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.

Input: Consider Input: Although the majority of cases of Legionnaires' disease (LD) are caused by Legionella pneumophila, an increasing number of other Legionella species have been reported to cause human disease. There are no clinical presentations unique to LD and hence accurate laboratory tests are required for early diagnosis. Therefore, we designed a real-time PCR assay that targets the 23S-5S rRNA intergenic spacer region (23S-5S PCR) and allows for detection of all Legionella species and discrimination of L. pneumophila from other Legionella species. In total, 271 isolates representing 50 Legionella species were tested and the assay was validated using 39 culture-positive and 110 culture-negative patient specimens collected between 1989 and 2006. PCR-positive results were obtained with all 39 culture-positive samples (100% sensitivity). Specimens that tested positive according to 23S-5S PCR, but were culture-negative, were further analysed by DNA sequencing of the amplicon or the macrophage infectivity potentiator (mip) gene. In addition to L. pneumophila, Legionella longbeachae, Legionella cincinnatiensis and Legionella micdadei were identified in the specimens. The assay showed a 7-log dynamic range displaying a sensitivity of 7.5 CFU/mL or three genome equivalents per reaction. Sixty-one specimens containing viruses or bacteria other than Legionellae were negative according to 23S-5S PCR, demonstrating its specificity. Use of this assay should contribute to the earlier detection of respiratory disease caused by Legionella species, as well as to increased rates of detection.

Output: Dual detection of Legionella pneumophila and Legionella species by real-time PCR targeting the 23S-5S rRNA gene spacer region


Input: Consider Input: Overlapping genes represent a fascinating evolutionary puzzle, since they encode two functionally unrelated proteins from the same DNA sequence. They originate by a mechanism of overprinting, in which point mutations in an existing frame allow the expression (the "birth") of a completely new protein from a second frame. In viruses, in which overlapping genes are abundant, these new proteins often play a critical role in infection, yet they are frequently overlooked during genome annotation. This results in erroneous interpretation of mutational studies and in a significant waste of resources. Therefore, overlapping genes need to be correctly detected, especially since they are now thought to be abundant also in eukaryotes. Developing better detection methods and conducting systematic evolutionary studies require a large, reliable benchmark dataset of known cases. We thus assembled a highquality dataset of 80 viral overlapping genes whose expression is experimentally proven. Many of them were not present in databases. We found that overall, overlapping genes differ significantly from non-overlapping genes in their nucleotide and amino acid composition. In particular, the proteins they encode are enriched in high-degeneracy amino acids and depleted in low-degeneracy ones, which may alleviate the evolutionary constraints acting on overlapping genes. Principal component analysis revealed that the vast majority of overlapping genes follow a similar composition bias, despite their heterogeneity in length and function. Six proven mammalian overlapping genes also followed this bias. We propose that this apparently near-universal composition bias may either favour the birth of overlapping genes, or/and result from selection pressure acting on them.

Output: Overlapping genes and the proteins they encode differ significantly in their sequence composition from non-overlapping genes


Input: Consider Input: To understand viral disease, detection and identification of these viruses are essential. Although PCR is widely used for rapid virus identification due to its low cost and high sensitivity and specificity, very few online database resources have compiled PCR primers for RNA viruses. To effectively detect viruses, the MRPrimerV database (http://MRPrimerV.com) contains 152 380 247 PCR primer pairs for detection of 1818 viruses, covering 7144 coding sequences (CDSs), representing 100% of the RNA viruses in the most up-to-date NCBI RefSeq database. Due to rigorous similarity testing against all human and viral sequences, every primer in MRPrimerV is highly target-specific. Because MR-PrimerV ranks CDSs by the penalty scores of their best primer, users need only use the first primer pair for a single-phase PCR or the first two primer pairs for two-phase PCR. Moreover, MRPrimerV provides the list of genome neighbors that can be detected using each primer pair, covering 22 192 variants of 532 RefSeq RNA viruses. We believe that the public availability of MRPrimerV will facilitate viral metagenomics studies aimed at evaluating the variability of viruses, as well as other scientific tasks.


Output: MRPrimerV: a database of PCR primers for RNA virus detection