Automated high-throughput mouse transsynaptic viral tracing using iDISCO+ tissue clearing, light-sheet microscopy, and BrainPipe.
Automated high-throughput mouse transsynaptic viral tracing using iDISCO+ tissue clearing, light-sheet microscopy, and BrainPipe.
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DOI:
10.1016/j.xpro.2022.101289
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发表时间:
2022-06-17
期刊:
影响因子:
--
通讯作者:
Wang, Samuel S-H
中科院分区:
文献类型:
--
作者:
Pisano, Thomas J.;Hoag, Austin T.;Dhanerawala, Zahra M.;Guariglia, Sara R.;Jung, Caroline;Boele, Henk-Jan;Seagraves, Kelly M.;Verpeut, Jessica L.;Wang, Samuel S-H
Transsynaptic viral tracing requires tissue sectioning, manual cell counting, and anatomical assignment, all of which are time intensive. We describe a protocol for BrainPipe, a scalable software for automated anatomical alignment and object counting in light-sheet microscopy volumes. BrainPipe can be generalized to new counting tasks by using a new atlas and training a neural network for object detection. Combining viral tracing, iDISCO+ tissue clearing, and BrainPipe facilitates mapping of cerebellar connectivity to the rest of the murine brain. For complete details on the use and execution of this protocol, please refer to. Using iDISCO+ whole-brain tissue clearing technique for transsynaptic viral tracing BrainPipe enables automated registration and analysis of light-sheet microscopy volumes Combining viral tracing, iDISCO+, and BrainPipe for high-throughput transsynaptic study Transsynaptic viral tracing requires tissue sectioning, manual cell counting, and anatomical assignment, all of which are time intensive. We describe a protocol for BrainPipe, a scalable software for automated anatomical alignment and object counting in light-sheet microscopy volumes. BrainPipe can be generalized to new counting tasks by using a new atlas and training a neural network for object detection. Combining viral tracing, iDISCO+ tissue clearing, and BrainPipe facilitates mapping of cerebellar connectivity to the rest of the murine brain.
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影响因子:
12.4
作者:
Mastakov, MY;Baer, K;During, MJ
通讯作者:
During, MJ
DOI:
10.3791/3564
发表时间:
2012-07-30
期刊:
Journal of visualized experiments : JoVE
影响因子:
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2.7
作者:
van der Walt, Stefan;Schonberger, Johannes L.;Yu, Tony
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