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.

Q: Estimating inhalation dose accurately under realistic conditions can enhance the accuracy of risk assessment. Conventional methods to quantify aerosol concentration that susceptible victims in contaminated environments are exposed to use real time particle counters to measure concentrations in environments without occupancy. Breathing-induced airflow interacts and influences concentration around nostrils or mouth and alter the ultimate exposure. This subject has not yet been systematically studied, particularly under transient emission. In this work, an experimental facility comprising two manikins was designed and fabricated. One of them mimicked realistic breathing, acting as a susceptible victim. Both steady and episodic emissions were generated in an air-conditioned environmental chamber in which two different ventilation schemes were tested. The scaled-dose of the victim under different expiratory velocities and pulmonary ventilation was measured. Inferring from results obtained from comprehensive tests, it can be concluded that breathing has very significant influence on the ultimate dose compared with that without breathing. Majority of results show that breathing reduces inhalation quantity and the reduction magnitude increases with breathing rate. This is attributed to the fact that the exhalation process plays a more significant role in reducing the dose level than the enhanced effect during inhalation period. The higher the breathing rate, the sharper the decline of the resultant concentration would be leading to lower dose. Nevertheless, under low pulmonary ventilation, results show that breathing increases dose marginally. Results also reveals that ventilation scheme also affects the exposure.

A: An experimental study quantifying pulmonary ventilation on inhalation of aerosol under steady and episodic emission
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Q: The Middle-East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic virus that causes severe and often fatal respiratory disease in humans. Efforts to develop antibody-based therapies have focused on neutralizing antibodies that target the receptor binding domain of the viral spike protein thereby blocking receptor binding. Here, we developed a set of human monoclonal antibodies that target functionally distinct domains of the MERS-CoV spike protein. These antibodies belong to six distinct epitope groups and interfere with the three critical entry functions of the MERS-CoV spike protein: sialic acid binding, receptor binding and membrane fusion. Passive immunization with potently as well as with poorly neutralizing antibodies protected mice from lethal MERS-CoV challenge. Collectively, these antibodies offer new ways to gain humoral protection in humans against the emerging MERS-CoV by targeting different spike protein epitopes and functions.

A: Towards a solution to MERS: protective human monoclonal antibodies targeting different domains and functions of the MERS-coronavirus spike glycoprotein
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Q: Virus infection is a complex biological phenomenon for which in vitro experiments provide a uniquely concise view where data is often obtained from a single population of cells, under controlled environmental conditions. Nonetheless, data interpretation and real understanding of viral dynamics is still hampered by the sheer complexity of the various intertwined spatio-temporal processes. In this paper we present a tool to address these issues: a cellular automata model describing critical aspects of in vitro viral infections taking into account spatial characteristics of virus spreading within a culture well. The aim of the model is to understand the key mechanisms of SARS-CoV infection dynamics during the first 24 hours post infection. We interrogate the model using a Latin Hypercube sensitivity analysis to identify which mechanisms are critical to the observed infection of host cells and the release of measured virus particles.

A:
A Simulation Framework to Investigate in vitro Viral Infection Dynamics
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