Quantitative relationship between cerebrovascular network and neuronal cell types in mice.
Quantitative relationship between cerebrovascular network and neuronal cell types in mice.
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DOI:
10.1016/j.celrep.2022.110978
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发表时间:
2022-06-21
期刊:
影响因子:
8.8
通讯作者:
Kim, Yongsoo
中科院分区:
文献类型:
--
作者:
Wu, Yuan-ting;Bennett, Hannah C.;Chon, Uree;Vanselow, Daniel J.;Zhang, Qingguang;Munoz-Castarieda, Rodrigo;Cheng, Keith C.;Osten, Pavel;Drew, Patrick J.;Kim, Yongsoo
The cerebrovasculature and its mural cells must meet brain regional energy demands, but how their spatial relationship with different neuronal cell types varies across the brain remains largely unknown. Here we apply brain-wide mapping methods to comprehensively define the quantitative relationships between the cerebrovasculature, capillary pericytes, and glutamatergic and GABAergic neurons, including neuronal nitric oxide synthase-positive (nNOS+) neurons and their subtypes in adult mice. Our results show high densities of vasculature with high fluid conductance and capillary pericytes in primary motor sensory cortices compared with association cortices that show significant positive and negative correlations with energy-demanding parvalbumin+ and vasomotor nNOS+ neurons, respectively. Thalamo-striatal areas that are connected to primary motor sensory cortices also show high densities of vasculature and pericytes, suggesting dense energy support for motor sensory processing areas. Our cellular-resolution resource offers opportunities to examine spatial relationships between the cerebrovascular network and neuronal cell composition in largely understudied subcortical areas. Wu et al. generate cerebrovascular, pericyte, and neuronal cell type maps with their distribution and spatial relationship to understand the organization of brain energy infrastructure in mice. Dense cerebrovascular networks support the high energy demand of motor sensory circuits with enriched parvalbumin neurons compared with association areas with a high density of nNOS neurons.
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影响因子:
7.7
作者:
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通讯作者:
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