Long non-coding RNAs (lncRNAs) are involved in various biological processes as well as many respiratory diseases, while the role of lncRNAs in acute lung injury (ALI) remains unclear. The present study aimed to profile the expression of lung lncRNAs and mRNAs in lipopolysaccharide (LPS)-induced ALI mouse model. C57BL/6 mice were exposed to LPS or phosphate-buffered saline for 24 h, and lncRNAs and mRNAs were profiled by Arraystar mouse LncRNA Array V3.0. Bioinformatics analysis gene ontology including (GO) and pathway analysis and cell study in vitro was used to investigate potential mechanisms. Based on the microarray results, 2632 lncRNAs and 2352 mRNAs were differentially expressed between ALI and control mice. The microarray results were confirmed by the quantitative real-time PCR (qRT-PCR) results of ten randomized selected lncRNAs. GO analysis showed that the altered mRNAs were mainly related to the processes of immune system, immune response and defense response. Pathway analysis suggests that tumor necrosis factor (TNF) signaling pathway, NOD-like receptor pathway, and cytokine–cytokine receptor interaction may be involved in ALI. LncRNA-mRNA co-expression network analysis indicated that one individual lncRNA may interact with several mRNAs, and one individual mRNA may also interact with several lncRNAs. Small interfering RNA (siRNA) for ENSMUST00000170214.1, - ENSMUST00000016031.13 significantly inhibited LPS-induced TNF-α and interleukin (IL)-1β production in murine RAW264.7 macrophages. Our results found significant changes of lncRNAs and mRNAs in the lungs of LPS-induced ALI mouse model, and intervention targeting lncRNAs may attenuate LPS-induced inflammation, which may help to elucidate the role of lncRNAs in the pathogenesis and treatment of ALI.
Carsharing-facilitating neighbourhood is an emerging concept in urban development that combines carsharing, sustainable transportation-residential planning, and attractive housing to reduce private car use and improve neighbourhood quality. To investigate residents’ preferences for such neighbourhoods, a stated choice experiment was designed that systematically varied attributes of carsharing-facilitating neighbourhoods to elicit their utility for people with a particular socio-demographic profile. The survey was conducted among residents who currently live in densely populated urban areas in The Netherlands. In total, 610 valid responses were obtained for analysis. To derive the utility of carsharing-facilitating neighbourhoods of a particular profile, a mixed logit model was estimated. Results indicate that the utility of a carsharing-facilitating neighbourhood primarily depends on carsharing cost, required carsharing booking time, green space density, housing costs, housing type, housing size and housing building year. Besides, the utility varies with socio-demographic characteristics, such as age, household composition, net monthly income, work status and education level. The estimated results can help policymakers and real estate developers understand the contribution of particular factors to the utility of carsharing-facilitating neighbourhoods, and determine target groups to develop implementation strategies.
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