In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Example Input: Rift Valley fever virus (RVFV) (genus Phlebovirus, family Bunyaviridae) is a negative-stranded RNA virus with a tripartite genome. RVFV is transmitted by mosquitoes and causes fever and severe hemorrhagic illness among humans, and fever and high rates of abortions in livestock. A nonstructural RVFV NSs protein inhibits the transcription of host mRNAs, including interferon-b mRNA, and is a major virulence factor. The present study explored a novel function of the RVFV NSs protein by testing the replication of RVFV lacking the NSs gene in the presence of actinomycin D (ActD) or a-amanitin, both of which served as a surrogate of the host mRNA synthesis suppression function of the NSs. In the presence of the hosttranscriptional inhibitors, the replication of RVFV lacking the NSs protein, but not that carrying NSs, induced doublestranded RNA-dependent protein kinase (PKR)-mediated eukaryotic initiation factor (eIF)2a phosphorylation, leading to the suppression of host and viral protein translation. RVFV NSs promoted post-transcriptional downregulation of PKR early in the course of the infection and suppressed the phosphorylated eIF2a accumulation. These data suggested that a combination of RVFV replication and NSs-induced host transcriptional suppression induces PKR-mediated eIF2a phosphorylation, while the NSs facilitates efficient viral translation by downregulating PKR and inhibiting PKR-mediated eIF2a phosphorylation. Thus, the two distinct functions of the NSs, i.e., the suppression of host transcription, including that of type I interferon mRNAs, and the downregulation of PKR, work together to prevent host innate antiviral functions, allowing efficient replication and survival of RVFV in infected mammalian hosts.
Example Output: Rift Valley Fever Virus NSs Protein Promotes Post-Transcriptional Downregulation of Protein Kinase PKR and Inhibits eIF2a Phosphorylation

Example Input: 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.
Example Output: 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 Input: Theoretically, there are several ways of preventing the common cold: quarantine, immunisation (or vaccination); early treatment of effected individuals; or physical barriers to reduce transmission. All these methods can be dismissed after considering the epidemiology of the common cold, apart from the last. Evidence for effectiveness for physical barriers (which include masks to reduce aerosol transmission; handwashing; and gloves and gowns) come from a variety of empirical studies. The chance of bias for these studies is variable, but we can conclude that all of these barrier methods have important potential for preventing transmission of the common cold, although some methods will not be acceptable to the community currently.
Example Output:
Common Cold 211 Interventions to prevent transmission of the common cold