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.

Ex Input:
Background: Porcine epidemic diarrhea virus (PEDV) is emerging as a pathogenic coronavirus that causes a huge economic burden to the swine industry. Interaction of the viral spike (S) surface glycoprotein with the host cell receptor is recognized as the first step of infection and is the main determinant of virus tropism. The mechanisms by which neutralizing antibodies inhibit PEDV have not been defined. Isolating PEDV neutralizing antibodies are crucial to identifying the receptor-binding domains of the viral spike and elucidating the mechanism of protection against PEDV infection. Methods: B cell hybridoma technique was used to generate hybridoma cells that secrete specific antibodies. E.coli prokaryotic expression system and Bac-to-Bac expression system were used to identify the target protein of each monoclonal antibody. qPCR was performed to analyze PEDV binding to Vero E6 cells with neutralizing antibody. Results: We identified 10 monoclonal antibodies using hybridoma technology. Remarkably, 4 mAbs (designed 2G8, 2B11, 3D9, 1E3) neutralized virus infection potently, of which 2B11 and 1E3 targeted the conformational epitope of the PEDV S protein. qPCR results showed that both 2B11 and 2G8 blocked virus entry into Vero cells. Conclusion: The data suggested that PEDV neutralizing antibody inhibited virus infection by binding to infectious virions, which could work as a tool to find the receptor-binding domains.

Ex Output:
Neutralizing antibodies against porcine epidemic diarrhea virus block virus attachment and internalization


Ex Input:
In the current COVID-19 crisis, the US and many countries in the world are suffering acute shortages of modern ventilators to care for desperately ill patients. Since modern ICU ventilators are powerful devices that can deliver very high gas flow rates and pressures, multiple physicians have attempted to ventilate more than one patient on a single ventilatorso-called "vent splitting". Early applications of this approach have utilized simple concatenations of ventilator tubing and T-pieces, to provide flow to more than one patient. Additional approaches using custom flow splitters -sometimes made using 3D printing technologies -have also advanced into the clinic with FDA approval. However, heretofore there has been less progress made on controlling individual ventilatory pressures for patients with severe lung disease. Given the inherent variability and instability of lung compliance amongst patients with COVID-19, there remains an important need to provide a means of extending ventilator usefulness to more than one patient, but in a way that provides more tailored pressures that can be titrated over time. In this descriptive report, we provide the basis for a ventilator circuit that can support two patients with individualized peak inspiratory and end-expiratory pressures. The circuit is comprised of exclusively "off the shelf" materials and is inexpensive to produce. The circuit can be used with typical ICU ventilators, and with anesthesia ventilators used in operating rooms. Inspiratory and end-expiratory pressures for each patient can be titrated over time, without changes for one patient affecting the ventilation parameters of the other patient. Using in-line spirometry, individual tidal volumes can be measured for each patient. This Pressure-Regulated Ventilator Splitting (PReVentS) Yale University protocol operates under a pressure-control ventilatory mode, and may function optimally when patients are not triggering breaths from the ventilator. This method has been tested thus far only in the laboratory with mock lungs, and has not yet been deployed in animals or in patients. However, given the novelty and potential utility of this approach, we deemed it appropriate to provide this information to the broader critical care community at the present time. In coming days and weeks, we will continue to characterize and refine this approach, using large animal models and proof-of-principle human studies.

Ex Output:
Pressure-Regulated Ventilator Splitting (PReVentS) - A COVID-19 Response Paradigm from Yale University


Ex Input:
Infectious diseases exert a large and in many contexts growing burden on human health, but violate most of the assumptions of classical epidemiological statistics and hence require a mathematically sophisticated approach. Viral shedding data are collected during human studies-either where volunteers are infected with a disease or where existing cases are recruited-in which the levels of live virus produced over time are measured. These have traditionally been difficult to analyse due to strong, complex correlations between parameters. Here, we show how a Bayesian approach to the inverse problem together with modern Markov chain Monte Carlo algorithms based on information geometry can overcome these difficulties and yield insights into the disease dynamics of two of the most prevalent human pathogens-influenza and norovirus-as well as Ebola virus disease.

Ex Output:

Bayesian uncertainty quantification for transmissibility of influenza, norovirus and Ebola using information geometry