Global community effect: large-scale cooperation yields collective survival of differentiating embryonic stem cells [preprint]
Bibliographic record
Abstract
“Community effect” conventionally describes differentiation occurring only when enough cells help their local (micrometers-scale) neighbors differentiate. Although new community effects are being uncovered for myriad differentiations, macroscopic-scale community effects - fates of millions of cells all entangled across centimeters - remain elusive. We found that differentiating mouse Embryonic Stem (ES) cells that are scattered as individuals over many centimeters form one macroscopic entity via long-range communications. The macroscopic population avoids extinction only if its centimeter-scale density is above a threshold value. Single-cell-level measurements, transcriptomics, and mathematical modeling revealed that this “global community effect” occurs because differentiating ES-cell populations secrete, accumulate, and sense survival-promoting factors, including FGF4, that diffuse over many millimeters and activate Yap1-induced survival mechanisms. Only above-threshold-density populations accumulate above-threshold-concentrations of factors required to survive. We thus uncovered a previously overlooked, large-scale cooperation that underlies ES-cell differentiation. Tuning such large-scale cooperation may enable constructions of macroscopic, synthetic multicellular structures.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".