Cell lineage-resolved embryonic morphological map reveals signaling associated with cell fate and size asymmetry
Bibliographic record
Abstract
How cells change shape is crucial for the development of tissues, organs and embryos. However, studying these shape changes in detail is challenging. Here we present a comprehensive real-time cellular map that covers over 95% of the cells formed during Caenorhabditis elegans embryogenesis, featuring nearly 400,000 3D cell regions. This map includes information on each cell’s identity, lineage, fate, shape, volume, surface area, contact area, and gene expression profiles, all accessible through our user-friendly software and website. Our map allows for detailed analysis of key developmental processes, including dorsal intercalation, intestinal formation, and muscle assembly. We show how Notch and Wnt signaling pathways, along with mechanical forces from cell interactions, regulate cell fate decisions and size asymmetries. Our findings suggest that repeated Notch signaling drives size disparities in the large excretory cell, which functions like a kidney. This work sets the stage for in-depth studies of the mechanisms controlling cell fate differentiation and morphogenesis. The authors present a 3D map of nearly all cells in C. elegans embryos, revealing how cell shape, size, and fate change over time. They show how Notch and Wnt signaling, along with mechanical forces, influence development, including organ formation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".