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Record W2090669556 · doi:10.1038/cddis.2013.224

Regulatory feedback loop between TP73 and TRIM32

2013· article· en· W2090669556 on OpenAlexafffund
Laura González-Cano, A-L Hillje, Sandra Fuertes-Álvarez, Margarita M. Marqués, Àngel Blanch, R W Ian, Meredith S. Irwin, Jens C. Schwamborn, María C. Marín

Bibliographic record

VenueCell Death and Disease · 2013
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Cancer Society Research InstituteDeutsche Forschungsgemeinschaft
KeywordsUbiquitin ligaseTranscription factorUbiquitinCell biologySuppressorTranscription (linguistics)BiologyNeurogenesisTranscriptional regulationEmbryonic stem cellGeneticsGene

Abstract

fetched live from OpenAlex

The p73 transcription factor is one of the members of the p53 family of tumor suppressors with unique biological functions in processes like neurogenesis, embryonic development and differentiation. For this reason, p73 activity is tightly regulated by multiple mechanisms, including transcription and post-translational modifications. Here, we identified a novel regulatory loop between TAp73 and the E3 ubiquitin ligase tripartite motif protein 32 (TRIM32). TRIM32, a new direct p73 transcriptional target in the context of neural progenitor cells, is differentially regulated by p73. Although TAp73 binds to the TRIM32 promoter and activates its expression, TAp73-induced TRIM32 expression is efficiently repressed by DNp73. TRIM32 in turn physically interacts with TAp73 and promotes its ubiquitination and degradation, impairing p73-dependent transcriptional activity. This mutual regulation between p73 and TRIM32 constitutes a novel feedback loop, which might have important implications in central nervous system development as well as relevance in oncogenesis, and thus emerges as a possible therapeutic target.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.504

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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations34
Published2013
Admission routes2
Has abstractyes

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