The emerging functions of the p53-miRNA network in stem cell biology
Bibliographic record
Abstract
The p53 pathway plays an essential role in tumor suppression, regulating multiple cellular processes coordinately to maintain genome integrity in both somatic cells and stem cells. Despite decades of research dedicated to p53 function in differentiated somatic cells, we are just starting to understand the complexity of the p53 pathway in the biology of pluripotent stem cells and tissue stem cells. Recent studies have demonstrated that p53 suppresses proliferation, promotes differentiation of embryonic stem (ES) cells and constitutes an important barrier to somatic reprogramming. In addition, emerging evidence reveals the role of the p53 network in the self-renewal, proliferation and genomic integrity of adult stem cells. Interestingly, non-coding RNAs, and microRNAs in particular, are integral components of the p53 network, regulating multiple p53-controlled biological processes to modulate the self-renewal and differentiation potential of a variety of stem cells. Thus, elucidation of the p53-miRNA axis in stem cell biology may generate profound insights into the mechanistic overlap between malignant transformation and stem cell biology.
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.
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 | 0.001 | 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 | 0.002 |
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".