著者

Xiaorong Wang Huimin Huang Yiyi Zhu Shaoli Li Peifen Zhang Jiajun Jiang Caixi Xi Lingling Wu Xingle Gao Yaoyang Fu Danhua Zhang Yiqing Chen Shaohua Hu Jianbo Lai

出版者

International Research and Cooperation Association for Bio & Socio-Sciences Advancement

雑誌

BioScience Trends (ISSN:18817815)

巻号頁・発行日

pp.2021.01317, (Released:2021-09-30)

参考文献数

60

被引用文献数

6

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Antipsychotic-induced metabolic dysfunction (AIMD) is an intractable clinical challenge worldwide. The situation is becoming more critical as second-generation antipsychotics (SGAs), to a great extent, have replaced the role of first-generation antipsychotics in managing major psychiatric disorders. Although the exact mechanisms for developing AIMD is intricate, emerging evidence has indicated the involvement of the microbiota-gut-brain axis in AIMD. SGAs treatment may change the diversity and compositions of intestinal flora (e.g., decreased abundance of Bacteroidetes and Akkermansia muciniphila, and increased Firmicutes). Short-chain fatty acids and other metabolites derived from gut microbiota, on the one hand, can regulate the activity of intestinal endocrine cells and their secretion of satiety hormones (e.g., glucagon-like peptide 1, peptide YY, cholecystokinin and ghrelin); on the other hand, can activate the vagus nerve or transport into the brain to exert a central modulation of foraging behaviors via binding to neuropeptide receptors. Interestingly, metformin, a classical antidiabetic agent, is capable of alleviating AIMD possibly by regulating the microbiota-gut-brain axis. That is, metformin can not only partially reverse the alterations of gut microbial communities due to SGAs treatment, but also play a positive role in rectifying the disturbances of peripheral and central satiety-related neuropeptides. Current evidence has indicated a promising role for metformin on ameliorating AMID, but further verifications in well-designed clinical trials are still warranted.

著者

Lingling Wu Junyi Zhang Akimasa Fujiwara

出版者

Eastern Asia Society for Transportation Studies

雑誌

Proceedings of the Eastern Asia Society for Transportation Studies

巻号頁・発行日

pp.154, 2011 (Released:2011-09-30)

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This study applies a multiple discrete-continuous extreme value (MDCEV) model to analyze tourist's time use behavior involving multiple activities. The MDCEV model is applied because it has several advantages over other existing time use models, including the joint representation of participation in multiple activities and the allocated time, diminishing marginal utilities (satiation effects), and different baseline utilities. Application analysis is carried out using a data collected from tourists in Japan. Influential factors related to time use in 7 activity categories are explored. Concretely speaking, individual attributes including age, employment status, residential area, travel experience, and trip-related attributes including travel mode, travel party, travel season are found to be important influential factors. It is also observed that the level of satiation is high for shopping activities and low for sport and hot spring activities.