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: Meliacine (MA), an antiviral principle present in partially purified leaf extracts of Melia azedarach L., prevents the development of herpetic stromal keratitis (HSK) in mice by diminishing the viral load in the eye and the severity of lesions caused by a virus-induced immunopathological reaction. The tetranortriterpenoid 1-cinnamoyl-3,11-dihydroxymeliacarpin (CDM), obtained from MA purification, displays anti-herpetic activity and impedes nuclear factor B (NF-B) activation in HSV-1 infected conjunctival cells. To extend our understanding about CDM biological properties, we investigated its anti-HSV-1 activity as well as the effect on NF-B activation and cytokine secretion induced by viral (HSV-1) and no-viral (LPS) stimuli, in corneal cells and macrophages. CDM exerted a potent anti-HSV-1 effect on corneal cells and inhibited NF-B translocation to the nucleus, leading to a decrease in IL-6 production. Besides, CDM seemed to modulate IL-6 and TNF-␣ responses in macrophages, whether they were infected with HSV-1 or stimulated with LPS. However, CDM did not affect NF-B activation in these cells, suggesting that an alternative NF-B cell signaling pathway would be involved in the modulation of cytokine production. We conclude that, in addition to its antiviral effect, CDM would be acting as an immunomodulating compound which would be responsible for the improvement of murine HSK already reported. 
 Title: A natural tetranortriterpenoid with immunomodulating properties as a potential anti-HSV agent
False

Paragraph: Background Characterisation of the severity profi le of human infections with infl uenza viruses of animal origin is a part of pandemic risk assessment, and an important part of the assessment of disease epidemiology. Our objective was to assess the clinical severity of human infections with avian infl uenza A H7N9 virus, which emerged in China in early 2013. Prevention. We estimated the risk of fatality, mechanical ventilation, and admission to the intensive care unit for patients who required hospital admission for medical reasons. We also used information about laboratory-confi rmed cases detected through sentinel infl uenza-like illness surveillance to estimate the symptomatic case fatality risk. 17 patients who were still in hospital, we estimated the fatality risk for all ages to be 36% (95% CI 26-45) on admission to hospital. Risks of mechanical ventilation or fatality (69%, 95% CI 60-77) and of admission to an intensive care unit, mechanical ventilation, or fatality (83%, 76-90) were high. With assumptions about coverage of the sentinel surveillance network and health-care-seeking behaviour for patients with infl uenza-like illness associated with infl uenza A H7N9 virus infection, and pro-rata extrapolation, we estimated that the symptomatic case fatality risk could be between 160 (63-460) and 2800 (1000-9400) per 100 000 symptomatic cases. Interpretation Human infections with avian infl uenza A H7N9 virus seem to be less serious than has been previously reported. Many mild cases might already have occurred. Continued vigilance and sustained intensive control eff orts are needed to minimise the risk of human infection. Funding 
 Title: Human infection with avian infl uenza A H7N9 virus: an assessment of clinical severity
True

Paragraph: Identification of epitopes which invokes strong humoral responses is an essential issue in the field of immunology. Various computational methods that have been developed based on the antigen structures and the mimotopes these years narrow the search for experimental validation. These methods can be divided into two categories: antigen structure-based methods and mimotopebased methods. Though new methods of the two kinds have been proposed in these years, they cannot maintain a high degree of satisfaction in various circumstances. In this paper, we proposed a new conformational B-cell epitope prediction method based on antigen preprocessing and mimotopes analysis. The method classifies the antigen surface residues into "epitopes" and "nonepitopes" by six epitope propensity scales, removing the "nonepitopes" and using the preprocessed antigen for epitope prediction based on mimotope sequences. The proposed method gives out the mean F score of 0.42 on the testing dataset. When compared with other publicly available servers by using the testing dataset, the new method yields better performance. The results demonstrate the proposed method is competent for the conformational B-cell epitope prediction. 
 Title: Conformational B-Cell Epitope Prediction Method Based on Antigen Preprocessing and Mimotopes Analysis

False