149 research outputs found

    Extraction and identification of the hepatoprotective bio-active components of the root of Actinidia deliciosa

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    The root of Actinidia deliciosa has been used as traditional drugs in China for a long time. This study therefore aimed at investigating the hepatoprotective bio-active components from the root of A. deliciosa comprehensively and accurately, thus promoting the exploitation and utilization of the whole resource of A. deliciosa. For the purpose of this study, the roots of A. deliciosa were fractionated into various extract fractions with differential polarity solvent. The hepatoprotective activities of various solvent extracts were assessed by examining the effect on carbon tetrachloride (CCl4)-induced hepatotoxicity in rats. The highest hepatoprotective activities fraction was further isolated with column chromatography. The structures of the activities monomers were identified with modern spectrum technology such as infrared (IR), ultraviolet (UV), electron impact mass spectrometry (EI-MS), proton nuclear magnetic resonance (1H-NMR), carbon nuclear magnetic resonance (13C-NMR) and distortionless enhancement by polarization transfer-nuclear magnetic resonance (DEPT-NMR). Of the various extract fractions, the ethyl acetate extract (Fr3) exhibited the highest hepatoprotective activities (p<0.05). When the Fr3 was separated into five fractions by silica gel chromatography, among the five fractions fraction, Fr9 showed the highest yield and the highest hepatoprotective activities. When using Fr9 at a dose of 200 mg/kg to pre- and post-treat the CCl4-induced rat, the activities of alanine transaminase (ALT) decreased by 90.10 and 88.60%, aspartate transaminase (AST) decreased by 80.69 and 79.92% in rat serum, the lipid peroxidation (malondialdehyde (MDA)) decreased by 42.11 and 45.53%, while glutathione (GSH) increased by 114.12 and 147.62% in the rats liver homogenate, respectively as compared with that of the CCl4 control rats. The fraction Fr9 was further separated into five fractions using silica gel chromatography, which were investigated for the main chemical constituents by column chromatography techniques, physico-chemical constants and spectroscopic analysis. Its main chemical constituents were three triterpenoids named 3β-hydroxy-urs-12-en-28-oic acid (ursolic acid), 2α,3α,23-trihydroxy-urs-12-en-28-oic acid and 2α,3β,19,23-tetrahydroxy-urs-12-en-28-oic acid. The findings indicate that the high hepatoprotective activity of the fraction of A. deliciosa root is due to its enriched triterpenoid.Key words: Actinidia deliciosa root, carbon tetrachloride (CCl4), hepatoprotective, Chemistry

    Predicting Berth Stay for Tanker Terminals: A Systematic and Dynamic Approach

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    Given the trend of digitization and increasing number of maritime transport, prediction of vessel berth stay has been triggered for requirements of operation research and scheduling optimization problem in the era of maritime big data, which takes a significant part in port efficiency and maritime logistics enhancement. This study proposes a systematic and dynamic approach of predicting berth stay for tanker terminals. The approach covers three innovative aspects: 1) Data source employed is multi-faceted, including cargo operation data from tanker terminals, time-series data from automatic identification system (AIS), etc. 2) The process of berth stay is decomposed into multiple blocks according to data analysis and information extraction innovatively, and practical operation scenarios are also developed accordingly. 3) The predictive models of berth stay are developed on the basis of prior data analysis and information extraction under two methods, including regression and decomposed distribution. The models are evaluated under four dynamic scenarios with certain designated cargoes among two different terminals. The evaluation results show that the proposed approach can predict berth stay with the accuracy up to 98.81% validated by historical baselines, and also demonstrate the proposed approach has dynamic capability of predicting berth stay among the scenarios. The model may be potentially applied for short-term pilot-booking or scheduling optimizations within a reasonable time frame for advancement of port intelligence and logistics efficiency
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