Formation of benign tumors by stem cell deregulation
Bibliographic record
Abstract
Within living organisms, stem cells respond to various cues, including to niche signals and growth factors. Niche signals originate from the stem cell's microenvironment and promote the undifferentiated state by preventing differentiation, allowing for stem cell self-renewal. On the other hand, growth factors promote stem cell growth and proliferation, while their sources comprise of a systemic input reflecting the animal's nutritional and metabolic status, and a localized, homeostatic feedback signal from the tissue that the stem cells serve. That homeostatic signal prevents unnecessary stem cell proliferation when the corresponding differentiated tissues already have optimal cell contents. Here, we recapitulate progresses made in our understanding of in vivo stem cell regulation, largely using simple models, and draw the conclusion that 2 types of stem cell deregulations can provoke the formation of benign tumors. Namely, constitutive niche signaling promotes the formation of undifferentiated "stem cell" tumors, while defective homeostatic signaling leads to the formation of differentiated tumors. Finally, we provide evidence that these general principles may be conserved in mammals and as such, may underlie benign tumor formation in humans, while benign tumors can evolve into cancer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".