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".

Input: Consider Input: Paragraph: The spread of the COVID-19 caused by the SARS-CoV-2 outbreak has been growing since its first identification in December 2019. The publishing of the first SARS-CoV-2 genome made a valuable source of data to study the details about its phylogeny, evolution, and interaction with the host. Protein-protein binding assays have confirmed that Angiotensin-converting enzyme 2 (ACE2) is more likely to be the cell receptor via which the virus invades the host cell. In the present work, we provide an insight into the interaction of the viral spike Receptor Binding Domain (RBD) from different coronavirus isolates with host ACE2 protein. By calculating : bioRxiv preprint 2 the binding energy between RBD and ACE2, we highlighted the putative jump in the affinity from a progenitor form of SARS-CoV-2 to the current virus responsible for COVID-19 outbreak. Our result was consistent with the phylogeny analysis and corroborates the opinion that the interface segment of the spike protein RBD might be acquired by SARS-CoV-2 via a complex evolutionary process rather than mutation accumulation. We also highlighted the relevance of Q493 and P499 amino acid residues of SARS-CoV-2 RBD for binding to hACE2 and maintaining the stability of the interface. Moreover, we show from the structural analysis that it is unlikely for the interface residues to be the result of human engineering. Finally, we studied the impact of eight different variants located at the interaction surface of ACE2, on the complex formation with SARS-CoV-2 RBD. We found that none of them is likely to disrupt the interaction with the viral RBD of SARS-CoV-2. 
 Title: Interaction of the spike protein RBD from SARS-CoV-2 with ACE2: similarity with SARS-CoV, hot-spot analysis and effect of the receptor polymorphism

Output: False


Input: Consider Input: Paragraph: Pulmonary arterial hypertension (PAH) is a chronic lung disease with poor diagnosis and limited therapeutic options. The currently available therapies are ineffective in improving the quality of life and reducing mortality rates. There exists a clear unmet medical need to treat this disease, which necessitates the discovery of novel therapeutic targets/agents for safe and successful therapy. An altered renin-angiotensin system (RAS) has been implicated as a causative factor in the pathogenesis of PAH. Angiotensin II (Ang II), a key effector peptide of the RAS, can exert deleterious effects on the pulmonary vasculature resulting in vasoconstriction, proliferation, and inflammation, all of which contribute to PAH development. Recently, a new member of the RAS, angiotensin converting enzyme 2 (ACE2), was discovered. This enzyme functions as a negative regulator of the angiotensin system by metabolizing Ang II to a putative protective peptide, angiotensin-(1-7). ACE2 is abundantly expressed in the lung tissue and emerging evidence suggests a beneficial role for this enzyme against lung diseases. In this review, we focus on ACE2 in relation to pulmonary hypertension and provide proof of principle for its therapeutic role in PAH. 
 Title: ACE2, a promising therapeutic target for pulmonary hypertension

Output: False


Input: Consider Input: Paragraph: h i g h l i g h t s • We obtained a spatial epidemic model with logistic growth. • Using multiple-scale analysis, we present amplitude equations. • There are different types of stationary patterns. • Reaction diffusion epidemic systems have rich dynamics. Mathematical models are very useful in analyzing the spread and control of infectious diseases which can be used to predict the developing tendency of the infectious disease, determine the key factors and to seek the optimum strategies of disease control. As a result, we investigated the pattern dynamics of a spatial epidemic model with logistic growth. By using amplitude equation, we found that there were different types of stationary patterns including spotted, mixed, and stripe patterns, which mean that spatial motion of individuals can form high density of diseases. The obtained results can be extended in other related fields, such as vegetation patterns in ecosystems. 
 Title: Physica A Dynamics of an epidemic model with spatial diffusion


Output: True