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: Feline coronavirus (FCoV) is common among cats living indoors in groups. In about 10% of infected cats, a potentially lethal disease, feline infectious peritonitis (FIP) occurs. Virus transmission is faecal-oral. Mutian®️ Xraphconn (Mutian X) is a product marketed to treat cats with FIP but is also being used to stop virus shedding, although no clear guidelines exist for its use for this purpose. The aim of this study was to establish the minimum dose and treatment duration required to ensure viral clearance from the faeces of asymptomatic virus-shedding cats. In five multicat households, 29 cats naturally infected with FCoV and actively shedding virus in the faeces were given Mutian X pills. Virus shedding was monitored using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) controlled for faecal inhibitors to ensure sensitivity. Mutian X given orally cleared the virus in 29 cats; although four cats required a repeated course to finally stop virus shedding. A dose of 4 mg/kg q24 h for four days was found to be the optimal treatment protocol: 2 mg/kg cleared only 80% of cats. Posttreatment using a sensitive RT-qPCR test was essential to ensure that virus clearance had been achieved, since failure to clear even one cat can result in re-infection of the others. Records of virus shedding by cats before treatment provided a retrospective control: significantly more cats stopped shedding virus after Mutian X than recovered from infection during the control period (p < .00001). This is the first report of the successful elimination of faecal FCoV shedding in chronically infected cats.
Title: Oral Mutian®️X stopped faecal feline coronavirus shedding by naturally infected cats

Answer: True

Question: Paragraph: Co-infections by multiple pathogens have important implications in many aspects of health, epidemiology and evolution. However, how to disentangle the non-linear dynamics of the immune response when two infections take place at the same time is largely unexplored. Using data sets of the immune response during influenza-pneumococcal coinfection in mice, we employ here topological data analysis to simplify and visualise high dimensional data sets. We identified persistent shapes of the simplicial complexes of the data in the three infection scenarios: single viral infection, single bacterial infection, and co-infection. The immune response was found to be distinct for each of the infection scenarios and we uncovered that the immune response during the co-infection has three phases and two transition points. During the first phase, its dynamics is inherited from its response to the primary (viral) infection. The immune response has an early shift (few hours post coinfection) and then modulates its response to react against the secondary (bacterial) infection. Between 18 and 26 h post co-infection the nature of the immune response changes again and does no longer resembles either of the single infection scenarios.
Title: Topological data analysis to model the shape of immune responses during co-infections

Answer: True

Question: Paragraph: The changing spatiotemporal patterns of the individual susceptible-infected-symptomatic-treated-recovered epidemic process and the interactions of information/material flows between regions, along with the 2002-2003 Severe Acute Respiratory Syndrome (SARS) epidemiological investigation data in mainland China, including three typical locations of individuals (working unit/home address, onset location and reporting unit), are used to define the in-out flow of the SARS epidemic spread. Moreover, the input/output transmission networks of the SARS epidemic are built according to the definition of in-out flow. The spatiotemporal distribution of the SARS in-out flow, spatial distribution and temporal change of node characteristic parameters, and the structural characteristics of the SARS transmission networks are comprehensively and systematically explored. The results show that (1) Beijing and Guangdong had the highest risk of self-spread and output cases, and prevention/control measures directed toward self-spread cases in Beijing should have focused on the later period of the SARS epidemic; (2) the SARS transmission networks in mainland China had significant clustering characteristics, with two clustering areas of output cases centered in Beijing and Guangdong; (3) Guangdong was the original source of the SARS epidemic, and while the infected cases of most other provinces occurred mainly during the early period, there was no significant spread to the surrounding provinces; in contrast, although the input/output interactions between Beijing and the other provinces countrywide began during the mid-late epidemic period, SARS in Beijing showed a significant capacity for spatial spreading; (4) Guangdong had a significant range of spatial spreading throughout the entire epidemic period, while Beijing and its surrounding provinces formed a separate, significant range of high-risk spreading during the mid-late period; especially in late period, the influence range of Beijing's neighboring provinces, such as Hebei, was even slightly larger than that of Beijing; and (5) the input network had a low-intensity spread capacity and middle-level influence range, while the output network had an extensive high-intensity spread capacity and influence range that covered almost the entire country, and this spread and influence indicated that significant clustering characteristics increased gradually. This analysis of the epidemic in-out flow and its corresponding transmission network helps reveal the potential spatiotemporal characteristics and evolvement mechanism of the SARS epidemic and provides more effective theoretical support for prevention and control measures. SARS, epidemic spread, in-out flow, transmission network, characteristic parameter Citation: Hu B S, Gong J H, Sun J, et al. Exploring the epidemic transmission network of SARS in-out flow in mainland China.
Title: Article Geography Exploring the epidemic transmission network of SARS in-out flow in mainland China

Answer:
False