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Record W2069167711 · doi:10.4161/cc.20207

The emerging functions of the p53-miRNA network in stem cell biology

2012· review· en· W2069167711 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCell Cycle · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsManitoba Beekeepers' Association
FundersNational Cancer Institute
KeywordsBiologyReprogrammingStem cellInduced pluripotent stem cellCell biologySomatic cellEmbryonic stem cellmicroRNACellular differentiationInduced stem cellsCellGeneticsGene

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.264
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it