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".

Paragraph: The World Health Organization (WHO) has declared the 2019 novel coronavirus (2019-nCoV) infection outbreak a global health emergency. Currently, there is no effective anti-2019-nCoV medication. The sequence identity of the 3CL proteases of 2019-nCoV and SARS is 96%, which provides a sound foundation for structural-based drug repositioning (SBDR). Based on a SARS 3CL protease X-ray crystal structure, we construct a 3D homology structure of 2019-nCoV 3CL protease. Based on this structure and existing experimental datasets for SARS 3CL protease inhibitors, we develop an SBDR model based on machine learning and mathematics to screen 1465 drugs in the DrugBank that have been approved by the U.S. Food and Drug Administration (FDA). We found that many FDA approved drugs are potentially highly potent to 2019-nCoV.
Title: Potentially highly potent drugs for 2019-nCoV
False

Paragraph: LETTERS that the quantitative assessment of the effectiveness of public health intervention measures for SARS is a difficult task for modelers. To make models useful for assessing the effects of specific intervention measures and for predicting the future dynamics during an ongoing epidemic, we need improved knowledge on the transmission mechanisms, pathogenesis, and the epidemiologic determinants of the spread of the virus. Any retrospective analysis of the 2003 SARS epidemic that improves our knowledge of SARS epidemiology is welcome.
Title: SARS epi-demiology and cumulative case curve
False

Paragraph: Background. Despite the high burden of respiratory infection and the importance of early and accurate diagnosis, there is no simple diagnostic test to rule in viral infection as a cause of respiratory symptoms. Methods. We performed RNA sequencing on human nasal epithelial cells following stimulation of the intracellular viral recognition receptor RIG-I. Next, we evaluated whether measuring identified host mRNAs and proteins from patient nasopharyngeal swabs could predict the presence of a respiratory virus in the sample. Results. Our first study showed that a signature of 3 mRNAs, CXCL10, IFIT2, and OASL, predicted respiratory virus detection with an accuracy of 97% (95% confidence interval [CI], 0.9-1.0), and identified proteins correlating with virus detection. In a second study, elevated CXCL11 or CXCL10 protein levels identified samples containing respiratory viruses, including viruses not on the initial test panel. Overall area under the curve (AUC) values were: CXCL11 AUC = 0.901 (95% CI, 0.86-0.94); CXCL10 AUC = 0.85 (95% CI, 0.80-0.91). Conclusions. Host antiviral mRNAs and single host proteins detectable using nasopharyngeal swabs accurately predict the presence of viral infection. This approach holds promise for developing rapid, cost-effective tests to improve management of patients with respiratory illnesses.
Title: Antiviral Response in the Nasopharynx Identifies Patients With Respiratory Virus Infection
True