Genes that affect both cell growth and polarity mediate stem cell quiescence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stem cells possess the capacity to expand and self-renew and do so by dividing in either a symmetrical or an asymmetrical manner. Under particular circumstances, some stem cell populations can undergo prolonged cell cycle arrest or quiescence, until they are triggered to divide by a given stimulus. In cancer treatment, these populations represent a significant roadblock to efficient therapies as their non-dividing state renders them refractory to most commonly used cytotoxic interventions. In certain organisms, germline stem cells undergo quiescence if animals experience inappropriate growth conditions, and recent studies have determined that the level of insulin signaling is key in the regulation of their proliferation rate, and that it functions through at least two tumor suppressor genes, PTEN and LKB1. These gene products regulate both growth and polarity in diverse cellular contexts, while it remains unclear how they can modulate cell division and prevent tumorigenesis through each of these functions, and whether indeed these functions are separable. We hope that understanding how these tumor suppressor genes impinge on quiescent stem cell populations could provide us with a means of designing more effective therapies to reduce the frequency of stem cell-derived tumor growth that occurs following treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it