睡眠(系统调用)
增食欲素
认知
神经科学
医学
药理学
受体
食欲素受体
心理学
内科学
神经肽
计算机科学
操作系统
作者
Jason M. Uslaner,Spencer J. Tye,Donnie Eddins,Xiaohai Wang,Steven V. Fox,Alan T. Savitz,Jacquelyn Binns,Christopher E. Cannon,Susan L. Garson,Lihang Yao,Robert A. Hodgson,Joanne Stevens,Mark R. Bowlby,Pamela L. Tannenbaum,Joseph Brunner,Terrence P. McDonald,Anthony L. Gotter,Scott D. Kuduk,Paul J. Coleman,Christopher J. Winrow
标识
DOI:10.1126/scitranslmed.3005213
摘要
Current treatments for insomnia, such as zolpidem (Ambien) and eszopiclone (Lunesta), are γ-aminobutyric acid type A (GABAA)-positive allosteric modulators that carry a number of side effects including the potential to disrupt cognition. In an effort to develop better tolerated medicines, we have identified dual orexin 1 and 2 receptor antagonists (DORAs), which promote sleep in preclinical animal models and humans. We compare the effects of orally administered eszopiclone, zolpidem, and diazepam to the dual orexin receptor antagonist DORA-22 on sleep and the novel object recognition test in rat, and on sleep and two cognition tests (delayed match to sample and serial choice reaction time) in the rhesus monkey. Each compound's minimal dose that promoted sleep versus the minimal dose that exerted deficits in these cognitive tests was determined, and a therapeutic margin was established. We found that DORA-22 has a wider therapeutic margin for sleep versus cognitive impairment in rat and rhesus monkey compared to the other compounds tested. These data were further supported with the demonstration of a wider therapeutic margin for DORA-22 compared to the other compounds on sleep versus the expression of hippocampal activity-regulated cytoskeletal-associated protein (Arc), an immediate-early gene product involved in synaptic plasticity. These findings suggest that DORAs might provide an effective treatment for insomnia with a greater therapeutic margin for sleep versus cognitive disturbances compared to the GABAA-positive allosteric modulators currently in use.
科研通智能强力驱动
Strongly Powered by AbleSci AI