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Record W2589027510 · doi:10.1073/pnas.1621436114

p53 regulates the cardiac transcriptome

2017· article· en· W2589027510 on OpenAlexafffund
Tak W. Mak, Ludger Hauck, Daniela Grothe, Filio Billia

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsHeart and Stroke FoundationUniversity of TorontoUniversity Health NetworkToronto General HospitalPrincess Margaret Cancer CentreOntario Institute for Cancer Research
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsTranscriptomeBiologyGeneRegulatorEpigeneticsTranscription factorGene expressionRegulation of gene expressionCell biologyGene regulatory networkGenetics

Abstract

fetched live from OpenAlex

The tumor suppressor Trp53 (p53) inhibits cell growth after acute stress by regulating gene transcription. The mammalian genome contains hundreds of p53-binding sites. However, whether p53 participates in the regulation of cardiac tissue homeostasis under normal conditions is not known. To examine the physiologic role of p53 in adult cardiomyocytes in vivo, Cre-loxP-mediated conditional gene targeting in adult mice was used. Genome-wide transcriptome analyses of conditional heart-specific p53 knockout mice were performed. Genome-wide annotation and pathway analyses of >5,000 differentially expressed transcripts identified many p53-regulated gene clusters. Correlative analyses identified >20 gene sets containing more than 1,000 genes relevant to cardiac architecture and function. These transcriptomic changes orchestrate cardiac architecture, excitation-contraction coupling, mitochondrial biogenesis, and oxidative phosphorylation capacity. Interestingly, the gene expression signature in p53-deficient hearts confers resistance to acute biomechanical stress. The data presented here demonstrate a role for p53, a previously unrecognized master regulator of the cardiac transcriptome. The complex contributions of p53 define a biological paradigm for the p53 regulator network in the heart under physiological conditions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.275
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.319
Teacher spread0.273 · 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

Citations130
Published2017
Admission routes2
Has abstractyes

Explore more

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