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".

Example 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
Example Output: True

Example Input: Paragraph: Immune responses are a double-edged sword. Effective and appropriate immune responses capable of controlling viral infection while also largely preserving tissue integrity, are critical for host survival. Too strong immune responses might result in immune pathology, while too weak immune responses might cause viral persistence. Physiologic ageing is accompanied with a decline in the normal functioning of the immune system, which is termed as "immunosenescence". We show that aged mice (16-19 months old) are more resistant to influenza A virus (IAV) infection than the young mice. Strong immune responses in the young mice after IAV infection result in faster clearance of virus, but also cause severe lung injury and higher mortality rate. While in the aged mice, the delayed and milder immune responses contribute to reduced pulmonary damage, and are still capable to clear the infection even with a slower kinetics, displaying a more resistant phenotype during IAV infection. Hence, our work demonstrates that moderate immune responses as a decline with ageing in the aged mice balance the immune pathology and viral clearance, might be beneficial for the host during certain circumstances. Our results provide important insight to our basic knowledge of immunosenescence and immune defenses to invading pathogens. Further, our results indicate that age factors should be considered when investigating the vaccination and therapeutic strategies for severe IAV infection. 
 Title: Aged Mice are More Resistant to Influenza Virus Infection due to Reduced Inflammation and Lung Pathology
Example Output: True

Example Input: Paragraph: Identification and discovery of viruses using next-generation sequencing technology is a fastdeveloping area with potential wide application in clinical diagnostics, public health monitoring and novel virus discovery. However, tremendous sequence data from NGS study has posed great challenge both in accuracy and velocity for application of NGS study. Here we describe VIP ("Virus Identification Pipeline"), a one-touch computational pipeline for virus identification and discovery from metagenomic NGS data. VIP performs the following steps to achieve its goal: (i) map and filter out background-related reads, (ii) extensive classification of reads on the basis of nucleotide and remote amino acid homology, (iii) multiple k-mer based de novo assembly and phylogenetic analysis to provide evolutionary insight. We validated the feasibility and veracity of this pipeline with sequencing results of various types of clinical samples and public datasets. VIP has also contributed to timely virus diagnosis (~10 min) in acutely ill patients, demonstrating its potential in the performance of unbiased NGS-based clinical studies with demand of short turnaround time. VIP is released under GPLv3 and is available for free download at: https://github.com/keylabivdc/VIP. The world contains a high diversity of human viral pathogens. There are approximately 300 recognized viral pathogen species, and additional species continue to be discovered. The identification of viral pathogens has a tremendous impact on infectious diseases, virology and public health. Nearly all of the outbreaks of public health issues over the last decade have been caused by viruses, including Severe Acute Respiratory Syndrome (SARS) coronavirus 1 , 2009 pandemic influenza H1N1 2 , H7N9 avian influenza viruses 3 and the recently described Ebola virus in West Africa 4 . Traditional diagnostic methods for viruses, such as cell culture, serodiagnosis, or nucleic acid-based testing are narrow in scope and require a priori knowledge of the potential infectious agents 5,6 . Accurate diagnosis and timely treatment for the infection dramatically reduced the risk of continued transmission and mortality in hospitalized patients 7 . Wild interest in comprehensive detection of these newly emerging and re-emerging viruses from clinical samples highlight the need for rapid, broad-spectrum diagnostic assays. Shotgun metagenomic sequencing of clinical samples for viral pathogen identification provides a promising alternative solution. Although metagenomics is typically applied to understanding genomic diversity from environment samples, this methodology has also revolutionized virology with comprehensive applications, including viral pathogen identification of infectious disease in clinical laboratories 8 and virus discovery in acute and chronic illnesses of unknown origin 9 . Many novel viruses have been discovered using popular next generation sequencing (NGS) platforms such as pyrosequencing (454 Roche), semiconductor sequencing (Life Technology) and illumina dye sequencing (Illumina) 10-12 . Achievements obtained by viral metagenomics show significant advantages over traditional methods of identifying a viral pathogen, including no need of sequence information for that pathogen, identifying multiple pathogens in a single assay and eliminating the need for time-consuming culturing or antibody laboratory tests. A key feature of latest NGS platforms is their speed. It takes minimum turnaround times about 8 hours for sequencing 13 . Thus, it is critical that subsequent computational handling of the large amount of sequence 
 Title: VIP: an integrated pipeline for metagenomics of virus identification and discovery OPEN
Example Output:
True