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Record W3214779735 · doi:10.1111/febs.16307

From quiescence to repair: C/EBPβ as a regulator of muscle stem cell function in health and disease

2021· article· en· W3214779735 on OpenAlexafffund
Hamood AlSudais, Nadine Wiper‐Bergeron

Bibliographic record

VenueFEBS Journal · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchCancer Research Society
KeywordsRegulatorBiologyStem cellCell biologySkeletal muscleMyocyteCellular differentiationCcaat-enhancer-binding proteinsCancer researchEndocrinologyNuclear proteinTranscription factorGeneticsGene

Abstract

fetched live from OpenAlex

CCAAT/Enhancer Binding protein beta (C/EBPβ) is a transcriptional regulator involved in numerous physiological processes. Herein, we describe a role for C/EBPβ as a regulator of skeletal muscle stem cell function. In particular, C/EBPβ is expressed in muscle stem cells in healthy muscle where it inhibits myogenic differentiation. Downregulation of C/EBPβ expression at the protein and transcriptional level allows for differentiation. Persistence of C/EBPβ promotes stem cell self-renewal and C/EBPβ expression is required for mitotic quiescence in this cell population. As a critical regulator of skeletal muscle homeostasis, C/EBPβ expression is stimulated in pathological conditions such as cancer cachexia, which perturbs muscle regeneration and promotes myofiber atrophy in the context of systemic inflammation. C/EBPβ is also an important regulator of cytokine expression and immune response genes, a mechanism by which it can influence muscle stem cell function. In this viewpoint, we describe a role for C/EBPβ in muscle stem cells and propose a functional intersection between C/EBPβ and NF-kB action in the regulation of cancer cachexia.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.261

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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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