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 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

Ex Output:
False

Ex Input:
Paragraph: Despite the significant role of seasonal influenza vaccination in preventing and minimizing the serious complications of influenza infection in type 2 diabetes mellitus (T2DM) patients, unsatisfactory compliance still exists for vaccination. Study objectives were to explore the vaccination status and determinants in T2DM patients in southwestern Saudi Arabia. A cross-sectional study on a representative sample of T2DM patients in Abha city, southwestern Saudi Arabia, was conducted. Data for sociodemographic characteristics, clinical criteria, vaccination status, vaccination motivators and barriers and seasonal influenza knowledge were collected. Out of 353 T2DM patients included in the study, seasonal influenza vaccination coverage was 61% in year 2017. A significant factors associated with non-vaccination were; poor influenza and its vaccine knowledge (OR = 4.31, 95% CI: 2.73-6.80), illiteracy (OR = 1.93, 95% CI: 1.11-3.37), and more than 10 years disease duration (OR = 2.07, 95% CI: 1.11-3.87). Presence of family history of DM and ischemic heart comorbidity minimized the possibility of non-vaccination (OR = 0.54 and 0.28 respectively). Healthcare givers' advice was the most reported vaccination motivator (84.7%) while; fear of vaccine side effects was the most stated barrier (73%). In conclusion, influenza vaccination rate among T2DM in the present study is less than the recommended level. Continuous primary health care center-based educational programs should be implemented to aware and encourage influenza vaccination among T2DM patients.
Title: Influenza Vaccination in Type 2 Diabetes Patients: Coverage Status and Its Determinants in Southwestern Saudi Arabia

Ex Output:
True

Ex Input:
Paragraph: The search for new biomarkers for diagnosis, prognosis and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.
Title: Applications of protein microarrays for biomarker discovery

Ex Output:
True