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: In recent years, the biomedical community has witnessed a rapid scientific and technological evolution following the development and refinement of high-throughput methodologies. Concurrently and consequentially, the scientific perspective has changed from the reductionist approach of meticulously analyzing the fine details of a single component of biology, to the "holistic" approach of broadmindedly examining the globally interacting elements of biological systems. The emergence of this new way of thinking has brought about a scientific revolution in which genomics, proteomics, metabolomics and other "omics" have become the predominant tools by which large amounts of data are amassed, analyzed and applied to complex questions of biology that were previously unsolvable. This enormous transformation of basic science research and the ensuing plethora of promising data, especially in the realm of human health and disease, have unfortunately not been followed by a parallel increase in the clinical application of this information. On the contrary, the number of new potential drugs in development has been steadily decreasing, suggesting the existence of roadblocks that prevent the translation of promising research into medically relevant therapeutic or diagnostic application. In this paper we will review, in a non-inclusive fashion, several recent scientific advancements in the field of translational research, with a specific focus on how they relate to infectious disease. We will also present a current picture of the limitations and challenges that exist for translational research, as well as ways that have been proposed by the National Institutes of Health to improve the state of this field.
Title: Translational research in infectious disease: current paradigms and challenges ahead

Output: True

Input: Consider Input: Paragraph: The family Potyviridae encompasses~30% of plant viruses and is responsible for significant economic losses worldwide. Recently, a small overlapping coding sequence, termed pipo, was found to be conserved in the genomes of all potyvirids. PIPO is expressed as part of a frameshift protein, P3N-PIPO, which is essential for virus cell-to-cell movement. However, the frameshift expression mechanism has hitherto remained unknown. Here, we demonstrate that transcriptional slippage, specific to the viral RNA polymerase, results in a population of transcripts with an additional "A" inserted within a highly conserved GAAAAAA sequence, thus enabling expression of P3N-PIPO. The slippage efficiency is~2% in Turnip mosaic virus and slippage is inhibited by mutations in the GAAAAAA sequence. While utilization of transcriptional slippage is well known in negative-sense RNA viruses such as Ebola, mumps and measles, to our knowledge this is the first report of its widespread utilization for gene expression in positive-sense RNA viruses.
Title: Transcriptional slippage in the positive-sense RNA virus family Potyviridae

Output: False

Input: Consider Input: Paragraph: Background: Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven detection can provide relevant epidemiological data on numbers of contact persons and dynamics of contacts between pairs of individuals. We aimed to analyse contact networks with respect to sociodemographic and geographical characteristics, vaccine-induced immunity and self-reported symptoms. Methods: In 2014, volunteers from two large participatory surveillance panels in the Netherlands and Belgium were invited for a survey. Participants were asked to record numbers of contacts at different locations and self-reported influenza-like-illness symptoms, and to invite 4 individuals they had met face to face in the preceding 2 weeks. We calculated correlations between linked individuals to investigate mixing patterns. Results: In total 1560 individuals completed the survey who reported in total 30591 contact persons; 488 recruiterrecruit pairs were analysed. Recruitment was assortative by age, education, household size, influenza vaccination status and sentiments, indicating that participants tended to recruit contact persons similar to themselves. We also found assortative recruitment by symptoms, reaffirming our objective of sampling contact persons whom a participant may infect or by whom a participant may get infected in case of an outbreak. Recruitment was random by sex and numbers of contact persons. Relationships between pairs were influenced by the spatial distribution of peer recruitment. Conclusions: Although complex mechanisms influence online peer recruitment, the observed statistical relationships reflected the observed contact network patterns in the general population relevant for the transmission of respiratory pathogens. This provides useful and innovative input for predictive epidemic models relying on network information.
Title: Tracking social contact networks with online respondent-driven detection: who recruits whom?
Output: True