A defined platform of human peri-gastrulation-like biological fate patterning reveals coordination between Reaction-Diffusion and Positional-Information
Bibliographic record
Abstract
Abstract How position dependent cell fate acquisition occurs during embryogenesis has been a central question in developmental biology. To study this process, we developed a defined, high-throughput assay using BMP4 to induce peri-gastrulation-like fate patterning in geometrically constrained human pluripotent stem cell colonies. We observed that, upon BMP4 treatment, phosphorylated SMAD1 (pSMAD1) activity in the colonies organized into a radial gradient – an observation mechanistically compliant with a BMP4-NOGGIN Reaction-Diffusion (RD) model. Consequent fate acquisition occurred as a function of both the pSMAD1 signaling strength, and induction time – consistent with the Positional-Information (PI) paradigm. Our findings implicate coordination between RD and PI underlying the peri-gastrulation-like fate patterning. This model not only predicts experimental results of perturbing key parameters like colony size, and BMP4 dose, but also identifies experimental conditions that rescue patterning in colonies of sizes that have been reported to be patterning-reticent, and recapitulate RD-like periodic patterns in large colonies.
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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 | 0.000 | 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) | 0.001 | 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".