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: Objective: Coronavirus disease 2019 (COVID-19) is an escalating global epidemic caused by SARS-CoV-2, with a high mortality in critical patients. Effective indicators for predicting disease severity in SARS-CoV-2 infected patients are urgently needed. Methods: In this study, 43 COVID-19 patients admitted in Chongqing Public Health Medical Center were involved. Demographic data, clinical features, and laboratory examinations were obtained through electronic medical records. Peripheral blood specimens were collected from COVID-19 patients and examined for lymphocyte subsets and cytokine profiles by flow cytometry. Potential contributing factors for prediction of disease severity were further analyzed. Results: A total of 43 COVID-19 patients were included in this study, including 29 mild patients and 14 sever patients. Severe patients were significantly older (61.9±9.4 vs 44.4±15.9) and had higher incidence in co-infection with bacteria compared to mild group (85.7%vs27.6%). Significantly more severe patients had the clinical symptoms of anhelation (78.6%) and asthma (71.4%). For laboratory examination, 57.1% severe cases showed significant reduction in lymphocyte count. The levels of Interluekin-6 (IL6), IL10, erythrocyte sedimentation rate (ESR) and D-Dimer (D-D) were significantly higher in severe patients than mild patients, while the level of albumin (ALB) was remarkably All rights reserved. No reuse allowed without permission. the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. : medRxiv preprint lower in severe patients. Further analysis demonstrated that ESR, D-D, age, ALB and IL6 were the major contributing factors for distinguishing severe patients from mild patients. Moreover, ESR was identified as the most powerful factor to predict disease progression of COVID-19 patients. : Age and the levels of ESR, D-D, ALB and IL6 are closely related to the disease severity of COVID-19 patients. ESR can be used as a valuable indicator for distinguishing severe COVID-19 patients in early stage, so as to increase the survival of severe patients.

Output: Potential Factors for Prediction of Disease Severity of COVID-19 Patients


Input: Consider Input: A one year active surveillance program for influenza A viruses among avian species in a live-bird market (LBM) in Bangkok, Thailand was conducted in 2009. Out of 970 samples collected, influenza A virus subtypes H4N6 (n = 2) and H4N9 (n = 1) were isolated from healthy Muscovy ducks. All three viruses were characterized by whole genome sequencing with subsequent phylogenetic analysis and genetic comparison. Phylogenetic analysis of all eight viral genes showed that the viruses clustered in the Eurasian lineage of influenza A viruses. Genetic analysis showed that H4N6 and H4N9 viruses display low pathogenic avian influenza characteristics. The HA cleavage site and receptor binding sites were conserved and resembled to LPAI viruses. This study is the first to report isolation of H4N6 and H4N9 viruses from birds in LBM in Thailand and shows the genetic diversity of the viruses circulating in the LBM. In addition, co-infection of H4N6 and H4N9 in the same Muscovy duck was observed.


Output: Genetic characterization of avian influenza subtype H4N6 and H4N9 from live bird market, Thailand