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.
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Question: The prevalence of self-reported preventive behaviors in response to an anticipated local human-to-human H5N1 transmission outbreak and factors associated with such behaviors have not been examined. A random, anonymous, cross-sectional telephone survey of 503 Hong Kong Chinese adults. The public in Hong Kong is likely to adopt self-protective behaviors (e.g., wearing face mask in public venues (73.8%), increasing the frequency of handwashing (86.7%)) and behaviors that protect others (e.g., wearing face masks when experiencing influenza-like illness (ILI, 92.4%), immediately seeking medical consultation (94.2%), making declarations when crossing the border with ILI (87.1%), complying to quarantine policies (88.3%)). Multivariate analyses indicated that factors related to age, full-time employment, perceived susceptibility, perceived efficacy of preventive measures, perceived higher fatality as compared to SARS, perceived chance of a major local outbreak, and being worried about self/family members contracting the virus were significantly associated with the inclination to adopt self-protective measures. Similar analyses showed that education level, variables related to perceived efficacy, perceived major local outbreak and such were significantly associated with various behaviors directed towards protecting others. In the event of a human-to-human H5N1 outbreak, the public in Hong Kong is likely to adopt preventive measures that may help contain the spread of the virus in the community.

Answer: BMC Infectious Diseases Anticipated and current preventive behaviors in response to an anticipated human-to-human H5N1 epidemic in the Hong Kong Chinese general population


Question: The infection of a novel coronavirus found in Wuhan of China (2019-nCoV) is rapidly spreading, and the incidence rate is increasing worldwide. Due to the lack of effective treatment options for 2019-nCoV, various strategies are being tested in China, including drug repurposing. In this study, we used our pretrained deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI) to identify commercially available drugs that could act on viral proteins of 2019-nCoV. The result showed that atazanavir, an antiretroviral medication used to treat and prevent the human immunodeficiency virus (HIV), is the best chemical compound, showing a inhibitory potency with Kd of 94.94 nM against the 2019-nCoV 3C-like proteinase, followed by efavirenz (199.17 nM), ritonavir (204.05 nM), and dolutegravir (336.91 nM). Interestingly, lopinavir, ritonavir, and darunavir are all designed to target viral proteinases. However, in our prediction, they may also bind to the replication complex components of 2019-nCoV with an inhibitory potency with Kd < 1000 nM. In addition, we also found that several antiviral agents, such as Kaletra, could be used for the treatment of 2019-nCoV, although there is no real-world evidence supporting the prediction. Overall, we suggest that the list of antiviral drugs identified by the MT-DTI model should be considered, when establishing effective treatment strategies for 2019-nCoV.

Answer: China through a drug-target interaction deep learning model


Question: 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.

Answer:
Coronaviruses as DNA Wannabes: A New Model for the Regulation of RNA Virus Replication Fidelity