TASK DEFINITION: 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.
PROBLEM: Background. Bacteria are found in 50%-90% of cases of acute otitis media (AOM) with or without otorrhea, and viruses are found in 20%-49% of cases. However, for at least 15% of patients with AOM, the microbiological etiology is never determined. Our aim was to specify the full etiology of acute middle ear infection by using modern microbiological methods concomitantly for bacterial and viral detection. Methods. The subjects were 79 young children having AOM with new onset (!48 h) of otorrhea through a tympanostomy tube. Middle ear fluid samples were suctioned from the middle ear through the tympanostomy tube. Bacteria were sought by culture and polymerase chain reaction; viruses were analyzed by culture, antigen detection, and polymerase chain reaction. Results. At least 1 respiratory tract pathogen was noted in 76 children (96%). Bacteria were found in 73 cases (92%), and viruses were found in 55 (70%). In 52 patients (66%), both bacteria and viruses were found. Bacteria typical of AOM were detected in 86% of patients. Picornaviruses accounted for 60% of all viral findings. Conclusions. In the great majority of children, AOM is a coinfection with bacteria and viruses. The patent tympanostomy tube does not change the spectrum of causative agents in AOM. A microbiological etiology can be established in practically all cases.

SOLUTION: Microbiology of Acute Otitis Media in Children with Tympanostomy Tubes: Prevalences of Bacteria and Viruses

PROBLEM: Motivation: Deep sequencing of clinical samples is now an established tool for the detection of infectious pathogens, with direct medical applications. The large amount of data generated produces an opportunity to detect species even at very low levels, provided that computational tools can effectively profile the relevant metagenomic communities. Data interpretation is complicated by the fact that short sequencing reads can match multiple organisms and by the lack of completeness of existing databases, in particular for viral pathogens. Here we present metaMix, a Bayesian mixture model framework for resolving complex metagenomic mixtures. We show that the use of parallel Monte Carlo Markov chains for the exploration of the species space enables the identification of the set of species most likely to contribute to the mixture. Results: We demonstrate the greater accuracy of metaMix compared with relevant methods, particularly for profiling complex communities consisting of several related species. We designed metaMix specifically for the analysis of deep transcriptome sequencing datasets, with a focus on viral pathogen detection; however, the principles are generally applicable to all types of metagenomic mixtures. Availability and implementation: metaMix is implemented as a user friendly R package, freely available on CRAN: http://cran.r-project.org/web/packages/metaMix Contact: sofia.morfopoulou.10@ucl.ac.uk Supplementary information: Supplementary data are available at Bionformatics online.

SOLUTION: Bayesian mixture analysis for metagenomic community profiling

PROBLEM: Neonatal enteritis caused by the porcine epidemic diarrhea virus (PEDV) is an important cause of high mortality and economic losses to the swine industry. Virus neutralization (V/N) assays are commonly requested in diagnostic laboratories for the assessment of protective antibodies. However, the visual assessment of viral cytopathic effects by operators to determine antibody titers or for viral quantification is a tedious, subjective and time-consuming process, especially when high volume testing is involved. To improve the ease of testing, a colorimetric virus neutralization and TCID 50 assays were developed and validated in this study using (3-(4,5dimethylthiazol-2-yl) Tr-2,5-diphenyltetrazolium-bromide) (MTT), a colorimetric agent which measures cell viability. The respective conventional assays were used as the gold standards. An OD cut off value of ≤0.53, selected by receiver operating characteristics analysis, could distinguish between wells with and without CPE accurately. Performance and reproducibility parameters of the colorimetric assays were comparable to the conventional assays. The described methods can reduce testing time in diagnostic laboratories, while significantly improving current protocols.

SOLUTION:
A convenient colorimetric assay for the quantification of porcine epidemic diarrhea virus and neutralizing antibodies