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: It is reported that bacterial colonization of the airway in neonates affects the likelihood and severity of subsequent wheezing in childhood. This study aimed to explore the impact of bacterial colonization on the severity of virus-induced wheezing, and accompanying airway inflammation. Nasopharyngeal aspirates (NPAs) from 68 hospitalized children with bronchiolitis and 85 children with recurrent wheezing were obtained. Eleven common respiratory viruses were sought by PCR and/or direct fluorescence assay. Bacteria were isolated from NPAs by routine culture methods. Cell numbers and concentrations of cytokines/chemokines in the NPAs were measured, and nucleated cells were characterized. The frequency of bacterial colonization in children with recurrent wheezing was significantly higher than in children with an initial attack of bronchiolitis. Bacterial colonization accompanying virus infection had no effect on clinical manifestations, duration of hospitalization, concentrations of cytokines/chemokines (except interleukin-10 (IL-10)) or cellularity in the children with bronchiolitis; however, among the children with recurrent wheezing, those who had coexistent non-invasive bacterial colonization and virus infection presented more frequent cyanosis, longer duration of hospitalization, a higher concentration of IL-10 and a higher percentage of neutrophils in NPAs than those with virus infection but without bacterial colonization. Bacterial colonization was common in children with virus-induced wheezing, particularly in the situation of recurrent wheezing. To some extent, bacterial colonization accompanying virus infection may contribute to the severity of the wheezing because of its impact on airway inflammation.

Output: Impact of bacterial colonization on the severity, and accompanying airway inflammation, of virus-induced wheezing in children


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 acute respiratory distress syndrome (ARDS) is a lethal inflammatory disorder of the lung. Its incidence is estimated at 75 cases per 100,000 population and appears to be increasing [1] . Even with optimal treatment, mortality is about 30% [1-3]. As such, ARDS represents a major public health problem. The effects of two recent crises created by unusual viral infections of the respiratory tract -the severe acute respiratory syndrome (SARS) epidemic caused by the novel SARS coronavirus [4, 5] and the bird flu [6] highlight the importance of research into ARDS. Both viruses cause an ARDS-like picture. Because lung repair and regeneration contribute substantially to the pathophysiology of ARDS, understanding these processes is essential [7] . This chapter focuses on specific cell populations and markers involved in cell division and regeneration. In addition, a brief review of two pathways intimately associated with cell division is provided because of their potential for pharmacologic manipulation.


Output: Cell Regeneration in Lung Injury