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.

Q: Bacterial and viral co-infections of the respiratory tract are life-threatening and present a global burden to the global community. Staphylococcus aureus, Streptococcus pneumoniae, and Streptococcus pyogenes are frequent colonizers of the upper respiratory tract. Imbalances through acquisition of seasonal viruses, e.g., Influenza A virus, can lead to bacterial dissemination to the lower respiratory tract, which in turn can result in severe pneumonia. In this review, we summarize the current knowledge about bacterial and viral co-infections of the respiratory tract and focus on potential experimental models suitable for mimicking this disease. Transmission of IAV and pneumonia is mainly modeled by mouse infection. Few studies utilizing ferrets, rats, guinea pigs, rabbits, and non-human primates are also available. The knowledge gained from these studies led to important discoveries and advances in understanding these infectious diseases. Nevertheless, mouse and other infection models have limitations, especially in translation of the discoveries to humans. Here, we suggest the use of human engineered lung tissue, human ex vivo lung tissue, and porcine models to study respiratory co-infections, which might contribute to a greater translation of the results to humans and improve both, animal and human health.

A: Port d'Entrée for Respiratory Infections -Does the Influenza A Virus Pave the Way for Bacteria?
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Q: Background: Diagnosis of community-acquired pneumonia (CAP) caused by Mycoplasma pneumoniae (Mp) in children has been hampered by difficulty in obtaining convalescent serum and time constraints. In this study, the two diagnostic assays that targeted respectively on Mp-antibody and Mp-DNA were retrospectively investigated. Methods: A total of 3146 children were clinically diagnosed to have CAP and were confirmed by chest X-ray during March 2015 to February 2016 in Children's hospital of Hebei Province (China). Both of the sera and sputum samples were collected in 24 h after their admission. The Mp-antibody was examined by the passive particle agglutination assay and a fourfold or greater increase of antibody titers of paired sera or≧1:160 titer of single serum was set as the serology positive. Mp-DNA in the sputum samples was tested by a multiplex-PCR method named GeXP assay (multiplex PCR combined with automated capillary electrophoresis). In order to eliminate the false positive results caused by the asymptomatic carriage after infected by M. pneumoniae, the inconsistent samples were tested by the real-time isothermal transcription-mediated RNA amplification assay (SAT). The inter-rated agreement test was performed in 3146 CAP patients, with a highest kappa value in the schoolage children as 0.783. There were 6.29% (198/3146) cases showed inconsistent results determined by GeXP and serology assay. All of the 19 GeXP(+)/Serology (−) samples and a randomly chosen 27 from 179 GeXP(−)/Serology (+) samples were tested by SAT assay, and a 97.8% diagnosis agreement was observed between SAT and GeXP assay, but not with the serology assay. In addition, patients who were detected only by serology or only by multiplex-PCR were significantly younger than those with both methods positive (3.0 and 1.5 years vs. 5.0 years, p < 0. 01). The Viral-Mp coinfection accounted for 37.0% (97/262), which was more common in winter and spring (p < 0.05) and in the infantile group (p < 0.01), compared to the pure Mp positive ones. In some children CAP cases, the Mp laboratory diagnosis was inconsistent between serology and multiplex-PCR assay. Verified by the SAT assay, the GeXP showed a more sensitive and reliable performance compared with the serology assay. Furthermore, employing the multiplex-PCR could provide more information on the associated pathogens for clinical assessment of CAP.

A: A comparison study between GeXP-based multiplex-PCR and serology assay for Mycoplasma pneumoniae detection in children with community acquired pneumonia
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Q: Genome signatures are data vectors derived from the compositional statistics of DNA. The self-organizing map (SOM) is a neural network method for the conceptualisation of relationships within complex data, such as genome signatures. The various parameters of the SOM training phase are investigated for their effect on the accuracy of the resulting output map. It is concluded that larger SOMs, as well as taking longer to train, are less sensitive in phylogenetic classifi cation of unknown DNA sequences. However, where a classifi cation can be made, a larger SOM is more accurate. Increasing the number of iterations in the training phase of the SOM only slightly increases accuracy, without improving sensitivity. The optimal length of the DNA sequence k-mer from which the genome signature should be derived is 4 or 5, but shorter values are almost as effective. In general, these results indicate that small, rapidly trained SOMs are generally as good as larger, longer trained ones for the analysis of genome signatures. These results may also be more generally applicable to the use of SOMs for other complex data sets, such as microarray data.

A:
Correspondence: Genome Signatures, Self-Organizing Maps and Higher Order Phylogenies: A Parametric Analysis
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