ArticleExperimental cell research2017
High-content image informatics of the structural nuclear protein NuMA parses trajectories for stem/progenitor cell lineages and oncogenic transformation.
Article in Experimental cell research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence for stromal cell quality assessment: A systematic review of human mesenchymal stromal cell properties and viability.Cell and tissue research · 2026Pooled it
- The mitotic protein NuMA plays a spindle-independent role in nuclear formation and mechanics.The Journal of cell biology · 2020Article
- Fluorescence Imaging of Actin Turnover Parses Early Stem Cell Lineage Divergence and Senescence.Scientific reports · 2019Article
- Orthogonal potency analysis of mesenchymal stromal cell function during ex vivo expansion.Experimental cell research · 2018Article
- Architecture in 3D cell culture: An essential feature for in vitro toxicology.Toxicology in vitro : an international journal published in association with BIBRA · 2017Review
- Special issue: Nuclear architecture and chromatin motions in the DNA damage response.Mutation researchArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Stem and progenitor cells that exhibit significant regenerative potential and critical roles in cancer initiation and progression remain difficult to characterize. Cell fates are determined by reciprocal signaling between the cell microenvironment and the nucleus; hence parameters derived from nuclear remodeling are ideal candidates for stem/progenitor cell characterization. Here we applied high-content, single cell analysis of nuclear shape and organization to examine stem and progenitor cells destined to distinct differentiation endpoints, yet undistinguishable by conventional methods. Nuclear descriptors defined through image informatics classified mesenchymal stem cells poised to either adipogenic or osteogenic differentiation, and oligodendrocyte precursors isolated from different regions of the brain and destined to distinct astrocyte subtypes. Nuclear descriptors also revealed early changes in stem cells after chemical oncogenesis, allowing the identification of a class of cancer-mitigating biomaterials. To capture the metrology of nuclear changes, we developed a simple and quantitative "imaging-derived" parsing index, which reflects the dynamic evolution of the high-dimensional space of nuclear organizational features. A comparative analysis of parsing outcomes via either nuclear shape or textural metrics of the nuclear structural protein NuMA indicates the nuclear shape alone is a weak phenotypic predictor. In contrast, variations in the NuMA organization parsed emergent cell phenotypes and discerned emergent stages of stem cell transformation, supporting a prognosticating role for this protein in the outcomes of nuclear functions.
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Registered trials
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