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.
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Question: Coronaviruses strains 229E and OC43 have been associated with various respiratory illnesses ranging from the self-resolving common cold to severe pneumonia. Although chronic underlying conditions are major determinants of severe respiratory virus infections, few data about coronavirus-related pneumonia in immunocompromised patients are available. Here we report 2 well-documented cases of pneumonia related to coronavirus 229E, each with a different clinical presentation. Diagnosis was made on the basis of viral culture and electron microscopy findings that exhibited typical crown-like particles and through amplification of the viral genome by reverse transcriptase-polymerase chain reaction. On the basis of this report, coronaviruses should be considered as potential causative microorganisms of pneumonia in immunocompromised patients.

Answer: Coronavirus 229E-Related Pneumonia in Immunocompromised Patients


Question: Understanding the causes of infectious disease to facilitate better control requires observational and experimental studies. Often these must be conducted at many scales such as at the molecular, cellular, organism, and population level. Studies need to consider both intrinsic and extrinsic factors affecting the pathogen/host interaction. They also require a combination of study methods covered by disciplines such as pathology, epidemiology, microbiology, and ecology. Therefore, it is important that disciplines work together when designing and conducting studies. Finally, we need to integrate and interpret data across levels and disciplines to better formulate control strategies. This requires another group of specialists with broad crossdisciplinary training in epidemiology and an ability to readily work with others.

Answer: Determining Causality and Controlling Disease is Based on Collaborative Research involving Multidisciplinary Approaches


Question: Risk indicators viral load (ORF1ab Ct), lymphocyte percentage (LYM%), C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT) and lactic acid (LA) in COVID-19 patients have been proposed in recent studies. However, the predictive effects of those indicators on disease classification and prognosis remains largely unknown. We dynamically measured those reported indicators in 132 cases of COVID-19 patients including the moderate-cured (moderated and cured), severe-cured (severe and cured) and critically ill (died). Our data showed that CRP, PCT, IL-6, LYM%, lactic acid and viral load could predict prognosis and guide classification of COVID-19 patients in different degrees. CRP, IL-6 and LYM% were more effective than other three factors in predicting prognosis. For disease classification, CRP and LYM% were sensitive in identifying the types between critically ill and severe (or moderate). Notably, among the investigated factors, LYM% was the only one that could distinguish between the severe and moderate types. Collectively, we concluded that LYM% was the most sensitive and reliable predictor for disease typing and prognosis. During the COVID-19 pandemic, the precise classification and prognosis prediction are critical for saving the insufficient medical resources, stratified treatment and improving the survival rate of critically ill patients. We recommend that LYM% be used independently or in combination with other indicators in the management of COVID-19.

Answer:
Validation of reported risk factors for disease classification and prognosis in COVID-19: a descriptive and retrospective study