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: The novel corona virus SARS-CoV-2 (COVID-19) can infect healthcare workers. We developed an institutional algorithm to protect operating room team members during the COVID-19 pandemic and rationally conserve personal protective equipment (PPE). Study Design: An interventional platform (operating room, interventional suites, and endoscopy) PPE taskforce was convened by the hospital and medical school leadership and tasked with developing a common algorithm for PPE use, to be used throughout the interventional platform. In conjunction with our infection disease experts, we developed our guidelines based upon potential patterns of spread, risk of exposure and conservation of PPE. A decision tree algorithm describing our institutional guidelines for precautions for operating room team members was created. This algorithm is based on urgency of operation, anticipated viral burden at the surgical site, opportunity for a procedure to aerosolize virus, and likelihood a patient could be infected based on symptoms and testing. Conclusion: Despite COVID-19 being a new threat, we have shown that by developing an easyto-follow decision tree algorithm for the interventional platform teams, we can ensure optimal healthcare worker safety.

Ex Output:
Journal Pre-proof Precautions for Operating Room Team Members during the COVID-19 Pandemic Precautions for Operating Room Team Members during the COVID-19 Pandemic


Ex Input:
Diarrhea outbreaks in pig farms have raised major concerns in Europe and USA, as they can lead to dramatic pig losses. During a suspected outbreak in Belgium of porcine epidemic diarrhea virus (PEDV), we performed viral metagenomics to assess other potential viral pathogens. Although PEDV was detected, its low abundance indicated that other viruses were involved in the outbreak. Interestingly, a porcine bocavirus and several enteroviruses were most abundant in the sample. We also observed the presence of a porcine enterovirus genome with a gene insertion, resembling a C28 peptidase gene found in toroviruses, which was confirmed using re-sequencing, bioinformatics, and proteomics approaches. Moreover, the predicted cleavage sites for the insertion suggest that this gene was being expressed as a single protein, rather than a fused protein. Recombination in enteroviruses has been reported as a major mechanism to generate genetic diversity, but gene insertions across viral families are rather uncommon. Although such inter-family recombinations are rare, our finding suggests that these events may significantly contribute to viral evolution.

Ex Output:
Identification of an enterovirus recombinant with a torovirus-like gene insertion during a diarrhea outbreak in fattening pigs


Ex Input:
Since we focused on the distribution of outbreaks rather than the total number of cases, we analyzed only the first positive report associated with each outbreak or the first negative report (if all suspected cases from that farm were rabies negative) when multiple animals were reported sick or dead. Information for each outbreak included species infected, date of disease onset, the district where the outbreak occurred (Peru is divided into regions, provinces, districts and towns), and GPS data when available from the farm or community where the outbreak occurred (N = 914 outbreaks). We excluded data from two regions on the coast of Peru (Lima and Ancash) that reported small numbers of unconfirmed outbreaks and 23 outbreaks from the region of Puno, where dog rabies causes most livestock infections [1]. Using a standardized questionnaire, we asked farmers whether their animals had been bitten by vampire bats in the last year; whether they knew that vampire bats can transmit rabies; whether they knew that SENASA was the relevant authority for reporting rabies; and if they vaccinated their animals against rabies. Questionnaires were performed in Quechua or Spanish by a local assistant. Procedures were approved by the Ethics Committee of the College of Veterinary Science, University of Glasgow. Written and signed informed consent approval was obtained from each farmer who participated in the study. Least-cost distances were calculated using the gdistance package of R, setting resistance values to 1 and 10000 below and above 3,600m, respectively. The transition function was used to create a least-cost distance across a conductance map, with 8 possible path directions. Distances were corrected to account for geographical projection using the geoCorrection function. The costDistance function was used to calculate the distance from the origin of each wave to the center of each hexbin. To assess the sensitivity of wavefront speeds and R 2 to the inferred location of index outbreaks, we performed a bootstrap analysis using the total number of outbreaks N [2]. This analysis consisted in four consecutive steps: (1) randomly sampling N outbreaks, allowing the same outbreak to be sampled multiple times (i.e. bootstrapping with replacement) using the sample function of R; (2) randomly sampling 5000 different plausible origins for each wave; (3) for each of those 5000 origins, calculating the slope and R 2 of the regression between the least-cost distance to the origin and the time of disease arrival; (4) selecting the slope of the regression with the highest R 2 for each origin. This procedure was repeated 200 times for each valley, and the range of both the speed of the wave (1/slope of the regression) and its associated R 2 were estimated. The distributions of the speed of the wave and R 2 obtained are shown in figure S1 . This analysis was the same as the one described above, except for step (1). This step was replaced by randomly selecting an elevation threshold from a uniform distribution ranging from 3500 to 4500 meters using the runif function in R. We focus our sensitivity analysis on elevations above 3600 meters because clear evidence of bat presence and viral circulation below this limit which implies the absence of any impassable threshold (figure 3, figure 5 ). In both valleys, the estimated speed of the wave and R 2 declined slightly with the elevation threshold ( figure S2 ). However, all estimated values remained within the 95% CI of the estimation using 3600 meters, the assumed value in our main analysis. Thus, the estimation of the wave speed was largely insensitive to the elevation threshold. The negative correlation between wavefront speeds and R 2 and the elevation threshold is explained by longer least-cost distances when using a smaller elevation threshold because there are more elevation obstacles in the landscape. We validated the predictions of outbreak arrival dates to a particular location ahead of the wave using the following procedure. First, we estimated the most likely origin of the wave by maximising the R 2 of the linear regression using the first 75% of outbreak locations. We then predicted the month of arrival for the remaining outbreak locations in the wave front (5 and 7 hexagonal cells to predict in Chalhuanca and Rio Apurimac, respectively) using the predict function in R. Finally, we calculated the averaged difference between the predicted and arrival date. All true arrival dates from the test dataset occurred within the 95% CI of the predicted arrival dates (figure S1). Similar results were obtained when using half of the data to predict the other half (50% training, 50% test set); all arrival dates of the test set occurred within the 95% CI of the predicted arrival dates. Figure S1 . Sensitivity of wavefront speeds to the inferred wave origins. The distribution of the estimated wave speeds (left) and their associated R 2 (right) from the bootstrap procedure are shown for Chalhuanca (top plots) and Rio Apurimac (bottom plots). Supplementary Figures and Tables Amazonian regions are colored in blue and red, respectively.

Ex Output:

Electronic Supplementary Materials Spatial Expansions and Travelling Waves of Rabies in Vampire Bats