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:
The evolution of viral quasispecies can influence viral pathogenesis and the response to antiviral treatments. Mutant clouds in infected organisms represent the first stage in the genetic and antigenic diversification of RNA viruses, such as foot and mouth disease virus (FMDV), an important animal pathogen. Antigenic variants of FMDV have been classically diagnosed by immunological or RT-PCR-based methods. DNA microarrays are becoming increasingly useful for the analysis of gene expression and single nucleotide polymorphisms (SNPs). Recently, a FMDV microarray was described to detect simultaneously the seven FMDV serotypes. These results encourage the development of new oligonucleotide microarrays to probe the fine genetic and antigenic composition of FMDV for diagnosis, vaccine design, and to gain insight into the molecular epidemiology of this pathogen. A FMDV microarray was designed and optimized to detect SNPs at a major antigenic site of the virus. A screening of point mutants of the genomic region encoding antigenic site A of FMDV C-S8c1 was achieved. The hybridization pattern of a mutant includes specific positive and negative signals as well as crosshybridization signals, which are of different intensity depending on the thermodynamic stability of each probe-target pair. Moreover, an array bioinformatic classification method was developed to evaluate the hybridization signals. This statistical analysis shows that the procedure allows a very accurate classification per variant genome. A specific approach based on a microarray platform aimed at distinguishing point mutants within an important determinant of antigenicity and host cell tropism, namely the G-H loop of capsid protein VP1, was developed. The procedure is of general applicability as a test for specificity and discriminatory power of microarray-based diagnostic procedures using multiple oligonucleotide probes.

Ex Output:
BMC Genomics Microarray-based identification of antigenic variants of foot-and-mouth disease virus: a bioinformatics quality assessment

Ex Input:
hydroxychloroquine and azithromycin on viral load in the upper respiratory tract of severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) patients. The authors report that hydroxychloroquine (HCQ) had significant virus reducing effects, and that dual treatment of both HCQ and azithromycin further enhanced virus reduction. These data have triggered speculation whether these drugs should be considered as candidates for the treatment of severe COVID-19. However, questions have been raised regarding the study's data integrity, statistical analyses, and experimental design. We therefore reanalysed the original data to interrogate the main claims of the paper. Here we apply Bayesian statistics to assess the robustness of the original paper's claims by testing four variants of the data: 1) The assumes a positive effect, compared to a model of no effect. We find that the statistical evidence is highly sensitive to these data variants. Statistical evidence for the positive effect model ranged from strong for the original data (BF +0 ~11), to moderate when including patients who deteriorated (BF +0 ~4.35), to anecdotal when excluding untested patients (BF +0 ~2), and to anecdotal negative evidence if untested patients were assumed positive (BF +0 ~0.6). To assess whether HCQ is more effective when combined with AZ, we performed the same tests, and found only anecdotal evidence for the positive effect model for the original data (BF +0 ~2.8), and moderate evidence for all other variants of the data (BF +0 ~5.6). Our analyses only explore the effects of different assumptions about excluded and untested patients. These assumptions are not adequately reported, nor are they justified in the original paper, and we find that varying them causes substantive changes to the evidential support for the main claims of the original paper. This statistical uncertainty is exacerbated by the fact that the treatments were not randomised, and subject to several confounding variables including the patients consent to treatment, different care centres, and clinical decision-making. Furthermore, while the viral load measurements were noisy, showing multiple reversals between test outcomes, there is greater certainty around other clinical outcomes such as the 4 patients who seriously deteriorated. The fact that all of these belonged to the HCQ group should be assigned greater weight when evaluating the potential clinical efficacy of HCQ. Randomised controlled trials are currently underway, and will be critical in resolving this uncertainty as to whether HCQ and AZ are effective as a treatment for COVID-19. Warning: There have been reports of people self-administering chloroquine phosphate (intended for treatment of disease in aquarium fish) , which has led to at least one death and one serious illness. We state that under no circumstances should people self-administer hydroxychloroquine, chloroquine phosphate, azithromycin, or anything similar-sounding, or indeed any other drug, unless approved by a medical doctor. The FDA has issued a specific warning: https://www.fda.gov/animal-veterinary/product-safety-information/fda-letter-stakeholders-do-not-use-chloroquine-phosphate-intended-fis h-treatment-covid-19-humans . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not peer-reviewed) The copyright holder for this preprint .

Ex Output:
Reply to Gautret et al. 2020: A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19

Ex Input:
Background: Pandemic influenza A (H1N1) virus emerged in North America in April 2009 and spread globally. We describe the epidemiology and public health response to the first known outbreak of 2009 H1N1 in a train, which occurred in June 2009 in China. Methods: After 2 provinces provided initial reports of 2009 H1N1 infection in 2 persons who had travelled on the same train, we conducted a retrospective epidemiologic investigation to collect information from the passengers, crew members, contacts, and health care providers. We explored the source of infection and possible routes of transmission in the train. All cases were confirmed by real-time reverse transcription polymerase chain reaction testing. Results: Train #1223 traveled 40 hours, made 28 stops in 4 Chinese provinces, and boarded 2555 passengers, who logged a total of 59 144 person-hours of travel time. Nineteen confirmed 2009 H1N1 cases were identified. Of these, 13 were infected and developed symptoms on the train and 6 occurred among contacts who developed illness during medical monitoring. In addition, 3 asymptomatic cases were identified based on RT-PCR testing of respiratory swabs from contacts. The attack rate among contacts of confirmed cases in the same car was higher than that among contacts in other cars (3.15% vs. 0%, P < 0.001). Attack rates increased with exposure time. Conclusions: Close contact and long exposure may have contributed to the transmission of 2009 H1N1 virus in the train. Trains may have played an important role in the 2009 influenza pandemic.

Ex Output:
Transmission of Pandemic Influenza A (H1N1) Virus in a Train in China