The development of an online database for interventions tested in transgenic mouse models of Alzheimer's disease

K. J. Egan, H. M. Vesterinen, S. K. McCann, E. S. Sena, M. R. MacLeod
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引用次数: 5

Abstract

Despite many efforts by the research community, Alzheimer's disease (AD) is still an incurable neurodegenerative condition that affects an estimated 44 million individuals worldwide and this figure is expected to increase to 135 million by the year 2050. As the research community currently reflects on previous endeavours, it is essential that we maximize the use of existing knowledge to inform future trials in the field. This article describes the development of a systematically identified data set relating to over 300 interventions tested in over 10,000 animals. The data set includes cohort-level information for six structural outcomes and six behavioural assessments. We encourage others to use this dataset to inform the design of future animal experiments modelling AD and to promote effective translation to human health.

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在阿尔茨海默病转基因小鼠模型中测试干预措施的在线数据库的开发
尽管研究界做出了许多努力,但阿尔茨海默病(AD)仍然是一种无法治愈的神经退行性疾病,全球约有4400万人受到影响,预计到2050年这一数字将增加到1.35亿。正如研究界目前对以往努力的反思,我们必须最大限度地利用现有知识,为该领域的未来试验提供信息。本文描述了一个系统识别数据集的开发,该数据集涉及在10,000多只动物中测试的300多种干预措施。数据集包括6个结构结果和6个行为评估的队列水平信息。我们鼓励其他人使用该数据集为未来动物实验建模AD的设计提供信息,并促进对人类健康的有效转化。
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