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    In:  Journal of ethnopharmacology : an interdisciplinary journal devoted to bioscientific research on indigenous drugs Vol. 174 (2015), p. 230
    ISSN: 0378-8741
    Language: English
    Titel der Quelle: Journal of ethnopharmacology : an interdisciplinary journal devoted to bioscientific research on indigenous drugs
    Publ. der Quelle: Shannon : Elsevier Science Ireland
    Angaben zur Quelle: Vol. 174 (2015), p. 230
    DDC: 610
    Abstract: Dolichos falcatus Klein (DF), a Chinese Dai ethnic medicine popularly known as "Tuoyeteng" in Yunnan province of China, has been widely used in China to treat fracture, rheumatoid arthritis and soft tissue injuries for a long time. Our previous study showed that saponins in DF (DFS) ameliorated the gouty arthritis induced by MSU crystals in vivo and in vitro. The present study was carried out to evaluate the no-observed-adverse-effect level (NOAEL) of DFS. Sprague-Dawley rats (10/sex/group) were gavaged with DFS at dose level of 0, 50, 100 and 200mg/kg body weight /day for 90-days. DFS administration did not result in mortality or show treatment-related changes in clinical signs of toxicity, body weights gain or feed consumption. Similarly, in addition to slightly hemolytic anemia and gastrointestinal tract lesion in males of high-dose treatment group, no toxicologically significant treatment-related changes in hematological, clinical chemistry, urine analysis parameters, organ weights, and macroscopic and microscopic abnormalities were noted during the testing period. The results of subchronic toxicity study support the NOAEL for DFS as 200mg/kg/d in females and as 100mg/kg/d in males. These results provide an important reference for further DFS-related clinical trials or new drug exploration.
    Note: Copyright: Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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  • 2
    ISBN: 9783036574431 , 9783036574424
    Language: Undetermined
    Pages: 1 Online-Ressource (262 p.)
    Keywords: Technology: general issues ; History of engineering & technology ; Transport technology & trades
    Abstract: Maritime traffic data (e.g., radar data, AIS data, and CCTV data) provide designers, officers on watch, and traffic operators with extensive information about the states of ships at present and in history, representing a treasure trove for behavior analysis. Additionally, navigation rules and regulations (i.e., knowledge) offer valuable prior knowledge about ship manners at sea. Combining multisource heterogeneous big data and artificial intelligence techniques inspires innovative and important means for the development of MASS. This reprint collects twelve contributions published in “Data-/Knowledge-Driven Behavior Analysis of Maritime Autonomous Surface Ships” Special Issue during 2021–2022, aiming to provide new views on data-/knowledge-driven analytical tools for maritime autonomous surface ships, including data-driven behavior modeling, knowledge-driven behavior modeling, multisource heterogeneous traffic data fusion, risk analysis and management of MASS, etc
    Note: English
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