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".
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Question: Paragraph: Aquaporins are small channel proteins which facilitate the diffusion of water and small neutral molecules across biological membranes. Compared with animals, plant genomes encode numerous aquaporins, which display a large variety of subcellular localization patterns. More specifically, plant aquaporins of the plasma membrane intrinsic protein (PIP) subfamily were first described as plasma membrane (PM)-resident proteins, but recent research has demonstrated that the trafficking and subcellular localization of these proteins are complex and highly regulated. In the past few years, PIPs emerged as new model proteins to study subcellular sorting and membrane dynamics in plant cells. At least two distinct sorting motifs (one cytosolic, the other buried in the membrane) are required to direct PIPs to the PM. Hetero-oligomerization and interaction with SNAREs (soluble N-ethylmaleimide-sensitive factor protein attachment protein receptors) also influence the subcellular trafficking of PIPs. In addition to these constitutive processes, both the progression of PIPs through the secretory pathway and their dynamics at the PM are responsive to changing environmental conditions. The first aquaporins discovered in plants were classified on the basis of their subcellular localization. NIPs (nodulin26-like 
 Title: Trafficking of Plant Plasma Membrane Aquaporins: Multiple Regulation Levels and Complex Sorting Signals

Answer: False


Question: Paragraph: Pathogens that spill over between species cause a significant human and animal health burden. Here, we describe characteristics of animal reservoirs that are required for pathogen spillover. We assembled and analyzed a database of 330 disease systems in which a pathogen spills over from a reservoir of one or more species. Three-quarters of reservoirs included wildlife, and 84% included mammals. Further, 65% of pathogens depended on a community of reservoir hosts, rather than a single species, for persistence. Among mammals, the most frequently identified reservoir hosts were rodents, artiodactyls, and carnivores. The distribution among orders of mammalian species identified as reservoirs did not differ from that expected by chance. Among disease systems with high priority pathogens and epidemic potential, we found birds, primates, and bats to be overrepresented. We also analyzed the life history traits of mammalian reservoir hosts and compared them to mammals as a whole. Reservoir species had faster life history characteristics than mammals overall, exhibiting traits associated with greater reproductive output rather than long-term survival. Thus, we find that in many respects, reservoirs of spillover pathogens are indeed special. The described patterns provide a useful resource for studying and managing emerging infectious diseases. 
 Title: Are disease reservoirs special? Taxonomic and life history characteristics

Answer: False


Question: Paragraph: With growing amounts of data available, identification of clusters of persons linked to each other by transmission of an infectious disease increasingly relies on automated algorithms. We propose cluster finding to be a two-step process: first, possible transmission clusters are identified using a cluster algorithm, second, the plausibility that the identified clusters represent genuine transmission clusters is evaluated. Aim: To introduce visual tools to assess automatically identified clusters. Methods: We developed tools to visualise: (i) clusters found in dimensions of time, geographical location and genetic data; (ii) nested sub-clusters within identified clusters; (iii) intra-cluster pairwise dissimilarities per dimension; (iv) intra-cluster correlation between dimensions. We applied our tools to notified mumps cases in the Netherlands with available disease onset date (January 2009 -June 2016), geographical information (location of residence), and pathogen sequence data (n = 112). We compared identified clusters to clusters reported by the Netherlands Early Warning Committee (NEWC). Results: We identified five mumps clusters. Three clusters were considered plausible. One was questionable because, in phylogenetic analysis, genetic sequences related to it segregated in two groups. One was implausible with no smaller nested clusters, high intra-cluster dissimilarities on all dimensions, and low intra-cluster correlation between dimensions. The NEWC reports concurred with our findings: the plausible/questionable clusters corresponded to reported outbreaks; the implausible cluster did not. Conclusion: Our tools for assessing automatically identified clusters allow outbreak investigators to rapidly spot plausible transmission clusters for mumps and other human-to-human transmissible diseases. This fast information processing potentially reduces workload. 
 Title: Visual tools to assess the plausibility of algorithm- identified infectious disease clusters: an application to mumps data from the Netherlands

Answer:
False