• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.5
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• pp.149-162
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• 2018

It is necessary to select the appropriate global climate model (GCM) to take into account the impacts of climate change on integrated water management. The objective of this study was to develop the selection technique of representative GCMs for uncertainty in climate change scenario. The selection technique which set priorities of GCMs consisted of two steps. First step was evaluating original GCMs by comparing with grid-based observational data for the past period. Second step was evaluating whether the statistical downscaled data reflect characteristics for the historical period. Spatial Disaggregation Quantile Delta Mapping (SDQDM), one of the statistical downscaling methods, was used for the downscaled data. The way of evaluating was using explanatory power, the stepwise ratio of the entire GCMs by Expert Team on Climate Change Detection and Indices (ETCCDI) basis. We used 26 GCMs based on CMIP5 data. The Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios were selected for this study. The period for evaluating reproducibility of historical period was 30 years from 1976 to 2005. Precipitation, maximum temperature, and minimum temperature were used as collected climate variables. As a result, we suggested representative 13 GCMs among 26 GCMs by using the selection technique developed in this research. Furthermore, this result can be utilized as a basic data for integrated water management.

• Molecules and Cells
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• v.42 no.6
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• pp.480-494
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• 2019

Aggregates of disease-causing proteins dysregulate cellular functions, thereby causing neuronal cell loss in diverse neurodegenerative diseases. Although many in vitro or in vivo studies of protein aggregate inhibitors have been performed, a therapeutic strategy to control aggregate toxicity has not been earnestly pursued, partly due to the limitations of available aggregate models. In this study, we established a tetracycline (Tet)-inducible nuclear aggregate (${\beta}23$) expression model to screen potential lead compounds inhibiting ${\beta}23$-induced toxicity. High-throughput screening identified several natural compounds as nuclear ${\beta}23$ inhibitors, including peucedanocoumarin III (PCIII). Interestingly, PCIII accelerates disaggregation and proteasomal clearance of both nuclear and cytosolic ${\beta}23$ aggregates and protects SH-SY5Y cells from toxicity induced by ${\beta}23$ expression. Of translational relevance, PCIII disassembled fibrils and enhanced clearance of cytosolic and nuclear protein aggregates in cellular models of huntingtin and ${\alpha}$-synuclein aggregation. Moreover, cellular toxicity was diminished with PCIII treatment for polyglutamine (PolyQ)-huntingtin expression and ${\alpha}$-synuclein expression in conjunction with 6-hydroxydopamine (6-OHDA) treatment. Importantly, PCIII not only inhibited ${\alpha}$-synuclein aggregation but also disaggregated preformed ${\alpha}$-synuclein fibrils in vitro. Taken together, our results suggest that a Tet-Off ${\beta}23$ cell model could serve as a robust platform for screening effective lead compounds inhibiting nuclear or cytosolic protein aggregates. Brain-permeable PCIII or its derivatives could be beneficial for eliminating established protein aggregates.