Pearls and pitfalls in experimental models of spreading depression
Pearls and pitfalls in experimental models of spreading depression
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DOI：
10.1177/0333102412470216
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发表时间：
2013-06-01
期刊：
影响因子：
4.9
通讯作者：
Ayata, Cenk
中科院分区：
文献类型：
--
作者：
Ayata, Cenk
背景：扩散性抑制（SD）是偏头痛先兆的电生理学基础，也是头痛的潜在触发因素。自从Leao于1944年发现SD以来，SD已经从被视为一种附带现象转变为与偏头痛和脑损伤的病理生理学相关的治疗靶点。目的：尽管经过数十年的研究，SD的基础仍然知之甚少，阻碍了我们选择性阻断其发生和传播的努力。然而，实验模型已用于测量SD发生的可能性（即SD易感性），并表征SD的遗传、生理和药理学调节，以寻找潜在的治疗方法，如偏头痛预防和中风。在这里，我回顾实验SD敏感性终点和替代品，最低的基本模型要求，以提高其效用在drug screen.Conclusion：SD敏感性的实验模型的优势和注意事项的关键重新评估需要设定标准，提高数据质量，解释和和解。
Background: Spreading depression (SD) is the electrophysiological substrate of migraine aura and a potential trigger for headache. Since its discovery by Leao in 1944, SD has transformed from being viewed as an epiphenomenon into a therapeutic target relevant in the pathophysiology of migraine and brain injury.Aim: Despite decades of research, the underpinnings of SD are still poorly understood, hampering our efforts to selectively block its initiation and spread. Experimental models have nevertheless been useful to measure the likelihood of SD occurrence (i.e. SD susceptibility) and characterize genetic, physiological and pharmacological modulation of SD in search of potential therapies, such as in migraine prophylaxis and stroke. Here, I review experimental SD susceptibility endpoints and surrogates, and minimum essential model requirements to improve their utility in drug screening.Conclusion: A critical reappraisal of strengths and caveats of experimental models of SD susceptibility is needed to set standards and improve data quality, interpretation and reconciliation.