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: Coronaviruses (CoVs) are positive-sense single-stranded RNA viruses and contain the largest known RNA genomes, ranging from 27 to 32 kilobases in length. CoVs are capable of transspecies movement as evidenced by the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) epidemic in 2002-2003 [1,2]. Additionally, the emergence of Middle East Respiratory Syndrome coronavirus (MERS-CoV) in 2012 demonstrates that CoVs continue to cause severe and lethal human disease [3] . Exactly how CoVs maintain the integrity of their large genomes while generating the population diversity required for emergence and adaptation has been a major question in RNA virology. The discovery of 39-to-59 exoribonuclease (ExoN) activity within CoV nonstructural protein 14 (nsp14-ExoN), which is critical for CoV high-fidelity replication, has challenged the long-held paradigm that RNA viruses cannot proofread and raises the possibility of an entirely new model for how RNA viruses regulate replication fidelity. We will summarize: 1) the data supporting proofreading during CoV replication; 2) the possibility of a multi-protein fidelity complex, using E. coli DNA polymerase III as a conceptual framework; and 3) the promise of genetic and therapeutic interference with fidelity regulation as an approach for attenuation and treatment of CoVs.
Title: Coronaviruses as DNA Wannabes: A New Model for the Regulation of RNA Virus Replication Fidelity

A: True
****
Q: Paragraph: Despite being simple eukaryotic organisms, the yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe have been widely used as a model to study human pathologies and the replication of human, animal, and plant viruses, as well as the function of individual viral proteins. The complete genome of S. cerevisiae was the first of eukaryotic origin to be sequenced and contains about 6,000 genes. More than 75% of the genes have an assigned function, while more than 40% share conserved sequences with known or predicted human genes. This strong homology has allowed the function of human orthologs to be unveiled starting from the data obtained in yeast. RNA plant viruses were the first to be studied in yeast. In this paper, we focus on the use of the yeast model to study the function of the proteins of human immunodeficiency virus type 1 (HIV-1) and the search for its cellular partners. This human retrovirus is the cause of AIDS. The WHO estimates that there are 33.4 million people worldwide living with HIV/AIDS, with 2.7 million new HIV infections per year and 2.0 million annual deaths due to AIDS. Current therapy is able to control the disease but there is no permanent cure or a vaccine. By using yeast, it is possible to dissect the function of some HIV-1 proteins and discover new cellular factors common to this simple cell and humans that may become potential therapeutic targets, leading to a long-lasting treatment for AIDS.
Title: Yeast and the AIDS Virus: The Odd Couple

A: False
****
Q: Paragraph: Backgrounds: In December 2019, a novel coronavirus (COVID-19) pneumonia hit Wuhan, Hubei Province, China and spread to the rest of China and overseas. The emergence of this virus coincided with the Spring Festival Travel Rush in China. It is possible to estimate total number of cases of COVID-19 in Wuhan, by 23 January 2020, given the cases reported in other cities and population flow data between cities. Methods: We built a model to estimate the total number of cases in Wuhan by 23 January 2020, based on the number of cases detected outside Wuhan city in China, with the assumption that if the same screening effort used in other cities applied in Wuhan. We employed population flow data from different sources between Wuhan and other cities/regions by 23 January 2020. The number of total cases was determined by the maximum log likelihood estimation. Findings: From overall cities/regions data, we predicted 1326 (95% CI: 1177, 1484), 1151 (95% CI: 1018, 1292) and 5277 (95% CI: 4732, 5859) as total cases in Wuhan by 23 January 2020, based on different source of data from Changjiang Daily newspaper, Tencent, and Baidu. From separate cities/regions data, we estimated 1059 (95% CI: 918, 1209), 5214 (95% CI: 4659, 5808) as total cases in Wuhan in Wuhan by 23 January 2020, based on different sources of population flow data from Tencent and Baidu. Conclusion: Sources of population follow data and methods impact the estimates of local cases in Wuhan before city lock down.
Title: Estimation of local novel coronavirus (COVID-19) cases in Wuhan, China from off-site reported cases and population flow data from different sources

A:
True
****