Narirutin-Rich Celluclast Extract from Mandarin (<i>Citrus unshiu</i>) Peel Alleviates High-Fat Diet-Induced Obesity and Promotes Energy Metabolism in C57BL/6 Mice

Mandarin peel, a main by-product from the processing of citrus juice, has been highlighted for its various bioactivities and functional ingredients. Our previous study proved the inhibitory effects of Celluclast extract from mandarin peel (MPCE) on lipid accumulation and differentiation in 3T3-L1 adipocytes. Therefore, the current study aimed to evaluate the anti-obesity effect of MPCE in high-fat diet (HFD)-induced obese mice. The high-performance liquid chromatography (HPLC) analysis exhibited that narirutin and hesperidin are the main active components of MPCE. Our current results showed that MPCE supplementation decreased adiposity by reducing body and organ weights in HFD-induced obese mice. MPCE also reduced triglyceride (TG), alanine transaminase (ALT), aspartate transaminase (AST), and leptin contents in the serum of HFD-fed mice. Moreover, MPCE significantly inhibited hepatic lipid accumulation by regulating the expression levels of proteins associated with lipid metabolism, including sterol regulatory element-binding protein (SREBP1c), fatty acid synthase (FAS), and acetyl-CoA carboxylase (ACC). Furthermore, MPCE administration significantly inhibited both adipogenesis and lipogenesis, with modulation of energy metabolism by activating 5′ adenosine monophosphate-activated protein kinase (AMPK) and lipolytic enzymes such as hormone-sensitive lipase (HSL) in the white adipose tissue (WAT). Altogether, our findings indicate that MPCE improves HFD-induced obesity and can be used as a curative agent in pharmaceuticals and nutraceuticals to alleviate obesity and related disorders

Comparing Potential Unstable Sites and Stable Sites on Revegetated Cut-Slopes of Mountainous Terrain in Korea

This study employs a diverse set of variables to explain slope stabilization on stable versus failure-prone revegetated cut-slopes in Korea. A field survey was conducted at potential unstable sites and stable sites using 23 variables. Through a non-parametric test of the field survey results, 15 variables were identified as primary determinants of slope failure. Of these variables, one described physical characteristics (elapsed year); four variables described vegetation properties (plant community, vegetation coverage rate, number of trees, and number of herbs); and 10 variables represented soil properties (porosity, soil hardness, water content, sand ratio and silt ratio of soil texture, tensile strength, permeability coefficient, soil depth, soil acidity, salt concentration, and organic matter). Slope angle, which was mainly considered in previous studies, of variables in physical characteristics was not statistically selected as one of the 15 variables because most of sites were located on steep slopes. The vegetation community, vegetation coverage, and number of trees influence slope stabilization. Vegetation coverage is highly correlated with other soil and vegetation variables, making it a major indicator of slope stabilization. All soil variables were related to slope failure such that subsequent slope failure was related to the method of slope revegetation rather than the environmental condition of the slope. Slope failure did not occur in revegetated slopes that matched the characteristics of the surrounding landscape and contained a large number of native trees. Most soil and vegetation variables showed differing values for whether a revegetated slope is potentially unstable or stable

Development of Revegetated Slope Stability Assessment System in South Korea

This research was conducted to develop the revegetated slope stability assess (RSSA) system for revegetated cut-slopes in South Korea. A field survey was conducted on potential risk slopes and stable slopes using the twenty three variables. Through a nort-parametric test and a correlation analysis of the field survey results, nine variables were identified as primary determinants of slope failures. Of these variables, six variables were from the soil category, (soil porosity, soil water content, soil depth, soil tensile strength, salt concentration, and soil organic matter) and three variables were from the vegetation category, (vegetation coverage, number of trees, and vegetation community). None of the physical characteristic variables were selected as determinants. Discriminant analysis was conducted to develop evaluation indicators from nine variables. As a result, the discriminant function included four variables: soil porosity, soil tensile strength, soil organic matter, and vegetation coverage as the indicators of the discriminant function. The data of vegetation community was excluded from the discriminant analysis as it was a nominal scale but used for the final screening of stability using the relationship between the discriminant score and vegetation community. RSSA system was developed by combining these two processes. Although RSSA system is not a complete system for slope stability assessment, it is very practical for revegetated slope stability assessment because it requires relatively few indicators which can be easily measured. Therefore, it should be useful for the initial assessment or supplemental assessment with the integrated slope stability assessment system to be developed in the future.N