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: Influenza has been well documented to significantly contribute to winter increase of mortality in the temperate countries, but its severity in the subtropics and tropics was not recognized until recently and geographical variations of disease burden in these regions remain poorly understood. In this study, we applied a standardized modeling strategy to the mortality and virology data from three Asian cities: subtropical Guangzhou and Hong Kong, and tropical Singapore, to estimate the disease burden of influenza in these cities. We found that influenza was associated with 10.6, 13.4 and 8.3 deaths per 100,000 population in Guangzhou, Hong Kong and Singapore, respectively. The annual rates of excess deaths in the elders were estimated highest in Guangzhou and lowest in Singapore. The excess death rate attributable to A/H1N1 subtype was found slightly higher than the rates attributable to A/H3N2 during the study period of 2004-2006 based on the data from Hong Kong and Guangzhou. Our study revealed a geographical variation in the disease burden of influenza in these subtropical and tropical cities. These results highlight a need to explore the determinants for severity of seasonal influenza.

Output: Influenza associated mortality in the subtropics and tropics: Results from three Asian cities


Input: Consider Input: The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. The retrospective study using the past SARS-CoV and MERS-CoV data demonstrated that our machine learning based method can successfully predict effective drug candidates : bioRxiv preprint against a specific coronavirus. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 is able to suppress the CpG-induced IL-6 production in peripheral blood mononuclear cells, suggesting that it may also have anti-inflammatory effect that is highly relevant to the prevention immunopathology induced by SARS-CoV-2 infection. Further pharmacokinetic and toxicokinetic evaluation in rats and monkeys showed a high concentration of CVL218 in lung and observed no apparent signs of toxicity, indicating the appealing potential of this drug for the treatment of the pneumonia caused by SARS-CoV-2 infection. Moreover, molecular docking simulation suggested that CVL218 may bind to the N-terminal domain of nucleocapsid (N) protein of SARS-CoV-2, providing a possible model to explain its antiviral action. We also proposed several possible mechanisms to explain the antiviral activities of PARP1 inhibitors against SARS-CoV-2, based on the data present in this study and previous evidences reported in the literature. In summary, the PARP1 inhibitor CVL218 discovered by our data-driven drug repositioning framework can serve as a potential therapeutic agent for the treatment of COVID-19. author/funder. All rights reserved. No reuse allowed without permission. : bioRxiv preprint known evidences reported in the literature, we also discussed several putative mechanisms of the anti-SARS-CoV-2 effects for CVL218 or other PARP1 inhibitors to be involved in the treatment of COVID-19. Overall, our results indicated that the PARP1 inhibitor CVL218 identified by our drug repositioning pipeline may serve as an effective therapeutic agent against COVID-19. Results The overview of our data-driven drug repositioning framework is shown in Figure 1A . We first constructed a virus related knowledge graph consisting of drug-target interactions, protein-protein interactions and similarity networks from publically available databases (Methods). Three different types of nodes (i.e., drugs, human targets and virus targets) within the knowledge graph were connected through edges describing their interactions, associations or similarities to establish bridges of information aggregation and knowledge mining. We then applied a network-based knowledge mining algorithm to predict an initial list of drug candidates that can be potentially used to treat SARS-CoV-2 infection ( Figure 1B and Methods). Next, we further narrowed down the list of drug candidates with the previously reported evidences of antiviral activities based on the text mining results from the large-scale literature texts, which were derived through a deep learning based relation extraction method named BERE [4] ( Figure 1C and Methods), followed by a minimum of manual checking. After that, we used the connectivity map analysis approach [5] with the gene expression profiles of ten SARS-CoV-infected patients [6] to further refine the list of drug candidates against SARS-CoV-2 ( Figure 1D , Table 1, Table S1 and Methods). The above screening process revealed that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor PJ-34 could potentially have the antiviral activities against SARS-CoV-2. 4 author/funder. All rights reserved. No reuse allowed without permission.

Output: A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19


Input: Consider Input: the virus [9], highlighting the rapid responses of the scientific community to this previously unknown global pathogen. Advancements in synthetic organic chemistry, molecular biology, and informatics have made possible the in vitro and in vivo [10-13]. The term "chemical genetics" has been coined to signify the use of chemicals to per-1 Department of Microbiology 2 Department of Biochemistry turb systematically, and thus determine, the function of proteins in the same way that mutations are used in classical genetics [14-16]. We decided to dissect the pathogenic pathways of the SARS-CoV using chemical Pokfulam, Hong Kong SAR China genetics. We hypothesized that by using forward chemical genetics [15, 16], in which small molecules that in-4 The Aaron Diamond AIDS Research Center 455 First Avenue duce altered phenotypes in cells or organisms are identified and their cellular targets will then be determined New York, New York 10016 subsequently, we will be able to isolate novel small-molecule compounds perturbing the biological pathways that are essential for the pathogenesis of SARS-CoV. Summary The severe acute respiratory syndrome-associated tion with ACE2 [9]. After being internalized into the target coronavirus (SARS-CoV) infected more than 8,000 cells, SARS-CoV undergoes a very rapid replication cypeople across 29 countries and caused more than 900 cle through a series of concerted transcriptional, translafatalities. Based on the concept of chemical genetics, tional, posttranslational, and proteolytic processing we screened 50,240 structurally diverse small moleevents, leading to maturation and release of infective cules from which we identified 104 compounds with viral particles into the culture supernatant [17-19]. We anti-SARS-CoV activity. Of these 104 compounds, 2 speculated that the various biological pathways intarget the SARS-CoV main protease (M pro ), 7 target volved in viral pathogenesis could be perturbed by small helicase (Hel), and 18 target spike (S) protein-angiomolecules using chemical genetic approaches. To extensin-converting enzyme 2 (ACE2)-mediated viral enamine the feasibility of employing chemical genetic try. The EC 50 of the majority of the 104 compounds approaches in SARS-CoV research, we acquired a determined by SARS-CoV plaque reduction assay chemical library (ChemBridge Corporation) of 50,240 were found to be at low micromolar range. Three sestructurally diverse small-molecule compounds that lected compounds, MP576, HE602, and VE607, valivary in functional groups and charges. As the SARSdated to be inhibitors of SARS-CoV M pro , Hel, and viral CoV replicates effectively in Vero cells (African green entry, respectively, exhibited potent antiviral activity monkey kidney cell line) and full cytopathic effects (CPE) (EC 50 Ͻ 10 M) and comparable inhibitory activities in of the infected cells can be observed within 96 hr postintarget-specific in vitro assays. fection, Vero cell CPE was used as a phenotypic indicator of successful viral infection in a cell-based assay to


Output: Identification of Novel Small-Molecule Inhibitors of Severe Acute Respiratory Syndrome-Associated Coronavirus by Chemical Genetics use of large collections of small molecules (chemical libraries) to investigate protein/chemical interactions