Cytokinetic furrowing and abscission dynamics during brain development revealed by live imaging is a research paper. On theSindex it has a DataRank of 0.130. It has been cited 1 time, with 1 citing works in its 1-hop citation network. Its calibrated FAIR score is 33/100.
Summary McNeely et al. quantitatively analyze polarized cytokinetic furrow ingression and abscission in mouse neuroepithelium by live imaging. The findings show important differences from HeLa cells, and suggest abscission timing and midbody release may be developmentally regulated, to influence daughter cell fate during brain growth. Abstract While mechanisms of cytokinesis have been identified in single cell models, the spatial and temporal regulation in developing tissues is less understood. Here we compare cytokinetic furrowing and abscission in mouse neuroepithelial stem cells (NESCs) at different developmental stages and in a cytokinesis mutant, including imaging abscission dynamics in a polarized epithelium for the first time. We find that asymmetric furrows of NESCs ingress at a constant but slow rate, and form the midbody at the apical membrane. Usually, bilateral abscission on each midbody flank releases the midbody remnant extracellularly. Interestingly, midbody remnants are more associated with early proliferative divisions. Unexpectedly, in the microcephalic Kif20b mutant, abscission is accelerated and occurs when the midbody is wider. The daughter cells of mutant NESCs show increased cell cycle exit that is p53-independent. We suggest that abscission mechanisms are developmentally regulated. These results provide significant insight into adaptations of a fundamental cell biological process required for proper brain growth.
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Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.104
From this paper's citation signal
Citation Network Contribution
0.0264
From 1 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 80% comes from its base citations and 20% from the citation network (1 citing paper contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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