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".

Example Input: Paragraph: Self-assembly refers to the spontaneous organization of individual building blocks into higher order structures. It occurs in biological systems such as spherical viruses, which utilize icosahedral symmetry as a guiding principle for the assembly of coat proteins into a capsid shell. In this study, we characterize the self-assembling protein nanoparticle (SAPN) system, which was inspired by such viruses. To facilitate self-assembly, monomeric building blocks have been designed to contain two oligomerization domains. An N-terminal pentameric coiled-coil domain is linked to a C-terminal coiled-coil trimer by two glycine residues. By combining monomers with inherent propensity to form five-and threefold symmetries in higher order agglomerates, the supposition is that nanoparticles will form that exhibit local and global symmetry axes of order 3 and 5. This article explores the principles that govern the assembly of such a system. Specifically, we show that the system predominantly forms according to a spherical core-shell morphology using a combination of scanning transmission electron microscopy and small angle neutron scattering. We introduce a mathematical toolkit to provide a specific description of the possible SAPN morphologies, and we apply it to characterize all particles with maximal symmetry. In particular, we present schematics that define the relative positions of all individual chains in the symmetric SAPN particles, and provide a guide of how this approach can be generalized to nonspherical morphologies, hence providing unprecedented insights into their geometries that can be exploited in future applications. 
 Title: Article Principles Governing the Self-Assembly of Coiled-Coil Protein Nanoparticles
Example Output: True

Example Input: Paragraph: Background: Mechanisms influencing severity of acute lower respiratory infection (ALRI) in children are not established. We aimed to assess the role of inflammatory markers and respiratory viruses in ALRI severity. Methods: Concentrations of interleukin(IL)-33, soluble suppression of tumorigenicity (sST)2, IL-1ß, tumor necrosis factor α, IL-4, IL-6 and IL-8 and types of respiratory viruses were evaluated in children at the first and fifth days after hospital admission. Disease severity was defined as need for mechanical ventilation. Results: Seventy-nine children < 5 years-old were included; 33(41.8%) received mechanical ventilation. No associations between virus type, viral load or co-detections and severity of disease were observed. Detection of IL-33 and sST2 in nasopharyngeal aspirates (NPA) on admission were associated with higher risk for mechanical ventilation (RR = 2.89 and RR = 4.57, respectively). IL-6 and IL-8 concentrations were higher on Day 5 in mechanically ventilated children. IL-6 NPA concentrations decreased from Day 1 to Day 5 in children who did not receive mechanical ventilation. Increase in sST2 NPA concentrations from Day 1 to Day 5 was associated with longer hospital length of stay (p < 0.01). Conclusions: An exacerbated local activation of the IL-33/ST2 axis and persistently high sST2 concentrations over time were associated with severity of viral ALRI in children. 
 Title: IL-33 and ST2 as predictors of disease severity in children with viral acute lower respiratory infection
Example Output: False

Example Input: Paragraph: Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R 0 , 2). 
 Title: Highly dynamic animal contact network and implications on disease transmission
Example Output:
True