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.

Bats have been recognized as the natural reservoirs of a large variety of viruses. Special attention has been paid to bat coronaviruses as the two emerging coronaviruses which have caused unexpected human disease outbreaks in the 21st century, Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV), are suggested to be originated from bats. Various species of horseshoe bats in China have been found to harbor genetically diverse SARS-like coronaviruses. Some strains are highly similar to SARS-CoV even in the spike protein and are able to use the same receptor as SARS-CoV for cell entry. On the other hand, diverse coronaviruses phylogenetically related to MERS-CoV have been discovered worldwide in a wide range of bat species, some of which can be classified to the same coronavirus species as MERS-CoV. Coronaviruses genetically related to human coronavirus 229E and NL63 have been detected in bats as well. Moreover, intermediate hosts are believed to play an important role in the transmission and emergence of these coronaviruses from bats to humans. Understanding the bat origin of human coronaviruses is helpful for the prediction and prevention of another pandemic emergence in the future.
Bat origin of human coronaviruses

Background: Adverse events are associated with significant morbidity, mortality and cost in hospitalized patients. Measuring adverse events is necessary for quality improvement, but current detection methods are inaccurate, untimely and expensive. The advent of electronic health records and the development of automated methods for encoding and classifying electronic narrative data, such as natural language processing, offer an opportunity to identify potentially better methods. The objective of this study is to determine the accuracy of using automated methods for detecting three highly prevalent adverse events: a) hospital-acquired pneumonia, b) catheter-associated bloodstream infections, and c) in-hospital falls. Methods/design: This validation study will be conducted at two large Canadian academic health centres: the McGill University Health Centre (MUHC) and The Ottawa Hospital (TOH). The study population consists of all medical, surgical and intensive care unit patients admitted to these centres between 2008 and 2014. An automated detection algorithm will be developed and validated for each of the three adverse events using electronic data extracted from multiple clinical databases. A random sample of MUHC patients will be used to develop the automated detection algorithms (cohort 1, development set). The accuracy of these algorithms will be assessed using chart review as the reference standard. Then, receiver operating characteristic curves will be used to identify optimal cut points for each of the data sources. Multivariate logistic regression and the areas under curve (AUC) will be used to identify the optimal combination of data sources that maximize the accuracy of adverse event detection. The most accurate algorithms will then be validated on a second random sample of MUHC patients (cohort 1, validation set), and accuracy will be measured using chart review as the reference standard. The most accurate algorithms validated at the MUHC will then be applied to TOH data (cohort 2), and their accuracy will be assessed using a reference standard assessment of the medical chart. Discussion: There is a need for more accurate, timely and efficient measures of adverse events in acute care hospitals. This is a critical requirement for evaluating the effectiveness of preventive interventions and for tracking progress in patient safety through time.
Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol

Strand exchange nucleic acid circuitry can be used to transduce isothermal nucleic acid amplification products into signals that can be readable on an off-the-shelf glucometer. Loop-mediated isothermal amplification (LAMP) is limited by the accumulation of non-specific products, but nucleic acid circuitry can be used to probe and distinguish specific amplicons. By combining this high temperature isothermal amplification method with a thermostable invertase, we can directly transduce Middle-East respiratory syndrome coronavirus and Zaire Ebolavirus templates into glucose signals, with a sensitivity as low as 20-100 copies/μ l, equating to atto-molar (or low zepto-mole). Virus from cell lysates and synthetic templates could be readily amplified and detected even in sputum or saliva. An OR gate that coordinately triggered on viral amplicons further guaranteed fail-safe virus detection. The method describes has potential for accelerating point-of-care applications, in that biological samples could be applied to a transducer that would then directly interface with an off-the-shelf, approved medical device. The Middle-East respiratory syndrome coronavirus (MERS-CoV) belongs to the human betacoronavirus family of coronaviruses, which are large positive-stranded RNA viruses whose genomes typically range between ~27 to ~31 kb in size. The first case of MERS-CoV infection was identified in 2012 in a Saudi Arabian patient who died from a severe respiratory illness 1-3 . Since then, the infection has spread globally and through the middle of 2014 had caused 614 laboratory-confirmed cases and 181 deaths 2,4,5 . MERS-CoV is thus one of the most serious emergent viral pathogens since its relative, SARS-CoV 6 . In order to control spreading infections and receive timely treatment, sensitive and specific detection of MERS-CoV at point-of-need or point-of-care is extremely important. While methods such as immunofluorescence assays (targeting MERS-CoV N and S proteins) 7 and real-time reverse transcription polymerase chain reaction (RT-PCR, targeting viral genes in or around ORF1A, ORF1B and upE) have been successfully used for clinical diagnosis 8-10 , these methods are not readily adapted to point-of-care applications. A simple molecular assay for MERS-CoV can potentially be developed by relying on the exquisite sensitivity and extreme simplicity of isothermal amplification reactions 11-16 , such as loop-mediated isothermal amplification (LAMP), which yields up to 10 10 -fold amplification within 10 min to two hours 17,18 . Unfortunately, LAMP also creates many non-specific amplicons that often yield false positive results and because of this its potential for point-of-care assays has not been realized. We recently found that sequence-specific, nucleic acid strand exchange reactions can be used to efficiently distinguish between specific and non-specific LAMP amplicons [19] [20] [21] . We now show that LAMP reactions can be made user-friendly and field-based by integrating LAMP, strand exchange signal transduction, and a commercial-off-the-shelf device, a glucometer, for pathogen detection. The use of glucometers to monitor non-glucose targets was pioneered by Lu's group, who adapted this device for aptamer-or DNAzyme-based detection of cocaine, ATP and metal ions 22-25 . These and other efforts 26-30 inspired our more generalizable approach to molecular diagnostics. The addition of a thermostable invertase allows all reactions to occur in the same tube at a wide temperature range, and the simplicity of the format ultimately yields atto-molar (or low zepto-mole) detection of pathogens such as MERS-CoV or Zaire Ebolavirus (ZEBOV or Zaire Ebola), even in sputum or saliva samples. The strand exchange reactions ensure low false positives, while the use of an OR gate guards against false negative detection. Moreover, the reaction components are modular and can be readily adapted to different protocols covering different reaction temperatures, times, volumes, and vagaries of reagent storage.

A Sweet Spot for Molecular Diagnostics: Coupling Isothermal Amplification and Strand Exchange Circuits to Glucometers OPEN