著者

Nozomi Asaoka Hiroyuki Kawai Naoya Nishitani Haruko Kinoshita Norihiro Shibui Kazuki Nagayasu Hisashi Shirakawa Shuji Kaneko

出版者

日本毒性学会

雑誌

The Journal of Toxicological Sciences (ISSN:03881350)

巻号頁・発行日

vol.41, no.6, pp.813-816, 2016-12-01 (Released:2016-11-16)

参考文献数

16

被引用文献数

12

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N-[[1-(5-fluoropentyl)-1H-indazol-3-yl]carbonyl]-3-methyl-D-valine methyl ester (5F-ADB) is one of the most potent synthetic cannabinoids and elicits severe psychotic symptoms in humans, sometimes causing death. To investigate the neuronal mechanisms underlying its toxicity, we examined the effects of 5F-ADB on midbrain dopaminergic and serotonergic systems, which modulate various basic brain functions such as those in reward-related behavior. 5F-ADB-induced changes in spontaneous firing activity of dopaminergic and serotonergic neurons were recorded by ex vivo electrophysiological techniques. In dopaminergic neurons, 5F-ADB (1 μM) significantly increased the spontaneous firing rate, while 5F-ADB failed to activate dopaminergic neurons in the presence of the CB1 antagonist AM251 (1 μM). However, the same concentration of 5F-ADB did not affect serotonergic-neuron activity. These results suggest that 5F-ADB activates local CB1 receptors and potentiates midbrain dopaminergic systems with no direct effects on midbrain serotonergic systems.

著者

Shuji Kaneko Takuya Nagashima

出版者

The Pharmaceutical Society of Japan

雑誌

Biological and Pharmaceutical Bulletin (ISSN:09186158)

巻号頁・発行日

vol.43, no.3, pp.362-365, 2020-03-01 (Released:2020-03-01)

参考文献数

11

被引用文献数

15

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Recent pharmacological studies have been developed based on finding new disease-related genes, accompanied by the production of gene-manipulated disease model animals and high-affinity ligands for the target proteins. However, the emergence of this gene-based strategy in drug development has led to the rapid depletion of drug target molecules. To overcome this, we have attempted to utilize clinical big data to explore a novel and unexpected hypothesis of drug–drug interaction that would lead to drug repositioning. Here, we introduce our data-driven approach in which adverse event self-reports are statistically analyzed and compared in order to find and validate new drug targets. The hypotheses provided by such a data-driven approach will likely impact the style of future drug development and pharmaceutical study.