Phenotypic characterization of liver tissue heterogeneity through a next-generation 3D single-cell atlas.

ABSTRACT: Three-dimensional (3D) geometrical models are potent tools for quantifying complex tissue features and exploring structure-function relationships. However, these models are generally incomplete due to experimental limitations in acquiring multiple (> 4) fluorescent channels in thick tissue sections simultaneously. Indeed, predictive geometrical and functional models of the liver have been restricted to few tissue and cellular components, excluding important cellular populations such as hepatic stellate cells (HSCs) and Kupffer cells (KCs). Here, we combined deep-tissue immunostaining, multiphoton microscopy, deep-learning techniques, and 3D image processing to computationally expand the number of simultaneously reconstructed tissue structures. We then generated a spatial single-cell atlas

SUBMITTER: Martinez-Torres D 

PROVIDER: S-EPMC10837128 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature