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".

[Q]: Paragraph: Detection and characterisation of the canine parvovirus (CPV-2) strains that are currently circulating are essential for the understanding of viral evolution and the development of measures to control its spread. In the present study, stool samples from 144 dogs were analysed by polymerase chain reaction (PCR) for CPV-2, and 29.2% (42/144) of them were positive. From the 42 positive strains, 71.4% (30) of the dogs had signs of haemorrhagic gastroenteritis. The sequencing of the 583 bp fragment of the VP2 gene from the positive strains identified 78.6% (33/42) of them as type 2c, 19% (8/42) as type 2b and 2.4% (1/42) as type 2a. A phylogenetic analysis of the variants circulating in the canine population of Brazil showed that they are very similar to those found in other countries and type 2c has become the predominant type circulating in Brazil. 
 Title: Typing of canine parvovirus strains circulating in Brazil between 2008 and 2010
[A]: True


[Q]: Paragraph: The analysis of 26 longevity curves of different populations of inbred (Fischer 344) and outbred (Sprague-Dawley) rats highlighted a remarkable betweenpopulations variability in survival parameters. This variability is independent of the breeding characteristics of the strain. The two strains differed in the slope of the survival curves, with Fischer 344 rats showing a higher survival over the second year of life as well as a lower interindividual variability. A model-free approach based on principal component analysis allowed us to quantify these differences and to highlight some limitations of the classical Gompertzian approach. 
 Title: WITHIN-AND BETWEEN-STRAIN VARIABILITY IN LONGEVITY OF INBRED AND OUTBRED RATS UNDER THE SAME ENVIRONMENTAL CONDITIONS
[A]: False


[Q]: Paragraph: Recent years have seen the development of numerous methodologies for reconstructing transmission trees in infectious disease outbreaks from densely sampled whole genome sequence data. However, a fundamental and as of yet poorly addressed limitation of such approaches is the requirement for genetic diversity to arise on epidemiological timescales. Specifically, the position of infected individuals in a transmission tree can only be resolved by genetic data if mutations have accumulated between the sampled pathogen genomes. To quantify and compare the useful genetic diversity expected from genetic data in different pathogen outbreaks, we introduce here the concept of 'transmission divergence', defined as the number of mutations separating whole genome sequences sampled from transmission pairs. Using parameter values obtained by literature review, we simulate outbreak scenarios alongside sequence evolution using two models described in the literature to describe transmission divergence of ten major outbreak-causing pathogens. We find that while mean values vary significantly between the pathogens considered, their transmission divergence is generally very low, with many outbreaks characterised by large numbers of genetically identical transmission pairs. We describe the impact of transmission divergence on our ability to reconstruct outbreaks using two outbreak reconstruction tools, the R packages outbreaker and phybreak, and demonstrate that, in agreement with previous observations, genetic sequence data of rapidly evolving pathogens such as RNA viruses can provide valuable information on individual transmission events. Conversely, sequence data of pathogens with lower mean transmission divergence, including Streptococcus pneumoniae, Shigella sonnei and Clostridium difficile, provide little to no information about individual transmission events. Our results highlight the informational limitations of genetic sequence data in certain outbreak scenarios, and demonstrate the need to expand the toolkit of outbreak reconstruction tools to integrate other types of epidemiological data. The increasing availability of genetic sequence data has sparked an interest in using pathogen whole genome sequences to reconstruct the history of individual transmission events PLOS Pathogens | https://doi. 
 Title: When are pathogen genome sequences informative of transmission events?
[A]:
True