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Record W2671227891 · doi:10.7554/elife.24139

Poly(A) tail length regulates PABPC1 expression to tune translation in the heart

2017· article· en· W2671227891 on OpenAlexaff
Sandip Chorghade, Joseph Seimetz, Russell Emmons, Jing Yang, Stefan Bresson, Michael De Lisio, Gianni Parise, Nicholas K. Conrad, Auinash Kalsotra

Bibliographic record

VenueeLife · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcMaster UniversityUniversity of Ottawa
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsTranslation (biology)Poly(A)-binding proteinMessenger RNACell biologyPolyadenylationProtein biosynthesisBiologyHEK 293 cellsBinding proteinRegulation of gene expressionMolecular biologyCell cultureGeneBiochemistryGenetics

Abstract

fetched live from OpenAlex

The rate of protein synthesis in the adult heart is one of the lowest in mammalian tissues, but it increases substantially in response to stress and hypertrophic stimuli through largely obscure mechanisms. Here, we demonstrate that regulated expression of cytosolic poly(A)-binding protein 1 (PABPC1) modulates protein synthetic capacity of the mammalian heart. We uncover a poly(A) tail-based regulatory mechanism that dynamically controls PABPC1 protein synthesis in cardiomyocytes and thereby titrates cellular translation in response to developmental and hypertrophic cues. Our findings identify PABPC1 as a direct regulator of cardiac hypertrophy and define a new paradigm of gene regulation in the heart, where controlled changes in poly(A) tail length influence mRNA translation.

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 score0.128
Threshold uncertainty score0.181

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 head0.028
GPT teacher head0.319
Teacher spread0.292 · 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

Citations99
Published2017
Admission routes1
Has abstractyes

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