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Record W1491133549 · doi:10.1002/stem.1606

MOZ-Mediated Repression of <i>p16INK4a</i> Is Critical for the Self-Renewal of Neural and Hematopoietic Stem Cells

2013· article· en· W1491133549 on OpenAlexaff
Flor M. Pérez-Campo, Guilherme Costa, Michael Lie‐A‐Ling, Stefano Stifani, Valérie Kouskoff, Georges Lacaud

Bibliographic record

VenueStem Cells · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMontreal Neurological Institute and Hospital
FundersCancer Research UKBiotechnology and Biological Sciences Research CouncilDirectorate for Biological SciencesUniversidad de CantabriaLeukemia and Lymphoma Research
KeywordsBiologyNeural stem cellStem cellProgenitor cellCell biologyHaematopoiesisGene silencingPsychological repressionCancer researchGene expressionGeneticsGene

Abstract

fetched live from OpenAlex

Although inhibition of p16(INK4a) expression is critical to preserve the proliferative capacity of stem cells, the molecular mechanisms responsible for silencing p16(INK4a) expression remain poorly characterized. Here, we show that the histone acetyltransferase (HAT) monocytic leukemia zinc finger protein (MOZ) controls the proliferation of both hematopoietic and neural stem cells by modulating the transcriptional repression of p16(INK4a) . In the absence of the HAT activity of MOZ, expression of p16(INK4a) is upregulated in progenitor and stem cells, inducing an early entrance into replicative senescence. Genetic deletion of p16(INK4a) reverses the proliferative defect in both Moz(HAT) (-) (/) (-) hematopoietic and neural progenitors. Our results suggest a critical requirement for MOZ HAT activity to silence p16(INK4a) expression and to protect stem cells from early entrance into replicative senescence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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

Citations78
Published2013
Admission routes1
Has abstractyes

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