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".

Example Input: Paragraph: We have previously reported that the 3C-like proteinase of the coronavirus infectious bronchitis virus (IBV) is responsible for processing of the 1a and 1a/1b polyproteins to three mature products of 24, 10, and 100 kDa (Liu et al., 1994 (Liu et al., , 1997 Ng and Liu, 1998) . The C-terminal cleavage site of the 100-kDa protein was defined to be the Q 891(1b) -S 892(1b) dipeptide bond encoded by nucleotides 15, 129 to 15, 134 (Liu and Brown, 1995). In this report, other cleavage sites of the 3C-like proteinase in the polyprotein encoded by the ORF 1b region were mapped by coexpression, deletion, and site-directed mutagenesis studies. Using two ORF 1b-specific antisera, V58 and V17, three more Q-S(G) dipeptide bonds, encoded by nucleotides 16,929 to 16,934, 18,492 to 18,497, and 19,506 to 19,511, respectively, were demonstrated to be the cleavage sites of the 3C-like proteinase. Cleavage at these four positions would result in the release of four mature products with molecular masses of approximately 68, 58, 39, and 35 kDa. Among them, the 39-and 35-kDa proteins were specifically identified in IBV-infected cells. Taken together with the 100-kDa protein previously identified, these results suggest that the ORF 1b region of IBV mRNA1 may be able to encode five mature products. 
 Title: Proteolytic Mapping of the Coronavirus Infectious Bronchitis Virus 1b Polyprotein: Evidence for the Presence of Four Cleavage Sites of the 3C-like Proteinase and Identification of Two Novel Cleavage Products
Example Output: False

Example Input: Paragraph: Formalin-inactivated Japanese encephalitis virus (JEV) vaccines are widely available, but the effects of formalin inactivation on the antigenic structure of JEV and the profile of antibodies elicited after vaccination are not well understood. We used a panel of monoclonal antibodies (MAbs) to map the antigenic structure of live JEV virus, untreated control virus (UCV), formalin-inactivated commercial vaccine (FICV), and formalin-inactivated virus (FIV). The binding activity of T16 MAb against Nakayama-derived FICV and several strains of FIV was significantly lower compared to live virus and UCV. T16 MAb, a weakly neutralizing JEV serocomplex antibody, was found to inhibit JEV infection at the post-attachment step. The T16 epitope was mapped to amino acids 329, 331, and 389 within domain III (EDIII) of the envelope (E) glycoprotein. When we explored the effect of formalin inactivation on the immunogenicity of JEV, we found that Nakayama-derived FICV, FIV, and UCV all exhibited similar immunogenicity in a mouse model, inducing anti-JEV and anti-EDII 101/ 106/107 epitope-specific antibodies. However, the EDIII 329/331/389 epitope-specific IgG antibody and neutralizing antibody titers were significantly lower for FICV-immunized and FIV-immunized mouse serum than for UCV-immunized. Formalin inactivation seems to alter the antigenic structure of the E protein, which may reduce the potency of commercially available JEV vaccines. Virus inactivation by H 2 O 2 , but not by UV or by short-duration and higher temperature formalin treatment, is able to maintain the antigenic structure of the JEV E protein. Thus, an alternative inactivation method, such as H 2 O 2 , which is able to maintain the integrity of the E protein may be essential to improving the potency of inactivated JEV vaccines. We demonstrated that formalin inactivation of Japanese encephalitis virus (JEV) alters the antigenic structure of the JEV envelope glycoprotein (E), in particular an epitope in domain III, and that this reduces the ability of the inactivated vaccine to elicit protective neutralizing antibodies. Ours and others' previous studies have highlighted the importance of improving the immunogenicity of genotype III (GIII)-derived JEV vaccine in order to provide cross-protection against genotype I (GI) viruses, which are emerging and replacing GIII viruses in many JEV-endemic regions. Encouraging the wide use of live-attenuated or chimeric vaccines, such as SA14-14-2 or yellow-fever 17D/JEV vaccines, respectively, developing GI virus-derived inactivated or premembrane/E-containing, noninfectious virus-like particle (VLP) vaccines are two other possible ways to address this potential problem. In this exploratory study, we highlight an alternative inactivation method, such as H 2 O 2 treatment, which may improve the antigenic stability and immunogenicity of JEV. Japanese encephalitis virus (JEV), the most important etiological agent of viral encephalitis in Asian countries, causes regular outbreaks in eastern and southeastern Asia, India, and more recently in Australia [1,2]. Annually, 30,000 to 50,000 Japanese encephalitis (JE)-confirmed cases are reported in the JEV endemic areas, and 20% to 60% of symptomatic CNS infections are fatal [3-6]; 25% to 50% of symptomatic survivors have long-term neurological sequelae [7] . Asymptomatic JEV infection is about a thousand-fold higher than confirmed cases [8] [9] [10] . JEV is transmitted by virus-infected Culex mosquitos from inapparently infected viremic-amplifying hosts such as pigs or aquatic birds to symptomatic accidental hosts, such as horses and humans. Migratory birds have been implicated as the source of virus been introduced into new geographic regions, and associated with JE epidemics and replacement of genotype III (GIII)with genotype I (GI)-JEV from southeast Asia to east Asia [11, 12] . The genome of JEV consists of a~11-kb, positive-sense, single-stranded RNA, which is translated and processed by viral and host proteases to three structural proteins-capsid, precursor membrane/membrane protein (prM/M) and envelope glycoprotein (E)-and seven nonstructural proteins (NS)-NS1, 2A, 2B, 3, 4A, 4B and 5. The mature virion consists of 180 E proteins forming 90 homodimers and 180 processed M proteins. The immature virion is formed by 60 E and prM hetero-trimers [13, 14] . E protein is the most critical protein eliciting protective immunity in hosts after viral infection, offering critical protection in mice [15] and inducing protective antibodies in recovering humans [16] . The ectodomain of E protein can be separated into three structural domains: E domain I (EDI) to III (EDIII). The fusion peptide in EDII elicits group cross-reactive non-or low-neutralizing antibodies; EDIII, the receptor-binding domain, elicits potent type-specific neutralizing antibodies; and EDI, the center domain connecting EDII and EDIII, elicits complex cross-reactive high-or non-neutralizing antibodies after viral infection [16] [17] [18] . Vaccination remains the most effective strategy to control JE epidemics [19]. Live-attenuated and formalin-inactivated JEV vaccines are available for human use, but only live-attenuated vaccines are available for domestic animals, such as swine and horses. The first generation inactivated JEV vaccine, developed by BIKEN in Japan, was the mouse brain-derived, formalin-inactivated GIII Nakayama strain; manufacture of this vaccine has ceased since 2005 because of undesirable adverse effects [20] . Second generation tissue culture-derived, formalin-Formalin Inactivation Alters the Immunogenicity of JEV PLOS Neglected Tropical Diseases | 
 Title: Formalin Inactivation of Japanese Encephalitis Virus Vaccine Alters the Antigenicity and Immunogenicity of a Neutralization Epitope in Envelope Protein Domain III
Example Output: False

