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.

Globally, there are a number of emerging pathogens. For most, there are no licensed vaccines available for human use, although there is ongoing research and development. However, given the extensive and increasing list of emerging pathogens and the investment required to bring vaccines into clinical use, the task is huge. Overlaid on this task is the risk of anti-microbial resistance (AMR) acquisition by micro-organisms which can endow a relatively harmless organism with pathogenic potential. Furthermore, climate change also introduces a challenge by causing some of the insect vectors and environmental conditions prevalent in tropical regions to begin to spread out from these traditional areas, thus increasing the risk of migration of zoonotic disease. Vaccination provides a defence against these emerging pathogens. However, vaccines for pathogens which cause severe, but occasional, disease outbreaks in endemic pockets have suffered from a lack of commercial incentive for development to a clinical standard, encompassing Phase III clinical trials for efficacy. An alternative is to develop such vaccines to request US Emergency Use Authorization (EUA), or equivalent status in the United States, Canada and the European Union, making use of a considerable number of regulatory mechanisms that are available prior to licensing. This review covers the status of vaccine development for some of the emerging pathogens, the hurdles that need to be overcome to achieve EUA or an equivalent regional or national status and how these considerations may impact vaccine development for the future, such that a more comprehensive stockpile of promising vaccines can be achieved.
Vaccines for emerging pathogens: prospects for licensure

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.
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

Background: Bovine rotavirus (BRV) is a non-enveloped dsRNA virus that cause neonatal calf diarrhea. Lipid rafts are cholesterol-enrich membrane mircodomains that play a vital role in many cellular processes. In this study, the effect of cellular cholesterol depletion on infection of MA-104 cells with bovine rotavirus was investigated. Results: We demonstrated that cholesterol depletion of the plasma membrane by MβCD had no effect on BRV binding to cells but significantly impaired BRV entry in a dose-dependent manner and the effect was partially reversed by addition of exogenous cholesterol, suggesting the reduction of BRV infection by MβCD was specifically due to cholesterol depletion. Cholesterol depletion after virus entry did not reduce BRV replication, whereas affected virus assembly. Conclusions: Taken together, our results demonstrate that cell membrane cholesterol is essential to BRV infectivity.

Critical role of cellular cholesterol in bovine rotavirus infection