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: Viruses evolve extremely quickly, so reliable methods for viral host prediction are necessary to safeguard biosecurity and biosafety alike. Novel human-infecting viruses are difficult to detect with standard bioinformatics workflows. Here, we predict whether a virus can infect humans directly from next-generation sequencing reads. We show that deep neural architectures significantly outperform both shallow machine learning and standard, homology-based algorithms, cutting the error rates in half and generalizing to taxonomic units distant from those presented during training. We propose a new approach for convolutional filter visualization to disentangle the information content of each nucleotide from its contribution to the final classification decision. Nucleotide-resolution maps of the learned associations between pathogen genomes and the infectious phenotype can be used to detect virulencerelated genes in novel agents, as we show here for the SARS-CoV-2 coronavirus, unknown before it caused a COVID-19 pandemic in 2020. 
 Title: Interpretable detection of novel human viruses from genome sequencing data

A: True
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Q: Paragraph: To assess the viability of isolation and contact tracing to control onwards transmission from imported cases of 2019-nCoV. We developed a stochastic transmission model, parameterised to the 2019-nCoV outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a 2019 nCoV-like pathogen. We considered scenarios that varied in: the number of initial cases; the basic reproduction number R0; the delay from symptom onset to isolation; the probability contacts were traced; the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings: While simulated outbreaks starting with only 5 initial cases, R0 of 1.5 and little transmission before symptom onset could be controlled even with low contact tracing probability, the prospects of controlling an outbreak dramatically dropped with the number of initial cases, with higher R0, and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R0 of 1.5 were controllable with under 50% of contacts successfully traced. For R0 of 2.5 and 3.5, more than 70% and 90% of contacts respectively had to be traced to control the majority of outbreaks. The delay between symptom onset and isolation played the largest role in determining whether an outbreak was controllable for lower values of R0. For higher values of R0 and a large initial number of cases, contact tracing and isolation was only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation: We found that in most scenarios contact tracing and case isolation alone is unlikely to control a new outbreak of 2019-nCov within three months. The probability of control decreases with longer delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. 
 Title: Title: Feasibility of controlling 2019-nCoV outbreaks by isolation of cases and contacts

A: True
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Q: Paragraph: Still disappointing results from a seductive idea • Mucosal surfaces of the respiratory tract represent a major portal of entry for most human viruses and a critical component of the mammalian immunologic repertoire. The major antibody isotype in external secretions is secretory immunoglobin A (S-IgA). The major effector cells in mucosal surfaces, however, are not IgA B cells, but T lymphocytes, which may account for up to 80% of the mucosal lymphoid cell population. • Mucosal immunoprophylaxis is theoretically an important approach to control infections acquired through these portals. Passive antibodies can protect against mucosal viral infections, as shown for respiratory syncytial virus, but very high quantities of passive antibodies are needed to restrict virus replication on mucosal surface. • Factors likely to induce mucosal antibody and cell-mediated immune responses include oral or respiratory routes of immunization and active (effectively replicating) vaccine agents. • Very few antiviral vaccines have been developed to protect the mucosal surface of the respiratory tract, and only an attenuated influenza virus vaccine uses the nasal route. Other vaccines, approved for parenteral use, have been administered experimentally by the nasal route; these include active (replicating) and inactive (nonreplicating) vaccines. By this route they induce only a moderate local mucosal response. • Neither the development of mucosal immunity nor the administration of vaccines via the mucosal route is essential for control or prevention of most respiratory viral infections and diseases acquired through the respiratory tract. Nonetheless, the example of the live attenuated intranasal influenza vaccine, which induces both systemic and local immune response, is promising for the future of mucosal immunization against respiratory viral infections. 
 Title: Vaccination antivirale et immunité muqueuse respiratoire Un concept séduisant pour des résultats encore décevants Key points Immunologie/Virologie

A:
True
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