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: Background: The detrimental role of viruses has been well described in CF, although the pattern of virus infections has not been investigated in a longitudinal study. The primary aim was to determine the feasibility of fortnightly parent collected swabs in young children with CF. Methods: Children under three years with CF were recruited. Nasal swabs were collected by parents every fortnight and during periods of symptoms over 12 months. Nasal swabs were posted and virus detected using real-time PCR. Results: Only 27% of the patients completed the study to 10 months, although 98% of the swabs returned were adequate for analysis. Mould was observed growing on 23% of the returned swabs. There was no evidence to demonstrate relationships with symptoms and viruses, prolonged symptoms, prolonged shedding or patterns of virus infections. Conclusions: This study highlights the need to further investigate the role of viruses in children with CF using a robust method of frequent collection in children for a longitudinal study, with appropriate storage and shipping techniques to avoid mould growth or other potential contaminants.
Title: Original Article
[A]: False

[Q]: Paragraph: 1. Predicting infectious disease dynamics is a central challenge in disease ecology. Models 36 that can assess which individuals are most at risk of being exposed to a pathogen not only 37 provide valuable insights into disease transmission and dynamics but can also guide 38 management interventions. Constructing such models for wild animal populations, 39 however, is particularly challenging; often only serological data is available on a subset 40 of individuals and non-linear relationships between variables are common. 41 42 2. Here we take advantage of the latest advances in statistical machine learning to construct 43 pathogen-risk models that automatically incorporate complex non-linear relationships 44 with minimal statistical assumptions from ecological data with missing values. Our 45 approach compares multiple machine learning algorithms in a unified environment to 46 find the model with the best predictive performance and uses game theory to better 47 interpret results. We apply this framework on two major pathogens that infect African 48 lions: canine distemper virus (CDV) and feline parvovirus. 49 50 3. Our modelling approach provided enhanced predictive performance compared to more 51 traditional approaches, as well as new insights into disease risks in a wild population. We 52 were able to efficiently capture and visualise strong non-linear patterns, as well as model 53 complex interactions between variables in shaping exposure risk from CDV and feline 54 parvovirus. For example, we found that lions were more likely to be exposed to CDV at a 55 young age but only in low rainfall years. 56 57 . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/569012 doi: bioRxiv preprint 3 4. When combined with our data calibration approach, our framework helped us to answer 58 questions about risk of pathogen exposure which are difficult to address with previous 59 methods. Our framework not only has the potential to aid in predicting disease risk in 60 animal populations, but also can be used to build robust predictive models suitable for 61 other ecological applications such as modelling species distribution or diversity patterns.
Title: How to make more from exposure data? An integrated machine Author Contributions Data Accessibility Statement Running Title Machine learning and pathogen exposure risk
[A]: True

[Q]: Paragraph: This nationwide, prospective cohort study evaluated pulmonary function and radiological sequelae according to infection severity in 73 survivors from the 2015 Middle East respiratory syndrome (MERS) outbreak in Korea. Patients with severe pneumonia in MERS-coronavirus infection had more impaired pulmonary function than those with no or mild pneumonia at the 1-year follow-up, which was compatible with the radiological sequelae. Severe pneumonia significantly impairs pulmonary function and makes long radiological sequelae in MERS. The 2015 outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) infection in the Republic of Korea developed from a traveler returning from the Middle East, 1 which is the largest outbreak outside of the Arabian Peninsula to date. This unprecedented nationwide outbreak resulted in 186 laboratory-confirmed cases with 38 fatalities and > 16,000 individuals being quarantined. 2-4 During the outbreak, a comprehensive screening test including MERS-CoV real-time reverse transcription polymerase chain reaction (rRT-PCR) was performed in all possible contactors to prevent further spread of the disease. Positive MERS-CoV rRT-PCR findings were observed in patients with no or mild symptoms, who were also subjected to epidemiological investigation and follow-up. 1 There have been many reports of long-term sequelae of severe acute respiratory syndrome (SARS), 5-10 but to the best of our knowledge no report has addressed long-term sequelae in
Title: Brief Communication Correlation between Pneumonia Severity and Pulmonary Complications in Middle East Respiratory Syndrome
[A]:
False