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: Interferon lambda 4 (IFNλ4) has been recently known and studied for its role in hepatitis C virus (HCV) infection, but its clinical potential is significantly hampered due to its poor expression in vitro. Our study reports the successful production of IFNλ4 from a mammalian cell line through a glycoengineering and structure-based approach. We introduced de novo N-glycosylation of IFNλ4, guided by structural analysis, and produced IFNλ4 variants in Expi293F that displayed improved expression and potency. To preserve the structure and functionality of IFNλ4, the model structure of the IFNλ4 signaling complex was analyzed and the N-glycosylation candidate sites were selected. The receptor binding activity of engineered IFNλ4 variants and their receptormediated signaling pathway were similar to the E. coli version of IFNλ4 (eIFNλ4), while the antiviral activity and induction levels of interferon-stimulated gene (ISG) were all more robust in our variants. Our engineered IFNλ4 variants may be further developed for clinical applications and utilized in basic research to decipher the immunological roles of IFNλ4. Previously, the transient expression of wild-type IFNλ4 in mammalian cells failed to produce significant amounts of recombinant

Output: Structure-based glycoengineering of interferon lambda 4 enhances its productivity and anti-viral potency


Input: Consider Input: Objectives: We compared the expelled air dispersion distances during coughing from a human patient simulator (HPS) lying at 45u with and without wearing a surgical mask or N95 mask in a negative pressure isolation room. Methods: Airflow was marked with intrapulmonary smoke. Coughing bouts were generated by short bursts of oxygen flow at 650, 320, and 220L/min to simulate normal, mild and poor coughing efforts, respectively. The coughing jet was revealed by laser light-sheet and images were captured by high definition video. Smoke concentration in the plume was estimated from the light scattered by smoke particles. Significant exposure was arbitrarily defined where there was $ 20% of normalized smoke concentration. Results: During normal cough, expelled air dispersion distances were 68, 30 and 15 cm along the median sagittal plane when the HPS wore no mask, a surgical mask and a N95 mask, respectively. In moderate lung injury, the corresponding air dispersion distances for mild coughing efforts were reduced to 55, 27 and 14 cm, respectively, p , 0.001. The distances were reduced to 30, 24 and 12 cm, respectively during poor coughing effort as in severe lung injury. Lateral dispersion distances during normal cough were 0, 28 and 15 cm when the HPS wore no mask, a surgical mask and a N95 mask, respectively. Conclusions: Normal cough produced a turbulent jet about 0.7 m towards the end of the bed from the recumbent subject. N95 mask was more effective than surgical mask in preventing expelled air leakage during coughing but there was still significant sideway leakage.

Output: Exhaled Air Dispersion during Coughing with and without Wearing a Surgical or N95 Mask


Input: Consider Input: COVID-19 is spreading all across the globe. Up until March 23, 2020, the confirmed cases in 173 12 countries and regions of the globe had surpassed 346,000, and more than 14,700 deaths had resulted. The 13 confirmed cases outside of China had also reached over 81,000, with over 3,200 deaths. In this study, a 14 Convolutional Neural Network (CNN) was proposed to analyze and predict the number of confirmed cases. 15 Several cities with the most confirmed cases in China were the focus of this study, and a COVID-19 16 forecasting model, based on the CNN deep neural network method, was proposed. To compare the overall 17 efficacies of different algorithms, the indicators of mean absolute error and root mean square error were 18 applied in the experiment of this study. The experiment results indicated that compared with other deep 19 learning methods, the CNN model proposed in this study has the greatest prediction efficacy. The feasibility 20 and practicality of the model in predicting the cumulative number of COVID-19 confirmed cases were also 21 verified in this study. 22


Output: Multiple-Input Deep Convolutional Neural Network Model for COVID-19 Forecasting in China 2