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: Background: Host genetic factors may play a role in susceptibility and resistance to SARS associated coronavirus (SARS-CoV) infection. The study was carried out to investigate the association between the genetic polymorphisms of 2',5'-oligoadenylate synthetase 1 (OAS1) gene as well as myxovirus resistance 1 (MxA) gene and susceptibility to SARS in Chinese Han population. A hospital-based case-control study was conducted. A collective of 66 SARS cases and 64 close contact uninfected controls were enrolled in this study. End point real time polymerase chain reaction (PCR) and PCR-based Restriction Fragment Length Polymorphism (RFLP) analysis were used to detect the single nucleic polymorphisms (SNPs) in OAS1 and MxA genes. Information on other factors associated with SARS infection was collected using a pre-tested questionnaire. Univariate and multivariate logistic analyses were conducted. Results: One polymorphism in the 3'-untranslated region (3'-UTR) of the OAS1 gene was associated with SARS infection. Compared to AA genotype, AG and GG genotypes were found associated with a protective effect on SARS infection with ORs (95% CI) of 0.42 (0.20~0.89) and 0.30 (0.09~0.97), respectively. Also, a GT genotype at position 88 in the MxA gene promoter was associated with increased susceptibility to SARS infection compared to a GG genotype (OR = 3.06, 95% CI: 1.25~7.50). The associations of AG genotype in OAS1 and GT genotype in MxA remained significant in multivariate analyses after adjusting for SARS protective measures (OR = 0.38, 95% CI: 0.14~0.98 and OR = 3.22, 95% CI: 1.13~9.18, respectively). Conclusion: SNPs in the OAS1 3'-UTR and MxA promoter region appear associated with host susceptibility to SARS in Chinese Han population. 
 Title: BMC Infectious Diseases Association of SARS susceptibility with single nucleic acid polymorphisms of OAS1 and MxA genes: a case-control study

Ex Output:
True


Ex Input:
Paragraph: Host-pathogen interactions provide a fascinating example of two or more active genomes directly exerting mutual influence upon each other. These encounters can lead to multiple outcomes from symbiotic homeostasis to mutual annihilation, undergo multiple cycles of latency and lysogeny, and lead to coevolution of the interacting genomes. Such systems pose numerous challenges but also some advantages to modeling, especially in terms of functional, mathematical genome representations. The main challenges for the modeling process start with the conceptual definition of a genome for instance in the case of hostintegrated viral genomes. Furthermore, hardly understood influences of the activity of either genome on the other(s) via direct and indirect mechanisms amplify the needs for a coherent description of genome activity. Finally, genetic and local environmental heterogeneities in both the host's cellular and the pathogen populations need to be considered in multiscale modeling efforts. We will review here two prominent examples of host-pathogen interactions at the genome level, discuss the current modeling efforts and their shortcomings, and explore novel ideas of representing active genomes which promise being particularly adapted to dealing with the modeling challenges posed by host-pathogen interactions. 
 Title: Critical Dynamics in Host-Pathogen Systems

Ex Output:
True


Ex Input:
Paragraph: Contact history is crucial during an infectious disease outbreak and vital when seeking to understand and predict the spread of infectious diseases in human populations. e transmission connectivity networks of people infected with highly contagious Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia were assessed to identify super-spreading events among the infected patients between 2012 and 2016. Of the 1379 MERS cases recorded during the study period, 321 (23.3%) cases were linked to hospital infection, out of which 203 (14.7%) cases occurred among healthcare workers. ere were 1113 isolated cases while the number of recorded contacts per MERS patient is between 1 (n � 210) and 17 (n � 1), with a mean of 0.27 (SD � 0.76). Five super-important nodes were identified based on their high number of connected contacts worthy of prioritization (at least degree of 5). e number of secondary cases in each SSE varies (range, 5-17). e eigenvector centrality was significantly (p < 0.05) associated with place of exposure, with hospitals having on average significantly higher eigenvector centrality than other places of exposure. Results suggested that being a healthcare worker has a higher eigenvector centrality score on average than being nonhealthcare workers. Pathogenic droplets are easily transmitted within a confined area of hospitals; therefore, control measures should be put in place to curtail the number of hospital visitors and movements of nonessential staff within the healthcare facility with MERS cases. 
 Title: Network Analysis of MERS Coronavirus within Households, Communities, and Hospitals to Identify Most Centralized and Super-Spreading in the Arabian Peninsula, 2012 to 2016

Ex Output:

False