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.

Input: Consider Input: Human rhinovirus (HRV) remains a leading cause of several human diseases including the common cold. Despite considerable research over the last 60 years, development of an effective vaccine to HRV has been viewed by many as unfeasible due, in part, to the antigenic diversity of circulating HRVs in nature. Over 150 antigenically distinct types of HRV are currently known which span three species: HRV A, HRV B, and HRV C. Early attempts to develop a rhinovirus vaccine have shown that inactivated HRV is capable of serving as a strong immunogen and inducing neutralizing antibodies. Yet, limitations to virus preparation and recovery, continued identification of antigenic variants of HRV, and logistical challenges pertaining to preparing a polyvalent preparation of the magnitude required for true efficacy against circulating rhinoviruses continue to prove a daunting challenge. In this review, we describe HRV biology, antigenic diversity, and past and present advances in HRV vaccine design.

Output: MINI REVIEW Rhinovirus Biology, Antigenic Diversity, and Advancements in the Design of a Human Rhinovirus Vaccine

Input: Consider Input: The response to the novel coronavirus outbreak in China suggests that many of the lessons from the 2003 SARS epidemic have been implemented and the response improved as a consequence. Nevertheless some questions remain and not all lessons have been successful. The national and international response demonstrates the complex link between public health, science and politics when an outbreak threatens to impact on global economies and reputations. The unprecedented measures implemented in China are a bold attempt to control the outbreakwe need to understand their effectiveness to balance costs and benefits for similar events in the future.

Output: Epidemiology and Infection SARS to novel coronavirus -old lessons and new lessons

Input: Consider Input: 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.
Output: China through a drug-target interaction deep learning model