Extrapolating brain development from experimental species to humans

Extrapolating brain development from experimental species to humans
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DOI:
10.1016/j.neuro.2007.01.014
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发表时间:
2007-09-01
期刊:
影响因子:
3.4
通讯作者:
Arland, K. J. S.
Arland, K. J. S.
中科院分区:
医学3区
文献类型:
--
作者:
Clancy, Barbara;Finlay, Barbara L.;Arland, K. J. S.

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为了更好地了解不同危害对发育中的人类神经系统的神经毒性影响,研究人员和临床医生依赖于从许多以不同速度发育和成熟的模型物种收集的数据。我们回顾了常用的方法来推断大脑发育的时间从实验哺乳动物物种到人类,包括形态学比较,“经验法则”和“基于事件”的分析。大多数研究在范围或细节上都受到限制,许多研究必然局限于大鼠/人类的比较,很少有人能识别出以不同速度发育的大脑区域。我们认为这个问题最好用“神经信息学”来解决,这是一种结合了神经科学、进化科学、统计建模和计算机科学的分析。目前使用的这种方法涉及数值分配给10个哺乳动物物种和数百个经验得出的发展中的神经事件,包括特定的灵长类动物的进化进展。其结果是一个可访问的在线资源(http://www.translatingtime.net/),可用于将实验室物种的神经发育文献中的日期等同于人类,预测人类缺乏数据的神经发育事件,并帮助开发临床相关的实验模型。(C)2007爱思唯尔公司All rights reserved.
To better understand the neurotoxic effects of diverse hazards on the developing human nervous system, researchers and clinicians rely on data collected from a number of model species that develop and mature at varying rates. We review the methods commonly used to extrapolate the timing of brain development from experimental mammalian species to humans, including morphological comparisons, "rules of thumb" and "event-based" analyses. Most are unavoidably limited in range or detail, many are necessarily restricted to rat/human comparisons, and few can identify brain regions that develop at different rates. We suggest this issue is best addressed using "neuroinformatics", an analysis that combines neuroscience, evolutionary science, statistical modeling and computer science. A current use of this approach relates numeric values assigned to 10 mammalian species and hundreds of empirically derived developing neural events, including specific evolutionary advances in primates. The result is an accessible, online resource (http://www.translatingtime.net/) that can be used to equate dates in the neurodevelopmental literature across laboratory species to humans, predict neurodevelopmental events for which data are lacking in humans, and help to develop clinically relevant experimental models. (C) 2007 Elsevier Inc. All rights reserved.