Cell size and polarization determine cytokinesis furrow ingression dynamics in mouse embryos
Bibliographic record
Abstract
Cytokinesis is the final step of cell division during which a contractile ring forms a furrow that partitions the cytoplasm in two. How furrow ingression is spatiotemporally regulated and how it is adapted to complex cellular environments and developmental transitions remain poorly understood. Here, we examine furrow ingression dynamics in the context of the early mouse embryo and find that cell size is a powerful determinant of furrow ingression speed during reductive cell divisions. In addition, the emergence of cell polarity and the assembly of the apical domain in outer cells locally inhibits the recruitment of cytokinesis components and thereby negatively regulates furrow ingression specifically on one side of the furrow. We show that this biasing of cytokinesis is not dependent upon cell–cell adhesion or shape but rather is cell intrinsic and is caused by a paucity of cytokinetic machinery in the apical domain. The results thus reveal that in the mouse embryo cell polarity directly regulates the recruitment of cytokinetic machinery in a cell-autonomous manner and that subcellular organization can instigate differential force generation and constriction speed in different zones of the cytokinetic furrow.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".