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: Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R 0 , 2). 
 Title: Highly dynamic animal contact network and implications on disease transmission

Output: True


Input: Consider Input: Paragraph: Dendritic cells (DCs) link the sensing of the environment by the innate immune system to the initiation of adaptive immune responses. Accordingly, DCs are considered to be a major target in the development of immunomodulating compounds. In this study, the effect of niclosamide, a Food and Drug Administrationapproved antihelminthic drug, on the activation of lipopolysaccharide (LPS)-stimulated murine bone marrow-derived DCs was examined. Our experimental results show that niclosamide reduced the pro-inflammatory cytokine and chemokine expression of LPS-activated DCs. In addition, niclosamide also affected the expression of MHC and costimulatory molecules and influenced the ability of the cells to take up antigens. Therefore, in mixed cell cultures composed of syngeneic OVA-specific T cells and DCs, niclosamide-treated DCs showed a decreased ability to stimulate T cell proliferation and IFN-c production. Furthermore, intravenous injection of niclosamide also attenuated contact hypersensitivity (CHS) in mice during sensitization with 2,4-dinitro-1-fluorobenzene. Blocking the LPS-induced activation of MAPK-ERK, JNK and NF-jB may contribute to the inhibitory effect of niclosamide on DC activation. Collectively, our findings suggest that niclosamide can manipulate the function of DCs. These results provide new insight into the immunopharmacological role of niclosamide and suggest that it may be useful for the treatment of chronic inflammatory disorders or DC-mediated autoimmune diseases. 
 Title: Antihelminthic niclosamide modulates dendritic cells activation and function

Output: True


Input: Consider Input: Paragraph: Modelers published thoughtful articles after the 2003 SARS crisis, but had limited if any real-time impact on the global response and may even have inadvertently contributed to a lingering misunderstanding of the means by which the epidemic was controlled. The impact of any intervention depends on its efficiency as well as efficacy, and efficient isolation of infected individuals before they become symptomatic is difficult to imagine. Nonetheless, in exploring the possible impact of quarantine, the product of efficiency and efficacy was varied over the entire unit interval. Another mistake was repeatedly fitting otherwise appropriate gamma distributions to times to event regardless of whether they were stationary or not, particularly onset-isolation intervals whose progressive reduction evidently contributed to SARS control. By virtue of their unknown biology, newly-emerging diseases are more challenging than familiar human scourges. Influenza, for example, recurs annually and has been modeled more thoroughly than any other infectious disease. Moreover, models were integrated into preparedness exercises, during which working relationships were established that bore fruit during the 2009 A/H1N1 pandemic. To provide the most accurate and timely advice possible, especially about the possible impact of measures designed to control diseases caused by novel human pathogens, we must appreciate the value and difficulty of policy-oriented modeling. Effective communication of insights gleaned from modeling SARS will help to ensure that policymakers involve modelers in future outbreaks of newly-emerging infectious diseases. Accordingly, we illustrate the increasingly timely care-seeking by which, together with increasingly accurate diagnoses and effective isolation, SARS was controlled via heuristic arguments and descriptive analyses of familiar observations. Published by Elsevier B.V. 
 Title: Modeling and public health emergency responses: Lessons from SARS


Output: True