Depletion of nuclear actin is a key mediator of quiescence in epithelial cells
Bibliographic record
Abstract
Functional differentiation is orchestrated by precise growth-regulatory controls conveyed by the tissue microenvironment. Cues from laminin 111 (LN1) lower transcription and suppress mammary epithelial cell growth in culture, but how LN1 induces quiescence is unknown. Recent literature points to involvement of nuclear β-actin in transcriptional regulation. Here, we show that quiescence induced by growth factor withdrawal, or LN1 addition, rapidly decreases nuclear β-actin. LN1, but not other extracellular matrix (ECM) molecules, decreases the levels of nuclear β-actin and destabilizes RNA polymerase (RNA Pol) II and III binding to transcription sites, leading to a dramatic drop in transcription and DNA synthesis. Constitutive overexpression of globular β-actin in the nucleus reverses the effect of LN1 on transcription and RNA Pol II association and prevents the cells from becoming quiescent in the presence of LN1. The physiological relevance of our findings was verified by identifying a clear spatial separation of LN1 and β-actin in developing mammary end buds. These data indicate a novel role for nuclear β-actin in growth arrest of epithelial cells and underscore the importance of the integrity of the basement membrane in homeostasis.
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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".