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Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy

Quantifying neuron morphology and distribution at the whole-brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single-cell labeling and whole-brain imaging to study human brains. We propose adaptive cell tom...

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Autores principales: Han, Xiaofeng, Guo, Shuxia, Ji, Nan, Li, Tian, Liu, Jian, Ye, Xiangqiao, Wang, Yi, Yun, Zhixi, Xiong, Feng, Rong, Jing, Liu, Di, Ma, Hui, Wang, Yujin, Huang, Yue, Zhang, Peng, Wu, Wenhao, Ding, Liya, Hawrylycz, Michael, Lein, Ed, Ascoli, Giorgio A., Xie, Wei, Liu, Lijuan, Zhang, Liwei, Peng, Hanchuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569712/
https://www.ncbi.nlm.nih.gov/pubmed/37824619
http://dx.doi.org/10.1126/sciadv.adf3771
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author Han, Xiaofeng
Guo, Shuxia
Ji, Nan
Li, Tian
Liu, Jian
Ye, Xiangqiao
Wang, Yi
Yun, Zhixi
Xiong, Feng
Rong, Jing
Liu, Di
Ma, Hui
Wang, Yujin
Huang, Yue
Zhang, Peng
Wu, Wenhao
Ding, Liya
Hawrylycz, Michael
Lein, Ed
Ascoli, Giorgio A.
Xie, Wei
Liu, Lijuan
Zhang, Liwei
Peng, Hanchuan
author_facet Han, Xiaofeng
Guo, Shuxia
Ji, Nan
Li, Tian
Liu, Jian
Ye, Xiangqiao
Wang, Yi
Yun, Zhixi
Xiong, Feng
Rong, Jing
Liu, Di
Ma, Hui
Wang, Yujin
Huang, Yue
Zhang, Peng
Wu, Wenhao
Ding, Liya
Hawrylycz, Michael
Lein, Ed
Ascoli, Giorgio A.
Xie, Wei
Liu, Lijuan
Zhang, Liwei
Peng, Hanchuan
author_sort Han, Xiaofeng
collection PubMed
description Quantifying neuron morphology and distribution at the whole-brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single-cell labeling and whole-brain imaging to study human brains. We propose adaptive cell tomography (ACTomography), a low-cost, high-throughput, and high-efficacy tomography approach, based on adaptive targeting of individual cells. We established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and one donated fresh postmortem brain. We collected three-dimensional images of 1746 cortical neurons, of which 852 neurons were reconstructed to quantify local dendritic morphology, and mapped to standard atlases. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor field of neuron morphology to characterize anatomical modularity of a human brain.
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spelling pubmed-105697122023-10-13 Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy Han, Xiaofeng Guo, Shuxia Ji, Nan Li, Tian Liu, Jian Ye, Xiangqiao Wang, Yi Yun, Zhixi Xiong, Feng Rong, Jing Liu, Di Ma, Hui Wang, Yujin Huang, Yue Zhang, Peng Wu, Wenhao Ding, Liya Hawrylycz, Michael Lein, Ed Ascoli, Giorgio A. Xie, Wei Liu, Lijuan Zhang, Liwei Peng, Hanchuan Sci Adv Neuroscience Quantifying neuron morphology and distribution at the whole-brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single-cell labeling and whole-brain imaging to study human brains. We propose adaptive cell tomography (ACTomography), a low-cost, high-throughput, and high-efficacy tomography approach, based on adaptive targeting of individual cells. We established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and one donated fresh postmortem brain. We collected three-dimensional images of 1746 cortical neurons, of which 852 neurons were reconstructed to quantify local dendritic morphology, and mapped to standard atlases. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor field of neuron morphology to characterize anatomical modularity of a human brain. American Association for the Advancement of Science 2023-10-12 /pmc/articles/PMC10569712/ /pubmed/37824619 http://dx.doi.org/10.1126/sciadv.adf3771 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Neuroscience
Han, Xiaofeng
Guo, Shuxia
Ji, Nan
Li, Tian
Liu, Jian
Ye, Xiangqiao
Wang, Yi
Yun, Zhixi
Xiong, Feng
Rong, Jing
Liu, Di
Ma, Hui
Wang, Yujin
Huang, Yue
Zhang, Peng
Wu, Wenhao
Ding, Liya
Hawrylycz, Michael
Lein, Ed
Ascoli, Giorgio A.
Xie, Wei
Liu, Lijuan
Zhang, Liwei
Peng, Hanchuan
Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
title Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
title_full Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
title_fullStr Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
title_full_unstemmed Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
title_short Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
title_sort whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569712/
https://www.ncbi.nlm.nih.gov/pubmed/37824619
http://dx.doi.org/10.1126/sciadv.adf3771
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