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Record W2560306568 · doi:10.3390/ijms17122041

The Regulation of Tumor Suppressor p63 by the Ubiquitin-Proteasome System

2016· review· en· W2560306568 on OpenAlexafffund
Stephen Armstrong, Hong Wu, Benfan Wang, Yasser Abuetabh, Consolato Sergi, Roger Leng

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2016
Typereview
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Alberta
FundersAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche MédicaleCanadian Institutes of Health ResearchWomen and Children's Health Research InstituteChildren's Health Research Institute
KeywordsTransactivationUbiquitinProteasomeUbiquitin ligaseSuppressorRegulatorCell biologyBiologyCell cycleApoptosisMetastasis suppressorCancer researchTranscription factorGeneticsCancerGene

Abstract

fetched live from OpenAlex

The protein p63 has been identified as a homolog of the tumor suppressor protein p53 and is capable of inducing apoptosis, cell cycle arrest, or senescence. p63 has at least six isoforms, which can be divided into two major groups: the TAp63 variants that contain the N-terminal transactivation domain and the ΔNp63 variants that lack the N-terminal transactivation domain. The TAp63 variants are generally considered to be tumor suppressors involved in activating apoptosis and suppressing metastasis. ΔNp63 variants cannot induce apoptosis but can act as dominant negative inhibitors to block the function of TAp53, TAp73, and TAp63. p63 is rarely mutated in human tumors and is predominately regulated at the post-translational level by phosphorylation and ubiquitination. This review focuses primarily on regulation of p63 by the ubiquitin E-3 ligase family of enzymes via ubiquitination and proteasome-mediated degradation, and introduces a new key regulator of the p63 protein.

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 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)0.002
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 score0.954
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.024
GPT teacher head0.324
Teacher spread0.301 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations50
Published2016
Admission routes2
Has abstractyes

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