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Record W2070404499 · doi:10.1042/bj20121667

Evidence of a novel role for Pygopus in rRNA transcription

2013· article· en· W2070404499 on OpenAlexafffund
Phillip Andrews, Zhijian He, Youlian R. Tzenov, Catherine Popadiuk, Kenneth R. Kao

Bibliographic record

VenueBiochemical Journal · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsTranscription (linguistics)Ribosomal RNABiologyComputational biologyGeneticsGenePhilosophy

Abstract

fetched live from OpenAlex

Increased protein synthesis during cell proliferation is accompanied by a compensatory increase in efficient ribosome production, but the mechanisms by which cells adapt to this requirement are not fully understood. In the present study, we demonstrate evidence that Pygo (Pygopus), a protein originally identified as a core component of the Wnt-β-catenin transcription complex is also involved in rRNA transcription during cancer cell growth. Pygo was detected in the nucleoli of several transformed cell lines and was associated with treacle and UBF (upstream binding factor), proteins that are essential for ribosome biogenesis in development and cancer. Pygo was also detected at the ribosomal gene promoter along with core components of the rDNA (ribosomal DNA) transcription complex. RNAi (RNA interference)-mediated depletion of hPygo2 (human Pygo 2) reduced histone H4 acetylation at the rDNA promoter, down-regulated rRNA production, and induced growth arrest in both p53-positive and -negative cells. In p53-positive cells, hPygo2 knockdown triggered the ribosomal stress pathway, culminating in p53-dependent growth arrest at G1-phase of the cell cycle. The results of the present study suggest a novel involvement of Pygo in the promotion of rRNA transcription in cancer cells.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.108

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 head0.061
GPT teacher head0.279
Teacher spread0.218 · 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 designBench or experimental
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

Citations10
Published2013
Admission routes2
Has abstractyes

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