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: This review provides an integrated scenario of the most relevant aspects in the development of useful drugs provided by natural sources and recent advances in the biosynthesis and structural design of antimicrobial peptides. Anti-infective drugs have had a key role in the contemporary world, contributing to dramatically decrease mortality rates caused by infectious diseases worldwide. Antimicrobial peptides (AMPs) are multifunctional effectors of the innate immune system of mucosal surfaces and present antimicrobial activity against a range of pathogenic viruses, bacteria, and fungi. However, the discovery and development of new antibacterial drugs is a crucial step to overcome the great challenge posed by the emergence of antibiotic resistance. In this review, we outline recent advances in the development of novel AMPs with improved antimicrobial activities that were achieved through characteristic structural design. In addition, we describe recent progress made to overcome some of the major limitations that have hindered peptide biosynthesis. 
 Title: The next generation of antimicrobial peptides (AMPs) as molecular therapeutic tools for the treatment of diseases with social and economic impacts
Example Output: False

Example Input: Paragraph: Estimating the case-fatality risk (CFR)-the probability that a person dies from an infection given that they are a case-is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR-preferential ascertainment of severe cases and bias from reporting delays-and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases. PLOS Neglected Tropical Diseases | 
 Title: Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks
Example Output: False

Example Input: Paragraph: One contribution of 15 to a theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. Subject Areas: computational biology, ecology, environmental science, health and disease and epidemiology Lassa fever (LF) is a zoonotic disease that is widespread in West Africa and involves animal-to-human and human-to-human transmission. Animal-tohuman transmission occurs upon exposure to rodent excreta and secretions, i.e. urine and saliva, and human-to-human transmission occurs via the bodily fluids of an infected person. To elucidate the seasonal drivers of LF epidemics, we employed a mathematical model to analyse the datasets of human infection, rodent population dynamics and climatological variations and capture the underlying transmission dynamics. The surveillance-based incidence data of human cases in Nigeria were explored, and moreover, a mathematical model was used for describing the transmission dynamics of LF in rodent populations. While quantifying the case fatality risk and the rate of exposure of humans to animals, we explicitly estimated the corresponding contact rate of humans with infected rodents, accounting for the seasonal population dynamics of rodents. Our findings reveal that seasonal migratory dynamics of rodents play a key role in regulating the cyclical pattern of LF epidemics. The estimated timing of high exposure of humans to animals coincides with the time shortly after the start of the dry season and can be associated with the breeding season of rodents in Nigeria. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. 
 Title: Quantifying the seasonal drivers of transmission for Lassa fever in Nigeria
Example Output:
False