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Record W4295752673 · doi:10.1093/stcltm/szac068

Carm1 and the Epigenetic Control of Stem Cell Function

2022· article· en· W4295752673 on OpenAlexafffund
John Saber, Michael A. Rudnicki

Bibliographic record

VenueStem Cells Translational Medicine · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyMyogenesisCell biologyMyocyte

Abstract

fetched live from OpenAlex

Coactivator-associated arginine methyltransferase 1 (CARM1) is a methyltransferase whose function has been highly studied in the context of nuclear receptor signaling. However, CARM1 is known to epigenetically regulate expression of several myogenic genes involved in differentiation such as Myog and MEF2C. CARM1 also acts to regulate myogenesis through its influence on various cellular processes from embryonic to adult myogenesis. First, CARM1 has a crucial role in establishing polarity-regulated gene expression during an asymmetric satellite cell division by methylating PAX7, leading to the expression of Myf5. Second, satellite cells express the CARM1-FL and CARM1-ΔE15 isoforms. The former has been shown to promote pre-mRNA splicing through its interaction with CA150 and U1C, leading to their methylation and increased activity, while the latter displays a reduction in both metrics, thus, modulating alternative pre-mRNA splice forms in muscle cells. Third, CARM1 is a regulator of autophagy through its positive reinforcement of AMPK activity and gene expression. Autophagy already has known implications in ageing and disease, and CARM1 could follow suite. Thus, CARM1 is a central regulator of several important processes impacting muscle stem cell function and myogenesis.

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 score0.337
Threshold uncertainty score0.296

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 head0.005
GPT teacher head0.196
Teacher spread0.190 · 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

Citations16
Published2022
Admission routes2
Has abstractyes

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