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A protocol for visualization of murine in situ neurovascular interfaces.

Authors :
Dang DD
Chandrashekhar V
Chandrashekhar V
Ghabdanzanluqui N
Knutsen RH
Nazari MA
Nimmagadda L
Donahue DR
McGavern DB
Kozel BA
Heiss JD
Pacak K
Zhuang Z
Rosenblum JS
Source :
STAR protocols [STAR Protoc] 2023 Sep 15; Vol. 4 (3), pp. 102367. Date of Electronic Publication: 2023 Jun 19.
Publication Year :
2023

Abstract

Mapping cranial vasculature and adjacent neurovascular interfaces in their entirety will enhance our understanding of central nervous system function in any physiologic state. We present a workflow to visualize in situ murine vasculature and surrounding cranial structures using terminal polymer casting of vessels, iterative sample processing and image acquisition, and automated image registration and processing. While this method does not obtain dynamic imaging due to mouse sacrifice, these studies can be performed before sacrifice and processed with other acquired images. For complete details on the use and execution of this protocol, please refer to Rosenblum et al. <superscript>1</superscript> .<br />Competing Interests: Declaration of interests J.S.R., Vikram Chandrashekhar, and Vibhu Chandrashekhar are affiliated with Neurosimplicity, LLC, which is a medical device and technology company focusing on medical image processing. The content of this manuscript does not necessarily reflect the views, policies, or opinions of the U.S. Department of Health and Human Services. The mention of commercial products, their source, or their use in connection with material reported herein is not to be construed as an actual or implied endorsement of such products by the United States Government. Neurosimplicity, LLC has patent applications directed to the technology described in this manuscript.<br /> (Published by Elsevier Inc.)

Subjects

Subjects :
Animals
Mice
Workflow
Skull

Details

Language :
English
ISSN :
2666-1667
Volume :
4
Issue :
3
Database :
MEDLINE
Journal :
STAR protocols
Publication Type :
Academic Journal
Accession number :
37339049
Full Text :
https://doi.org/10.1016/j.xpro.2023.102367