Epidermal stem cells self-renew upon neighboring differentiation
Bibliographic record
Abstract
Many adult tissues are dynamically sustained by the rapid turnover of stem cells. Yet, how cell fates such as self-renewal and differentiation are orchestrated to achieve long-term homeostasis remains elusive. Studies utilizing clonal tracing experiments in multiple tissues have argued that while stem cell fate is balanced at the population level, individual cell fate - to divide or differentiate – is determined intrinsically by each cell seemingly at random ( 1 2 3 4 5). These studies leave open the question of how cell fates are regulated to achieve fate balance across the tissue. Stem cell fate choices could be made autonomously by each cell throughout the tissue or be the result of cell coordination ( 6 7). Here we developed a novel live tracking strategy that allowed recording of every division and differentiation event within a region of epidermis for a week. These measurements reveal that stem cell fates are not autonomous. Rather, direct neighbors undergo coupled opposite fate decisions. We further found a clear ordering of events, with self-renewal triggered by neighbor differentiation, but not vice-versa. Typically, around 1-2 days after cell delamination, a neighboring cell entered S/G2 phase and divided. Functional blocking of this local feedback showed that differentiation continues to occur in the absence of cell division, resulting in a rapid depletion of the epidermal stem cell pool. We thus demonstrate that the epidermis is maintained by nearest neighbor coordination of cell fates, rather than by asymmetric divisions or fine-tuned cell-autonomous stochastic fate choices. These findings establish differentiation-dependent division as a core feature of homeostatic control, and define the relevant time and length scales over which homeostasis is enforced in epithelial tissues.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".