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: The genome of coronaviruses contains structural and non-structural genes, including several so-called accessory genes. All group 1b coronaviruses encode a single accessory protein between the spike and envelope genes, except for human coronavirus (HCoV) 229E. The prototype virus has a split gene, encoding the putative ORF4a and ORF4b proteins. To determine whether primary HCoV-229E isolates exhibit this unusual genome organization, we analyzed the ORF4a/b region of five current clinical isolates from The Netherlands and three early isolates collected at the Common Cold Unit (CCU) in Salisbury, UK. Results: All Dutch isolates were identical in the ORF4a/b region at amino acid level. All CCU isolates are only 98% identical to the Dutch isolates at the nucleotide level, but more closely related to the prototype HCoV-229E (>98%). Remarkably, our analyses revealed that the laboratory adapted, prototype HCoV-229E has a 2-nucleotide deletion in the ORF4a/b region, whereas all clinical isolates carry a single ORF, 660 nt in size, encoding a single protein of 219 amino acids, which is a homologue of the ORF3 proteins encoded by HCoV-NL63 and PEDV. Conclusion: Thus, the genome organization of the group 1b coronaviruses HCoV-NL63, PEDV and HCoV-229E is identical. It is possible that extensive culturing of the HCoV-229E laboratory strain resulted in truncation of ORF4. This may indicate that the protein is not essential in cell culture, but the highly conserved amino acid sequence of the ORF4 protein among clinical isolates suggests that the protein plays an important role in vivo. 
 Title: Virology Journal Human coronavirus 229E encodes a single ORF4 protein between the spike and the envelope genes
[A]: False


[Q]: 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
[A]: False


[Q]: Paragraph: ELISAs provide a valuable tool in the detection and diagnosis of virus infection. The ability to produce recombinant viral proteins will ensure that future ELISAs are safe, specific and rapid. This latter point being the most crucial advantage in that even if a virus cannot be cultured, provided gene sequence is available, it is possible to rapidly respond to emerging viruses and new viral strains of existing pathogens. Indeed, ELISAs based on peptides (corresponding to epitopes) also hold great promise, as in this case no cloning or expression of a recombinant protein is required. Both recombinant protein and peptide based systems lend themselves to large scale production and purification. These approaches can also be used to distinguish recombinant vaccines from parental or wild type viruses. 
 Title: Recombinant viral proteins for use in diagnostic ELISAs to detect virus infection
[A]:
True