Example Input: Paragraph: Purpose: COVID-19 has become global threaten. CT acts as an important method of 60 diagnosis. However, human-based interpretation of CT imaging is time consuming. 61 More than that, substantial inter-observer-variation cannot be ignored. We aim at 62 developing a diagnostic tool for artificial intelligence (AI)-based classification of CT 63 images for recognizing COVID-19 and other common infectious diseases of the lung. 64 Experimental Design: In this study, images were retrospectively collected and 65 prospectively analyzed using machine learning. CT scan images of the lung that show 66 or do not show COVID-19 were used to train and validate a classification framework 67 based on convolutional neural network. Five conditions including COVID-19 68 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, pulmonary 69 tuberculosis, and normal lung were evaluated. Training and validation set of images 70 were collected from Wuhan Jin Yin-Tan Hospital whereas test set of images were 71 collected from Zhongshan Hospital Xiamen University and the fifth Hospital of 72 Wuhan. 73 Results: Accuracy, sensitivity, and specificity of the AI framework were reported. For 74 test dataset, accuracies for recognizing normal lung, COVID-19 pneumonia, 75 non-COVID-19 viral pneumonia, bacterial pneumonia, and pulmonary tuberculosis 76 were 99.4%, 98.8%, 98.5%, 98.3%, and 98.6%, respectively. For the test dataset, 77 accuracy, sensitivity, specificity, PPV, and NPV of recognizing COVID-19 were 78 98.8%, 98.2%, 98.9%, 94.5%, and 99.7%, respectively. 79 All rights reserved. No reuse allowed without permission. the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 
 Title: Deep Learning-Based Recognizing COVID-19 Deep Learning-Based Recognizing COVID-19 and other Common Infectious Diseases of the Lung by Chest CT 2 Scan Images
Example Output:
False