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".

[EX Q]: 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
[EX A]: False

[EX Q]: Paragraph: Proteinchip profiling is a powerful and innovative proteomic technology for the discovery of biomarkers and the development of diagnostic/prognostic assays. On the basis of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), Ciphergen's proteinchip system offers a single, unified, and high throughput platform for a multitude of proteomic research applications. Proteins are the major functional components of the cell. The study of proteomics helps to better understand the mechanism of a disease. Remarkable findings in disease biomarkers have shed light on the early diagnosis, monitoring, and prognosis of various diseases, especially for cancer. In this paper, the development and technology of SELDI-TOF MS are introduced. The research progress and encouraging research results in malignancies, infectious diseases, neurological diseases, and diabetes mellitus using SELDI-TOF MS are reviewed. This paper concludes by evaluating the pros and cons, and the future perspectives are also expounded. 
 Title: Research Progress in SELDI-TOF MS and Its Clinical Applications
[EX A]: True

[EX Q]: Paragraph: autoimmune arthritis. In the present study, we provide compelling experimental in vivo evidence in support of our hypothesis. Using the SCHOOL approach and the SARS-CoV fusion peptide sequence, we rationally designed a novel immunomodulatory peptide that targets TCR. We showed that this peptide ameliorates collagen-induced arthritis in DBA/1J mice and protects against bone and cartilage damage. Incorporation of the peptide into self-assembling lipopeptide nanoparticles that mimic native human high density lipoproteins significantly increases peptide dosage efficacy. Together, our data further confirm that viral immune evasion strategies that target MIRRs can be transferred to therapeutic strategies that require similar functionalities. 
 Title: SARS Coronavirus Fusion Peptide- Derived Sequence Suppresses Collagen-Induced Arthritis in DBA/1J Mice OPEN
[EX A]:
True