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用于微计算机断层扫描分析的可扩展方法能够对脑损伤和植入物进行大规模定量表征。

Scalable method for micro-CT analysis enables large scale quantitative characterization of brain lesions and implants.

作者信息

Kastner David B, Kharazia Viktor, Nevers Rhino, Smyth Clay, Astudillo-Maya Daniela A, Williams Greer M, Yang Zhounan, Holobetz Cristofer M, Santina Luca Della, Parkinson Dilworth Y, Frank Loren M

机构信息

Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, 94143, USA.

Kavli Institute for Fundamental Neuroscience and Department of Physiology, University of California, San Francisco, CA, 94158, USA.

出版信息

Sci Rep. 2020 Nov 30;10(1):20851. doi: 10.1038/s41598-020-77796-3.

Abstract

Anatomic evaluation is an important aspect of many studies in neuroscience; however, it often lacks information about the three-dimensional structure of the brain. Micro-CT imaging provides an excellent, nondestructive, method for the evaluation of brain structure, but current applications to neurophysiological or lesion studies require removal of the skull as well as hazardous chemicals, dehydration, or embedding, limiting their scalability and utility. Here we present a protocol using eosin in combination with bone decalcification to enhance contrast in the tissue and then employ monochromatic and propagation phase-contrast micro-CT imaging to enable the imaging of brain structure with the preservation of the surrounding skull. Instead of relying on descriptive, time-consuming, or subjective methods, we develop simple quantitative analyses to map the locations of recording electrodes and to characterize the presence and extent of hippocampal brain lesions.

摘要

解剖学评估是神经科学许多研究的一个重要方面;然而,它往往缺乏关于大脑三维结构的信息。微型计算机断层扫描(Micro-CT)成像为大脑结构评估提供了一种出色的、非破坏性的方法,但目前在神经生理学或损伤研究中的应用需要去除颅骨以及使用危险化学品、进行脱水或包埋,这限制了它们的可扩展性和实用性。在此,我们提出一种方案,即使用伊红结合骨脱钙来增强组织对比度,然后采用单色和传播相衬微型计算机断层扫描成像,以在保留周围颅骨的情况下实现大脑结构成像。我们不再依赖描述性、耗时或主观的方法,而是开发了简单的定量分析方法来绘制记录电极的位置,并表征海马体脑损伤的存在和程度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7091/7705725/44a925c804d5/41598_2020_77796_Fig1_HTML.jpg

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