements (SRE) within the promoter. Consistent with these data, we showed that Tat transactivation of the Egr-1 promoter was abrogated when astrocytes were cultured in serum-reduced media. Taken together, these results reveal that Tat directly transactivates Egr-1 expression and suggest that Tat interaction with Egr-1 is probably one of the very upstream molecular events that initiate Tat-induced astrocyte dysfunction and subsequent Tat neurotoxicity. 
 Title: Activation of Egr-1 expression in astrocytes by HIV-1 Tat: new insights into astrocyte-mediated Tat neurotoxicity
[A]: True


[Q]: Paragraph: Background: Overcrowding, reduced nurse to patient ratio, limited distance between incubators and absence of microbiological surveillance have been shown to promote spread of multidrug-resistant gram-negative organisms (MDRGN) in patients with birthweight < 1500 g. Patients > 1500 g treated on an intermediate care unit are unrepresented in recent literature. We therefore intended to present data obtained from a short-term overcrowded neonatal intermediate care unit (NIMCU) at a level III (international categorization) perinatal center at University Hospital Frankfurt, Germany. Methods: During a 25 day overcrowding (OV) and 28 day post-overcrowding period (POST-OV) on NIMCU, epidemiological data obtained from continuously hold microbiological surveillance were investigated and compared to the last 12 months of ward-regular bed occupancy preceding OV (PRAE-OV). Results: During OV, the number of patients simultaneously treated at the NIMCU increased from 18 to 22, resulting in a reduced bed-to-bed space. Nurse: patient ratio was 4:22 during OV compared to 3:18 during PRAE-OV. Cumulative incidence of MDRGN was 4.7% in OV and 2.4% POST-OV compared to 4.8% to PRAE-OV, respectively, without any significant variations. During OV and POST-OV, septic episodes due to MDRGN were not observed. In one case, potential nosocomial transmission of Enterobacter cloacae resistant to Piperacillin and 3rd/4th generation cephalosporins was observed. Conclusions: Prevention of nosocomial spread of MDRGN in an overcrowded NIMCU is based on staff's diligent training and adequate staffing. Concise microbiological surveillance should be guaranteed to escort through overcrowding periods. In our setting, impact of bed-to-bed distance on MDRGN transmission seemed to be less strong. 
 Title: Overcrowding in a neonatal intermediate care unit: impact on the incidence of multidrug-resistant gram-negative organisms
[A]:
True