Quiescence Entry, Maintenance, and Exit in Adult Stem Cells
Bibliographic record
Abstract
Cells of unicellular and multicellular eukaryotes can respond to certain environmental cues by arresting the cell cycle and entering a reversible state of quiescence. Quiescent cells do not divide, but can re-enter the cell cycle and resume proliferation if exposed to some signals from the environment. Quiescent cells in mammals and humans include adult stem cells. These cells exhibit improved stress resistance and enhanced survival ability. In response to certain extrinsic signals, adult stem cells can self-renew by dividing asymmetrically. Such asymmetric divisions not only allow the maintenance of a population of quiescent cells, but also yield daughter progenitor cells. A multistep process of the controlled proliferation of these progenitor cells leads to the formation of one or more types of fully differentiated cells. An age-related decline in the ability of adult stem cells to balance quiescence maintenance and regulated proliferation has been implicated in many aging-associated diseases. In this review, we describe many traits shared by different types of quiescent adult stem cells. We discuss how these traits contribute to the quiescence, self-renewal, and proliferation of adult stem cells. We examine the cell-intrinsic mechanisms that allow establishing and sustaining the characteristic traits of adult stem cells, thereby regulating quiescence entry, maintenance, and exit.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".