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: Increasing numbers of H5N1 influenza viruses (IVs) are responsible for human deaths, especially in North Africa and Southeast Asian. The binding of hemagglutinin (HA) on the viral surface to host sialic acid (SA) receptors is a requisite step in the infection process. Phylogenetic analysis reveals that H5N1 viruses can be divided into 10 clades based on their HA sequences, with most human IVs centered from clade 1 and clade 2.1 to clade 2.3. Protein sequence alignment in various clades indicates the high conservation in the receptor-binding domains (RBDs) is essential for binding with the SA receptor. Two glycosylation sites, 158N and 169N, also participate in receptor recognition. In the present work, we attempted to construct a serial H5N1 HA models including diverse glycosylated HAs to simulate the binding process with various SA receptors in silico. As the SA-a-2,3-Gal and SA-a-2,6-Gal receptor adopted two distinctive topologies, straight and fishhooklike, respectively, the presence of N-glycans at 158N would decrease the affinity of HA for all of the receptors, particularly SA-a-2,6-Gal analogs. The steric clashes of the huge glycans shown at another glycosylation site, 169N, located on an adjacent HA monomer, would be more effective in preventing the binding of SA-a-2,3-Gal analogs. 
 Title: Two Glycosylation Sites in H5N1 Influenza Virus Hemagglutinin That Affect Binding Preference by Computer-Based Analysis

Output: False


Input: Consider Input: Paragraph: Although viruses are known to be the second most common etiological factor in communityacquired pneumonia (CAP), the respiratory viral profile of the patients with healthcare-associated pneumonia (HCAP) has not yet been elucidated. We investigated the prevalence and the clinical impact of respiratory virus infection in adult patients with HCAP. Patients admitted with HCAP or CAP, between January and December 2016, to a tertiary referral hospital in Korea, were prospectively enrolled, and virus identification was performed using reverse-transcription polymerase chain reaction (RT-PCR). Among 452 enrolled patients (224 with HCAP, 228 with CAP), samples for respiratory viruses were collected from sputum or endotracheal aspirate in 430 (95.1%) patients and from nasopharyngeal specimens in 22 (4.9%) patients. Eighty-seven (19.2%) patients had a viral infection, and the proportion of those with viral infection was significantly lower in the HCAP than in the CAP group (13.8% vs 24.6%, p = 0.004). In both the HCAP and CAP groups, influenza A was the most common respiratory virus, followed by entero-rhinovirus. The seasonal distributions of respiratory viruses were also similar in both groups. In the HCAP group, the viral infection resulted in a similar length of hospital stay and in-hospital mortality as viral-bacterial coinfection and bacterial infection, and the CAP group showed similar results. Conclusions 
 Title: Comparison of viral infection in healthcare- associated pneumonia (HCAP) and community-acquired pneumonia (CAP)

Output: True


Input: Consider Input: Paragraph: Despite the considerable advances in medical and pharmaceutical research during the past years, diseases caused by viruses have remained a major burden to public health. Virtual in silico screening has repeatedly proven to be useful to meet the special challenges of antiviral drug discovery. Large virtual compound libraries are filtered by different computational screening methods such as docking, ligand-based similarity searches or pharmacophore-based screening, reducing the number of candidate molecules to a smaller set of promising candidates that are then tested biologically. This rational approach makes the drug discovery process more goal-oriented and saves resources in terms of time and money. In this review we discuss how different virtual screening techniques can be applied to antiviral drug discovery, present recent success stories in this field and finally address the main differences between the methods. Section editors: 
 Title: In silico virtual screening approaches for anti-viral drug discovery


Output: False